Pan-cancer proteogenomics characterization of tumor immunity.

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

A proteogenomic portrait of lung squamous cell carcinoma.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer.

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Safety of Immunosuppression in a Prospective Cohort of Inflammatory Bowel Disease Patients With a HIstoRy of CancEr: SAPPHIRE Registry.

BACKGROUND & AIMS: In patients with inflammatory bowel disease (IBD) and a history of cancer, retrospective studies have suggested that exposure to immunosuppressive agents does not increase the risk of incident (recurrent or new) cancer compared with unexposed patients. SAPPHIRE is a prospective registry aimed at addressing this issue. METHODS: Since 2016, patients with IBD and confirmed index cancer before enrollment were followed up annually. Patients receiving chemotherapy or radiation at enrollment, or recurrent cancer within 5 years, were excluded. The primary outcome was development of incident cancer related to exposure to immunosuppressive medications. RESULTS: Among 305 patients (47% male, 88% white), the median age at IBD diagnosis and cancer were 32 and 52 years, respectively. Index cancers were solid organ (46%), dermatologic (32%), gastrointestinal (13%), and hematologic (9%). During a median follow-up period of 4.8 years, 210 patients (69%) were exposed to immunosuppressive therapy and 46 patients (15%) developed incident cancers (25 new, 21 recurrent). In unadjusted analysis, the crude rate of incident cancer in unexposed patients was 2.58 per 100 person-years vs 4.78 per 100 person-years (relative risk, 1.85; 95% CI, 0.92-3.73) for immunosuppression-exposed patients. In a proportional hazards model adjusting for sex, smoking history, age and stage at index malignancy, and nonmelanoma skin cancer, no significant association was found between receipt of immunosuppression and incident cancer (adjusted hazard ratio, 1.41; 95% CI, 0.69-2.90), or with any major drug class. CONCLUSIONS: In this interim analysis of patients with IBD and a history of cancer, despite numerically increased adjusted hazard ratios, we did not find a statistically significant association between subsequent exposure to immunosuppressive therapies and development of incident cancers.

Anti-Integrin αvß6 Autoantibodies Are a Novel Biomarker That Antedate Ulcerative Colitis.

BACKGROUND & AIMS: Better biomarkers for prediction of ulcerative colitis (UC) development and prognostication are needed. Anti-integrin αvß6 (anti-αvß6) autoantibodies have been described in patients with UC. We tested for the presence of anti-αvß6 antibodies in the preclinical phase of UC and studied their association with disease-related outcomes after diagnosis. METHODS: Anti-αvß6 autoantibodies were measured in 4 longitudinal serum samples collected from 82 subjects who later developed UC and 82 matched controls from a Department of Defense preclinical cohort (PREDICTS [Proteomic Evaluation and Discovery in an IBD Cohort of Tri-service Subjects]). In a distinct, external validation cohort (Crohn's and Colitis Canada Genetic Environmental Microbial project cohort), we tested 12 pre-UC subjects and 49 matched controls. Furthermore, anti-αvß6 autoantibodies were measured in 2 incident UC cohorts (COMPASS [Comprehensive Care for the Recently Diagnosed IBD Patients], n = 55 and OSCCAR [Ocean State Crohn's and Colitis Area Registry], n = 104) and associations between anti-αvß6 autoantibodies and UC-related outcomes were defined using Cox proportional hazards model. RESULTS: Anti-αvß6 autoantibodies were significantly higher among individuals who developed UC compared with controls up to 10 years before diagnosis in PREDICTS. The anti-αvß6 autoantibody seropositivity was 12.2% 10 years before diagnosis and increased to 52.4% at the time of diagnosis in subjects who developed UC compared with 2.7% in controls across the 4 time points. Anti-αvß6 autoantibodies predicted UC development with an area under the curve of at least 0.8 up to 10 years before diagnosis. The presence of anti-αvß6 autoantibodies in preclinical UC samples was validated in the GEM cohort. Finally, high anti-αvß6 autoantibodies was associated with a composite of adverse UC outcomes, including hospitalization, disease extension, colectomy, systemic steroid use, and/or escalation to biologic therapy in recently diagnosed UC. CONCLUSIONS: Anti-integrin αvß6 autoantibodies precede the clinical diagnosis of UC by up to 10 years and are associated with adverse UC-related outcomes.

Preclinical Serological Signatures are Associated With Complicated Crohn's Disease Phenotype at Diagnosis.

