Systems medicine dissection of chr1q-amp reveals a novel PBX1-FOXM1 axis for targeted therapy in multiple myeloma.

Understanding the biological and clinical impact of copy number aberrations (CNAs) on the development of precision therapies in cancer remains an unmet challenge. Genetic amplification of chromosome 1q (chr1q-amp) is a major CNA conferring an adverse prognosis in several types of cancer, including in the blood cancer multiple myeloma (MM). Although several genes across chromosome 1 (chr1q) portend high-risk MM disease, the underpinning molecular etiology remains elusive. Here, with reference to the 3-dimensional (3D) chromatin structure, we integrate multi-omics data sets from patients with MM with genetic variables to obtain an associated clinical risk map across chr1q and to identify 103 adverse prognosis genes in chr1q-amp MM. Prominent among these genes, the transcription factor PBX1 is ectopically expressed by genetic amplification and epigenetic activation of its own preserved 3D regulatory domain. By binding to reprogrammed superenhancers, PBX1 directly regulates critical oncogenic pathways and a FOXM1-dependent transcriptional program. Together, PBX1 and FOXM1 activate a proliferative gene signature that predicts adverse prognosis across multiple types of cancer. Notably, pharmacological disruption of the PBX1-FOXM1 axis with existing agents (thiostrepton) and a novel PBX1 small molecule inhibitor (T417) is selectively toxic against chr1q-amp myeloma and solid tumor cells. Overall, our systems medicine approach successfully identifies CNA-driven oncogenic circuitries, links them to clinical phenotypes, and proposes novel CNA-targeted therapy strategies in MM and other types of cancer.

ARID1A Regulates Progesterone Receptor Expression in Early Endometrial Endometrioid Carcinoma Pathogenesis.

Loss of progesterone receptor (PR) expression is an established risk factor for unresponsiveness to progesterone therapy in patients with endometrial atypical hyperplasia and endometrioid carcinoma. ARID1A is one of the most commonly mutated genes in endometrioid carcinomas, and the loss of its expression is associated with tumor progression. In this study, we investigated the roles of ARID1A deficiency in PR expression in human and murine endometrial epithelial neoplasia. An analysis of genome-wide chromatin immunoprecipitation sequencing in isogenic ARID1A-/- and ARID1A+/+ human endometrial epithelial cells revealed that ARID1A-/- cells showed significantly reduced chromatin immunoprecipitation sequencing signals for ARID1A, BRG1, and H3K27AC in the PgR enhancer region. We then performed immunohistochemistry to correlate the protein expression levels of ARID1A, estrogen receptor, and PR in 50 human samples of endometrial atypical hyperplasia and 75 human samples of endometrial carcinomas. The expression levels of PR but not were significantly lower in ARID1A-deficient low-grade endometrial carcinomas and atypical hyperplasia (P = .0002). When Pten and Pten/Arid1a conditional knockout murine models were used, Pten-/-;Arid1a-/- mice exhibited significantly decreased epithelial PR expression in endometrial carcinomas (P = .003) and atypical hyperplasia (P < .0001) compared with that in the same tissues from Pten-/-;Arid1a+/+ mice. Our data suggest that the loss of ARID1A expression, as occurs in ARID1A-mutated endometrioid carcinomas, decreases PgR transcription by modulating the PgR enhancer region during early tumor development.

ARID1A loss activates MAPK signaling via DUSP4 downregulation.

