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Importance Non-invasive molecular biomarkers are needed to improve the early, accurate and precise diagnosis of invasive cutaneous melanoma. Objective To independently validate a previously-identified circulating microRNA signature of melanoma (MEL38). Secondly, to develop of a complementary microRNA signature, optimized for prognostication. Design, Setting & Participants MicroRNA expression profiling was performed on plasma samples from a multi-centre observational case-control study, involving patients with primary or metastatic melanoma, melanoma in-situ, non-melanoma skin cancer, or benign nevi. MicroRNA profiles from patients with length of survival, treatment and sentinel node biopsy data were used to develop the prognostic signature. Main Outcomes and Measures The primary outcome of interest for MEL38 was its association with melanoma status, including area under the curve, binary diagnostic sensitivity and specificity, and incidence-adjusted positive and negative predictive values. The prognostic signature was assessed using rates of survival per risk group and relationship to conventional predictors of outcome. Results Circulating microRNA profiles of 372 invasive melanoma patients and 210 control individuals were generated. The average age of all participants was 59, 49% were male. A MEL38 score >5.5 indicated the presence of invasive melanoma. Overall 551/582 (95%) of patients were correctly diagnosed, with 93% sensitivity and 98% specificity. MEL38 score range from 0 to 10 with an area under the curve of 0.98 (95% CI 0.97 to 1.0, P A novel prognostic 12-microRNA signature (MEL12) developed from 232 patients identified low, standard, or high-risk groups, with 94%, 78% and 58% rates of 10-year survival respectively (Log rank P Conclusion and Relevance The circulating MEL38 signature may assist in diagnosing patients with invasive melanoma versus other conditions associated with a lower – or negligible - risk of mortality. A complementary and prognostic MEL12 signature is predictive of SLNB status, clinical stage, and probability of survival. Plasma microRNA profiling may help optimise existing diagnostic pathways as well as enable personalised, risk-informed melanoma treatment decisions.

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: Rates of melanoma diagnoses have increased dramatically over the past 40 years, without the proportionate decrease in mortality observed in other common cancer types. Factors that make the early and accurate diagnosis of invasive cutaneous melanoma (ICM) challenging include (i) the large number of potential locations and small size of pigmented lesions, (ii) inherent subjectivity in visual diagnostic examinations, and (iii) a lack of objective molecular biomarkers. A 38-microRNA expression signature of melanoma (MEL38) was previously identified in a plasma-based pilot study and independent validated in multiple series of solid tissue biopsies. Patients & Methods: Using digital microRNA expression profiling, the diagnostic and prognostic performance of MEL38 was assessed using prospectively-collected or archival plasma from 582 patients. Criteria for inclusion was histologically confirmed ICM (n=372), or other conditions including nevi, melanoma in-situ (MIS) and non-melanoma skin cancer (n=210). A second microRNA profile was also developed, optimised to predict a patient's probability of 10-year melanoma-specific survival (MSS). Results: The MEL38 score correctly identified the ICM status of 551/582 (95%) plasma microRNA profiles, with an area under the curve of 0.98 (P5.5 (range 1 to 10) resulted an ICM detection sensitivity of 93% and specificity of 98%. Multivariate analysis indicated the MEL38 score is significantly different between ICM vs other disease states, independent of patient age, gender, biopsy site or plasma type (fresh vs archival) at P An optimised 12-microRNA signature (MEL12) specifically for melanoma prognosis was developed to compliment the diagnostic ability of MEL38. Rates of MSS between low, standard and high-risk MEL12 groups were 94%, 78% and 58% respectively (Log rank P Conclusion: In a large series of clinically annotated plasma samples, the MEL38 signature was able to accurately stratify patients with ICM from those with non-ICM conditions associated with negligible or dramatically lower risk of mortality. In patients clinically or genomically-diagnosed with ICM, the MEL12 signature can provide a prognostic assessment, significantly related to SLNB status, clinical stage, and probability of 10-year MSS. Adoption of plasma microRNA profiling in the clinic may facilitate personalised, risk-informed treatment decisions, and potentially reducing the rates of melanoma under and over diagnosis. Citation Format: Ryan Van Laar, Babak Latif, Sam King, Christopher Love, Nadine Taubenheim, Esha Kalanooriya, Wandi Wang, Mirette Saad, Ingrid Winship, Tony Landgren. Clinical validation of a liquid biopsy microRNA assay for diagnosis and risk stratification of invasive cutaneous melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB296.

