Lactate inhibits ATP6V0d2 expression in tumor-associated macrophages to promote HIF-2α–mediated tumor progression

Liu, Na; Luo, Jing; Kuang, Dong; Xu, Sanpeng; Duan, Yaqi; Xia, Yu; Wei, Zhengping; Xie, Xiuxiu; Yin, Bingjiao; Chen, Fang; Luo, Shunqun; Liu, Huicheng; Wang, Jing; Jiang, Kan; Gong, Feili; Tang, Zhaohui; Cheng, Xiang; Li, Hua-Bin; Li, Zhuoya; Laurence, Arian; Wang, Guoping; Xiang, Yang

doi:10.1172/jci123027

Cited by 165 publications

(127 citation statements)

References 39 publications

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“…But the specific correlation of ATP6V0D2 dysregulation and tumor acidity remains uncertain. Downregulated ATP6V0D2 probably functions through increasing HIF-2α expression produced by macrophage to enhance tumor vascularization and growth [49]. Previous studies showed that an elevated expression of ATP6V0D2 was found in stomach cancer specimens, whereas the expression was reduced in the colorectal and renal cancer specimens, which confirmed our findings [50,51].…”

Section: Discussionsupporting

confidence: 91%

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

et al. 2020

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Background: Clear cell renal cell carcinoma (ccRCC) comprises the majority of kidney cancer death worldwide, whose incidence and mortality are not promising. Identifying ideal biomarkers to construct a more accurate prognostic model than conventional clinical parameters is crucial.Methods: Raw count of RNA-sequencing data and clinicopathological data were acquired from The Cancer Genome Atlas (TCGA). Tumor samples were divided into two sets. Differentially expressed genes (DEGs) were screened in the whole set and prognosis-related genes were identified from the training set. Their common genes were used in LASSO and best subset regression which were performed to identify the best prognostic 5 genes. The gene-based risk score was developed based on the Cox coefficient of the individual gene. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess its prognostic power. GSE29609 dataset from GEO (Gene Expression Omnibus) database was used to validate the signature. Univariate and multivariate Cox regression were performed to screen independent prognostic parameters to construct a nomogram. The predictive power of the nomogram was revealed by time-dependent ROC curves and the calibration plot and verified in the validation set. Finally, Functional enrichment analysis of DEGs and 5 novel genes were performed to suggest the potential biological pathways.Results: PADI1, ATP6V0D2, DPP6, C9orf135 and PLG were screened to be significantly related to the prognosis of ccRCC patients. The risk score effectively stratified the patients into high-risk group with poor overall survival (OS) based on survival analysis. AJCC-stage, age, recurrence and risk score were regarded as independent prognostic parameters by Cox regression analysis and were used to construct a nomogram. Time-dependent ROC curves showed the nomogram performed best in 1-, 3-and 5-year survival predictions compared with AJCC-stage and risk score in validation sets. The calibration plot showed good agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis suggested several enriched biological pathways related to cancer. Conclusions:In our study, we constructed a gene-based model integrating clinical prognostic parameters to predict prognosis of ccRCC well, which might provide a reliable prognosis assessment tool for clinician and aid treatment decision-making in the clinic. © The Author(s) 2020. This 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'

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Section: Discussionsupporting

confidence: 91%

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

et al. 2020

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“…Macrophages, a key representative of myeloid lineages possess two polarized types of the classically activated (M1) macrophage phenotype and the alternatively activated (M2) macrophage phenotype ( Biswas and Mantovani, 2010 ). MCT1/4-mediated lactate secretion from cancer cells plays an important role in mediating macrophage polarization to the M2-like state, which presents with immunosuppressive properties ( Colegio et al, 2014 ; Ohashi et al, 2017 ; Mu et al, 2018 ; Liu et al, 2019 ; Stone et al, 2019 ). In gastric cancer, the lactate-MCT-hypoxic inducible factor-1α (HIF-1α) axis has been identified as a crucial signaling axis that connects metabolic rewiring and immune evasion.…”

Section: How Mct1 and Mct4 Link Cancer Cells And The Tumor Microenvirmentioning

confidence: 99%

Role of Proton-Coupled Monocarboxylate Transporters in Cancer: From Metabolic Crosstalk to Therapeutic Potential

Sun

Wang

et al. 2020

Front. Cell Dev. Biol.

