Validation of a microRNA liquid biopsy assay for diagnosis and risk stratification of invasive cutaneous melanoma.

BACKGROUND: Noninvasive molecular biomarkers are needed to improve the early, accurate and precise diagnosis of invasive cutaneous melanoma. OBJECTIVES: To independently validate a previously identified circulating microRNA signature of melanoma (MEL38), and, secondly, to develop a complementary microRNA signature, optimized for prognostication. PATIENTS AND METHODS: MicroRNA expression profiling was performed on plasma samples from a multicentre observational case-control study, involving patients with primary or metastatic melanoma, melanoma in situ, nonmelanoma skin cancer, or benign naevi. MicroRNA profiles from patients with length of survival, treatment and sentinel lymph node biopsy (SLNB) data were used to develop the prognostic signature. 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 patients with invasive melanoma and 210 control individuals were generated. The average age of all participants was 59 years; 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 ranged from 0 to 10 with an area under the curve of 0.98 (95% confidence interval 0.97-0.99, P < 0.001). 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 melanoma-specific survival, respectively (log-rank P < 0.001). MEL12 prognostic risk groups were significantly associated with clinical staging (χ2, P < 0.001) and SLNB status (P = 0.027). Patients who were classified as high risk by MEL12 were approximately three times more likely to have melanoma detected in their sentinel lymph nodes compared to low-risk patients. CONCLUSIONS: The circulating MEL38 signature may assist in diagnosing patients with invasive melanoma vs. 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 to optimize existing diagnostic pathways as well as enable personalized, risk-informed melanoma treatment decisions.

Development and validation of a plasma-based melanoma biomarker suitable for clinical use.

This corrects the article DOI: 10.1038/bjc.2017.85.

BreastPRS is a gene expression assay that stratifies intermediate-risk Oncotype DX patients into high- or low-risk for disease recurrence.

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 < 0.0001). 59 of 260 (23 %) patients from four previously published studies were classified as intermediate-risk when the 120-gene Oncotype DX approximation algorithm was applied. BreastPRS reclassified the 59 patients into binary risk groups (high- vs. low-risk). 23 (39 %) patients were classified as low-risk and 36 (61 %) as high-risk (P = 0.029, HR: 3.64, 95 % CI: 1.40-9.50). At 10 years from diagnosis, the low-risk group had a 90 % recurrence-free survival (RFS) rate compared to 60 % for the high-risk group. BreastPRS recurrence score is comparable with Oncotype DX and can reclassify Oncotype DX intermediate-risk patients into two groups with significant differences in RFS. Further studies are needed to validate these findings.

Effect of ASCO/CAP guidelines for determining ER status on molecular subtype.

BACKGROUND: Determination of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status is standard for predicting prognosis and determining treatment options for patients with breast cancer. In 2010, the American Society of Clinical Oncology (ASCO) and College of American Pathologists (CAP) issued guidelines that tumors with ≥1% positively staining cells should be considered ER positive. Here, we determined how this cutoff relates to molecular subtype. METHODS: Clinicopathological characteristics were compared between ER-negative, ER-positive, and low-ER-staining (1-10%) tumors using chi-square analysis with P<0.05 defining statistical significance. Gene expression data were generated for 26 low-ER-staining tumors, and their intrinsic subtype determined. Immunohistochemistry (IHC)-defined surrogate subtypes, using the threshold of positivity defined by ASCO/CAP guidelines, were compared with molecular subtypes. RESULTS: Low-ER-staining tumors were clinicopathologically more similar to ER-negative than to ER-positive tumors; 88% of low-staining tumors were basal like or HER2 enriched. Only those tumors expressing 10% ER-positive cells were classified as luminal A subtype. CONCLUSIONS: Under ASCO/CAP guidelines, tumors with 1-10% ER staining would be classified as ER positive, yet most are basal like or HER2 enriched and have pathological features similar to ER-negative tumors. Clinical trials seeking to treat tumors of ER-negative basal-like and/or HER2-enriched subtypes should thus not preclude enrollment based solely on results of ER immunohistochemistry. As ER status is a critical element in the choice of treatments for patients with breast cancer, it is imperative that the most effective method for classifying tumors be developed.

Recreational Music-Making alters gene expression pathways in patients with coronary heart disease.

