Dataset Information

Non-genetic stratification reveals epigenetic heterogeneity and identifies vulnerabilities of glycolysis addiction in lung adenocarcinoma subtype.

ABSTRACT: Lung adenocarcinoma (LUAD) exhibits high heterogeneity and is well known for its high genetic variation. Recently, the understanding of non-genetic variation provides a new perspective to study the heterogeneity of LUAD. Little is known about whether super-enhancers (SEs) may be primarily responsible for the inter-tumor heterogeneity of LUAD. We used super-enhancer RNA (seRNA) levels of a large-scale clinical well-annotated LUAD cohort to stratify patients into three clusters with different prognosis and other malignant characteristics. Mechanistically, estrogen-related receptor alpha (ERRα) in cluster 3-like cell lines acts as a cofactor of BRD4 to assist SE-promoter loops to activate glycolysis-related target gene expression, thereby promoting glycolysis and malignant progression, which confers a therapeutic vulnerability to glycolytic inhibitors. Our study identified three groups of patients according to seRNA levels, among which patients in cluster 3 have the worst prognosis and vulnerability of glycolysis dependency. We also proposed a 3-TF index model to stratify patients with glycolysis-addicted tumors according to tumor SE stratification.

SUBMITTER: Song X

PROVIDER: S-EPMC9550819 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Non-genetic stratification reveals epigenetic heterogeneity and identifies vulnerabilities of glycolysis addiction in lung adenocarcinoma subtype.

Song Xuming X Zhang Te T Ding Hanlin H Feng Yipeng Y Yang Wenmin W Yin Xuewen X Chen Bing B Liang Yingkuan Y Mao Qixing Q Xia Wenjie W Yu Guiping G Xu Lin L Dong Gaochao G Jiang Feng F

Oncogenesis 20221010 1

Lung adenocarcinoma (LUAD) exhibits high heterogeneity and is well known for its high genetic variation. Recently, the understanding of non-genetic variation provides a new perspective to study the heterogeneity of LUAD. Little is known about whether super-enhancers (SEs) may be primarily responsible for the inter-tumor heterogeneity of LUAD. We used super-enhancer RNA (seRNA) levels of a large-scale clinical well-annotated LUAD cohort to stratify patients into three clusters with different prog ...[more]

PMID: 36216804

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Project description:BackgroundWith fatal malignant peculiarities and poor survival rate, outcomes of pancreatic adenocarcinoma (PAAD) were frustrated by non-response and even resistance to therapy due to heterogeneity across clinical patients. Nevertheless, pharmacogenomics has been developed for individualized-treatment and still maintains obscure in PAAD.MethodsA total of 964 samples from 10 independent multi-center cohorts were enrolled in our study. With drug response data from the profiling of relative inhibition simultaneously in mixtures (PRISM) and genomics of drug sensitivity in cancer (GDSC) databases, we established and validated multidimensionally three pharmacogenomics-classified subtypes using non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms, separately. The heterogenous biological characteristics and precision medicine strategies among subtypes were further investigated.ResultsThree pharmacogenomics-classified subtypes after stable and reproducible validation, distinguished in six aspects of prognosis, biological peculiarities, immune landscapes, genomic variations, immunotherapy and individualized management strategies. Subtype 2 was close to immunocompetent phenotype and projected to immunotherapy; Subtype 3 held most favorable outcomes and metabolic pathways distinctively, promising to be treated with first-line agents. Subtype 1 with worst prognosis, was anticipated to chromosome instability (CIN) phenotype and resistant to chemotherapeutic agents. In addition, ITGB6 contributed to subtype 1 resistance to 5-fluorouracil, and knockdown of ITGB6 enhanced sensitivity to 5-fluorouracil in in vitro experiments. Ultimately, appropriate clinical stratified treatments were assigned to corresponding subtypes according to pharmacogenomic transcripts. Some limitations were not taken into account, thus needs to be supported by more research.ConclusionA span-new molecular subtype exploited for PAAD uncovered an insight into precise medication on ground of pharmacogenomics, and highly refined multiple clinical management strategies for specific patients.

Dataset Information

Non-genetic stratification reveals epigenetic heterogeneity and identifies vulnerabilities of glycolysis addiction in lung adenocarcinoma subtype.

Publications

Non-genetic stratification reveals epigenetic heterogeneity and identifies vulnerabilities of glycolysis addiction in lung adenocarcinoma subtype.

Similar Datasets

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