BACKGROUND: ARID1A, a tumor suppressor gene encoding BAF250, a protein participating in chromatin remodeling, is frequently mutated in endometrium-related malignancies, including ovarian or uterine clear cell carcinoma (CCC) and endometrioid carcinoma (EMCA). However, how ARID1A mutations alter downstream signaling to promote tumor development is yet to be established. METHODS: We used RNA-sequencing (RNA-seq) to explore transcriptomic changes in isogenic human endometrial epithelial cells after deleting ARID1A. Chromatin immunoprecipitation sequencing (ChIP-seq) was employed to assess the active or repressive histone marks on DUSP4 promoter and regulatory regions. We validated our findings using genetically engineered murine endometroid carcinoma models, human endometroid carcinoma tissues, and in silico approaches. RESULTS: RNA-seq revealed the downregulation of the MAPK phosphatase dual-specificity phosphatase 4 (DUSP4) in ARID1A-deficient cells. ChIP-seq demonstrated decreased histone acetylation marks (H3K27Ac, H3K9Ac) on DUSP4 regulatory regions as one of the causes for DUSP4 downregulation in ARID1A-deficient cells. Ectopic DUSP4 expression decreased cell proliferation, and pharmacologically inhibiting the MAPK pathway significantly mitigated tumor formation in vivo. CONCLUSIONS: Our findings suggest that ARID1A protein transcriptionally modulates DUSP4 expression by remodeling chromatin, subsequently inactivating the MAPK pathway, leading to tumor suppression. The ARID1A-DUSP4-MAPK axis may be further considered for developing targeted therapies against ARID1A-mutated cancers.

Assessing aneuploidy with repetitive element sequencing.

We report a sensitive PCR-based assay called Repetitive Element AneupLoidy Sequencing System (RealSeqS) that can detect aneuploidy in samples containing as little as 3 pg of DNA. Using a single primer pair, we amplified ∼350,000 amplicons distributed throughout the genome. Aneuploidy was detected in 49% of liquid biopsies from a total of 883 nonmetastatic, clinically detected cancers of the colorectum, esophagus, liver, lung, ovary, pancreas, breast, or stomach. Combining aneuploidy with somatic mutation detection and eight standard protein biomarkers yielded a median sensitivity of 80% in these eight cancer types, while only 1% of 812 healthy controls scored positive.

IntAPT: integrated assembly of phenotype-specific transcripts from multiple RNA-seq profiles.

MOTIVATION: High-throughput RNA sequencing has revolutionized the scope and depth of transcriptome analysis. Accurate reconstruction of a phenotype-specific transcriptome is challenging due to the noise and variability of RNA-seq data. This requires computational identification of transcripts from multiple samples of the same phenotype, given the underlying consensus transcript structure. RESULTS: We present a Bayesian method, integrated assembly of phenotype-specific transcripts (IntAPT), that identifies phenotype-specific isoforms from multiple RNA-seq profiles. IntAPT features a novel two-layer Bayesian model to capture the presence of isoforms at the group layer and to quantify the abundance of isoforms at the sample layer. A spike-and-slab prior is used to model the isoform expression and to enforce the sparsity of expressed isoforms. Dependencies between the existence of isoforms and their expression are modeled explicitly to facilitate parameter estimation. Model parameters are estimated iteratively using Gibbs sampling to infer the joint posterior distribution, from which the presence and abundance of isoforms can reliably be determined. Studies using both simulations and real datasets show that IntAPT consistently outperforms existing methods for the IntAPT. Experimental results demonstrate that, despite sequencing errors, IntAPT exhibits a robust performance among multiple samples, resulting in notably improved identification of expressed isoforms of low abundance. AVAILABILITY AND IMPLEMENTATION: The IntAPT package is available at http://github.com/henryxushi/IntAPT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Origin of Ovarian Cancer Species and Precancerous Landscape.

Unlike other human cancers, in which all primary tumors arise de novo, ovarian epithelial cancers are primarily imported from either endometrial or fallopian tube epithelium. The prevailing paradigm in the genesis of high-grade serous carcinoma (HGSC), the most common ovarian cancer, posits to its development in fallopian tubes through stepwise tumor progression. Recent progress has been made not only in gathering terabytes of omics data but also in detailing the histologic-molecular correlations required for looking into, and making sense of, the tissue origin of HGSC. This emerging paradigm is changing many facets of ovarian cancer research and routine gynecology practice. The precancerous landscape in fallopian tubes contains multiple concurrent precursor lesions, including serous tubal intraepithelial carcinoma (STIC), with genetic heterogeneity providing a platform for HGSC evolution. Mathematical models imply that a prolonged time (decades) elapses from the development of a TP53 mutation, the earliest known molecular alteration, to an STIC, followed by a shorter span (6 years) for progression to an HGSC. Genetic predisposition accelerates the trajectory. This timeline may allow for the early diagnosis of HGSC and STIC, followed by intent-to-cure surgery. This review discusses the recent advances in this tubal paradigm and its biological and clinical implications, alongside the promise and challenge of studying STIC and other precancerous lesions of HGSC.

