Comprehensive Assessment of the Intrinsic Pancreatic Microbiome.

OBJECTIVE: We sought to comprehensively profile tissue and cyst fluid in patients with benign, precancerous, and cancerous conditions of the pancreas to characterize the intrinsic pancreatic microbiome. SUMMARY BACKGROUND DATA: Small studies in pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasm (IPMN) have suggested that intra-pancreatic microbial dysbiosis may drive malignant transformation. METHODS: Pancreatic samples were collected at the time of resection from 109 patients. Samples included tumor tissue (control, n=20; IPMN, n=20; PDAC, n=19) and pancreatic cyst fluid (IPMN, n=30; SCA, n=10; MCN, n=10). Assessment of bacterial DNA by quantitative PCR and 16S ribosomal RNA gene sequencing was performed. Downstream analyses determined the relative abundances of individual taxa between groups and compared intergroup diversity. Whole-genome sequencing data from 140 patients with PDAC in the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) were analyzed to validate findings. RESULTS: Sequencing of pancreatic tissue yielded few microbial reads regardless of diagnosis, and analysis of pancreatic tissue showed no difference in the abundance and composition of bacterial taxa between normal pancreas, IPMN, or PDAC groups. Low-grade dysplasia (LGD) and high-grade dysplasia (HGD) IPMN were characterized by low bacterial abundances with no difference in tissue composition and a slight increase in Pseudomonas and Sediminibacterium in HGD cyst fluid. Decontamination analysis using the CPTAC database confirmed a low-biomass, low-diversity intrinsic pancreatic microbiome that did not differ by pathology. CONCLUSIONS: Our analysis of the pancreatic microbiome demonstrated very low intrinsic biomass that is relatively conserved across diverse neoplastic conditions and thus unlikely to drive malignant transformation.

Timing of Adjuvant Immunotherapy in Stage III Melanoma, Does it Matter?

BACKGROUND: The optimal time to initiate adjuvant immune checkpoint inhibitors (ICI) following resection remains undefined. Herein, we investigated the impact of time to adjuvant ICI on survival in patients with stage III melanoma. METHODS: Patients with resected stage III melanoma receiving adjuvant immune therapy were identified within a multi-institutional retrospective cohort. Patients were stratified by time to adjuvant ICI: within 6 weeks, 6-12 weeks, and greater than 12 weeks from surgery. Recurrence-free survival (RFS) was compared among time strata with Kaplan-Meier and Cox proportional hazards methods in the multi-institutional cohort. RESULTS: Altogether, 626 patients were identified within the multi-institutional cohort: 39% of patients initiated adjuvant ICI within 6 weeks, 42.2% within 6-12 weeks, and 18.8% greater than 12 weeks from surgery. In a multivariate Cox model, adjusting for histology, nodal tumor burden, and pathologic stage, we found that increased time to adjuvant ICI was associated with improved RFS. Patients who initiated adjuvant ICI within 6 weeks of surgery had worse RFS. These findings were preserved in a conditional landmark analysis and separate subgroups of patients with (1) new melanoma diagnoses, (2) occult stage III disease, and (3) those receiving anti-PD-1 monotherapy. CONCLUSIONS: Outcomes for patients with stage III melanoma are not compromised when adjuvant ICI is initiated beyond 6 weeks from resection. Additional work is needed to better understand the underlying mechanisms and implications of timing of adjuvant ICI on long-term outcomes.

Digital spatial profiling of intraductal papillary mucinous neoplasms: Toward a molecular framework for risk stratification.

The histopathologic heterogeneity of intraductal papillary mucinous neoplasms (IPMN) complicates the prediction of pancreatic ductal adenocarcinoma (PDAC) risk. Intratumoral regions of pancreaticobiliary (PB), intestinal (INT), and gastric foveolar (GF) epithelium may occur with either low-grade dysplasia (LGD) or high-grade dysplasia (HGD). We used digital spatial RNA profiling of dysplastic epithelium (83 regions) from surgically resected IPMN tissues (12 patients) to differentiate subtypes and predict genes associated with malignancy. The expression patterns of PB and GF lesions diverged from INT, suggesting that PB and GF arise from a common lineage. Transcriptional dysregulation within PB lesions mirrored that of PDAC, whereas INT and GF foci did not. Tumor necrosis factor/nuclear factor κB (TNF-NFκB) and cell cycle (cycling S and cycling G2-M) programs occurred with relative prominence in PB and INT subtypes, respectively. Together, this study delineates markers of high-risk IPMN and insights into malignant progression.

