Epigenome-Wide Association Study Using Prediagnostic Bloods Identifies New Genomic Regions Associated With Pancreatic Cancer Risk

Sex-Related Differences in Pancreatic Ductal Adenocarcinoma Progression and Response to Therapy

Pancreatic ductal adenocarcinoma (PDAC) is one of the most deadly malignancies with an increasing incidence rate and limited therapeutic options. Biological sex has an impact on many aspects of PDAC development and response to therapy, yet it is highly unappreciated in both basic and translational research, and worryingly in PDAC clinical trials. In this review, we summarize how biological sex influences PDAC incidence and mortality, genetic and epigenetic landscapes, anti-tumor immunity, responses to hormones, cachexia, and the efficacy of therapy. We highlight the importance of sex as a variable and discuss how to implement it into preclinical and clinical research. These considerations should be of use to researchers aiming at improving understanding of PDAC biology and developing precision medicine therapeutic strategies.

Identification of novel susceptibility methylation loci for pancreatic cancer in a two-phase epigenome-wide association study

The role of DNA methylation and its interplay with gene expression in the susceptibility to pancreatic cancer (PanC) remains largely unexplored. To fill in this gap, we conducted an integrative two-phase epigenome-wide association study (EWAS) of PanC using genomic DNA from 44 cases and 556 controls (20 local controls and 536 public controls in the Framingham Heart Study) in phase 1 and 23 cases and 22 controls in phase 2. We validated the findings using pre-diagnostic blood samples from 13 cases and 26 controls in the Women's Health Initiative (WHI) Study. We further examined gene expression in peripheral leukocytes of 47 cases and 31 controls involved in the methylation study using RNA sequencing and performed bidirectional Mendelian randomization (MR) analysis using existing single nucleotide polymorphism (SNP) data. In phase 1, we identified 2776 significantly differentially methylated CpG sites (DMPs) and 154 significantly differentially methylated regions (DMRs). In phase 2, we validated six DMPs (in or near AIM2, DGKA, STK39, and TNFSF8) and three DMRs (in or near nc886, LY6G5C, and HLA-DPB1). The DMR near nc886 was further validated in the WHI samples (P = 6.69 × 10-5). MR analysis suggested that the CpG sites cg00308130 and cg16684184 for nc886 and cg16875057 for STK39 were causally related to PanC susceptibility and that PanC influenced methylation of cg15354065 for DGKA. This first integrative EWAS of PanC provides novel insights into the role of DNA methylation and its interplay with SNPs and gene expression in the disease susceptibility.

Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans

Ethnic differences in non-communicable disease risk have been described between individuals of South Asian and European ethnicity that are only partially explained by genetics and other known risk factors. DNA methylation is one underexplored mechanism that may explain differences in disease risk. Currently, there is little knowledge of how DNA methylation varies between South Asian and European ethnicities. This study characterised differences in blood DNA methylation between individuals of self-reported European and South Asian ethnicity from two UK-based cohorts: Southall and Brent Revisited and Born in Bradford. DNA methylation differences between ethnicities were widespread throughout the genome (n = 16,433 CpG sites, 3.4% sites tested). Specifically, 76% of associations were attributable to ethnic differences in cell composition with fewer effects attributable to smoking and genetic variation. Ethnicity-associated CpG sites were enriched for EWAS Catalog phenotypes including metabolites. This work highlights the need to consider ethnic diversity in epigenetic research.

Expression and prognostic potential of TMEM204: a pan-cancer analysis

TMEM204 (Transmembrane Protein 204) is a member of the TMEM family that regulates cell function and angiogenesis. Previous studies showed that TMEM204 is related to pancreatic cancer, but its roles in other cancers remain unknown. To reveal this relationship, we conducted a pan-cancer analysis by several online databases. The expression of TMEM204 was analyzed by Oncomine and Tumor Immune Estimation Resource2.0 (TIMER2.0). The prognostic potential of TMEM204 was evaluated by the GEPIA2, UALCAN, and Oncolnc. The methylation level of gene expression was analyzed by UALCAN, and the relationship between cancer and immune invasion was displayed by TIMER2.0. The Protein-Protein Interactions Network and functional analysis of TMEM204 and its related genes were conducted by STRING and Webgestalt. We found that TMEM204 expression was up-regulated and correlated with prognosis in multiple cancers. In liver hepatocellular carcinoma (LIHC), high TMEM204 expression was associated with a good prognosis, and with high infiltrating levels of CD8⁺ T and CD4⁺ T cells, macrophages, neutrophils, and myeloid dendritic cells. In addition, the methylation level in LIHC was higher than in normal tissues. p53 signaling pathway and Fanconi anemia pathway were implicated by KEGG pathway analysis. These results indicate that TMEM204 is associated with the prognosis, methylation, and immune invasion of cancers, especially LIHC. TMEM204 may act as a prognostic marker of LIHC and its role in other cancers should be studied.

