Subtype and cell type specific expression of lncRNAs provide insight into breast cancer.

Long non-coding RNAs (lncRNAs) are involved in breast cancer pathogenesis through chromatin remodeling, transcriptional and post-transcriptional gene regulation. We report robust associations between lncRNA expression and breast cancer clinicopathological features in two population-based cohorts: SCAN-B and TCGA. Using co-expression analysis of lncRNAs with protein coding genes, we discovered three distinct clusters of lncRNAs. In silico cell type deconvolution coupled with single-cell RNA-seq analyses revealed that these three clusters were driven by cell type specific expression of lncRNAs. In one cluster lncRNAs were expressed by cancer cells and were mostly associated with the estrogen signaling pathways. In the two other clusters, lncRNAs were expressed either by immune cells or fibroblasts of the tumor microenvironment. To further investigate the cis-regulatory regions driving lncRNA expression in breast cancer, we identified subtype-specific transcription factor (TF) occupancy at lncRNA promoters. We also integrated lncRNA expression with DNA methylation data to identify long-range regulatory regions for lncRNA which were validated using ChiA-Pet-Pol2 loops. lncRNAs play an important role in shaping the gene regulatory landscape in breast cancer. We provide a detailed subtype and cell type-specific expression of lncRNA, which improves the understanding of underlying transcriptional regulation in breast cancer.

Gene Expression in Barrett's Esophagus Cell Lines Resemble Esophageal Squamous Cell Carcinoma Instead of Esophageal Adenocarcinoma.

Esophageal adenocarcinoma (EAC) is strongly associated with Barrett's esophagus (BE), a pre-malignant condition resulting from gastric reflux. Esophageal squamous cell carcinoma (ESCC), the other major subtype of esophageal cancer, shows strong association with smoking and alcohol intake and no association with gastric reflux. In this study, we constructed and validated gene expression signatures of EAC vs. ESCC tumors using publicly available datasets, and subsequently assessed the enrichment levels of these signatures in commonly used EAC and ESCC cell lines, normal esophageal tissues and normal esophageal cell lines, and primary BE tissues and BE cell lines. We found that unlike ESCC cell lines which were quite similar to primary ESCC tumors, EAC cell lines were considerably different from primary EAC tumors but still more similar to EAC tumors than ESCC tumors, as the genes up in EAC vs. ESCC (EAChi) had considerably lower expression in EAC cell lines than EAC tumors. However, more surprisingly, unlike various normal cell lines (EPC2, Het-1A) which were very similar to various tissues from normal esophagus, BE cell lines (BAR-T, CP-A) were extremely different from primary BE tissues, as BE cell lines had substantially lower levels of EAChi and substantially higher levels of ESCChi gene expression. This ESCC-like profile of the BAR-T remained unaltered even after prolonged exposure to an acidic bile mixture in vitro resulting in malignant transformation of this cell line. However, primary BE tissues had EAC-like gene expression profiles as expected. Only one EAC case from the Cancer Genome Atlas resembled BE cell lines, and while it had the clinical profile and some mutational features of EAC, it had some mutational features, the copy number alteration profile, and the gene expression profile of ESCC instead. These incomprehensible changes in gene expression patterns may result in ambiguous changes in the phenotype and warrants careful evaluation to inform selection of appropriate in vitro tools for future studies on esophageal adenocarcinoma.

Genomic and immunologic correlates of LAG-3 expression in cancer.

Immune checkpoint blockade leads to unprecedented responses in many cancers. Although currently available agents mostly target the PD-1 and CTLA-4 pathways, agents targeting the immune checkpoint protein LAG-3 are under active clinical development, and early clinical data show that LAG-3 expression is a biomarker of response to LAG-3 blockade. To determine which cancers may benefit most from LAG-3 blockade, we performed a pan-cancer analysis of The Cancer Genome Atlas dataset to identify genomic and immunologic correlates of LAG-3 expression. High mutation burden, and expression of exogenous virus (EBV, HPV) or endogenous retrovirus (ERV3-2), were associated with overexpression of LAG-3 in multiple cancers. Although CD8+ T-cell marker (CD8A) and LAG-3 were strongly co-expressed with each other and with PD-L1 in most cancers, there were three notable exceptions: HPV+ head-neck squamous cell cancer, renal cell cancer, and glioblastoma. These results may have important implications for guiding development clinical trials of LAG-3 blockade.

Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples.

We give results from a detailed analysis of human Ribosomal Protein (RP) levels in normal and cancer samples and cell lines from large mRNA, copy number variation and ribosome profiling datasets. After normalizing total RP mRNA levels per sample, we find highly consistent tissue specific RP mRNA signatures in normal and tumor samples. Multiple RP mRNA-subtypes exist in several cancers, with significant survival and genomic differences. Some RP mRNA variations among subtypes correlate with copy number loss of RP genes. In kidney cancer, RP subtypes map to molecular subtypes related to cell-of-origin. Pan-cancer analysis of TCGA data showed widespread single/double copy loss of RP genes, without significantly affecting survival. In several cancer cell lines, CRISPR-Cas9 knockout of RP genes did not affect cell viability. Matched RP ribosome profiling and mRNA data in humans and rodents stratified by tissue and development stage and were strongly correlated, showing that RP translation rates were proportional to mRNA levels. In a small dataset of human adult and fetal tissues, RP protein levels showed development stage and tissue specific heterogeneity of RP levels. Our results suggest that heterogeneous RP levels play a significant functional role in cellular physiology, in both normal and disease states.

DNA hypomethylation promotes transposable element expression and activation of immune signaling in renal cell cancer.

Recently, we reported that expression of endogenous retroviruses (ERVs) is associated with response to immune checkpoint blockade (ICB) in renal cell carcinoma (RCC). We show that decitabine, a DNA hypomethylating agent, activates transposable element (TE) expression (LINE1 and ERVs ERV3-2 and ERV4700) and antiviral signaling to potentially enhance response to ICB in kidney cancer cell lines and primary cells. KO of RIGI and MDA5 dsRNA sensors attenuated activation of antiviral signaling associated with DNA hypomethylation, and RIGI and MDA5 IPs showed increased ERV binding with decitabine treatment. Bioinformatic analyses showed the decitabine-induced signature could be associated with increased immune infiltration and response to ICB. Cytokine secretion induced by decitabine could modestly improve T cell activation and robustly enhanced T cell migration. In a small retrospective cohort of metastatic clear cell RCC (ccRCC) patients treated with anti-PD1/PDL1 blockade, activation of some antiviral genes was significantly higher in responders. Thus, we identified a potential strategy to induce TE expression through inhibition of DNA methylation in modulating T cell action via regulation of the innate antiviral pathway.

A Quasi Birth-and-Death model for tumor recurrence.

A major cause of chemoresistance and recurrence in tumors is the presence of dormant tumor foci that survive chemotherapy and can eventually transition to active growth to regenerate the cancer. In this paper, we propose a Quasi Birth-and-Death (QBD) model for the dynamics of tumor growth and recurrence/remission of the cancer. Starting from a discrete-state master equation that describes the time-dependent transition probabilities between states with different numbers of dormant and active tumor foci, we develop a framework based on a continuum-limit approach to determine the time-dependent probability that an undetectable residual tumor will become large enough to be detectable. We derive an exact formula for the probability of recurrence at large times and show that it displays a phase transition as a function of the ratio of the death rate µA of an active tumor focus to its doubling rate λ. We also derive forward and backward Kolmogorov equations for the transition probability density in the continuum limit and, using a first-passage time formalism, we obtain a drift-diffusion equation for the mean recurrence time and solve it analytically to leading order for a large detectable tumor size N. We show that simulations of the discrete-state model agree with the analytical results, except for O(1/N) corrections. As an example of the use of our model in a clinical setting, we show that a range of model parameters can fit Kaplan-Meier recurrence-free survival data for ovarian cancer. Finally, we show in simulations that extending the duration of chemotherapy increases both the mean recurrence time and the asymptotic (large-time) probability of no recurrence. Our results should be useful in planning optimized chemotherapy dosing and duration for cancer treatment, especially in cancer types for which no targeted therapy is available.

TuBA: Tunable biclustering algorithm reveals clinically relevant tumor transcriptional profiles in breast cancer.

