A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters.

Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. However, while a global change in transcription is recognized as a defining feature of cancer, the contribution of alternative promoters still remains largely unexplored. Here, we infer active promoters using RNA-seq data from 18,468 cancer and normal samples, demonstrating that alternative promoters are a major contributor to context-specific regulation of transcription. We find that promoters are deregulated across tissues, cancer types, and patients, affecting known cancer genes and novel candidates. For genes with independently regulated promoters, we demonstrate that promoter activity provides a more accurate predictor of patient survival than gene expression. Our study suggests that a dynamic landscape of active promoters shapes the cancer transcriptome, opening new diagnostic avenues and opportunities to further explore the interplay of regulatory mechanisms with transcriptional aberrations in cancer.

Large-Scale Whole-Genome Sequencing of Three Diverse Asian Populations in Singapore.

Underrepresentation of Asian genomes has hindered population and medical genetics research on Asians, leading to population disparities in precision medicine. By whole-genome sequencing of 4,810 Singapore Chinese, Malays, and Indians, we found 98.3 million SNPs and small insertions or deletions, over half of which are novel. Population structure analysis demonstrated great representation of Asian genetic diversity by three ethnicities in Singapore and revealed a Malay-related novel ancestry component. Furthermore, demographic inference suggested that Malays split from Chinese ∼24,800 years ago and experienced significant admixture with East Asians ∼1,700 years ago, coinciding with the Austronesian expansion. Additionally, we identified 20 candidate loci for natural selection, 14 of which harbored robust associations with complex traits and diseases. Finally, we show that our data can substantially improve genotype imputation in diverse Asian and Oceanian populations. These results highlight the value of our data as a resource to empower human genetics discovery across broad geographic regions.

Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer.

Gastric cancer (GC) is the fifth most common cancer worldwide and is a heterogeneous disease. Among GC subtypes, the mesenchymal phenotype (Mes-like) is more invasive than the epithelial phenotype (Epi-like). Although gene expression of the epithelial-to-mesenchymal transition (EMT) has been studied, the regulatory landscape shaping this process is not fully understood. Here we use ATAC-seq and RNA-seq data from a compendium of GC cell lines and primary tumors to detect drivers of regulatory state changes and their transcriptional responses. Using the ATAC-seq data, we developed a machine learning approach to determine the transcription factors (TFs) regulating the subtypes of GC. We identified TFs driving the mesenchymal (RUNX2, ZEB1, SNAI2, AP-1 dimer) and the epithelial (GATA4, GATA6, KLF5, HNF4A, FOXA2, GRHL2) states in GC. We identified DNA copy number alterations associated with dysregulation of these TFs, specifically deletion of GATA4 and amplification of MAPK9 Comparisons with bulk and single-cell RNA-seq data sets identified activation toward fibroblast-like epigenomic and expression signatures in Mes-like GC. The activation of this mesenchymal fibrotic program is associated with differentially accessible DNA cis-regulatory elements flanking upregulated mesenchymal genes. These findings establish a map of TF activity in GC and highlight the role of copy number driven alterations in shaping epigenomic regulatory programs as potential drivers of GC heterogeneity and progression.

AQP5 enriches for stem cells and cancer origins in the distal stomach.

LGR5 marks resident adult epithelial stem cells at the gland base in the mouse pyloric stomach1, but the identity of the equivalent human stem cell population remains unknown owing to a lack of surface markers that facilitate its prospective isolation and validation. In mouse models of intestinal cancer, LGR5+ intestinal stem cells are major sources of cancer following hyperactivation of the WNT pathway2. However, the contribution of pyloric LGR5+ stem cells to gastric cancer following dysregulation of the WNT pathway-a frequent event in gastric cancer in humans3-is unknown. Here we use comparative profiling of LGR5+ stem cell populations along the mouse gastrointestinal tract to identify, and then functionally validate, the membrane protein AQP5 as a marker that enriches for mouse and human adult pyloric stem cells. We show that stem cells within the AQP5+ compartment are a source of WNT-driven, invasive gastric cancer in vivo, using newly generated Aqp5-creERT2 mouse models. Additionally, tumour-resident AQP5+ cells can selectively initiate organoid growth in vitro, which indicates that this population contains potential cancer stem cells. In humans, AQP5 is frequently expressed in primary intestinal and diffuse subtypes of gastric cancer (and in metastases of these subtypes), and often displays altered cellular localization compared with healthy tissue. These newly identified markers and mouse models will be an invaluable resource for deciphering the early formation of gastric cancer, and for isolating and characterizing human-stomach stem cells as a prerequisite for harnessing the regenerative-medicine potential of these cells in the clinic.

Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

Regulatory enhancer profiling of mesenchymal-type gastric cancer reveals subtype-specific epigenomic landscapes and targetable vulnerabilities.

OBJECTIVE: Gastric cancer (GC) comprises multiple molecular subtypes. Recent studies have highlighted mesenchymal-subtype GC (Mes-GC) as a clinically aggressive subtype with few treatment options. Combining multiple studies, we derived and applied a consensus Mes-GC classifier to define the Mes-GC enhancer landscape revealing disease vulnerabilities. DESIGN: Transcriptomic profiles of ~1000 primary GCs and cell lines were analysed to derive a consensus Mes-GC classifier. Clinical and genomic associations were performed across >1200 patients with GC. Genome-wide epigenomic profiles (H3K27ac, H3K4me1 and assay for transposase-accessible chromatin with sequencing (ATAC-seq)) of 49 primary GCs and GC cell lines were generated to identify Mes-GC-specific enhancer landscapes. Upstream regulators and downstream targets of Mes-GC enhancers were interrogated using chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA sequencing, CRISPR/Cas9 editing, functional assays and pharmacological inhibition. RESULTS: We identified and validated a 993-gene cancer-cell intrinsic Mes-GC classifier applicable to retrospective cohorts or prospective single samples. Multicohort analysis of Mes-GCs confirmed associations with poor patient survival, therapy resistance and few targetable genomic alterations. Analysis of enhancer profiles revealed a distinctive Mes-GC epigenomic landscape, with TEAD1 as a master regulator of Mes-GC enhancers and Mes-GCs exhibiting preferential sensitivity to TEAD1 pharmacological inhibition. Analysis of Mes-GC super-enhancers also highlighted NUAK1 kinase as a downstream target, with synergistic effects observed between NUAK1 inhibition and cisplatin treatment. CONCLUSION: Our results establish a consensus Mes-GC classifier applicable to multiple transcriptomic scenarios. Mes-GCs exhibit a distinct epigenomic landscape, and TEAD1 inhibition and combinatorial NUAK1 inhibition/cisplatin may represent potential targetable options.

Comprehensive molecular phenotyping of ARID1A-deficient gastric cancer reveals pervasive epigenomic reprogramming and therapeutic opportunities.

OBJECTIVE: Gastric cancer (GC) is a leading cause of cancer mortality, with ARID1A being the second most frequently mutated driver gene in GC. We sought to decipher ARID1A-specific GC regulatory networks and examine therapeutic vulnerabilities arising from ARID1A loss. DESIGN: Genomic profiling of GC patients including a Singapore cohort (>200 patients) was performed to derive mutational signatures of ARID1A inactivation across molecular subtypes. Single-cell transcriptomic profiles of ARID1A-mutated GCs were analysed to examine tumour microenvironmental changes arising from ARID1A loss. Genome-wide ARID1A binding and chromatin profiles (H3K27ac, H3K4me3, H3K4me1, ATAC-seq) were generated to identify gastric-specific epigenetic landscapes regulated by ARID1A. Distinct cancer hallmarks of ARID1A-mutated GCs were converged at the genomic, single-cell and epigenomic level, and targeted by pharmacological inhibition. RESULTS: We observed prevalent ARID1A inactivation across GC molecular subtypes, with distinct mutational signatures and linked to a NFKB-driven proinflammatory tumour microenvironment. ARID1A-depletion caused loss of H3K27ac activation signals at ARID1A-occupied distal enhancers, but unexpectedly gain of H3K27ac at ARID1A-occupied promoters in genes such as NFKB1 and NFKB2. Promoter activation in ARID1A-mutated GCs was associated with enhanced gene expression, increased BRD4 binding, and reduced HDAC1 and CTCF occupancy. Combined targeting of promoter activation and tumour inflammation via bromodomain and NFKB inhibitors confirmed therapeutic synergy specific to ARID1A-genomic status. CONCLUSION: Our results suggest a therapeutic strategy for ARID1A-mutated GCs targeting both tumour-intrinsic (BRD4-assocatiated promoter activation) and extrinsic (NFKB immunomodulation) cancer phenotypes.

