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Lichen myxedematosus is a chronic cutaneous mucinosis that can present on a spectrum from localized cutaneous lesions to systemic disease of scleromyxedema. The clinical presentation of localized cutaneous lichen myxedematosus is waxy lichenoid papules, nodules, and/or plaques that have histopathologic findings of mucin deposition and a variable degree of fibroblast proliferation. There is an absence of serum paraproteins, and there are no other systemic causes of cutaneous mucinosis such as thyroid disease. The pathogenesis of lichen myxedematosus is unknown. We report 3 cases of localized cutaneous lichen myxedematosus with a light chain-restricted plasmacytic component by in situ hybridization. Our findings deliver an insight for disease pathogenesis and highlight for the first time, the significance of plasma cells in lesions of localized cutaneous lichen myxedematosus. We suggest that plasma cell light chain restriction could represent a clue to distinguish localized cutaneous disease from systemic disease.

Purpose In patients with chronic myelogenous leukemia (CML), point mutations in the BCR-ABL1 kinase domain are the most common cause of treatment failure with a tyrosine kinase inhibitor (TKI). It is not clear whether the splice variant BCR-ABL135INS is also associated with treatment failure. Patients and methods We reviewed all CML patients who had BCR-ABL1 kinase mutation analysis performed between August 1, 2007, and January 15, 2014. Patients who had BCR-ABL135INS detected had their medical records reviewed to determine response to TKI therapy. Results Two hundred and eighty four patients had kinase mutation testing performed; of these, 64 patients (23%) had BCR-ABL135INS detected. Forty-five patients were in chronic phase (70%), 10 were in accelerated phase (16%), 6 were in blastic phase (9%), and 3 were in other settings (5%). Of the 34 chronic phase patients who began therapy with imatinib, 23 patients (68%) failed therapy: 8 patients (24%) had primary refractory disease, 11 patients (32%) progressed, and 4 patients (12%) had disease progression after dose interruption. In contrast to the patients with disease progression or lack of response, none of 23 patients who were responding to imatinib had BCR-ABL135INS detected. DNA sequencing of commonly mutated spliceosomal genes SF3B1, U2AF1, SRSF2, ZRSR2, SFA31, PRPF408, U2A565, and SF1 did not reveal mutations in seven BCR-ABL135INS –positive patients tested. Conclusions The splice variant BCR-ABL135INS is frequently found in patients who are resistant to imatinib. Mutations in the commonly mutated spliceosomal proteins do not contribute to this association.

Demonstrating the presence of myelodysplastic syndrome (MDS)-specific molecular abnormalities can aid in diagnosis and patient management. We explored the potential of using peripheral blood (PB) cell-free DNA (cf-DNA) and next-generation sequencing (NGS).We performed NGS on a panel of 14 target genes using total nucleic acid extracted from the plasma of 16 patients, all of whom had confirmed diagnoses for early MDS with blasts5%. PB cellular DNA from the same patients was sequenced using conventional Sanger sequencing and NGS.Deep sequencing of the cf-DNA identified one or more mutated gene(s), confirming the diagnosis of MDS in all cases. Five samples (31%) showed abnormalities in cf-DNA by NGS that were not detected by Sanger sequencing on cellular PB DNA. NGS of PB cell DNA showed the same findings as those of cf-DNA in four of five patients, but failed to show a mutation in the RUNX1 gene that was detected in one patient's cf-DNA. Mutant allele frequency was significantly higher in cf-DNA compared with cellular DNA (p = 0.008).These data suggest that cf-DNA when analyzed using NGS is a reliable approach for detecting molecular abnormalities in MDS and should be used to determine if bone marrow aspiration and biopsy are necessary.

SummaryIntroduction Detection of mutations in the myeloid differentiation primary response gene 88 (MYD88) has clinical implications on diagnosis and therapy, especially in patients with Waldenstrom's macroglobulinemia (WM) and IgM monoclonal gammopathy of unknown significance (IgM-MGUS). We describe a method that provides greatly increased sensitivity for detecting minority mutations in MYD88. Methods We used a locked nucleic acid oligonucleotide to block amplification of wild-type DNA during polymerase chain reaction (PCR). Sanger sequencing of amplified DNA was used for detecting mutations in MYD88 gene. This approach was used to test samples from patients with WM and IgM-MGUS. Results When compared to traditional PCR followed by Sanger sequencing, our methodology was significantly more sensitive (one mutant allele in a background of 200 wild-type alleles). Using sequencing allowed us to visualize the PCR product, giving advantages over other methodologies such as allele-specific PCR. Based on analyzing 36 randomly selected, MYD88 mutated, clinically tested samples, we demonstrate that traditional PCR failed to detect MYD88 mutations in 64% of the samples that were clearly positive by wild-type blocking PCR. Conclusion The new methodology is essential for attaining accurate results in clinical testing.

Prevalence of somatic mutations in patients with aplastic anemia using peripheral blood cfDNA as compared with BM

Introduction:Primary central nervous system lymphoma (PCNSL) is a diffuse large B-cell lymphoma (DLBCL) with a tropism for the CNS microenvironment. Limited studies suggested differential expression of multiple extracellular matrix (ECM) and adhesions-related genes in PCNSL as compared to nodal DLBCL. We used next generation sequencing to evaluate expression profiles of 1408 genes and and performed differential expression profiling to compare PCNSL with nodal DLBCL, CD5+ DLBCL and EBV+ DLBCL. CD5+ DLBCL was selected because it is frequently ABC subtype. We also selected EBV+ DLBCL due to its poor outcome, similar to PCNSL. Methods:RNA was extracted from 30 formalin-fixed paraffin-embedded (FFPE) tissue samples from PCNSL patients and 23 FFPE tissue samples from cases with lymph node DLBCL-NOS, 8 samples CD5+DLBCL, 14 samples EBV+ DLBCL.. We sequenced the RNA using a 1408 gene panel (Illumina). Next Generation Sequencing was based on hybrid capture methodology. Total number of reads per sample must exceed 5 million to be accepted. RNA levels were quantified using FPKM. Levels of expression of each of the 1408 genes were compared between groups. The T-score is used to show differences. Considering the number of analyzed samples and to correct for multiple testing, only T-score less or greater than 3 was considered clinically significant. Results:PCNSL showed significant overexpression in 25 genes as compared with CD5+ DLBCL, while only 5 genes were highly expressed in PCNSL as compared with nodal DLBCL and 8 when compared with EBV+ DLBCL (Table below). Four genes were significantly less expressed in PCNSL as compared with CD5+ DLBCL, and only one gene when compared to nodal and EBV+ DLBCL. There was no significant difference in RNA expression of MYD88, CD79B, CARD11, KMT2D or SPP1 between PCNSL and DLBC-NOS, CD5+ DLBCL and EBV+ DLBCL . There was no significant difference between PCNSL and the other sub types in MYC, Ki67, BCL2, CD44, or CD274 (PD-L1) expression. Several genes emerged as highly expressed in PCNSL as compared with other subtypes of DLBCL (negative T-score). However, CLTC (Clathrin Heavy Chain) gene is uniquely highly overexpressed in PCNSL and not in any of the other 3 types of lymphoma. The CLTC gene is involved in anaplastic lymphoma as a partner gene for ALK (CLTC-ALK) in t(2,17) translocation. The SEPT2 (SEPTIN2) gene is uniquely highly expressed in PCNSL as compared with nodal and EBV DLBC lymphoma. SEPT2 gene plays significant role in Hodgkin lymphoma and in maintaining Reed-Stenberg cells . In contrast, VEGFC was significantly lower in PCNSL compared with nodal DLBCL. Conclusions:RNA molecular profiling suggests significant difference between PCNSL and CD5+ DLBCL and less difference when compared with nodal and EBV+ DLBCL. The strikingly high expression of CLTC gene in PCNSL suggests possible targeting of this gene might present a specific therapeutic approach for PCNSL. Figure Disclosures Abdulhaq: Novartis:Consultancy, Honoraria, Speakers Bureau;Astellas:Honoraria, Speakers Bureau;Amgen:Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau;Morphosys:Membership on an entity's Board of Directors or advisory committees, Research Funding;Oncopeptide:Research Funding.

e16061 Background: Fibroblast Growth Factor Receptors (FGFR1-4) abnormalities (fusion, amplification and mutations) are common in urothelial, breast and endometrial cancers. However, FGFR1-4 have been shown to play a major role in cell proliferation, differentiation, and apoptosis in other types of cancers including colorectal (CRC) and lung cancers. We explored the value of using DNA and RNA next generation sequencing (NGS) in determining the presence of abnormalities in FGFR1-4 in various types of cancer. Methods: Using targeted panel and next generation sequencing (NGS), we analyzed DNA sequencing data (434 genes) in 438 Solid tumors and RNA data (1408 genes) in 160 lung cancers and 53 colorectal cancers (CRC). The expression levels of the CRC and lung cancer were also compared with expression levels of 32 cases of endometrial, urothelial and breast cancers as a group of cancers known to have high incidence. Results: The DNA data showed mutations in 85 samples and CNV in 12 samples. The detected mutations were 18% in FGFR1, 25% in FGFR2, 45% in FGFR3, and 12% in FGFR4. Only 20% of the detected mutations by NGS testing can be detected if the PCR-based FDA-approved kit was used. Analysis of the expression levels of FGFR1-4 mRNA in CRC and lung cancer showed highest expression in FGFR2, followed by FGFR1 then FGFR3. Expression of FGFR4 was the lowest (P < 0.0001). There was no difference between CRC and lung cancer in FGFR1 and FGFR2 mRNA, but FGFR3 was slightly higher in lung cancer as compared with CRC (P = 0.01). FGFR4 was significantly higher in CRC as compared with lung cancer (P < 0.0001). No fusion involving FGFR1-4 was detected in any of the tested CRC or lung cancers. Upon comparing overall expression between CRC/lung cancer with the group of cancers that are known to have high incidence of FGFR1-4 abnormalities (urothelial, breast, and endometrial), FGFR1 and FGFR2 mRNA were significantly lower in CRC/lung cancers (P < 0.0001 and P = 0.0002, respectively), but there was no significant difference in FGFR3. However, significant overlap is noted. In contrast, FGFR4 was significantly higher in CRC (P < 0.0001). Conclusions: This data suggests that while FGFR1-3 genes are overall expressed in CRC and lung, some cases may have significantly high expression of FGFR1-3 and perhaps these cases should be singled out for treatment with FGFR inhibitors. Furthermore, NGS testing for mutations significantly more efficient and can detect significant number of mutations that can be missed if PCR-based testing is used. NGS testing of DNA and RNA is the most appropriate testing for abnormalities in FGFR1-4.

e21535 Background: N TRK (NTRK1, NTRK2 or NTRK3) fusions are oncogenic drivers of various types of cancer and lead to activation of the PI3K/AKT pathway. Treatment of patients with NTRK fusion using TRK inhibitors, such as larotrectinib or entrectinib, is associated with high response rates ( > 75%). However these fusions are very rare in most common cancers, such as lung and colorectal cancers. We examined the expression levels of NTRK1, NTRK2, and NTRk3 in non-small cell lung cancer using targeted RNA sequencing. We also examined the effects of NTRK overexpression on PI3K/AKT pathway in non-small cell lung cancer. Methods: RNA was extracted from 160 FFPE samples of non-small cell lung cancers and sequenced using targeted next generation sequencing (NGS). The RNA sequencing was based on hybrid capture using a targeted panel of 1408 genes. The number of reads ranged from 5 to 10 million. The RNA levels were measured using Cufflinks as FPKM. Results: NTRK2 fusion was detected in one sample (0.04%). However, overexpression of NTRK1-3 mRNA was more common and showed bimodal expression pattern. Most of the samples (75%) had low levels (median 0.6, 6,79, and 3.17 FPKM for NTR2, NTRK2, and NTRK3, respectively) while the upper 25% of samples had significantly (P < 0.0001) higher levels (Median 2.7, 280, and 17.7 KPFM for NTRK1, NTRK2, and NTRK3, respectively). There was significant difference in expression between the three genes (P < 0.0001). The highest levels were detected in NTRK2 and lowest in NTRK1. In addition, significant variation in alternative splicing was noted in NTRK2. All cases with high expression levels (above the upper quartile) showed significant variation in alternative splicing involving almost all exons. To explore, if high expression correlates with activation of the PI3K/AKT1 pathway, we examined the correlation between high levels (above upper quartile) of NTRK2 with various genes in PI3K/AKT pathway. High levels of NTRK2 mRNA (above the upper quartile) correlated with significantly higher levels of PIK3CA (P < 0.0001) and MDM2 (P = 0.0001). There was no correlation between high expression of NTRK1 or NTRK3 and PIK3CA or MDM2 mRNA. Conclusions: Although fusions involving NTRK1-3 genes in lung cancer are rare, significantly high expression levels can be seen almost 25% of lung cancers. Furthermore, high expression in NTRK2 correlates with activation in the PI3K/AKT pathway. This data suggests that therapy targeting NTRK2 overexpression and/or activation of PI3K/AKT pathway in patients with high NTRK2 mRNA should be explored.

