FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3147702576> ?p ?o ?g. }

• W3147702576 endingPage "102368" @default.
• W3147702576 startingPage "102368" @default.
• W3147702576 abstract "•ViralMine parses oncoviral genotypes and co-infection from in situ tumor data•Oncoviral genotyping of TCGA CESC, HNSC, and LIHC cohorts•Tumor fitness, immunogenicity, and mutational signatures associate with oncoviral genotype The role of oncoviral genotype and co-infection driving oncogenesis remains unclear. We have developed a scalable, high throughput tool for sensitive and precise oncoviral genotype deconvolution. Using tumor RNA sequencing data, we applied it to 537 virally infected liver, cervical, and head and neck tumors, providing the first comprehensive integrative landscape of tumor-viral gene expression, viral antigen immunogenicity, patient survival, and mutational profiling organized by tumor oncoviral genotype. We find that HBV and HPV genotype and co-infection serve as significant predictors of patient survival and immune activation. Finally, we demonstrate that HPV genotype is more associated with viral oncogene expression than cancer type, implying that expression may be similar across episomal and stochastic integration-based infections. While oncoviral infections are known risk factors for oncogenesis, viral genotype and co-infection are shown to strongly associate with disease progression, patient survival, mutational signatures, and putative tumor neoantigen immunogenicity, facilitating novel clinical associations with infections. The role of oncoviral genotype and co-infection driving oncogenesis remains unclear. We have developed a scalable, high throughput tool for sensitive and precise oncoviral genotype deconvolution. Using tumor RNA sequencing data, we applied it to 537 virally infected liver, cervical, and head and neck tumors, providing the first comprehensive integrative landscape of tumor-viral gene expression, viral antigen immunogenicity, patient survival, and mutational profiling organized by tumor oncoviral genotype. We find that HBV and HPV genotype and co-infection serve as significant predictors of patient survival and immune activation. Finally, we demonstrate that HPV genotype is more associated with viral oncogene expression than cancer type, implying that expression may be similar across episomal and stochastic integration-based infections. While oncoviral infections are known risk factors for oncogenesis, viral genotype and co-infection are shown to strongly associate with disease progression, patient survival, mutational signatures, and putative tumor neoantigen immunogenicity, facilitating novel clinical associations with infections. Chronic infection with hepatitis B virus (HBV) and human papillomavirus (HPV) are well-known oncogenic risk factors, with strong viral genotype associations (Castellsagué, 2008Castellsagué X. Natural history and epidemiology of HPV infection and cervical cancer.Gynecol. Oncol. 2008; 110: S4-S7https://doi.org/10.1016/j.ygyno.2008.07.045Abstract Full Text Full Text PDF PubMed Scopus (319) Google Scholar; An et al., 2018An P. Xu J. Yu Y. Winkler C.A. Host and viral genetic variation in HBV-related hepatocellular carcinoma.Front. Genet. 2018; 9: 261Crossref PubMed Scopus (54) Google Scholar). Given that HBV-related hepatocellular carcinoma (HCC) and HPV-related head and neck and cervical cancer incidence is on the rise globally (Vaccarella et al., 2013Vaccarella S. Lortet-Tieulent J. Plummer M. Franceschi S. Bray F. Worldwide trends in cervical cancer incidence: impact of screening against changes in disease risk factors.Eur. J. Cancer. 2013; 49: 3262-3273https://doi.org/10.1016/j.ejca.2013.04.024Abstract Full Text Full Text PDF PubMed Scopus (277) Google Scholar; Simard et al., 2014Simard E.P. Torre L.A. Jemal A. International trends in head and neck cancer incidence rates: differences by country, sex and anatomic site.Oral Oncol. 2014; 50: 387-403Crossref PubMed Scopus (184) Google Scholar; Zhu et al., 2016Zhu R.X. Seto W.K. Lai C.L. Yuen M.F. Epidemiology of hepatocellular carcinoma in the asia-pacific region.Gut Liver. 2016; 10: 332-339Crossref PubMed Scopus (322) Google Scholar), scalably exploiting tumor RNA sequencing (RNA-seq) data to accurately infer detailed viral signatures is clinically urgent. Although averaged infection phenotypes such as viral load and predominant genotype have been previously characterized and shown to be strong prognostic factors in cancer development (Schiffman et al., 2007Schiffman M. Castle P.E. Jeronimo J. Rodriguez A.C. Wacholder S. Human papillomavirus and cervical cancer.Lancet. 