BACKGROUND: Traditional clustering approaches for gene expression data are not well adapted to address the complexity and heterogeneity of tumors, where small sets of genes may be aberrantly co-expressed in specific subsets of tumors. Biclustering algorithms that perform local clustering on subsets of genes and conditions help address this problem. We propose a graph-based Tunable Biclustering Algorithm (TuBA) based on a novel pairwise proximity measure, examining the relationship of samples at the extremes of genes' expression profiles to identify similarly altered signatures. RESULTS: TuBA's predictions are consistent in 3,940 breast invasive carcinoma samples from 3 independent sources, using different technologies for measuring gene expression (RNA sequencing and Microarray). More than 60% of biclusters identified independently in each dataset had significant agreement in their gene sets, as well as similar clinical implications. Approximately 50% of biclusters were enriched in the estrogen receptor-negative/HER2-negative (or basal-like) subtype, while >50% were associated with transcriptionally active copy number changes. Biclusters representing gene co-expression patterns in stromal tissue were also identified in tumor specimens. CONCLUSIONS: TuBA offers a simple biclustering method that can identify biologically relevant gene co-expression signatures not captured by traditional unsupervised clustering approaches. It complements biclustering approaches that are designed to identify constant or coherent submatrices in gene expression datasets, and outperforms them in identifying a multitude of altered transcriptional profiles that are associated with observed genomic heterogeneity of diseased states in breast cancer, both within and across tumor subtypes, a promising step in understanding disease heterogeneity, and a necessary first step in individualized therapy.

Endogenous retrovirus expression is associated with response to immune checkpoint blockade in clear cell renal cell carcinoma.

Although a subset of clear cell renal cell carcinoma (ccRCC) patients respond to immune checkpoint blockade (ICB), predictors of response remain uncertain. We investigated whether abnormal expression of endogenous retroviruses (ERVs) in tumors is associated with local immune checkpoint activation (ICA) and response to ICB. Twenty potentially immunogenic ERVs (πERVs) were identified in ccRCC in The Cancer Genome Atlas data set, and tumors were stratified into 3 groups based on their expression levels. πERV-high ccRCC tumors showed increased immune infiltration, checkpoint pathway upregulation, and higher CD8+ T cell fraction in infiltrating leukocytes compared with πERV-low ccRCC tumors. Similar results were observed in ER+/HER2- breast, colon, and head and neck squamous cell cancers. ERV expression correlated with expression of genes associated with histone methylation and chromatin regulation, and πERV-high ccRCC was enriched in BAP1 mutant tumors. ERV3-2 expression correlated with ICA in 11 solid cancers, including the 4 named above. In a small retrospective cohort of 24 metastatic ccRCC patients treated with single-agent PD-1/PD-L1 blockade, ERV3-2 expression in tumors was significantly higher in responders compared with nonresponders. Thus, abnormal expression of πERVs is associated with ICA in several solid cancers, including ccRCC, and ERV3-2 expression is associated with response to ICB in ccRCC.

Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma.

Human endogenous retroviruses (hERVs) are remnants of exogenous retroviruses that have integrated into the genome throughout evolution. We developed a computational workflow, hervQuant, which identified more than 3,000 transcriptionally active hERVs within The Cancer Genome Atlas (TCGA) pan-cancer RNA-Seq database. hERV expression was associated with clinical prognosis in several tumor types, most significantly clear cell renal cell carcinoma (ccRCC). We explored two mechanisms by which hERV expression may influence the tumor immune microenvironment in ccRCC: (i) RIG-I-like signaling and (ii) retroviral antigen activation of adaptive immunity. We demonstrated the ability of hERV signatures associated with these immune mechanisms to predict patient survival in ccRCC, independent of clinical staging and molecular subtyping. We identified potential tumor-specific hERV epitopes with evidence of translational activity through the use of a ccRCC ribosome profiling (Ribo-Seq) dataset, validated their ability to bind HLA in vitro, and identified the presence of MHC tetramer-positive T cells against predicted epitopes. hERV sequences identified through this screening approach were significantly more highly expressed in ccRCC tumors responsive to treatment with programmed death receptor 1 (PD-1) inhibition. hervQuant provides insights into the role of hERVs within the tumor immune microenvironment, as well as evidence that hERV expression could serve as a biomarker for patient prognosis and response to immunotherapy.