Treating ARID1A mutated cancers by harnessing synthetic lethality and DNA damage response.

Chromatin remodeling is an essential cellular process for organizing chromatin structure into either open or close configuration at specific chromatin locations by orchestrating and modifying histone complexes. This task is responsible for fundamental cell physiology including transcription, DNA replication, methylation, and damage repair. Aberrations in this activity have emerged as epigenomic mechanisms in cancer development that increase tumor clonal fitness and adaptability amidst various selection pressures. Inactivating mutations in AT-rich interaction domain 1A (ARID1A), a gene encoding a large nuclear protein member belonging to the SWI/SNF chromatin remodeling complex, result in its loss of expression. ARID1A is the most commonly mutated chromatin remodeler gene, exhibiting the highest mutation frequency in endometrium-related uterine and ovarian carcinomas. As a tumor suppressor gene, ARID1A is essential for regulating cell cycle, facilitating DNA damage repair, and controlling expression of genes that are essential for maintaining cellular differentiation and homeostasis in non-transformed cells. Thus, ARID1A deficiency due to somatic mutations propels tumor progression and dissemination. The recent success of PARP inhibitors in treating homologous recombination DNA repair-deficient tumors has engendered keen interest in developing synthetic lethality-based therapeutic strategies for ARID1A-mutated neoplasms. In this review, we summarize recent advances in understanding the biology of ARID1A in cancer development, with special emphasis on its roles in DNA damage repair. We also discuss strategies to harness synthetic lethal mechanisms for future therapeutics against ARID1A-mutated cancers.

Mutation and methylation profiles of ectopic and eutopic endometrial tissues.

Adenomyosis and peritoneal endometriosis are common gynecologic lesions; they are characterized by aberrant locations of normal-appearing endometrium in myometrium and peritoneal surface, respectively. Both ectopic lesions are speculated to originate from uterine eutopic endometrium, which is composed of epithelium and stroma, but how these two different tissue types co-evolve in ectopic locations remains unclear. Here, we analyzed exome-wide mutations and global methylation in microdissected epithelium and stroma separately in paired adenomyosis, peritoneal endometriosis, and endometrium to investigate their relationship. Analyses of somatic mutations and their allele frequencies indicate monoclonal development not only in epithelium but also in the stroma of adenomyosis and peritoneal endometriosis. Our preliminary phylogenetic study suggests a plausible clonal derivation in epithelium and stroma of both ectopic and eutopic endometrium from the same founder epithelium-stroma progenitor cells. While a patient-specific methylation landscape is evident, adenomyosis epithelium and stroma can be distinguished from normal-appearing eutopic endometrium epigenetically. In summary, endometrial stroma, like its epithelial counterpart, could be clonal and both ectopic and eutopic endometrium following divergent evolutionary trajectories. Our data also warrant future investigations into the role of endometrial stroma in the pathobiology of endometrium-related disorders. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Genome-wide mutation analysis in precancerous lesions of endometrial carcinoma.

Clinicopathological evidence supports endometrial atypical hyperplasia (AH) or endometrial intraepithelial neoplasia as the precursor of uterine endometrioid carcinoma (EC), the most common gynecologic malignancy. However, the pathogenic progression from AH to EC remains unclear. Here, we employed whole-exome sequencing to identify somatic mutations and copy number changes in micro-dissected lesions from 30 pairs of newly diagnosed AH and EC. We found that all but one pair of AHs shared the same DNA mismatch repair status as their corresponding ECs. The percentage of common mutations between AH lesions and corresponding ECs varied significantly, ranging from 0.1% to 82%. Microsatellite stable AHs had fewer cancer driver mutations than ECs (5 versus 7, p = 0.017), but among microsatellite unstable AHs and ECs there was no difference in mutational numbers (36 versus 38, p = 0.65). As compared to AH specimens, 19 (79%) of 24 microsatellite stable EC tumors gained new cancer driver mutations, most of which involved PTEN, ARID1A, PIK3CA, CTNNB1, or CHD4. Our results suggest that some AH lesions are the immediate precursor of ECs, and progression depends on acquisition of additional cancer driver mutations. However, a complex clonal relationship between AH and EC can also be appreciated, as in some cases both lesions diverge very early or arise independently, thus co-developing with distinct genetic trajectories. Our genome-wide profile of mutations in AH and EC shines new light on the molecular landscape of tumor progression. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A novel human endometrial epithelial cell line for modeling gynecological diseases and for drug screening.