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Proton-coupled monocarboxylate transporters (MCTs), representing the first four isoforms of the SLC16A gene family, mainly participate in the transport of lactate, pyruvate, and other monocarboxylates. Cancer cells exhibit a metabolic shift from oxidative metabolism to an enhanced glycolytic phenotype, leading to a higher production of lactate in the cytoplasm. Excessive accumulation of lactate threatens the survival of cancer cells, and the overexpression of proton-coupled MCTs observed in multiple types of cancer facilitates enhanced export of lactate from highly glycolytic cancer cells. Proton-coupled MCTs not only play critical roles in the metabolic symbiosis between hypoxic and normoxic cancer cells within tumors but also mediate metabolic interaction between cancer cells and cancer-associated stromal cells. Of the four proton-coupled MCTs, MCT1 and MCT4 are the predominantly expressed isoforms in cancer and have been identified as potential therapeutic targets in cancer. Therefore, in this review, we primarily focus on the roles of MCT1 and MCT4 in the metabolic reprogramming of cancer cells under hypoxic and nutrient-deprived conditions. Additionally, we discuss how MCT1 and MCT4 serve as metabolic links between cancer cells and cancer-associated stromal cells via transport of crucial monocarboxylates, as well as present emerging opportunities and challenges in targeting MCT1 and MCT4 for cancer treatment.

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“…Likely, HIF-2α/ARNT heterodimer, known as HIF-2, is sensible to oxygen availability in tumors, and is also tightly controlled by proteasomal degradation via prolyl hydroxylases (PHDs) in both normoxic and hypoxic conditions [ 21 ]. Moreover, HIF-2α promotes tumor progression via macrophage lactate /HIF-2α/ATP6v0d2 axis [ 22 ], and some lncRNAs may be its transcriptional targets within solid tumors [ 21 ]. Role of HIF-3α has not yet been fully understood, which has long been thought negatively associated with HIF-1α and HIF-2α expression and function to directly or indirectly regulate hypoxia-induced pathological processes [ 23 – 25 ].…”

Section: Introductionmentioning

confidence: 99%

Epigenetic crosstalk between hypoxia and tumor driven by HIF regulation

Mao

Wang

et al. 2020

J Exp Clin Cancer Res

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Hypoxia is the major influence factor in physiological and pathological courses which are mainly mediated by hypoxia-inducible factors (HIFs) in response to low oxygen tensions within solid tumors. Under normoxia, HIF signaling pathway is inhibited due to HIF-α subunits degradation. However, in hypoxic conditions, HIF-α is activated and stabilized, and HIF target genes are successively activated, resulting in a series of tumour-specific activities. The activation of HIFs, including HIF-1α, HIF-2α and HIF-3α, subsequently induce downstream target genes which leads to series of responses, the resulting abnormal processes or metabolites in turn affect HIFs stability. Given its functions in tumors progression, HIFs have been regarded as therapeutic targets for improved treatment efficacy. Epigenetics refers to alterations in gene expression that are stable between cell divisions, and sometimes between generations, but do not involve changes in the underlying DNA sequence of the organism. And with the development of research, epigenetic regulation has been found to play an important role in the development of tumors, which providing accumulating basic or clinical evidences for tumor treatments. Here, given how little has been reported about the overall association between hypoxic tumors and epigenetics, we made a more systematic review from epigenetic perspective in hope of helping others better understand hypoxia or HIF pathway, and providing more established and potential therapeutic strategies in tumors to facilitate epigenetic studies of tumors.

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Lactate inhibits ATP6V0d2 expression in tumor-associated macrophages to promote HIF-2α–mediated tumor progression

Cited by 165 publications

References 39 publications

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

Construction of a novel gene-based model for prognosis prediction of clear cell renal cell carcinoma

Role of Proton-Coupled Monocarboxylate Transporters in Cancer: From Metabolic Crosstalk to Therapeutic Potential

Epigenetic crosstalk between hypoxia and tumor driven by HIF regulation

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