BACKGROUND: At diagnosis, up to one-third of patients with Crohn's disease (CD) have a complicated phenotype with stricturing (B2) or penetrating (B3) behavior or require early surgery. We evaluated protein biomarkers and antimicrobial antibodies in serum archived years before CD diagnosis to assess whether complicated diagnoses were associated with a specific serological signature. METHODS: Prediagnosis serum was obtained from 201 patients with CD and 201 healthy controls. Samples were evaluated with a comprehensive panel of 1129 proteomic markers (SomaLogic) and antimicrobial antibodies. CD diagnosis and complications were defined by the International Classification of Diseases-Ninth Revision and Current Procedural Terminology codes. Cox regression models were utilized to assess the association between markers and the subsequent risk of being diagnosed with complicated CD. In addition, biological pathway and network analyses were performed. RESULTS: Forty-seven CD subjects (24%) had a B2 (n = 36) or B3 (n = 9) phenotype or CD-related surgery (n = 2) at diagnosis. Subjects presenting with complicated CD at diagnosis had higher levels of antimicrobial antibodies six years before diagnosis as compared with those diagnosed with noncomplicated CD. Twenty-two protein biomarkers (reflecting inflammatory, fibrosis, and tissue protection markers) were found to be associated with complicated CD. Pathway analysis of the altered protein biomarkers identified higher activation of the innate immune system and complement or coagulation cascades up to six years before diagnosis in complicated CD. CONCLUSIONS: Proteins and antimicrobial antibodies associated with dysregulated innate immunity, excessive adaptive response to microbial antigens, and fibrosis precede and predict a complicated phenotype at the time of diagnosis in CD patients.

Neutralizing Anti-Granulocyte Macrophage-Colony Stimulating Factor Autoantibodies Recognize Post-Translational Glycosylations on Granulocyte Macrophage-Colony Stimulating Factor Years Before Diagnosis and Predict Complicated Crohn's Disease.

BACKGROUND & AIMS: Anti-granulocyte macrophage-colony stimulating factor autoantibodies (aGMAbs) are detected in patients with ileal Crohn's disease (CD). Their induction and mode of action during or before disease are not well understood. We aimed to investigate the underlying mechanisms associated with aGMAb induction, from functional orientation to recognized epitopes, for their impact on intestinal immune homeostasis and use as a predictive biomarker for complicated CD. METHODS: We characterized using enzyme-linked immunosorbent assay naturally occurring aGMAbs in longitudinal serum samples from patients archived before the diagnosis of CD (n = 220) as well as from 400 healthy individuals (matched controls) as part of the US Defense Medical Surveillance System. We used biochemical, cellular, and transcriptional analysis to uncover a mechanism that governs the impaired immune balance in CD mucosa after diagnosis. RESULTS: Neutralizing aGMAbs were found to be specific for post-translational glycosylation on granulocyte macrophage-colony stimulating factor (GM-CSF), detectable years before diagnosis, and associated with complicated CD at presentation. Glycosylation of GM-CSF was altered in patients with CD, and aGMAb affected myeloid homeostasis and promoted group 1 innate lymphoid cells. Perturbations in immune homeostasis preceded the diagnosis in the serum of patients with CD presenting with aGMAb and were detectable in the noninflamed CD mucosa. CONCLUSIONS: Anti-GMAbs predict the diagnosis of complicated CD long before the diagnosis of disease, recognize uniquely glycosylated epitopes, and impair myeloid cell and innate lymphoid cell balance associated with altered intestinal immune homeostasis.

Intestinal Host Response to SARS-CoV-2 Infection and COVID-19 Outcomes in Patients With Gastrointestinal Symptoms.

BACKGROUND & AIMS: Given that gastrointestinal (GI) symptoms are a prominent extrapulmonary manifestation of COVID-19, we investigated intestinal infection with SARS-CoV-2, its effect on pathogenesis, and clinical significance. METHODS: Human intestinal biopsy tissues were obtained from patients with COVID-19 (n = 19) and uninfected control individuals (n = 10) for microscopic examination, cytometry by time of flight analyses, and RNA sequencing. Additionally, disease severity and mortality were examined in patients with and without GI symptoms in 2 large, independent cohorts of hospitalized patients in the United States (N = 634) and Europe (N = 287) using multivariate logistic regressions. RESULTS: COVID-19 case patients and control individuals in the biopsy cohort were comparable for age, sex, rates of hospitalization, and relevant comorbid conditions. SARS-CoV-2 was detected in small intestinal epithelial cells by immunofluorescence staining or electron microscopy in 15 of 17 patients studied. High-dimensional analyses of GI tissues showed low levels of inflammation, including down-regulation of key inflammatory genes including IFNG, CXCL8, CXCL2, and IL1B and reduced frequencies of proinflammatory dendritic cells compared with control individuals. Consistent with these findings, we found a significant reduction in disease severity and mortality in patients presenting with GI symptoms that was independent of sex, age, and comorbid illnesses and despite similar nasopharyngeal SARS-CoV-2 viral loads. Furthermore, there was reduced levels of key inflammatory proteins in circulation in patients with GI symptoms. CONCLUSIONS: These data highlight the absence of a proinflammatory response in the GI tract despite detection of SARS-CoV-2. In parallel, reduced mortality in patients with COVID-19 presenting with GI symptoms was observed. A potential role of the GI tract in attenuating SARS-CoV-2-associated inflammation needs to be further examined.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Serum Biomarkers Identify Patients Who Will Develop Inflammatory Bowel Diseases Up to 5 Years Before Diagnosis.