Endometrium-related malignancies including uterine endometrioid carcinoma, ovarian clear cell carcinoma and ovarian endometrioid carcinoma are major types of gynecologic cancer, claiming more than 13,000 women's lives annually in the United States. In vitro cell models that recapitulate "normal" endometrial epithelial cells and their malignant counterparts are critically needed to facilitate the studies of pathogenesis in endometrium-related carcinomas. To achieve this objective, we have established a human endometrial epithelial cell line, hEM3, through immortalization and clonal selection from a primary human endometrium culture. hEM3 exhibits stable growth in vitro without senescence. hEM3 expresses protein markers characteristic of the endometrial epithelium, and they include PAX8, EpCAM, cytokeratin 7/8, and ER. hEM3 does not harbor pathogenic germline mutations in genes involving DNA mismatch repair (MMR) or homologous repair (HR) pathways. Despite its unlimited capacity of in vitro proliferation, hEM3 cells are not transformed, as they are not tumorigenic in immunocompromised mice. The cell line is amenable for gene editing, and we have established several gene-specific knockout clones targeting ARID1A, a tumor suppressor gene involved in the SWI/SNF chromatin remodeling. Drug screening demonstrates that both HDAC inhibitor and PARP inhibitor are effective in targeting cells with ARID1A deletion. Together, our data support the potential of hEM3 as a cell line model for studying the pathobiology of endometrium-related diseases and for developing effective precision therapies.

Proteome-wide Tyrosine Phosphorylation Analysis Reveals Dysregulated Signaling Pathways in Ovarian Tumors.

The recent accomplishment of comprehensive proteogenomic analysis of high-grade serous ovarian carcinoma (HGSOC) tissues reveals cancer associated molecular alterations were not limited to variations among DNA, and mRNA/protein expression, but are a result of complex reprogramming of signaling pathways/networks mediated by the protein and post-translational modification (PTM) interactomes. A systematic, multiplexed approach interrogating enzyme-substrate relationships in the context of PTMs is fundamental in understanding the dynamics of these pathways, regulation of cellular processes, and their roles in disease processes. Here, as part of Clinical Proteomic Tumor Analysis Consortium (CPTAC) project, we established a multiplexed PTM assay (tyrosine phosphorylation, and lysine acetylation, ubiquitylation and SUMOylation) method to identify protein probes' PTMs on the human proteome array. Further, we focused on the tyrosine phosphorylation and identified 19 kinases are potentially responsible for the dysregulated signaling pathways observed in HGSOC. Additionally, elevated kinase activity was observed when 14 ovarian cancer cell lines or tumor tissues were subjected to test the autophosphorylation status of PTK2 (pY397) and PTK2B (pY402) as a proxy for kinase activity. Taken together, this report demonstrates that PTM signatures based on lysate reactions on human proteome array is a powerful, unbiased approach to identify dysregulated PTM pathways in tumors.

Cancer-Associated Mutations in Endometriosis without Cancer.