On statistical modeling of sequencing noise in high depth data to assess tumor evolution.

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerge from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified using targeted sequencing assays by analysis of noise in high-depth data. Here, we develop a comprehensive, unbiased model for sequencing error background. We find that noise in sufficiently deep DNA sequencing data can be approximated by aggregating negative binomial distributions. Mutations with frequencies above noise may have prognostic value. We evaluate our model with simulated exponentially expanded populations as well as data from cell line and patient sample dilution experiments, demonstrating its utility in prognosticating tumor progression. Our results may have the potential to identify significant mutations that can cause recurrence. These results are relevant in the pre-treatment clinical setting to determine appropriate therapy and prepare for potential recurrence pretreatment.

Immune Activation and Benefit From Avelumab in EBV-Positive Gastric Cancer.

Response to immune checkpoint therapy can be associated with a high mutation burden, but other mechanisms are also likely to be important. We identified a patient with metastatic gastric cancer with meaningful clinical benefit from treatment with the anti-programmed death-ligand 1 (PD-L1) antibody avelumab. This tumor showed no evidence of high mutation burden or mismatch repair defect but was strongly positive for presence of Epstein-Barr virus (EBV) encoded RNA. Analysis of The Cancer Genome Atlas gastric cancer data (25 EBV+, 80 microsatellite-instable [MSI], 310 microsatellite-stable [MSS]) showed that EBV-positive tumors were MSS. Two-sided Wilcoxon rank-sum tests showed that: 1) EBV-positive tumors had low mutation burden (median = 2.07 vs 3.13 in log10 scale, P < 10-12) but stronger evidence of immune infiltration (median ImmuneScore 2212 vs 1295, P < 10-4; log2 fold-change of CD8A = 1.85, P < 10-6) compared with MSI tumors, and 2) EBV-positive tumors had higher expression of immune checkpoint pathway (PD-1, CTLA-4 pathway) genes in RNA-seq data (log2 fold-changes: PD-1 = 1.85, PD-L1 = 1.93, PD-L2 = 1.50, CTLA-4 = 1.31, CD80 = 0.89, CD86 = 1.31, P < 10-4 each), and higher lymphocytic infiltration by histology (median tumor-infiltrating lymphocyte score = 3 vs 2, P < .001) compared with MSS tumors. These data suggest that EBV-positive low-mutation burden gastric cancers are a subset of MSS gastric cancers that may respond to immune checkpoint therapy.

Widespread alternative exon usage in clinically distinct subtypes of Invasive Ductal Carcinoma.

Cancer cells can have different patterns of exon usage of individual genes when compared to normal tissue, suggesting that alternative splicing may play a role in shaping the tumor phenotype. The discovery and identification of gene variants has increased dramatically with the introduction of RNA-sequencing technology, which enables whole transcriptome analysis of known, as well as novel isoforms. Here we report alternative splicing and transcriptional events among subtypes of invasive ductal carcinoma in The Cancer Genome Atlas (TCGA) Breast Invasive Carcinoma (BRCA) cohort. Alternative exon usage was widespread, and although common events were shared among three subtypes, ER+ HER2-, ER- HER2-, and HER2+, many events on the exon level were subtype specific. Additional RNA-seq analysis was carried out in an independent cohort of 43 ER+ HER2- and ER- HER2- primary breast tumors, confirming many of the exon events identified in the TCGA cohort. Alternative splicing and transcriptional events detected in five genes, MYO6, EPB41L1, TPD52, IQCG, and ACOX2 were validated by qRT-PCR in a third cohort of 40 ER+ HER2- and ER- HER2- patients, showing that these events were truly subtype specific.

Identifying a Clinically Applicable Mutational Burden Threshold as a Potential Biomarker of Response to Immune Checkpoint Therapy in Solid Tumors.

