EZH1/2 alteration as a potential biomarker for immune checkpoint inhibitors across multiple cancer types.
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ABSTRACT:
SUBMITTER: Huang H
PROVIDER: S-EPMC10724995 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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EZH1/2 alteration as a potential biomarker for immune checkpoint inhibitors across multiple cancer types.
Huang Huageng H Deng Xinyi X Yu Le L Huang He H Wang Zhao Z Hong Huangming H Lin Tongyu T
Journal of translational medicine 20231215 1
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Project description:BackgroundImmune checkpoint inhibitors (ICIs) are dramatically changing the treatment landscape of a variety of cancers. Nevertheless, the variability in ICI responses highlight the importance in identifying predictive biomarkers. PTPRD and PTPRT (PTPRD/PTPRT) are the phosphatases of JAK-STAT signaling, a critical pathway in anti-cancer immunity regulation. However, the pan-cancer association between PTPRD/PTPRT mutation and the efficacy of ICIs remains unclear across pan-cancer patients.MethodsWe analyzed the association between PTPRD/PTPRT mutations and patient outcomes using clinical data and genomic mutations from TCGA pan-cancer cohort. Furthermore, the ICI-treatment cohort was used to evaluate the relationship between PTPRD/PTPRT mutation and the efficacy of ICIs. Another ICIs-treatment cohort was used to validate the findings. The TCGA pan-cancer dataset was analyzed to explore the correlation between PTPRD/PTPRT mutations and immune signatures. Moreover, we combined four factors to construct a nomogram model that could be used to predict the survival of pan-cancer patients receiving ICI treatment. The calibration curves and area under the curve were applied to assess the performance of the model.ResultsPTPRD/PTPRT mutations were shown to be associated with a worse prognosis in TCGA cohort (P < 0.05). In the Samstein cohort, prolonged overall survival (OS) was observed in PTPRD/PTPRT mutant cancers, compared with wild-type cancers (mOS: 40.00 vs 16.00 months, HR = 0.570, 95%CI: 0.479-0.679, P < 0.0001). In the validation cohort, significant OS advantage was observed in PTPRD/PTPRT mutant patients (mOS: 31.32 vs 15.53 months, HR = 0.658, 95%CI: 0.464-0.934, P = 0.0292). Furthermore, PTPRD/PTPRT mutations were associated with a higher tumor mutational burden, MSI score, and TCR score (P < 0.0001). Enhanced immune signatures were found in the PTPRD/PTPRT mutant cancers (P < 0.05). Finally, we successfully established a nomogram model that could be used to predict the survival of NSCLC patients who received ICI treatment. Based on the risk score of the model, patients in the low-risk group showed a better mOS than those in the high-risk group (mOS: 2.75 vs 1.08 years, HR = 0.567, 95%CI: 0.492-0.654; P < 0.001).ConclusionsPTPRD/PTPRT mutations may be a potential biomarker for predicting ICI treatment responsiveness in multiple cancer types.
| S-EPMC9556668 | biostudies-literature
Project description:BackgroundImmune checkpoint inhibitors (ICIs) have achieved impressive success in different cancer types, yet responses vary and predictive biomarkers are urgently needed. Growing evidence points to a link between DNA methylation and anti-tumor immunity, while clinical data on the association of genomic alterations in DNA methylation-related genes and ICI response are lacking.MethodsClinical cohorts with annotated response and survival data and matched mutational data from published studies were collected and consolidated. The predictive function of specific mutated genes was first tested in the discovery cohort and later validated in the validation cohort. The association between specific mutated genes and tumor immunogenicity and anti-tumor immunity was further investigated in the Cancer Genome Altas (TCGA) dataset.ResultsAmong twenty-one key genes involving in the regulation of DNA methylation, TET1-mutant (TET1-MUT) was enriched in patients responding to ICI treatment in the discovery cohort (p=0.003). TET1 was recurrently mutated across multiple cancers and more frequently seen in skin, lung, gastrointestinal, and urogenital cancers. In the discovery cohort (n = 519), significant differences were observed between TET1-MUT and TET1-wildtype (TET1-WT) patients regarding objective response rate (ORR, 60.9% versus 22.8%, P < 0.001), durable clinical benefit (DCB, 71.4% versus 31.6%, P < 0.001), and progression-free survival (PFS, hazard ratio = 0.46 [95% confidence interval, 0.25 to 0.82], P = 0.008). In the validation cohort (n = 1395), significant overall survival (OS) benefit was detected in the TET1-MUT patients compared to TET1-WT patients (hazard ratio = 0.47 [95% confidence interval, 0.25 to 0.88], P = 0.019), which was, importantly, independent of tumor mutational burden and high microsatellite instability; as well as not attributed to the prognostic impact of TET1-MUT (P > 0.05 in both two non-ICI-treated cohorts). In TCGA dataset, TET1-MUT was strongly associated with higher tumor mutational burden and neoantigen load, and inflamed pattern of tumor-infiltrating T lymphocytes, immune signatures and immune-related gene expressions.ConclusionsTET1-MUT was strongly associated with higher ORR, better DCB, longer PFS, and improved OS in patients receiving ICI treatment, suggesting that TET1-MUT is a novel predictive biomarker for immune checkpoint blockade across multiple cancer types.