BACKGROUND: Psychosocial stress profoundly impacts long-term cardiovascular health through adverse effects on sympathetic nervous system activity, endothelial dysfunction, and atherosclerotic development. Recreational Music Making (RMM) is a unique stress amelioration strategy encompassing group music-based activities that has great therapeutic potential for treating patients with stress-related cardiovascular disease. MATERIAL/METHODS: Participants (n=34) with a history of ischemic heart disease were subjected to an acute time-limited stressor, then randomized to RMM or quiet reading for one hour. Peripheral blood gene expression using GeneChip® Human Genome U133A 2.0 arrays was assessed at baseline, following stress, and after the relaxation session. RESULTS: Full gene set enrichment analysis identified 16 molecular pathways differentially regulated (P<0.005) during stress that function in immune response, cell mobility, and transcription. During relaxation, two pathways showed a significant change in expression in the control group, while 12 pathways governing immune function and gene expression were modulated among RMM participants. Only 13% (2/16) of pathways showed differential expression during stress and relaxation. CONCLUSIONS: Human stress and relaxation responses may be controlled by different molecular pathways. Relaxation through active engagement in Recreational Music Making may be more effective than quiet reading at altering gene expression and thus more clinically useful for stress amelioration.

Options available--from start to finish--for obtaining data from DNA microarrays II.

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.

Implementation of a novel microarray-based diagnostic test for cancer of unknown primary.

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.

Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen.

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 naïve 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.

Characterisation and validation of Mel38; A multi-tissue microRNA signature of cutaneous melanoma.

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.

A plasma microRNA biomarker of melanoma as a personalised assessment of treatment response.

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.

An expression-based site of origin diagnostic method designed for clinical application to cancer of unknown origin.

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.

Empirical array quality weights in the analysis of microarray data.

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.

Genomic analysis of a spontaneous model of breast cancer metastasis to bone reveals a role for the extracellular matrix.

A clinically relevant model of spontaneous breast cancer metastasis to multiple sites, including bone, was characterized and used to identify genes involved in metastatic progression. The metastatic potential of several genetically related tumor lines was assayed using a novel real-time quantitative RT-PCR assay of tumor burden. Based on this assay, the tumor lines were categorized as nonmetastatic (67NR), weakly metastatic to lymph node (168FARN) or lung (66cl4), or highly metastatic to lymph node, lung, and bone (4T1.2 and 4T1.13). In vitro assays that mimic stages of metastasis showed that highly metastatic tumors lines were more adhesive, invasive, and migratory than the less metastatic lines. To identify metastasis-related genes in this model, each metastatic tumor was array profiled against the nonmetastatic 67NR using 15,000 mouse cDNA arrays. A significant proportion of genes relating to the extracellular matrix had elevated expression in highly metastatic tumors. The role of one of these genes, POEM, was further investigated in the model. In situ hybridization showed that POEM expression was specific to the tumor epithelium of highly metastatic tumors. Decreased POEM expression in 4T1.2 tumors significantly inhibited spontaneous metastasis to the lung, bone, and kidney. Taken together, our data support a role for the extracellular matrix in metastatic progression and describe, for the first time, a role for POEM in this process.

Gene expression profiling during intensive cardiovascular lifestyle modification: Relationships with vascular function and weight loss.

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.

Importance of substantial weight loss for altering gene expression during cardiovascular lifestyle modification.

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 <0.05 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. 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.

Gene expression differences in adipose tissue associated with breast tumorigenesis.

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.

Translating a gene expression signature for multiple myeloma prognosis into a robust high-throughput assay for clinical use.

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 <45.2) or high (≥45.2) risk for relapse (newly diagnosed setting) or shorter overall survival (relapse setting). A personalized and outcome-annotated gene expression heat map is provided to assist in the clinical interpretation of the result. CONCLUSIONS: The 70-gene assay, commercialized under the name 'MyPRS®' (Myeloma Prognostic Risk Score) and performed in Signal Genetics' CLIA-certified high throughput flow-cytometry and molecular profiling laboratory is a reproducible and standardized method of multiple myeloma prognostication.

Intensive cardiovascular risk reduction induces sustainable changes in expression of genes and pathways important to vascular function.

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<0.001 versus controls) and physical fitness (+34%; P<0.001) led to significant improvements in cardiovascular disease risk factors. Analysis of variance with false discovery rate correction for multiple testing (P<0.05) identified 26 genes after 12 weeks and 143 genes after 52 weeks that were differentially expressed from baseline in participants. Controls showed little change in cardiovascular disease risk factors or gene expression. Quantitative reverse transcription polymerase chain reaction validated differential expression for selected transcripts. Lifestyle modification effectively reduced expression of proinflammatory genes associated with neutrophil activation and molecular pathways important to vascular function, including cytokine production, carbohydrate metabolism, and steroid hormones. Prescription medications did not significantly affect changes in gene expression. 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.

Genomic signatures for predicting survival and adjuvant chemotherapy benefit in patients with non-small-cell lung cancer.

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 < 0.0001) compared to those with the low-risk, good prognosis profile, adjusted for covariates. The prognosis signature was found to especially accurate at identifying early stage patients at risk of disease specific death within 24 months of diagnosis when compared to traditional methods of outcome prediction.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.

Design and multiseries validation of a web-based gene expression assay for predicting breast cancer recurrence and patient survival.

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.