High Tumor Mutation Burden Group Research Articles

Plasma versus tissue tumor mutational burden as biomarkers of durvalumab plus tremelimumab response in patients with metastatic colorectal cancer in the CO.26 trial.

Tissue derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset on which this was validated lacked colorectal cancers (CRCs), and there is limited evidence for immunotherapy benefit in CRC using this threshold. CO.26 was a randomized phase II study of 180 patients comparing durvalumab and tremelimumab (D+T, n=119 patients) versus best supportive care (BSC, n=61 patients). ctDNA sequencing was available for 168 patients (n=118 D+T, n=50), of which 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on overall survival were determined using a minimal p-value approach. This report includes the final overall survival analysis. Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D+T compared to BSC in microsatellite stable (MSS) metastatic CRC (HR 0.71 [95% CI:0.28-1.80], p=0.47). No tissue TMB threshold could identify a high TMB group that benefited from ICI. In contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D+T (HR=0.34 [95%CI:0.13-0.85], p=0.022), as was clonal pTMB ≥10.6 mutations/Mb (HR=0.10 [95%CI:0.014-0.79], p=0.029) and subclonal pTMB ≥25.9/Mb (HR=0.20 [95% CI:0.061-0.69], p=0.010). Higher pTMB was associated with length of time on cytotoxic agents (p=0.021) and prior anti-EGFR exposure (p=2.44x10-06). pTMB derived from either clonal or subclonal mutations may identify a group more likely to benefit from immunotherapy, though validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.

A novel sub-regional radiomics model to predict immunotherapy response in non-small cell lung carcinoma.

Identifying precise biomarkers of immunotherapy response for non-small cell lung carcinoma (NSCLC) before treatment is challenging. This study aimed to construct and investigate the potential performance of a sub-regional radiomics model (SRRM) as a novel tumor biomarker in predicting the response of patients with NSCLC treated with immune checkpoint inhibitors, and test whether its predictive performance is superior to that of conventional radiomics, tumor mutational burden (TMB) score and programmed death ligand-1 (PD-L1) expression. We categorized 264 patients from retrospective databases of two centers into training (n = 159) and validation (n = 105) cohorts. Radiomic features were extracted from three sub-regions of the tumor region of interest using the K-means method. We extracted 1,896 features from each sub-region, resulting in 5688 features per sample. The least absolute shrinkage and selection operator regression method was used to select sub-regional radiomic features. The SRRM was constructed and validated using the support vector machine algorithm. We used next-generation sequencing to classify patients from the two cohorts into high TMB (≥ 10 muts/Mb) and low TMB (< 10 muts/Mb) groups; immunohistochemistry was performed to assess PD-L1 expression in formalin-fixed, paraffin-embedded tumor sections, with high expression defined as ≥ 50% of tumor cells being positive. Associations between the SRRM and progression-free survival (PFS) and variant genes were assessed. Eleven sub-regional radiomic features were employed to develop the SRRM. The areas under the receiver operating characteristic curve (AUCs) of the proposed SRRM were 0.90 (95% confidence interval [CI] 0.84-0.96) and 0.86 (95% CI 0.76-0.95) in the training and validation cohorts, respectively. The SRRM (low vs. high; cutoff value = 0.936) was significantly associated with PFS in the training (hazard ratio [HR] = 0.35 [0.24-0.50], P < 0.001) and validation (HR = 0.42 [0.26-0.67], P = 0.001) cohorts. A significant correlation between the SRRM and three variant genes (H3C4, PAX5, and EGFR) was observed. In the validation cohort, the SRRM demonstrated a higher AUC (0.86, P < 0.001) than that for PD-L1 expression (0.66, P = 0.034) and TMB score (0.54, P = 0.552). The SRRM had better predictive performance and was superior to conventional radiomics, PD-L1 expression, and TMB score. The SRRM effectively stratified the progression-free survival (PFS) risk among patients with NSCLC receiving immunotherapy.

