low-TMB Group Research Articles

Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma.

Tumor mutational burden (TMB) is a valuable prognostic biomarker. This study explored the predictive value of TMB and the potential association between TMB and immune infiltration in diffuse large B-cell lymphoma (DLBCL). We downloaded the gene expression profile, somatic mutation, and clinical data of DLBCL patients from The Cancer Genome Atlas (TCGA) database. We classified the samples into high-and low-TMB groups to identify differentially expressed genes (DEGs). Functional enrichment analyses were performed to determine the biological functions of the DEGs. We utilized the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to estimate the abundance of 22 immune cells, and the significant difference was determined by the Wilcoxon rank-sum test between the high- and low-TMB group. Hub gene had been screened as the prognostic TMB-related immune biomarker by the combination of the Immunology Database and Analysis Portal (ImmPort) database and the univariate Cox analysis from the Gene Expression Omnibus (GEO) database including six DLBCL datasets. Various database applications such as Tumor Immune Estimation Resource (TIMER), CellMiner, konckTF, and Genotype-Tissue Expression (GTEx) verified the functions of the target gene. Wet assay confirmed the target gene expression at RNA and protein levels in DLBCL tissue and cell samples. Single nucleotide polymorphism (SNP) occurred more frequently than insertion and deletion, and C > T was the most common single nucleotide variant (SNV) in DLBCL. Survival analysis showed that the high-TMB group conferred poor survival outcomes. A total of 62 DEGs were obtained, and 13 TMB-related immune genes were identified. Univariate Cox analysis results illustrated that CD1c mutation was associated with lower TMB and manifested a satisfactory clinical prognosis by analysis of large samples from the GEO database. In addition, infiltration levels of immune cells in the high-TMB group were lower. Using the TIMER database, we systematically analyzed that the expression of CD1c was positively correlated with B cells, neutrophils, and dendritic cells and negatively correlated with CD8+ T cells, CD4+ T cells, and macrophages. Drug sensitivity showed a significant positive correlation between CD1c expression level and clinical drug sensitivity from the CellMiner database. CREB1, AHR, and TOX were used to comprehensively explore the regulation of CD1c-related transcription factors and signaling pathways by the KnockTF database. We searched the GETx database to compare the mRNA expression levels of CD1c between DLBCL and normal tissues, and the results suggested a significant difference between them. Moreover, wet experiments were conducted to verify the high expression of CD1c in DLBCL at the RNA and protein levels. Higher TMB correlated with poor survival outcomes and inhibited the immune infiltrates in DLBCL. Our results suggest that CD1c is a TMB-related prognostic biomarker.

Prognostic Value of Tumor Mutational Burden in Follicular Lymphoma Patients Treated with Immunochemotherapy

