Search

Aim: Successful treatment of cutaneous melanoma depends on early and accurate diagnosis of clinically suspicious melanocytic skin lesions. Multiple international studies have described the challenge of providing accurate and reproducible histopathological assessments of melanocytic lesions, highlighting the need for new diagnostic tools including disease-specific biomarkers. Previously, a 38-miRNA signature (MEL38) was identified in melanoma patient plasma and validated as a novel biomarker. In this study, MEL38 expression in solid tissue biopsies representing the benign nevi to metastatic melanoma spectrum is examined. Patients & methods: Nanostring digital gene expression assessment of the MEL38 signature was performed on 308 formalin-fixed paraffin-embedded biopsies of nevi, melanoma in situ and invasive melanoma. Genomic data were interrogated using hierarchical clustering, univariate and multivariate statistical approaches. Classification scores computed from the MEL38 signature were analyzed for their association with demographic data and histopathology results, including MPATH-DX class, AJCC disease stage and tissue subtype. Results: The MEL38 score can stratify higher-risk melanomas (MPATH-Dx class V or more advanced) from lower-risk skin lesions (class I–IV) with an area under the curve of 0.97 (p

Background: Successful treatment of cutaneous melanoma depends on early and accurate diagnosis of clinically suspicious melanocytic skin lesions. Multiple international studies have described the challenge of providing accurate and reproducible histopathological assessments of melanocytic lesions, highlighting the need for new diagnostic tools including disease-specific biomarkers. Previously, a 38-microRNA signature (“Mel38”) was identified in melanoma patient plasma and validated as a novel biomarker. In this study, Mel38 expression in solid tissue biopsies representing the benign naevi to metastatic melanoma spectrum is examined. Methods: Nanostring digital gene expression assessment of the Mel38 signature was performed on 308 formalin fixed paraffin embedded biopsies of naevi, melanoma in-situ and invasive melanoma. Genomic data were interrogated using hierarchical clustering, univariate, and multivariate statistical approaches. Classification scores computed from the Mel38 signature were analysed for their association with demographic data and histopathology results, including MPATH-DX class, AJCC disease stage and tissue subtype. Results: The Mel38 score can stratify higher-risk melanomas (MPATH-Dx Class V or more advanced) from lower-risk skin lesions (Class I-IV) with an area-under-the curve of 0.97 (PConclusion: Melanoma-specific circulating microRNAs maintain their association with malignancy when measured in the hypothesized tissue of origin. The Mel38 signature is an accurate and reproducible metric of melanoma status, based on changes in microRNA expression that occur as the disease develops and spreads. Inclusion of the Mel38 score into routine practice would provide physicians with previously unavailable, personalised genomic information about their patient’s skin lesions. Combining molecular biomarker data with conventional histopathology data may improve diagnostic accuracy, healthcare resource utilisation, and patient outcomes.

Background: Successful treatment of cutaneous melanoma depends on early and accurate diagnosis of clinically suspicious melanocytic skin lesions. Multiple international studies have described the challenge of providing accurate and reproducible histopathological assessments of melanocytic lesions, highlighting the need for new diagnostic tools including disease-specific biomarkers. Previously, a 38-microRNA signature (“Mel38”) was identified in melanoma patient plasma and validated as a novel biomarker. In this study, Mel38 expression in solid tissue biopsies representing the benign naevi to metastatic melanoma spectrum is examined. Methods: Nanostring digital gene expression assessment of the Mel38 signature was performed on 308 formalin fixed paraffin embedded biopsies of naevi, melanoma in-situ and invasive melanoma. Genomic data were interrogated using hierarchical clustering, univariate, and multivariate statistical approaches. Classification scores computed from the Mel38 signature were analysed for their association with demographic data and histopathology results, including MPATH-DX class, AJCC disease stage and tissue subtype. Results: The Mel38 score can stratify higher-risk melanomas (MPATH-Dx Class V or more advanced) from lower-risk skin lesions (Class I-IV) with an area-under-the curve of 0.96 (PConclusion: Melanoma-specific circulating microRNAs maintain their association with malignancy when measured in the hypothesized tissue of origin. The Mel38 signature is an accurate and reproducible metric of melanoma status, based on changes in microRNA expression that occur as the disease develops and spreads. Inclusion of the Mel38 score into routine practice would provide physicians with previously unavailable, personalised genomic information about their patient’s skin lesions. Combining molecular biomarker data with conventional histopathology data may improve diagnostic accuracy, healthcare resource utilisation, and patient outcomes.

