Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma

Large-scale multi-omic analysis identifies noncoding somatic driver mutations and nominates ZFP36L2 as a driver gene for pancreatic ductal adenocarcinoma

Identification of somatic driver mutations in the noncoding genome remains challenging. To comprehensively characterize noncoding driver mutations for pancreatic ductal adenocarcinoma (PDAC), we first created genome-scale maps of accessible chromatin regions (ACRs) and histone modification marks (HMMs) in pancreatic cell lines and purified pancreatic acinar and duct cells. Integration with whole-genome mutation calls from 506 PDACs revealed 314 ACRs/HMMs significantly enriched with 3,614 noncoding somatic mutations (NCSMs). Functional assessment using massively parallel reporter assays (MPRA) identified 178 NCSMs impacting reporter activity (19.45% of those tested). Focused luciferase validation confirmed negative effects on gene regulatory activity for NCSMs near CDKN2A and ZFP36L2. For the latter, CRISPR interference (CRISPRi) further identified ZFP36L2 as a target gene (16.0 - 24.0% reduced expression, P = 0.023-0.0047) with disrupted KLF9 binding likely mediating the effect. Our integrative approach provides a catalog of potentially functional noncoding driver mutations and nominates ZFP36L2 as a PDAC driver gene.

Axon guidance cue SEMA3A promotes the aggressive phenotype of basal-like PDAC

OBJECTIVE

The dysregulation of the axon guidance pathway is common in pancreatic ductal adenocarcinoma (PDAC), yet our understanding of its biological relevance is limited. Here, we investigated the functional role of the axon guidance cue SEMA3A in supporting PDAC progression.

DESIGN

We integrated bulk and single-cell transcriptomic datasets of human PDAC with in situ hybridisation analyses of patients' tissues to evaluate SEMA3A expression in molecular subtypes of PDAC. Gain and loss of function experiments in PDAC cell lines and organoids were performed to dissect how SEMA3A contributes to define a biologically aggressive phenotype.

RESULTS

In PDAC tissues, SEMA3A is expressed by stromal elements and selectively enriched in basal-like/squamous epithelial cells. Accordingly, expression of SEMA3A in PDAC cells is induced by both cell-intrinsic and cell-extrinsic determinants of the basal-like phenotype. In vitro, SEMA3A promotes cell migration as well as anoikis resistance. At the molecular level, these phenotypes are associated with increased focal adhesion kinase signalling through canonical SEMA3A-NRP1 axis. SEMA3A provides mouse PDAC cells with greater metastatic competence and favours intratumoural infiltration of tumour-associated macrophages and reduced density of T cells. Mechanistically, SEMA3A functions as chemoattractant for macrophages and skews their polarisation towards an M2-like phenotype. In SEMA3Ahigh tumours, depletion of macrophages results in greater intratumour infiltration by CD8+T cells and better control of the disease from antitumour treatment.

CONCLUSIONS

Here, we show that SEMA3A is a stress-sensitive locus that promotes the malignant phenotype of basal-like PDAC through both cell-intrinsic and cell-extrinsic mechanisms.

Thyroid poorly differentiated carcinoma metastatic to pancreas diagnosed by fine-needle aspiration and demonstrating a novel BRAF fusion

Differentiating pancreatic duct adenocarcinoma from metastasis can be challenging by morphology alone. Metastasis from a classic papillary thyroid carcinoma can present as a poorly differentiated carcinoma and mimic pancreatic ductal adenocarcinoma's morphology.

Identification of SLC12A8 as a valuable prognostic biomarker and immunotherapeutic target by comprehensive pan-cancer analysis

Solute carrier family 12 member 8 (SLC12A8) is a nicotinamide mononucleotide transporter. Despite emerging evidence supporting its potential involvement in oncogenesis, a systematic pan-cancer analysis of SLC12A8 has not been performed. Thus, this research aimed to explore the prognostic implications of SLC12A8 and assess its possible immune-related functions across 33 different tumor types. And multiple datasets were retrieved from the databases of TCGA, GTEx, Broad Institute CCLE, TISCH, HPA, and GDSC2. After this data acquisition, bioinformatics analyses were conducted to assess the potential involvement of SLC12A8 in cancer pathogenesis. These analyses focused on examining the relationship between SLC12A8 and prognosis, drug sensitivity, chemotherapy response, immune checkpoints (ICPs), immune cell infiltration, and immunotherapy efficacy across various tumor types. Furthermore, experimental methods such as EdU assay, wound healing assay, and transwell assay were conducted to evaluate the cell proliferative and invasive abilities. Finally, the data analysis demonstrated that SLC12A8 was differentially expressed and predicted unfavorable survival outcomes in the majority of the tumor types in the TCGA dataset. Furthermore, a notable upregulation in the expression of SLC12A8 mRNA and protein was observed in cancer tissues compared to normal tissues. Additionally, the SLC12A8 levels demonstrated a strong association with ICPs, chemokines, immune-activating genes, immune-suppressive genes, chemokine receptors, chemotherapy response, and immunotherapy efficacy. In vitro experiments substantiated that knockdown of SLC12A8 restricted the malignant phenotypes of MDA-MB-231 and BT-549 cells. So SLC12A8 holds promise as a cancer biomarker with the capacity to interact with other ICPs to synergistically regulate the immune microenvironment. Thus, the identification of SLC12A8 contributes to the development of novel therapeutic strategies for enhancing the efficacy of immunotherapy.

Integrative identification of non-coding regulatory regions driving metastatic prostate cancer

Large-scale sequencing efforts of thousands of tumor samples have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of germline and somatic variants occur within non-coding portions of the genome. These genomic regions do not directly encode for specific proteins, but can play key roles in cancer progression, for example by driving aberrant gene expression control. Here, we designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Application of this approach to whole-genome sequencing (WGS) data from a large cohort of metastatic castration-resistant prostate cancer (mCRPC) revealed a large set of recurrently mutated regions. We used (i) in silico prioritization of functional non-coding mutations, (ii) massively parallel reporter assays, and (iii) in vivo CRISPR-interference (CRISPRi) screens in xenografted mice to systematically identify and validate driver regulatory regions that drive mCRPC. We discovered that one of these enhancer regions, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. We found that both SF3A1 and CCDC157 are promoters of tumor growth in xenograft models of prostate cancer. We nominated a number of transcription factors, including SOX6, to be responsible for higher expression of SF3A1 and CCDC157. Collectively, we have established and confirmed an integrative computational and experimental approach that enables the systematic detection of non-coding regulatory regions that drive the progression of human cancers.

