Integrative analysis revealed that distinct cuprotosis patterns reshaped tumor microenvironment and responses to immunotherapy of colorectal cancer

Cuprotosis is a novel form of programmed cell death that involves direct targeting of key enzymes in the tricarboxylic acid (TCA) cycle by excess copper and may result in mitochondrial metabolic dysfunction. However, whether cuprotosis may mediate the tumor microenvironment (TME) and immune regulation in colorectal cancer (CRC) remains unclear.Ten cuprotosis-related genes were selected and unsupervised consensus clustering was performed to identify the cuprotosis patterns and the correlated TME characteristics. Using principal component analysis, a COPsig score was established to quantify cuprotosis patterns in individual patients. The top 9 most important cuprotosis signature genes were analyzed using single-cell transcriptome data.Three distinct cuprotosis patterns were identified. The TME cell infiltration characteristics of three patterns were associated with immune-excluded, immune-desert, and immune-inflamed phenotype, respectively. Based on individual cuprotosis patterns, patients were assigned into high and low COPsig score groups. Patients with a higher COPsig score were characterized by longer overall survival time, lower immune cell as well as stromal infiltration, and greater tumor mutational burden. Moreover, further analysis demonstrated that CRC patients with a higher COPsig score were more likely to respond to immune checkpoint inhibitors and 5-fluorouracil chemotherapy. Single-cell transcriptome analysis indicated that cuprotosis signature genes recruited tumor-associated macrophages to TME through the regulation of TCA and the metabolism of glutamine and fatty acid, thus influencing the prognosis of CRC patients.This study indicated that distinct cuprotosis patterns laid a solid foundation to the explanation of heterogeneity and complexity of individual TME, thus guiding more effective immunotherapy as well as adjuvant chemotherapy strategies.

[1]  Liying Song,et al.  Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer , 2022, Frontiers in Pharmacology.

[2]  T. Golub,et al.  Copper induces cell death by targeting lipoylated TCA cycle proteins , 2022, Science.

[3]  Xiaojie Xie,et al.  CXCR4-dependent macrophage-to-fibroblast signaling contributes to cardiac diastolic dysfunction in heart failure with preserved ejection fraction , 2022, International journal of biological sciences.

[4]  M. Kriegsmann,et al.  Simultaneous targeting of TGF-β/PD-L1 synergizes with radiotherapy by reprogramming the tumor microenvironment to overcome immune evasion. , 2021, Cancer cell.

[5]  G. Long,et al.  Immune checkpoint inhibitors in melanoma , 2021, The Lancet.

[6]  Qianhui Xu,et al.  Landscape of Immune Microenvironment Under Immune Cell Infiltration Pattern in Breast Cancer , 2021, Frontiers in Immunology.

[7]  G. Mayhew,et al.  Fibroblast growth factor receptor 3 alterations and response to immune checkpoint inhibition in metastatic urothelial cancer: a real world experience , 2021, British Journal of Cancer.

[8]  J. Joyce,et al.  Therapeutic Targeting of the Tumor Microenvironment. , 2021, Cancer discovery.

[9]  Jianxun Song,et al.  Metabolic Reprogramming and Reactive Oxygen Species in T Cell Immunity , 2021, Frontiers in Immunology.

[10]  A. Jemal,et al.  Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries , 2021, CA: a cancer journal for clinicians.

[11]  C. Kundu,et al.  5-Fluorouracil (5-FU) resistance and the new strategy to enhance the sensitivity against cancer: Implication of DNA repair inhibition. , 2021, Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie.

[12]  Yan Li,et al.  Prognosis and personalized treatment prediction in TP53-mutant hepatocellular carcinoma: an in silico strategy towards precision oncology , 2020, Briefings Bioinform..

[13]  P. Gibbs,et al.  Pembrolizumab in Microsatellite-Instability-High Advanced Colorectal Cancer. , 2020, The New England journal of medicine.

[14]  A. Zorzano,et al.  Macrophage mitochondrial MFN2 (mitofusin 2) links immune stress and immune response through reactive oxygen species (ROS) production , 2020, Autophagy.

[15]  D. Ettinger,et al.  Multisystem Immune-Related Adverse Events Associated With Immune Checkpoint Inhibitors for Treatment of Non-Small Cell Lung Cancer. , 2020, JAMA oncology.

[16]  H. Nader,et al.  Effects of syndecan-4 gene silencing by micro RNA interference in anoikis resistant endothelial cells: Syndecan-4 silencing and anoikis resistance. , 2020, The international journal of biochemistry & cell biology.

[17]  Young-Joon Kim,et al.  Genome-wide identification of differentially methylated promoters and enhancers associated with response to anti-PD-1 therapy in non-small cell lung cancer , 2020, Experimental & Molecular Medicine.

[18]  Jasjit K. Banwait,et al.  Andrographis-mediated chemosensitization through activation of ferroptosis and suppression of β-catenin/Wnt-signaling pathways in colorectal cancer. , 2020, Carcinogenesis.