BACKGROUND: Endometriosis, defined as the presence of ectopic endometrial stroma and epithelium, affects approximately 10% of reproductive-age women and can cause pelvic pain and infertility. Endometriotic lesions are considered to be benign inflammatory lesions but have cancerlike features such as local invasion and resistance to apoptosis. METHODS: We analyzed deeply infiltrating endometriotic lesions from 27 patients by means of exomewide sequencing (24 patients) or cancer-driver targeted sequencing (3 patients). Mutations were validated with the use of digital genomic methods in microdissected epithelium and stroma. Epithelial and stromal components of lesions from an additional 12 patients were analyzed by means of a droplet digital polymerase-chain-reaction (PCR) assay for recurrent activating KRAS mutations. RESULTS: Exome sequencing revealed somatic mutations in 19 of 24 patients (79%). Five patients harbored known cancer driver mutations in ARID1A, PIK3CA, KRAS, or PPP2R1A, which were validated by Safe-Sequencing System or immunohistochemical analysis. The likelihood of driver genes being affected at this rate in the absence of selection was estimated at P=0.001 (binomial test). Targeted sequencing and a droplet digital PCR assay identified KRAS mutations in 2 of 3 patients and 3 of 12 patients, respectively, with mutations in the epithelium but not the stroma. One patient harbored two different KRAS mutations, c.35G→T and c.35G→C, and another carried identical KRAS c.35G→A mutations in three distinct lesions. CONCLUSIONS: We found that lesions in deep infiltrating endometriosis, which are associated with virtually no risk of malignant transformation, harbor somatic cancer driver mutations. Ten of 39 deep infiltrating lesions (26%) carried driver mutations; all the tested somatic mutations appeared to be confined to the epithelial compartment of endometriotic lesions.

Long Interspersed Nuclear Element 1 Retrotransposons Become Deregulated during the Development of Ovarian Cancer Precursor Lesions.

There is growing evidence that most high-grade serous ovarian carcinomas likely arise from local dissemination of precursor lesions of the fallopian tube. Evolution of these lesions from early p53 signatures to latter-stage, serous tubal intraepithelial carcinomas (STICs) is characterized by cytologic atypia, accumulation of somatic mutations, and genomic instability, the etiologies of which remain unclear. Long interspersed element 1 (LINE-1) retrotransposon is expressed in many carcinomas, including high-grade serous ovarian carcinoma, where it contributes to genomic instability; however, the timing of LINE-1 activation during this evolution has yet to be elucidated. In this study, we assessed LINE-1 open reading frame 1 protein expression in 12 p53 signature lesions, 32 STICs, and 112 various types of ovarian cancers via immunohistochemical staining and examined LINE-1 promoter methylation in representative cases. We found that 78% and 57% of STICs, with and without concurrent ovarian carcinomas, respectively, exhibited intense LINE-1 immunoreactivity compared with adjacent, normal-appearing fallopian tube epithelium. Hypomethylation of the LINE-1 promoter was found in all STICs exhibiting overexpression. None of the 12 p53 signatures demonstrated significant LINE-1 expression. In ovarian cancer, 84 (75%) of 112 ovarian carcinomas overexpressed LINE-1. Our results indicate that LINE-1 retrotransposons often become deregulated during progression of ovarian cancer precursor lesions from the p53 signature to STIC stages and remain highly expressed in carcinoma.

Molecular Classification and Emerging Targeted Therapy in Endometrial Cancer.

Recent advances in molecular studies, especially genome-wide analyses, have revealed the landscape of genomic alterations present in endometrial carcinomas, and have provided valuable insight into the pathogenesis of this disease. The current challenges are in developing a molecular-morphologic classification system to enhance traditional pathologic diagnosis and in determining the optimal approach to using this new information to guide clinical management. Molecular assays may be particularly beneficial in allowing the earlier detection of endometrial cancer or precursor lesions and in guiding personalized treatment approaches. In this review, we describe the current molecular landscape of endometrial cancers, efforts underway to incorporate molecular alterations into the current classification systems, and the development of diagnostic tools for the early detection of endometrial cancer. Finally, we present opportunities for using these data to tailor therapeutic strategies. A comprehensive understanding of the molecular alterations responsible for the origination, relapse, and resistance patterns of this disease will ultimately improve outcomes for patients with endometrial cancer.

Genomic landscape and evolutionary trajectories of ovarian cancer precursor lesions.