INTRODUCTION: Follicular lymphoma (FL) is the most prevalent indolent non-Hodgkin lymphoma subtype. It is characterized by frequent relapses, and patients who progress or relapse within 24 months (POD24) of front-line immunochemotherapy (ICT) have a poor outcome. Several prognostic indices have been proposed to identify high-risk patients, but none of them are currently used in clinical practice to guide treatment. Tumor mutational burden (TMB), defined as the number of somatic mutations/megabase (mut/Mb), has been proposed as a biomarker for predicting response to immune checkpoint inhibitors in several types of cancer. Therefore, this study aimed to explore the role of TMB in FL patients treated with frontline ICT. METHODS: The study included a total of 103 patients with FL grade 1-3a treated with frontline ICT. TMB was determined by Next Generation Sequencing (NGS) in 98 diagnostic lymph node biopsies with enough material available, with the Oncomine Tumor Mutational Load Assay (Thermo Fisher). This assay covers 1.65Mb across 409 genes frequently mutated in cancer, allowing an accurate estimation of TMB. Sequencing was performed on the Ion GeneStudio S5 system with >300X mean read depth. Only exonic non-synonymous variants remaining after manual variant refinement to exclude artefacts were considered. In addition, the mutational profile of 56 of the 98 patients was analyzed using a QIAgen custom DNA panel which covered 64 genes frequently mutated in FL. Sequencing was performed using NextSeq (Illumina) with >3000X mean read depth. Variants were analyzed and interpreted for pathogenicity using several databases, and only pathogenic or presumed pathogenic variants (P/PP) were considered. Statistical analysis was performed using SPSS and R. RESULTS: The final cohort included 94 patients, as in 4/98 patients (4%) TMB could not be accurately estimated due to a high frequency of artefacts caused by cytosine deamination. Median age at diagnosis of 61 years (range 24-86), 51% males and 49% females. Patients with advanced disease stage at diagnosis represented 87% of the cohort. Median TMB was 5.08mut/Mb (range 1.69-13.80 mut/Mb), and all cases genetically profiled presented at least one P/PP variant. The number of P/PP mutations correlated with TMB at diagnosis (p=0.004). TMB did not correlate with clinical parameters, such as age at diagnosis (p=0.891), histologic grade (p=0.243), Ann Arbor stage (p=0.200), ECOG (p=0.190), FLIPI (p=0.363), FLIPI2 (p=0.693), or LDH levels (p=0.483). However, lower TMB at diagnosis was associated with the absence of the t(14;18)(q32;q21) translocation (mean 3.93 vs 5.42 mut/Mb, p=0.006). The analysis of the mutational status of the 64 genes frequently mutated in FL revealed that mutations in genes involved in cellular migration ( GNA13, GNAI2) were associated with higher TMB values (4.50 vs 7.56 mut/Mb, p=0.001). An statistically significant association between low TMB and shorter progression-free survival (PFS) (p=0.011) was found when stratifying patients into two groups: high basal TMB (>2.55mut/Mb) and low basal TMB (≤2.55mut/Mb) (Figure 1). 2-year PFS was 54.5% (95%CI: 33.2-89.5%) in low-TMB patients and 84.9% (95%CI: 77.3-93.7%) in high-TMB patients. 5-year PFS was 39.0% (95%CI: 19.7-77.0%) in low-TMB patients and 70.5% (95%CI: 60.0-82.9%) in high-TMB patients. The proportion of POD24 cases was higher in the low-TMB group (46.1% vs 16.9%, p=0.039), none of them being refractory to treatment (7/70 in the high-TMB group). Genetically, the low-TMB group was enriched in patients with mutations affecting genes involved in the mTOR signaling pathway ( ATP6AP1, ATP6AP2, ATP6V1B2, RRAGC) (50.0% vs 8.7%, p=0.006). CONCLUSIONS: FL patients harboring t(14;18) or mutations in genes involved in migration have higher TMB values at diagnosis. Patient stratification based on TMB values allows the identification of a subgroup of FL patients with ≤2.55 mut/Mb with shorter PFS after treatment with frontline ICT. The prognostic usefulness of TMB should also be explored at relapse, in particular in patients receiving novel immunotherapies such as bispecific antibodies and CAR T-cell therapies, that are being approved for relapsed/refractory FL. ACKNOWLEDGMENTS: Work supported by Institut de Salud Carlos III-Federación Española de Enfermedades Raras (ISCIII-FEDER) grant PI19/00034, GLD18/00117, 2017SGR205, PT20/00023, and Xarxa de Banc de Tumors de Catalunya.

Correlation of tumor mutational burden with prognosis and immune infiltration in lung adenocarcinoma.

Tumor mutational burden (TMB) plays an important role in the evaluation of immunotherapy efficacy in lung adenocarcinoma (LUAD). To improve the clinical management of LUAD by investigating the prognostic value of TMB and the relationship between TMB and immune infiltration. TMB scores were calculated from the mutation data of 587 LUAD samples from The Cancer Genome Atlas (TCGA), and patients were divided into low-TMB and high-TMB groups based on the quartiles of the TMB score. Differentially expressed genes (DEGs), immune cell infiltration and survival analysis were compared between the low-TMB and high-TMB groups. We queried the expression of genes in lung cancer tissues through the GEPIA online database and performed experimental validation of the function of aberrant genes expressed in lung cancer tissues. We obtained sample information from TCGA for 587 LUAD patients, and the results of survival analysis for the high- and low- TMB groups suggested that patients in the high-TMB group had lower survival rates than those in the low-TMB group. A total of 756 DEGs were identified in the study, and gene set enrichment analysis (GSEA) showed that DEGs in the low-TMB group were enriched in immune-related pathways. Among the differentially expressed genes obtained, 15 immune-related key genes were screened with the help of ImmPort database, including 5 prognosis-related genes (CD274, PDCD1, CTLA4, LAG3, TIGIT). No difference in the expression of PDCD1, CTLA4, LAG3, TIGIT in lung cancer tissues and differential expression of CD274 in lung cancer tissues. The survival rate of LUAD patients with low TMB was better than that of LUAD patients with high TMB. CD274 expression was down regulated in human LUAD cell lines H1299, PC-9, A549 and SPC-A1, which inhibited malignant progression of A549 cells.