Background Successful treatment of cutaneous melanoma depends on early and accurate diagnosis of clinically suspicious melanocytic skin lesions. Currently, histopathology examination of excised skin lesions is considered the ‘gold standard’ for diagnosis of melanoma. Multiple studies have shown the low accuracy and reproducibility of this method, underscoring the urgent need for new diagnostic tools, including disease-specific biomarkers. Previously, a 38-microRNA signature of melanoma (‘Mel38’) was previously identified in plasma and validated as novel circulating biomarker. In this study, Mel38 expression in solid biopsy tissue is examined to determine its ability to contribute to accurate and reproducible melanoma diagnoses.Methods Nanostring digital gene expression profiling was used to apply the Mel38 signature in a cohort of 308 formalin fixed paraffin embedded skin biopsies (‘Mel38’). Genomic data were interrogated using hierarchical clustering, univariate and multivariate statistical approaches. Mel38 classification scores (range 0 to 10) were compared to consensus histopathology results, including MPATH-DX class, AJCC disease stage, histological subtype as well as technical assay factors.Results The Mel38 score can identify high-risk melanomas (MPATH-Dx Class IV) from less-malignant forms of the disease with an area-under-the curve of 0.96 (P 2.3 identifies higher-risk melanomas, associated with poorer outcomes and more intensive suggested clinical actions. Multivariate analysis showed the score to be a significant predictor of malignancy, independent of technical and clinical covariates. Analysis of the Mel38 signature in spitz naevi reveal an intra-subtype profile, in common to both benign and malignant conditions.Conclusion Melanoma-specific circulating microRNAs maintain their association with malignancy when measured in the hypothesized tissue of origin. The Mel38 signature is an accurate and reproducible metric of melanoma status, based on changes in microRNA expression that occur as the disease develops and spreads. Inclusion of the Mel38 score into routine practice would give physicians a genomic assessment of a patient’s disease status. Combining molecular biomarker data with conventional histopathology data may improve diagnostic accuracy, reproducibility, and patient outcomes.

Background: In Australia, more money is spent on skin cancer than any other malignancy. Despite this, the mortality rate of melanoma, the deadliest form, has steadily increased over the past 50 years. Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible for this lack of progress. Methods: Whole-microRNAome profiling was performed on plasma samples from 32 patients with histologically confirmed melanoma and 16 normal controls. A classification algorithm was trained on these data and independently validated on multiple previously published microRNA data sets, representing (i) melanoma patient- and normal-blood, (ii) melanoma and nevi biopsy tissue, and (iii) cell lines and purified exosomes. Results: 38 circulating microRNAs had biologically and statistically significant differences between melanoma and normal plasma samples (MEL38). A support vector machine algorithm, trained on these markers, showed strong independent classification accuracy (AUC 0.79–0.94). A majority of MEL38 genes have been previously associated with melanoma and are known regulators of angiogenesis, metastasis, tumour suppression, and treatment resistance. Conclusions: MEL38 exhibits disease state specificity and robustness to platform and specimen-type variation. It has potential to become an objective diagnostic biomarker and improve the precision and accuracy of melanoma detection and monitoring.

New tools for monitoring response to primary melanoma treatment are needed to reduce recurrence rates and patient anxiety. A previously developed plasma-based microRNA signature (MEL38) was measured in four melanoma patient samples obtained before and 12-14 days after treatment (i.e. surgical excision), as well as in two nonmelanoma controls. The value of the MEL38 score and selected individual genes were compared between the time points. The MEL38 scores of the four patients with melanoma became more 'normal like' after tumour excision, with a statistically significant 15% mean reduction. MicroRNAs involved in tumour suppression were upregulated in the postexcision samples and those involved in facilitating treatment resistance and tumour invasion were downregulated. Based on these limited preliminary data, the MEL38 signature may have clinical utility in assessing an individual patient's response to the most common form of melanoma treatment. Additional studies are needed on larger, clinically diverse patient cohorts, sampled over longer periods of time.

Background Histopathologic examination of melanocytic neoplasms can be challenging and subjective, with no specific circulating or tissue-based biomarkers currently available. Recently, a circulating 38-microRNA profile of melanoma (Mel38) was described. In this study, Mel38 expression and its impact on downstream mRNA regulation in solid tissue is examined. Methods Mel38 was applied to archival, clinically-annotated, solid-tissue genomic datasets representing benign naevi, primary and metastatic melanoma. Statistical analysis of the signature in relation to disease status, patient outcome and molecular pathways was performed. Results Mel38 is able to stratify genomic data from solid tissue biopsies on the basis of disease status and differences in melanoma-specific survival. Experimentally-verified messenger-RNA targets of Mel38 also exhibit prognostic expression patterns and represent key molecular pathways and events in melanoma development and progression. Conclusion The Mel38 microRNA profile may have diagnostic and prognostic utility in solid tissue as well as being a robust circulating biomarker of melanoma.

Objective To examine relationships between weight loss through changes in lifestyle and peripheral blood gene expression profiles. Methods A prospective nonrandomized trial was conducted over 1 year in participants undergoing intensive lifestyle modification to reverse or stabilize progression of coronary artery disease. Cardiovascular risk factors, inflammatory biomarkers, and gene expression as a function of weight loss were assessed in 89 lifestyle participants and 71 retrospectively matched controls undergoing usual care. Results Substantial weight loss (-15.2 ± 3.8%) in lifestyle participants (n = 33) was associated with improvement in selected cardiovascular risk factors and significant changes in peripheral blood gene expression from pre- to post-intervention: 132 unique genes showed significant expression changes (false discovery rate corrected P-value Conclusions Weight loss (≥10%) during lifestyle modification is associated with down-regulation of genetic pathways governing interactions between circulating immune cells and the vascular endothelium and may be required to successfully reduce CVD risk.