2007; 370: 890-907https://doi.org/10.1016/s0140-6736(07)61416-0Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Schiffman et al., 2009Schiffman M. Clifford G. Buonaguro F.M. Classification of weakly carcinogenic human papillomavirus types: addressing the limits of epidemiology at the borderline.Infect. Agents Cancer. 2009; 4: 8Crossref PubMed Scopus (331) Google Scholar; Cuzick and Wheeler, 2016Cuzick J. Wheeler C. Need for Expanded HPV Genotyping for Cervical Screening. Papillomavirus research, 2016: 112-115Google Scholar; Pazgan-Simon et al., 2018Pazgan-Simon M. Simon K.A. Jarowicz E. Rotter K. Szymanek-Pasternak A. Zuwała-Jagiełło J. Hepatitis B virus treatment in hepatocellular carcinoma patients prolongs survival and reduces the risk of cancer recurrence.Clin. Exp. Hepatol. 2018; 4: 210-216Crossref PubMed Scopus (16) Google Scholar; Zapatka et al., 2020Zapatka M. Borozan I. Brewer D.S. Iskar M. Grundhoff A. Alawi M. Desai N. Sültmann H. Moch H. au fnm et al.The landscape of viral associations in human cancers.Nat. Genet. 2020; 52: 320-330Crossref PubMed Scopus (87) Google Scholar), the effects of more granular measures such as exon-level viral expression or the ratio of expressed viral genotypes (co-infection) have not yet been fully mapped out in the host tumor microenvironment. This leaves key facets of these DNA oncoviral infections unknown, creating a clinical blind spot for the development of potential new anti-oncoviral therapeutic options. Here we present a new in situ tool to comprehensively characterize DNA oncoviruses, which we applied to 1,230 tumor samples spanning across liver, cervical, and head and neck cancers. Although HBV and HPV infect highly disparate cancers via different mechanisms, their strong genotype-specific association with oncogenic risk, relatively unknown co-infection rates (Vermeulen et al., 2007Vermeulen C.F. Jordanova E.S. Szuhai K. Kolkman-Uljee S. Vrede M.A. Peters A.A. Schuuring E. Fleuren G.J. Physical status of multiple human papillomavirus genotypes in flow-sorted cervical cancer cells.Cancer Genet. Cytogenet. 2007; 175: 132-137Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar; Chaturvedi et al., 2011Chaturvedi A.K. Katki H.A. Hildesheim A. Rodríguez A.C. Quint W. Schiffman M. Van Doorn L.J. Porras C. Wacholder S. Gonzalez P. et al.Human papillomavirus infection with multiple types: pattern of coinfection and risk of cervical disease.J. Infect. Dis. 2011; 203: 910-920Crossref PubMed Scopus (188) Google Scholar; Senapati et al., 2017Senapati R. Nayak B. Kar S.K. Dwibedi B. HPV genotypes co-infections associated with cervical carcinoma: special focus on phylogenetically related and non-vaccine targeted genotypes.PLoS One. 2017; 12: e0187844Crossref PubMed Scopus (26) Google Scholar), and disease progression associations can be naturally combined in an integrative, viral genotype-centric, study leveraging tumor RNA-seq data. Indeed, our tool ViralMine, extracts and quantifies viral RNA from high-depth coverage tumor sequencing with high-fidelity sequence recovery, allowing for precise and accurate viral genotype deconvolution and viral exon-level expression analysis (Figure 1A) within the context of the tumor microenvironment. Previous studies have adopted similar negative selection strategies to extract viral sequences from tumor RNA profiling (Tang et al., 2013Tang K.W. Alaei-Mahabadi B. Samuelsson T. Lindh M. Larsson E. The landscape of viral expression and host gene fusion and adaptation in human cancer.Nat. Commun. 2013; 4: 2513https://doi.org/10.1038/ncomms3513Crossref PubMed Scopus (201) Google Scholar; Cao et al., 2016Cao S. Wendl M.C. Wyczalkowski M.A. Wylie K. Ye K. Jayasinghe R. Xie M. Wu S. Niu B. Grubb R. et al.Divergent viral presentation among human tumors and adjacent normal tissues.Sci. Rep. 2016; 6: 28294https://doi.org/10.1038/srep28294Crossref PubMed Scopus (41) Google Scholar; Cancer Genome Atlas Research Network et al., 2017aCancer Genome Atlas Research Network Integrated genomic and molecular characterization of cervical cancer.Nature. 