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 0.97 (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.

Epitopes involved in a protective immune response to Hendra virus (HeV) (Henipavirus, Paramxyoviridae) were investigated by generating five neutralizing monoclonal antibodies (mAbs) to the virus attachment protein (G) of HeV (HeV G) and sequencing of the G gene of groups of neutralization-escape variants selected with each mAb. Amino acid substitutions occurred at eight distinct sites on HeV G. Relationships between these sites were investigated in binding and neutralization assays using heterologous combinations of variants and mAbs. The sites were also mapped to a proposed structural model for the attachment proteins of Paramyxoviridae. Their specific locations and the nature of their interactions with the mAb panel provided the first functional evidence that HeV G in fact resembled the proposed structure. Four sites (aa 183–185, 417, 447 and 570) contributed to a major discontinuous epitope, on the base of the globular head, that was similar to immunodominant virus neutralization sites found in other paramyxoviruses. Amino acid similarity between HeV and Nipah virus was relatively highly conserved at these sites but decreased significantly at the other sites identified in this study. These included another discontinuous epitope on the base of the head region defined by sites aa 289 and 324 and well separated epitopes on the top of the head at sites aa 191–195 and 385–356. The latter epitope corresponded to immunodominant neutralization sites found in Rinderpest virus and Measles virus.

Gene expression profiling offers a promising new technique for the diagnosis and prognosis of cancer. We have applied this technology to build a clinically robust site of origin classifier with the ultimate aim of applying it to determine the origin of cancer of unknown primary (CUP). A single cDNA microarray platform was used to profile 229 primary and metastatic tumors representing 14 tumor types and multiple histologic subtypes. This data set was subsequently used for training and validation of a support vector machine (SVM) classifier, demonstrating 89% accuracy using a 13-class model. Further, we show the translation of a five-class classifier to a quantitative PCR–based platform. Selecting 79 optimal gene markers, we generated a quantitative-PCR low-density array, allowing the assay of both fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissue. Data generated using both quantitative PCR and microarray were subsequently used to train and validate a cross-platform SVM model with high prediction accuracy. Finally, we applied our SVM classifiers to 13 cases of CUP. We show that the microarray SVM classifier was capable of making high confidence predictions in 11 of 13 cases. These predictions were supported by comprehensive review of the patients' clinical histories.

Histone deacetylase inhibitors (HDACis) inhibit tumor cell growth and survival, possibly through their ability to regulate the expression of specific proliferative and/or apoptotic genes. However, the HDACi-regulated genes necessary and/or sufficient for their biological effects remain undefined. We demonstrate that the HDACis suberoylanilide hydroxamic acid (SAHA) and depsipeptide regulate a highly overlapping gene set with at least 22% of genes showing altered expression over a 16-h culture period. SAHA and depsipeptide coordinately regulated the expression of several genes within distinct apoptosis and cell cycle pathways. Multiple genes within the Myc, type β TGF, cyclin/cyclin-dependent kinase, TNF, Bcl-2, and caspase pathways were regulated in a manner that favored induction of apoptosis and decreased cellular proliferation. APAF - 1 , a gene central to the intrinsic apoptotic pathway, was induced by SAHA and depsipeptide and shown to be important, but not essential, for HDACi-induced cell death. Overexpression of p16 INK4A and arrest of cells in G 1 can suppress HDACi-mediated apoptosis. Although p16 INK4A did not affect the genome-wide transcription changes mediated by SAHA, a small number of apoptotic genes, including BCLXL and B - MYB , were differentially regulated in a manner consistent with attenuated HDACi-mediated apoptosis in arrested cells. We demonstrate that different HDACi alter transcription of a large and common set of genes that control diverse molecular pathways important for cell survival and proliferation. The ability of HDACi to target multiple apoptotic and cell proliferation pathways may provide a competitive advantage over other chemotherapeutic agents because suppression/loss of a single pathway may not confer resistance to these agents.