The clonal relationship between ovarian high-grade serous carcinoma (HGSC) and its presumed precursor lesion, serous tubal intraepithelial carcinoma (STIC), has been reported. However, when analyzing patients with concurrent ovarian carcinoma and tubal lesion, the extensive carcinoma tissues present at diagnosis may have effaced the natural habitat of precursor clone(s), obscuring tumor clonal evolutionary history, or may have disseminated to anatomically adjacent fimbriae ends, masquerading as precursor lesions. To circumvent these limitations, we analyzed the genomic landscape of incidental tubal precursor lesions including p53 signature, dormant STIC or serous tubal intraepithelial lesion (STIL) and proliferative STIC in women without ovarian carcinoma or any cancer diagnosis using whole-exome sequencing and amplicon sequencing. In three of the four cancer-free women with multiple discrete tubal lesions we observed non-identical TP53 mutations between precursor lesions from the same individual. In one of the four women with co-existing ovarian HGSC and tubal precursor lesion we found non-identical TP53 mutations and a lack of common mutations shared between her precursor lesion and carcinoma. Analyzing the evolutionary history of multiple tubal lesions in the same four patients with concurrent ovarian carcinoma indicated distinct evolution trajectories. Collectively, the results support diverse clonal origins of tubal precursor lesions at the very early stages of tumorigenesis. Mathematical modeling based on lesion-specific proliferation rates indicated that p53 signature and dormant STIC may take a prolonged time (two decades or more) to develop into STIC, whereas STIC may progress to carcinoma in a much shorter time (6 years). The above findings may have implications for future research aimed at prevention and early detection of ovarian cancer. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Human transposon insertion profiling: Analysis, visualization and identification of somatic LINE-1 insertions in ovarian cancer.

Mammalian genomes are replete with interspersed repeats reflecting the activity of transposable elements. These mobile DNAs are self-propagating, and their continued transposition is a source of both heritable structural variation as well as somatic mutation in human genomes. Tailored approaches to map these sequences are useful to identify insertion alleles. Here, we describe in detail a strategy to amplify and sequence long interspersed element-1 (LINE-1, L1) retrotransposon insertions selectively in the human genome, transposon insertion profiling by next-generation sequencing (TIPseq). We also report the development of a machine-learning-based computational pipeline, TIPseqHunter, to identify insertion sites with high precision and reliability. We demonstrate the utility of this approach to detect somatic retrotransposition events in high-grade ovarian serous carcinoma.

Epigenetic therapy activates type I interferon signaling in murine ovarian cancer to reduce immunosuppression and tumor burden.

Ovarian cancer is the most lethal of all gynecological cancers, and there is an urgent unmet need to develop new therapies. Epithelial ovarian cancer (EOC) is characterized by an immune suppressive microenvironment, and response of ovarian cancers to immune therapies has thus far been disappointing. We now find, in a mouse model of EOC, that clinically relevant doses of DNA methyltransferase and histone deacetylase inhibitors (DNMTi and HDACi, respectively) reduce the immune suppressive microenvironment through type I IFN signaling and improve response to immune checkpoint therapy. These data indicate that the type I IFN response is required for effective in vivo antitumorigenic actions of the DNMTi 5-azacytidine (AZA). Through type I IFN signaling, AZA increases the numbers of CD45+ immune cells and the percentage of active CD8+ T and natural killer (NK) cells in the tumor microenvironment, while reducing tumor burden and extending survival. AZA also increases viral defense gene expression in both tumor and immune cells, and reduces the percentage of macrophages and myeloid-derived suppressor cells in the tumor microenvironment. The addition of an HDACi to AZA enhances the modulation of the immune microenvironment, specifically increasing T and NK cell activation and reducing macrophages over AZA treatment alone, while further increasing the survival of the mice. Finally, a triple combination of DNMTi/HDACi plus the immune checkpoint inhibitor α-PD-1 provides the best antitumor effect and longest overall survival, and may be an attractive candidate for future clinical trials in ovarian cancer.

T cell-inflamed phenotype and increased Foxp3 expression in infiltrating T-cells of mismatch-repair deficient endometrial cancers.