Integrative multiomics enhancer activity profiling identifies therapeutic vulnerabilities in cholangiocarcinoma of different etiologies.

OBJECTIVES: Cholangiocarcinoma (CCA) is a heterogeneous malignancy with high mortality and dismal prognosis, and an urgent clinical need for new therapies. Knowledge of the CCA epigenome is largely limited to aberrant DNA methylation. Dysregulation of enhancer activities has been identified to affect carcinogenesis and leveraged for new therapies but is uninvestigated in CCA. Our aim is to identify potential therapeutic targets in different subtypes of CCA through enhancer profiling. DESIGN: Integrative multiomics enhancer activity profiling of diverse CCA was performed. A panel of diverse CCA cell lines, patient-derived and cell line-derived xenografts were used to study identified enriched pathways and vulnerabilities. NanoString, multiplex immunohistochemistry staining and single-cell spatial transcriptomics were used to explore the immunogenicity of diverse CCA. RESULTS: We identified three distinct groups, associated with different etiologies and unique pathways. Drug inhibitors of identified pathways reduced tumour growth in in vitro and in vivo models. The first group (ESTRO), with mostly fluke-positive CCAs, displayed activation in estrogen signalling and were sensitive to MTOR inhibitors. Another group (OXPHO), with mostly BAP1 and IDH-mutant CCAs, displayed activated oxidative phosphorylation pathways, and were sensitive to oxidative phosphorylation inhibitors. Immune-related pathways were activated in the final group (IMMUN), made up of an immunogenic CCA subtype and CCA with aristolochic acid (AA) mutational signatures. Intratumour differences in AA mutation load were correlated to intratumour variation of different immune cell populations. CONCLUSION: Our study elucidates the mechanisms underlying enhancer dysregulation and deepens understanding of different tumourigenesis processes in distinct CCA subtypes, with potential significant therapeutics and clinical benefits.

RegAB Homolog of Burkholderia pseudomallei is the Master Regulator of Redox Control and involved in Virulence.

Burkholderia pseudomallei, the etiological agent of melioidosis in humans and animals, often occupies environmental niches and infection sites characterized by limited concentrations of oxygen. Versatile genomic features enable this pathogen to maintain its physiology and virulence under hypoxia, but the crucial regulatory networks employed to switch from oxygen dependent respiration to alternative terminal electron acceptors (TEA) like nitrate, remains poorly understood. Here, we combined a Tn5 transposon mutagenesis screen and an anaerobic growth screen to identify a two-component signal transduction system with homology to RegAB. We show that RegAB is not only essential for anaerobic growth, but also for full virulence in cell lines and a mouse infection model. Further investigations of the RegAB regulon, using a global transcriptomic approach, identified 20 additional regulators under transcriptional control of RegAB, indicating a superordinate role of RegAB in the B. pseudomallei anaerobiosis regulatory network. Of the 20 identified regulators, NarX/L and a FNR homolog were selected for further analyses and a role in adaptation to anaerobic conditions was demonstrated. Growth experiments identified nitrate and intermediates of the denitrification process as the likely signal activateing RegAB, NarX/L, and probably of the downstream regulators Dnr or NsrR homologs. While deletions of individual genes involved in the denitrification process demonstrated their important role in anaerobic fitness, they showed no effect on virulence. This further highlights the central role of RegAB as the master regulator of anaerobic metabolism in B. pseudomallei and that the complete RegAB-mediated response is required to achieve full virulence. In summary, our analysis of the RegAB-dependent modulon and its interconnected regulons revealed a key role for RegAB of B. pseudomallei in the coordination of the response to hypoxic conditions and virulence, in the environment and the host.