Molecular prognostic assays, such as Oncotype DX, are increasingly incorporated into the management of patients with invasive breast carcinoma. BreastPRS is a new molecular assay developed and validated from a meta-analysis of publically available genomic datasets. We applied the assay to matched fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tumor samples to translate the assay to FFPE. A linear relationship of the BreastPRS prognostic score was observed between tissue preservation formats. BreastPRS recurrence scores were compared with Oncotype DX recurrence scores from 246 patients with invasive breast carcinoma and known Oncotype DX results. Using this series, a 120-gene Oncotype DX approximation algorithm was trained to predict Oncotype DX risk groups and then applied to series of untreated, node-negative, estrogen receptor (ER)-positive patients from previously published studies with known clinical outcomes. Correlation of recurrence score and risk group between Oncotype DX and BreastPRS was statistically significant (P

Patients with carcinoma of unknown primary (CUP) present with metastatic disease for which the primary site cannot be found, despite extensive standard investigation. Here, we describe the development and implementation of the first clinically available microarray-based test for this cancer type (CUPPrint), based on 633 individual tumors representing 30 carcinoma and 17 noncarcinoma classes. Tissue of origin prediction for either fresh frozen or paraffin-embedded tumor samples is achieved with the use of a custom 8-pack 1.9k microarray and robust classification algorithm. An expression profile of 495 genes was used to predict tumor origin by applying a k-nearest neighbor algorithm. Internal cross-validation and analysis of an independent, previously published, 229-sample dataset revealed that clinically informative predictions were made for up to 94% of samples analyzed. Analysis of 13 previously published CUP specimens yielded predicted tumor origins that supported the clinical suspicion in 12 cases (92%). Microarray profiling presents a promising tool to assist in the identification of the primary tumor and might direct a more tailored treatment for CUP patients.

Background: Gene expression profiling (GEP) is increasingly being integrated into clinical practice for prognostication of multiple myeloma. MyPRSTM utilizes the 70-gene panel with survival data derived from cohorts of myeloma patients treated under intensive clinical trial regimens including tandem transplants. We aim to validate and expand the prognostic impact of GEP characterization of myeloma in patients treated with various anti-myeloma therapies at a single academic center. Methods: MyPRSTM GEP analysison bone marrow aspirate sampleswas performed on 417 multiple myeloma patients atMoffitt Cancer Center who had bone marrow examination at different phases in the course of their disease. Myeloma risk prognostication was conducted based on the risk classification (cutoff of score 45.2), risk score (0-100), and molecular subtyping. Trend (Jonckheere-Terpstra) test was performed to evaluate the associations of GEP scores and molecular subtypes. Overall survival (OS) was estimated using the Kaplan-Meier method from the time of GEP analysis and OS curves were compared using the log-rank test. Multivariate Cox proportional hazards regression models were built for OS. Results: Median age was 62 (range, 21-86), majority of patients were male (57.6%) and 71 patients (17%) had high-risk disease based on GEP with a median score of 30.7 (range, 8.7-99.4). Median time from myeloma diagnosis to GEP was 15.8 (range, 0.1-370.1) months. Molecular subtypes werehyperdiploidy(HY) 25.2%, cycle family (CD)-2 21.1%, low bone disease (LB) 17.5%, proliferation (PR) 13.4%, MMSET associated (MS) 9.8%, MAF associated (MF) 7.7%, and CD-1 5.1%. There was an increasing trend of higher GEP scores among various molecular subtypes from CD to PR (p Conclusions: Analysis of GEP in myeloma patients irrespective of disease status treated at a single academic institution validates the prognostic significance based on 70-gene GEP score, risk groups and molecular subtyping. Although less robust, GEP risk re-classification with a new threshold value based on the median also demonstrates prognostic significance. Interestingly, parsing of the GEP-70 score by separating patients into different GEP score groups (either in 20-point increments or quartiles) results in distinct groups with distinct survival characteristics suggesting powerful prognostic value of GEP analysis. To this end, a higher GEP score was associated with a worse prognostic score even within the same GEP risk classification. These data indicate the potential for the development of a new risk classification based on GEP score into 4 risk groups. Increased numbers of patients will be required to validate the potential of these score-based risk classifications. In conclusion, our data demonstrate that GEP score remains a powerful prognostic tool regardless of the disease setting. Figure 1 (OS by GEP risk: high vs. low) Figure 1. (OS by GEP risk: high vs. low) Figure 2 (OS by new GEP score cut-off of 30.7) Figure 2. (OS by new GEP score cut-off of 30.7) Figure 3 Figure 3. Disclosures Nishihori: Signal Genetics: Research Funding; Novartis: Research Funding. Baz:Novartis: Research Funding; Takeda/Millennium: Research Funding; Signal Genetics: Research Funding; Karyopharm: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding; Merck: Research Funding. Van Laar:Signal Genetics, Inc.: Employment. Bender:Signal Genetics, Inc.: Employment. Alsina:Signal Genetics: Consultancy; Novartis: Research Funding; Takeda/Millennium: Research Funding; Amgen/Onyx: Consultancy, Speakers Bureau. Shain:Novartis: Speakers Bureau; Amgen/Onyx: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda/Millennium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Signal Genetics: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau.