BACKGROUND & AIMS: Biomarkers are needed to identify patients at risk for development of inflammatory bowel diseases. We aimed to identify serum biomarkers of Crohn's disease and ulcerative colitis that can be detected and quantified before diagnosis. METHODS: We obtained serum samples from patients archived before a diagnosis of Crohn's disease (n = 200) or ulcerative colitis (n = 199), as well as from 200 healthy individuals (controls), collected from 1998 through 2013 as part of the US Defense Medical Surveillance System. We measured levels of antibodies against microbes (anti-Saccharomyces cerevisiae IgA or IgG, anti-Escherichiacoli outer membrane porin C, anti-CBir1, anti-flagellin 2, anti-flagellin X, and perinuclear anti-neutrophil cytoplasmic antibodies) and 1129 proteins in each sample. We then used functional principal component analysis to derive the time-varying trajectory for each marker, which then was used in a multivariate model to predict disease status. Predictive performances at different prediagnosis timepoints were evaluated using area under the receiver operating characteristic curves (AUROCs). Biological pathways that were up-regulated in serum from patients with Crohn's disease were identified based on changes in protein abundance at different time periods preceding diagnosis. RESULTS: We identified a panel of 51 protein biomarkers that were predictive of Crohn's disease within 5 years with an AUROC of 0.76 and a diagnosis within 1 year with an AUROC of 0.87. Based on the proteins included in the panel, imminent development of CD was associated with changes in the complement cascade, lysosomes, innate immune response, and glycosaminoglycan metabolism. Serum antibodies and proteins identified patients who received a diagnosis of ulcerative colitis within 5 years with an AUROC of only 0.56 and within 1 year with an AUROC of 0.72. CONCLUSIONS: We identified a panel of serum antibodies and proteins that were predictive of patients who will receive a diagnosis of Crohn's disease within 5 years with high accuracy. By contrast we did not identify biomarkers associated with future diagnosis of ulcerative colitis.

Deep Remission at 1 Year Prevents Progression of Early Crohn's Disease.

BACKGROUND & AIMS: We investigated the effects of inducing deep remission in patients with early Crohn's disease (CD). METHODS: We collected follow-up data from 122 patients (mean age, 31.2 ± 11.3 y) with early, moderate to severe CD (median duration, 0.2 years; interquartile range, 0.1-0.5) who participated in the Effect of Tight Control Management on CD (CALM) study, at 31 sites, representing 50% of the original CALM patient population. Fifty percent of patients (n = 61) were randomly assigned to a tight control strategy (increased therapy based on fecal level of calprotectin, serum level of C-reactive protein, and symptoms), and 50% were assigned to conventional management. We categorized patients as those who were vs were not in deep remission (CD endoscopic index of severity scores below 4, with no deep ulcerations or steroid treatment, for 8 or more weeks) at the end of the follow-up period (median, 3.02 years; range, 0.05-6.26 years). The primary outcome was a composite of major adverse outcomes that indicate CD progression during the follow-up period: new internal fistulas or abscesses, strictures, perianal fistulas or abscesses, or hospitalization or surgery for CD. Kaplan-Meier and penalized Cox regression with bootstrapping were used to compare composite rates between patients who achieved or did not achieve remission at the end of the follow-up period. RESULTS: Major adverse outcomes were reported for 34 patients (27.9%) during the follow-up period. Significantly fewer patients in deep remission at the end of the CALM study had major adverse outcomes during the follow-up period (P = .01). When we adjusted for potential confounders, deep remission (adjusted hazard ratio, 0.19; 95% confidence interval, 0.07-0.31) was significantly associated with a lower risk of major adverse outcome. CONCLUSIONS: In an analysis of follow-up data from the CALM study, we associated induction of deep remission in early, moderate to severe CD with decreased risk of disease progression over a median time of 3 years, regardless of tight control or conventional management strategy.