2017; 543: 378-384Crossref PubMed Scopus (662) Google Scholar; Zapatka et al., 2020Zapatka M. Borozan I. Brewer D.S. Iskar M. Grundhoff A. Alawi M. Desai N. Sültmann H. Moch H. au fnm et al.The landscape of viral associations in human cancers.Nat. Genet. 2020; 52: 320-330Crossref PubMed Scopus (87) Google Scholar), whereas our data-driven method goes considerably further by facilitating scalable viral gene expression characterization and deconvolution of complex viral co-infection patterns. We found that viral genotype is associated with overall patient survival, cancer-specific expression signaling, and tumor immunogenicity in HCC. Similarly, viral genotype was linked to significant expression differences in host oncogenesis and immune response pathways in HPV related cervical cancer, and striated patient survival (see results). We found that HPV co-infection creates a notable increase in average putative neoantigen immunogenicity, indicating a potential emergent property of co-infection within cervical tumors. Finally, a comparison of HPV gene expression in head and neck cancers and cervical cancers revealed significant variation across viral tumor genotype but not cancer type. In order to validate the key genotyping capability of ViralMine (Figure 1A, see transparent methods), we obtained tumor RNA-seq data for the “core set” of cervical cancers from the The Cancer Genome Atlas (TCGA) with previous HPV infection information (n = 178, 169 HPV+) and a group of 50 Chinese patients with HCC screened for HBV infection to ethnicity-match the Asian dominated TCGA LIHC cohort (GSE65485, n = 50, 44 HBV+) (Figure 1B) (Dong et al., 2015Dong H. Zhang L. Qian Z. Zhu X. Zhu G. Chen Y. Xie X. Ye Q. Zang J. Ren Z. Ji Q. Identification of HBV-MLL4 integration and its molecular basis in Chinese hepatocellular carcinoma.PLoS One. 2015; 10: e0123175PubMed Google Scholar; Cancer Genome Atlas Research Network et al., 2017aCancer Genome Atlas Research Network Integrated genomic and molecular characterization of cervical cancer.Nature. 2017; 543: 378-384Crossref PubMed Scopus (662) Google Scholar), for a total of 213 virally infected samples. We inferred viral genotypes in both cohorts against the existing genotype information, obtaining perfect sensitivity in both datasets, and specificities of 0.97 and 0.95 in the HPV+ cervical cancers and HBV-associated HCC tumors, respectively (Figure S1). These results demonstrate that the overall performance of ViralMine in the cervical TCGA (CESC) core set cohort nearly perfectly matched consensus calls made using a combination of different assays, including MassArray, BioBloom Tools, and PathSeq RNA-Sequencing inference techniques (Cancer Genome Atlas Research Network et al., 2017aCancer Genome Atlas Research Network Integrated genomic and molecular characterization of cervical cancer.Nature. 2017; 543: 378-384Crossref PubMed Scopus (662) Google Scholar). We also observed robust average performance using read downsampling with patient randomization, indicating that even relatively low viral expression is sufficient for accurate genotyping with ViralMine (Figure S9), although we do note that immunotherapy treatments that stimulate viral clearance may have an adverse effect on viral sequence recovery (Figure S10). Applying ViralMine to large-scale tumor expression datasets, especially those with missing or incomplete viral information, we exhaustively screened liver cancer patients from the TCGA (LIHC, n = 334) for HBV infection and found 115 positive patients. This included 71 patients not previously reported HBV+ (Cancer Genome Atlas Research Network, 2017bCancer Genome Atlas Research NetworkComprehensive and integrative genomic characterization of hepatocellular carcinoma.Cell. 2017; 169: 1327-1341.e23Abstract Full Text Full Text PDF PubMed Scopus (918) Google Scholar) and 44 patients who were, with the majority (85/115, 74%) infected with HBV genotype C (Figures 2A and 2B ). We also screened a different dataset of 21 patients with HCC for combined HBV integration and genotyping analysis (Figures 1B and 2B; Table S5) (GSE94660, n = 21) and found 11 patients positive for HBV genotype C, 9 HBV for genotype B, and 1 patient HBV- (Yoo et al., 2017Yoo S. Wang W. Wang Q. Fiel M.I. Lee E. Hiotis S.P. Zhu J. A pilot systematic genomic comparison of recurrence risks of hepatitis B virus-associated hepatocellular carcinoma with low- and high-degree liver fibrosis.BMC Med. 2017; 15: 214Crossref PubMed Scopus (30) Google