Pan-Cancer Analysis of PARP1 Alterations as Biomarkers in the Prediction of Immunotherapeutic Effects and the Association of Its Expression Levels and Immunotherapy Signatures.
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ABSTRACT:
SUBMITTER: Zhang X
PROVIDER: S-EPMC8438309 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ARID1A alterations would compromise mismatch repair pathway and increase the number of tumor-infiltrating lymphocytes and PD-L1 expression in some cancers, which would cooperate with immune checkpoint inhibitors (ICIs) treatment. However, a comprehensive analysis of ARID1A alteration frequency and its predictive value for ICI treatment outcome in cancers has not yet been investigated. Hence, we performed this pan-cancer analysis to evaluate the prevalence and predictive value of ARID1A alterations across >40,000 cases in multiple cancer types. We found a high frequency (6.2%) of ARID1A, which were associated with significantly higher tumor mutation burden level across various cancers. Importantly, patients with ARID1A alterations and advanced cancers had the substantially prolonged overall survival in ICI treatment cohort, suggesting it might be used to predict a survival benefit from ICI therapy across multiple cancer types. Notably, ARID1A alterations were correlated with markedly high immune infiltrates in endometrial, stomach and colon cancer. However, patients with ARID1A-mutant renal clear cell carcinoma had dramatically lower CD8+ T cell infiltrations than those without, indicating the association between ARID1A alterations and immune infiltrates was cancer-dependent. Collectively, our findings highlight the important value of ARID1A alterations as pan-cancer predictive biomarkers for ICI treatment.
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Project description:Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab. TMB and GEP were independently predictive of response and demonstrated low correlation, suggesting that they capture distinct features of neoantigenicity and T cell activation. Analysis of The Cancer Genome Atlas database showed TMB and GEP to have a low correlation, and analysis by joint stratification revealed biomarker-defined patterns of targetable-resistance biology. These biomarkers may have utility in clinical trial design by guiding rational selection of anti-PD-1 monotherapy and combination immunotherapy regimens.
| S-EPMC6718162 | biostudies-literature
Project description:Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and widely adopted for various tumor types. Nevertheless, tumor immunotherapy has a few drawbacks, including significant uncertainty of outcome, the possibility of severe immune-related adverse events for patients receiving such treatments, and the lack of effective biomarkers to determine the ICI treatments' responsiveness. DNA methylation profiles were recently identified as an indicator of the tumor immune microenvironment. They serve as a potential hot spot for predicting responses to ICI treatment for their stability and convenience of measurement by liquid biopsy. We demonstrated the possibility of DNA methylation profiles as a predictor for responses to the ICI treatments at the pan-cancer level by analyzing DNA methylation profiles considered responsive and non-responsive to the treatments. An SVM model was built based on this differential analysis in the pan-cancer levels. The performance of the model was then assessed both at the pan-cancer level and in specific tumor types. It was also compared to the existing gene expression profile-based method. DNA methylation profiles were shown to be predictable for the responses to the ICI treatments in the TCGA cases in pan-cancer levels. The proposed SVM model was shown to have high performance in pan-cancer and specific cancer types. This performance was comparable to that of gene expression profile-based one. The combination of the two models had even higher performance, indicating the potential complementarity of the DNA methylation and gene expression profiles in the prediction of ICI treatment responses.
| S-EPMC8695566 | biostudies-literature
Project description:Owing to a lack of response to the anti-PD1 therapy for most cancer patients, we develop a network approach to infer genes, pathways, and potential therapeutic combinations that are associated with tumor response to anti-PD1. Here, our prediction identifies genes and pathways known to be associated with anti-PD1, and is further validated by 6 CRISPR gene sets associated with tumor resistance to cytotoxic T cells and targets of the 36 compounds that have been tested in clinical trials for combination treatments with anti-PD1. Integration of our top prediction and TCGA data identifies hundreds of genes whose expression and genetic alterations that could affect response to anti-PD1 in each TCGA cancer type, and the comparison of these genes across cancer types reveals that the tumor immunoregulation associated with response to anti-PD1 would be tissue-specific. In addition, the integration identifies the gene signature to calculate the MHC I association immunoscore (MIAS) that shows a good correlation with patient response to anti-PD1 for 411 melanoma samples complied from 6 cohorts. Furthermore, mapping drug target data to the top genes in our association prediction identifies inhibitors that could potentially enhance tumor response to anti-PD1, such as inhibitors of the encoded proteins of CDK4, GSK3B, and PTK2.
