Identification of neoantigens and immunological subtypes in clear cell renal cell carcinoma for mRNA vaccine development and patient selection

Clear cell renal cell carcinoma (ccRCC) is a common urological malignancy with diverse histological types. This study aimed to detect neoantigens in ccRCC to develop mRNA vaccines and distinguish between ccRCC immunological subtypes for construction of an immune landscape to select patients suitable for vaccination. Using The Cancer Genome Atlas SpliceSeq database, The Cancer Genome Atlas, and the International Cancer Genome Consortium cohorts, we comprehensively analysed potential tumour antigens of ccRCC associated with aberrant alternative splicing, somatic mutation, nonsense-mediated mRNA decay factors, antigen-presenting cells, and overall survival. Immune subtypes (C1/C2) and nine immune gene modules of ccRCC were identified by consistency clustering and weighted correlation network analysis. The immune landscape as well as molecular and cellular characteristics of immunotypes were assessed. Rho-guanine nucleotide exchange factor 3 (ARHGEF3) was identified as a new ccRCC antigen for development of an mRNA vaccine. A higher tumour mutation burden, differential expression of immune checkpoints, and immunogenic cell death were observed in cases with the C2 immunotype. Cellular characteristics increased the complexity of the immune environment, and worse outcomes were observed in ccRCC cases with the C2 immunotype. We constructed the immune landscape for selecting patients with the C2 immunotype suitable for vaccination.

[1]  Wei Tang,et al.  ARHGEF3 Associated with Invasion, Metastasis, and Proliferation in Human Osteosarcoma , 2021, BioMed research international.

[2]  Akiyasu C. Yoshizawa,et al.  Aberrant splicing isoforms detected by full-length transcriptome sequencing as transcripts of potential neoantigens in non-small cell lung cancer , 2021, Genome Biology.

[3]  Sihua Peng,et al.  Prognostic value of immune scores in the microenvironment of colorectal cancer , 2020, Oncology letters.

[4]  Zongtai Li,et al.  Depiction of tumor stemlike features and underlying relationships with hazard immune infiltrations based on large prostate cancer cohorts , 2020, Briefings Bioinform..

[5]  Ashton C. Berger,et al.  Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma , 2020, Nature Medicine.

[6]  Wei-wei Wang,et al.  Prognostic values of immune scores and immune microenvironment-related genes for hepatocellular carcinoma , 2020, Aging.

[7]  A. Rowan,et al.  Escape from nonsense-mediated decay associates with anti-tumor immunogenicity , 2019, Nature Communications.

[8]  W. Linehan,et al.  The Cancer Genome Atlas of renal cell carcinoma: findings and clinical implications , 2019, Nature Reviews Urology.

[9]  C. Brennan,et al.  Tumor mutational load predicts survival after immunotherapy across multiple cancer types , 2019, Nature Genetics.

[10]  T A Chan,et al.  Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.

[11]  J. Hoheisel,et al.  Function, clinical application, and strategies of Pre-mRNA splicing in cancer , 2018, Cell Death & Differentiation.

[12]  Xia Li,et al.  TIP: A Web Server for Resolving Tumor Immunophenotype Profiling. , 2018, Cancer research.

[13]  D. Weissman,et al.  mRNA vaccines — a new era in vaccinology , 2018, Nature Reviews Drug Discovery.

[14]  Samuel F. Bakhoum,et al.  Chromosomal instability drives metastasis through a cytosolic DNA response , 2017, Nature.

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

[16]  J. Joo,et al.  The prognostic value of BAP1, PBRM1, pS6, PTEN, TGase2, PD-L1, CA9, PSMA, and Ki-67 tissue markers in localized renal cell carcinoma: A retrospective study of tissue microarrays using immunohistochemistry , 2017, PloS one.

[17]  Jin Zhang,et al.  AHNAK2 is a Novel Prognostic Marker and Oncogenic Protein for Clear Cell Renal Cell Carcinoma , 2017, Theranostics.

[18]  M. Frey,et al.  Homologous recombination deficiency (HRD) testing in ovarian cancer clinical practice: a review of the literature , 2017, Gynecologic Oncology Research and Practice.

[19]  Steven K. Albanese,et al.  Mechanistically distinct cancer-associated mTOR activation clusters predict sensitivity to rapamycin. , 2016, The Journal of clinical investigation.

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

[21]  Ö. Türeci,et al.  Targeting the Heterogeneity of Cancer with Individualized Neoepitope Vaccines , 2016, Clinical Cancer Research.

[22]  Y. Zeng,et al.  The putative tumor activator ARHGEF3 promotes nasopharyngeal carcinoma cell pathogenesis by inhibiting cellular apoptosis , 2016, Oncotarget.

[23]  G. Hoyne,et al.  The Role of Alternative Splicing in the Control of Immune Homeostasis and Cellular Differentiation , 2015, International journal of molecular sciences.

[24]  J. Hsieh,et al.  A river model to map convergent cancer evolution and guide therapy in RCC , 2015, Nature Reviews Urology.

[25]  A. Ravaud,et al.  Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. , 2015, The New England journal of medicine.

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

[27]  J. Reeves,et al.  Pazopanib versus sunitinib in metastatic renal-cell carcinoma. , 2013, The New England journal of medicine.

[28]  Han Liu,et al.  Clinical and pathologic impact of select chromatin-modulating tumor suppressors in clear cell renal cell carcinoma. , 2013, European urology.

[29]  F. Montorsi,et al.  A review of integrated staging systems for renal cell carcinoma. , 2012, European urology.

[30]  N. Grishin,et al.  BAP1 loss defines a new class of renal cell carcinoma , 2012, Nature Genetics.

[31]  Guangchuang Yu,et al.  clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.

[32]  T. Spector,et al.  Identification of a role for the ARHGEF3 gene in postmenopausal osteoporosis. , 2008, American journal of human genetics.

[33]  Z. Szallasi,et al.  A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers , 2006, Nature Genetics.

[34]  Roy Parker,et al.  Nonsense-mediated mRNA decay: terminating erroneous gene expression. , 2004, Current opinion in cell biology.

[35]  R. Gray.  Modeling Survival Data: Extending the Cox Model , 2002 .

[36]  S. Berget.  Exon Recognition in Vertebrate Splicing (*) , 1995, The Journal of Biological Chemistry.

[37]  J. Brooks,et al.  Mutations of the VHL tumour suppressor gene in renal carcinoma , 1994, Nature Genetics.

[38]  I. Endo,et al.  Immune cytolytic activity is associated with reduced intra-tumoral genetic heterogeneity and with better clinical outcomes in triple negative breast cancer. , 2021, American journal of cancer research.

[39]  A. Dreher.  Modeling Survival Data Extending The Cox Model , 2016 .

[40]  Steven A. Roberts,et al.  Mutational heterogeneity in cancer and the search for new cancer-associated genes , 2013 .

[41]  L. Schwartz,et al.  NCCN clinical practice guidelines in oncology: kidney cancer. , 2009, Journal of the National Comprehensive Cancer Network : JNCCN.

[42]  M. Karno,et al.  Renal cell carcinoma. , 1956, Bulletin. Tufts-New England Medical Center.