Scholar). Similarly, we analyzed HPV-infected tumors across the entire set of cervical cancers from the TCGA (CESC, n = 304), finding 285 HPV+ (93.7%), with HPV genotypes for the virally infected tumors indicated in Figure 1C. Among the cervical histological subtypes, neither HPV+ adenocarcinomas nor squamous cell carcinomas were found to be correlated with a specific viral genotype (Figure S2A). We also screened cancers from the head and neck TCGA cohort (HNSC, n = 521), finding 73 HPV+ (14%), of which the vast majority (81%) were HPV16, which restricted inter-tumoral genotype comparisons (Figures 2A and 2B). Co-infections, of HPV genotypes (see transparent methods for details; Figure S11) were found in 92 of the 285 HPV+ cervical cancers (32.5%) with 82 infected with two HPV genotypes (29%) and 10 with three HPV genotypes (3.5%), yielding higher co-infection rates compared with previous co-infection surveys, considering much smaller cohorts of cervical lesions (Figures 2B and S3A; Table S5) (Vermeulen et al., 2007Vermeulen C.F. Jordanova E.S. Szuhai K. Kolkman-Uljee S. Vrede M.A. Peters A.A. Schuuring E. Fleuren G.J. Physical status of multiple human papillomavirus genotypes in flow-sorted cervical cancer cells.Cancer Genet. Cytogenet. 2007; 175: 132-137Abstract Full Text Full Text PDF PubMed Scopus (12) Google Scholar; Senapati et al., 2017Senapati R. Nayak B. Kar S.K. Dwibedi B. HPV genotypes co-infections associated with cervical carcinoma: special focus on phylogenetically related and non-vaccine targeted genotypes.PLoS One. 2017; 12: e0187844Crossref PubMed Scopus (26) Google Scholar). As with primary HPV infection genotypes, these surprisingly high co-infection rates among CESC samples were not preferentially associated with either adenocarcinomas or squamous cell carcinoma subtypes (Figure S2B). In the TCGA head and neck HPV-associated tumors, 8 of 73 were co-infected (11%) with two HPV genotypes (Figures 2B and S3B). In HBV-related HCCs in the TCGA cohort, 14 tumors were co-infected with more than one HBV genotype (12%), of which 12 had two genotypes and 2 had three concurrent genotypes (Figures 2B and S3C). Although it is technically possible to conflate a recombinant virus with distinct viral genotypes only looking at RNA data, typical recovered viral contigs (average of 500–1,000 bp) were of a length to suggest that we are quantifying the latter. We also noted a lack of correlation between patient viral load and somatic tumor mutational burden (TMB), and between viral genotype and viral load, across cancer types (Figures 2A and S4), indicating viral genotype classification as an independent readout. However, we found no significant associations between viral genotype and several expression-based immune activity markers for either HPV or HBV, potentially signaling that viral genotype alone does not have a significant effect on tumor immune activity. In order to test the hypothesis that particular viral genotypes are associated with unique downstream onco-expression signaling, we performed gene set enrichment analysis (GSEA) of the differentially expressed genes between HBV genotype C- (n = 77) and HBV genotype B- (n = 18) associated HCCs of TCGA. We found HBV genotype C tumors were enriched in pathways involved in cell proliferation, tumor recurrence, and tumor growth, whereas cell survival pathways and liver-specific genes sets were downregulated compared with patients with HBV B tumors (false discovery rate (FDR) <0.0001) (Figure 3A; Table S1). Interestingly, for tumors with HBV co-infection (n = 14), genes in pathways involved in 3′ UTR translation, peptide chain elongation, and miRNA deregulation were significantly downregulated compared with tumors with a single HBV genotype (n = 100; FDR<0.0001) (Figure S5; Table S1), indicating that regulatory instability may increase with multi-genotypic HBV infections in the tumor. Integration analysis using only expressed transcripts among HBV+ genotype C and B HCC patient groups (n = 172) identified HBV C-preferred integration loci in known HCC driver genes CCNE1 and KMT2B (Huang et al., 2012Huang J. Deng Q. Wang Q. Li K.Y. Dai J.H. Li N. Zhu Z.D. Zhou B. Liu X.Y. Liu R.F. et al.Exome sequencing of hepatitis B virus–associated hepatocellular carcinoma.Nat. Genet. 