Background: A commercially available gene expression profiling (GEP) model is an important risk stratification method in multiple myeloma. GEP is helpful in dividing myeloma into low and high risk based on a pre-determined threshold, however, the value of sequential GEP testing on patients receiving sequential anti-myeloma therapies has yet to be fully determined. Methods: Fifty four myeloma patients at Moffitt Cancer Center underwent two sequential GEPs based a dedicated 70-gene panel using an Affymetrixmicroarray platform (MyPRSTM) from bone marrow aspirate samples during the course of their disease. Myeloma was characterized based on the risk classification (cutoff of score 45.2), risk score (0-100), differences in the score/classification, and molecular subtyping. Pearson correlation analysis was performed to correlate GEP scores at two time points. Overall survival (OS) was estimated using the Kaplan-Meier method from the time of first GEP analysis and OS curves were compared using the log-rank test. Multivariate Cox proportional hazards regression models were built for OS. Results: Majority were male (67%) and hadDurie-Salmon stage 2 or 3 disease (83%).Immunophenotypeswere IgG (56%), IgA (22%) and light chain (20%). At first GEP testing (Time 1), 20% (11/54) were high risk and the median score was 28.6 (range, 10.8-66.5) with frequency of molecular subtypes being cycle family (CD) 1&2 28%,hyperdiploidy(HY) 24%, low bone disease (LB) 22%, proliferation (PR) 17%, and MMSET associated (MS) 9%. There were no MAF associated cases in this cohort. At second GEP testing (Time 2), 28% (15/54) were high risk with a median score of 33.5 (range, 11.4-96.3). Pearson correlation coefficient for the GEP scores of Times 1 & 2 was r=0.77 (p Conclusions: Serial GEP analysis on myeloma patients demonstrates longitudinal changes in risk scores, molecular subtyping and risk classification suggesting clonal evolution or modifications of overall transcribed genetic signature with systemic therapy. GEP risk score may potentially provide graded risk assessment rather than dichotomous categorization as different risk threshold may be found based on observation of a new cutoff value predictive of OS. Further analysis of gene expression patterns is ongoing to elucidate risk stratification based on molecular signatures and to elucidate potential treatment associated profiles. Figure 1 Figure 1. Disclosures Nishihori: Novartis: Research Funding; Signal Genetics: Research Funding. Baz:Novartis: Research Funding; Millennium: Research Funding; Merck: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Signal Genetics: Research Funding; Karyopharm: Research Funding; Bristol-Myers Squibb: Research Funding. Van Laar:Signal Genetics, Inc.: Employment. Bender:Signal Genetics, Inc.: Employment. Alsina:Takeda/Millennium: Research Funding; Novartis: Research Funding; Signal Genetics: Consultancy; Amgen/Onyx: Consultancy, Speakers Bureau. Shain:Takeda/Millennium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Signal Genetics: Research Funding; Amgen/Onyx: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Speakers Bureau.

Background: There is a global consensus that multiple myeloma patients with high-risk disease require additional monitoring and therapy compared to low/standard risk patients in order to maximize their chances of survival. Current diagnostic guidelines recommend FISH-based assessment of chromosomal aberrations to determine risk status (i.e. t(14;20), t(14;16), t(4;14) and/or Del17p), however, studies show FISH for MM may have a 20-30% QNS rate and is up to 15% discordant between laboratories, even when starting from isolated plasma cells. In this study we demonstrate that MyPRS gene expression profiling reproduces the key high risk translocations for MM risk stratification, in addition to having other significant advantages. Methods: Reproducibility studies show that MyPRS results are less than 1% discordant starting from isolated plasma cells and return successful results in up to 95% of cases. 270 MM patients from Johns Hopkins University (MD) and Weill Cornell Medicine (NY) had both FISH and MyPRS gene expression profiling performed between 2012 and 2016 using standard and previously published methodology, respectively. Results: Retrospective review of the matched FISH and MyPRS results showed: 25/28 (89%) patients wish FISH-identified t(4;14) were classified as MMSET (MS) subtype. 10/10 (100%) patients with t(14;16) or t(14;20) were classified as MAF-like (MF) subtype 62/67 (93%) patients with t(11;14) were assigned to the Cyclin D (1 or 2) subtype. Patients with FISH hyperdiploidy status were classified as the Hyperdiploid (HY) subtype or had multiple gains detected by the separate MyPRS Virtual Karyotype (VK) algorithm, included in MyPRS. TP53del was seen in patients with multiple molecular subtypes, predominantly Proliferation (PR) and MMSET (MS). Assessment of TP53 function by gene expression is a more clinically relevant prognostic marker than TP53del, as dysregulation of the tumor suppressor is affected by mutations as well as deletions. Analysis of the TP53 expression in the 39 patients with delTP53 showed a statistically significant difference, compared to patients without this deletion (P Conclusion: Gene expression profiling is a superior and more reliable method for determining an individual patients' prognostic risk status. The molecular subtypes of MM, as reported by Signal Genetics MyPRS assay, are driven by large-scale changes in gene expression caused by or closely associated with chromosomal changes, including translocations. Physicians who are managing myeloma patients and wishing to base their assessment of risk on R-ISS or mSMART Guidelines may obtain the required data points from either FISH or MyPRS, with the latter offering lower QNS rates, higher reproducibility, assessment of a larger number of cells and a substantially lower price point ($5,480 vs. $1,912; 2016 CMS data). A larger cohort study is now underway to further validate these observations. Figure GEP-based TP53 expression in patients with and without Del17p. P Disclosures Van Laar: Signal Genetics, Inc.: Employment. Borrelo:Sidney Kimmel Cancer Institute: Employment. Jabalayan:Weill Cornell Medical Center: Employment. Niesvizky:Celgene: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy, Research Funding, Speakers Bureau; Onyx: Consultancy, Research Funding, Speakers Bureau. Zielinski:Signal Genetics, Inc.: Employment. Leigh:Signal Genetics, Inc.: Employment. Brown:Signal Genetics, Inc.: Employment. Bender:Signal Genetics, Inc.: Employment.