| S-EPMC8748689 | biostudies-literature
Project description:Importance:Long noncoding RNAs (lncRNAs) are involved in innate and adaptive immunity in cancer by mediating the functional state of immunologic cells, pathways, and genes. However, whether lncRNAs are associated with immune molecular classification and clinical outcomes of cancer immunotherapy is largely unknown. Objectives:To explore lncRNA-based immune subtypes associated with survival and response to cancer immunotherapy and to present a novel lncRNA score for immunotherapy prediction using computational algorithms. Design, Setting, and Participants:In this cohort study, an individual patient analysis based on a phase 2, single-arm clinical trial and multicohort was performed from June 25 through September 30, 2019. Data are from the phase 2 IMvigor210 trial and from The Cancer Genome Atlas (TCGA). The study analyzed lncRNA and genomic data of 348 patients with bladder cancer from the IMvigor210 trial and 71 patients with melanoma from TCGA who were treated with immunotherapy. In addition, a pancancer multicohort that included 2951 patients was obtained from TCGA. Main Outcomes and Measures:The primary end point was overall survival (OS). Results:Among 348 patients from the IMvigor210 trial (272 [78.2%] male) and 71 patients with melanoma from TCGA (mean [SD] age, 58.3 [13.4] years; 37 [52.1%] female), 4 distinct classes with statistically significant differences in OS (median months, not reached vs 9.6 vs 8.1 vs 6.7 months; P = .002) were identified. The greatest OS benefit was obtained in the immune-active class, as characterized by the immune-functional lncRNA signature and high CTL infiltration. Patients with low vs high lncRNA scores had statistically significantly longer OS (hazard ratio, 0.32; 95% CI, 0.24-0.42; P < .001) in the IMvigor210 trial and across various cancer types. The lncRNA score was associated with immunotherapeutic OS benefit in the IMvigor210 trial cohort (area under the curve [AUC], 0.79 at 12 months and 0.77 at 20 months) and in TCGA melanoma cohort (AUC, 0.87 at 24 months), superior tumor alteration burden, programmed cell death ligand 1 (PD-L1) expression, and cytotoxic T-lymphocyte (CTL) infiltration. Addition of the lncRNA score to the combination of tumor alteration burden, PD-L1 expression, and CTL infiltration to build a novel multiomics algorithm correlated more strongly with OS in the IMvigor210 trial cohort (AUC, 0.81 at 12 months and 0.80 at 20 months). Conclusions and Relevance:This study identifies novel lncRNA-based immune classes in cancer immunotherapy and recommends immunotherapy for patients in the immune-active class. In addition, the study recommends that the lncRNA score should be integrated into multiomic panels for precision immunotherapy.
| S-EPMC7139278 | biostudies-literature
Project description:Molecular subtyping is expected to enable bladder cancer (BC) precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE) in tumor immune escape and immunotherapy, we aimed to develop a novel TIDE-based subtyping method to facilitate personalized management. Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. In conclusion, our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.