2012; 44: 1117-1121https://doi.org/10.1038/ng.2391Crossref PubMed Scopus (294) Google Scholar; Cancer Genome Atlas Research Network, 2017bCancer Genome Atlas Research NetworkComprehensive and integrative genomic characterization of hepatocellular carcinoma.Cell. 2017; 169: 1327-1341.e23Abstract Full Text Full Text PDF PubMed Scopus (918) Google Scholar), whereas total average rate of integration among the two tumor groups (1.81 integrations per HBV C tumor, 1.85 per HBV B tumor) was similar (two-tailed t test, p = 0.9) (Figure S6). Finally, although the APOBEC3 pathway has been shown to activate in response to HBV infection in liver malignancies (Vartanian et al., 2010Vartanian J.P. Henry M. Marchio A. Suspène R. Aynaud M.M. Guétard D. Cervantes-Gonzalez M. Battiston C. Mazzaferro V. Pineau P. et al.Massive APOBEC3 editing of hepatitis B viral DNA in cirrhosis.PLoS Pathog. 2010; 6: e1000928Crossref PubMed Scopus (123) Google Scholar), we did not find any significant differential expression associated with HBV genotype within HBV+ tumors. Given the genotype-driven molecular differences found above, we sought to determine if the predictive impact of viral genotype in patient survival was significant. We constructed Cox proportional hazard models in HBV-related HCC from TCGA and, using bootstrap resampling to control overfitting, computed robust time-dependent Brier scores for models using clinical tumor stage, tumor vascular invasion, and tumor HBV genotype. Comparing the resulting survival models (Figure 3B), we found both tumor stage and HBV genotype significantly reduced prediction error against the naive reference model, whereas vascular invasion did not. Survival prediction was additionally improved using a model including both tumor stage and HBV genotype terms, significantly so over the HBV genotype-only model (likelihood ratio test, p < 0.001) and almost so over tumor stage alone (p = 0.101). HBV genotype is a remarkably strong predictor of overall patient survival. We surveyed differentially expressed host genes between HPV genotype 16- (HPV16, n = 173) and HPV genotype 18- (HPV18, n = 39) infected cervical tumors of TCGA, representing the two most dominant genotypes. Via GSEA, we found that pathways in tumor vasculature and endothelial growth are enriched in HPV16- over HPV18-infected tumors, whereas TNF-signal-regulated apoptosis is downregulated (FDR<0.01) (Figure 4A; Table S1). Similarly, we tested for the effect of co-infection and found that in contrast to single HPV genotype cervical tumors (n = 193), those infected with multiple HPV genotypes (n = 92) are enriched in non-IFR3 antiviral activation of lymphocytes and B cell antigen activation pathways (FDR<0.05) (Figure 4B), suggesting preferential activation of alternative immune regulatory pathways in HPV co-infected tumors. We also carried out viral integration analysis finding no significant sites of preferential integration across either HPV genotype (Cao et al., 2016Cao S. Wendl M.C. Wyczalkowski M.A. Wylie K. Ye K. Jayasinghe R. Xie M. Wu S. Niu B. Grubb R. et al.Divergent viral presentation among human tumors and adjacent normal tissues.Sci. Rep. 2016; 6: 28294https://doi.org/10.1038/srep28294Crossref PubMed Scopus (41) Google Scholar) or co-infection status (Figure S7) (Tang et al., 2013Tang K.W. Alaei-Mahabadi B. Samuelsson T. Lindh M. Larsson E. The landscape of viral expression and host gene fusion and adaptation in human cancer.Nat. Commun. 2013; 4: 2513https://doi.org/10.1038/ncomms3513Crossref PubMed Scopus (201) Google Scholar; Hu et al., 2015Hu Z. Zhu D. Wang W. Li W. Jia W. Zeng X. Ding W. Yu L. Wang X. Wang L. et al.Genome-wide profiling of HPV integration in cervical cancer identifies clustered genomic hot spots and a potential microhomology-mediated integration mechanism.Nat. Genet. 2015; 47: 158-163https://doi.org/10.1038/ng.3178Crossref PubMed Scopus (243) Google Scholar; Cancer Genome Atlas Research Network et al., 2017aCancer Genome Atlas Research Network Integrated genomic and molecular characterization of cervical cancer.Nature. 2017; 543: 378-384Crossref PubMed Scopus (662) Google Scholar). Finally, whereas it was previously shown that APOBEC3 expression (associated with antiviral activity) is upregulated in HPV-associated head and neck cancers but not cervical cancers (Zapatka et al., 2020Zapatka M. Borozan I. Brewer D.S. Iskar M. Grundhoff A. Alawi M. Desai N. Sültmann H. Moch H. au fnm et al.The landscape of viral associations in human cancers.Nat. Genet. 