Prognostic value of neutrophil extracellular trap signature in clear cell renal cell carcinoma

Introduction Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of urological carcinoma. Although targeted therapy and immunotherapy are usually employed, they often result in primary and acquired resistance. There is currently a lack of dependable biomarkers that can accurately anticipate the prognosis of ccRCC. Recent research has indicated the critical role of neutrophil extracellular traps (NETs) in the development, metastasis, and immune evasion of cancer. The aim of this study was to explore the value of NETs in the development and prognosis of ccRCC. Methods Clinical features and genetic expression information of ccRCC patients were acquired from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and E-MTAB-1980 database. NETs-related gene set were obtained from previous studies. A NETs-related gene signature was constructed based on TCGA data and validated using ICGC and E-MTAB-1980 databases. Furthermore, the immune microenvironment and responsiveness to anticancer medications in ccRCC patients with varying levels of NETs risks were investigated. Results A total of 31 NET-related genes were differently expressed between normal kidney and ccRCC tissues. 17 out of 31 were significantly associated with overall survival. After LASSO Cox regression analysis, nine NETs-related genes were enrolled to construct the NETs prognosis signature, and all the ccRCC patients from TCGA were divided into low and high risk group. This signature demonstrated excellent performance in predicting the overall survival of TCGA patients as well as the validation ICGC and E-MTAB-1980 patients. Additionally, the NETs signature was significantly correlated with immune infiltration and drug sensitivity. Conclusions The NETs signature established by the current study has prognostic significance in ccRCC, and may serve as a useful biomarker for patient stratification and treatment decisions. Further validation and clinical studies are required to fully translate these findings into clinical practice.

[1]  A. Roointan,et al.  Clear Cell Renal Cell Carcinoma: A Comprehensive in silico Study in Searching for Therapeutic Targets , 2023, Kidney and Blood Pressure Research.

[2]  G. Fricker,et al.  The Role of Solute Carrier Transporters in Efficient Anticancer Drug Delivery and Therapy , 2023, Pharmaceutics.

[3]  Yan-ping Zhang,et al.  Neutrophil extracellular traps-associated modification patterns depict the tumor microenvironment, precision immunotherapy, and prognosis of clear cell renal cell carcinoma , 2022, Frontiers in Oncology.

[4]  Jing Quan,et al.  Identification and validation of the molecular subtype and prognostic signature for clear cell renal cell carcinoma based on neutrophil extracellular traps , 2022, Frontiers in Cell and Developmental Biology.

[5]  Yi Wang,et al.  The role of neutrophil extracellular traps in cancer progression, metastasis and therapy , 2022, Experimental Hematology & Oncology.

[6]  P. Tran,et al.  Diagnostic and Prognostic Biomarkers in Renal Clear Cell Carcinoma , 2022, Biomedicines.

[7]  Qilin Li,et al.  A novel neutrophil extracellular trap signature to predict prognosis and immunotherapy response in head and neck squamous cell carcinoma , 2022, Frontiers in Immunology.

[8]  Yi Zhang,et al.  A signature for pan-cancer prognosis based on neutrophil extracellular traps , 2022, Journal for ImmunoTherapy of Cancer.

[9]  J. Spicer,et al.  Neutrophil Extracellular Traps in Cancer Therapy Resistance , 2022, Cancers.

[10]  W. Tong,et al.  Pan-Cancer Analysis Identified CD93 as a Valuable Biomarker for Predicting Patient Prognosis and Immunotherapy Response , 2022, Frontiers in Molecular Biosciences.

[11]  N. Chen,et al.  A Neutrophil Extracellular Traps Signature Predicts the Clinical Outcomes and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma , 2022, Frontiers in Molecular Biosciences.

[12]  Michael R Hamblin,et al.  Comprehensive analysis of ceRNA networks to determine genes related to prognosis, overall survival, and immune infiltration in clear cell renal carcinoma , 2021, Comput. Biol. Medicine.

[13]  Panos K. Chrysanthis,et al.  Signatures , 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..

[14]  C. Efrimescu,et al.  Neutrophil Extracellular Trapping Role in Cancer, Metastases, and Cancer-Related Thrombosis: a Narrative Review of the Current Evidence Base , 2021, Current Oncology Reports.

[15]  Robert F. Gruener,et al.  oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data , 2021, Briefings Bioinform..

[16]  Umama Khan,et al.  Neutrophil Extracellular Traps in Colorectal Cancer Progression and Metastasis , 2021, International journal of molecular sciences.

[17]  Zhenfeng Zhang,et al.  Tumor-derived lactate inhibit the efficacy of lenvatinib through regulating PD-L1 expression on neutrophil in hepatocellular carcinoma , 2021, Journal for ImmunoTherapy of Cancer.