PURPOSE: An association between mutational burden and response to immune checkpoint therapy has been documented in several cancer types. The potential for such a mutational burden threshold to predict response to immune checkpoint therapy was evaluated in several clinical datasets, where mutational burden was measured either by whole-exome sequencing (WXS) or using commercially available sequencing panels. METHODS: WXS and RNA-seq data of 33 solid cancer types from TCGA were analyzed to determine whether a robust immune checkpoint activating mutation (iCAM) burden threshold associated with evidence of immune checkpoint activation exists in these cancers that may serve as a biomarker for response to immune checkpoint blockade therapy. RESULTS: We find that a robust iCAM threshold, associated with signatures of immune checkpoint activation, exists in 8 of 33 solid cancers: melanoma, lung adenocarcinoma, colon adenocarcinoma, endometrial cancer, stomach adenocarcinoma, cervical cancer, ER+HER2- breast cancer, and bladder-urothelial cancer. Tumors with mutational burden higher than the threshold (iCAM+) also had clear histologic evidence of lymphocytic infiltration. In published datasets of melanoma, lung adenocarcinoma and colon cancer, patients with iCAM+ tumors had significantly better response to immune checkpoint therapy compared to those with iCAM- tumors. ROC analysis using TCGA predictions as gold standard showed that iCAM+ tumors are accurately identifiable using clinical sequencing assays, such as FoundationOne or StrandAdvantage. Using the FoundationOne derived threshold, analysis of 113 melanoma tumors, showed that iCAM+ patients have significantly better response to immune checkpoint therapy. iCAM+ and iCAM- tumors have distinct mutation patterns and different immune microenvironments. CONCLUSION: In 8 solid cancers, a mutational burden threshold exists that may predict response to immune checkpoint blockade. This threshold is identifiable using available clinical sequencing assays.

Immune activation and response to pembrolizumab in POLE-mutant endometrial cancer.

Antibodies that target the immune checkpoint receptor programmed cell death protein 1 (PD-1) have resulted in prolonged and beneficial responses toward a variety of human cancers. However, anti-PD-1 therapy in some patients provides no benefit and/or results in adverse side effects. The factors that determine whether patients will be drug sensitive or resistant are not fully understood; therefore, genomic assessment of exceptional responders can provide important insight into patient response. Here, we identified a patient with endometrial cancer who had an exceptional response to the anti-PD-1 antibody pembrolizumab. Clinical grade targeted genomic profiling of a pretreatment tumor sample from this individual identified a mutation in DNA polymerase epsilon (POLE) that associated with an ultramutator phenotype. Analysis of The Cancer Genome Atlas (TCGA) revealed that the presence of POLE mutation associates with high mutational burden and elevated expression of several immune checkpoint genes. Together, these data suggest that cancers harboring POLE mutations are good candidates for immune checkpoint inhibitor therapy.

Glutaminase 2 is a novel negative regulator of small GTPase Rac1 and mediates p53 function in suppressing metastasis.

Glutaminase (GLS) isoenzymes GLS1 and GLS2 are key enzymes for glutamine metabolism. Interestingly, GLS1 and GLS2 display contrasting functions in tumorigenesis with elusive mechanism; GLS1 promotes tumorigenesis, whereas GLS2 exhibits a tumor-suppressive function. In this study, we found that GLS2 but not GLS1 binds to small GTPase Rac1 and inhibits its interaction with Rac1 activators guanine-nucleotide exchange factors, which in turn inhibits Rac1 to suppress cancer metastasis. This function of GLS2 is independent of GLS2 glutaminase activity. Furthermore, decreased GLS2 expression is associated with enhanced metastasis in human cancer. As a p53 target, GLS2 mediates p53's function in metastasis suppression through inhibiting Rac1. In summary, our results reveal that GLS2 is a novel negative regulator of Rac1, and uncover a novel function and mechanism whereby GLS2 suppresses metastasis. Our results also elucidate a novel mechanism that contributes to the contrasting functions of GLS1 and GLS2 in tumorigenesis.

Expression of an estrogen-regulated variant transcript of the peroxisomal branched chain fatty acid oxidase ACOX2 in breast carcinomas.