2020; 52: 320-330Crossref PubMed Scopus (87) Google Scholar), we found that APOBEC3 is significantly upregulated in cervical tumors with HPV16 over HPV18, and in tumors with a singular HPV infection over those with multiple HPV genotypes, controlling for HPV genotype (HPV18, HPV45) (Figure 4D). Thus the increase in APOBEC activity seen in HPV+ patients (Zapatka et al., 2020Zapatka M. Borozan I. Brewer D.S. Iskar M. Grundhoff A. Alawi M. Desai N. Sültmann H. Moch H. au fnm et al.The landscape of viral associations in human cancers.Nat. Genet. 2020; 52: 320-330Crossref PubMed Scopus (87) Google Scholar) is actually further dependent on HPV genotype and co-infection rather than viral infection status alone. Increased APOBEC3 activation has been shown to be linked with further tumor mutagenesis (Burns et al., 2013Burns M.B. Temiz N.A. Harris R.S. Evidence for APOBEC3B mutagenesis in multiple human cancers.Nat. Genet. 2013; 45: 977-983Crossref PubMed Scopus (478) Google Scholar), signaling that HPV16 infection may further drive cervical tumorigenesis. In order to quantify the predictive effect of viral genotype and co-infection status on patient survival, we built Cox proportional hazard models of overall survival in the CESC TCGA using predictors clinical tumor stage, HPV molecular terms (tumor HPV genotype, viral expression, and viral co-infection status), and patient TMB. As before, we computed and compared time-dependent Brier scores between models to compare prediction error (Figure 4C). Although all models slightly but significantly reduced prediction error with respect to the naive reference model, we note that it is driven by the relatively small number of events (deaths) among patients with cervical cancer. However, the addition of HPV molecular terms to clinical tumor stage (TS + HPV_Terms) significantly reduced prediction error compared with tumor stage alone (Tumor_Stg_only), indicating that additional predictive survival power is encoded by HPV phenotype (likelihood ratio test, p = 0.023). Furthermore, we found this genotype-driven model performs on par with a model using tumor stage and patient TMB (TS + TMB) (likelihood ratio test, p = 1) as predictors. Taken together, our results confirm that HPV16 modestly but significantly associates with poorer survival (Hang et al., 2017Hang D. Jia M. Ma H. Zhou J. Feng X. Lyu Z. Yin J. Cui H. Yin Y. Jin G. et al.Independent prognostic role of human papillomavirus genotype in cervical cancer.BMC Infect. Dis. 2017; 17: 391Crossref PubMed Scopus (25) Google Scholar) and that HPV phenotype is a reasonable predictor of survival, adding significant predictive power beyond tumor staging and tumor mutation burden alone. To further parse the association of overall tumor mutation burden and viral genotypes by specific mutation type, we derived single base-pair substitution (SBS)-based mutational signatures (Alexandrov et al., 2013Alexandrov L.B. Nik-Zainal S. Wedge D.C. Aparicio S.A. Behjati S. Biankin A.V. Bignell G.R. Bolli N. Borg A. Børresen-Dale A.L. et al.Signatures of mutational processes in human cancer.Nature. 2013; 500: 415-421Crossref PubMed Scopus (5422) Google Scholar) for the LIHC, CESC, and HNSC TCGA by stratifying patients based on tumor HBV genotype and HPV viral clade, respectively. As shown by Alexandrov et al., these signatures are key descriptors of cancer phenotypes and can serve as prognostic and predictive biomarkers (Trucco et al., 2019Trucco L.D. Mundra P.A. Hogan K. Garcia-Martinez P. Viros A. Mandal A.K. Macagno N. Gaudy-Marqueste C. Allan D. Baenke F. et al.Ultraviolet radiation-induced DNA damage is prognostic for outcome in melanoma.Nat. Med. 2019; 25: 221-224Crossref PubMed Scopus (37) Google Scholar; Alexandrov et al., 2013Alexandrov L.B. Nik-Zainal S. Wedge D.C. Aparicio S.A. Behjati S. Biankin A.V. Bignell G.R. Bolli N. Borg A. Børresen-Dale A.L. et al.Signatures of mutational processes in human cancer.Nature. 2013; 500: 415-421Crossref PubMed Scopus (5422) Google Scholar; Trucco et al., 2019Trucco L.D. Mundra P.A. Hogan K. Garcia-Martinez P. Viros A. Mandal A.K. Macagno N. Gaudy-Marqueste C. Allan D. Baenke F. et al.Ultraviolet radiation-induced DNA damage is prognostic for outcome in melanoma.Nat. Med. 2019; 25: 221-224Crossref PubMed Scopus (37) Google Scholar). Using their algorithm (see transparent methods), we found signatures linked to tobacco smoking and those of unknown etiology (see Single Base Substitution (SBS) Signatures, Alexandrov et al., 2013Alexandrov L.B. Nik-Zainal S. Wedge D.C. Aparicio S.A. Behjati S. Biankin A.V. Bignell G.R. Bolli N. Borg A. Børresen-Dale A.L. et al.Signatures of mutational processes in human cancer.Nature. 