Microarray technology has undergone a rapid evolution. With widespread interest in large-scale genomic research, an abundance of equipment and reagents have now become available and affordable to a large cross section of the scientific community. As protocols become more refined, careful investigators are able to obtain good quality microarray data quickly. In most recent times, however, perhaps one of the biggest obstacles researchers face is not the manufacture and use of microarrays at the bench, but storage and analysis of the array data. This review discusses the most recent equipment, reagents and protocols available to the researcher, as well as describing data analysis and storage options available from the evolving field of microarray informatics.

Venetoclax (VEN) is being evaluated in relapsed/refractory multiple myeloma (R/R MM) patients as a single agent (NCT01794520). Improved objective response rates were observed in t(11;14) patients (40% in t(11;14)+ vs 6% in t(11;14)-), which were shown to associate with a favorable BCL-2 family expression profile (high BCL2:BCL2L1 (BCL-XL). Forty percent of t(11;14)+ population exhibited VEN favorable biomarker profile with an 88% ORR compared to 20% in t(11;14)+ patients with unfavorable profile. Thus, a favorable BCL-2 family expression profile may identify certain MM subgroups with increased sensitivity to the anti-tumor activity of VEN as a single agent. To better understand and identify the patient populations that may benefit from VEN, we retrospectively analyzed the prevalence of a favorable BCL-2 family expression profile in t(11;14)+ and other MM molecular subtypes in two published cohorts (GSE4581 and GSE9782). Our results showed that BCL2 expression varied significantly across molecular and cytogenetic subgroups. The t(11;14)+ subgroup expressed high BCL2 and the lowest BCL2L1 and MCL1 in both newly diagnosed (NDMM) and R/R MM patients. Correspondingly, the t(11;14) MM was enriched for the highest ratios of BCL2/MCL1 and BCL2/BCL2L1, further supporting the single agent VEN activity observed in this patient population. Based on prevalence study in cohort GSE9782, we observed 40% of t(11;14)+ R/R MM patients exhibited a favorable BCL-2 family expression profile, using clinical defined cutoffs, thus highly consistent with the VEN single agent trial. Furthermore, this favorable profile existed in other molecular subtypes, especially the ones that harbor abnormal MAF (23%) and D3 (37.5%) translocations, as well as dysregulated expression of cyclinD1 (21.2%)/D1+D2 (26.7%). The molecular subgroup with overexpression of cyclin D2 had the lowest prevalence of the favorable profile (7.5%). In the NDMM cohort, overall 27% patients had favorable profile. More specifically, the t(11;14) patients had the highest (61%) and D2 patients had the lowest (13%) prevalence of a favorable BCL-2 family profile. Collectively, our data suggests that MM subgroups are associated with distinct BCL-2 family expression profiles, and that the t(11;14) subgroup is particularly suited for single agent VEN treatment as indicated by the high prevalence of a favorable BCL-2 family expression profile. In addition, we further identified patients in the non t(11;14) MM subgroups with a favorable BCL-2 family expression profile that may also potentially benefit from VEN monotherapy. Citation Format: Jenny Wu, Caleb Stein, Jeremy A. Ross, Franklin Peale, John D. Shaughnessy, Ryan Van Laar, Gareth Morgan, Jeffrey M. Venstrom, Elizabeth A. Punnoose, Yanwen Yanwen Jiang. BCL-2 family expression profiling may identify distinct molecular subtypes of multiple myeloma with increased susceptibility to single agent Venetoclax [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2772. doi:10.1158/1538-7445.AM2017-2772

To examine relationships between weight loss through changes in lifestyle and peripheral blood gene expression profiles.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.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-value0.05 and fold-change ≥1.4). Altered molecular pathways were related to immune function and inflammatory responses involving endothelial activation. In contrast, participants losing minimal weight (-3.1 ± 2.5%, n = 32) showed only minor changes in cardiovascular risk factors and markers of inflammation and no changes in gene expression compared to non intervention controls after 1 year.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.