Histone lysine methyltransferase Pr-set7/SETD8 promotes neural stem cell reactivation.

The ability of neural stem cells (NSCs) to switch between quiescence and proliferation is crucial for brain development and homeostasis. Increasing evidence suggests that variants of histone lysine methyltransferases including KMT5A are associated with neurodevelopmental disorders. However, the function of KMT5A/Pr-set7/SETD8 in the central nervous system is not well established. Here, we show that Drosophila Pr-Set7 is a novel regulator of NSC reactivation. Loss of function of pr-set7 causes a delay in NSC reactivation and loss of H4K20 monomethylation in the brain. Through NSC-specific in vivo profiling, we demonstrate that Pr-set7 binds to the promoter region of cyclin-dependent kinase 1 (cdk1) and Wnt pathway transcriptional co-activator earthbound1/jerky (ebd1). Further validation indicates that Pr-set7 is required for the expression of cdk1 and ebd1 in the brain. Similar to Pr-set7, Cdk1 and Ebd1 promote NSC reactivation. Finally, overexpression of Cdk1 and Ebd1 significantly suppressed NSC reactivation defects observed in pr-set7-depleted brains. Therefore, Pr-set7 promotes NSC reactivation by regulating Wnt signaling and cell cycle progression. Our findings may contribute to the understanding of mammalian KMT5A/PR-SET7/SETD8 during brain development.

Deep learning-based subtyping of gastric cancer histology predicts clinical outcome: a multi-institutional retrospective study.

INTRODUCTION: The Laurén classification is widely used for Gastric Cancer (GC) histology subtyping. However, this classification is prone to interobserver variability and its prognostic value remains controversial. Deep Learning (DL)-based assessment of hematoxylin and eosin (H&E) stained slides is a potentially useful tool to provide an additional layer of clinically relevant information, but has not been systematically assessed in GC. OBJECTIVE: We aimed to train, test and externally validate a deep learning-based classifier for GC histology subtyping using routine H&E stained tissue sections from gastric adenocarcinomas and to assess its potential prognostic utility. METHODS: We trained a binary classifier on intestinal and diffuse type GC whole slide images for a subset of the TCGA cohort (N = 166) using attention-based multiple instance learning. The ground truth of 166 GC was obtained by two expert pathologists. We deployed the model on two external GC patient cohorts, one from Europe (N = 322) and one from Japan (N = 243). We assessed classification performance using the Area Under the Receiver Operating Characteristic Curve (AUROC) and prognostic value (overall, cancer specific and disease free survival) of the DL-based classifier with uni- and multivariate Cox proportional hazard models and Kaplan-Meier curves with log-rank test statistics. RESULTS: Internal validation using the TCGA GC cohort using five-fold cross-validation achieved a mean AUROC of 0.93 ± 0.07. External validation showed that the DL-based classifier can better stratify GC patients' 5-year survival compared to pathologist-based Laurén classification for all survival endpoints, despite frequently divergent model-pathologist classifications. Univariate overall survival Hazard Ratios (HRs) of pathologist-based Laurén classification (diffuse type versus intestinal type) were 1.14 (95% Confidence Interval (CI) 0.66-1.44, p-value = 0.51) and 1.23 (95% CI 0.96-1.43, p-value = 0.09) in the Japanese and European cohorts, respectively. DL-based histology classification resulted in HR of 1.46 (95% CI 1.18-1.65, p-value < 0.005) and 1.41 (95% CI 1.20-1.57, p-value < 0.005), in the Japanese and European cohorts, respectively. In diffuse type GC (as defined by the pathologist), classifying patients using the DL diffuse and intestinal classifications provided a superior survival stratification, and demonstrated statistically significant survival stratification when combined with pathologist classification for both the Asian (overall survival log-rank test p-value < 0.005, HR 1.43 (95% CI 1.05-1.66, p-value = 0.03) and European cohorts (overall survival log-rank test p-value < 0.005, HR 1.56 (95% CI 1.16-1.76, p-value < 0.005)). CONCLUSION: Our study shows that gastric adenocarcinoma subtyping using pathologist's Laurén classification as ground truth can be performed using current state of the art DL techniques. Patient survival stratification seems to be better by DL-based histology typing compared with expert pathologist histology typing. DL-based GC histology typing has potential as an aid in subtyping. Further investigations are warranted to fully understand the underlying biological mechanisms for the improved survival stratification despite apparent imperfect classification by the DL algorithm.