BACKGROUND: Alternate transcripts from a single gene locus greatly enhance the combinatorial flexibility of the human transcriptome. Different patterns of exon usage have been observed when comparing normal tissue to cancers, suggesting that variant transcripts may play a role in the tumor phenotype. METHODS: Ribonucleic acid-sequencing (RNA-seq) data from breast cancer samples was used to identify an intronic start variant transcript of Acyl-CoA oxidase 2, ACOX2 (ACOX2-i9). Difference in expression between Estrogen Receptor (ER) positive and ER negative patients was assessed by the Wilcoxon rank sum test, and the findings validated in The Cancer Genome Atlas (TCGA) breast cancer dataset (BRCA). ACOX2-i9 expression was also assessed in cell lines using both quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) and Western blot analysis. Knock down by short hairpin RNA (shRNA) and colony formation assays were used to determine whether ACOX2-i9 expression would influence cellular fitness. The effect of ACOX2-i9 expression on patient survival was assessed by the Kaplan-Meier survival function, and association to clinical parameters was analyzed using a Fisher exact test. RESULTS: The expression and translation of ACOX2-i9 into a 25 kDa protein was demonstrated in HepG2 cells as well as in several breast cancer cell lines. shRNA knock down of the ACOX2-i9 variant resulted in decreased cell viability of T47D and MDA-MB 436 cells. Moreover, expression of ACOX2-i9 was shown to be estrogen regulated, being induced by propyl pyrazoletriol and inhibited by tamoxifen and fulvestrant in ER+ T47D and Mcf-7 cells, but not in the ER- MDA-MB 436 cell line. This variant transcript showed expression predominantly in ER-positive breast tumors as assessed in our initial set of 53 breast cancers and further validated in 87 tumor/normal pairs from the TCGA breast cancer dataset, and expression was associated with better outcome in ER positive patients. CONCLUSIONS: ACOX2-i9 is specifically enriched in ER+ breast cancers where expression of the variant is associated with improved outcome. These data identify variant ACOX2 as a potential novel therapeutic biomarker in ER+ breast tumors.

Differential regulation of antagonistic pleiotropy in synthetic and natural populations suggests its role in adaptation.

Antagonistic pleiotropy (AP), the ability of a gene to show opposing effects in different phenotypes, has been identified in various life history traits and complex disorders, indicating its fundamental role in balancing fitness over the course of evolution. It is intuitive that natural selection might maintain AP to allow organisms phenotypic flexibility in different environments. However, despite several attempts, little evidence exists for its role in adaptation. We performed a meta-analysis in yeast to identify the genetic basis of AP in bi-parental segregants, natural isolates, and a laboratory strain genome-wide deletion collection, by comparing growth in favorable and stress conditions. We found that whereas AP was abundant in the synthetic populations, it was absent in the natural isolates. This finding indicated resolution of trade-offs, i.e., mitigation of trade-offs over evolutionary history, probably through accumulation of compensatory mutations. In the deletion collection, organizational genes showed AP, suggesting ancient resolutions of trade-offs in the basic cellular pathways. We find abundant AP in the segregants, greater than estimated in the deletion collection or observed in previous studies, with IRA2, a negative regulator of the Ras/PKA signaling pathway, showing trade-offs across diverse environments. Additionally, IRA2 and several other Ras/PKA pathway genes showed balancing selection in isolates of S. cerevisiae and S. paradoxus, indicating that multiple alleles maintain AP in this pathway in natural populations. We propose that during AP resolution, retaining the ability to vary signaling pathways such as Ras/PKA, may provide organisms with phenotypic flexibility. However, with increasing organismal complexity AP resolution may become difficult. A partial resolution of AP could manifest as complex human diseases, and the inability to resolve AP may play a role in speciation. Our findings suggest that testing a universal phenomenon like AP across multiple experimental systems may elucidate mechanisms underlying its regulation and evolution.

IRF5 is a novel regulator of CXCL13 expression in breast cancer that regulates CXCR5(+) B- and T-cell trafficking to tumor-conditioned media.