| S-EPMC6798429 | biostudies-literature
Project description:Immune checkpoint inhibitors (ICIs) therapy elicits admirable anti-tumor responses across many types of cancer. Growing evidence point to a link to Mediator complex subunit 12 (MED12) and DNA damage repair (DDR) and TGF-β signing, while the clinical data on the association of MED12 and ICIs response are lacking. In this study, clinical and whole-exome sequencing (WES) data from published studies were merged as a WES cohort to explore the association between MED12 mutation (MED12-Mut) and ICIs efficiency across cancers. Then, Memorial Sloan Kettering Cancer Center (MSKCC) cohort was used for validating our findings. The Cancer Genome Atlas (TCGA) cohort was used to perform anti-tumor immunity and prognosis analysis. In the WES cohort (n = 474), significant differences were detected between MED12-Mut and MED12-wildtype (MED12-Wt) patients regarding durable clinical benefit (DCB, 80.00% vs. 53.67%, P = 0.022). In addition, significantly prolonged PFS was observed in MED12-Mut patients (mPFS: not reached, NR vs. 5.87 months, HR: 0.38, 95% CI 0.17-0.85, log-rank P = 0.015), After taking into account age, gender, metastasis, treatment and TMB status, the result of multivariable Cox proportional hazards regression showed significantly better PFS (HR:0.40, 95% CI 0.18-0.92; P = 0.031). In the MSKCC cohort (n = 1513), overall survival advantage was achieved in MED12-Mut patients (mOS: 41 vs. 19 months, HR:0.54, 95%CI 0.34-0.85; log-rank P = 0.007), after taking into account same factors in WES cohort, this link still existed (HR: 0.60, 95% CI: 0.38-0.96, P = 0.033), Notably, TMB was also found significantly higher in MED12-Mut patients in both WES and MSKCC cohort. Further tumor-infiltrating lymphocytes and DDR-related gene analysis revealed anti-tumor immunity in MED12-Mut patients. Totally, MED12-Mut successfully predicted better clinical outcomes in ICIs-treated pan-cancer cohort, indicating that MED12-Mut could serve as a potential predictive biomarker for immune checkpoint inhibitors in pan-cancer.
| S-EPMC9618186 | biostudies-literature
Project description:Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose1. Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions.