Clinical relevance of PD-1 positive CD8 T-cells in gastric cancer.

BACKGROUND: We evaluated the relevance of PD-1+CD8+ T-cells in gastric cancer (GC) including prognostic significance, association with chemotherapy and immunotherapy sensitivity and correlations with the tumor microenvironment (TME). METHODS: Discovery cohort: GC samples were evaluated for AE1/3, CD8, PD-1, Ki-67 and Granzyme-B expression with fluorescence-based multiplex immunohistochemistry (mIHC). Validation cohorts: we analyzed bulk RNAseq GC datasets from TCGA, the "3G" chemotherapy trial and an immunotherapy phase 2 trial. The cox proportional hazards model was used to identify factors that influenced overall survival (OS). To study the TME, we analyzed single-cell RNAseq performed on GCs. RESULTS: In the discovery cohort of 350 GCs, increased PD-1 expression of CD8 T-cells was prognostic for OS (HR 0.822, p = 0.042). PD-1 expression in CD8 T-cells highly correlated with cytolytic [Granzyme-B+] (r = 0.714, p < 0.001) and proliferative [Ki-67+] (r = 0.798, p < 0.001) activity. Analysis of bulk RNAseq datasets showed tumors with high PD-1 and CD8A expression levels had improved OS when treated with immunotherapy (HR 0.117, p = 0.036) and chemotherapy (HR 0.475, p = 0.017). Analysis of an scRNAseq dataset of 152,423 cells from 40 GCs revealed that T-cell and NK-cell proportions were higher (24% vs 18% and 19% vs 15%, p < 0.0001), while macrophage proportions were lower (7% vs 11%, p < 0.0001) in CD8PD-1high compared to CD8PD-1low tumors. CONCLUSION: This is one of the largest GC cohorts of mIHC combined with analysis of multiple datasets providing orthogonal validation of the clinical relevance of PD-1+CD8+ T-cells being associated with improved OS. CD8PD-1high tumors have distinct features of an immunologically active, T-cell inflamed TME.

Colorectal Surgery in Patients with Liver Cirrhosis: A Systematic Review.

BACKGROUND: Colorectal surgery in patients with liver cirrhosis poses a significant challenge due to the associated peri-operative morbidity and mortality risks. The aim of this systematic review was to evaluate the outcomes in this cohort of patients following colorectal surgery. METHODS: The PubMed, Embase and Cochrane databases and references were searched up to October 2022 using the PRISMA guidelines. The data collated included: patient demographics, pathology or type of colorectal operation performed, severity of liver cirrhosis, post-operative complication rates, mortality rates and prognostic factors. A quality assessment of included studies was performed with the Newcastle-Ottawa scale. RESULTS: Sixteen studies reporting the outcomes of colorectal surgery in patients with liver cirrhosis were identified, including the results of 8646 patients. The indications, pathologies and/or type of operations varied. The overall complication rate ranged from 29 to 75%, minor complication ranged 14.5-37% and major complication ranged 6.7-59.3%. The mortality rates ranged from 0 to 37%. CONCLUSION: Colorectal surgery in patients with liver cirrhosis still carries considerable morbidity and mortality rates. This group of patients needs to be managed in a multidisciplinary setting to achieve excellent outcomes. Future research should focus on uniform definitions to enable interpretable outcomes.