Background— Healthy lifestyle changes are thought to mediate cardiovascular disease risk through pathways affecting endothelial function and progression of atherosclerosis; however, the extent, persistence, and clinical significance of molecular change during lifestyle modification are not well known. We examined the effect of a rigorous cardiovascular disease risk reduction program on peripheral blood gene expression profiles in 63 participants and 63 matched controls to characterize molecular responses and identify regulatory pathways important to cardiovascular health. Methods and Results— Dramatic changes in dietary fat intake (−61%; P P P Conclusions— Successful and sustained modulation of gene expression through lifestyle changes may have beneficial effects on the vascular system not apparent from traditional risk factors. Healthy lifestyles may restore homeostasis to the leukocyte transcriptome by downregulating lactoferrin and other genes important in the pathogenesis of atherosclerosis. Clinical Trial Registration— URL: www.clinicaltrials.gov . Unique identifier: NCT01805492

Long thought to function only as an inert energy storage depot, the role of adipose tissue in breast tumorigenesis has been largely ignored. In light of increasing rates of obesity and use of breast conserving therapy and autologous fat grafting, improved understanding of the role of adipose tissue in tumor etiology is crucial. Thus, adipose tissue adjacent to and distant from invasive breast tumors (n = 20), or adjacent to non-malignant diagnoses (n = 20) was laser microdissected from post-menopausal women. Gene expression data were generated using microarrays and data analyzed to identify significant patterns of differential expression between adipose tissue groups at the individual gene and molecular pathway level. Pathway analysis revealed significant differences in immune response between non-malignant, distant, and tumor-adjacent adipose tissue, with the highest response in tumor-adjacent and lowest in non-malignant adipose tissue. Adipose tissue from invasive breasts exhibits increased expression of anti-inflammatory genes such as MARCO and VSIG4 while genes differentially expressed between tumor-adjacent and distant adipose tissue such as SPP1, RRM2, and MMP9, are associated with increased cellular proliferation, invasion, and angiogenesis. These data suggest that molecular profiles of adipose tissue differ depending on presence of or proximity to tumor cells. Heightened immunotolerance in adipose tissue from invasive breasts provides a microenvironment favorable to tumorigenesis. In addition, tumor-adjacent adipose tissue demonstrates expression of genes associated with tumor growth and progression. Thus, adipose tissue is not an inert component of the breast microenvironment but plays an active role in tumorigenesis.