2013; 500: 415-421Crossref PubMed Scopus (5422) Google Scholar) were preferentially enriched in the HBV B-associated liver cancer mutational profile and were absent from the HBV C profile (Figure 5A; average enrichments in Table S2). Both patient groups were enriched in SBS22 and SBS24, linked to carcinogenic aristolochic acid and aflatoxin B1 exposures, respectively, as previously reported enriched across HBV+ LIHC patients (Cancer Genome Atlas Research Network, 2017bCancer Genome Atlas Research NetworkComprehensive and integrative genomic characterization of hepatocellular carcinoma.Cell. 2017; 169: 1327-1341.e23Abstract Full Text Full Text PDF PubMed Scopus (918) Google Scholar). In cervical cancers, however, we found that tumor mutational profiles associated with HPV a9 infections (including genotypes 16, 31, 33, 35, 52, and 58) are enriched in signatures SBS3, SBS9, SBS26, and SBS29, whereas these signatures are absent from the HPV a7 (including genotypes 18, 39, 45, 59, and 68) mutational profile (Figure 5A; Table S2). Signatures SBS3 and SBS26 are both linked to defective DNA damage repair pathways, whereas SBS29 is associated with exposure to chewing tobacco and SBS9 serves as a signature of hypermutation in lymphoid cells. On the other hand, signature SBS40 (of unknown etiology) is enriched only in HPV a7 tumors. Although no head and neck tumors were associated with HPV genotypes in the a7 clade, we found head and neck tumors associated with HPV a9 infections were actually enriched in the majority of the same signatures as the cervical HPV a9 tumors (SBS3, 9, 29 and 36; Figure 5A; Table S2), with exceptions for signatures SBS36, linked to defective base excision repair, and SBS26. In order to clearly visualize any trends in mutational signatures scaling with overall viral burden, we selected representative patients spanning the range of total viral expression from each tumor genotype (Figure 5B). We found no association between viral expression and mutational signature enrichment in patients, across any HBV or HPV cohort (pmin > ~0.7), or across patient TMB (pmin > ~0.5) (Figure S8). Our results suggest that viral genotype does indeed delineate specific mutational signatures, regardless of total viral expression or tumor mutation burden, across both HPV-associated cervical and head and neck cancers and HBV-associated HCC liver cancer. Apart from enriching in mutational signatures with well-established functional associations (SBS1, 4, 5, 26), other strong genotype-specific enrichments are for mutational signatures of unknown etiology (SBS17, 40, 46), suggesting potentially new functional viral associations and hypotheses. Given the evidence that HBV genotype serves as a significant predictor of patient survival in HCC, we hypothesized that a lower tumor antigen immunogenicity might drive worse outcomes in patients with HBV C-associated HCC. Inferring HLA types calculated from HBV + patient tumor RNA-seq in the TCGA LIHC, we estimated the MHC-I binding affinities for a total of 37,222 and 142,539 unique tumor neoantigens across patients with HBV B and HBV C, respectively (Table S6). Comparing predicted neoantigen MHC-I binding affinities reveals a significantly higher binding affinity bias (lower ic50) for HBV B-related tumor neoantigens over peptides from HBV C-related" @default.
• W3147702576 created "2021-04-13" @default.
• W3147702576 creator A5015321462 @default.
• W3147702576 creator A5043236874 @default.
• W3147702576 creator A5059651582 @default.
• W3147702576 creator A5063172143 @default.
• W3147702576 creator A5078457997 @default.
• W3147702576 creator A5084915000 @default.
• W3147702576 creator A5090322942 @default.
• W3147702576 date "2021-04-01" @default.
• W3147702576 modified "2023-09-30" @default.
• W3147702576 title "Landscape of oncoviral genotype and co-infection via human papilloma and hepatitis B viral tumor in situ profiling" @default.
• W3147702576 cites W1917716589 @default.
• W3147702576 cites W1967427273 @default.
• W3147702576 cites W1976489901 @default.
• W3147702576 cites W1985912950 @default.
• W3147702576 cites W1995462034 @default.