Nutrient transporters: connecting cancer metabolism to therapeutic opportunities

Cancer cells rely on certain extracellular nutrients to sustain their metabolism and growth. Solute carrier (SLC) transporters enable cells to acquire extracellular nutrients or shuttle intracellular nutrients across organelles. However, the function of many SLC transporters in cancer is unknown. Determining the key SLC transporters promoting cancer growth could reveal important therapeutic opportunities. Here we summarize recent findings and knowledge gaps on SLC transporters in cancer. We highlight existing inhibitors for studying these transporters, clinical trials on treating cancer by blocking transporters, and compensatory transporters used by cancer cells to evade treatment. We propose targeting transporters simultaneously or in combination with targeted therapy or immunotherapy as alternative strategies for effective cancer therapy.

Genetics, Genomics and Emerging Molecular Therapies of Pancreatic Cancer

The number of cases of pancreatic cancers in 2019 in Poland was 3852 (approx. 2% of all cancers). The course of the disease is very fast, and the average survival time from the diagnosis is 6 months. Only <2% of patients live for 5 years from the diagnosis, 8% live for 2 years, and almost half live for only about 3 months. A family predisposition to pancreatic cancer occurs in about 10% of cases. Several oncogenes in which somatic changes lead to the development of tumours, including genes BRCA1/2 and PALB2, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1, are involved in pancreatic cancer. Between 4% and 10% of individuals with pancreatic cancer will have a mutation in one of these genes. Six percent of patients with pancreatic cancer have NTRK pathogenic fusion. The pathogenesis of pancreatic cancer can in many cases be characterised by homologous recombination deficiency (HRD)-cell inability to effectively repair DNA. It is estimated that from 24% to as many as 44% of pancreatic cancers show HRD. The most common cause of HRD are inactivating mutations in the genes regulating this DNA repair system, mainly BRCA1 and BRCA2, but also PALB2, RAD51C and several dozen others.

Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers

Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.

Diagnostic Potential of microRNAs in Extracellular Vesicles Derived from Bronchoalveolar Lavage Fluid for Pneumonia—A Preliminary Report

Current clinical needs require the development and use of rapid and effective diagnostic indicators to accelerate the identification of pneumonia and the process of microbiological diagnosis. MicroRNAs (miRNAs) in extracellular vesicles (EVs) have become attractive candidates for novel biomarkers to evaluate the presence and progress of many diseases. We assessed their performance as biomarkers of pneumonia. Patients were divided into the pneumonia group (with pneumonia) and the control group (without pneumonia). We identified and compared two upregulated miRNAs in EVs derived from bronchoalveolar lavage fluid (BALF-EVs) between the two groups (P_{miR–17–5p} = 0.009; P_{miR–193a–5p} = 0.031). Interestingly, in cell-debris pellets and EVs-free supernatants derived from bronchoalveolar lavage fluid (BALF-cell-debris pellets and BALF-EVs-free supernatants), total plasma, and EVs derived from plasma (plasma-EVs), the expression of miR–17–5p and miR–193a–5p showed no difference between pneumonia group and control group. In vitro experiments revealed that miR–17–5p and miR–193a–5p were strikingly upregulated in EVs derived from macrophages stimulated by lipopolysaccharide. MiR–17–5p (area under the curve, AUC: 0.753) and miR–193a–5p (AUC: 0.692) in BALF-EVs are not inferior to procalcitonin (AUC: 0.685) in the diagnosis of pneumonia. Furthermore, miR–17–5p and miR–193a–5p in BALF-EVs had a significantly higher specificity compared to procalcitonin and could be served as a potential diagnostic marker. MiR–17–5p and miR–193a–5p in EVs may be involved in lung inflammation by influencing the forkhead box O (FoxO) signaling pathway and protein processing in endoplasmic reticulum. This study is one of the few studies which focused on the potential diagnostic role of miRNAs in BALF-EVs for pneumonia and the possibility to use them as new biomarkers for a rapid and early diagnosis.

ATP13A3 facilitates polyamine transport in human pancreatic cancer cells

The purpose of this study is to provide an increased understanding of the molecular mechanisms responsible for mammalian polyamine transport, a process that has been a long-standing 'black box' for the polyamine field. Here, we describe how ATP13A3, a P-type ATPase, functions as a polyamine transporter in response to different polyamine stimuli and polyamine-targeted therapies in highly proliferating pancreatic cancer cells. We assessed the expression, cellular localization and the response of the human ATP13A3 protein to polyamine treatments in different pancreatic cancer cell lines using Western blot and immunofluorescence microscopy. Using CRISPR mutagenesis and radiolabeled polyamine uptake assays, we investigated the role of ATP13A3 protein in polyamine transport. Highly metastatic cancer cells with high polyamine import express higher levels of the full-length ATP13A3 compared to cells with slow proliferation and low import activity. Highlighting its role in polyamine trafficking, the localization of ATP13A3 is altered in the presence of polyamine stimuli and polyamine-targeted therapies in these cells. Using CRISPR mutagenesis, we demonstrate that the first membrane-associated domain of this protein is critical and indispensable for its function as a spermidine and spermine transporter in cells. Further analysis of existing databases revealed that pancreatic cancer patients with high expression of ATP13A3 have decreased overall survival consistent with the role of intracellular polyamines in supporting tumor growth. Our studies shed light on the mysterious polyamine transport process in human cells and clearly establishes ATP13A3 as an intrinsic component of the spermidine and spermine transport system in humans.