[19]  F. Ginhoux,et al.  The Extended Polydimensional Immunome Characterization (EPIC) web-based reference and discovery tool for cytometry data , 2020, Nature Biotechnology.

[20]  M. Mittelbrunn,et al.  Glycolysis – a key player in the inflammatory response , 2020, The FEBS journal.

[21]  M. Zheng,et al.  METTL14 suppresses proliferation and metastasis of colorectal cancer by down-regulating oncogenic long non-coding RNA XIST , 2020, Molecular Cancer.

[22]  Y. Saeys,et al.  NicheNet: modeling intercellular communication by linking ligands to target genes , 2019, Nature Methods.

[23]  T. Buchler,et al.  5-fluorouracil and other fluoropyrimidines in colorectal cancer: Past, present and future. , 2019, Pharmacology & therapeutics.

[24]  Kongming Wu,et al.  Blocking TGF-β Signaling To Enhance The Efficacy Of Immune Checkpoint Inhibitor , 2019, OncoTargets and therapy.

[25]  De-Hua Wu,et al.  Combination of TMB and CNA Stratifies Prognostic and Predictive Responses to Immunotherapy Across Metastatic Cancer , 2019, Clinical Cancer Research.

[26]  H. Nader,et al.  Heparan sulfate proteoglycans as trastuzumab targets in anoikis‐resistant endothelial cells , 2019, Journal of cellular biochemistry.

[27]  Qiang Wu,et al.  Association of LRP1B Mutation With Tumor Mutation Burden and Outcomes in Melanoma and Non-small Cell Lung Cancer Patients Treated With Immune Check-Point Blockades , 2019, Front. Immunol..

[28]  F. Song,et al.  The new identified biomarkers determine sensitivity to immune check-point blockade therapies in melanoma , 2019, Oncoimmunology.

[29]  J. Galon,et al.  Approaches to treat immune hot, altered and cold tumours with combination immunotherapies , 2019, Nature Reviews Drug Discovery.

[30]  A. Butte,et al.  Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage , 2018, Nature Immunology.

[31]  Jacob D. Jaffe,et al.  Next-generation characterization of the Cancer Cell Line Encyclopedia , 2019, Nature.

[32]  C. Borner,et al.  Copper-induced cell death and the protective role of glutathione: the implication of impaired protein folding rather than oxidative stress. , 2018, Metallomics : integrated biometal science.

[33]  Yassen Assenov,et al.  Maftools: efficient and comprehensive analysis of somatic variants in cancer , 2018, Genome research.

[34]  E. Alici,et al.  The Role of CXC Chemokine Receptors 1–4 on Immune Cells in the Tumor Microenvironment , 2018, Front. Immunol..

[35]  S. Ricard-Blum,et al.  Proteoglycan Chemical Diversity Drives Multifunctional Cell Regulation and Therapeutics. , 2018, Chemical reviews.

[36]  T. Ma,et al.  miR‑21‑5p targets PDHA1 to regulate glycolysis and cancer progression in gastric cancer. , 2018, Oncology reports.

[37]  X. Liu,et al.  Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response , 2018, Nature Medicine.

[38]  Gang Yang,et al.  Tumor microenvironment participates in metastasis of pancreatic cancer , 2018, Molecular Cancer.

[39]  Shangha Pan,et al.  PGC1α promotes cholangiocarcinoma metastasis by upregulating PDHA1 and MPC1 expression to reverse the Warburg effect , 2018, Cell Death & Disease.

[40]  R. Weinberg,et al.  Understanding the tumor immune microenvironment (TIME) for effective therapy , 2018, Nature Medicine.

[41]  Ye Xu,et al.  A robust gene signature for the prediction of early relapse in stage I–III colon cancer , 2018, Molecular oncology.

[42]  Camille Stephan-Otto Attolini,et al.  TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis , 2018, Nature.

[43]  R. Bourgon,et al.  TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells , 2018, Nature.

[44]  A. Wree,et al.  NLRP3 inflammasome driven liver injury and fibrosis: Roles of IL‐17 and TNF in mice , 2018, Hepatology.

[45]  E. Yates,et al.  Coupling of vinculin to F-actin demands Syndecan-4 proteoglycan. , 2017, Matrix biology : journal of the International Society for Matrix Biology.

[46]  Ludmila V. Danilova,et al.  Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade , 2017, Science.

[47]  Laurence Zitvogel,et al.  The immune contexture in cancer prognosis and treatment , 2017, Nature Reviews Clinical Oncology.

[48]  Tithi Ghosh,et al.  Tumor promoting role of anti-tumor macrophages in tumor microenvironment. , 2017, Cellular immunology.

[49]  Yumin Xia,et al.  TWEAK/Fn14 signaling in tumors , 2017, Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine.

[50]  Matthew L. Albert,et al.  Dying cells actively regulate adaptive immune responses , 2017, Nature Reviews Immunology.