Background: In preclinical studies, multiple myeloma (MM) cells are sensitive to selective inhibition of the pro-survival protein BCL-2 by venetoclax (VEN). Resistance to VEN in these models was mediated through BCL-XL and MCL-1, and MCL-1 mediated resistance was neutralized by co-treatment with the proteasome inhibitor bortezomib (BTZ). MM cells harboring the t(11;14) translocation have a higher ratio of BCL-2 relative to MCL-1 mRNA and increased sensitivity to VEN alone, compared to cells with other cytogenetic abnormalities, suggesting that MM subgroups with a favorable BCL-2 family profile might be particularly sensitive to VEN. Clinically, VEN has shown activity in CLL, a disease typically expressing high BCL-2 and low BCL-XL and MCL-1 expression. In MM, VEN is being evaluated as a single agent (NCT01794520) and in combination with BTZ and dexamethasone (Dex) (NCT01794507, NCT02755597) in relapsed/refractory (R/R) patients. As a single agent, improved objective response rates were observed in patients with R/R t(11;14) MM (40% in t(11;14) vs 6% in non-t(11;14)-). In the BTZ/Dex combination study, patients with high BCL-2 expression had an increased objective response rate. Thus, BCL-2 family profiling may explain increased susceptibility of certain MM subgroups to antitumor activity of VEN both as a single agent and in combination. We analyzed MM subgroups for expression of BCL-2 family members to better understand and identify the patient population that can benefit with VEN. Methods: We used publically available data (GSE4581; GSE9782) to analyze BCL-2 family mRNA expression within molecular/cytogenetic defined subgroups among newly diagnosed (NDMM n=414), and R/R (n=264) MM patients, and in comparison to other hematological malignancies (genealogic database). Results: BCL-2, BCL-XL and MCL-1 expression was assessed in MM and compared with 12 major hematologic malignancies. Based on median expression, BCL-2 in MM ranked 6th of 12 tested, with highest BCL-2 expression observed in small lymphocytic leukemia and mantle cell lymphoma. In MM, BCL-2 expression varied significantly across molecular and cytogenetic subgroups. Highest expression was among patients with t(11;14) molecular subtypes (CD1, CD2), in addition to subtypes that are not enriched with t(11;14) like the hyperdiploid and low bone disease subtypes, and lowest in the high-risk subtypes (proliferation, MMSET, MAF/MAFB) (p=0.0001), both in NDMM and R/R MM. BCL-XL and MCL-1 were highly expressed in MM relative to other hematologic malignancies. Expression of BCL-XL and MCL-1 were lowest in the t(11;14) MM population (both p Conclusions: Our analysis suggests that MM subgroups are associated with distinct BCL-2 family expression profiles, and the t(11;14) subgroup amongst MM subgroups may be particularly suited for single agent VEN activity due to a high BCL-2/MCL-1 and BCL-2/BCL-XL ratio. In the non-t(11;14) MM subgroups, VEN treatment in earlier lines of therapy, as well as combination strategies with agents that will down-modulate BCL-XL and/or MCL-1, such as BTZ, may enable maximum VEN activity, and will be further assessed in clinical studies. Disclosures Wu: Genentech: Employment. Ross:AbbVie: Employment, Equity Ownership. Peale:Genentech: Employment, Equity Ownership. Shaughnessy:Signal Genetics: Consultancy, Equity Ownership. Van Laar:Signal Genetics, Inc.: Employment. Morgan:Takeda: Consultancy, Honoraria; Janssen: Research Funding; Bristol Meyers: Consultancy, Honoraria; Univ of AR for Medical Sciences: Employment; Celgene: Consultancy, Honoraria, Research Funding. Venstrom:Genentech: Employment. Punnoose:Genetech, Inc.: Employment.