Pancreatic cancer evolution and heterogeneity: integrating omics and clinical data

Pancreatic ductal adenocarcinoma (PDAC), already among the deadliest epithelial malignancies, is rising in both incidence and contribution to overall cancer deaths. Decades of research have improved our understanding of PDAC carcinogenesis, including characterizing germline predisposition, the cell of origin, precursor lesions, the sequence of genetic alterations, including simple and structural alterations, transcriptional changes and subtypes, tumour heterogeneity, metastatic progression and the tumour microenvironment. These fundamental advances inform contemporary translational efforts in primary prevention, screening and early detection, multidisciplinary management and survivorship, as prospective clinical trials begin to adopt molecular-based selection criteria to guide targeted therapies. Genomic and transcriptomic data on PDAC were also included in the international pan-cancer analysis of approximately 2,600 cancers, a milestone in cancer research that allows further insight through comparison with other tumour types. Thus, this is an ideal time to review our current knowledge of PDAC evolution and heterogeneity, gained from the study of preclinical models and patient biospecimens, and to propose a model of PDAC evolution that takes into consideration findings from varied sources, with a particular focus on the genomics of human PDAC.

HOXD13 promotes the malignant progression of colon cancer by upregulating PTPRN2

PURPOSE

The homeobox (HOX) family plays an important role in multi-biological processes, such as morphogenesis and tumors. However, the function of HOXD13 in colon cancer remains unclear.

MATERIALS AND METHODS

The Cancer Genome Atlas database was used to analyze the expression of HOXD13 and its effect on the survival rate of colon cancer patients. Wound healing, Transwell, and clone formation were used to evaluate the effects of changes in HOXD13 expression on the function of colon cancer cells. A nude mouse xenograft tumor model was used to test the effects of HOXD13 on tumor growth in vivo.

RESULTS

Our results showed that HOXD13 was highly expressed in colon cancer and predicted a poor prognosis for patients. In in vitro experiments, the knockdown of HOXD13 can inhibit the proliferation and invasion of colon cancer cells. In vivo experiments showed the inhibited tumor growth after the knockdown of HODX13. In addition, HOXD13 bound to the protein tyrosine phosphatase receptor type N2 (PTPRN2) promoter and promoted the transcription of PTPRN2.

CONCLUSION

We revealed the function and mechanism of HOXD13 in colon cancer and suggest that HOXD13 may be a candidate marker for the diagnosis and treatment of colon cancer.

Functional annotation of noncoding mutations in cancer

Recurrent regulatory mutations affecting transcription factor binding sites in 2,500 cancer samples.

In a cancer genome, the noncoding sequence contains the vast majority of somatic mutations. While very few are expected to be cancer drivers, those affecting regulatory elements have the potential to have downstream effects on gene regulation that may contribute to cancer progression. To prioritize regulatory mutations, we screened somatic mutations in the Pan-Cancer Analysis of Whole Genomes cohort of 2,515 cancer genomes on individual bases to assess their potential regulatory roles in their respective cancer types. We found a highly significant enrichment of regulatory mutations associated with the deamination signature overlapping a CpG site in the CCAAT/Enhancer Binding Protein β recognition sites in many cancer types. Overall, 5,749 mutated regulatory elements were identified in 1,844 tumor samples from 39 cohorts containing 11,962 candidate regulatory mutations. Our analysis indicated 20 or more regulatory mutations in 5.5% of the samples, and an overall average of six per tumor. Several recurrent elements were identified, and major cancer-related pathways were significantly enriched for genes nearby the mutated regulatory elements. Our results provide a detailed view of the role of regulatory elements in cancer genomes.

The molecular biology of pancreatic adenocarcinoma: translational challenges and clinical perspectives

Pancreatic cancer is an increasingly common cause of cancer mortality with a tight correspondence between disease mortality and incidence. Furthermore, it is usually diagnosed at an advanced stage with a very dismal prognosis. Due to the high heterogeneity, metabolic reprogramming, and dense stromal environment associated with pancreatic cancer, patients benefit little from current conventional therapy. Recent insight into the biology and genetics of pancreatic cancer has supported its molecular classification, thus expanding clinical therapeutic options. In this review, we summarize how the biological features of pancreatic cancer and its metabolic reprogramming as well as the tumor microenvironment regulate its development and progression. We further discuss potential biomarkers for pancreatic cancer diagnosis, prediction, and surveillance based on novel liquid biopsies. We also outline recent advances in defining pancreatic cancer subtypes and subtype-specific therapeutic responses and current preclinical therapeutic models. Finally, we discuss prospects and challenges in the clinical development of pancreatic cancer therapeutics.

The pancreatic cancer genome revisited

Pancreatic cancer is a genetic disease, and the recurrent genetic alterations characteristic of pancreatic cancer indicate the cellular processes that are targeted for malignant transformation. In addition to somatic alterations in the most common driver genes (KRAS, CDKN2A, TP53 and SMAD4), large-scale studies have revealed major roles for genetic alterations of the SWI/SNF and COMPASS complexes, copy number alterations in GATA6 and MYC that partially define phenotypes of pancreatic cancer, and the role(s) of polyploidy and chromothripsis as factors contributing to pancreatic cancer biology and progression. Germline variants that increase the risk of pancreatic cancer continue to be discovered along with a greater appreciation of the features of pancreatic cancers with mismatch repair deficiencies and homologous recombination deficiencies that confer sensitivity to therapeutic targeting. Wild-type KRAS pancreatic cancers, some of which are driven by alternative oncogenic events affecting NRG1 or NTRK1 - for which targeted therapies exist - further underscore that pancreatic cancer is formally entering the era of precision medicine. Given the vast developments within this field, here we review the wide-ranging and most current information related to pancreatic cancer genomics with the goal of integrating this information into a unifying description of the life history of pancreatic cancer.