The prognostic value of tumor mutation burden (TMB) and its relationship with immune infiltration in breast cancer patients

ObjectiveAlthough the tumor mutation burden (TMB) was reported as a biomarker for immunotherapy of various cancers, whether it can effectively predict the survival prognosis in breast cancer patients remains unclear. In this study, the prognostic value of TMB and its correlation with immune infiltration were explored by using multigroup studies.MethodsThe somatic mutation data of 986 breast cancer patients were obtained from TCGA database. Breast cancer patients were divided into a low-TMB group and a high-TMB group according to the quartile of TMB scores. The differentially expressed genes (DEGs) were identified by the “limma” R program. The CIBERSORT algorithm was utilized to estimate the immune cell fraction of each sample. The TIMER database was utilized to evaluate the association between CNVs of immune genes and tumor immune cell infiltration and the prognostic value of the immune cells in breast cancer.ResultsIn breast cancer, TP53, PIK3CA, TTN, CDH1 and other genes were the most important mutated genes. Higher survival rate of patients was found in the low-TMB group. Among the top 10 DEGs, three of them belong to the KRT gene family. GSEA enrichment analysis showed that MAPK, Hedgehog, mTOR, TGF-bate and GnRH signaling pathways were enriched in the low-TMB group. The infiltration levels of the most of immune cells were higher in the low-TMB group (P < 0.01). Higher expression of CCL18 and TRGC1 was correlated with poor prognosis. Breast cancer patients with CCL18 copy number variations, especially arm-level gains, showed significantly decreased immune cell infiltration. In the low B cell infiltration group, the survival prognosis of breast cancer patients was poor.ConclusionsTMB is a potential prognosis marker in breast cancer. Immune-related gene CCL18 and TRGC1 are biomarkers of poor prognosis while immune (B cell) infiltration is a biomarker of good prognosis.

The prognostic value of TMB in early-stage non-small cell lung cancer: a systematic review and meta-analysis.

Tumor mutation burden (TMB) has been validated as a predictive biomarker for immunotherapy response and survival in numerous cancer types. Limited data is available on the inherent prognostic role of TMB in early-stage tumors. To evaluate the prognostic role of TMB in early-stage, resected non-small cell lung cancer (NSCLC). Systematic review and meta-analysis of pertinent prospective and retrospective studies. Publication search was performed in PubMed, Embase, Cochrane Library, and Web of Science databases. Based on the level of heterogeneity, a random- or fixed-effects model was used to calculate pooled effects of hazard ratio (HR) for overall survival (OS) and disease-free survival (DFS). The source of heterogeneity was investigated using sensitivity analysis, subgroup analysis, and publication bias assessment. Ten studies comprising 2520 patients were included in this analysis. There was no statistically significant difference in OS (HR, 1.18, 95% CI, 0.70, 1.33; p 0.53, I2 = 80%; phet < 0.0001) and DFS (HR, 1.18, 95% CI, 0.91, 1.52; p = 0.53, I2 = 75%; phet = 0.0001) between the high-TMB and low-TMB group. Subgroup analyses indicated that East Asian ethnicity, and TMB detected using whole exome sequencing, and studies with <100 patients had poor DFS in the high-TMB group. The inherent prognostic role of TMB is limited in early-stage NSCLC. Ethnic differences in mutation burden must be considered while designing future trials on neoadjuvant immunotherapy. Further research in the harmonization and standardization of panel-based TMB is essential for its widespread clinical utility.Registration: CRD42023392846.

Non‑small cell lung cancer carrying PBRM1 mutation suggests an immunologically cold phenotype leading to immunotherapy failure even with high TMB

High tumor mutation load (TMB-H, or TMB ≥ 10) has been approved by the U.S. FDA as a biomarker for pembrolizumab treatment of solid tumors, including non‑small cell lung cancer (NSCLC). Patients with cancer who have immunotherapy-resistant gene mutations cannot achieve clinical benefits even in TMB-H. In this study, we aimed to identify gene mutations associated with immunotherapy resistance and further informed mechanisms in NSCLC. A combined cohort of 350 immune checkpoint blockade-treated patients from Memorial Sloan Kettering Cancer Center (MSKCC) was used to identify genes whose mutations could negatively influence immunotherapy efficacy. An external NSCLC cohort for which profession-free survival (PFS) data were available was used for independent validation. CIBERSORT algorithms were used to characterize tumor immune infiltrating patterns. Immunogenomic features were analysed in the TCGA NSCLC cohort. We observed that PBRM1 mutations independently and negatively influence immunotherapy efficacy. Survival analysis showed that the overall survival (OS) and PFS of patients with PBRM1 mutations (MT) were significantly shorter than the wild type (WT). Moreover, compared with PBRM1-WT/TMB-H group, OS was worse in the PBRM1-MT/TMB-H group. Notably, in patients with TMB-H/PBRM1-MT, it was equal to that in the low-TMB group. The CIBERSORT algorithm further confirmed that the immune infiltration abundance of CD8+ T cells and activated CD4+ memory T was significantly lower in the MT group. Immunogenomic differences were observed in terms of immune signatures, T-cell receptor repertoire, and immune-related genes between WT and MT groups. Nevertheless, we noticed an inverse relationship, given that MT tumors had a higher TMB than the WT group in MSKCC and TCGA cohort. In conclusion, our study revealed that NSCLC with PBRM1 mutation might be an immunologically cold phenotype and exhibited immunotherapy resistance. NSCLC with PBRM1 mutation might be misclassified as immunoresponsive based on TMB.