Perspectives for next generation sequencing in patients with follicular lymphoma

Aim. To study the prognostic significance of gene mutations and intracellular signaling pathways involved in lymphomagenesis in patients with follicular lymphoma using next generation sequencing (NGS).Materials and methods. The prospective study included 26 patients with a median age of 51.5 years. Mutational screening was performed for cohort using custom NGS Panel of 118 genes. Gene set enrichment analysis (GSEA) was performed using Metascape. The data was analyzed in SPSS Statistics 26 and R 4.2.2.Results. The highest mutation frequency was noted in the genes: KMT2C – 50 %, KMT2D – 50 %, CREBBP – 31 %, NOTCH2 – 31 %, GNAS – 23 %. Missense mutations occurred with a frequency of 84.3 %. ARID1A gene mutation is an unfavorable prognostic factor according to progressive-free (p = 0.014) and event-free (p = 0.029) survival analysis. Tumor mutation burden (TMB) was defined as the number of mutations per megabase (Mb) of the coding sequence, the median TMB was 5.0 (3.3–8.3) mutations/Mb. The TMB threshold of 6 mutations/Mb divided patients into groups with high (44 %) and low (56 %) TMB. In the high TMB group, 2-year event-free survival was 27.3 % (95 % confidence interval 6.0–61.0), which was significantly lower than in low TMB group – 72.7 % (95 % confidence interval 41.9–91.6; p = 0.037). The most enriched cellular pathways according to GSEA results were regulation of cell activation (–log10(q-value) = 6.357), chromatin remodeling (–log10(q-value) = 5.707), histone modification (–log10(q-value) = 4.569). We have also demonstrated other possibilities of GSEA using follicular lymphoma as an example.Conclusion. TMB is a significant prognostic factor in patients with follicular lymphoma. We have shown that mutations in the MYC, CREBBP, EZH2, KMT2D genes lead to dysregulation in several intracellular processes, mediating complex molecular changes. The most enriched intracellular pathways in follicular lymphoma are those of chromatin remodeling, regulation of cell activation and histone modification.

Predictive value of tumor mutational burden for PD-1/PD-L1 inhibitors in NSCLC: A meta-analysis.

To investigate the association between tumor mutational burden (TMB) and the therapeutic effect of Programmed Death 1/Programmed Death Ligand 1 inhibitors in non-small cell lung cancer. Four electronic databases, PubMed, Embase, Web of Science, and Cochrane Library, were searched on May 10, 2023, and no time limitation was applied. Analyses were performed using STATA17.0. We assessed the methodological quality of each randomized controlled trial using the Newcastle-Ottawa scale. After exhaustive database search and rigorous screening, 10 studies were included in the meta-analysis. Our findings indicate that high TMB significantly improves progression-free survival but reduces overall response rate. The overall survival was not significantly different between the high and low TMB groups. No significant publication bias was observed. High TMB serves as a potential predictive biomarker for improved progression-free survival and reduced overall response rate in patients with non-small cell lung cancer treated with programmed death 1/programmed death ligand 1 inhibitors. However, its predictive value in overall survival requires further investigation.

Screening and validation of potential markers associated with uterine corpus endometrial carcinoma and polycystic ovary syndrome based on bioinformatics methods