Clinical studies using prognostic and predictive signatures have shown that an immune signal emanating from whole tumors reflects the level of immune cell infiltration--a high immune signal linked to improved outcome. Factors regulating immune cell trafficking to the tumor, however, are not known. Previous work has shown that expression of interferon regulatory factor 5 (IRF5), a critical immune regulator, is lost in ~80% of invasive ductal carcinomas examined. We postulated that IRF5-positive and -negative breast tumors would differentially regulate immune cell trafficking to the tumor. Using a focused tumor inflammatory array, differences in cytokine and chemokine expression were examined between IRF5-positive and -negative MDA-MB-231 cells grown in three-dimensional culture. A number of cytokines/chemokines were found to be dysregulated between cultures. CXCL13 was identified as a direct target of IRF5 resulting in the enhanced recruitment of B and T cells to IRF5-positive tumor-conditioned media. The ability of IRF5 to regulate mediators of cell migration was confirmed by enzyme-linked immunosorbent assay, chromatin immunoprecipitation assay, small interfering RNA knockdown and immunofluorescence staining of human breast tumor tissues. Analysis of primary immune cell subsets revealed that IRF5 specifically recruits CXCR5(+) B and T cells to the tumor; CXCR5 is the receptor for CXCL13. Analysis of primary breast tumor tissues revealed a significant correlation between IRF5 and CXCL13 expression providing clinical relevance to the study. Together, these data support that IRF5 directly regulates a network of genes that shapes a tumor immune response and may, in combination with CXCL13, serve as a novel prognostic marker for antitumor immunity.

Inter-species prediction of protein phosphorylation in the sbv IMPROVER species translation challenge.

MOTIVATION: Animal models are widely used in biomedical research for reasons ranging from practical to ethical. An important issue is whether rodent models are predictive of human biology. This has been addressed recently in the framework of a series of challenges designed by the systems biology verification for Industrial Methodology for Process Verification in Research (sbv IMPROVER) initiative. In particular, one of the sub-challenges was devoted to the prediction of protein phosphorylation responses in human bronchial epithelial cells, exposed to a number of different chemical stimuli, given the responses in rat bronchial epithelial cells. Participating teams were asked to make inter-species predictions on the basis of available training examples, comprising transcriptomics and phosphoproteomics data. RESULTS: Here, the two best performing teams present their data-driven approaches and computational methods. In addition, post hoc analyses of the datasets and challenge results were performed by the participants and challenge organizers. The challenge outcome indicates that successful prediction of protein phosphorylation status in human based on rat phosphorylation levels is feasible. However, within the limitations of the computational tools used, the inclusion of gene expression data does not improve the prediction quality. The post hoc analysis of time-specific measurements sheds light on the signaling pathways in both species. AVAILABILITY AND IMPLEMENTATION: A detailed description of the dataset, challenge design and outcome is available at www.sbvimprover.com. The code used by team IGB is provided under http://github.com/uci-igb/improver2013. Implementations of the algorithms applied by team AMG are available at http://bhanot.biomaps.rutgers.edu/wiki/AMG-sc2-code.zip. CONTACT: meikelbiehl@gmail.com.

Inter-species inference of gene set enrichment in lung epithelial cells from proteomic and large transcriptomic datasets.

MOTIVATION: Translating findings in rodent models to human models has been a cornerstone of modern biology and drug development. However, in many cases, a naive 'extrapolation' between the two species has not succeeded. As a result, clinical trials of new drugs sometimes fail even after considerable success in the mouse or rat stage of development. In addition to in vitro studies, inter-species translation requires analytical tools that can predict the enriched gene sets in human cells under various stimuli from corresponding measurements in animals. Such tools can improve our understanding of the underlying biology and optimize the allocation of resources for drug development. RESULTS: We developed an algorithm to predict differential gene set enrichment as part of the sbv IMPROVER (systems biology verification in Industrial Methodology for Process Verification in Research) Species Translation Challenge, which focused on phosphoproteomic and transcriptomic measurements of normal human bronchial epithelial (NHBE) primary cells under various stimuli and corresponding measurements in rat (NRBE) primary cells. We find that gene sets exhibit a higher inter-species correlation compared with individual genes, and are potentially more suited for direct prediction. Furthermore, in contrast to a similar cross-species response in protein phosphorylation states 5 and 25 min after exposure to stimuli, gene set enrichment 6 h after exposure is significantly different in NHBE cells compared with NRBE cells. In spite of this difference, we were able to develop a robust algorithm to predict gene set activation in NHBE with high accuracy using simple analytical methods. AVAILABILITY AND IMPLEMENTATION: Implementation of all algorithms is available as source code (in Matlab) at http://bhanot.biomaps.rutgers.edu/wiki/codes_SC3_Predicting_GeneSets.zip, along with the relevant data used in the analysis. Gene sets, gene expression and protein phosphorylation data are available on request. CONTACT: hormoz@kitp.ucsb.edu.