e21534 Background: Expression level of PD-L1 mRNA as determined by next generation sequencing (NGS) is becoming more routinely available in cancer profiling. We explored the relevance of PD-L1 mRNA expression as detected by RNA sequencing in providing information relevant to clinical practice and compared lung cancer with colorectal cancer in activating interferon pathway. Methods: RNA was extracted from 160 non-small cell lung cancers and 53 colorectal cancers (CRC) as well as from 103 samples of various types cancers that were also analyzed for PD-L1 expression by IHC. The RNA sequencing was performed using a targeted panel of 1408 genes. IHC for PD-L1 staining was performed with the FDA-cleared diagnostic assay using the 22C3 antibody. Results: Based on comparing the number of PD-L1 IHC positive tumor cells and CD274 mRNA, significant correlation between the two methodology can be demonstrated as continuous variables (P < 0.0001) as well as when the IHC positivity is grouped as 0 to 1, 2 to 9, 10 to 49, and > = 50 (P < 0.0001). However, cancers with PD-L1 by IHC > 50% had distinctly higher levels of CD274 mRNA, while all other levels of IHC positivity showed significant overlap. Overall lung cancer showed significantly higher levels in STAT1 (P = 0.002), STAT3 (P < 0.0001), STAT4 (P = 0.005), PTPN2 (0.002) as compared with CRC. However, when only CRC cases that show PD-L1 overexpression were considered, there was no significant difference in the expression in any of these genes as compared lung cancer cases that also show PD-L1 overexpression. The only difference is that lung cancer cases with PD-L1 overexpression showed higher levels of IKBKE mRNA as compared with CRC cases with PD-L1 overexpression (P = 0.004). In addition, lung cancer overall showed higher levels of PD-L2 (P = 0.0002), PD-1 (P = 0.0002), CD8A (P < 0.0001), and CD19 (P = 0.0008), but CRC with PD-L1 overexpression showed no difference in the expression of any of these genes when compared to lung cancer cases with PD-L1 overexpression. Conclusions: While CRC shows overall significantly lower RNA levels of PD-L1, PD-L2, PD-1, CD19, CD8A and genes involved in interferon pathway, CRC cases with high expression of PD-L1 mRNA are similar to lung cancer high expressors of PD-L1. Furthermore, PD-L1 quantification using NGS testing can be used to select patient for immunotherapy and might provide valuable information on co-markers that may provide better insight to selecting patients for immunotherapy.

Background The role of MET amplification in lung cancer, particularly in relation to checkpoint inhibition and EGFR WT, has not been fully explored. In this study, we correlated PD-L1 expression with MET amplification and EGFR, KRAS, or TP53 mutation in primary lung cancer. Methods In this retrospective study, tissue collected from 471 various tumors, including 397 lung cancers, was tested for MET amplification by FISH with a MET/centromere probe. PD-L1 expression was evaluated using clone SP142 and standard immunohistochemistry, and TP53, KRAS, and EGFR mutations were tested using next generation sequencing. Results Our results revealed that PD-L1 expression in non-small cell lung cancer is inversely correlated with EGFR mutation (P=0.0003), and positively correlated with TP53 mutation (P=0.0001) and MET amplification (P=0.004). Patients with TP53 mutations had significantly higher MET amplification (P=0.007), and were more likely (P=0.0002) to be EGFR wild type. There was no correlation between KRAS mutation and overall PD-L1 expression, but significant positive correlation between PD-L1 expression and KRAS with TP53 co-mutation (P=0.0002). A cut-off for the ratio of MET: centromere signal was determined as 1.5%, and 4% of lung cancer patients were identified as MET amplified. Conclusions This data suggests that in lung cancer both MET and TP53 play direct roles in regulating PD-L1 opposing EGFR. Moreover, KRAS and TP53 co-mutation may cooperate to drive PD-L1 expression in lung cancer. Adding MET or TP53 inhibitors to checkpoint inhibitors may be an attractive combination therapy in patients with lung cancer and MET amplification.

Introduction We compared mutations detected in EGFR, KRAS, and BRAF genes using next-generation sequencing (NGS) and confirmed by Sanger sequencing with mutations that could be detected by FDA-cleared testing kits. Methods Paraffin-embedded tissue from 822 patients was tested for mutations in EGFR, KRAS, and BRAF by NGS. Sanger sequencing of hot spots was used with locked nucleic acid to increase sensitivity for specific hot-spot mutations. This included 442 (54%) lung cancers, 168 (20%) colorectal cancers, 29 (4%) brain tumors, 33 (4%) melanomas, 14 (2%) thyroid cancers, and 16% others (pancreas, head and neck, and cancer of unknown origin). Results were compared with the approved list of detectable mutations in FDA kits for EGFR, KRAS, and BRAF. Results Of the 101 patients with EGFR abnormalities as detected by NGS, only 58 (57%) were detectable by cobas v2 and only 35 (35%) by therascreen. Therefore, 42 and 65%, respectively, more mutations were detected by NGS, including two patients with EGFR amplification. Of the 117 patients with BRAF mutation detected by NGS, 62 (53%) mutations were within codon 600, detectable by commercial kits, but 55 (47%) of the mutations were outside codon V600, detected by NGS only. Of the 321 patients with mutations in KRAS detected by NGS, 284 (88.5%) had mutations detectable by therascreen and 300 (93.5%) had mutations detectable by cobas. Therefore, 11.5 and 6.5% additional KRAS mutations were detected by NGS, respectively. Conclusion NGS provides significantly more comprehensive testing for mutations as compared with FDA-cleared kits currently available commercially.

Accurate detection and identification of low frequency mutations can be problematic when assessing residual disease after therapy, screening for emerging resistance mutations during therapy, or when patients have few circulating tumor cells. Wild-type blocking PCR followed by sequencing analysis offers high sensitivity, flexibility, and simplicity as a methodology for detecting these low frequency mutations. By adding a custom designed locked nucleic acid oligonucleotide to a new or previously established conventional PCR based sequencing assay, sensitivities of approximately 1 mutant allele in a background of 1,000 WT alleles can be achieved (1:1,000). Sequencing artifacts associated with deamination events commonly found in formalin fixed paraffin embedded tissues can be partially remedied by the use of uracil DNA glycosylase during extraction steps. The optimized protocol here is specific for detecting MYD88 mutation, but can serve as a template to design any WTB-PCR assay. Advantages of the WTB-PCR assay over other commonly utilized assays for the detection of low frequency mutations including allele specific PCR and real-time quantitative PCR include fewer occurrences of false positives, greater flexibility and ease of implementation, and the ability to detect both known and unknown mutations.

To avoid relying solely on serum prostate-specific antigen (sPSA) in screening for prostate cancer (PCa), we developed a scoring system for detecting PCa and the prediction of aggressiveness. We analyzed urine and plasma specimens from 121 patients with PCa or benign prostatic hyperplasia (BPH) for the levels of UAP1, PDLIM5, IMPDH2, HSPD1, PCA3, PSA, TMPRSS2, ERG, GAPDH, and B2M genes. Patient age, sPSA level, and polymerase chain reaction data were entered through multiple algorithms to determine models most useful for the detection of cancer and predicting aggressiveness.In the first algorithm, we distinguished PCa from BPH (area under the receiver operating characteristic curve [AUROC] of 0.78). Another algorithm distinguished patients with the Gleason score (GS) of ≥7 from GS of7 cancer or BPH (AUROC of 0.88). By incorporating the two algorithms into a scoring system, 75% of the analyzed samples showed concordance between the two models (99% specificity and 68% sensitivity for predicting GS ≥7 in this group).A scoring system incorporating two algorithms using urine and plasma biomarkers highly predicts the presence of GS ≥7 PCa in 75% of patients. Our algorithms may assist with both biopsy indication and patient prognosis.

Introduction: Targeted RNA sequencing using Next Generation Sequencing (NGS) has significant advantages over transcriptome sequencing. In addition to information on mutations, fusion and alternative splicing, RNA quantification using targeted RNA sequencing is sensitive, reproducible and provides better dynamic range. We used targeted RNA sequencing for RNA profiling of diffuse large B-cell lymphoma (DLBCL) and explored its utility in the sub-classification of DLBC to ABC and GCB. Method: RNA extracted from 441 FFPE lymphnode samples with DLBC lymphoma and sequenced targeting 1408 genes. These cases were previously subclassified as ABC vs GCB using expression profiling and immunohistochemistry. We first normalized RNA expression data to PAX5 expression, then we tried to narrow down important markers using univariate significance tests. Setting the cutoff for false discovery rate at 0.0001, 48 variables remained significant, including 46 RNA levels and two genes (MYD88 and EZH2) mutation status. Using 60% of samples as training set, we used multiple statistical approaches for classification. Deep learning emerged as the best approach. We used autoencoder with 5 hidden layers and developed a model for classification of ABC vs GCB. To further improve on classification, we divided patients in each subgroup based on survival using simple tree model. In this tree model, expression level of CD58 emerged as a powerful prognostic marker for the ABC group and RLTPR expression in the GCB group. Results: Using probability of scoring developed based on deep learning and logestic regression, approximately 30% of the cases had a score between 0.5 and 0.75. For the remaining 70% of patients, the ABC vs GCB classification showed sensitivity and specificity of 96% and 97% for the testing set. We also applied the same approach to 60 independent cases classified using NanoString (Lymph2Cx). Our model showed sensitivity and specificity of 96% and 97% in the NanoString independent cases. Using the tree model for further classification of the ABC and GCB classes, CD58 mRNA levels separated the ABC group into two subgroups (ABC1 and ABC2) and RLTPR mRNA separated the GCB into two subgroups (GCB1 and GCB2) with significant difference in overall survival (P=0.0010) and progression-free survival (PFS) (P=0.0027). Conclusion: Targeted RNA sequencing is very reliable and practical for the subclassification of DLBCL and can provide clinical-grade reproducible test for prognostically subclassification of DLBCL. Figure Disclosures Albitar: Genomic Testing Ccoperative: Employment, Equity Ownership. De Dios:Genomic Testing Ccoperative: Employment. Tam:Takeda: Consultancy; Paragon Genomics: Consultancy. Hsi:Abbvie: Research Funding; Eli Lilly: Research Funding; Cleveland Clinic&Abbvie Biotherapeutics Inc: Patents & Royalties: US8,603,477 B2; Jazz: Consultancy. Ferreri:Roche: Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy; Kite: Consultancy. Piris:Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Lecture Fees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansen: Membership on an entity's Board of Directors or advisory committees, Other: Lecture Fees; Nanostring: Membership on an entity's Board of Directors or advisory committees; Kyowa Kirin: Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding. Kantarjian:Ariad: Research Funding; Agios: Honoraria, Research Funding; Daiichi-Sankyo: Research Funding; Novartis: Research Funding; BMS: Research Funding; Takeda: Honoraria; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Research Funding; Jazz Pharma: Research Funding; Cyclacel: Research Funding; Immunogen: Research Funding; Amgen: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Astex: Research Funding.