Multidimensional Immunophenotyping of Intraductal Papillary Mucinous Neoplasms Reveals Novel T Cell and Macrophage Signature.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMN) are the only radiographically identifiable precursor to pancreatic adenocarcinoma, yet little is known about how these lesions progress to cancer. Inflammation has been associated with dysplastic progression; however, the cause and composition of this inflammation remains poorly characterized. We sought to comprehensively profile immune cell infiltration using parallel spatial transcriptomic and flow cytometric techniques. METHODS: Twelve patients with resected IPMN exhibiting both high-grade dysplasia (HGD) and low-grade dysplasia (LGD) were selected for spatial transcriptomics (NanoString GeoMx). Immune (CD45+), epithelial (PanCK+), and stromal (SMA+) compartments were analyzed separately using the GeoMx NGS Pipeline. An additional 11 patients resected for IPMN of varying degrees of dysplasia underwent immunophenotyping using flow cytometry (DURAClone IM). RESULTS: Spatial transcriptomics revealed that T cells represent the dominant immune cell within IPMN stroma, which was confirmed by flow cytometry (56%). Spatial profiling found that the T-cell infiltrate was significantly higher in regions of LGD compared with HGD (62% vs. 50%, p = 0.038). Macrophages were the only other immune cell type with > 10% abundance, yet conversely, were generally more abundant in regions of HGD compared to LGD (19% vs. 11%, p = 0.058). Correspondingly, immune cells within regions of HGD demonstrated transcriptional upregulation of genes associated with macrophage activity including secretion (CXCL1) and phagocytosis (C1QA, C1S, C4B). CONCLUSIONS: IPMN immune infiltrate is primarily composed of T cells and macrophages. Regions of HGD appear to be relatively deplete of T cells and show a trend toward macrophage enrichment compared with regions of LGD.

The role of the histone H3 variant CENPA in prostate cancer.

Overexpression of centromeric proteins has been identified in a number of human malignancies, but the functional and mechanistic contributions of these proteins to disease progression have not been characterized. The centromeric histone H3 variant centromere protein A (CENPA) is an epigenetic mark that determines centromere identity. Here, using an array of approaches, including RNA-sequencing and ChIP-sequencing analyses, immunohistochemistry-based tissue microarrays, and various cell biology assays, we demonstrate that CENPA is highly overexpressed in prostate cancer in both tissue and cell lines and that the level of CENPA expression correlates with the disease stage in a large cohort of patients. Gain-of-function and loss-of-function experiments confirmed that CENPA promotes prostate cancer cell line growth. The results from the integrated sequencing experiments suggested a previously unidentified function of CENPA as a transcriptional regulator that modulates expression of critical proliferation, cell-cycle, and centromere/kinetochore genes. Taken together, our findings show that CENPA overexpression is crucial to prostate cancer growth.

Analysis of the androgen receptor-regulated lncRNA landscape identifies a role for ARLNC1 in prostate cancer progression.

The androgen receptor (AR) plays a critical role in the development of the normal prostate as well as prostate cancer. Using an integrative transcriptomic analysis of prostate cancer cell lines and tissues, we identified ARLNC1 (AR-regulated long noncoding RNA 1) as an important long noncoding RNA that is strongly associated with AR signaling in prostate cancer progression. Not only was ARLNC1 induced by the AR protein, but ARLNC1 stabilized the AR transcript via RNA-RNA interaction. ARLNC1 knockdown suppressed AR expression, global AR signaling and prostate cancer growth in vitro and in vivo. Taken together, these data support a role for ARLNC1 in maintaining a positive feedback loop that potentiates AR signaling during prostate cancer progression and identify ARLNC1 as a novel therapeutic target.

Oncogenic Role of THOR, a Conserved Cancer/Testis Long Non-coding RNA.

Large-scale transcriptome sequencing efforts have vastly expanded the catalog of long non-coding RNAs (lncRNAs) with varying evolutionary conservation, lineage expression, and cancer specificity. Here, we functionally characterize a novel ultraconserved lncRNA, THOR (ENSG00000226856), which exhibits expression exclusively in testis and a broad range of human cancers. THOR knockdown and overexpression in multiple cell lines and animal models alters cell or tumor growth supporting an oncogenic role. We discovered a conserved interaction of THOR with IGF2BP1 and show that THOR contributes to the mRNA stabilization activities of IGF2BP1. Notably, transgenic THOR knockout produced fertilization defects in zebrafish and also conferred a resistance to melanoma onset. Likewise, ectopic expression of human THOR in zebrafish accelerated the onset of melanoma. THOR represents a novel class of functionally important cancer/testis lncRNAs whose structure and function have undergone positive evolutionary selection.

TACO produces robust multisample transcriptome assemblies from RNA-seq.

Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporated into RNA-seq analysis workflows.

Genome-Wide STAT3 Binding Analysis after Histone Deacetylase Inhibition Reveals Novel Target Genes in Dendritic Cells.

STAT3 is a master transcriptional regulator that plays an important role in the induction of both immune activation and immune tolerance in dendritic cells (DCs). The transcriptional targets of STAT3 in promoting DC activation are becoming increasingly understood; however, the mechanisms underpinning its role in causing DC suppression remain largely unknown. To determine the functional gene targets of STAT3, we compared the genome-wide binding of STAT3 using ChIP sequencing coupled with gene expression microarrays to determine STAT3-dependent gene regulation in DCs after histone deacetylase (HDAC) inhibition. HDAC inhibition boosted the ability of STAT3 to bind to distinct DNA targets and regulate gene expression. Among the top 500 STAT3 binding sites, the frequency of canonical motifs was significantly higher than that of noncanonical motifs. Functional analysis revealed that after treatment with an HDAC inhibitor, the upregulated STAT3 target genes were those that were primarily the negative regulators of proinflammatory cytokines and those in the IL-10 signaling pathway. The downregulated STAT3-dependent targets were those involved in immune effector processes and antigen processing/presentation. The expression and functional relevance of these genes were validated. Specifically, functional studies confirmed that the upregulation of IL-10Ra by STAT3 contributed to the suppressive function of DCs following HDAC inhibition.

The lncRNA landscape of breast cancer reveals a role for DSCAM-AS1 in breast cancer progression.

Molecular classification of cancers into subtypes has resulted in an advance in our understanding of tumour biology and treatment response across multiple tumour types. However, to date, cancer profiling has largely focused on protein-coding genes, which comprise <1% of the genome. Here we leverage a compendium of 58,648 long noncoding RNAs (lncRNAs) to subtype 947 breast cancer samples. We show that lncRNA-based profiling categorizes breast tumours by their known molecular subtypes in breast cancer. We identify a cohort of breast cancer-associated and oestrogen-regulated lncRNAs, and investigate the role of the top prioritized oestrogen receptor (ER)-regulated lncRNA, DSCAM-AS1. We demonstrate that DSCAM-AS1 mediates tumour progression and tamoxifen resistance and identify hnRNPL as an interacting protein involved in the mechanism of DSCAM-AS1 action. By highlighting the role of DSCAM-AS1 in breast cancer biology and treatment resistance, this study provides insight into the potential clinical implications of lncRNAs in breast cancer.

Targeting the MLL complex in castration-resistant prostate cancer.

Resistance to androgen deprivation therapies and increased androgen receptor (AR) activity are major drivers of castration-resistant prostate cancer (CRPC). Although prior work has focused on targeting AR directly, co-activators of AR signaling, which may represent new therapeutic targets, are relatively underexplored. Here we demonstrate that the mixed-lineage leukemia protein (MLL) complex, a well-known driver of MLL fusion-positive leukemia, acts as a co-activator of AR signaling. AR directly interacts with the MLL complex via the menin-MLL subunit. Menin expression is higher in CRPC than in both hormone-naive prostate cancer and benign prostate tissue, and high menin expression correlates with poor overall survival of individuals diagnosed with prostate cancer. Treatment with a small-molecule inhibitor of menin-MLL interaction blocks AR signaling and inhibits the growth of castration-resistant tumors in vivo in mice. Taken together, this work identifies the MLL complex as a crucial co-activator of AR and a potential therapeutic target in advanced prostate cancer.

Analysis of long non-coding RNAs highlights tissue-specific expression patterns and epigenetic profiles in normal and psoriatic skin.

BACKGROUND: Although analysis pipelines have been developed to use RNA-seq to identify long non-coding RNAs (lncRNAs), inference of their biological and pathological relevance remains a challenge. As a result, most transcriptome studies of autoimmune disease have only assessed protein-coding transcripts. RESULTS: We used RNA-seq data from 99 lesional psoriatic, 27 uninvolved psoriatic, and 90 normal skin biopsies, and applied computational approaches to identify and characterize expressed lncRNAs. We detect 2,942 previously annotated and 1,080 novel lncRNAs which are expected to be skin specific. Notably, over 40% of the novel lncRNAs are differentially expressed and the proportions of differentially expressed transcripts among protein-coding mRNAs and previously-annotated lncRNAs are lower in psoriasis lesions versus uninvolved or normal skin. We find that many lncRNAs, in particular those that are differentially expressed, are co-expressed with genes involved in immune related functions, and that novel lncRNAs are enriched for localization in the epidermal differentiation complex. We also identify distinct tissue-specific expression patterns and epigenetic profiles for novel lncRNAs, some of which are shown to be regulated by cytokine treatment in cultured human keratinocytes. CONCLUSIONS: Together, our results implicate many lncRNAs in the immunopathogenesis of psoriasis, and our results provide a resource for lncRNA studies in other autoimmune diseases.