In the current study we sought to determine whether mutation burden (MB) is reflected in gene expression patterns. We generated 389 gene expression profiles and 311 mutation profiles from 182 cases, split into a training set of 97 and test set of 84. Copy number variants (CNV), rearrangements (TX) and short variant mutations (SV) were identified with FoundationOne Heme (F1) and U133Plus2.0 (u133) gene expression data, GEP70 and GEP80 risk scores, subgroup and CNV calls provided by Signal Genetics. 145 Kegg pathways, transcription factor binding sites (TFbs) for 195 TF mapped to u133 genes and 1161 F1 features and u133 GEP signatures/scores were evaluated for enrichment of defined genes. u133 data for normal plasma cells (n=22), MGUS (n=44), smoldering MM (n=12), relapsed MM (n=76), and MM cell lines (n=42) were derived from GSE31162. Newly diagnosed MM samples came from GSE31162 (n=584), GSE19784 (n=321), GSE15695 (n=247) and E-MTAB-317 (n=233). Of 593 genes assayed by F1, 293 were mutated at least twice. There were a total of 3454 mutations (average = 11, minimum = 3, and maximum = 37). KRAS was mutated in 40 tumors, while TP53 was mutated 45 times in 31 tumors. TP53 and 62 other genes had 2 or more unique mutations in a single tumor. A linear curve of MB exhibited a sharp upward inflection at 19 mutations. We sought to determine if GEP could identify characteristic features of MM flanking the inflection point. A training set of 97 (86 = 21 MB) and a test set of 84 (49 15 but < 21 MB and 7 >= 21MB) was produced. A mean ratio identified 576 genes exhibiting 2-fold higher expression in MM with high MB (hiMB) and 1617 genes from low MB (loMB). Notably, forty-four of the 293 mutated genes were in this list of genes. A geometric mean ratio of the two gene sets was then calculated for all samples. The mean of the resulting score (MB.2) was higher in MM with hiMB (1.66) than MM with loMB (-0.235) in the training set. MM with hiMB (0.329) had a higher MB.2 score than the group with intermediate MB.2 (0.158) and both higher than MM with loMB (-0.122). MB.2 was lowest in normal PC (-0.518) and progressively increased with disease progression: MGUS (-0.341), SMM (-0.308), MM (0.199), relapsed MM (0.334), MM cell lines (1.168).[SP1] 57% of the 182 cases harbored only SV mutations, 32% had SV and CNV, 32% SV and TX and 7% had SV, CNV and TX mutations. SV only mutations were present in 76% of MB.2 quartile 1 (MBq1) and 30% of MBq4. SV, CNV and TX mutations were present in 4% of MBq1 and 17% of MBq4. MB.2 was positively correlated with GEP70, GEP80, proliferation index, and TP53 target genes in MM and genes modulated by thalidomide and dexamethasone in PGx studies, in at least 6 of the 7 cohorts studied. The CD2 subtype, a myeloid classification and GEP70 low risk were significantly overrepresented in both MBq1 and GEP70q1 in all 7 cohorts. Conversely, the MF, MS, and PR subtypes, GEP70 and GEP80 high risk, as well as +1q, amp1q21, and del13q were significantly overrepresented in MBq4 and GEP70q4 in all 7 cohorts. MB.2 [SP2] genes derived from MM with loMB where enriched in 45 of 148 Kegg pathways. Notable were Hedgehog, Prostaglandin, Tx factors in cancer, HOX, MYB signaling, ephrin-B reverse signaling and embryonic stem cells. Five pathways related to B-cell biology were enriched. Mitotic cell cycle, integrin signaling, chromatin acetylation, ubiquitin ligation, and G1 to G1/S were underrepresented. MB.2 genes from MM with hiMB were enriched in TP53, lipid lysis, complement cascade, adherens junctions, Wnt regulation of CYR61, cyclins, prostaglandins, cell cycle, and MYC target pathways. Interferon signaling, TNF-NF-kB, EGFR, NOD, endoplasmic reticulum, ubiquitin ligation, Wnt-Hedgehog-NOTCH and BMP-SMAD modules were underrepresented. An enrichment of Rel and NF-kB TFbs was observed for genes negatively correlated with MB.2. and genes positively correlated with MB.2 and GEP70 were enriched for E2F and TP53 binding site. In conclusion, we show that MB can be captured by GEP in MM, that MB increases with disease progression, and pathways enriched by hiMB and loMB are different and may imply differences in pathogenesis as well as treatment. [SP1]This is an important finding - suggest emphasizing more [SP2]Starting with this para suggest referring to groups are low vs high mutation burden for improved readability. Disclosures Shaughnessy: Signal Genetics: Consultancy, Patents & Royalties. Cho:Genentech Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Agenus, Inc.: Research Funding; Janssen: Consultancy, Research Funding; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Ludwig Institute for Cancer Research: Membership on an entity's Board of Directors or advisory committees. Chari:Novartis: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Array Biopharma: Consultancy, Research Funding; Amgen Inc.: Honoraria, Research Funding; Pharmacyclics: Research Funding. van Laar:Signal Genetics, Inc.: Employment. Jagannath:Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol Myer Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees. Barlogie:Signal Genetics: Patents & Royalties.