Drivers of Gene Expression Dysregulation in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) remains a devastating disease with a poor prognosis. The functional consequences of common genetic aberrations and their roles in treatment strategies have been extensively reviewed. In addition to these genomic aberrations, consideration of non-genetic drivers of altered oncogene expression is essential to account for the diversity in PDAC phenotypes. In this review we seek to assess our current understanding of mechanisms of gene expression dysregulation. We focus on four drivers of gene expression dysregulation, including mutations, transcription factors, epigenetic regulators, and RNA stability/isoform regulation, in the context of PDAC pathogenesis. Recent studies provide much-needed insight into the role of gene expression dysregulation in dissecting tumor heterogeneity and stratifying patients for the development of personalized treatment strategies.

Interpretation of allele-specific chromatin accessibility using cell state-aware deep learning

Genomic sequence variation within enhancers and promoters can have a significant impact on the cellular state and phenotype. However, sifting through the millions of candidate variants in a personal genome or a cancer genome, to identify those that impact cis-regulatory function, remains a major challenge. Interpretation of noncoding genome variation benefits from explainable artificial intelligence to predict and interpret the impact of a mutation on gene regulation. Here we generate phased whole genomes with matched chromatin accessibility, histone modifications, and gene expression for 10 melanoma cell lines. We find that training a specialized deep learning model, called DeepMEL2, on melanoma chromatin accessibility data can capture the various regulatory programs of the melanocytic and mesenchymal-like melanoma cell states. This model outperforms motif-based variant scoring, as well as more generic deep learning models. We detect hundreds to thousands of allele-specific chromatin accessibility variants (ASCAVs) in each melanoma genome, of which 15%-20% can be explained by gains or losses of transcription factor binding sites. A considerable fraction of ASCAVs are caused by changes in AP-1 binding, as confirmed by matched ChIP-seq data to identify allele-specific binding of JUN and FOSL1. Finally, by augmenting the DeepMEL2 model with ChIP-seq data for GABPA, the TERT promoter mutation, as well as additional ETS motif gains, can be identified with high confidence. In conclusion, we present a new integrative genomics approach and a deep learning model to identify and interpret functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.

Molecular Subtyping and Precision Medicine for Pancreatic Cancer

Substantial progress in recent years has dramatically increased our knowledge of the molecular basis of cancer, revealing new potential therapeutic targets and paving the way for effective personalised medicine for the treatment of many tumour types. However, pancreatic cancer has been lagging behind in this success and continues to be one of the most lethal solid malignancies. Its molecular heterogeneity and the unselected design of the majority of clinical trials to date can in part explain the reason for our failure to make a significant change in the survival outcomes for patients with pancreatic cancer. A changing paradigm in drug development is required to validate the new molecular taxonomy and to rapidly translate preclinical discovery into clinical trials. Here, we review the molecular subtyping of pancreatic cancer, the challenges in identifying effective treatment regimens according to defined low-prevalence molecular subgroups and we illustrate a new model of translational therapeutic development that was established in the U.K. (Precision-Panc) as a potentially effective solution to improve outcomes for patients with pancreatic cancer.

Computational methods for detecting cancer hotspots

Cancer mutations that are recurrently observed among patients are known as hotspots. Hotspots are highly relevant because they are, presumably, likely functional. Known hotspots in BRAF, PIK3CA, TP53, KRAS, IDH1 support this idea. However, hundreds of hotspots have never been validated experimentally. The detection of hotspots nevertheless is challenging because background mutations obscure their statistical and computational identification. Although several algorithms have been applied to identify hotspots, they have not been reviewed before. Thus, in this mini-review, we summarize more than 40 computational methods applied to detect cancer hotspots in coding and non-coding DNA. We first organize the methods in cluster-based, 3D, position-specific, and miscellaneous to provide a general overview. Then, we describe their embed procedures, implementations, variations, and differences. Finally, we discuss some advantages, provide some ideas for future developments, and mention opportunities such as application to viral integrations, translocations, and epigenetics.

Solute carrier family 12 member 8 impacts the biological behaviors of breast carcinoma cells by activating TLR/NLR signaling pathway

This study aimed to understand the expression of solute carrier family 12 member 8 (SLC12A8) in breast carcinoma and its biological functions, as well as its effect on the Toll-like receptor /NOD-like receptor (TLR/NLR) signaling pathway. The expression of SLC12A8 was analyzed using the public RNA sequencing dataset from TCGA database and the two datasets from Oncomine database. The former dataset was also used to evaluate the prognostic value of SLC12A8 in breast carcinoma. Real-time qPCR and western blot were applied to measure relative expression of SLC12A8. Functionally, the effect of SLC12A8 on the cells proliferation and motion was studied using cell counting kit 8 and Transwell assays respectively. Mechanistic studies were conducted using Gene Set Enrichment Analysis (GSEA) and confirmed by western blot. As a result, SLC12A8 was upregulated in breast carcinoma, and high levels of SLC12A8 led to a poorer prognosis and can be regarded as an independent prognosticator for patients with breast carcinoma. Functional experiments demonstrated that SLC12A8-knockdown suppressed while SLC12A8-overexpression elevated the viability, invasiveness and motility of breast carcinoma cells. Furthermore, GSEA indicated that high SLC12A8 was positively correlated with TLR/NLR signaling pathway. Silencing SLC12A8 significantly reduced the protein expression of TLR/NLR-related markers, whereas overexpression of SLC12A8 caused an elevation on the protein expression of these markers. All these data suggested that SLC12A8 plays a promoting effect on the cells viability, invasiveness and motility in breast carcinoma by activating TLR/NLR signaling pathway.