Introduction: The principle of precision cancer medicine is to customize therapy based on the genomic profiles of the cancer and the host constitution/response to the cancer. Since RNA expression is influence by many genetic mechanisms, RNA profiling may provide broader coverage of genomic changes and might be a better predictor of response to therapy. However, incorporating the many biological changes of the host and the cancer in the decision of selecting therapeutic approach is not practical without using computer-aided algorithms. This is particularly relevant when combination therapy is used. We explored the potential of developing algorithms for the prediction of complete response (CR) to novel combination therapy in patients with acute myeloid leukemia (AML) using targeted RNA expression profiling. Methods: RNA was extracted from the peripheral blood (PB) and bone marrow (BM) samples from patients with AML being treated on two different protocols: FLAG-IDA+venetoclax (F-I-V)( Abou Dalle I et al, ASH 2019; the NCT # is NCT03214562) and ivosidenib+venetoclax (I-V). In the initial study, 22 samples (9 PB and 13 BM) were used as training set. Subsequently 16 PB samples from the F-I-V arm and 4 from the I-V arm were collected and tested blindly as testing set after the development and locking of the algorithm. RNA was sequenced using NGS panel composed on compared of 1408 genes. The RNA sequencing is based on hybrid capture and the number of reads ranged from 5 to 10 million. RNA quantification was performed using Cufflinks. The RNA levels were normalized to ABL1 mRNA levels. Each gene is normalized by the mean and standard deviation of the gene. To develop a model for predicting CR, we used the training set in each arm and first evaluated the performance of each of the 1408 genes using receiver operating characteristic (ROC) curve. Then used the following mathematical methods for developing algorithms for predicting CR: Support Vector machine (SVM), Bayesian modeling with Gaussian Processes (GP), and Naïve Bayesian (NB). Results: In univariate analysis, multiple genes showed very high AUC. In the F-I-V arm, top genes in predicting CR were GLI3, SETBP1, SH3D19, ARHGAP20, ETS1, IKZF2, GNG4 and MAGEE1 with AUC ranged from 0.74 to 0.85. In the I-V arm, the top genes in predicting CR were STL, TNFRSF10D, PTGS2, RET, TFRC, NAV3, WSB1, and GAS1 with AUC varied from 0.91 to 0.96. Using the training samples we developed algorithms for predicting CR by SVM, NB and Bayesian GP. Upon testing these models using leave-one-out (LOO), the three algorithms performed similarly with AUC around 0.97 for the I-V arm and around 0.96 for the F-I-V arm. There was no difference between BM and PB in predicting CR. Therefore, we collected and sequenced only peripheral blood for blind testing. The three algorithms were tested using 16 PB samples from the F-I-V arm and 4 samples from the I-V arm. The SVM and NB algorithms predicted CR correctly in 15 of the 16 samples (94%) while Bayesian GP missed 4 of the 16 samples. As for the I-V arm, the NB predicted CR correctly in the 4 samples, while both SVM and Bayesian GP missed 3 of 4. Conclusions: While the data is limited and further validation is need, algorithms using RNA expression profiling of peripheral blood using targeted RNA NGS may provide an excellent tool for customizing therapeutic approach, especially in the age of combination therapy when number of cases for training can be limited. Furthermore, this study suggests that modeling using Nave Bayesian is reliable approach in developing prediction algorithms. Disclosures Albitar: Genomic Testing Ccoperative: Employment, Equity Ownership. Konopleva:Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Ascentage: Research Funding; Kisoji: Consultancy, Honoraria; Ablynx: Research Funding; Agios: Research Funding; Amgen: Consultancy, Honoraria; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Astra Zeneca: Research Funding; Calithera: Research Funding; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Forty-Seven: Consultancy, Honoraria; Eli Lilly: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Cellectis: Research Funding. Loghavi:MDACC: Employment; AlphaSights: Consultancy; GLG Consultants: Consultancy. Takahashi:Symbio Pharmaceuticals: Consultancy. Kantarjian:Daiichi-Sankyo: Research Funding; Ariad: Research Funding; Cyclacel: Research Funding; AbbVie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; BMS: Research Funding; Jazz Pharma: Research Funding; Novartis: Research Funding; Takeda: Honoraria; Pfizer: Honoraria, Research Funding; Immunogen: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astex: Research Funding. DiNardo:syros: Honoraria; daiichi sankyo: Honoraria; celgene: Consultancy, Honoraria; jazz: Honoraria; abbvie: Consultancy, Honoraria; agios: Consultancy, Honoraria; medimmune: Honoraria; notable labs: Membership on an entity's Board of Directors or advisory committees.

Introduction: Isocitrate dehydrogenase 1 and 2 (IDH1/2) are homodimeric enzymes that play an important role in cellular metabolism, epigenetic regulation, and DNA repair. Early studies suggested that mutations in IDH1/2 were loss of function mutations associated with a tumor suppressor function. However, biallelic mutations are extremely rare, and studies demonstrate that mutant IDH1/2 enzymes are responsible for NADPH-dependent reduction of αKG to the oncometabolite d-2-hydroxyglutarate (D2HG), suggesting an oncoprotein. Cellular RNA levels are tightly regulated by very complex cellular processes, and the regulation of mutant mRNA in cancer cells is rarely studied. We explored the effects of IDH1/2 mutations on mRNA levels in patients with Acute myeloid leukemia (AML). Using next generation sequencing (NGS) and variant allele frequency (VAF) of mutant RNA, we compared relative mutant mRNA or variant allele frequency (RNA-VAF) with variant allele frequency of mutant DNA (DNA-VAF) in the same samples from patients with AML. Methods: RNA and DNA were extracted from 48 bone marrow and peripheral blood samples from patients with confirmed AML, including 12 patients with IDH1 mutations, 2 with IDH2 mutation and 34 samples from AML without IDH1/2 mutations. Samples were collected pretherapy as well as while on therapy. We sequenced the DNA using 177 gene panel and the RNA using 1408 gene panel. The DNA sequencing is based on Single Primer Extension (SPE) library preparation with unique molecular identifier (UMI) (Qiagen, Germantown, MD). Average coverage of DNA sequencing was >1000X. The RNA sequencing is based on hybrid capture and the number of reads ranged from 5 to 10 million. Sequencing data of DNA is analyzed using the DRAGEN Platform. Sequence duplicates were removed before calculating VAF. The RNA sequencing data is analyzed using Illumina basespace. RNA VAF is calculated also after removing duplicates using Isaac variant caller. Only mutations detected by both DNA and RNA variant callers are compared. Results: A total of 176 mutations were detected using the DNA panel and 122 mutations using the RNA panel. Some mutations were called by RNA variant caller, but not by DNA variant caller and vice versa. All mutations detected in IDH1 and IDH2 were detected in both DNA and RNA. When the IDH1/2 mutations are considered (#14), the VAF in RNA (median: 41%, range: 13%-74%) was significant higher (P=0.006, Wilcoxon matched pairs test ) as compared with DNA (median:28%, range: 13%-74%). The VAF of the other 31 mutations that were detected in both DNA and RNA varied dependent on the gene. ASXL1, DNMT3A, RUNX1, PTPN11, SRSF2, STAG2 and U2AF1 mutations showed no significant difference between DNA and RNA in VAF (P=0.71). Although the number is small, mutations in NRAS and NPM1 showed significantly higher VAF in RNA as compared with with that of DNA (P=0.008). Conclusion: This data suggests that, in general, stability of mutant RNA varies between genes and between the mutations in the same gene. Mutant IDH1/2 RNA is significantly more stable in myeloid leukemic cells a compared with the wild-type mRNA. Most likely this reflects increased levels of mutant IDH1/2 as compared with wild-type IDH1/2, confirming that IDH1/2 is oncoprotein and may explain the efficacy of therapeutic inhibition of IDH1/2 in treating cancers. Furthermore this suggests that mRNA testing might be more sensitive in monitoring minimal residual disease in patients with IDH1/2 mutations. Figure Disclosures Albitar: Genomic Testing Ccoperative: Employment, Equity Ownership. Konopleva:Forty-Seven: Consultancy, Honoraria; Stemline Therapeutics: Consultancy, Honoraria, Research Funding; Calithera: Research Funding; Eli Lilly: Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Cellectis: Research Funding; Amgen: Consultancy, Honoraria; F. Hoffman La-Roche: Consultancy, Honoraria, Research Funding; Genentech: Honoraria, Research Funding; Ascentage: Research Funding; Kisoji: Consultancy, Honoraria; Reata Pharmaceuticals: Equity Ownership, Patents & Royalties; Ablynx: Research Funding; Astra Zeneca: Research Funding; Agios: Research Funding. Loghavi:GLG Consultants: Consultancy; AlphaSights: Consultancy; MDACC: Employment. Takahashi:Symbio Pharmaceuticals: Consultancy. Kantarjian:Jazz Pharma: Research Funding; Pfizer: Honoraria, Research Funding; Ariad: Research Funding; Cyclacel: Research Funding; Novartis: Research Funding; Astex: Research Funding; Takeda: Honoraria; Agios: Honoraria, Research Funding; BMS: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Daiichi-Sankyo: Research Funding; Immunogen: Research Funding. DiNardo:medimmune: Honoraria; agios: Consultancy, Honoraria; notable labs: Membership on an entity's Board of Directors or advisory committees; jazz: Honoraria; abbvie: Consultancy, Honoraria; celgene: Consultancy, Honoraria; daiichi sankyo: Honoraria; syros: Honoraria.

Introduction: RNA expression profiling using Next Generation Sequencing (NGS) provides important and reproducible information on expression levels of various genes. We studied the expression levels of MYC and BCL2 in patients with diffuse large B-Cell lymphoma (DLBCL) using NGS targeted RNA sequencing. We correlated levels of expression of these genes with outcome. Methods: RNA extracted from 441 FFPE samples with DLBC lymphoma and sequenced targeting 1408 genes. The RNA sequencing is based on hybrid capture and the number of reads ranged from 5 to 10 million. RNA quantification was performed using Cufflinks. The RNA levels were normalized to PAX5 mRNA levels. Of these cases, 380 were subclassified as ABC or GCB using expression profiling. The rest were classified as "undetermined", therefore were not included in further analysis. All patients were treated with R-CHOP. Results: The expression of MYC and BCL2 mRNA was slightly higher in ABC as compared with GCB (P=0.01 and P=0.02, respectively). However, in the GCB subtype, patients with MYC expression above the median showed significantly shorter survival as compared with those below the median (P=0.0007, Log-rank test). In contrast, there was no significant difference in survival using median of MYC expression as cutoff in patients classified as ABC subtype (P=0.38). Using upper 15% cut-off point for BCL2 mRNA expression, GCB patients with high BCL2 expression had significantly shorter survival (P=0.005). In contrast, there was no significant difference in survival between high and low BCL2 expression groups in the ABC subtype (P=0.1). When both MYC and BCL2 are considered, patients with high expression of both BCL2 and MYC (double-RNA expression) had significantly shorter survival as compared with patients with low expression of both MYC and BCL2 (P=0.0009) when both GCB and ABC groups are considered. Patients with high BCL2 expression also had poor survival similar to those double-RNA expression. Considering only patients with GCB, high expressor of both MYC and BCL2 had significantly worse outcome (P=0.0015) as compared with low expressors of both MYC and BCL2, but patients with high BCL2 also had significantly poor outcome as compared to low expressor of both MYC and BCL2 (P=0.0005). In contrast, there was no difference in survival for high or low MYC and BCL2 expressor in the ABC group. Conclusion: The data support the concept that in DLBCL, MYC and BCL2 mRNA expression levels are clinically relevant in GCB, but not ABC subtype. Furthermore, targeted RNA sequencing might provide a reliable and practical objective approach for the subclassification of DLBCL and determining double-RNA expression lymphoma. Figure Disclosures Albitar: Genomic Testing Cooperative: Employment, Equity Ownership. Tam:Takeda: Consultancy; Paragon Genomics: Consultancy. Hsi:Abbvie: Research Funding; Eli Lilly: Research Funding; Cleveland Clinic&Abbvie Biotherapeutics Inc: Patents & Royalties: US8,603,477 B2; Jazz: Consultancy. Piris:Calgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansen: Membership on an entity's Board of Directors or advisory committees, Other: Lecture Fees; Nanostring: Membership on an entity's Board of Directors or advisory committees; Kyowa Kirin: Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding; Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Lecture Fees, Research Funding. Kantarjian:Immunogen: Research Funding; BMS: Research Funding; Cyclacel: Research Funding; Pfizer: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Ariad: Research Funding; Amgen: Honoraria, Research Funding; Takeda: Honoraria; AbbVie: Honoraria, Research Funding; Astex: Research Funding; Jazz Pharma: Research Funding; Novartis: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Research Funding.