High Tumor Mutation Burden Is Associated with Poor Clinical Outcome in EGFR-Mutated Lung Adenocarcinomas Treated with Targeted Therapy.

Simple SummaryTumor mutation burden (TMB) represents the mutational load in the tumor cell genome and serves as a surrogate marker for tumor neoantigen production and potential immunogenicity. TMB has been widely explored as a complementary or alternative biomarker for immune checkpoint inhibitors in various malignancies including lung cancer. However, its clinical implication in the targeted-therapy setting is scarcely investigated. This study demonstrates that high TMB is independently associated with poor progression-free and overall survivals, and a low frequency of secondary T790M mutation in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma that are treated with tyrosine kinase inhibitors (TKIs). To the best of our knowledge, this is the first study demonstrating the significant association between the TMB level and resistance pattern after TKI failure.This study aimed to determine the association between TMB and treatment outcomes in patients with epidermal growth factor receptor (EGFR)-mutated lung cancer that were treated with tyrosine kinase inhibitors (TKIs). The TMB was assessed using a 409-gene targeted next-generation sequencing panel. We compared the response rate (RR), progression-free survival (PFS), overall survival (OS), and frequency of secondary T790M mutations among the different TMB groups. The median TMB of the study population (n = 88) was 3.36/megabases. We divided 52 (59%) and 36 (41%) patients into the low and high TMB groups, respectively. A high TMB level was significantly associated with liver metastasis and more advanced stage (all p < 0.05). RR was significantly lower in the high TMB group than that of the low TMB group (50.0% vs. 80.7%, all p = 0.0384). In multivariate analysis, high TMB was independently associated with a shorter PFS (hazard ratio [HR] = 1.80, p = 0.0427) and shorter OS (HR = 2.05, p = 0.0397) than that of the low TMB group. Further, high TMB was independently associated with decreased T790M mutation development. These results suggest that high TMB may be a predictive biomarker for adverse treatment outcomes and represent a patients’ subgroup warranting tailored therapeutic approaches.

Tumor mutational burden and efficacy of chemotherapy in lung cancer.

TMB is one of the potent biomarkers of response to immune checkpoint blockade. The association between TMB and efficacy of chemotherapy in advanced lung cancer has not been comprehensively explored. Ninety lung cancer patients receiving first-line chemotherapy with large panel next-generation sequencing data of pre-treatment tumor tissue were identified. The effect of TMB on PFS of chemotherapy were evaluated in univariate and multivariate analyses. The median TMB level of lung cancer patients enrolled in this study was 9.4 mutations/Mb, with TMB levels in smokers significantly higher than those in non-smokers. All patients were divided into high TMB and low TMB groups with the cutoff of the median TMB. The patients with low TMB had longer PFS of first-line chemotherapy (median PFS 9.77 vs 6.33months, HR = 0.523, 95% CI 0.32-0.852, log-rank P = 0.009). Subgroup analysis showed that PFS of chemotherapy favored low TMB than high TMB among subgroups of male, age<60, NSCLC, adenocarcinoma, stage IV, ECOG PS 0, driver mutation positive, TP53 wild type and patients not receiving bevacizumab. In multivariate analysis, PFS of chemotherapy remained significantly longer in low TMB group (HR = 0.554, p = 0.036). In those patients received immunotherapy upon unsatisfactory chemotherapy, PFS of immunotherapy was much longer in high TMB group (median PFS 32.88 vs 6.62months, HR = 0.2426, 95% CI 0.06-0.977, log-rank P = 0.04). TMB level of tumor tissue is a potent biomarker for efficacy of chemotherapy and immunotherapy in lung cancer. It may provide some clues for the decision of treatment strategy.

Comprehensive analysis of tumor mutation burden and immune microenvironment in prostate cancer.

Prostate adenocarcinoma (PRAD) is a high incidence of malignant tumor of the urinary system and the second most common male cancer in the world. Immune checkpoint inhibitor (ICIS) therapy is becoming a new hope for cancer treatment. To realize the possibility of PRAD patients benefiting from ICIS treatment, we analyzed the mutation spectrum of all PRAD patients, calculated the TMB of each PRAD patient, and divided the patients into high TMB group and low TMB group. Differentially expressed genes (DEGs) between the two groups were identified and path analysis was carried out. The immune cell infiltration of each PRAD patient was evaluated and survival analysis was performed to explore the effect of immune cell infiltration on the prognosis. We found that high TMB was associated with better survival outcomes, with higher TMB scores in young patients, T2 and N0 patients. 28 hub genes were screened by the overlap between 229 DEGs and immune-related genes. T cells CD8 and CD4 memory activated in the high TMB group were higher than those in the low TMB group, while Mast cells resting in the low TMB group were higher than that in the high TMB group. High neutrophil infiltration is associated with poor prognosis in patients with PRAD. Finally, from the immune genes used to construct the prognostic risk model of TMB, it is found that CHP2 and NRG1 are independent prognostic factors of PRAD. This study provides new insights into the immune microenvironment and potential immunotherapy of PRAD.