| S-EPMC9363980 | biostudies-literature
Project description:BackgroundA critical and challenging process in immunotherapy is to identify cancer patients who could benefit from immune checkpoint inhibitors (ICIs). Exploration of predictive biomarkers could help to maximize the clinical benefits. Eph receptors have been shown to play essential roles in tumor immunity. However, the association between EPH gene mutation and ICI response is lacking.MethodsClinical data and whole-exome sequencing (WES) data from published studies were collected and consolidated as a discovery cohort to analyze the association between EPH gene mutation and efficacy of ICI therapy. Another independent cohort from Memorial Sloan Kettering Cancer Center (MSKCC) was adopted to validate our findings. The Cancer Genome Atlas (TCGA) cohort was used to perform anti-tumor immunity and pathway enrichment analysis.ResultsAmong fourteen EPH genes, EPHA7-mutant (EPHA7-MUT) was enriched in patients responding to ICI therapy (FDR adjusted P < 0.05). In the discovery cohort (n = 386), significant differences were detected between EPHA7-MUT and EPHA7-wildtype (EPHA7-WT) patients regarding objective response rate (ORR, 52.6% vs 29.1%, FDR adjusted P = 0.0357) and durable clinical benefit (DCB, 70.3% vs 42.7%, FDR adjusted P = 0.0200). In the validation cohort (n = 1144), significant overall survival advantage was observed in EPHA7-MUT patients (HR = 0.62 [95% confidence interval, 0.39 to 0.97], multivariable adjusted P = 0.0367), which was independent of tumor mutational burden (TMB) and copy number alteration (CNA). Notably, EPHA7-MUT patients without ICI therapy had significantly worse overall survival in TCGA cohort (HR = 1.33 [95% confidence interval, 1.06 to 1.67], multivariable adjusted P = 0.0139). Further gene set enrichment analysis revealed enhanced anti-tumor immunity in EPHA7-MUT tumor.ConclusionsEPHA7-MUT successfully predicted better clinical outcomes in ICI-treated patients across multiple cancer types, indicating that EPHA7-MUT could serve as a potential predictive biomarker for immune checkpoint inhibitors.
| S-EPMC7852135 | biostudies-literature
Project description:Breast cancer is the most common cancer type and the leading cause of cancer-associated mortality in women worldwide. In recent years, immune checkpoint inhibitors (ICIs) have made significant progress in the treatment of breast cancer, yet there are still a considerable number of patients who are unable to gain lasting and ideal clinical benefits by immunotherapy alone, which leads to the development of a combination regimen as a novel research hotspot. Furthermore, one miRNA can target several checkpoint molecules, mimicking the therapeutic effect of a combined immune checkpoint blockade (ICB), which means that the miRNA therapy has been considered to increase the efficiency of ICIs. In this review, we summarized potential miRNA therapeutics candidates which can affect multiple targets of immune checkpoints in breast cancer with more therapeutic potential, and the obstacles to applying miRNA therapeutically through the analyses of the resources available from a drug target perspective. We also included the content of "too many targets for miRNA effect" (TMTME), combined with applying TargetScan database, to discuss adverse events. This review aims to ignite enthusiasm to explore the application of miRNAs with multiple targets of immune checkpoint molecules, in combination with ICIs for treating breast cancer.
| S-EPMC9913694 | biostudies-literature
Project description:Siglec-9, a cell surface transmembrane receptor mainly expressed on B cells, CD56+ NK cells, and CD4+ and CD8+ T cells, is strongly related to the tumor immune microenvironment. However, the expression pattern of Siglec-9 and its prognostic potential have not been investigated in a pan-cancer perspective. This study aimed to explore the association of Siglec-9 with prognosis, tumor stage, molecular subtype, and the immune microenvironment in pan-cancer. The mRNA expression of Siglec-9 was obtained from The Cancer Genome Atlas (TCGA), the Broad Institute Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx). The relationship between Siglec-9 mRNA expression and prognosis was evaluated by the Kaplan-Meier analysis. The correlation between Siglec-9 and tumor-infiltrating immune cells, immune subtype, and molecular subtype was evaluated on Tumor Immune Estimation Resource (TIMER) and Integrated Repository Portal for Tumor-Immune System Interactions (TISIDB). The correlation between Siglec-9 expression and immune checkpoint, mismatch repair (MMR), DNA methyltransferase (DNMT), tumor mutation burden (TMB), and microsatellite instability (MSI) was also analyzed. It showed that Siglec-9 expression was significantly altered in most TCGA tumors. Siglec-9 expression was associated with the prognosis of patients with adrenocortical carcinoma (ACC), lung adenocarcinoma (LUSC), thymoma (THYM), colon adenocarcinoma (COAD), glioblastoma multiforme (GBM), prostate adenocarcinoma (PRAD), esophageal carcinoma (ESCA), and brain lower-grade glioma (LGG). Particularly, increased Siglec-9 expression was strongly correlated with poor prognosis in LGG. Correlation between Siglec-9 expression and tumor stage was also observed in various cancers. In addition, Siglec-9 was positively associated with infiltration of immune cells including neutrophils, dendritic cells (DCs), macrophage, and CD4+ and CD8+ T cells. Moreover, a significant correlation between Siglec-9 and MSI, TMB, MMR, DNMT, immune checkpoint, immune subtype, molecular subtype, and immunomodulators was observed in multiple cancers. Specifically, poor prognostic value and strong correlation to immune cell infiltration were verified with the LGG dataset from the Chinese Glioma Genome Atlas (CGGA). These findings indicated that Siglec-9 can be a novel biomarker and a potential target for cancer immunotherapy.