Cellular RNA levels are tightly regulated by very complex nuclear and cytoplasmic processes. The regulation of mutant mRNA in cancer cells is rarely studied. We explored the effects of mutations on mRNA levels in patients with diffuse large B-cell lymphoma (DLBCL). Using next generation sequencing (NGS) and variant allele frequency (VAF) of mutant RNA, we compared relative mutant mRNA or variant allele frequency (RNA-VAF) with variant allele frequency of mutant DNA (DNA-VAF) in the same samples from patients with DLBCL. Methods: RNA and DNA were extracted from 427 FFPE samples from patients with DLBCL. We sequenced the DNA using 177 gene panel and the RNA using 1408 gene panel. The DNA sequencing is based on Single Primer Extension (SPE) library preparation with unique molecular identifier (UMI) (Qiagen, Germantown, MD). The RNA sequencing is based on hybrid capture. Sequencing data of DNA is analyzed using the DRAGEN Platform. Sequence duplicates were removed before calculating VAF. The RNA sequencing data is analyzed using Illumina basespace. RNA VAF is calculated also after removing duplicates using Isaac variant caller. Only mutations detected by both DNA and RNA variant callers are compared. Results: A total of 1770 mutations were detected using the DNA panel and 2207 mutations were detected using the larger RNA sequencing panel. We focused on the most commonly mutated genes that included in both DNA and RNA panels and compared the VAF of the same mutations between DNA and RNA. The selected genes are: KMT2D, NOTCH2, CARD11, MYC, MYD88, EZH2, TP53, CD79B, BCL2, and TET2. The overall VAF in the RNA was significantly higher (P Figure Disclosures Albitar: Genomic Testing Ccoperative: Employment, Equity Ownership. Tam:Takeda: Consultancy; Paragon Genomics: Consultancy. Hsi:Abbvie: Research Funding; Jazz: Consultancy; Eli Lilly: Research Funding; Cleveland Clinic&Abbvie Biotherapeutics Inc: Patents & Royalties: US8,603,477 B2. Piris:Nanostring: Membership on an entity's Board of Directors or advisory committees; Kyowa Kirin: Membership on an entity's Board of Directors or advisory committees; Kura: Research Funding; Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees, Other: Lecture Fees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansen: Membership on an entity's Board of Directors or advisory committees, Other: Lecture Fees. Kantarjian:Agios: Honoraria, Research Funding; Daiichi-Sankyo: Research Funding; Pfizer: Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Immunogen: Research Funding; Novartis: Research Funding; Jazz Pharma: Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Research Funding; Astex: Research Funding; Takeda: Honoraria; BMS: Research Funding; Cyclacel: Research Funding; Ariad: Research Funding.

Background: Circulating cell-free DNA (ccfDNA) is highly fragmented DNA in plasma that is released by normal or tumor cells when they undergo apoptosis or necrosis. ccfDNA allows for non-invasive sampling of somatic genomic alterations and is informative in various solid tumors, including as a marker of measurable residual disease (MRD). We sought to assess the utility of baseline assessment and tracking of leukemia-associated mutations through peripheral blood sampling of ccfDNA in patients (pts) with acute leukemias. Methods: Plasma ccfDNA was isolated and analyzed using a next-generation sequencing (NGS) assay of 275 genes. This NGS analysis is based on Single Primer Extension library preparation with unique molecular identifier (Qiagen, Germantown, MD); a sequence coverage ≥ 100X (after removing duplicates) was required. Amplicon-based NGS was also performed on DNA extracted from the bone marrow (BM) in a CLIA-certified molecular diagnostics laboratory. This BM panel detects mutations in the coding sequence of 28 leukemia-associated genes, with an analytic sensitivity of 5-10%. The ccfDNA panel included all 28 genes evaluated on the BM NGS panel (ABL1, ASXL1, BRAF, DNMT3A, EGFR, EZH2, FLT3, GATA1, GATA2, HRAS, IDH1, IDH2, IKZF1, JAK2, KIT, KRAS, MDM2, MLL, MPL, MYD88, NOTCH1, NPM1, NRAS, PTPN11, RUNX1, TET2, TP53, WT1). Established bioinformatics pipelines were used to identify somatic variants. Results: Twenty-four pts (AML, n=22; ALL, n=2) underwent paired ccfDNA and BM sequencing at diagnosis prior to receiving frontline intensive chemotherapy. For baseline samples, ccfDNA was collected a median of 6 days after BM collection (range, 0-27 days) and a median of 0.5 days after start of induction chemotherapy (range, -7 to 7 days). Eleven pts (46%) also had ccfDNA collected at ≥1 time point during remission. Among the 28 genes of interest, the median number of mutations per pt detected in BM and in ccfDNA was 1 (range, 0-4) for both assays (P=0.39). A total of 40 mutations were detected: 18 mutations (45%) were detected by both methods, 7 (18%) were detected only in ccfDNA, and 15 (38%) were detected only in BM. Time from start of chemotherapy until ccfDNA collection did not appear to impact the concordance of ccfDNA and BM mutation analysis (P=0.87). Among mutations detected by ccfDNA in baseline samples, the median variant allelic frequency (VAF) was 33.7% (range, 2.7-90.8%). Among the 18 overlapping mutations, the concordance of VAF assessment by both methods was high (R2 = 0.849). Mutations detected by only one of the two methods were generally of lower VAF than those detected by both methods, suggesting that either method may miss small subclonal populations. The median VAF of mutations (as measured in ccfDNA) that were detected by both methods was higher than those detected only in ccfDNA (39.8% vs 25.2%, respectively; P=0.04); similarly, the median VAF of mutations (as measured in BM) that were detected by both methods was higher than those detected only in BM (40.2% vs 6.6%; P=0.001). Among the 7 mutations detected only by ccfDNA, ASXL1 was detected in 2 pts, WT1 in 1 pt, IDH1 in 1 pt, and BRAF and two EGFR mutations in 1 pt. Among the 5 pts in whom mutations were detected in ccfDNA but not BM, 2 eventually relapsed. In both pts, the discordant mutation (IDH1 and ASXL1) was detected in the relapse BM, suggesting that these were true mutations that were missed by NGS of the baseline BM. ccfDNA detected leukemia-associated mutations during remission that appeared to herald overt relapse (Figure 1). Two pts with t(8;21) AML developed new RUNX1 mutations detected by ccfDNA while in remission and subsequently relapsed 3 months and 14 months later. In both of these pts, the new RUNX1 mutation was confirmed in the BM at the time of morphological relapse. Another pt with AML had persistent TP53 and TET2 mutations detected by ccfDNA 1 month after allogeneic stem cell transplant and subsequently relapsed 1 month later. Conclusions: This study demonstrates that sequencing of ccfDNA can identify prognostic or targetable mutations not detected by BM NGS. However, true mutations were missed by both ccfDNA and BM analysis, suggesting that these methodologies may be complementary in the assessment and monitoring of pts with leukemia. The use of ccfDNA as a non-invasive method to detect mutations and track MRD in AML and other leukemias should be evaluated in larger, prospective cohorts. Disclosures Short: Takeda Oncology: Consultancy, Research Funding; AstraZeneca: Consultancy; Amgen: Honoraria. Jabbour:Amgen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Cyclacel LTD: Research Funding; AbbVie: Consultancy, Research Funding; Adaptive: Consultancy, Research Funding; Takeda: Consultancy, Research Funding. Garcia-Manero:Amphivena: Consultancy, Research Funding; Helsinn: Research Funding; Novartis: Research Funding; AbbVie: Research Funding; Celgene: Consultancy, Research Funding; Astex: Consultancy, Research Funding; Onconova: Research Funding; H3 Biomedicine: Research Funding; Merck: Research Funding. Kantarjian:BMS: Research Funding; Amgen: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Immunogen: Research Funding; Takeda: Honoraria; Novartis: Research Funding; Ariad: Research Funding; Astex: Research Funding; Pfizer: Honoraria, Research Funding; Actinium: Honoraria, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Research Funding; Jazz Pharma: Research Funding; Cyclacel: Research Funding; AbbVie: Honoraria, Research Funding. Ravandi:Macrogenix: Consultancy, Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Xencor: Consultancy, Research Funding; Menarini Ricerche: Research Funding; Cyclacel LTD: Research Funding; Selvita: Research Funding.

7535 Background: Primary central nervous system lymphoma (PCNSL) is a rare type of non-Hodgkin lymphoma, distinguished by poor prognosis. Previous studies have identified MYD88, CD79b and PIM1 as the most common genetic mutations in PCNSL. However, the extent to which mutations vary by ethnicity is unknown. The purpose of this study was to describe differences in genetic mutations and survival by Hispanic ethnicity in PCNSL. Methods: We retrospectively reviewed records of 30 patients with PCNSL diagnosed between January 2007- December 2017. We examined mutations in 275 genes by DNA analysis and 1382 genes by RNA analysis utilizing next generation sequencing. Results: Among the thirty patients, median age was 60 years, 60% were male, and 60% were Hispanic. Twenty-four patients had activated B-cell (ABC) and 5 patients had germinal center (GC) type per Hans criteria. Among 29 patients with complete mutation data, 125 different mutated genes were detected. Missense mutations were the most common (75%) followed by frame shift mutations (25%). The most commonly affected genes were: MYD88 (44%), CARD11 (21%), CD79b (17%), PIM1 (17%), KMT2D (17%) and ETV6 (14%). CD79b mutation was more common in GC type vs. ABC type (60% vs. 8%, P=.01). MYD88 mutation was less frequent in Hispanic patients (27% vs 66%, P=.02), while there were no statistically significant differences in CARD11 (22% vs 18%, P=.79), KMT2D (22% vs 9%, P=.36), CD79B (16% vs 19%, P=.92) and PIM1 (16% vs 19%, P=.92). There were more Hispanic patients with >3 mutated genes (89% vs 55 %. P=.03). Two-year progression-free survival (PFS) and overall survival (OS) were 46% and 50%, respectively. Both outcomes were superior among Hispanic vs. non-Hispanic patients (2-yr PFS 60% vs 27%, P=.09), (2-yr OS 60% vs 36%, P=.23), but this was not statistically significant. MYD88, CARD11, PIM1, and KMT2D were not associated with significant differences in 2-year OS or PFS. However, patients with CD79b mutations had superior 2-yr PFS (P=.04). Conclusions: We identified highly recurrent genetic alterations in PCNSL. Our data suggest that some heterogeneity in the most frequent mutations in PCNSL may be related to ethnicity. However, the superiority in 2-yr PFS and OS did not reach statistical significance in our Hispanic patients. Further studies on a larger patient population may further help to describe the differences in incidence, tumor biology, and outcomes in Hispanic patients.

7549 Background: The cell of origin of primary central nervous system lymphoma (PCNSL) remains controversial. Data using immunohistochemistry (IHC) and Hans algorithm suggested that both germinal-center B-cell–like (GCB) and activated B-cell-like (ABC) subtypes can be seen in PCNSL. We explored the potential of DNA and RNA molecular profiling in characterizing the biology of PCNSL and compared this profile with ABC subtype of diffuse large B-cell lymphoma (DLBCL). Methods: RNA and DNA were extracted from 30 formalin-fixed paraffin-embedded (FFPE) tissue samples from PCNSL patients and 30 FFPE tissue samples from cases with lymph node DLBCL of ABC subtype. Subtyping of DLBCL cases was performed using IHC and gene expression profiling. We sequenced the DNA using a 275 gene panel (Qiagen) and the RNA using a 1382 gene panel (Illumina). Next Generation Sequencing on Illumina platform was used for detecting mutations and expression profiling. The levels of RNA expression were normalized to that of PAX5. Mutations detected by RNA sequencing were compared to those detected by DNA sequencing. Results: There was no significant difference between DLBCL-ABC and PCNSL in mutation rate of MYD88, CD79B, CARD11 or KMT2D: 33.3%, 10%, 10%, and 13.3%, respectively, in DLBCL-ABC vs 30%, 10%, 10%, and 10%, respectively, in PCNSL. However, NOTCH2 mutations were significantly different and detected in 16.7% of DLBCL-ABC as compared with 3% in PCNSL (P=.001). An algorithm that uses expression profiling of 46 different genes and distinguishes DLBCL-ABC from GCB showed that all PCNSL cases classified as ABC. The GCB classical marker LMO2 was expressed at very low level in both DLBCL-ABC and PCNSL, but was at relatively higher level in PCNSL (P=.002, Kruskal-Wallis ANOVA). There was significantly higher expression of the adhesion molecule CXCR4 (P=.008), activation molecules BTK (P=.0003) and PLCG2 (P=.002), and BCL6 (P=.002) in PCNSL as compared with DLBCL-ABC. There was no significant difference between the two groups in MYC, Ki67, BCL2, CD44, or CD274 (PD-L1) expression. Conclusions: DNA and RNA molecular profiling of PCNSL suggests similarity to DLBCL-ABC subtype. However, PCNSL is unique by expressing higher levels of the adhesion molecule CXCR4 and the activation molecules BTK and PLCG2. The lack of increased expression of MYC and Ki67 suggests that PCNSL is unlikely to be similar to Burkitt lymphoma.