DNA methylation-based predictors of health: applications and statistical considerations

DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.

ER-phagy: mechanisms, regulation and diseases connected to the lysosomal clearance of the endoplasmic reticulum

ER-phagy (reticulo-phagy) defines the degradation of portions of the endoplasmic reticulum (ER) within lysosomes or vacuoles. It is part of the self-digestion (i.e., auto-phagic) programs recycling cytoplasmic material and organelles, which rapidly mobilize metabolites in cells confronted with nutrient shortage. Moreover, selective clearance of ER subdomains participates to the control of ER size and activity during ER stress, the re-establishment of ER homeostasis after ER stress resolution and the removal of ER parts, in which aberrant and potentially cytotoxic material has been segregated. ER-phagy relies on the individual and/or concerted activation of the ER-phagy receptors, ER peripheral or integral membrane proteins that share the presence of LC3/Atg8-binding motifs in their cytosolic domains. ER-phagy involves the physical separation of portions of the ER from the bulk ER network, and their delivery to the endolysosomal/vacuolar catabolic district. This last step is accomplished by a variety of mechanisms including macro-ER-phagy (in which ER fragments are sequestered by double-membrane autophagosomes that eventually fuse with lysosomes/vacuoles), micro-ER-phagy (in which ER fragments are directly engulfed by endosomes/lysosomes/vacuoles), or direct fusion of ER-derived vesicles with lysosomes/vacuoles. ER-phagy is dysfunctional in specific human diseases and its regulators are subverted by pathogens, highlighting its crucial role for cell and organism life.

Integration of Tumor Heterogeneity for Recurrence Prediction in Patients with Esophageal Squamous Cell Cancer

Simple Summary

This manuscript reports a deep sequencing study comprehensively analyzing the clinical impact of mutations considering the abundance of mutations. We built an eight-gene mutation predictor considering intratumoral heterogeneity to predict post-surgery recurrence in ESCC patients. Unlike previous studies that simply treated mutations as binary variables (mutant and wild type), we quantified mutations by the fraction of cancer cells carrying the mutations, and our results showed that the cancer cell fraction of mutations was more informative than the mutation status of genes in recurrence prediction. The predictor was further validated as a powerful recurrence indicator in our validation set and the TCGA-ESCC cohort. With the popularization of targeted deep sequencing in clinical work, our study will help clinicians make accurate predictions of recurrence for patients and will provide a new perspective in the clinical transformation of genomic findings.

Abstract

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest malignancies in China. The prognostic value of mutations, especially those in minor tumor clones, has not been systematically investigated. We conducted targeted deep sequencing to analyze the mutation status and the cancer cell fraction (CCF) of mutations in 201 ESCC patients. Our analysis showed that the prognostic effect of mutations was relevant to the CCF, and it should be considered in prognosis prediction. EP300 was a promising biomarker for overall survival, impairing prognosis in a CCF dose-dependent manner. We constructed a CCF-based predictor using a smooth clipped absolute deviation Cox model in the training set of 143 patients. The 3-year disease-free survival rates were 6.3% (95% CI: 1.6–23.9%), 29.8% (20.9–42.6%) and 70.5% (56.6–87.7%) in high-, intermediate- and low-risk patients, respectively, in the training set. The prognostic accuracy was verified in a validation set of 58 patients and the TCGA-ESCC cohort. The eight-gene model predicted prognosis independent of clinicopathological factors and the combination of our model and pathological staging markedly improved the prognostic accuracy of pathological staging alone. Our study describes a novel recurrence predictor for ESCC patients and provides a new perspective for the clinical translation of genomic findings.

The Crosstalk Between Long Non-Coding RNAs and Various Types of Death in Cancer Cells

With the increasing aging population, cancer has become one of the leading causes of death worldwide, and the number of cancer cases and deaths is only anticipated to grow further. Long non-coding RNAs (lncRNAs), which are closely associated with the expression level of downstream genes and various types of bioactivity, are regarded as one of the key regulators of cancer cell proliferation and death. Cell death, including apoptosis, necrosis, autophagy, pyroptosis, and ferroptosis, plays a vital role in the progression of cancer. A better understanding of the regulatory relationships between lncRNAs and these various types of cancer cell death is therefore urgently required. The occurrence and development of tumors can be controlled by increasing or decreasing the expression of lncRNAs, a method which confers broad prospects for cancer treatment. Therefore, it is urgent for us to understand the influence of lncRNAs on the development of different modes of tumor death, and to evaluate whether lncRNAs have the potential to be used as biological targets for inducing cell death and predicting prognosis and recurrence of chemotherapy. The purpose of this review is to provide an overview of the various forms of cancer cell death, including apoptosis, necrosis, autophagy, pyroptosis, and ferroptosis, and to describe the mechanisms of different types of cancer cell death that are regulated by lncRNAs in order to explore potential targets for cancer therapy.