Low TMB as predictor for additional benefit from neoadjuvant immune checkpoint inhibition in triple-negative breast cancer.

581 Background: It is commonly anticipated that a high tumor mutational burden (TMB) is a predictor of response to immune checkpoint blockade (ICB). We previously showed that triple-negative breast cancer (TNBC) from the GeparNuevo study with high TMB displayed increased response both to neoadjuvant chemo-ICB with durvalumab but also to chemotherapy alone, with no significant interaction with treatment arm (Karn et al. Ann Oncol 2020). In contrast, we also observed that cases with very low TMB more often displayed a pCR after treatment with chemo-ICB than with chemotherapy alone. This may in fact suggest a benefit of ICB to those TNBC with rather low TMB. Methods: We have analyzed the distant disease-free survival (DDFS) of GeparNuevo patients according to TMB and treatment arm (neoadjuvant chemotherapy plus durvalumab or chemotherapy plus placebo). For TMB (mut/Mb) we applied the identical cutoff of the upper tertile as in our previous analysis. Results: The median follow-up of the time-to-event data was 43.7 months. Data of TMB was available in 149 of 174 patients. We found that within the high-TMB tumors (durvalumab: n=27; placebo: n=23), DDFS was similar between both arms of the trial (durvalumab vs. placebo: HR (hazard ratio) 0.95 [95%CI 0.19-4.69], p=0.95). Strikingly however, within the low-TMB group (durvalumab: n=47; placebo: n=52) we observed a significantly better DDFS in the durvalumab-chemotherapy combination arm, in contrast to the arm treated only with chemotherapy (durvalumab vs. placebo: HR 0.23 [95%CI 0.06-0.79], p=0.02; interaction test for TMB and treatment arm p=0.17). The observation was also robust to alternative TMB cutoffs. Similar results were obtained for invasive disease-free survival. Conclusions: Our results show, in contrast to other published data, that patients with early TNBC and low TMB/neoantigen counts may benefit from short-term neoadjuvant durvalumab treatment, while for those with high TMB, durvalumab plus chemotherapy does not improve efficacy over chemotherapy alone.

Identification of a pyroptosis-related prognostic signature in breast cancer

BackgroundThe relationship between pyroptosis and cancer is complex. It is controversial that whether pyroptosis represses or promotes tumor development. This study aimed to explore prognostic molecular characteristics to predict the prognosis of breast cancer (BRCA) based on a comprehensive analysis of pyroptosis-related gene expression data.MethodsRNA-sequcing data of BRCA were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Ominibus (GEO) datasets. First, pyroptosis-related differentially expressed genes (DEGs) between normal and tumor tissues were identified from the TCGA database. Based on the DEGs, 1053 BRCA patients were divided into two clusters. Second, DEGs between the two clusters were used to construct a signature by a least absolute shrinkage and selection operator (LASSO) Cox regression model, and the GEO cohort was used to validate the signature. Various statistical methods were applied to assess this gene signature. Finally, Single-sample gene set enrichment analysis (ssGSEA) was employed to compare the enrichment scores of 16 types of immune cells and 13 immune-related pathways between the low- and high-risk groups. We calculated the tumor mutational burden (TMB) of TCGA cohort and evaluated the correlations between the TMB and riskscores of the TCGA cohort. We also compared the TMB between the low- and high-risk groups.ResultsA total of 39 pyroptosis-related DEGs were identified from the TCGA-breast cancer dataset. A prognostic signature comprising 16 genes in the two clusters of DEGs was developed to divide patients into high-risk and low-risk groups, and its prognostic performance was excellent in two independent patient cohorts. The high-risk group generally had lower levels of immune cell infiltration and lower activity of immune pathway activity than did the low-risk group, and different risk groups revealed different proportions of immune subtypes. The TMB is higher in high-risk group compared with low-risk group. OS of low-TMB group is better than that of high-TMB group.ConclusionA 16-gene signature comprising pyroptosis-related genes was constructed to assess the prognosis of breast cancer patients and its prognostic performance was excellent in two independent patient cohorts. The signature was found closely associated with the tumor immune microenvironment and the potential correlation could provide some clues for further studies. The signature was also correlated with TMB and the mechanisms are still warranted.

Identification of a Gene Prognostic Model of Gastric Cancer Based on Analysis of Tumor Mutation Burden.