MYC Instructs and Maintains Pancreatic Adenocarcinoma Phenotype

The signature features of pancreatic ductal adenocarcinoma (PDAC) are its fibroinflammatory stroma, poor immune activity, and dismal prognosis. We show that acute activation of Myc in indolent pancreatic intraepithelial neoplasm (PanIN) epithelial cells in vivo is, alone, sufficient to trigger immediate release of instructive signals that together coordinate changes in multiple stromal and immune-cell types and drive transition to pancreatic adenocarcinomas that share all the characteristic stromal features of their spontaneous human counterpart. We also demonstrate that this Myc-driven PDAC switch is completely and immediately reversible: Myc deactivation/inhibition triggers meticulous disassembly of advanced PDAC tumor and stroma and concomitant death of tumor cells. Hence, both the formation and deconstruction of the complex PDAC phenotype are continuously dependent on a single, reversible Myc switch. SIGNIFICANCE: We show that Myc activation in indolent Kras G12D-induced PanIN epithelium acts as an immediate pleiotropic switch, triggering tissue-specific signals that instruct all the diverse signature stromal features of spontaneous human PDAC. Subsequent Myc deactivation or inhibition immediately triggers a program that coordinately disassembles PDAC back to PanIN.See related commentary by English and Sears, p. 495.

Alternative polyadenylation drives oncogenic gene expression in pancreatic ductal adenocarcinoma

Alternative polyadenylation (APA) is a gene regulatory process that dictates mRNA 3'-UTR length, resulting in changes in mRNA stability and localization. APA is frequently disrupted in cancer and promotes tumorigenesis through altered expression of oncogenes and tumor suppressors. Pan-cancer analyses have revealed common APA events across the tumor landscape; however, little is known about tumor type-specific alterations that may uncover novel events and vulnerabilities. Here, we integrate RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project and The Cancer Genome Atlas (TCGA) to comprehensively analyze APA events in 148 pancreatic ductal adenocarcinomas (PDACs). We report widespread, recurrent, and functionally relevant 3'-UTR alterations associated with gene expression changes of known and newly identified PDAC growth-promoting genes and experimentally validate the effects of these APA events on protein expression. We find enrichment for APA events in genes associated with known PDAC pathways, loss of tumor-suppressive miRNA binding sites, and increased heterogeneity in 3'-UTR forms of metabolic genes. Survival analyses reveal a subset of 3'-UTR alterations that independently characterize a poor prognostic cohort among PDAC patients. Finally, we identify and validate the casein kinase CSNK1A1 (also known as CK1alpha or CK1a) as an APA-regulated therapeutic target in PDAC. Knockdown or pharmacological inhibition of CSNK1A1 attenuates PDAC cell proliferation and clonogenic growth. Our single-cancer analysis reveals APA as an underappreciated driver of protumorigenic gene expression in PDAC via the loss of miRNA regulation.

Recent insights into the biology of pancreatic cancer

Pancreatic cancer (PDAC) is one of the deadliest types of human cancers, owing to late stage at presentation and pervasive therapeutic resistance. The extensive tumour heterogeneity, as well as substantial crosstalk between the neoplastic epithelium and components within the microenvironment are the defining features of PDAC biology that dictate the dismal natural history. Recent advances in genomic and molecular profiling have informed on the genetic makeup and evolutionary patterns of tumour progression, leading to treatment breakthroughs in minor subsets of patients with specific tumour mutational profiles. The nature and function of tumour heterogeneity, including stromal heterogeneity, in PDAC development and therapeutic resistance, are increasingly being elucidated. Deep insight has been gained regarding the metabolic and immunological deregulation, which further sheds light on the complex biology and the observed treatment recalcitrance. Here we will summarize these recent achievements and offer our perspective on the path forward.

Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations

Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.

How to interpret and integrate multi-omics data at systems level

Current parallel sequencing technologies generate biological sequence data explosively and enable omics studies that analyze collective biological features. The more omics data that is accumulated, the more they show the regulatory complexity of biological phenotypes. This high order regulatory complexity needs systems-level approaches, including network analysis, to understand it. There are a series of layers in the omics field that are closely connected to each other as described in ‘central dogma.’ We, therefore, have to not only interpret each single omics layer but also to integrate multi-omics layers systematically to get a full picture of the regulatory landscape of the biological phenotype. Especially, individual omics data has their own adequate biological network to apply systematic analysis appropriately. A full regulatory landscape can only be obtained when multi-omics data are incorporated within adequate networks. In this review, we discuss how to interpret and integrate multi-omics data systematically using recent studies. We also propose an analysis framework for systematic multi-omics interpretation by centering on the transcriptional core regulator, which can be incorporated in all omics networks.

Noncoding mutations target cis-regulatory elements of the FOXA1 plexus in prostate cancer

Prostate cancer is the second most commonly diagnosed malignancy among men worldwide. Recurrently mutated in primary and metastatic prostate tumors, FOXA1 encodes a pioneer transcription factor involved in disease onset and progression through both androgen receptor-dependent and androgen receptor-independent mechanisms. Despite its oncogenic properties however, the regulation of FOXA1 expression remains unknown. Here, we identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic single-nucleotide variants in primary prostate tumors. We find that deletion and repression of these cis-regulatory elements significantly decreases FOXA1 expression and prostate cancer cell growth. Six of the ten single-nucleotide variants mapping to FOXA1 regulatory plexus significantly alter the transactivation potential of cis-regulatory elements by modulating the binding of transcription factors. Collectively, our results identify cis-regulatory elements within the FOXA1 plexus mutated in primary prostate tumors as potential targets for therapeutic intervention.

FOXA1 pioneer transcription factor is recurrently mutated in primary and metastatic prostate tumors. Here, authors identify a set of six cis-regulatory elements in the FOXA1 regulatory plexus harboring somatic SNVs in primary prostate tumors and characterize their role in regulating FOXA1 expression and prostate cancer cell growth.

Identification of recurrent noncoding mutations in B-cell lymphoma using capture Hi-C

The identification of driver mutations is fundamental to understanding oncogenesis. Although genes frequently mutated in B-cell lymphoma have been identified, the search for driver mutations has largely focused on the coding genome. Here we report an analysis of the noncoding genome using whole-genome sequencing data from 117 patients with B-cell lymphoma. Using promoter capture Hi-C data in naive B cells, we define cis-regulatory elements, which represent an enriched subset of the noncoding genome in which to search for driver mutations. Regulatory regions were identified whose mutation significantly alters gene expression, including copy number variation at cis-regulatory elements targeting CD69, IGLL5, and MMP14, and single nucleotide variants in a cis-regulatory element for TPRG1 We also show the commonality of pathways targeted by coding and noncoding mutations, exemplified by MMP14, which regulates Notch signaling, a pathway important in lymphomagenesis and whose expression is associated with patient survival. This study provides an enhanced understanding of lymphomagenesis and describes the advantages of using chromosome conformation capture to decipher noncoding mutations relevant to cancer biology.