2024-04-19 | GSE248167 | GEO
Project description:AimInsulin-like growth factor-1 receptor (IGF-1R) is one of the main members of the tyrosine protein kinase receptor family. This receptor binds insulin-like growth factor-1 (IGF-1) with a high affinity. IGF-1 is a member of a family of proteins involved in mediating growth and development. However, the correlations of IGF-1 and IGF-1R to prognosis and tumor-infiltrating lymphocytes in different cancers remain unclear.MethodThis research comprehensively analyzed the expression pattern of IGF-1 and IGF-1R and the influence of IGF-1 and IGF-1R on clinical significance in prognosis prediction among 33 types of malignancies using The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) databases. The correlation between IGF-1, IGF-1R, and cancer immunity was explored.ResultsIGF-1 and IGF-1R displayed inconsistent gene expression levels among diverse cancer cell lines. Typically, high expression level of IGF-1 and IGF-1R was detected in most malignant tumors. High expression of IGF-1 was closely bound up with the unfavorable overall survival (OS) for patients in BLCA, CHOL, and LAML upon Cox and Kaplan-Meier analyses. While high expression of IGF-1R was closely bound up with the unfavorable overall survival (OS) for patients in BLCA, LIHC, and LUAD. Furthermore, high expression level of IGF-1 and IGF-1R were closely connected with high degrees of tumor infiltrates, including CD4+ T cell, dendritic cells, and macrophages. In addition, we found that IGF-1 was commonly positively correlated with the expression of gene markers including LAIR1, ICOS, CD40LG, CTLA4, CD48, CD28, CD200R1, HAVCR2, and CD86. Whereas, IGF-1R was commonly positively correlated with the expression of gene markers including NRP1 and CD276. More importantly, IGF-1 and IGF-1R expression were correlated with tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) of different types of cancers.ConclusionsThe impact of high IGF-1 and IGF-1R on prognosis and immune infiltrates differs across cancer types. Anti-IGF-1R therapy may inhibit tumor growth and contribute to immunotherapy in LIHC and KIRC.
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Project description:Pan-cancer genomic analyses based on the magnitude of pathway activity are currently lacking. Focusing on the cell cycle, we examined the DNA mutations and chromosome arm-level aneuploidy within tumours with low, intermediate and high cell-cycle activity in 9515 pan-cancer patients with 32 different tumour types. Boxplots showed that cell-cycle activity varied broadly across and within all cancers. TP53 and PIK3CA mutations were common in all cell cycle score (CCS) tertiles but with increasing frequency as cell-cycle activity levels increased (P < 0.001). Mutations in BRAF and gains in 16p were less frequent in CCS High tumours (P < 0.001). In Kaplan-Meier analysis, patients whose tumours were CCS Low had a longer Progression Free Interval (PFI) relative to Intermediate or High (P < 0.001) and this significance remained in multivariable analysis (CCS Intermediate: HR = 1.37; 95% CI 1.17-1.60, CCS High: 1.54; 1.29-1.84, CCS Low = Ref). These results demonstrate that whilst similar DNA alterations can be found at all cell-cycle activity levels, some notable exceptions exist. Moreover, independent prognostic information can be derived on a pan-cancer level from a simple measure of cell-cycle activity.
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Project description:There is conflicting data regarding the role of PBAF complex mutations and response to immune checkpoint blockade (ICB) therapy in clear cell renal cell carcinoma (ccRCC) and other solid tumors. We assess the prevalence of PBAF complex mutations from two large cohorts including the pan-cancer TCGA project (n?=?10,359) and the MSK-IMPACT pan-cancer immunotherapy cohort (n?=?3700). Across both cohorts, PBAF complex mutations, predominantly PBRM1 mutations, are most common in ccRCC. In multivariate models of ccRCC patients treated with ICB (n?=?189), loss-of-function (LOF) mutations in PBRM1 are not associated with overall survival (OS) (HR?=?1.24, p?=?0.47) or time to treatment failure (HR?=?0.85, p?=?0.44). In a series of 11 solid tumors (n?=?2936), LOF mutations are not associated with improved OS in a stratified multivariate model (HR?=?0.9, p?=?0.7). In a current series of solid tumors treated with ICB, we are unable to demonstrate favorable response to ICB in patients with PBAF complex mutations.
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Project description:Histone methyltransferase SETD2 plays a critical role in maintaining genomic integrity and stability. Here, we investigated the characteristics of SETD2 somatic mutation in the cancer genome atlas pan-cancer cohort. Our data revealed that, compared with SETD2 nonmutant patients, SETD2 mutant patients had higher tumor mutation burden and microsatellite instability. In addition, the transcriptions of most genes related to immune activities were upregulated in patients with SETD2 mutant tumors. Further examination of cancer patients treated with immune checkpoint inhibitors suggested SETD2 mutation was associated with favorable clinical outcomes. These results have implication for the personalization of cancer immunotherapy.
| S-EPMC8203790 | biostudies-literature