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: Small-RNAs (including microRNAs) are a novel class of molecules with functions that include the regulation of coding genes as well as development, proliferation, apoptosis and differentiation of myeloma cells. The presence of these genes has been detected inside cells and also in the extracellular environment, suggesting they may be useful for risk stratification and treatment monitoring. We sought to explore the small-RNA profiles of bone marrow specimens submitted for MyPRS analysis and identify candidate molecules associated with a patient's 70-gene (mRNA) prognostic risk score. Method and Results: 32 bone marrow aspirate samples from patients with multiple myeloma, 3 whole-blood control samples and the MM cell line NCI-H929 were included in the present study. Plasma cells were isolated from the bone marrow aspirates as per standard MyPRS protocols. Total RNA was then extracted using the miRNeasy Mini Kit protocol (Qiagen, Canada). All miRNA libraries were prepared using the Illumina TruSeq Small RNA protocol following the manufacturer's instructions with 11-15 cycles of PCR amplification. Individual libraries were prepared using a unique index primer to allow for pooling of multiple samples. After amplification, Novex TBE PAGE gel electrophoresis was used to select for fragments sized 145- 160 nt, corresponding to mature miRNA's and other small RNA molecules. Libraries were validated and quantified using an Agilent 2100 Bioanalyzer High Sensitivity DNA chip, sequenced on an Illumina NextSeq 500 and analyzed using Illumina BaseSpace Onsite. After adapter trimming, an average of 3.7, 17.7 and 0.5 million reads were generated from the multiple myeloma, normal blood and NCI-H929 cell line libraries, respectively. When comparing the MM vs. control data, 757/6041 total miRNA's passed a low-count filter and 535 of these were found to be differentially expressed. The top 10 miRNA families with the largest difference between sample types according to DESEq2 were mir-1285, let-7, mir-1248, mir-1303, mir-1260b, mir-1301, mir-10, mir-128, mir-129 and mir-130. Within the MM sample group, 620 individual miRNAs were reliably detected and compared between GEP70 high and low risk disease, with 14 passing a differential expression filter. Hierarchal clustering of patients using all 620 genes did not separate patients into high and low risk groups and only 2/411 miRNA families (mir-130 and mir-17) were found to differ between these classes. Serum levels of miR-130a in MM patients have been shown to be associated with extramedullary disease and miR-17 is thought to regulate the Myc oncogene. Conclusion: In this study we identified a number of novel microRNAs with patterns of expression in patient bone marrow aspirates associated with the extensively validated 70-gene risk score available commercially as 'MyPRS'. Two particular miRNA's were identified that appear to be associated with high risk behavior, one of which correlates with the Myc oncogene whose relationship to clinically aggressive MM is well described. Further work is planned to expand the number of patients in the study and to investigate whether these microRNA's are present in the extracellular bone marrow environment and peripheral fluids. Disclosures van Laar: Signal Genetics, Inc.: Employment. Leigh:Signal Genetics, Inc.: Employment. Zielinski: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.

Background Improved methods are needed for predicting prognosis and the benefit of delivering adjuvant chemotherapy (ACT) in patients with non-small-cell lung cancer (NSCLC). Methods A novel prognostic algorithm was identified using genomic profiles from 332 stage I-III adenocarcinomas and independently validated on a separate series of 264 patients with stage I-II tumors, compiled from five previous studies. The prognostic algorithm was used to interrogate genomic data from a series of patients treated with adjuvant chemotherapy. Those genes associated with outcome in the adjuvant treatment setting, independent to prognosis were used to train an algorithm able to classify a patient as either a responder or non-responder to ACT. The performance of this signature was independently validated on a separate series of genomic profiles from patients enrolled in a randomized controlled trial of cisplatin/vinorelbine vs. observation alone (JBR.10). Results NSCLC patients exhibiting the high-risk, poor-prognosis form of the 160-gene prognosis signature experienced a 2.80-times higher rate of 5-year disease specific death (log rank P Separately, NSCLC patients with the 37-gene ACT-response signature (n = 70, 64 %), benefited significantly from cisplatin/vinorelbine (adjusted HR: 0.23, P = 0.0032). For those patients predicted to be responders, receiving this form of ACT conferred a 25 % improvement in the probability of 5-year-survival, compared to observation alone and adjusted for covariates. Conversely, in those patients predicted to be non-responders, ACT was observed to offer no significant survival benefit (adjusted HR: 0.55, P = 0.32). The two gene signatures overlap by one gene only SPSB3, which interacts with the oncogene MET. In this study, higher levels of SPSB3 which were associated with favorable prognosis and benefit from ACT. Conclusions These complimentary prognostic and predictive gene signatures may assist physicians in their management and treatment of patients with early stage lung cancer.

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.