[18]  N. Vogelzang,et al.  Biomarkers in renal cell carcinoma: Are we there yet? , 2021, Asian journal of urology.

[19]  S. Baker,et al.  DNA Methylation‐Based Epigenetic Repression of SLC22A4 Promotes Resistance to Cytarabine in Acute Myeloid Leukemia , 2020, Clinical and translational science.

[20]  M. Carleton,et al.  CXCR1 and CXCR2 Chemokine Receptor Agonists Produced by Tumors Induce Neutrophil Extracellular Traps that Interfere with Immune Cytotoxicity. , 2020, Immunity.

[21]  E. Głodkowska-Mrówka,et al.  Nitric oxide and peroxynitrite trigger and enhance release of neutrophil extracellular traps , 2019, Cellular and Molecular Life Sciences.

[22]  J. Mier.  The tumor microenvironment in renal cell cancer , 2019, Current opinion in oncology.

[23]  Dongjun Lee,et al.  VNN3 is a potential novel biomarker for predicting prognosis in clear cell renal cell carcinoma , 2019, Animal cells and systems.

[24]  Zesong Li,et al.  Loss of KCNJ15 expression promotes malignant phenotypes and correlates with poor prognosis in renal carcinoma , 2019, Cancer management and research.

[25]  A. Tsung,et al.  Neutrophil extracellular traps promote inflammation and development of hepatocellular carcinoma in nonalcoholic steatohepatitis , 2018, Hepatology.

[26]  Jianlin Chen,et al.  Formyl peptide receptor 2 expression predicts poor prognosis and promotes invasion and metastasis in epithelial ovarian cancer , 2017, Oncology reports.

[27]  V. Papayannopoulos.  Neutrophil extracellular traps in immunity and disease , 2017, Nature Reviews Immunology.

[28]  Dai Bo,et al.  Identification and validation of soluble carrier family expression signature for predicting poor outcome of renal cell carcinoma , 2017, Journal of Cancer.

[29]  M. Fafutis-Morris,et al.  Neutrophil Extracellular Traps and Its Implications in Inflammation: An Overview , 2017, Front. Immunol..

[30]  Ludmila V. Danilova,et al.  Erratum to: Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures , 2016, Genome Biology.

[31]  E. V. Van Allen,et al.  Tumor immune microenvironment characterization in clear cell renal cell carcinoma identifies prognostic and immunotherapeutically relevant messenger RNA signatures , 2016, Genome Biology.

[32]  N. Vorobjeva,et al.  Neutrophil extracellular traps and their role in the development of chronic inflammation and autoimmunity. , 2015, Autoimmunity reviews.

[33]  C. Mathers,et al.  Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012 , 2015, International journal of cancer.

[34]  A. Jemal,et al.  Global cancer statistics, 2012 , 2015, CA: a cancer journal for clinicians.

[35]  W. Linehan,et al.  Decade in review—kidney cancer: Discoveries, therapies and opportunities , 2014, Nature Reviews Urology.

[36]  Z. Trajanoski,et al.  Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. , 2013, Immunity.

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

[38]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[39]  Paul Kubes,et al.  Neutrophil extracellular traps sequester circulating tumor cells and promote metastasis. , 2013, The Journal of clinical investigation.

[40]  H. Aburatani,et al.  Integrated molecular analysis of clear-cell renal cell carcinoma , 2013, Nature Genetics.

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

[42]  Hong-tao Lu,et al.  Expression of tissue levels of matrix metalloproteinases and tissue inhibitors of metalloproteinases in renal cell carcinoma , 2013, World Journal of Surgical Oncology.

[43]  Sridhar Ramaswamy,et al.  Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells , 2012, Nucleic Acids Res..

[44]  Xiao‐Yu Yin,et al.  Peritumoral neutrophils link inflammatory response to disease progression by fostering angiogenesis in hepatocellular carcinoma. , 2011, Journal of hepatology.

[45]  A. Fischer,et al.  Response: , 2010 .

[46]  Lorenzo Marconi,et al.  EAU guidelines on renal cell carcinoma: 2014 update. , 2010, European urology.

[47]  J. Weinstein,et al.  Profiling SLCO and SLC22 genes in the NCI-60 cancer cell lines to identify drug uptake transporters , 2008, Molecular Cancer Therapeutics.

[48]  S. Cho,et al.  Increased expression of matrix metalloproteinase 9 correlates with poor prognostic variables in renal cell carcinoma. , 2003, European urology.

[49]  P. Grambsch,et al.  Modeling Survival Data: Extending the Cox Model , 2000 .

[50]  A. Jemal,et al.  Global cancer statistics , 2011, CA: a cancer journal for clinicians.