Genomics meets immunity in pancreatic cancer: Current research and future directions for pancreatic adenocarcinoma immunotherapy

Pancreatic adenocarcinoma (PDAC) remains a formidable disease that needs improved therapeutic strategies. Even though immunotherapy has revolutionized treatment for various solid tumor types, it remains largely ineffective in treating individuals with PDAC. This review describes how the application of genome-wide analysis is revitalizing the field of PDAC immunotherapy. Major themes include new insights into the body’s immune response to the cancer, and key immunosuppressive elements that blunt that antitumor immunity. In particular, new evidence indicates that T cell-based antitumor immunity against PDAC is more common, and more easily generated, than previously thought. However, equally common are an array of cellular and molecular defenses employed by the tumor against those T cells. These discoveries have changed how current immunotherapies are deployed and have directed development of novel strategies to better treat this disease. Thus, the impact of genomic analysis has been two-fold: both in demonstrating the heterogeneity of immune targets and defenses in this disease, as well as providing a powerful tool for designing and identifying personalized therapies that exploit each tumor’s unique phenotype. Such personalized treatment combinations may be the key to developing successful immunotherapies for pancreatic adenocarcinoma.

IW-Scoring: an Integrative Weighted Scoring framework for annotating and prioritizing genetic variations in the noncoding genome

The vast majority of germline and somatic variations occur in the noncoding part of the genome, only a small fraction of which are believed to be functional. From the tens of thousands of noncoding variations detectable in each genome, identifying and prioritizing driver candidates with putative functional significance is challenging. To address this, we implemented IW-Scoring, a new Integrative Weighted Scoring model to annotate and prioritise functionally relevant noncoding variations. We evaluate 11 scoring methods, and apply an unsupervised spectral approach for subsequent selective integration into two linear weighted functional scoring schemas for known and novel variations. IW-Scoring produces stable high-quality performance as the best predictors for three independent data sets. We demonstrate the robustness of IW-Scoring in identifying recurrent functional mutations in the TERT promoter, as well as disease SNPs in proximity to consensus motifs and with gene regulatory effects. Using follicular lymphoma as a paradigmatic cancer model, we apply IW-Scoring to locate 11 recurrently mutated noncoding regions in 14 follicular lymphoma genomes, and validate 9 of these regions in an extension cohort, including the promoter and enhancer regions of PAX5. Overall, IW-Scoring demonstrates greater versatility in identifying trait- and disease-associated noncoding variants. Scores from IW-Scoring as well as other methods are freely available from http://www.snp-nexus.org/IW-Scoring/.

Dissecting the sources of gene expression variation in a pan-cancer analysis identifies novel regulatory mutations

Although the catalog of cancer-associated mutations in protein-coding regions is nearly complete for all major cancer types, an assessment of regulatory changes in cancer genomes and their clinical significance remain largely preliminary. Adopting bottom-up approach, we quantify the effects of different sources of gene expression variation in a cohort of 3899 samples from 10 cancer types. We find that copy number alterations, epigenetic changes, transcription factors and microRNAs collectively explain, on average, only 31–38% and 18–26% expression variation for cancer-associated and other genes, respectively, and that among these factors copy number alteration has the highest effect. We show that the genes with systematic, large expression variation that could not be attributed to these factors are enriched for pathways related to cancer hallmarks. Integrating whole genome sequencing data and focusing on genes with systematic expression variation we identify novel, recurrent regulatory mutations affecting known cancer genes such as NKX2-1 and GRIN2D in multiple cancer types. Nonetheless, at a genome-wide scale proportions of gene expression variation attributed to recurrent point mutations appear to be modest so far, especially when compared to that attributed to copy number changes – a pattern different from that observed for other complex diseases and traits. We suspect that, owing to plasticity and redundancy in biological pathways, regulatory alterations show complex combinatorial patterns, modulating gene expression in cancer genomes at a finer scale.

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk

We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts the specific regulatory effects and the deleterious impact of genetic variants. Applying this framework to 1,790 autism spectrum disorder (ASD) simplex families reveals a role in disease for noncoding mutations-ASD probands harbor both transcriptional- and post-transcriptional-regulation-disrupting de novo mutations of significantly higher functional impact than those in unaffected siblings. Further analysis suggests involvement of noncoding mutations in synaptic transmission and neuronal development and, taken together with previous studies, reveals a convergent genetic landscape of coding and noncoding mutations in ASD. We demonstrate that sequences carrying prioritized mutations identified in probands possess allele-specific regulatory activity, and we highlight a link between noncoding mutations and heterogeneity in the IQ of ASD probands. Our predictive genomics framework illuminates the role of noncoding mutations in ASD and prioritizes mutations with high impact for further study, and is broadly applicable to complex human diseases.

Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases

We integrated clinical, genomic, and transcriptomic data from 224 primaries and 95 metastases from 289 patients to characterize progression of pancreatic ductal adenocarcinoma (PDAC). Driver gene alterations and mutational and expression-based signatures were preserved, with truncations, inversions, and translocations most conserved. Cell cycle progression (CCP) increased with sequential inactivation of tumor suppressors, yet remained higher in metastases, perhaps driven by cell cycle regulatory gene variants. Half of the cases were hypoxic by expression markers, overlapping with molecular subtypes. Paired tumor heterogeneity showed cancer cell migration by Halstedian progression. Multiple PDACs arising synchronously and metachronously in the same pancreas were actually intra-parenchymal metastases, not independent primary tumors. Established clinical co-variates dominated survival analyses, although CCP and hypoxia may inform clinical practice.