Background: The 70-gene prognostic risk score (MyPRSR) for patients with multiple myeloma is conventionally used in a binary high/low risk fashion. The ability to more precisely estimate a patients' risk of 5-year relapse or death based on their specific risk score may increase the clinical utility of the assay. Methods and Results: Logistic regression analysis of the 70-gene score in relation to event free and overall survival data from UAMS TT2/3 series was performed. 274 patients with at least 5 years' follow-up data were included in the analysis. A binary fitted line plot, which fits a model with one continuous predictor with an iterative reweighted least squares algorithm to obtain maximum likelihood estimates of the parameters, was generated for 5-year relapse-free and overall-survival. These plots correspond to the probability of a certain event occurring based on a specific 70-gene score. The deviance R-square value for the relapse free survival analysis was 12.28% and the odds ratio for the 70-gene score as a continuous predictor was 1.03 (95% CI: 1.02 to 1.05). For overall survival the deviance R-square value was 15.5% and odds ratio 1.07 (95% CI: 1.05 to 1.10). Conclusion: The 70-gene prognostic risk score is continuously associated with increased risk of 5-year relapse and death. Presentation of a patients' risk score in this format may enable superior risk-based management compared to binary high/low risk stratification. Further work is ongoing to investigate the association between GEP70 and risk of progression from precursor conditions, such as MGUS, to MM requiring treatment. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures van Laar: Signal Genetics, Inc.: Employment. Bender:Signal Genetics, Inc.: Employment. Zielinski:Signal Genetics, Inc.: Employment. Leigh:Signal Genetics, Inc.: Employment. Barlogie:Mount Sinai Hospital: Employment. Morgan:Univ of AR for Medical Sciences: Employment; Bristol Meyers: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

Gene expression analysis is a valuable tool for determining the risk of disease recurrence and overall survival of an individual patient with breast cancer. The purpose of this study was to create and validate a robust prognostic algorithm and implement it within an online analysis environment. Genomic and clinical data from 477 clinically diverse patients with breast cancer were analyzed with Cox regression models to identify genes associated with outcome, independent of standard prognostic factors. Percentile-ranked expression data were used to train a "metagene" algorithm to stratify patients as having a high or low risk of recurrence. The classifier was applied to 1016 patients from five independent series. The 200-gene algorithm stratifies patients into risk groups with statistically and clinically significant differences in recurrence-free and overall survival. Multivariate analysis revealed the classifier to be the strongest predictor of outcome in each validation series. In untreated node-negative patients, 88% sensitivity and 44% specificity for 10-year recurrence-free survival was observed, with positive and negative predictive values of 32% and 92%, respectively. High-risk patients appear to significantly benefit from systemic adjuvant therapy. A 200-gene prognosis signature has been developed and validated using genomic and clinical data representing a range of breast cancer clinicopathological subtypes. It is a strong independent predictor of patient outcome and is available for research use.

Purpose Patients with adenocarcinoma of unknown primary origin (ACUP) constitute approximately 4% of all malignancies. For effective treatment of these patients, it is considered optimal to identify the primary tumor origins. Currently, the success rate of the diagnostic work-up is only 20% to 30%. Our goal was to evaluate the contribution of gene expression profiling for routine clinical practice in patients with ACUP. Patients and Methods Formalin-fixed, paraffin-embedded (FFPE) samples were obtained from 84 patients with a known primary adenocarcinoma and from 38 patients with ACUP. An extensive immunohistochemical panel classified 16 of the patients with ACUP, whereas 22 patients remained unclassified for their histogenetic origin. Information about staging procedures and clinical follow-up were available in all patient cases. The expression data were analyzed in relation to clinicopathologic variables and immunohistochemical results. Results The gene expression–based assay classified the primary site correctly in 70 (83%) of 84 patient cases of primary and metastatic tumors of known origin, with good sensitivity for the majority of the tumor classes and relatively poor sensitivity for primary lung adenocarcinoma. Gene expression profiling identified 15 (94%) of 16 patients with initial ACUP who were classified by immunohistochemistry, and it made a valuable contribution to a potential site of origin in 14 of the 22 patients with ACUP. Conclusion The gene expression platform can classify correctly from FFPE samples the majority of tumors classes both in patients with known primary and in patients with ACUP. Therefore, gene expression profiling represents an additional analytic approach to assist with the histogenetic diagnosis of patients with ACUP.