Disease progression in patients with chronic lymphocytic leukemia (CLL) treated with ibrutinib has been attributed to histologic transformation or acquired mutations in BTK and PLCG2. The rate of resistance and clonal composition of PD are incompletely characterized. We report on CLL patients treated with single-agent ibrutinib on an investigator-initiated phase 2 trial. With median follow-up of 34 months, 15 of 84 evaluable patients (17.9%) progressed. Relapsed/refractory disease at study entry, TP53 aberration, advanced Rai stage, and high β-2 microglobulin were independently associated with inferior progression-free survival (P < .05 for all tests). Histologic transformation occurred in 5 patients (6.0%) and was limited to the first 15 months on ibrutinib. In contrast, progression due to CLL in 10 patients (11.9%) occurred later, diagnosed at a median 38 months on study. At progression, mutations in BTK (Cys481) and/or PLCG2 (within the autoinhibitory domain) were found in 9 patients (10.7%), in 8 of 10 patients with progressive CLL, and in 1 patient with prolymphocytic transformation. Applying high-sensitivity testing (detection limit ∼1 in 1000 cells) to stored samples, we detected mutations up to 15 months before manifestation of clinical progression (range, 2.9-15.4 months). In 5 patients (6.0%), multiple subclones carrying different mutations arose independently, leading to subclonal heterogeneity of resistant disease. For a seamless transition to alternative targeted agents, patients progressing with CLL were continued on ibrutinib for up to 3 months, with 19.8 months median survival from the time of progression. This trial was registered at www.clinicaltrials.gov as #NCT01500733.

Background. We studied DNA chimerism in cell-free DNA (cfDNA) in patients treated with HSCT. Methods. Chimerism analysis was performed on CD3+ cells, polymorphonuclear (PMN) cells, and cfDNA using 16 small tandem repeat loci. The resulting labeled PCR-products were size-fractionated and quantified. Results. Analyzing samples from 191 patients treated with HSCT for nonneoplastic hematologic disorders demonstrated that the cfDNA chimerism is comparable to that seen in PMN cells. Analyzing leukemia patients (N = 126) showed that, of 84 patients with 100% donor DNA in PMN, 16 (19%) had evidence of clinical relapse and >10% recipient DNA in the plasma. Additional 16 patients of the 84 (19%) showed >10% recipient DNA in plasma, but without evidence of relapse. Eight patients had mixed chimerism in granulocytes, lymphocytes, and plasma, but three of these patients had >10% recipient DNA in plasma compared to PMN cells and these three patients had clinical evidence of relapse. The remaining 34 patients showed 100% donor DNA in both PMN and lymphocytes, but cfDNA showed various levels of chimerism. Of these patients 14 (41%) showed laboratory or clinical evidence of relapse and all had >10% recipient DNA in cfDNA. Conclusion. Monitoring patients after HSCT using cfDNA might be more reliable than cellular DNA in predicting early relapse.

NeoGenomics Laboratories, Inc. is a publicly traded high-complexity national clinical laboratory company that specializes in cancer diagnostic testing, focused on molecular and genomic approaches. NeoGenomics has been associated with innovation in providing world-class pathology and cancer genetic diagnostic services for pathologists, oncologists, urologists and gastroenterologists, as well as hospitals throughout the USA. The company mission also includes the integration of technical advances in molecular methodologies including computer-aided pattern-recognition mathematical algorithms in order to integrate data from multiple analytes and thereby develop precise (personalized) predictive tools for the diagnosis of disease, prognosis and response to therapy. The company has a unique business model in that it is committed to partnering with routine diagnostic laboratories, thereby providing them with the option of technical-component-only testing for esoteric biomarkers and allowing local control of the professional component, in the interpretation and the review of raw data. The company, through innovative research and development, is dedicated to the cost-effective delivery of leading-edge, high-quality patient care through the application of precise and personalized laboratory medicine.

Interferon-beta-1b (IFN-beta-1b) reduces relapses in multiple sclerosis (MS) and improves magnetic resonance imaging (MRI) outcomes. Mechanism of action of IFN-beta-1b is only marginally understood. The roles and plasma levels of factors within the ubiquitin-proteasome system (UPS) and the plasma proteasome enzymatic activity of MS patients have not been explored. We hypothesized that pharmacologic double inhibition of the UPS by IFN-beta-1b occurs in MS patients and contributes to improvement of clinical course and reduction in MRI activity.During a 6-month prospective study, we measured plasma proteasome and ubiquitin protein levels and the proteasome enzymatic activities in patients with MS pre- (n = 35) and post-treatment (n = 26) with IFN-beta-1b and 96 normal controls. The results were compared to clinical and brain MRI outcomes.Plasma levels of ubiquitin and proteasome enzymatic activities were elevated in MS patients before therapy with IFN-beta-1b as compared to normals (P0.01). Additionally, UPS enzymatic activities were increased in MS patients before treatment with IFN-beta-1b (P0.0001). Six months after treatment with IFN-beta-1b, plasma levels of proteasome and ubiquitin showed further elevation as compared to the pre-treatment values and normals. Treatment with IFN-beta-1b suppressed the enzymatic activity of plasma proteasome and such lowered level of enzymatic activity correlated with a decline in the number of post-contrast T1-weighted enhancing lesions.Since UPS is linked to protein degradation, it may contribute to the course of immune-mediated diseases such as MS, and pharmacologic inhibition of UPS through IFN-beta-1b therapy improves the clinical course of MS. Larger clinical trials are needed to confirm the results of this preliminary study.

Background With the adoption of digital pathology, image analysis (IA) of immunohistochemistry (IHC) slides can be integrated seamlessly into the digital pathology workflow. A pathologist can now use IA efficiently while reading the digital IHC slides on a computer monitor. Thus, the clinical acceptance of a digital pathology system for IHC quantitation depends both on the performance of the IHC IA, and the ability to manually read digital IHC slides on the monitor. A multisite study was conducted to compare the manual reading of IHC Human Epidermal Growth Factor Receptor 2 (HER2) slides on a monitor, using Aperio Technologies, Inc. ScanScope XT instrument and the Spectrum digital pathology information management system to conventional manual microscopy (MM). Design A total of 180 breast cancers were immunohistochemically stained using Dako HercepTest and assayed: (site 1) 80 retrospective specimens with equal HER2 score distribution from an academic center, and (site 2) 100 prospective specimens from a reference laboratory. At each site, 3 pathologists carried out a blinded read of the glass slides using a conventional light microscope, and reporting the HER2 score for each. The glass slides were scanned using a 20× objective, and after a wash-out period and randomization of the slides, the same 3 pathologists carried out another blinded read of the same slides, but this time of the digital image of the slides on the monitor, again reporting the HER2 score. Each of the methods: MM and reading digital slides on a computer monitor, from now on called manual digital read (MDR) were evaluated separately and comparatively using Percent Agreement (PA) of negative HER2 scores (0, 1+) versus equivocal (2+) versus positive HER2 scores (3+). Results Comparable PA values were obtained for MM and MDR IHC HER2 images on the monitor (MM: 76.3% to 91.3%; MDR: 70.0% to 86.0%; MM vs. MDR: 61.3% to 92.5%). Conclusions Results of manually reading IHC HER2 slides on a monitor using Aperio Technologies, Inc. digital pathology system show substantial equivalence to those obtained by conventional manual microscopy. The digital slides are easily read on a monitor.

This open-label, dose escalation, multicentre phase 1/2 trial was undertaken to determine the safety and tolerability of the heat shock protein 90 (HSP90) inhibitor tanespimycin (100-340 mg/m(2) )+ bortezomib (0·7-1·3 mg/m(2) ) given on days 1, 4, 8 and 11 in each 21-d cycle. Phase 2 expansion occurred at the highest tested dose of tanespimycin at 340 mg/m(2) and bortezomib at 1·3 mg/m(2) . Seventy-two patients (median age, 60 years) with relapsed or relapsed and refractory multiple myeloma (MM) were enrolled; 63 patients (89%) completed the study. Tanespimycin in combination with bortezomib was well tolerated; few patients experienced significant neutropenia, constipation and anorexia (

The ubiquitin-proteasome system (UPS) plays a major role in the homeostasis of cellular protein. We demonstrate that each of the major hematologic diseases (AML, ALL, and MDS) has a specific and different plasma profile of UPS protein and enzymatic activities. While high levels of proteasome and ubiquitin proteins and enzymatic activities are detected in the plasma samples from patients, normalizing enzymatic activities, show that each proteasome has lower enzymatic activities in these diseases as compared with normal controls. Proteasome protein levels in AML are strong predictor of survival independently of cytogenetics, performance status and age. The Ch-L activity when normalized to the level of proteasome protein show significant negative correlation with survival in ALL.

Background and Aim: A reliable test for the detection of hepatocellular carcinoma (HCC) could improve disease management. Recent reports suggested a link between abnormalities in the ubiquitin-proteasome system (UPS) and HCC. We investigated the potential of using UPS markers, along with HCC markers, to differentiate HCC from chronic liver disease (CLD). Methods: Sera from 135 HCC and 262 CLD patients were retrospectively analyzed for levels of UPS markers (proteasome, ubiquitin, and proteasome enzymatic activities) and the conventional HCC markers alpha fetoprotein (AFP), AFP-L3, and des-gamma-carboxyprothrombin (DCP). Multivariate logistic regression analysis was used to develop a model for differentiating HCC from CLD. The model was developed using a subset of 98 HCC patients and 104 CLD patients with advanced fibrosis or cirrhosis (Metavir F3-4) and then validated using an independent set (37 HCC and 44 CLD (F3-4)). Results: A UPS signature model incorporating six markers (trypsin-like, caspase-like, chymotrypsin-like, and normalized chymotrypsin-like activities of proteasomes; AFP; and DCP) accurately differentiated HCC from CLD (area under the curve = 0.938 [95% confidence interval, 0.884–0.991]). When analysis was restricted to patients with tumors ≤ 3 cm, the UPS model exhibited higher sensitivity (83.1% vs 51.8%) and specificity (90.2% vs 83.7%) than the three conventional markers, with good positive predictive values (34.2% vs 15.1%). These results were confirmed in the independent validation set. Conclusion: The UPS signature in combination with AFP and DCP provides sensitive and specific differentiation of HCC in patients with CLD. The importance of the UPS in HCC suggests that therapeutic approaches targeting the UPS should be explored.