| S-EPMC8968865 | biostudies-literature
Project description:In recent years, it has become evident that tumor cells have immune escape mechanisms, and immune checkpoint inhibitor therapy (anti-PD-1/PD-L1 antibody) has shown benefit in various cancers. In endometrial tumors with microsatellite-instability (MSI), somatic mutations have the potential to encode ''non-self'' immunogenic antigens, and lymphocytes have been shown to infiltrate the tumor. Therefore, immune checkpoint inhibitor therapy might be effective in endometrial cancers with MSI. Expression of mismatch repair (MMR) proteins (MLH1, PMS2, MSH2, and MSH6), the presence of tumor-infiltrating lymphocytes (CD8+), and PD-1/PD-L1 expression were assessed by immunohistochemistry in 149 patients with endometrial cancer. We examined whether tumors with MSI had an enhanced immune microenvironment and whether MSI could be a predictor of the therapeutic effect of PD-1/PD-L1 immunotherapy in endometrial cancer. Loss of MMR protein expression was identified in 42 (28.2%) of 149 patients (MSI group) with endometrial cancer. There was no significant relationship between MSI status and age (p = 0.193), histological grade (p = 0.097), FIGO stage (p = 0.508), pelvic lymph node metastasis (p = 0.139), or depth of myometrial invasion (p = 0.494). However, the presence of tumor-infiltrating lymphocytes (CD8+) and PD-L1/PD-1 expression were significantly higher in the MSI group compared to the microsatellite-stable group (p = 0.002, p = 0.001, and p = 0.008, respectively). These results suggest that immune checkpoint inhibitors (anti-PD-1/PD-L1 antibody) could be effective in endometrial cancers with MSI. The presence of MSI may be a biomarker for good response to PD-1/PD-L1 immunotherapy in endometrial cancer.
| S-EPMC5814165 | biostudies-literature
Project description:A deep understanding of the tumor microenvironment and the recognition of tumor-infiltrating lymphocytes as a prognostic factor have resulted in major milestones in immunotherapy that have led to therapeutic advances in treating many cancers. Yet, the translation of this knowledge to clinical success for ovarian cancer remains a challenge. The efficacy of immune checkpoint inhibitors as single agents or combined with chemotherapy has been unsatisfactory, leading to the exploration of alternative combination strategies with targeted agents (e.g., poly-ADP-ribose inhibitors (PARP)and angiogenesis inhibitors) and novel immunotherapy approaches. Among the different histological subtypes, clear cell ovarian cancer has shown a higher sensitivity to immunotherapy. A deeper understanding of the mechanism of immune resistance within the context of ovarian cancer and the identification of predictive biomarkers remain central discovery benchmarks to be realized. This will be critical to successfully define the precision use of immune checkpoint inhibitors for the treatment of ovarian cancer.
| S-EPMC10296292 | biostudies-literature
Project description:Multiple myeloma (MM) is related to immune disorders, recent studys have revealed that immunotherapy can greatly benefit MM patients. Immune checkpoints can negatively modulate the immune system and are closely associated with immune escape. Immune checkpoint-related therapy has attracted much attention and research in MM. However, the efficacy of those therapies need further improvements. There need more thoughts about the immune checkpoint to translate their use in clinical work. In our review, we aggregated the currently known immune checkpoints and their corresponding ligands, further more we propose various ways of potential translation applying treatment based on immune checkpoints for MM patients.
| S-EPMC10685608 | biostudies-literature