Personal Mutanomes Meet Modern Oncology Drug Discovery and Precision Health

Recent remarkable advances in genome sequencing have enabled detailed maps of identified and interpreted genomic variation, dubbed "mutanomes." The availability of thousands of exome/genome sequencing data has prompted the emergence of new challenges in the identification of novel druggable targets and therapeutic strategies. Typically, mutanomes are viewed as one- or two-dimensional. The three-dimensional protein structural view of personal mutanomes sheds light on the functional consequences of clinically actionable mutations revealed in tumor diagnosis and followed up in personalized treatments, in a mutanome-informed manner. In this review, we describe the protein structural landscape of personal mutanomes and provide expert opinions on rational strategies for more streamlined oncological drug discovery and molecularly targeted therapies for each individual and each tumor. We provide the structural mechanism of orthosteric versus allosteric drugs at the atom-level via targeting specific somatic alterations for combating drug resistance and the "undruggable" challenges in solid and hematologic neoplasias. We discuss computational biophysics strategies for innovative mutanome-informed cancer immunotherapies and combination immunotherapies. Finally, we highlight a personal mutanome infrastructure for the emerging development of personalized cancer medicine using a breast cancer case study.

Slc12a8 is a nicotinamide mononucleotide transporter

Nicotinamide mononucleotide (NMN) is a biosynthetic precursor of NAD⁺ known to promote cellular NAD⁺ production and counteract age-associated pathologies associated with a decline in tissue NAD⁺ levels. How NMN is taken up into cells has not been entirely clear. Here we show that the Slc12a8 gene encodes a specific NMN transporter. We find that Slc12a8 is highly expressed and regulated by NAD⁺ in the murine small intestine. Slc12a8 knockdown abrogates the uptake of NMN in vitro and in vivo. We further show that Slc12a8 specifically transports NMN, but not nicotinamide riboside, and that NMN transport depends on the presence of sodium ion. Slc12a8 deficiency significantly decreases NAD⁺ levels in the jejunum and ileum, which is associated with reduced NMN uptake as traced by doubly labeled isotopic NMN. Finally, we observe that Slc12a8 expression is upregulated in the aged murine ileum, which contributes to the maintenance of ileal NAD⁺ levels. Our work identifies the first NMN transporter and demonstrates that Slc12a8 has a critical role in regulating intestinal NAD⁺ metabolism.

The Identification and Interpretation of cis-Regulatory Noncoding Mutations in Cancer

In the need to characterise the genomic landscape of cancers and to establish novel biomarkers and therapeutic targets, studies have largely focused on the identification of driver mutations within the protein-coding gene regions, where the most pathogenic alterations are known to occur. However, the noncoding genome is significantly larger than its protein-coding counterpart, and evidence reveals that regulatory sequences also harbour functional mutations that significantly affect the regulation of genes and pathways implicated in cancer. Due to the sheer number of noncoding mutations (NCMs) and the limited knowledge of regulatory element functionality in cancer genomes, differentiating pathogenic mutations from background passenger noise is particularly challenging technically and computationally. Here we review various up-to-date high-throughput sequencing data/studies and in silico methods that can be employed to interrogate the noncoding genome. We aim to provide an overview of available data resources as well as computational and molecular techniques that can help and guide the search for functional NCMs in cancer genomes.

Combined inhibition of the PI3K/mTOR/MEK pathway induces Bim/Mcl-1-regulated apoptosis in pancreatic cancer cells

Pancreatic ductal adenocarcinoma (PDAC) progression and chemotherapy insensitivity have been associated with aberrant PI3K/mTOR/MEK signalling. However, cell death responses activated by inhibitors of these pathways can differ – contextually varying with tumour genetic background. Here, we demonstrate that combining the dual PI3K/mTOR inhibitor PF5212384 (PF384) and MEK inhibitor PD325901 (PD901) more effectively induces apoptosis compared with either agent alone, independent of KRAS mutational status in PDAC cell lines. Additionally, a non-caspase dependent decrease in cell viability upon PF384 treatment was observed, and may be attributed to autophagy and G0/G1 cell cycle arrest. Using reverse phase protein arrays, we identify key molecular events associated with the conversion of cytostatic responses (elicited by single inhibitor treatments) into a complete cell death response when PF384 and PD901 are combined. This response was also independent of KRAS mutation, occurring in both BxPC3 (KRAS wildtype) and MIA-PaCa-2 (KRAS^G12C mutated) cells. In both cell lines, Bim expression increased in response to PF384/PD901 treatment (by 60% and 48%, respectively), while siRNA-mediated silencing of Bim attenuated the apoptosis induced by combination treatment. In parallel, Mcl-1 levels decreased by 36% in BxPC3, and 30% in MIA-PaCa-2 cells. This is consistent with a functional role for Mcl-1, and siRNA-mediated silencing enhanced apoptosis in PF384/PD901-treated MIA-PaCa-2 cells, whilst Mcl-1 overexpression decreased apoptosis induction by 24%. Moreover, a novel role was identified for PDCD4 loss in driving the apoptotic response to PF384/PD901 in BxPC3 and MIA-PaCa-2 cell lines. Overall, our data indicates PF384/PD901 co-treatment activates the same apoptotic mechanism in wild-type or KRAS mutant PDAC cells.

Mutation hotspots at CTCF binding sites coupled to chromosomal instability in gastrointestinal cancers

Tissue-specific driver mutations in non-coding genomic regions remain undefined for most cancer types. Here, we unbiasedly analyze 212 gastric cancer (GC) whole genomes to identify recurrently mutated non-coding regions in GC. Applying comprehensive statistical approaches to accurately model background mutational processes, we observe significant enrichment of non-coding indels (insertions/deletions) in three gastric lineage-specific genes. We further identify 34 mutation hotspots, of which 11 overlap CTCF binding sites (CBSs). These CBS hotspots remain significant even after controlling for a genome-wide elevated mutation rate at CBSs. In 3 out of 4 tested CBS hotspots, mutations are nominally associated with expression change of neighboring genes. CBS hotspot mutations are enriched in tumors showing chromosomal instability, co-occur with neighboring chromosomal aberrations, and are common in gastric (25%) and colorectal (19%) tumors but rare in other cancer types. Mutational disruption of specific CBSs may thus represent a tissue-specific mechanism of tumorigenesis conserved across gastrointestinal cancers.