PurposeDespite the generally favorable clinical course in follicular lymphoma (FL), a minority of patients have a poor prognosis—with death within 3 years of diagnosis—most often due to transformation to aggressive disease.Patients and MethodsIn this study, we analyzed the potential of predicting early transformation on the basis of gene expression and immunologic parameters in FL biopsy samples taken at diagnosis.ResultsAt the gene-expression level, FL is a highly uniform disease at the time of diagnosis, precluding the detection of sufficiently validated prognostic gene-expression profiles suitable for a clinical setting. Combinations of differentially expressed genes indicate that immunologic mechanisms play a differential role in the risk of early transformation. Using immunohistochemistry for specific cell populations, the spatial distribution to neoplastic follicles and the activation of CD4–positive T-helper cells (P = .002) and specifically T-helper 1 (P = .004) were shown to be highly discriminatory to predict early transformation. A role for functional modulation of follicular dendritic cells could also be supported (P = .04). Other cell populations, including CD68-positive macrophages and regulatory T cells, were not differentially present.ConclusionThese results support the identification of FL as an immunologically functional disease in which an interaction of the tumor cells and the functional composition of the microenvironment determines the clinical behavior.

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.

Background Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or "filtered" from further analysis to avoid misleading results. Results In this article, a graduated approach to array quality is considered based on empirical reproducibility of the gene expression measures from replicate arrays. Weights are assigned to each microarray by fitting a heteroscedastic linear model with shared array variance terms. A novel gene-by-gene update algorithm is used to efficiently estimate the array variances. The inverse variances are used as weights in the linear model analysis to identify differentially expressed genes. The method successfully assigns lower weights to less reproducible arrays from different experiments. Down-weighting the observations from suspect arrays increases the power to detect differential expression. In smaller experiments, this approach outperforms the usual method of filtering the data. The method is available in the limma software package which is implemented in the R software environment. Conclusion This method complements existing normalisation and spot quality procedures, and allows poorer quality arrays, which would otherwise be discarded, to be included in an analysis. It is applicable to microarray data from experiments with some level of replication.

Background: Long thought to function only as an inert energy storage depot, the role of adipose tissue in breast tumorigenesis has been largely ignored. In light of increasing rates of obesity and use of breast conserving therapy and autologous fat grafting, improved understanding of the role of adipose in tumor etiology is crucial. Methods: Adipose adjacent to and distant from invasive breast tumors (n=20), or adjacent to non-malignant diagnoses (n=20) was laser microdissected from post-menopausal women. Gene expression data were generated using microarrays and data analyzed to identify significant patterns of differential expression between adipose groups, at the individual gene and molecular pathway level. Results: Pathway analysis revealed significant differences in immune response between non-malignant, distant and tumor adjacent adipose, with the highest response in tumor-adjacent and lowest in non-malignant adipose. Adipose from invasive breasts exhibits increased expression in anti-inflammatory genes, such as MARCO and VSIG4, while genes differentially expressed between tumor-adjacent and distant adipose such as SPP1, RRM2 and MMP9, are associated with increased cellular proliferation, invasion, and angiogenesis. Conclusions: Gene expression levels differ in breast adipose, depending on presence of or proximity to tumor cells. Heightened immunotolerance in adipose from invasive breasts provides a microenvironment favorable to tumorigenesis. In addition, tumor-adjacent adipose demonstrates expression of genes associated with tumor growth and progression. Together, these data suggest that adipose is not an inert component of the breast microenvironment but plays an active role in tumorigenesis. Citation Format: William C. Yarina, Lori A. Field, Brenda Deyarmin, Ryan van Laar, Jeffrey A. Hooke, Craig D. Shriver, Rachel E. Ellsworth. Molecular characterization of breast tumor-associated adipose. [abstract]. In: Abstracts: AACR Special Conference on Cellular Heterogeneity in the Tumor Microenvironment; 2014 Feb 26-Mar 1; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(1 Suppl):Abstract nr B49. doi:10.1158/1538-7445.CHTME14-B49

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.