Background: Endometrial cancer (UCEC) is a commonly occurring tumor in females, and polycystic ovary syndrome (PCOS) is closely related to UCEC, but the molecular mechanisms remain unclear. This article aims to explore potential molecular mechanisms in UCEC and PCOS, as well as identify prognostic genes for UCEC.Methods: Bioinformatics methods were employed to screen for DEGs in UCEC and PCOS. The shared DEGs were analyzed by constructing a protein-protein interaction (PPI) network using the String database and Cytoscape software. The enrichment analysis was performed using Metascape. The shared DEGs associated with the prognosis of UCEC were identified through univariate and lasso Cox regression methods. A multivariate Cox regression model was constructed and internally validated. The expression and test efficiency of the key prognostic genes were verified using external datasets for UCEC and PCOS. Furthermore, the Gepia database was utilized to analyze the expression of key prognostic genes and their correlation with the disease-free survival (RFS) of UCEC. Tumor mutation burden (TMB), immune infiltration, and the correlation of immune cells were assessed for the prognostic genes of UCEC.Results: There were 151 shared DEGs identified between UCEC and PCOS through bioinformatics screening. These shared DEGs were primarily enriched in leukocyte activation. Following model construction and verification, nine genes were determined to be prognostic for UCEC from the shared DEGs. Among them, TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 were confirmed as prognostic genes in UCEC through external validation. Additionally, RTN1 was identified as a key gene in both UCEC and PCOS. Gepia analysis revealed that higher expression of RTN1 was associated with RFS in UCEC. Immune infiltration analysis of the shared DEGs demonstrated significant differences in the expression of various immune cells between UCEC high and low TMB groups. The seven key prognostic genes in UCEC exhibited regulatory relationships with immune cells.Conclusion: This study identified TSPYL5, KCNJ15, RTN1, HMOX1, DCAF12L1, VNN2, and ANXA1 as the key prognostic DEGs of UCEC. These genes are associated with UCEC survival, TMB, immune cell infiltration, and immune cell regulation. Among them, RTN1 may serve as a potential biomarker for both UCEC and PCOS.

Pathway enrichment analysis in tumors with high mutation burdens and interferon-γ signature expression: A pancancer analysis.

3138 Background: Tumor mutation burden (TMB) correlates with immunotherapy response, but outcomes still vary in high TMB cancers, and many high TMB tumors lack T cell infiltration. Here, we assessed gene expression signatures of high TMB, including both inflamed and non-inflamed tumors (defined by interferon-γ [IFN-γ] gene signatures). Methods: Gene set enrichment analysis (GSEA) was assessed from RNA-sequencing data in tumors in TCGA. TMB and IFN-γ signature score were assessed by previously published methods. We performed GSEA on high vs low TMB tumors, and further stratified by high vs low IFN-γ signature expression within high TMB tumors. We validated results in Tempus RNA-sequencing data from 264 patients at Vanderbilt. Results: 4020 TCGA cases in non-small cell lung, melanoma, bladder, head and neck, kidney, and colorectal cancer were included. Major signatures upregulated in the high TMB group included cell cycle signaling, nuclear protein/mRNA export, cholesterol biosynthetics, and ubiquitin signaling. High TMB/high IFN-γ signature tumors were enriched in immune-related pathways (neutrophil and monocyte chemotaxis, T cell activation and proliferation, and interleukin-1 secretion), and non-immune pathways including cAMP metabolic process and phosphatidylinositol signaling. High TMB/low IFN-γ signature tumors had enriched pathways in nonsense mediated decay, electron transport chain/oxidative phosphorylation, and mitochondrial translational disassembly. 264 tumors from Vanderbilt were used for validation; pathways including cholesterol biosynthetics also correlated with immunotherapy response. Conclusions: High TMB tumors were enriched in pathways such as ubiquitin signaling, which could regulate immune cell function in antitumor immunity. Within high TMB cancers, tumors with higher IFN-γ signatures have enriched immune-related, and metabolic pathways, which could suggest novel therapeutic targets to make high TMB/ low IFN-γ tumors more immunogenic.

Construction and validation of a tumor mutational burden and immune-related prognostic model for predicting the prognosis of patients with lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is a highly malignant tumor with an extremely poor prognosis. Immune checkpoint inhibitors (ICIs) improve survival in some patients with LUSC. Tumor mutation burden (TMB) is a useful biomarker to predict the efficacy of ICIs. However, predictive and prognostic factors related to TMB in LUSC remain elusive. This study aimed to find effective biomarkers based on TMB and immune response and establish a prognostic model of LUSC. We downloaded Mutation Annotation Format (MAF) files from The Cancer Genome Atlas (TCGA) database and identified immune-related differentially expressed genes (DEGs) between high- and low-TMB groups. The prognostic model was established using cox regression. The primary outcome was overall survival (OS). Receiver operating characteristic (ROC) curves and calibration curves were used to verify the accuracy of the model. GSE37745 acted as external validation set. The expression and prognosis of hub genes as well as their correlation with immune cells and somatic copy number variation (sCNA) were analyzed. The TMB of patients with LUSC was correlated with prognosis and stage. High TMB group had higher survival rate (P<0.001). Five TMB-related hub immune genes (TINAGL1, FGFR2, CTSE, SFTPA1, and IGHV7-81) were identified and the prognostic model was constructed. The survival time of high-risk group was significantly shorter than that of low-risk group (P<0.001). The validation results of the model were quite stable in different data sets, and the area under curve (AUC) of training set and validation set were 0.658 and 0.644, respectively. Calibration chart, risk curve, and nomogram revealed that the prognostic model was reliable in predicting the prognostic risk of LUSC, and the risk score of the model could be used as an independent prognostic factor for LUSC patients (P<0.001). Our results show that high TMB is associated with poor prognosis in patients with LUSC. The prognostic model related to TMB and immunity can effectively predict the prognosis of LUSC, and risk score is one of the independent prognostic factors of LUSC. However, this study still has some limitations, which need to be further verified in large-scale and prospective studies.