ProNetView-ccRCC: A Web-Based Portal to Interactively Explore Clear Cell Renal Cell Carcinoma Proteogenomics Networks.

To better understand the molecular basis of cancer, the NCI's Clinical Proteomics Tumor Analysis Consortium (CPTAC) has been performing comprehensive large-scale proteogenomic characterizations of multiple cancer types. Gene and protein regulatory networks are subsequently being derived based on these proteogenomic profiles, which serve as tools to gain systems-level understanding of the molecular regulatory factories underlying these diseases. On the other hand, it remains a challenge to effectively visualize and navigate the resulting network models, which capture higher order structures in the proteogenomic profiles. There is a pressing need to have a new open community resource tool for intuitive visual exploration, interpretation, and communication of these gene/protein regulatory networks by the cancer research community. In this work, ProNetView-ccRCC (http://ccrcc.cptac-network-view.org/), an interactive web-based network exploration portal for investigating phosphopeptide co-expression network inferred based on the CPTAC clear cell renal cell carcinoma (ccRCC) phosphoproteomics data is introduced. ProNetView-ccRCC enables quick, user-intuitive visual interactions with the ccRCC tumor phosphoprotein co-expression network comprised of 3614 genes, as well as 30 functional pathway-enriched network modules. Users can interact with the network portal and can conveniently query for association between abundance of each phosphopeptide in the network and clinical variables such as tumor grade.

ProTrack: An Interactive Multi-Omics Data Browser for Proteogenomic Studies.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) initiative has generated extensive multi-omics data resources of deep proteogenomic profiles for multiple cancer types. To enable the broader community of biological and medical researchers to intuitively query, explore, and download data and analysis results from various CPTAC projects, a prototype user-friendly web application called "ProTrack" is built with the CPTAC clear cell renal cell carcinoma (ccRCC) data set (http://ccrcc.cptac-data-view.org). Here the salient features of this application which provides a dynamic, comprehensive, and granular visualization of the rich proteogenomic data is described.

A new method for constructing tumor specific gene co-expression networks based on samples with tumor purity heterogeneity.

Motivation: Tumor tissue samples often contain an unknown fraction of stromal cells. This problem is widely known as tumor purity heterogeneity (TPH) was recently recognized as a severe issue in omics studies. Specifically, if TPH is ignored when inferring co-expression networks, edges are likely to be estimated among genes with mean shift between non-tumor- and tumor cells rather than among gene pairs interacting with each other in tumor cells. To address this issue, we propose Tumor Specific Net (TSNet), a new method which constructs tumor-cell specific gene/protein co-expression networks based on gene/protein expression profiles of tumor tissues. TSNet treats the observed expression profile as a mixture of expressions from different cell types and explicitly models tumor purity percentage in each tumor sample. Results: Using extensive synthetic data experiments, we demonstrate that TSNet outperforms a standard graphical model which does not account for TPH. We then apply TSNet to estimate tumor specific gene co-expression networks based on TCGA ovarian cancer RNAseq data. We identify novel co-expression modules and hub structure specific to tumor cells. Availability and implementation: R codes can be found at https://github.com/petraf01/TSNet. Supplementary information: Supplementary data are available at Bioinformatics online.

A new method to study the change of miRNA-mRNA interactions due to environmental exposures.

MOTIVATION: Integrative approaches characterizing the interactions among different types of biological molecules have been demonstrated to be useful for revealing informative biological mechanisms. One such example is the interaction between microRNA (miRNA) and messenger RNA (mRNA), whose deregulation may be sensitive to environmental insult leading to altered phenotypes. The goal of this work is to develop an effective data integration method to characterize deregulation between miRNA and mRNA due to environmental toxicant exposures. We will use data from an animal experiment designed to investigate the effect of low-dose environmental chemical exposure on normal mammary gland development in rats to motivate and evaluate the proposed method. RESULTS: We propose a new network approach-integrative Joint Random Forest (iJRF), which characterizes the regulatory system between miRNAs and mRNAs using a network model. iJRF is designed to work under the high-dimension low-sample-size regime, and can borrow information across different treatment conditions to achieve more accurate network inference. It also effectively takes into account prior information of miRNA-mRNA regulatory relationships from existing databases. When iJRF is applied to the data from the environmental chemical exposure study, we detected a few important miRNAs that regulated a large number of mRNAs in the control group but not in the exposed groups, suggesting the disruption of miRNA activity due to chemical exposure. Effects of chemical exposure on two affected miRNAs were further validated using breast cancer human cell lines. AVAILABILITY AND IMPLEMENTATION: R package iJRF is available at CRAN. CONTACTS: pei.wang@mssm.edu or susan.teitelbaum@mssm.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.