Introduction: We previously reported a prognostic scoring system in CLL using pre-treatment factors in patients treated with ibrutinib [Ahn et al, 2016 ASH Annual Meeting]. Here we present long-term follow-up results and validation of the prognostic models in a large independent cohort of patients. We also determine the incidence of resistance-conferring mutations in BTK and PLCG2 genes in different clinical risk groups. Methods and Patients: The discovery cohort comprised 84 CLL patients on a phase II study with either TP53 aberration (deletion 17p or TP53 mutation) or age ≥65 years (NCT01500733). The validation cohort comprised 607 patients pooled from four phase II and III studies for ibrutinib in treatment-naïve or relapsed/refractory CLL (NCT01105247; NCT01578707; NCT01722487; NCT01744691). All patients received single-agent ibrutinib 420mg once daily. We used Cox regression models to identify independent predictors of PFS, Kaplan-Meier method to estimate probabilities of PFS, log-rank test to compare PFS, and Cochran-Armitage trend test to compare the incidence of mutation among subgroups. We used R version 3.5.0 or SAS® version 9.3 for statistical analyses. For biomarker correlation, we tested cellular DNA or cell-free DNA collected from patients in the discovery cohort with the targeted sequencing of BTK and PLCG2 genes. Result: At a median follow-up of 5.2 years, 28 (33.3%) of 84 patients in the discovery cohort progressed or died. 52 (61.9%) patients had treatment-naïve CLL. Independent factors of PFS on univariate analysis were; TP53 aberration, prior treatment, and β-2 microglobulin (B2M) >4mg/L (P4mg/L for Model 1, and TP53 aberration, advanced Rai stage, and relapsed/refractory CLL for Model 2 (Table 1). The high-risk group had all three adverse risk factors; the intermediate-risk group had two risk factors; and the low-risk group, none or one. The median PFS of the high-risk group was 38.9 months for Model 1 and 38.4 months for Model 2, and was significantly shorter than those of intermediate and low-risk groups. In the validation cohort, 254 (41.8%) of 607 patients progressed or died at a median follow-up of 4.2 years. 167 (27.5%) patients had treatment-naïve CLL. Both models showed statistically significant differences in PFS by risk groups (Table 1). For the high-risk group, 4-year PFS was 30.2% in Model 1 and 30.5% in Model 2, which were inferior to those of intermediate (53.4 and 52.4%) and low-risk groups (68.7 and 73.7%). Model 1 classified 20% of patients and Model 2 classified 28% of patients to the high-risk group. BTK and PLCG2 mutations are common genetic drivers of ibrutinib resistance in CLL. To determine whether the incidence of these mutations correlates with prognostic risk groups, we performed targeted sequencing of BTK and PLCG2 of samples collected from patients in the discovery cohort. We used cell-free DNA for patients who received long-term ibrutinib (≥3 years) and had low circulating tumor burden, and cellular DNA, for samples collected within 3 years on ibrutinib or at progression. Of 84 patients, 69 (82.1%) were tested at least once, and 37 (44.0%) were tested at least twice. The frequency of testing was similar across the risk groups by two models (P>0.05). The cumulative incidences of mutations at 5 years in the low-, intermediate-, and high-risk groups were: 21.4%, 44.8% and 50%, respectively, by Model 1 (P=0.02); and 22.6%, 41.4% and 66.7%, respectively, by Model 2 (P=0.01). Conclusion: We developed and validated prognostic models to predict the risk of disease progression or death in CLL patients treated with ibrutinib. Risk groups classified by three commonly available pre-treatment factors showed statistically significant differences in PFS. The clinically-defined high-risk disease was linked to higher propensity to develop clonal evolution with BTK and/or PLCG2 mutations, which heralded ibrutinib resistance. Disclosures Albitar: Neogenomics Laboratories: Employment. Ma:Neogenomics Laboratories: Employment. Ipe:Pharmacyclics, an AbbVie Company: Employment, Other: Travel; AbbVie: Equity Ownership. Tsao:Pharmacyclics LLC, an AbbVie Company: Employment. Cheng:Pharmacyclics LLC, an AbbVie Company: Employment. Dean:CTI BioPharma Corp.: Employment, Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment, Equity Ownership. Wiestner:Pharmacyclics LLC, an AbbVie Company: Research Funding.

Eltrombopag (EPAG), a thrombopoietin receptor agonist, has been shown to improve hematopoiesis in patients with aplastic anemia (AA), but in MDS patients the effect of thrombopoietin mimetics in bone marrow function is still unclear. In this phase-2 dose escalation study, we investigated the safety and effectiveness of EPAG treatment in low to intermediate-2 risk MDS patients (NCT 00961064). Thirty patients were enrolled from March 2011 to July 2017. Preceding enrollment the majority of patients were either diagnosed with AA (n=13) or hypoplastic MDS (n=5). EPAG was started at 50 mg/day, up to a maximal dose of 150 mg/day, increasing the dose by 25mg every 2 weeks. The primary endpoint was hematologic response at 16 or 20 weeks, defined as either: (1) an increase in platelet counts ≥20.000/uL or transfusion independence for a minimum of 8 weeks; (2) hemoglobin (Hb) increase of ≥1.5g/dL from baseline, or a reduction in red blood cells (RBC) transfusion of at least 50%; or (3) an increase in absolute neutrophil counts (ANC) of ≥0.5x109/L or by at least 100% in patients with a baseline ANC The primary endpoint of hematological response was met in 14/30 patients (47%). All responders continued EPAG on the extension arm. In 3 patients, peripheral blood cell counts declined on EPAG after the initial response. One patient withdrew from the study. Ten of the 14 responding patients achieved a robust response (RR) after a median treatment duration of 15 months (range 7-27 months). Robust response was defined as stable hematopoiesis with at least a hemoglobin >10g/dl, and thrombocytes >50.000/L, and ANC>1000/L. However, peripheral blood cell counts significantly declined in 5/10 RR and EPAG was restarted per protocol. In 4 of these patients peripheral blood cell counts recovered. One patient did not achieve a second response. Based on International Prognostic Score System (IPSS), 4/30 (13%) patients progressed on study, including 3 non-responders and 1 responder, at a median follow-up of 4 months (3-35 months). The responding patient was diagnosed with increased bone marrow myeloblast 7 months after discontinuation of EPAG for robust response and 35 months after enrolling in the study. New cytogenetic abnormalities determined progression in non-responding patients (Figure). Novel dose limiting toxicities were not observed. Three patients developed CTCAE grade III hepatic toxicities. One of them discontinued EPAG at 3 months. Elevated transaminases returned to baseline after EPAG discontinuation in 2 patients. In both cases EPAG was resumed either at the same (150mg/day) or reduced dose (50mg/day) level. There were no treatment-related death cases. One patient died on study before the primary endpoint from acute respiratory distress syndrome. Sequential acquisition of genomic aberrations has been associated with malignant transformation. Targeting next-generation sequencing for somatic variants in genes previously associated with myeloid malignancies (Myeloid cancer genes, MCG) was performed in 29/30 patients with sufficient material (bone marrow mononuclear cells) available from baseline, primary endpoint, and at time of progression. At baseline, 22/29 (76%) patients were found with at least one mutation:TET2 (14.5%), ASXL1 (12.5%), SF3B1 (8.3%), SETBP1 (8.3%), ATM (8.3%), and ZRSR2 (8.3%). After EPAG, additional somatic variants in different genes were detected in 4/14 responders and 7/16 non-responders. Variants present at baseline were no longer detected in post EPAG samples from 4 responding and 6 non-responding patients. The VAF of variants detected at both time points were similar, indicating no selective expansion of clones with EPAG in neither responder, non-responder nor patients with progression based on IPSS. In conclusion, our results suggest that EPAG is well-tolerated and effective in restoring hematopoiesis in patients with low to intermediate-2 risk MDS, particular with a prior history of hypoplastic bone marrow failure syndromes. EPAG was discontinued for robust response in the majority of responders but declining blood cell counts were observed in about 50% of them. Variants in MCG were more common at study entry compared to patients with aplastic anemia (Yoshizato, NEJM, 2015). However, EPAG appears not to selectively promote expansion of clones harboring MCGs in this patient population. Disclosures Townsley: National Institute of Health: Research Funding. Scheinberg:Pfizer: Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Janssen: Honoraria, Research Funding. Dunbar:National Institute of Health: Research Funding. Young:GlaxoSmithKline: Research Funding; CRADA with Novartis: Research Funding; National Institute of Health: Research Funding. Winkler:National Institute of Health: Research Funding.

Background: Acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) are heterogeneous groups of disorders with a spectrum of clinical presentations and outcomes. Prognosis depends on various factors including age, karyotype, performance status, previous treatments and mutation status. Genetic profiling with next generation sequencing (NGS) is increasingly being used at diagnosis to detect presence of somatic mutations for prognostic risk stratification, and identification of therapeutic targets. Here we seek to identify epidemiologic differences in genetic mutations based on population and demographic data in patients with a preliminary diagnosis of AML or MDS. Methods: NGS mutation data were collected for 62 genes related to AML/MDS on a total of 10,934 patient samples submitted for testing for suspected AML/MDS. Samples were run on either the 54-gene NeoType Myeloid Disorders Profile (Neogenomics) or the 37-gene OnkoSight Myeloid Malignancies Panel (Genpath). The frequency of gene mutations (i.e., the number of patient samples with mutations for each gene) was identified for 58 counties in the USA. Counties in which fewer than 50 patient samples were tested were excluded from the dataset to minimize sampling bias. The counties were then grouped into 3 categories ranging from most urban to most rural based on a modified version of the 2013 National Center for Health Statistics classification system G-1 - > 1,000,000 (N=34), G2 - 250,000 - 1,000,000 (N=16) and G3 < 250,000 (N=8). One-way ANOVA and subsequent T-tests were performed for all genes based on the 3 urban-rural groupings to determine if significant differences in frequency of mutations exist between the 3 groupings. Difference of proportions tests were performed to identify variations in the patterns of frequency between counties. Results: The top 10 most frequent mutations were TET2, ASXL1, DNMT3A, SRSF2, TP53, RUNX1, SF3B1, U2AF1, NRAS, and NPM1(highest to lowest). The three mutations with the widest range of variability across counties were DNMT3A, TET2, and ASXL1 (DTA mutations). The median age across all counties was 68 (range 44-77). The county with the youngest and highest median age was Montgomery, CA and Pinellas, FL, with ASXL1 and TET2 as the most frequent mutation, respectively. Sacramento, CA had an unusually high rate of ASXL1 mutations (> 24%). ASXL1 was also significantly higher than TET2 in Essex, NJ; Montgomery, MD; and Sacramento, CA. (p=0.0287, p < 0.0001, p < 0.0001, respectively). IDH1was higher than IDH2 for Martin, FL (p= 0.0481). The highest frequency of TP53 mutation (24%) was in Bexar, TX compared to Montgomery, MD which had the lowest (2%). When counties were grouped based on population density, the frequency of RUNX1 and SF3B1 were statistically different across the counties, highest in G2 compared to G1 and G3 (p= 0.0294 and 0.0010 respectively). Conclusion: Our retrospective observational study is the first of its kind to look at genetic mutations in AML/MDS patients across the United States using commercially available NGS platforms. In general, patients had analogous combinations and frequencies of mutations commonly seen in AML and MDS, and the wide variation in frequency of DTA mutations is consistent with information known about age-related clonal hematopoiesis. In counties that showed a higher rate of ASXL1 > TET2, there may be a potential environmental factor accounting for this difference as the reverse is more commonly seen. Likewise, IDH1 mutations are typically seen at a lower frequency compared to IDH2, and it is interesting to note the reverse in Martin, FL (G2) despite the mutation frequency of all other genes being similar compared to the median for all counties. Our data analysis also showed a significant difference in frequency of mutations for TP53, RUNX1 and SF3B1. These variations have important implications in regard to prognosis, and the approach to treatment. Our observations suggest further investigation is warranted to explore potential environmental exposures related to somatic mutational patterns in patients with AML and MDS. Disclosures McCloskey: Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Celgene Pharmaceuticals: Honoraria, Speakers Bureau; Amgen Pharmaceuticals: Speakers Bureau; Pfizer: Consultancy; Takeda Pharmaceuticals: Consultancy, Speakers Bureau; COTA: Equity Ownership. Koprivnikar:Amgen: Speakers Bureau; Otsuka: Consultancy; Alexion: Consultancy, Speakers Bureau.