Background Molecular signatures that predict outcome in tamoxifen treated breast cancer patients have been identified. For the first time, we compared these response profiles in an independent cohort of (neo)adjuvant systemic treatment naive breast cancer patients treated with first-line tamoxifen for metastatic disease. Methods From a consecutive series of 246 estrogen receptor (ER) positive primary tumors, gene expression profiling was performed on available frozen tumors using 44K oligoarrays (n = 69). A 78-gene tamoxifen response profile (formerly consisting of 81 cDNA-clones), a 21-gene set (microarray-based Recurrence Score), as well as the HOXB13-IL17BR ratio (Two-Gene-Index, RT-PCR) were analyzed. Performance of signatures in relation to time to progression (TTP) was compared with standard immunohistochemical (IHC) markers: ER, progesterone receptor (PgR) and HER2. Results In univariate analyses, the 78-gene tamoxifen response profile, 21-gene set and HOXB13-IL17BR ratio were all significantly associated with TTP with hazard ratios of 2.2 (95% CI 1.3–3.7, P = 0.005), 2.3 (95% CI 1.3–4.0, P = 0.003) and 4.2 (95% CI 1.4–12.3, P = 0.009), respectively. The concordance among the three classifiers was relatively low, they classified only 45–61% of patients in the same category. In multivariate analyses, the association remained significant for the 78-gene profile and the 21-gene set after adjusting for ER and PgR. Conclusion The 78-gene tamoxifen response profile, the 21-gene set and the HOXB13-IL17BR ratio were all significantly associated with TTP in an independent patient series treated with tamoxifen. The addition of multigene assays to ER (IHC) improves the prediction of outcome in tamoxifen treated patients and deserves incorporation in future clinical studies.

As molecular profiling technologies have evolved, our understanding of multiple myeloma heterogeneity and the relative effectiveness of treatment options have increased dramatically. Most recently, next generation sequencing (NGS) studies have provided a new degree of molecular resolution into this disease, however it remains a challenge to translate these methodologies and insights from research tools to widely-available clinical assays which can be performed as part of routine patient care. MyPRS® is a clinically and scientifically validated high-throughput gene-expression (Affymetrix) based assay available in all 50 US states. The CLIA and CAP-accredited laboratory workflow is able to isolate sufficient RNA from small amounts of fresh bone marrow aspirate, up to 72 hours post collection[1]. In order to expand the content of the MyPRS assay to include DNA-sequencing based variant, copy number and mutation detection, we have validated highly-scalable methods for isolating RNA and DNA separately and in parallel from individual patient specimens of varying quality and quantity. Yet another challenge of translational NGS profiling is performing complex laboratory procedures, developed primarily for research use only, with the requisite reproducibility and accuracy required for submission to regulatory agencies and ultimately for clinical use. Coupled with the protocols we developed for isolation of both DNA and RNA from small amounts of patient bone marrow aspirate, we performed an investigation of the Illumina NextSeq 500 and "on-site" BaseSpace data processing server. With the multiplexing and parallel processing capability of this platform we estimate being able to sequence, align and variant-call up to 150 myeloma-relevant genes at 1000x coverage per run. Results from our MM cell-line-, normal human- and NIST reference-DNA whole-exome-profiling studies show extremely high levels of technical reproducibility and agreement with results generated from 3rd party laboratories. In addition, we describe associations between the (RNA-expression based) prognostic, molecular subtyping and virtual karyotyping currently included in the MyPRS assay, with results from DNA-based exome profiling, performed on matched specimens. We believe findings underscore the need for comprehensive DNA and RNA based molecular profiling in order to make the most informed patient management decisions. 1. van Laar R, Flinchum R, Brown N, Ramsey J, Riccitelli S, Heuck C, Barlogie B, Shaughnessy Jr J: Translating a gene expression signature for multiple myeloma prognosis into a robust high-throughput assay for clinical use. BMC Medical Genomics 2014, 7 (1):25. Disclosures Zielinska: Signal Genetics: Employment. Leigh:Signal Genetics: Employment. Gomez:Signal Genetics: Employment. Van Laar:Signal Genetics: Employment.

Exosome-mediated processes are increasingly being implicated in the pathobiology of many forms of solid tumors and hematologic malignancies. In the case of blood cancers, an oncogenic role for exosomes has been demonstrated for multiple myeloma (MM). An increased understanding of the abundance and disease association of extra-cellular microRNAs in particular, may lead to opportinities to improve early detection and management of MM and precursor conditions. We performed microRNA profiling of cell-free bone marrow aspirate plasma on a series of 100 patients with diagnoses of MGUS, active multiple myeloma or relapsed multiple myeloma. The microRNA profiles were compared between disease status groups and also individually with each patient’s routine MyPRS results (ie. GEP70 high/low risk and molecular subtype gene signatures), generated from their malignant CD138+ plasma cells1. MicroRNAs with patterns of expression associated with these clinically validated genomic (mRNA) signatures were investigated to determine if they (i) were known regulators of the genes used in MyPRS and (ii) in a cross-validated analysis, were able to predict the patients MyPRS risk group and molecular subtype. An additional series of paired peripheral blood and bone marrow aspirates (isolated CD138+ plasma cells) were also microRNA and MyPRS profiled, to further investigate the role and potential clinical utility of extracellular microRNAs in multiple myeloma. Results will be presented which describe the abundance of individual microRNA's in realtion to disease status, including microRNA's previously linked to the regulation of mRNA's contained in the GEP70 signature. The ability to predict MGUS progression risk or active myeloma prognosis using molecular signatures in peripheral blood may increase access to, and adoption of, genomic technologies in the diagnosis and management of these related conditions. Reference: [1] van Laar R, Flinchum R, Brown N, et al. Translating a gene expression signature for multiple myeloma prognosis into a robust high-throughput assay for clinical use. BMC Medical Genomics. 2014;7(1):25. Disclosures Van Laar: Signal Genetics: Employment, Equity Ownership. Flinchum:Signal Genetics: Employment. Nathan:Signal Genetics: Employment. Ramsey:Signal Genetics: Employment. Shaughnessy:Signal Genetics: Consultancy.