Background: Research over the past decade has shown the importance of the stroma in tumorigenesis, however, having long been thought to function only as an inert energy storage depot, the role of adipose tissue in tumor etiology has been largely ignored. Improved understanding of the role of adipose in tumor development and progression is crucial given the increasing rates of obesity and the use of autologous fat transfer in breast reconstruction. Methods: Adipose, adjacent to and distant from invasive breast tumors, was laser microdissected from 20 post-menopausal women, and from 20 post-menopausal women with non-malignant breast disease. Gene expression data were generated using U133 2.0 microarrays. After quality control and visualization steps, the data were analyzed to identify significant patterns of differential expression between adipose classes, at the individual gene and molecular pathway level. A subset of genes were further analyzed by qRT-PCR in out-of-sample adipose specimens. Results: Pathway analysis revealed significant differences in immune response between non-malignant, distant and tumor adjacent adipose. 141 genes were differentially expressed (FDR 2-fold difference) between tumor-adjacent and non-malignant breasts including FCGR2A, FOLR2, LGMN and NLRP3. These four genes were also differentially expressed (FDR 2-fold difference) between distant and non-malignant adipose. Within invasive breasts, no genes were differentially expressed using FDR 3-fold higher levels (P Conclusions: Gene expression levels differ in breast adipose, depending on presence of or proximity to tumor cells. Tumor-adjacent and distant adipose from invasive breasts both exhibit increased expression in genes involved in the M2 anti-inflammatory response, suggesting that the microenvironment in an invasive breast has a decreased immune response compared to the non-malignant microenvironment. Genes expressed at higher levels in tumor-adjacent compared to distant adipose are associated with increased cellular proliferation, invasion, migration, angiogenesis and metastasis, suggesting that tumor-adjacent adipose promotes the growth and progression of the tumor. Together, these data suggest that adipose is not an inert component of the breast microenvironment but plays an active role in tumorigenesis. Citation Format: Lori Field, Brenda Deyarmin, Ryan van Laar, Craig Shriver, Rachel Ellsworth. Identification of gene expression profiles associated with different types of breast adipose and their relationship to tumorigenesis. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr A105.

Background: Research over the past decade has shown the importance of the stroma in tumorigenesis, however, having long been thought to function only as an inert energy storage depot, the role of adipose tissue in tumorigenesis has been largely ignored. Improved understanding of the role of adipose in tumorigenesis is crucial given the increasing rates of obesity and the use of autologous fat transfer in breast reconstruction. Methods: Adipose, adjacent to and distant from invasive breast tumors, was laser microdissected from 20 post-menopausal women, and from 20 post-menopausal women with non-malignant breast disease. Gene expression data were generated using U133 2.0 microarrays. After quality control and visualization steps, the data were analyzed to identify significant patterns of differential expression between adipose classes, at the individual gene and molecular pathway level. Results: Pathway analysis revealed that immune response differs between non-malignant, distant and tumor adjacent adipose; this response is seen as a gradient with the largest response closest to the tumor. Gene expression differed significantly in adipose from invasive compared to non-malignant breasts with FCGR2A, FOLR2, LGMN, MARCO and NLRP3 expressed at significantly higher levels and HLA-DQB1 and HLA-DQA1 at significantly lower levels in adipose from invasive breasts. Within the invasive breasts, MMP9, PLA2G7, RRM2 and SPP1 were expressed at >3-fold higher levels in adjacent compared to distant adipose. Conclusions: Gene expression levels differ in breast adipose, depending on presence of or proximity to tumor cells. Adipose adjacent to the tumor demonstrated the largest immune response; this response may reflect a reaction to surgical insult from the original biopsy; however, response to surgical injury has been associated with increased ability to metastasize. In addition, within breasts with invasive breast cancer, genes involved in cellular proliferation, degradation of the extracellular matrix and angiogenesis were expressed at higher levels in adjacent compared to distant adipose. Together, these data suggest that adipose is not an inert component of the breast microenvironment but plays an active role in tumorigenesis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4266. doi:1538-7445.AM2012-4266

Background Widespread adoption of genomic technologies in the management of heterogeneous indications, including Multiple Myeloma, has been hindered by concern over variation between published gene expression signatures, difficulty in physician interpretation and the challenge of obtaining sufficient genetic material from limited patient specimens. Methods Since 2006, the 70-gene prognostic signature, developed by the University of Arkansas for Medical Sciences (UAMS) has been applied to over 4,700 patients in studies performed in 4 countries and described in 17 peer-reviewed publications. Analysis of control sample and quality control data compiled over a 12-month period was performed. Results Over a 12 month period, the 70-gene prognosis score (range 0–100) of our multiple myeloma cell-line control sample had a standard deviation of 2.72 and a coefficient of variance of 0.03. The whole-genome microarray profile used to calculate a patient’s GEP70 score can be generated with as little as 15 ng of total RNA; approximately 30,000 CD-138+ plasma cells. Results from each GEP70 analysis are presented as either low (70-gene score