A tumor-associated splice-isoform of MAP2K7 drives dedifferentiation in MBNL1-low cancers via JNK activation.

Master splicing regulator MBNL1 shapes large transcriptomic changes that drive cellular differentiation during development. Here we demonstrate that MBNL1 is a suppressor of tumor dedifferentiation. We surveyed MBNL1 expression in matched tumor/normal pairs across The Cancer Genome Atlas and found that MBNL1 was down-regulated in several common cancers. Down-regulation of MBNL1 predicted poor overall survival in breast, lung, and stomach adenocarcinomas and increased relapse and distant metastasis in triple-negative breast cancer. Down-regulation of MBNL1 led to increased tumorigenic and stem/progenitor-like properties in vitro and in vivo. A discrete set of alternative splicing events (ASEs) are shared between MBNL1-low cancers and embryonic stem cells including a MAP2K7∆exon2 splice variant that leads to increased stem/progenitor-like properties via JNK activation. Accordingly, JNK inhibition is capable of reversing MAP2K7∆exon2-driven tumor dedifferentiation in MBNL1-low cancer cells. Our work elucidates an alternative-splicing mechanism that drives tumor dedifferentiation and identifies biomarkers that predict enhanced susceptibility to JNK inhibition.

Machine-learning model derived gene signature predictive of paclitaxel survival benefit in gastric cancer: results from the randomised phase III SAMIT trial.

OBJECTIVE: To date, there are no predictive biomarkers to guide selection of patients with gastric cancer (GC) who benefit from paclitaxel. Stomach cancer Adjuvant Multi-Institutional group Trial (SAMIT) was a 2×2 factorial randomised phase III study in which patients with GC were randomised to Pac-S-1 (paclitaxel +S-1), Pac-UFT (paclitaxel +UFT), S-1 alone or UFT alone after curative surgery. DESIGN: The primary objective of this study was to identify a gene signature that predicts survival benefit from paclitaxel chemotherapy in GC patients. SAMIT GC samples were profiled using a customised 476 gene NanoString panel. A random forest machine-learning model was applied on the NanoString profiles to develop a gene signature. An independent cohort of metastatic patients with GC treated with paclitaxel and ramucirumab (Pac-Ram) served as an external validation cohort. RESULTS: From the SAMIT trial 499 samples were analysed in this study. From the Pac-S-1 training cohort, the random forest model generated a 19-gene signature assigning patients to two groups: Pac-Sensitive and Pac-Resistant. In the Pac-UFT validation cohort, Pac-Sensitive patients exhibited a significant improvement in disease free survival (DFS): 3-year DFS 66% vs 40% (HR 0.44, p=0.0029). There was no survival difference between Pac-Sensitive and Pac-Resistant in the UFT or S-1 alone arms, test of interaction p<0.001. In the external Pac-Ram validation cohort, the signature predicted benefit for Pac-Sensitive (median PFS 147 days vs 112 days, HR 0.48, p=0.022). CONCLUSION: Using machine-learning techniques on one of the largest GC trials (SAMIT), we identify a gene signature representing the first predictive biomarker for paclitaxel benefit. TRIAL REGISTRATION NUMBER: UMIN Clinical Trials Registry: C000000082 (SAMIT); ClinicalTrials.gov identifier, 02628951 (South Korean trial).

STAT3-mediated upregulation of the AIM2 DNA sensor links innate immunity with cell migration to promote epithelial tumourigenesis.