Background: Core-binding factor (CBF) acute myeloid leukemias (AML) are classified as favorable prognosis subgroup but outcomes do not approach that of acute promyelocytic leukemia. We and others have shown that that 3-log reduction in fusion transcript by quantitative PCR (qPCR) at the end of induction portends for better outcome. In this study, we focused on finding gene expressions by RNA sequencing from samples at first diagnosis that could predict early molecular remission. In addition, RNA seq allowed us to identify biological difference distinguishing between the two cytogenetic subgroups [Inversion (Inv) 16 vs t (8;21)] that potentially can be used therapeutic approaches and to detect low frequency mutations. Methods: Samples collected at diagnosis from forty-five patients with CBF-AML, treated with fludarabine, cytarabine and granulocyte colony stimulating factor (FLAG) based regimen were analyzed. RNA sequencing was performed by hybridization based targeted panel that detects fusion, expression, and mutations in the 1385 genes (Illumina, San Diego, CA). Each sample was deeply sequenced (>55M reads) using Illumina paired-end 75 bp sequencing and duplicate reads were removed before fragment per kilobase of transcript per million mapped reads (FPKMs) were calculated for each gene. The expression data was mean centered around expression of ABL1. Cytogenetic subgroups were classified by a Bayes multi-variate logistic regression model. The models were evaluated by the Leave One Out Cross-validation technique. Results: The median age of patients was 36 years (range, 22-78); 26 patients (58%) had Inv16 and 19 (42%) had t(8;21). All patients achieved remission and 7 patients relapsed; 4 had t(8;21) and 3 had Inv16. The expression of RUNX1T1, NR6A1, VEGFA, PLCG1, and CD58 mRNA was significantly (P Our analysis also identified several mutations not commonly described in CBF AML; RICTOR (n=5), ACACA (n=4), FIP1L1, KDM5A, MSH6 (all n=3), KMT2D, ATM, PRKCA (all n= 2). Mutations in 43 other genes were seen in only one patient each. Presence of KIT (n = 16, 36%) or FLT3 (n = 10, 22%) mutations did not predict for relapse and this was consistent our prior analysis. Conclusion: Our data suggests that baseline targeted RNA NGS profiling, not only will detect the Inv16 and t(8;21) fusion RNA, but might help to predict early molecular response and relapse in patients with CBF-AML. Pathway based analysis to understand underlying biology of cytogenetic subgroups and molecular response prediction is ongoing. Our next steps will include accessing publicly available databases for further validation of data. Disclosures Cortes: novartis: Research Funding. DiNardo:Karyopharm: Honoraria; Agios: Consultancy; Abbvie: Honoraria; Bayer: Honoraria; Medimmune: Honoraria; Celgene: Honoraria. Kadia:Novartis: Consultancy; Jazz: Consultancy, Research Funding; Celgene: Research Funding; Celgene: Research Funding; Abbvie: Consultancy; Amgen: Consultancy, Research Funding; Novartis: Consultancy; BMS: Research Funding; Pfizer: Consultancy, Research Funding; Jazz: Consultancy, Research Funding; Abbvie: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy; Pfizer: Consultancy, Research Funding; BMS: Research Funding; Takeda: Consultancy.

Introduction Flow cytometry is the gold standard for diagnosing hematologic cancers based on morphologic detection and analysis of a few expensive and delicate immunological markers. On the other hand, targeted RNA sequencing panels are not sample or marker limited; in fact, 50ng of RNA stored for up to 6 months could yield results for thousands of markers. We hypothesized that an RNA-Seq-based targeted immuno-oncology gene expression panel could recapitulate the FLOW diagnostic patterns of AML and CLL routinely used in a clinical laboratory. Methods A custom panel of 2207 genes was constructed including 58 typical FLOW markers and well-referenced immune and oncology markers. Housekeeping genes were added to normalize between batches. A total of 52 CLL, 15 AML, and 20 normal clinical samples were tested in parallel with a clinically validated leukemia/lymphoma flow cytometry panel and targeted RNA-Seq. Paired-end 76 x 76 cycles sequencing was performed using Illumina NextSeq. Bowtie analysis suite was performed to determine gene expression. Unsupervised analysis was first performed to identify patterns associated with clinical diagnosis or sequencing artifacts. Two-way hierarchical clustering of genes having a median expression of >1 fpkm and at least 2 fold differential expression than the median in 10% of the samples revealed a strong CLL profile and a less pervasive AML profile without any supervised analysis. To determine which genes in the profiles were significantly associated with AML or CLL, genes with >5 fold differential expression were assessed after Benjamini-Hochberg correction with single tailed T-tests. Further, each FLOW marker was individually tested using a 1-way ANOVA. Pathway analysis was performed on GO terms using the Fischer exact test. All corrected p-values Results In general, the FLOW marker gene expression data highly correlated with protein marker expression and was adequate for rendering proper diagnosis. Overall, CLL had a strong immune-oncology pattern with 10+ flow markers including CD19, CD5, CD2, CD200, CD22, CD79, FCER2, IL3RA, IL2RA, PDCD1, and MS4A1 significantly associated with CLL. In addition, 295 other genes including immune targets like CD74, CD33, CD34, CD48, CD40, and gene targets like PAX5, BCL2, PARP3 further help classify CLL. Forty-three of these genes are involved in immune response pathway (p Conclusion Based on our preliminary study, we have shown that protein marker expression determined by flow are reproduced by our RNA expression panel. Importantly, we are able to classify and diagnose CLL and AML samples based on their RNA expression profiles. Disclosures Wong: NeoGenomics: Employment. Funari:NeoGenomics: Employment.

Background: Venetoclax (VEN) is a potent and selective small molecule BCL2 inhibitor, with activity both as a single agent in relapsed/refractory AML, and in frontline combinations with hypomethylating agents and low-dose cytarabine. The ability of VEN to reduce the apoptotic threshold indicates it may be effective in combination with genotoxic agents which induce apoptosis, such as the FLAG-IDA regimen. Objectives: A Phase 1b/2 clinical trial was designed to assess the safety and efficacy of VEN in combination with FLAG-IDA induction/consolidation. The primary safety endpoint was the overall incidence and severity of adverse events by CTCAE criteria. The primary efficacy endpoint was ORR by modified IWG AML criteria, and defined as CR, CRi, and PR. Secondary analyses include duration of response (DOR) and overall survival (OS), and exploratory analyses include gene expression signatures by RNA sequencing. Methods: Eligibility for the Phase 1b portion includes medically fit, relapsed/refractory (R/R) AML patients of any age with adequate organ function and ECOG PS ≤ 2. Patients receive FLAG-IDA induction/consolidation, in combination with VEN orally daily. FLAG-IDA induction for R/R AML consists of fludarabine 30 mg/m2 IV days 2-6, cytarabine 2 g/m2 IV days 2-6, idarubicin 6 mg/m2 IV days 4-6, and filgrastim 5 mcg/kg daily days 1-7 (or peg-filgrastim 6 mg after day 5 to replace remaining injections). The first cohort (dose -1) received FLAG-IDA with VEN 200 mg on days 1-21 of induction, incorporating a 2-day VEN dose ramp up. After the observation of gram-negative bacteremia and/or sepsis in 5 of the first 6 patients during cycle 1 nadir, an amended dose level -1 induction was designed with VEN 200 mg on days 1-14 and cytarabine 1.5 g/m². After completion of induction/consolidation, single-agent VEN at 400 mg orally continuously is provided as maintenance for patients not proceeding to SCT. The data cutoff for this analysis was 7.26.2018. Results: Twelve patients with a median age of 49 years (range 32 - 72) have been enrolled. All patients had relapsed/refractory AML with a median of 2 (range 1 - 4) prior treatments, and four (33%) patients had received ≥1 prior allogeneic SCT. Six patients (50%) had complex cytogenetics, 3 (25%) were intermediate risk, and 3 (25%) were favorable risk. Additional demographics including molecular annotation at study enrollment are provided in Table 1. The median number of FLAG-IDA + VEN cycles received is 2 (0.5 - 3). Severe adverse events regardless of causality were neutropenic fever/bacteremia (n=5), pneumonia/lung infection (n=4), sepsis (n=4), typhlitis (n=1), and hypotension (n=2). All cases of sepsis occurred in the original dose -1 cohort. No early mortality was observed on study (30-d and 60-d mortality 0%). Of 12 patients, one remains too early for response assessment. Of 11 patients, 8 patients (73%) achieved a best response of CR/CRi (7 CR, 1 CRi). Seven patients attained a best response within the first induction cycle, and one attained blast reduction after cycle 1 followed by CR after re-induction. Median time to ANC recovery > 500/ul in responding patients was 28 days (range 23 to 33 days). Of the 8 responding patients, three patients proceeded to allogeneic SCT, 2 remain on study, 2 patients relapsed, and 1 patient died in CR. Figure 1 depicts OS and DOR. With a median follow-up time of 4 months to date, median DOR has not been reached and the 6-month OS is 67%. NGS evaluation of RNA at pre-treatment and end of cycle 1 (EOC1) timepoints demonstrated no significant difference in BCL2 expression, either before/after therapy per patient, or based on clinical response. In patients who failed to achieve CR/CRi, significantly lower EOC1 expression (p=0.05) of BAX, BCLXL, BCL10, BCL2A1, BCL3, BCL9, TRS1, and TP53 was identified. Additionally, increased MCL1 expression at EOC1 was significantly (p=0.04) associated with relapse. Conclusion: FLAG-IDA chemotherapy with venetoclax demonstrates notable activity in a heavily pre-treated and R/R yet medically fit patient population. Neither prolonged cytopenias nor early mortality was observed. The ongoing Phase 1b portion aims to establish the best VEN dose in combination with intensive chemotherapy, to be followed with a Phase 2 portion with treatment arms for both newly diagnosed and R/R AML patients. Disclosures DiNardo: Medimmune: Honoraria; Bayer: Honoraria; Karyopharm: Honoraria; Abbvie: Honoraria; Celgene: Honoraria; Agios: Consultancy. Albitar:Neogenomics Laboratories: Employment. Kadia:Abbvie: Consultancy; Jazz: Consultancy, Research Funding; BMS: Research Funding; BMS: Research Funding; Celgene: Research Funding; Abbvie: Consultancy; Takeda: Consultancy; Novartis: Consultancy; Pfizer: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy; Amgen: Consultancy, Research Funding; Jazz: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy; Celgene: Research Funding. Ravandi:Bristol-Myers Squibb: Research Funding; Xencor: Research Funding; Sunesis: Honoraria; Macrogenix: Honoraria, Research Funding; Abbvie: Research Funding; Amgen: Honoraria, Research Funding, Speakers Bureau; Jazz: Honoraria; Jazz: Honoraria; Amgen: Honoraria, Research Funding, Speakers Bureau; Orsenix: Honoraria; Macrogenix: Honoraria, Research Funding; Orsenix: Honoraria; Astellas Pharmaceuticals: Consultancy, Honoraria; Xencor: Research Funding; Sunesis: Honoraria; Seattle Genetics: Research Funding; Abbvie: Research Funding; Astellas Pharmaceuticals: Consultancy, Honoraria; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding. Cortes:Novartis: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Arog: Research Funding. Konopleva:Stemline Therapeutics: Research Funding.

Here we review phospho-specific, quantitative flow cytometry approach as a rapid and reliable tool for measuring intracellular signaling proteins with potential applications in monitoring efficacy of targeted therapy. The single cell, multiparameter nature of flow cytometry allows simultaneous investigation of specific cell type and the corresponding intracellular markers. Peripheral blood can be directly stained with surface markers to delineate cell populations of interest, followed by fixation, permeabilization, and immunostaining with specific antibodies to the cellular targets. By using calibrated standardized phycoerythrin (PE)-conjugated beads for signal quantification, an informative Index value can be generated for each sample by multiplication of percentages of positive cells with fluorescence intensity per cell. This technique can yield both qualitative and quantitative information on effects of cellular markers upon targeted therapy, thereby providing another layer of advantages over the conventional flow cytometry analysis. Advances in this technology: high-throughput capability and automation, making it a valuable platform in modern drug discovery.