[51]  A. Butte,et al.  xCell: digitally portraying the tissue cellular heterogeneity landscape , 2017, bioRxiv.

[52]  I. Mellman,et al.  Elements of cancer immunity and the cancer–immune set point , 2017, Nature.

[53]  Pornpimol Charoentong,et al.  Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade , 2016, bioRxiv.

[54]  Carlos Caldas,et al.  Patterns of Immune Infiltration in Breast Cancer and Their Clinical Implications: A Gene-Expression-Based Retrospective Study , 2016, PLoS medicine.

[55]  P. Laurent-Puig,et al.  Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression , 2016, Genome Biology.

[56]  J. Rathmell,et al.  A guide to immunometabolism for immunologists , 2016, Nature Reviews Immunology.

[57]  A. Chiu,et al.  Role of Mitochondrial DNA Copy Number Alteration in Human Renal Cell Carcinoma † , 2016, International journal of molecular sciences.

[58]  N. Gogtay,et al.  Biostatistics Series Module 3: Comparing Groups: Numerical Variables , 2016, Indian journal of dermatology.

[59]  J. Taube,et al.  Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy , 2016, Nature Reviews Cancer.

[60]  L. Zitvogel,et al.  Targeting the tumor microenvironment: removing obstruction to anticancer immune responses and immunotherapy. , 2016, Annals of oncology : official journal of the European Society for Medical Oncology.

[61]  J. Sosman,et al.  Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma , 2016, Cell.

[62]  Gianluca Bontempi,et al.  TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data , 2015, Nucleic acids research.

[63]  Joshua A. Bittker,et al.  Correlating chemical sensitivity and basal gene expression reveals mechanism of action , 2015, Nature chemical biology.

[64]  J. Nesland,et al.  Decreased expression of pyruvate dehydrogenase A1 predicts an unfavorable prognosis in ovarian carcinoma. , 2016, American journal of cancer research.

[65]  S. Turley,et al.  Immunological hallmarks of stromal cells in the tumour microenvironment , 2015, Nature Reviews Immunology.

[66]  N. Savaskan,et al.  Glioblastoma cells induce differential glutamatergic gene expressions in human tumor-associated microglia/macrophages and monocyte-derived macrophages , 2015, Cancer biology & therapy.

[67]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[68]  N. Itano,et al.  Tumor-Associated Macrophages as Major Players in the Tumor Microenvironment , 2014, Cancers.

[69]  G. Cline,et al.  Functional polarization of tumour-associated macrophages by tumour-derived lactic acid , 2014, Nature.

[70]  E. Tartour,et al.  Control of the Immune Response by Pro-Angiogenic Factors , 2014, Front. Oncol..

[71]  J. V. Van Ginderachter,et al.  Mechanisms Driving Macrophage Diversity and Specialization in Distinct Tumor Microenvironments and Parallelisms with Other Tissues , 2014, Front. Immunol..

[72]  D. Quail,et al.  Microenvironmental regulation of tumor progression and metastasis , 2014 .

[73]  G. Getz,et al.  Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.

[74]  T. Crocenzi,et al.  Circulating and intratumoral macrophages in patients with hepatocellular carcinoma: correlation with therapeutic approach. , 2013, American journal of surgery.

[75]  C. Gialeli,et al.  Expression of matrix macromolecules and functional properties of EGF-responsive colon cancer cells are inhibited by panitumumab , 2013, Investigational New Drugs.

[76]  Justin Guinney,et al.  GSVA: gene set variation analysis for microarray and RNA-Seq data , 2013, BMC Bioinformatics.

[77]  R. Labianca,et al.  ESMO Consensus Guidelines for management of patients with colon and rectal cancer. a personalized approach to clinical decision making. , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.

[78]  Douglas Hanahan,et al.  Accessories to the Crime: Functions of Cells Recruited to the Tumor Microenvironment Prospects and Obstacles for Therapeutic Targeting of Function-enabling Stromal Cell Types , 2022 .

[79]  Witold R. Rudnicki,et al.  Feature Selection with the Boruta Package , 2010 .

[80]  Matthew D. Wilkerson,et al.  ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking , 2010, Bioinform..

[81]  V. Georgoulias,et al.  Safety and efficacy of first-line bevacizumab with FOLFOX, XELOX, FOLFIRI and fluoropyrimidines in metastatic colorectal cancer: the BEAT study. , 2009, Annals of oncology : official journal of the European Society for Medical Oncology.

[82]  B. Vértessy,et al.  Keeping uracil out of DNA: physiological role, structure and catalytic mechanism of dUTPases. , 2009, Accounts of chemical research.

[83]  M. J. van de Vijver,et al.  Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. , 2006, Journal of the National Cancer Institute.

[84]  D. Sargent,et al.  Survival of patients with advanced colorectal cancer improves with the availability of fluorouracil-leucovorin, irinotecan, and oxaliplatin in the course of treatment. , 2004, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.