Construction of a pyroptosis-related lncRNAs signature for predicting prognosis and immunotherapy response in glioma.

Recent studies have proved that pyroptosis-related long non-coding RNAs (PRlncRNAs) are closely linked to tumor progression, prognosis, and immunity. Here, we systematically evaluated the correlation of PRlncRNAs with glioma prognosis. This study included 3 glioma cohorts (The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gravendeel). Through Pearson correlation analysis, PRlncRNAs were screened from these 3 cohorts. Univariate Cox regression analysis was then carried out to determine the prognostic PRlncRNAs. A pyroptosis-related lncRNAs signature (PRLS) was then built by least absolute shrinkage and selection operator and multivariate Cox analyses. We systematically evaluated the correlation of the PRLS with the prognosis, immune features, and tumor mutation burden in glioma. A total of 14 prognostic PRlncRNAs overlapped in all cohorts and were selected as candidate lncRNAs. Based on The Cancer Genome Atlas cohort, a PRLS containing 7 PRlncRNAs was built. In all cohorts, the PRLS was proved to be a good predictor of glioma prognosis, with a higher risk score related to a poorer prognosis. We observed obvious differences in the immune microenvironment, immune cell infiltration level, and immune checkpoint expression in low- and high-risk subgroups. Compared with low-risk cases, high-risk cases had lower Tumor Immune Dysfunction and Exclusion scores and greater tumor mutation burden, indicating that high-risk cases can be more sensitive to immunotherapy. A nomogram combining PRLS and clinical parameters was constructed, which showed more robust and accurate predictive power. In conclusion, the PRLS is a potentially useful indicator for predicting prognosis and response to immunotherapy in glioma. Our findings may provide a useful insight into clinically individualized treatment strategies for patients.

Activated Mast Cells Combined with NRF2 Predict Prognosis for Esophageal Cancer.

Esophageal cancer (EC) had the sixth-highest mortality rate of all cancers due to its poor prognosis. Immune cells and mutation genes influenced the prognosis of EC, but their combined effect on predicting EC prognosis was unknown. In this study, we comprehensively analyzed the immune cell infiltration (ICI) and mutation genes and their combined effects for predicting prognosis in EC. The CIBERSORT and ESTIMATE algorithms were used to analyse the ICI scape based on the TCGA and GEO databases. EC tissues and pathologic sections from Huai'an, China, were used to verify the key immune cells and mutation genes and their interactions. Stromal/immune score patterns and ICI/gene had no statistical significance in overall survival (OS) (p > 0.05). The combination of ICI and tumor mutation burden (TMB) showed that the high TMB and high ICI score group had the shortest OS (p = 0.004). We recognized that the key mutation gene NRF2 was significantly different in the high/low ICI score subgroups (p = 0.002) and positivity with mast cells (MCs) (p < 0.05). Through experimental validation, we found that the MCs and activated mast cells (AC-MCs) were more infiltration in stage II/III (p = 0.032; p = 0.013) of EC patients and that NRF2 expression was upregulated in EC (p = 0.045). AC-MCs combined with NRF2 had a poor prognosis, according to survival analysis (p = 0.056) and interactive analysis (p = 0.032). We presume that NRF2 combined with AC-MCs could be a marker to predict prognosis and could influence immunotherapy through regulating PD-L1 in the EC.