Introduction: Gastric cancer is one of the most common cancers. Although some progress has been made in the treatment of gastric cancer with the improvement of surgical methods and the application of immunotherapy, the prognosis of gastric cancer patients is still unsatisfactory. In recent years, there has been increasing evidence that tumor mutational load (TMB) is strongly associated with survival outcomes and response to immunotherapy. Given the variable response of patients to immunotherapy, it is important to investigate clinical significance of TMB and explore appropriate biomarkers of prognosis in patients with gastric cancer (GC).Material and Methods: All data of patients with gastric cancer were obtained from the database of The Cancer Genome Atlas (TCGA). Samples were divided into two groups based on median TMB. Differently expressed genes (DEGs) between the high- and low-TMB groups were identified and further analyzed. We identified TMB-related genes using Lasso, univariate and multivariate Cox regression analysis and validated the survival result of 11 hub genes using Kaplan-Meier Plotter. In addition, “CIBERSORT” package was utilized to estimate the immune infiltration.Results: Single nucleotide polymorphism (SNP), C > T transition were the most common variant type and single nucleotide variant (SNV), respectively. Patients in the high-TMB group had better survival outcomes than those in the low-TMB group. Besides, eleven TMB-related DEGs were utilized to construct a prognostic model that could be an independent risk factor to predict the prognosis of patients with GC. What’s more, the infiltration levels of CD4+ memory-activated T cells, M0 and M1 macrophages were significantly increased in the high-TMB group compared with the low-TMB group.Conclusions: Herein, we found that patients with high TMB had better survival outcomes in GC. In addition, higher TMB might promote immune infiltration, which could provide new ideas for immunotherapy.

Abstract 398: Tumor mutational burden estimated by whole-exome sequencing across multiple cancer types

Abstract Purpose: Tumor mutational burden (TMB) is emerging as a promising biomarker in immune checkpoint inhibitor therapy. Although whole-exome sequencing (WES) is the gold standard to quantify TMB, most TMB measurements in routine diagnostic applications were done by gene panels due to their lower cost and technical accessibility. Therefore, data is lacking for WES derived TMB in several major tumors. However, panel derived TMB can be misleading because research found its correlation with WES derived TMB was compromised when a subset of samples with high TMB values were excluded from the dataset. In this study, we aim to establish the landscape of WES derived TMB in six tumor types in Chinese patients, test the association between WES-TMB and patient survival in immunotherapy, and compare the performance between WES-TMB and panel-TMB. Methods: We recruited 357 patients who had received immune checkpoint inhibition (ICI) therapy, representing six types of cancers (see Results for the list). We analyzed the tumors and patient-matched blood samples using WES and called somatic mutations of the patients. We defined our WES-TMB as the total number of somatic nonsynonymous mutations in the tumor exome. In each of the tumor types tested, we assigned the patients with the upper tertile TMB values as the high-TMB group and the remaining two thirds of patients as the low-TMB group. Results: The distribution of WES-TMB medians are highly variable among different tumors, ranging from 2.71 (cholangiocarcinoma), 2.97 (nervous system tumor), 3.69 (gastric cancer), 4.31 (hepatocellular carcinoma), 4.64 (colorectal cancer), to 5.67 (lung cancer) mutations/Mb. This trend is almost the same as other TMB studies done with panel sequencing, despite the values derived from WES tend to be lower. Additionally, TMB was significantly associated with overall survival in colorectal patients receiving ICI. The high-TMB group also showed better overall survival in hepatocellular carcinoma and gastric cancer. Conclusion: TMBs derived from panel are overestimated compared to that derived from WES although that doesn't affect the rank of TMBs in different cancer types. It is rational to define TMB subgroups by percentile within different cancer types. These results support TMB as a biomarker to predict clinical benefit to ICI therapy in colorectal cancer. Citation Format: Fei Xu, Jinwang Wei, Xiaochen Zhang, Jun Liu, Chun Dai, Guan Wang, Qiang Xu. Tumor mutational burden estimated by whole-exome sequencing across multiple cancer types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 398.

Clinical and utilization outcomes associated with tumor mutational burden in a real-world pan-tumor population.

Aim & methods: This real-world study examined the association of tumor mutational burden (TMB) with clinical and healthcare utilization in adults diagnosed with advanced solid tumor 1 January2015- 31 January2019. Results: There were 170 patients in low-TMB group (TMB<10mut/Mb) and 32 in high-TMB group (TMB ≥10mut/Mb). Median overall survival was 18.8 (95% CI: 17.3-28.8) and 15.9months (95% CI: 11.3-18.0) whereas median progression-free survival was 9.9 (95% CI: 8.6-11.4) and 7.8months (95% CI: 3.8-12.5) for the low- and high-TMB groups, respectively. Hospitalization (49.4 vs 37.5%), emergency visit (25.3 vs 21.9%), and median overall cost of care (US$135,403 vs 87,570) were all lower in low-TMB group. Conclusion: Despite the limited sample, these data provide a historical perspective for examining real-world outcomes associated with TMB.