The landscape of long noncoding RNAs in the human transcriptome.

Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.

Transcriptome meta-analysis of lung cancer reveals recurrent aberrations in NRG1 and Hippo pathway genes.

Lung cancer is emerging as a paradigm for disease molecular subtyping, facilitating targeted therapy based on driving somatic alterations. Here we perform transcriptome analysis of 153 samples representing lung adenocarcinomas, squamous cell carcinomas, large cell lung cancer, adenoid cystic carcinomas and cell lines. By integrating our data with The Cancer Genome Atlas and published sources, we analyse 753 lung cancer samples for gene fusions and other transcriptomic alterations. We show that higher numbers of gene fusions is an independent prognostic factor for poor survival in lung cancer. Our analysis confirms the recently reported CD74-NRG1 fusion and suggests that NRG1, NF1 and Hippo pathway fusions may play important roles in tumours without known driver mutations. In addition, we observe exon-skipping events in c-MET, which are attributable to splice site mutations. These classes of genetic aberrations may play a significant role in the genesis of lung cancers lacking known driver mutations.

A novel RNA in situ hybridization assay for the long noncoding RNA SChLAP1 predicts poor clinical outcome after radical prostatectomy in clinically localized prostate cancer.

Long noncoding RNAs (lncRNAs) are an emerging class of oncogenic molecules implicated in a diverse range of human malignancies. We recently identified SChLAP1 as a novel lncRNA that demonstrates outlier expression in a subset of prostate cancers, promotes tumor cell invasion and metastasis, and associates with lethal disease. Based on these findings, we sought to develop an RNA in situ hybridization (ISH) assay for SChLAP1 to 1) investigate the spectrum of SChLAP1 expression from benign prostatic tissue to metastatic castration-resistant prostate cancer and 2) to determine whether SChLAP1 expression by ISH is associated with outcome after radical prostatectomy in patients with clinically localized disease. The results from our current study demonstrate that SChLAP1 expression increases with prostate cancer progression, and high SChLAP1 expression by ISH is associated with poor outcome after radical prostatectomy in patients with clinically localized prostate cancer by both univariate (hazard ratio = 2.343, P = .005) and multivariate (hazard ratio = 1.99, P = .032) Cox regression analyses. This study highlights a potential clinical utility for SChLAP1 ISH as a novel tissue-based biomarker assay for outcome prognostication after radical prostatectomy.

RNA biomarkers associated with metastatic progression in prostate cancer: a multi-institutional high-throughput analysis of SChLAP1.

BACKGROUND: Improved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy. METHODS: Prostate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene. FINDINGS: 1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2·45, 95% CI 1·70-3·53; p<0·0001). The only other variable that independently predicted metastasis within 10 years was Gleason score (8-10 vs 5-7; OR 2·14, 95% CI 1·77-2·58; p<0·0001). INTERPRETATION: We identified and validated high SChLAP1 expression as significantly prognostic for metastatic disease progression of prostate cancer. Our findings suggest that further development of SChLAP1 as a potential biomarker, for treatment intensification in aggressive prostate cancer, warrants future study. FUNDING: Prostate Cancer Foundation, National Institutes of Health, Department of Defense, Early Detection Research Network, Doris Duke Charitable Foundation, and Howard Hughes Medical Institute.

The long non-coding RNA PCAT-1 promotes prostate cancer cell proliferation through cMyc.

Long non-coding RNAs (lncRNAs) represent an emerging layer of cancer biology, contributing to tumor proliferation, invasion, and metastasis. Here, we describe a role for the oncogenic lncRNA PCAT-1 in prostate cancer proliferation through cMyc. We find that PCAT-1-mediated proliferation is dependent on cMyc protein stabilization, and using expression profiling, we observed that cMyc is required for a subset of PCAT-1-induced expression changes. The PCAT-1-cMyc relationship is mediated through the post-transcriptional activity of the MYC 3' untranslated region, and we characterize a role for PCAT-1 in the disruption of MYC-targeting microRNAs. To further elucidate a role for post-transcriptional regulation, we demonstrate that targeting PCAT-1 with miR-3667-3p, which does not target MYC, is able to reverse the stabilization of cMyc by PCAT-1. This work establishes a basis for the oncogenic role of PCAT-1 in cancer cell proliferation and is the first study to implicate lncRNAs in the regulation of cMyc in prostate cancer.