Noncoding RNAs link metabolic reprogramming to immune microenvironment in cancers

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Abstract

Altered metabolic patterns in tumor cells not only meet their own growth requirements but also shape an immunosuppressive microenvironment through multiple mechanisms. Noncoding RNAs constitute approximately 60% of the transcriptional output of human cells and have been shown to regulate numerous cellular processes under developmental and pathological conditions. Given their extensive action mechanisms based on motif recognition patterns, noncoding RNAs may serve as hinges bridging metabolic activity and immune responses. Indeed, recent studies have shown that microRNAs, long noncoding RNAs and circRNAs are widely involved in tumor metabolic rewiring, immune cell infiltration and function. Hence, we summarized existing knowledge of the role of noncoding RNAs in the remodeling of tumor metabolism and the immune microenvironment, and notably, we established the TIMELnc manual, which is a free and public manual for researchers to identify pivotal lncRNAs that are simultaneously correlated with tumor metabolism and immune cell infiltration based on a bioinformatic approach.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-021-01179-y.

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Most cited references 325

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Understanding the Warburg effect: the metabolic requirements of cell proliferation.

Craig B Thompson, Matthew Vander Heiden, Lewis Cantley (2009)

In contrast to normal differentiated cells, which rely primarily on mitochondrial oxidative phosphorylation to generate the energy needed for cellular processes, most cancer cells instead rely on aerobic glycolysis, a phenomenon termed "the Warburg effect." Aerobic glycolysis is an inefficient way to generate adenosine 5'-triphosphate (ATP), however, and the advantage it confers to cancer cells has been unclear. Here we propose that the metabolism of cancer cells, and indeed all proliferating cells, is adapted to facilitate the uptake and incorporation of nutrients into the biomass (e.g., nucleotides, amino acids, and lipids) needed to produce a new cell. Supporting this idea are recent studies showing that (i) several signaling pathways implicated in cell proliferation also regulate metabolic pathways that incorporate nutrients into biomass; and that (ii) certain cancer-associated mutations enable cancer cells to acquire and metabolize nutrients in a manner conducive to proliferation rather than efficient ATP production. A better understanding of the mechanistic links between cellular metabolism and growth control may ultimately lead to better treatments for human cancer.

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starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data

Jun-Hao Li, Shun Liu, Hui Zhou … (2013)

Although microRNAs (miRNAs), other non-coding RNAs (ncRNAs) (e.g. lncRNAs, pseudogenes and circRNAs) and competing endogenous RNAs (ceRNAs) have been implicated in cell-fate determination and in various human diseases, surprisingly little is known about the regulatory interaction networks among the multiple classes of RNAs. In this study, we developed starBase v2.0 (http://starbase.sysu.edu.cn/) to systematically identify the RNA–RNA and protein–RNA interaction networks from 108 CLIP-Seq (PAR-CLIP, HITS-CLIP, iCLIP, CLASH) data sets generated by 37 independent studies. By analyzing millions of RNA-binding protein binding sites, we identified ∼9000 miRNA-circRNA, 16 000 miRNA-pseudogene and 285 000 protein–RNA regulatory relationships. Moreover, starBase v2.0 has been updated to provide the most comprehensive CLIP-Seq experimentally supported miRNA-mRNA and miRNA-lncRNA interaction networks to date. We identified ∼10 000 ceRNA pairs from CLIP-supported miRNA target sites. By combining 13 functional genomic annotations, we developed miRFunction and ceRNAFunction web servers to predict the function of miRNAs and other ncRNAs from the miRNA-mediated regulatory networks. Finally, we developed interactive web implementations to provide visualization, analysis and downloading of the aforementioned large-scale data sets. This study will greatly expand our understanding of ncRNA functions and their coordinated regulatory networks.

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The Emerging Hallmarks of Cancer Metabolism.

Natalya Pavlova, Craig B Thompson (2016)

Tumorigenesis is dependent on the reprogramming of cellular metabolism as both direct and indirect consequence of oncogenic mutations. A common feature of cancer cell metabolism is the ability to acquire necessary nutrients from a frequently nutrient-poor environment and utilize these nutrients to both maintain viability and build new biomass. The alterations in intracellular and extracellular metabolites that can accompany cancer-associated metabolic reprogramming have profound effects on gene expression, cellular differentiation, and the tumor microenvironment. In this Perspective, we have organized known cancer-associated metabolic changes into six hallmarks: (1) deregulated uptake of glucose and amino acids, (2) use of opportunistic modes of nutrient acquisition, (3) use of glycolysis/TCA cycle intermediates for biosynthesis and NADPH production, (4) increased demand for nitrogen, (5) alterations in metabolite-driven gene regulation, and (6) metabolic interactions with the microenvironment. While few tumors display all six hallmarks, most display several. The specific hallmarks exhibited by an individual tumor may ultimately contribute to better tumor classification and aid in directing treatment.

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Author and article information

Contributors

Xiaoxiao Fan: fanxx_gs@zju.edu.cn

Yuelong Liang: yuelongliang@zju.edu.cn

Hui Lin: 369369@zju.edu.cn

Journal

Journal ID (nlm-ta): J Hematol Oncol

Journal ID (iso-abbrev): J Hematol Oncol

Title: Journal of Hematology & Oncology

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-8722

Publication date (Electronic): 15 October 2021

Publication date PMC-release: 15 October 2021

Publication date Collection: 2021

Volume: 14

Electronic Location Identifier: 169

Affiliations

[1 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, , Zhejiang University, ; Hangzhou, 310016 China

[2 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, State Key Laboratory of Modern Optical Instrumentations, Centre for Optical and Electromagnetic Research, College of Optical Science and Engineering, International Research Center for Advanced Photonics, , Zhejiang University, ; Hangzhou, 310058 China

[3 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Zhejiang Engineering Research Center of Cognitive Healthcare, Sir Run Run Shaw Hospital, School of Medicine, , Zhejiang University, ; Hangzhou, 310016 China

Article

Publisher ID: 1179

DOI: 10.1186/s13045-021-01179-y

PMC ID: 8518176

PubMed ID: 34654454

SO-VID: 1441f49b-7540-4da0-b6e7-6eac395340f7

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 4 July 2021

Date accepted : 27 September 2021

Funding

Funded by: zhejiang province key research and development project

Award ID: 2020C01059

Award Recipient : Hui Lin

Funded by: national key research and development project

Award ID: 2017YFC0110802

Award Recipient : Hui Lin

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, national natural science foundation of china;

Award ID: 81872297

Award ID: 81874059

Award Recipient : Hui Lin

Funded by: zhejiang engineering research center of cognitive healthcare

Award ID: 2017E10011

Award Recipient : Hui Lin

Funded by: national key scientific instrument and equipment development project

Award ID: 81827804

Award Recipient : Hui Lin

Custom metadata

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: noncoding rnas,tumor metabolism,immune microenvironment,timelnc manual,bioinformatic approach

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ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: noncoding rnas, tumor metabolism, immune microenvironment, timelnc manual, bioinformatic approach

Noncoding RNAs link metabolic reprogramming to immune microenvironment in cancers

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Karger: Oncology

Most cited references 325

Understanding the Warburg effect: the metabolic requirements of cell proliferation.

starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data

The Emerging Hallmarks of Cancer Metabolism.

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