Significance of tumor mutation burden and immune infiltration in thymic epithelial tumors.

BackgroundThymic epithelial tumors (TETs) are relatively rare malignant thoracic tumors. Tumor mutation burden (TMB) and immune infiltration play important roles in tumorigenesis.MethodsResearch data was obtained using the Cancer Genome Atlas (TCGA) database to evaluate the landscape of tumor mutations, related factors, and relationship of prognosis. The CIBERSORT algorithm was used to evaluate immune cell infiltration in TETs and its relationship with TMB. Immune‐related differentially expressed genes (irDEGs) were identified. Hub irDEGs independently related to prognosis were analyzed using univariate and multivariate Cox proportional hazard models. A survival signature was constructed from hub irDEGs.ResultsA total of 122 patients were included in this study. GTF2I was the most common gene mutation. Higher TMB was significantly associated with the later stage, more advanced pathological type, and older age. The overall survival (OS) of patients in the low‐TMB group was significantly better. There was no significant correlation between TMB levels and PD‐L1 expression. Enrichment analysis showed that DEGs were mainly involved in the P13K–Akt signaling pathway. There were significant differences in macrophage and other types of immune cell infiltration between the high‐ and low‐TMB groups. CCR5, FASLG, and CD79A independently relating to prognosis were screened from 391 irDEGs. The low‐risk group had a significantly better prognosis than the high‐risk group based on the signature, which has a good predictive effect on OS.ConclusionsIn this study, TETs patients with high TMB had a significantly poor prognosis and an immune‐related gene signature was found to effectively evaluate the long‐term prognosis.

Gene expression and immune infiltration in melanoma patients with different mutation burden

BackgroundImmunotherapy is a vital component in cancer treatment. However, due to the complex genetic bases of cancer, a clear prediction index for efficacy has not been established. Tumor mutation burden (TMB) is one of the essential factors that affect immunotherapeutic efficacies, but it has not been determined whether the mutation is associated with the survival of Skin Cutaneous Melanoma (SKCM) patients. This study aimed at evaluating the correlation between TMB and immune infiltration.MethodsSomatic mutation profiles (n = 467), transcriptome data (n = 471), and their clinical information (n = 447) of all SKCM samples were downloaded from The Cancer Genome Atlas (TCGA) database. For each sample, TMB was calculated as the number of variants per megabase. Based on K-M survival analysis, they were allocated into the high-TMB and low-TMB groups (the optimal cutoff was determined by the ‘surv_cutpoint’ algorithm of survival R package). Then, Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) were performed, with immune-associated biological pathways found to be significantly enriched in the low-TMB group. Therefore, immune genes that were differentially expressed between the two groups were evaluated in Cox regression to determine their prognostic values, and a four-gene TMB immune prognostic model (TMB-IP) was constructed.ResultsElevated TMB levels were associated with better survival outcomes in SKCM patients. Based on the cutoff value in OS analysis, they were divided into high-TMB and low-TMB groups. GSEA revealed that the low-TMB group was associated with immunity while intersection analysis revealed that there were 38 differentially expressed immune-related genes between the two groups. Four TMB-associated immune genes were used to construct a TMB-IP model. The AUC of the ROC curve of this model reached a maximum of 0.75 (95%CI, 0.66–0.85) for OS outcomes. Validation in each clinical subgroup confirmed the efficacy of the model to distinguish between high and low TMB-IP score patients.ConclusionsIn SKCM patients, low TMB was associated with worse survival outcomes and enriched immune-associated pathways. The four TMB-associated immune genes model can effectively distinguish between high and low-risk patients.

Comprehensive analysis of tumour mutational burden and its clinical significance in prostate cancer

BackgroundThe tumorigenesis of prostate cancer involves genetic mutations. Tumour mutational burden (TMB) is an emerging biomarker for predicting the efficacy of immunotherapy.ResultsSingle-nucleotide polymorphisms were the most common variant type, and C>T transversion was the most commonly presented type of single-nucleotide variant. The high-TMB group had lower overall survival (OS) than the low-TMB group. TMB was associated with age, T stage and N stage. Functional enrichment analysis of differentially expressed genes (DEGs) showed that they are involved in pathways related to the terms spindle, chromosomal region, nuclear division, chromosome segregation, cell cycle, oocyte meiosis and other terms associated with DNA mutation and cell proliferation. Six hub genes, PLK1, KIF2C, MELK, EXO1, CEP55 and CDK1, were identified. All the genes were associated with disease-free survival, and CEP55 and CDK1 were associated with OS.ConclusionsThe present study provides a comprehensive analysis of the significance of TMB and DEGs and infiltrating immune cells related to TMB, which provides helpful information for exploring the significance of TMB in prostate cancer.

Identification of tumor mutation burden-related hub genes and the underlying mechanism in melanoma.