Mismatch repair-deficient endometrial cancers have a high somatic mutation burden, suggesting that patients with these tumors may benefit from immunotherapy. Elucidating the immune suppressive mechanisms of mismatch repair-deficient endometrial cancers is fundamental to developing future immune-based interventions. This study aimed to determine the immune cell populations associated with mismatch repair-deficient endometrial cancers, especially focusing on targetable regulatory pathways of the immune response. A total of 76 endometrial cancer hysterectomy specimens were evaluated for tumor-infiltrating immune cells by immunohistochemistry. Immune specific markers were used to evaluate each specimen for the number of CD8 + cytotoxic T lymphocytes, forkhead-box P3 (FoxP3) + regulatory T cells, CD68 + tumor-associated macrophages, as well as programmed death-1 (PD-1) + immune cells, and the percentage of programmed death ligand-1 (PD-L1) + immune cells. Mismatch repair-deficient tumors exhibited a significantly higher number of CD8 + cytotoxic T lymphocytes (p = 0.0006), FoxP3 + regulatory T cells (p = 0.0003), PD-1 + immune cells (p = 0.0069), and a higher percentage of PD-L1 + immune cells (p = 0.0007) occupying the tumor compared to mismatch repair-proficient endometrial cancers. There was no significant difference in CD68 + tumor-associated macrophages infiltration between the two groups. Endometrial cancers with tumor PD-L1 expression also showed significantly increased infiltration of CD8 + cytotoxic T lymphocytes (p = 0.0002), FoxP3 + regulatory T cells (p = 0.0003), PD-1 + immune cells (p < 0.0001), and PD-L1 + immune cells (p < 0.0001). Endometrial cancers showing mismatch repair-deficiency and PD-L1 expression in tumor cells exhibit a prominent T cell-inflamed phenotype. More importantly, the increased number of FoxP3 + regulatory T cells in mismatch repair-deficient endometrial cancers suggests that combination therapy by targeting both regulatory T cells and immune checkpoints may be warranted to improve clinical efficacy.

SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data.

Motivation: Recent advances in high-throughput RNA sequencing (RNA-seq) technologies have made it possible to reconstruct the full transcriptome of various types of cells. It is important to accurately assemble transcripts or identify isoforms for an improved understanding of molecular mechanisms in biological systems. Results: We have developed a novel Bayesian method, SparseIso, to reliably identify spliced isoforms from RNA-seq data. A spike-and-slab prior is incorporated into the Bayesian model to enforce the sparsity for isoform identification, effectively alleviating the problem of overfitting. A Gibbs sampling procedure is further developed to simultaneously identify and quantify transcripts from RNA-seq data. With the sampling approach, SparseIso estimates the joint distribution of all candidate transcripts, resulting in a significantly improved performance in detecting lowly expressed transcripts and multiple expressed isoforms of genes. Both simulation study and real data analysis have demonstrated that the proposed SparseIso method significantly outperforms existing methods for improved transcript assembly and isoform identification. Availability and implementation: The SparseIso package is available at http://github.com/henryxushi/SparseIso. Contact: xuan@vt.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

CRNET: an efficient sampling approach to infer functional regulatory networks by integrating large-scale ChIP-seq and time-course RNA-seq data.

Motivation: NGS techniques have been widely applied in genetic and epigenetic studies. Multiple ChIP-seq and RNA-seq profiles can now be jointly used to infer functional regulatory networks (FRNs). However, existing methods suffer from either oversimplified assumption on transcription factor (TF) regulation or slow convergence of sampling for FRN inference from large-scale ChIP-seq and time-course RNA-seq data. Results: We developed an efficient Bayesian integration method (CRNET) for FRN inference using a two-stage Gibbs sampler to estimate iteratively hidden TF activities and the posterior probabilities of binding events. A novel statistic measure that jointly considers regulation strength and regression error enables the sampling process of CRNET to converge quickly, thus making CRNET very efficient for large-scale FRN inference. Experiments on synthetic and benchmark data showed a significantly improved performance of CRNET when compared with existing methods. CRNET was applied to breast cancer data to identify FRNs functional at promoter or enhancer regions in breast cancer MCF-7 cells. Transcription factor MYC is predicted as a key functional factor in both promoter and enhancer FRNs. We experimentally validated the regulation effects of MYC on CRNET-predicted target genes using appropriate RNAi approaches in MCF-7 cells. Availability and implementation: R scripts of CRNET are available at http://www.cbil.ece.vt.edu/software.htm. Contact: xuan@vt.edu. Supplementary information: Supplementary data are available at Bioinformatics online.