Hypomethylating agents (HMA) and lenalidomide (LEN) are approved and used in the treatment of patients (pts) with MDS, though these drugs fail in most pts. No method exists to predict drug response beyond associating single actionable mutations with a single drug's response. We hypothesized that MDS pts can be clustered by similarities in genomic/molecular profiles, & that each cluster may be assigned combos of FDA-approved drugs to target their unique biomarker profile. Bone marrow cells from 88 MDS pts & the MDS-L cell line were analyzed by cytogenetics & for mutations in 14 myeloid genes using NGS. 31 pts had sufficient data for analysis. 20 profiles had similar aberrations & were grouped. Genomic data from pts and MDS-L were entered into a computational biology modeling (CBM) software, which generates a disease-specific protein network map using PubMed to create digital models and identify characteristic biomarkers unique to each pt. An algorithm was created to cluster the models based on overlapping disease-specific biomarkers. Digital drug simulations (DDS) were conducted both on MDS-L & pt simulation models by quantitatively measuring drug effect on a cell growth score (CGS), a composite of cell proliferation, viability & apoptosis. DDS identified drugs by assessing their impact on disease-specific biomarkers and calculated CGSs. Predictions were validated using MTT. 14/31 MDS pt profiles, including the MDS-L cell line, clustered into 4 groups based on biomarker characteristics.MDS-L cells harbor NRAS (G12A) mutation,-7,-12,+1,+8,+19,+20 and +21. Genes associated with increased copy number (CN) include AURKA, IGFR, PAR5, MTOR, IL6, JAK3, MDM4, MYC, MCL1, COX2, PDE4A, and RCE1; genes associated with decreased CN include DUSP1, RASA1, NR3C1, IRF1, ETV6, and SHH. CBM identified active biomarkers in MDS-L cells (90RSK, MAPK7, AKT and BTK), validated by western blot. DDS predicted nelfinavir+celecoxib to be effective in MDS-L. MDS-L cells were treated with nelfinavir, celecoxib, and nelfinavir+celecoxib with increasing doses. Nelfinavir & celecoxib reduced MDS-L viability in a dose-dependent manner, while nelfinavir+celecoxib showed additive reduction of MDS-L viability. DDS was performed on each pt to predict response to HMA and LEN. Two of the clusters (n=2/cluster) were predicted to be non-responders to any SOC therapy. A third cluster (n=3) was predicted to respond to HMA, but not LEN, and the fourth cluster (n=6) showed varying or no response to either HMA/LEN. These results use a novel concept of using genomics & CBM to cluster profiles with overlapping disease-relevant biomarkers & similar drug response predictions. CBM can identify pt populations who may benefit from certain therapeutic regimens, improving response rates, & give insights into the mechanisms by which each drug impacts the MDS-specific biomarkers Citation Format: Leylah M. Drusbosky, Kimberly E. Hawkins, Amy Meacham, Elizabeth Wise, Neeraj Kumar Singh, Chandan Kumar, Sumanth M. Vasista, Rakhi P. Suseela, Taher Abbasi, Shireen Vali, Kaoru Tohyama, Maher Albitar, Peter P. Sayeski, Christopher R. Cogle. Genomics-driven clustering of disease-related biomarkers identifies therapeutic options in myelodysplastic syndromes (MDS) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4285.

PURPOSE While HER2 testing is well established in directing appropriate treatment for breast cancer, a small percentage of cases show equivocal results by IHC and FISH. Alternative probes may be used in equivocal cases. We present a single community-based institution's experience in further evaluating these cases. PATIENTS AND METHODS Between 2014-2016, 4255 samples were submitted for HER2 amplification testing by alternative probes, TP53, RAI1, and RARA. Of patients tested by FISH, 505/3908 (12.9%) also had IHC data. RESULTS Most (73.9%) FISH equivocal cases remained equivocal after IHC testing. Duplicate testing by IHC using a different paraffin block resulted in poor reproducibility as 44% of IHC negative became equivocal and 40% of IHC equivocal became negative. Of the equivocal cases by IHC, 52.3% became positive by alternative FISH. However, 50.5% of cases equivocal by conventional FISH were classified as HER2 amplified by alternative probes. Most cases were positive by more than one probe; 78% of positive cases were positive by RAI1 and 73.9% by TP53. There was a significant difference between IHC and FISH alternative testing (P CONCLUSION The prevalence of double HER2 equivocal cases and the discrepancy between IHC and alternative FISH testing suggest that FISH alternative testing using both RAI1 and TP53 probes is necessary for conclusive classification. Due to the significant difference between IHC repeat testing, reflexing on IHC alone in this group of cases may not be reproducible. Because almost half of FISH equivocal cases converted to HER2 amplified upon alternative testing, clinical studies to determine benefit of anti-HER2 therapy in these patients is urgently needed. Alternative FISHIHC Score 0 NegativeIHC Score 1 NegativeIHC Score 2 EquivocalIHC Score 3 PositiveNo%No%No%No%Negative1463.65454.517847.7436.4Positive836.44545.519552.3763.6Total22100.099100.0373100.011100.0 Citation Format: Sally Agersborg, Christopher Mixon, Thanh Nguyen, Sramila Aithal, Forrest Blocker, Lawrence Weiss, Robert Gasparini, Shiping Jiang, Wayne Chen, Gregory Hess, Maher Albitar. Immunohistochemistry and alternative FISH testing in breast cancer with HER2 equivocal amplification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4524.

Objective CD33 is a cell surface antigen for committed myelomonocytic lineage. We explored the potential of detecting CD33 as cell-free circulating protein in patients with leukemia. Materials and Methods We developed a quantitative bead-based immunoflow cytometry assay to measure cell-free circulating CD33 (cCD33) levels in the plasma of patients with acute leukemia, and correlated these results with corresponding clinical behavior. We measured cCD33 levels in the plasma of 48 healthy subjects and in patients with acute myelogenous leukemia (n = 98), acute lymphoblastic leukemia (n = 46), myelodysplastic syndrome (MDS) (n = 50), and myeloproliferative disorder (n = 49). Results Patients with acute myeloid leukemia and myeloproliferative disorders had significantly higher concentrations of cCD33 than the other patient groups and normal individuals ( p = 0.0001), and among these groups, MDS patients displayed the lowest cCD33 levels ( p = 0.02). Circulating CD33 values correlated positively with the CD33 + blast cell counts in these patients. While there was no correlation between cCD33 levels and survival in acute myelogenous leukemia and MDS, higher cCD33 plasma concentrations did correlate with shorter survival in acute lymphoblastic leukemia ( p = 0.03), and with shorter complete remission duration in acute myelogenous leukemia ( p = 0.04) and MDS ( p = 0.03). Conclusion Circulating CD33 can be detected in the plasma from patients with leukemias, and cCD33 levels may have clinical implication, e.g., predictive and prognostic value, in these patients.

e15604Background: Microsatellite instability (MSI) and DNA mismatch repair defect (dMMR) are dependable predictive biomarkers of colorectal cancer (CRC) response to checkpoint inhibitors. We explor...

3022Background: DNA mismatch repair deficiency (dMMR) can be tested by immunohistochemistry (IHC) or microsatellite instability (MSI). While either IHC and MSI is adequate for establishing Lynch sy...

3088Background: Predictive biomarkers for selecting of patients who may benefit or experience serious adverse effects from checkpoint blockade therapy are urgently needed. These biomarkers may vary...

CD52 and CD20 antigens are important therapeutic targets for the monoclonal antibodies (mAbs) alemtuzumab and rituximab respectively. Circulating CD52 (cCD52) and CD20 (cCD20) have prognostic utility in lymphoid malignancies. The efficacy of mAb therapy in patients with chronic lymphocytic leukaemia (CLL) may be adversely affected by cCD52 or cCD20. In this report, blood and bone marrow (BM) cCD52 and cCD20 were measured at response assessment in previously treated (N = 235) patients with CLL who received fludarabine, cyclophosphamide, and rituximab (FCR). Univariate and multivariate statistical models evaluated correlations of pre- and response variables with progression-free (PFS) and overall survival (OS). Response variables included 1996 National Cancer Institute-Working Group (NCI-WG) response, polymerase chain reaction (PCR) for immunoglobulin heavy chain (IGHV) in BM, and cCD52 and cCD20 levels (blood and BM) at response assessment. Using multivariate analysis, response blood and BM cCD52, blood cCD20, and NCI-WG response were significant independent predictors of PFS. At the time of response assessment, BM cCD52 correlated with OS in univariate analysis. cCD52 and cCD20, therefore appear useful in predicting survival and may be important for monitoring patients following salvage FCR (fludarabine, cyclophosphamide, rituximab) therapy. These data further indicate that plasma may be a good target to evaluate for minimal residual disease using cCD52/cCD20 levels.

Background: Four individuals in whom Monoclonal B cell Lymphocytosis (MBL) had been previously detected were evaluated for the fourth time after 15–18 years since initial testing. All four were environmental health study participants without hematologic malignancies who had elevated absolute B cell counts at initial testing. Methods: The current laboratory evaluation included complete blood counts, lymphocyte immunophenotypes, immunoglobulin heavy-chain variable (IGHV) gene mutation status, and serum tests for monoclonal immunoglobulins and free light chains. Results from this evaluation were compared with those from the three previous evaluations. Clinical status was assessed by reviewing medical records. Results: B-cell clones with phenotypic characteristics of the original MBL clone were detected in three of the four individuals. Since the last evaluation in 2003, one participant who had a clinical diagnosis of Waldenstrom's Macroglobulinemia had developed a diffuse large cell lymphoma and was treated. Another participant continued to show a decline in lymphocyte and B cell counts, reaching clinical lymphocytopenia and B cell lymphopenia. The MBL clone was still detectable. The remaining two participants had stable blood counts and MBL phenotypes. Neither had been diagnosed with a hematologic malignancy. However, molecular analysis revealed clonal changes in both: one showed a marked decline in the percentage of somatically-mutated B cells, and the other showed a clonal transition from IGHV3-13 to IGHV4-34. Conclusions: A diversity of clonal evolution was observed in these MBL cases. These observations suggest that long-term follow-up studies using standardized MBL subcategories are essential to understanding B-cell pathobiology and optimizing clinical management. Published 2010 Wiley-Liss, Inc.

Immune-related deficiencies are well-known complications of chronic lymphocytic leukemia (CLL). Although recent data indicate that almost all CLL patients are preceded by a monoclonal B-cell lymphocytosis precursor state, patterns of immune defects preceding CLL diagnosis are unclear. We identified 109 persons who developed CLL from the prospective and nationwide Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial with 77 469 participants, with serially collected prediagnostic serum samples. We assayed monoclonal (M)–proteins, κ/λ free light chains (FLCs) in prediagnostic obtained up to 9.8 years before CLL diagnosis. The prevalence of an abnormal FLC ratio, M-protein, and hypogamma-globulinemia before CLL diagnosis was 38% (95% confidence interval, 29%-47%), 13% (7%-21%), and 3% (1%-8%), respectively. M-proteins and abnormal FLC ratios were detected up to 9.8 years before CLL diagnosis in a total of 48 persons (44%). Hypogammaglobulinemia was not present until 3 years before the diagnosis of CLL. Among 37 patients with information on tumor cell immunophenotype, an association between immunophenotype and involved FLC (P = .024, Fisher exact test) was observed. Among 61 persons with a normal FLC ratio and without an M-protein, 17 had elevated κ and/or λ FLC levels, indicating polyclonal B-cell activation in 17 of 109 (16%) patients. These findings support a role for chronic immune stimulation in CLL genesis.

Purpose: Cytogenetic abnormalities are currently the most important predictors of response and clinical outcome for patients with acute myeloid leukemia (AML) or advanced-stage myelodysplastic syndrome (MDS). Because clinical outcomes vary markedly within cytogenetic subgroups, additional biological markers are needed for risk stratification. Experimental Design: We assessed the utility of measuring pretreatment proteasome chymotrypsin-like, caspase-like, and trypsin-like activities in plasma to predict response and survival of patients with AML (n = 174) or advanced-stage MDS (n = 52). Results: All three enzymatic activities were significantly (P < 0.001) increased in the plasma of patients with AML and MDS compared with normal controls. Both chymotrypsin-like and caspase-like activities, but not trypsin-like activity, correlated with outcome. Chymotrypsin-like and caspase-like activities, but not trypsin-like activity, predicted response in univariate analysis (P = 0.002). However, only chymotrypsin-like activity was independent predictor of response from age grouping ( Conclusions: Measuring plasma chymotrypsin-like activity may provide a powerful biomarker for risk stratification in patients with AML and advanced-stage MDS, including those with normal karyotype.

Large-scale (approximately 36,000 atoms) long-time (30 ns each) molecular dynamics (MD) simulations on the complex of imatinib and 16 common mutants of the ABL tyrosine kinase domain have been performed to study the imatinib resistance mechanisms at the atomic level. MD simulations show that long time computational simulations could offer insight information that static models, simple homology modeling methods, or short-time simulations cannot provide for the BCR-ABL imatinib resistance problem. Three possible types of mutational effects from those mutants are found: the direct effect on the contact interaction with imatinib (e.g. some P-loop mutations), the effect on the conformation of a remote region contacting with imatinib (e.g. T315I), and the effect on interaction between two regions within the BCR-ABL domain (e.g. H396P). Insights of possible imatinib resistance mechanisms, not consistent with current consensus, are revealed from various analyses and our findings suggest that drugs with different binding modes may be necessary to overcome the drug resistance due to T315I and other mutations. The relevant patents are discussed.