Background: Tumor mutation burden (TMB) has emerged as an important predictive factor for drug resistance in cancers; however, the specific mechanism underlying TMB function in melanoma remains elusive.Methods: Data on somatic mutations, RNA sequencing (RNA-seq), miRNA sequencing (miRNA-seq), and clinical characteristics for 472 melanoma patients were extracted from the TCGA cohort. RNA-seq data of melanoma cell lines were obtained from the Cancer Cell Line Encyclopedia, and sensitivity of cell lines to therapeutic agents is available in the Cancer Therapeutics Response Portal. TMB was calculated based on somatic mutation data. Differentially expressed gene analysis, weighted gene co-expression network analysis, protein-protein interaction networks, Minimal Common Oncology Data Elements, and survival analysis were leveraged to determine TMB-related hub genes. Competing endogenous RNA (ceRNA) networks were constructed to explore the molecular mechanisms underlying hub gene function. The influence of key genes on drug sensitivity was analyzed to investigate their clinical significance.Results: Elevated TMB levels were significantly correlated with improved survival outcomes. In addition, six tumor-infiltrating immune cells, including naive B cells, regulatory T cells, memory resting CD4 T cells, memory B cells, activated mast cells, and resting NK cells, were significantly overexpressed in the low-TMB group relative to the high-TMB group. Furthermore, we identified FLNC, NEXN, and TNNT3 as TMB-related hub genes, and constructed their ceRNA networks, including five miRNAs (has-miR-590-3p, has-miR-374b-5p, has-miR-3127-5p, has-miR-1913, and has-miR-1291) and 31 lncRNAs (FAM66C, MIAT, NR2F2AS1, etc.). Finally, we observed that TMB-related genes were associated with distinct therapeutic responses to AKT/mTOR pathway inhibitors.Conclusions: We identified three TMB-associated key genes, established their ceRNA networks, and investigated their influence on therapeutic responses, which could provide insights into future precision medicine.

An miRNA signature associated with tumor mutation burden in endometrial cancer.

Tumor mutation burden (TMB) is an essential biomarker to predict immunotherapy response. TMB measurement was mainly evaluated by whole-exome sequencing (WES), which was costly and difficult to be widely applied. In the present study, we aimed to establish and validate a miRNA signature to predict TMB level in endometrial cancer using The Cancer Genome Atlas (TCGA) database. MiRNA expression and somatic mutation profiles of uterine corpus endometrial carcinoma (UCEC) were downloaded from TCGA database. Total 518 patients with UCEC were randomly classified into training set (n=311) and validation set (n=207). Thirty-five differentially expressed miRNAs between high-TMB and low-TMB group were identified in training set. Least absolute shrinkage and selection operator (LASSO) method was performed to select out 26 miRNAs to establish the optimal signature. The accuracy of the miRNA signature for predicting TMB level was 0.833 for training set, 0.749 for validation set and 0.799 for total set. Moreover, the miRNA signature had significant correlation with immune checkpoints related genes (PD-1, PD-L1, CTLA-4) and mismatch repair related genes (BRCA1, BRCA2, MLH1, MSH6) expression. In conclusion, this miRNA signature could predict TMB level in endometrial cancer and might have some merits in providing guidance for immunotherapy in endometrial cancer.

Association between tumor mutation burden and immune infiltration in ovarian cancer

BackgroundIt remains unclear whether the tumor mutation burden (TMB) or a TMB-related signature could be prognostic indicators in ovarian cancer (OC), as potential correlations with immune infiltrates and immunotherapy responsiveness remains poorly understood. MethodsData of 941 OC patients were collected from three datasets, including 587, 260, and 94 patients from The Cancer Genome Atlas (TCGA), GSE32062, and the International Cancer Genome Consortium (ICGC), respectively. TMB was calculated and correlations with clinical outcomes, immune infiltrates, and immunotherapy responsiveness were investigated in the TCGA OC cohort. Weighted gene co-expression network analysis was performed to identify TMB-related genes. A TMB-related signature was constructed and validated. ResultsHigher TMB was associated with better survival in the TCGA and ICGC OC cohorts. The high-TMB group had higher CD8+ T-cell infiltration than the low-TMB group. No significant correlation was found between TMB and immunotherapy response. Furthermore, we selected 8 prognostic and TMB-related genes to construct a TMB-related signature that could distinguish between the high- and low-risk patients; its predictive power was validated in the GSE32062 and ICGC datasets. SubMap analysis suggested that patients in the low-risk group might have a better response to anti-PD1 therapy. ConclusionsWe examined the prognostic value of TMB and its potential association with immune cell infiltration and immunotherapy responsiveness in OC. A TMB-related prognostic signature consisting of 8 genes was developed and verified, which might be a promising prognostic signature for the prognosis of OC patients.