OBJECTIVE: The absent in melanoma 2 (AIM2) cytosolic pattern recognition receptor and DNA sensor promotes the pathogenesis of autoimmune and chronic inflammatory diseases via caspase-1-containing inflammasome complexes. However, the role of AIM2 in cancer is ill-defined. DESIGN: The expression of AIM2 and its clinical significance was assessed in human gastric cancer (GC) patient cohorts. Genetic or therapeutic manipulation of AIM2 expression and activity was performed in the genetically engineered gp130 F/F spontaneous GC mouse model, as well as human GC cell line xenografts. The biological role and mechanism of action of AIM2 in gastric tumourigenesis, including its involvement in inflammasome activity and functional interaction with microtubule-associated end-binding protein 1 (EB1), was determined in vitro and in vivo. RESULTS: AIM2 expression is upregulated by interleukin-11 cytokine-mediated activation of the oncogenic latent transcription factor STAT3 in the tumour epithelium of GC mouse models and patients with GC. Genetic and therapeutic targeting of AIM2 in gp130 F/F mice suppressed tumourigenesis. Conversely, AIM2 overexpression augmented the tumour load of human GC cell line xenografts. The protumourigenic function of AIM2 was independent of inflammasome activity and inflammation. Rather, in vivo and in vitro AIM2 physically interacted with EB1 to promote epithelial cell migration and tumourigenesis. Furthermore, upregulated expression of AIM2 and EB1 in the tumour epithelium of patients with GC was independently associated with poor patient survival. CONCLUSION: AIM2 can play a driver role in epithelial carcinogenesis by linking cytokine-STAT3 signalling, innate immunity and epithelial cell migration, independent of inflammasome activation.

Epigenetic promoter alterations in GI tumour immune-editing and resistance to immune checkpoint inhibition.

OBJECTIVES: Epigenomic alterations in cancer interact with the immune microenvironment to dictate tumour evolution and therapeutic response. We aimed to study the regulation of the tumour immune microenvironment through epigenetic alternate promoter use in gastric cancer and to expand our findings to other gastrointestinal tumours. DESIGN: Alternate promoter burden (APB) was quantified using a novel bioinformatic algorithm (proActiv) to infer promoter activity from short-read RNA sequencing and samples categorised into APBhigh, APBint and APBlow. Single-cell RNA sequencing was performed to analyse the intratumour immune microenvironment. A humanised mouse cancer in vivo model was used to explore dynamic temporal interactions between tumour kinetics, alternate promoter usage and the human immune system. Multiple cohorts of gastrointestinal tumours treated with immunotherapy were assessed for correlation between APB and treatment outcomes. RESULTS: APBhigh gastric cancer tumours expressed decreased levels of T-cell cytolytic activity and exhibited signatures of immune depletion. Single-cell RNAsequencing analysis confirmed distinct immunological populations and lower T-cell proportions in APBhigh tumours. Functional in vivo studies using 'humanised mice' harbouring an active human immune system revealed distinct temporal relationships between APB and tumour growth, with APBhigh tumours having almost no human T-cell infiltration. Analysis of immunotherapy-treated patients with GI cancer confirmed resistance of APBhigh tumours to immune checkpoint inhibition. APBhigh gastric cancer exhibited significantly poorer progression-free survival compared with APBlow (median 55 days vs 121 days, HR 0.40, 95% CI 0.18 to 0.93, p=0.032). CONCLUSION: These findings demonstrate an association between alternate promoter use and the tumour microenvironment, leading to immune evasion and immunotherapy resistance.

An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia.

Targeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using whole-genome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRC-driven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine+PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP.

A genomic-augmented multivariate prognostic model for the survival of natural-killer/T-cell lymphoma patients from an international cohort.

With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural-killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next-generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk-features in International Prognostic Index (IPI), Prognostic Index for Natural-Killer cell lymphoma (PINK), and PINK-Epstein-Barr virus (PINK-E). Cox-proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression-free survival (PFS, HR: 3.73, 95% CI 2.07-6.73; p < .001) and overall survival (OS, HR: 5.23, 95% CI 2.57-10.65; p = .001) with known risk-features of these indices. When we assign an additional risk-score to samples, which are mutant for the GPM, the Harrell's C-indices of GPM-augmented IPI, PINK, and PINK-E improved significantly (p < .001, χ2 test) for both PFS and OS. Thus, we report on how genomic mutational information could steer toward better prognostication of NKTCL patients.