Background: Diagnostic and therapeutic advances have significantly improved the outcomes for multiple myeloma (MM) patients. However, pts who are refractory to or relapse after therapy with immune modulatory drugs and proteasome inhibitors remain a therapeutic challenge. Comprehensive genomic profiling via clinical next generation sequencing (NGS)-based assays studies of MM cases have revealed multiple targetable mutations that were previously unexploited in MM. Methods: Between June 2013 and May 2014 we performed genomic profiling of 351 patients who had progressed after initial therapy to assist physicians in therapy planning. Comprehensive genomic profiling was performed using the FoundationOne¨ or FoundationOne Heme¨ assays. FoundationOne assays 374 cancer-related and 24 frequently rearranged genes via DNA-seq, and FoundationOneHeme assays 405 cancer-related and 31 frequently rearranged genes via DNA-seq as well as 265 frequently rearranged genes by RNA-seq. All samples were sequenced in a CLIA-certified CAP-accredited laboratory to an average depth >500x . Patients with activating alterations of KRAS, NRAS or BRAF were considered for therapy with the targeted agent trametinib (TMTB) as were patients who had a gene expression signature suggesting activation of the MAPK pathway. Retrospective review of this case series was approved by the UAMS institutional review board. Results: We identified 63 patients who underwent treatment with Trametinib. 60 were treated based on activating mutations of KRAS, NRAS or BRAF and 3 were treated based on a GEP signature. The median age was 65 and patients had a median of 5 lines of prior therapy (range 1-20). 38 of 63 patients had prior treatment with Total Therapy. 43 underwent salvage with chemotherapy prior to initiation of TMTB, 15 had salvage transplants, 33 patients were exposed to novel agents (Pomalidomide, Carfilzomib) and 33 had Metronomic therapy before TMTB. 25% of patients were ISS stage 3 and 37% had GEP70 defined high risk. 13 had PET defined extra medullary disease (EMD). 41 patients were administered TMTB monotherapy and 22 received TMTB treatment in combination with other agents. In general the treatment was well tolerated. 10 patients discontinued therapy because of toxicities, 29 discontinued because of disease progression or death. None of the deaths were attributed to TMTB, Best treatment responses were SD in 30, PR in 8, VGPR in 2 and CR in 3 of the 63 pts. For 25 patients with evaluable PET data, treatment resulted in complete resolution of FDG avid lesions in 9 patients and a better than 50% reduction in 15 (Figure 1). We will present updated data on clinical responses as well as toxicities. Conclusions: Treatment with targeted therapy guided by prospective comprehensive genomic profiling across all classes of genomic alterations in this heavily pretreated population of MM patients resulted in an unexpectedly high objective response rate. Observation of CR with TMTB monotherapy further supports continued investigation of this individualized approach to MM management. Disclosures Van Laar: Signal Genetics: Employment, Equity Ownership. Ali:Foundation Medicine, Inc.: Employment, Equity Ownership. Miller:Foundation Medicine, Inc: Employment. Zangari:Norvartis: Membership on an entity's Board of Directors or advisory committees; Onyx: Research Funding; Millennium: Research Funding. van Rhee:Millenium: Speakers Bureau; Sanofi: Speakers Bureau; Celgene: Speakers Bureau; Janssen: Speakers Bureau. Morgan:Celgene Corp: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Myeloma UK: Membership on an entity's Board of Directors or advisory committees; International Myeloma Foundation: Membership on an entity's Board of Directors or advisory committees; The Binding Site: Membership on an entity's Board of Directors or advisory committees; MMRF: Membership on an entity's Board of Directors or advisory committees.

Heart disease and related sequelae are a leading cause of death and healthcare expenditure throughout the world. Although many patients opt for surgical interventions, lifestyle modification programs focusing on nutrition and exercise have shown substantial health benefits and are becoming increasing popular. We conducted a year-long lifestyle modification program to mediate cardiovascular risk through traditional risk factors and to investigate how molecular changes, if present, may contribute to long-term risk reduction. Here we describe the lifestyle intervention, including clinical and molecular data collected, and provide details of the experimental methods and quality control parameters for the gene expression data generated from participants and non-intervention controls. Our findings suggest successful and sustained modulation of gene expression through healthy lifestyle changes may have beneficial effects on vascular health that cannot be discerned from traditional risk factor profiles. The data are deposited in the Gene Expression Omnibus, series GSE46097 and GSE66175.