• W3147702576 cites W2014186896 @default.
• W3147702576 cites W2017474562 @default.
• W3147702576 cites W2041307935 @default.
• W3147702576 cites W2049553585 @default.
• W3147702576 cites W2079172413 @default.
• W3147702576 cites W2080277009 @default.
• W3147702576 cites W2091307968 @default.
• W3147702576 cites W2095729794 @default.
• W3147702576 cites W2104153021 @default.
• W3147702576 cites W2126216210 @default.
• W3147702576 cites W2131255017 @default.
• W3147702576 cites W2134448651 @default.
• W3147702576 cites W2152061559 @default.
• W3147702576 cites W2155254827 @default.
• W3147702576 cites W2165934724 @default.
• W3147702576 cites W2166632132 @default.
• W3147702576 cites W2171917618 @default.
• W3147702576 cites W2343898601 @default.
• W3147702576 cites W2464938966 @default.
• W3147702576 cites W2575837388 @default.
• W3147702576 cites W2605196547 @default.
• W3147702576 cites W2622708620 @default.
• W3147702576 cites W2625559053 @default.
• W3147702576 cites W2769554340 @default.
• W3147702576 cites W2772939762 @default.
• W3147702576 cites W2794971178 @default.
• W3147702576 cites W2810997009 @default.
• W3147702576 cites W2898074532 @default.
• W3147702576 cites W2901987494 @default.
• W3147702576 cites W2943793962 @default.
• W3147702576 cites W2946230264 @default.
• W3147702576 cites W3005400930 @default.
• W3147702576 cites W3005619707 @default.
• W3147702576 doi "https://doi.org/10.1016/j.isci.2021.102368" @default.
• W3147702576 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8050859" @default.
• W3147702576 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33889830" @default.
• W3147702576 hasPublicationYear "2021" @default.
• W3147702576 type Work @default.
• W3147702576 sameAs 3147702576 @default.
• W3147702576 citedByCount "4" @default.
• W3147702576 countsByYear W31477025762021 @default.
• W3147702576 countsByYear W31477025762022 @default.
• W3147702576 countsByYear W31477025762023 @default.
• W3147702576 crossrefType "journal-article" @default.
• W3147702576 hasAuthorship W3147702576A5015321462 @default.
• W3147702576 hasAuthorship W3147702576A5043236874 @default.
• W3147702576 hasAuthorship W3147702576A5059651582 @default.
• W3147702576 hasAuthorship W3147702576A5063172143 @default.
• W3147702576 hasAuthorship W3147702576A5078457997 @default.
• W3147702576 hasAuthorship W3147702576A5084915000 @default.
• W3147702576 hasAuthorship W3147702576A5090322942 @default.
• W3147702576 hasBestOaLocation W31477025761 @default.
• W3147702576 hasConcept C104317684 @default.
• W3147702576 hasConcept C111919701 @default.
• W3147702576 hasConcept C135763542 @default.
• W3147702576 hasConcept C159047783 @default.
• W3147702576 hasConcept C178790620 @default.
• W3147702576 hasConcept C185592680 @default.
• W3147702576 hasConcept C187191949 @default.
• W3147702576 hasConcept C2777822432 @default.
• W3147702576 hasConcept C41008148 @default.
• W3147702576 hasConcept C54355233 @default.
• W3147702576 hasConcept C70721500 @default.
• W3147702576 hasConcept C86803240 @default.
• W3147702576 hasConceptScore W3147702576C104317684 @default.
• W3147702576 hasConceptScore W3147702576C111919701 @default.
• W3147702576 hasConceptScore W3147702576C135763542 @default.
• W3147702576 hasConceptScore W3147702576C159047783 @default.
• W3147702576 hasConceptScore W3147702576C178790620 @default.
• W3147702576 hasConceptScore W3147702576C185592680 @default.
• W3147702576 hasConceptScore W3147702576C187191949 @default.
• W3147702576 hasConceptScore W3147702576C2777822432 @default.
• W3147702576 hasConceptScore W3147702576C41008148 @default.
• W3147702576 hasConceptScore W3147702576C54355233 @default.
• W3147702576 hasConceptScore W3147702576C70721500 @default.
• W3147702576 hasConceptScore W3147702576C86803240 @default.
• W3147702576 hasFunder F4320309658 @default.
• W3147702576 hasIssue "4" @default.
• W3147702576 hasLocation W31477025761 @default.
• W3147702576 hasLocation W31477025762 @default.
• W3147702576 hasLocation W31477025763 @default.

• next