The impact of non-coding somatic mutations in gastric cancer is unknown. Here, using whole genome sequencing data from 212 gastric tumors, the authors identify recurring mutations at specific CTCF binding sites that are common across gastrointestinal cancers and associated with chromosomal instability.

New Developments in the Molecular Mechanisms of Pancreatic Tumorigenesis

Pancreatic cancer is an aggressive disease with a dismal prognosis in dire need of novel diagnostic and therapeutic approaches. The past decade has witnessed an explosion of data on the genetic alterations that occur in pancreatic cancer, as comprehensive next-generation sequencing analyses have been performed on samples from large cohorts of patients. These studies have defined the genomic landscape of this disease and identified novel candidates whose mutations contribute to pancreatic tumorigenesis. They have also clarified the genetic alterations that underlie multistep tumorigenesis in precursor lesions and provided insights into clonal evolution in pancreatic neoplasia. In addition to these important insights into pancreatic cancer biology, these large scale genomic studies have also provided a foundation for the development of novel early detection strategies and targeted therapies. In this review, we discuss the results of these comprehensive sequencing studies of pancreatic neoplasms, with a particular focus on how their results will impact the clinical care of patients with pancreatic cancer.

An overview of polyamine metabolism in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest major cancers, with a five year survival rate of less than 8%. With current therapies only giving rise to modest life extension, new approaches are desperately needed. Even though targeting polyamine metabolism is a proven anticancer strategy, there are no reports, which thoroughly survey the literature describing the role of polyamine biosynthesis and transport in PDAC. This review seeks to fill this void by describing what is currently known about polyamine metabolism in PDAC and identifies new targets and opportunities to treat this disease. Due to the pleiotropic effects that polyamines play in cells, this review covers diverse areas ranging from polyamine metabolism (biosynthesis, catabolism and transport), as well as the potential role of polyamines in desmoplasia, autophagy and immune privilege. Understanding these diverse roles provides the opportunity to design new therapies to treat this deadly cancer via polyamine depletion.

Functional analysis of a CDKN2A 5'UTR germline variant associated with pancreatic cancer development

CDKN2A coding region germline variants are associated with pancreatic adenocarcinoma (PC) susceptibility. Recently, we described functional germline 5’UTR CDKN2A variants from melanoma patients affecting the post-transcriptional regulation of p16^INK4a mRNA that is dependent, at least in part, on an Internal Ribosome Entry Site (IRES) in the 5’UTR region. Here we describe a 5’UTR c.-201_-198delinsCTTT CDKN2A variant (frequency 0.0028 based on 350 PC patients), which seems to be private to PC, since it has never been found in public databases nor in thousands of melanoma patients tested. Functional analyses confirmed IRES activity of the 5’UTR in BX-PC3 PC cells and revealed a functional impact of the identified variant. Using gene reporter assays we observed reduced translation potential in cells treated with the mTOR inhibitor Torin1, a condition that favors the assessment of IRES activity. At the endogenous gene level we quantified allelic imbalance among polysome-associated mRNAs using a patient-derived cell line heterozygous for the c.-201_-198delinsCTTT. Overall, we conclude that this very rare private variant can be considered a potential mutation, specifically associated with PC. Our data indicate that sequencing of the entire 5'UTR of CDKN2A should be included in routine screening of PC cases with suspected inherited susceptibility.

Pancreatic Cancer: Molecular Characterization, Clonal Evolution and Cancer Stem Cells

Pancreatic Ductal Adenocarcinoma (PDAC) is the fourth most common cause of cancer-related death and is the most lethal of common malignancies with a five-year survival rate of <10%. PDAC arises from different types of non-invasive precursor lesions: intraductal papillary mucinous neoplasms, mucinous cystic neoplasms and pancreatic intraepithelial neoplasia. The genetic landscape of PDAC is characterized by the presence of four frequently-mutated genes: KRAS, CDKN2A, TP53 and SMAD4. The development of mouse models of PDAC has greatly contributed to the understanding of the molecular and cellular mechanisms through which driver genes contribute to pancreatic cancer development. Particularly, oncogenic KRAS-driven genetically-engineered mouse models that phenotypically and genetically recapitulate human pancreatic cancer have clarified the mechanisms through which various mutated genes act in neoplasia induction and progression and have led to identifying the possible cellular origin of these neoplasias. Patient-derived xenografts are increasingly used for preclinical studies and for the development of personalized medicine strategies. The studies of the purification and characterization of pancreatic cancer stem cells have suggested that a minority cell population is responsible for initiation and maintenance of pancreatic adenocarcinomas. The study of these cells could contribute to the identification and clinical development of more efficacious drug treatments.

Integrated analysis of long non-coding RNAs in human gastric cancer: An in silico study

Accumulating evidence highlights the important role of long non-coding RNAs (lncRNAs) in a large number of biological processes. However, the knowledge of genome scale expression of lncRNAs and their potential biological function in gastric cancer is still lacking. Using RNA-seq data from 420 gastric cancer patients in The Cancer Genome Atlas (TCGA), we identified 1,294 lncRNAs differentially expressed in gastric cancer compared with adjacent normal tissues. We also found 247 lncRNAs differentially expressed between intestinal subtype and diffuse subtype. Survival analysis revealed 33 lncRNAs independently associated with patient overall survival, of which 6 lncRNAs were validated in the internal validation set. There were 181 differentially expressed lncRNAs located in the recurrent somatic copy number alterations (SCNAs) regions and their correlations between copy number and RNA expression level were also analyzed. In addition, we inferred the function of lncRNAs by construction of a co-expression network for mRNAs and lncRNAs. Together, this study presented an integrative analysis of lncRNAs in gastric cancer and provided a valuable resource for further functional research of lncRNAs in gastric cancer.