The prognostic role of tumor mutation burden on survival of breast cancer: a systematic review and meta-analysis

BackgroundAs a potential genetic biomarker, tumor mutation burden (TMB) has made progress in numerous tumors. There are limited data regarding TMB and its prognostic role is controversial in breast cancer. This systematic review and meta-analysis were conducted to assess the prognostic value of TMB on survival of breast cancer.MethodsThe databases PubMed, Embase, Web of Science, and Cochrane Library were searched for articles published through May 31, 2022. Moreover, effective data were extracted from included studies and calculated pooled effects of hazard ratio (HR) for overall survival (OS) and progression-free survival (PFS) by STATA 16.0. Heterogeneity was conducted by the I2 statistic and p-value. Using publication bias evaluation, sensitivity analysis, and subgroup analysis, the origin of heterogeneity was further investigated.ResultsThey were up to 1,722 patients collected from sixteen cohorts for this analysis. The pooled effects of HR for both OS (HR: 1.14, 95% CI: 0.83,1.58, p > 0.01) and PFS (HR: 0.96, 95% CI: 0.53,1.71, p > 0.01) indicated no statistically significant difference in the high TMB and low TMB group. In immune checkpoint inhibitors (ICIs) subgroup, high TMB patients demonstrated benefit of OS (HR: 0.72, 95% CI: 0.59,0.87, p = 0.001) and PFS (HR: 0.52, 95% CI: 0.35,0.77, p < 0.001), whereas difference was not statistically significant in the non-ICIs subgroup (OS, HR:1.76, 95% CI: 0.97,3.20, p = 0.062; PFS, HR:2.31, 95% CI: 0.89,5.97, p = 0.086). In addition, sensitivity analysis revealed that the pooled effects were stable. The funnel plot and Begg's test suggested the absence of publication bias.ConclusionMeta-analysis revealed that the prognostic relevance of TMB in breast cancer is limited in scope. High TMB may be associated with longer survival only in ICIs-based treatment, but the association is not evident in non-ICIs-based treatment.Trial registration[https://www.crd.york.ac.uk/PROSPERO], Prospective Register of Systematic Reviews (PROSPERO), identifier: CRD42022342488.

Comparative Analysis of Mutation Status and Immune Landscape for Squamous Cell Carcinomas at Different Anatomical sites.

ObjectiveIt has been controversial whether tumor mutation burden (TMB) affects the prognosis and the efficacy of immunotherapy in different tumor types. We provided a comprehensive analysis of mutation status and immune landscape of squamous cell carcinomas (SCCs) from four sites in order to investigate the relationship of TMB with prognosis and immune cell infiltration in different SCCs.MethodsThe transcriptome profiles and somatic mutation data of SCCs downloaded from the Cancer Genome Atlas (the Cancer Genome Atlas) database were analyzed and visualized. Then, TMB was calculated to analyze its correlations with prognosis and clinical features. Differentially expressed genes (DEGs) between the high and low TMB groups were screened for functional enrichment analysis. CIBERSORT algorithm was used to compare differences of immune cell infiltration between two groups in different SCCs. In addition, immune DEGs associated with prognosis were identified and risk prediction model was constructed via Cox regression analysis.ResultsMissense mutation was the most dominant mutation type in SCCs. The difference was that the top10 mutated genes varied widely among different SCCs. High TMB group had better prognosis in lung squamous cell carcinoma (LUSC) and cervical squamous cell carcinoma (CESC), while the result was reverse in head and neck squamous cell carcinoma (HNSCC) and esophageal squamous cell carcinoma (ESCC). In addition, patients with older age, smoking history, earlier pathological stage and no lymphatic invasion had higher TMB. The identified DEGs were mainly enriched in the regulation of immune system, muscular system and the activity of epidermal cells. The proportions of CD8+T cells, CD4+ memory T cells, follicular helper T cells, macrophages were distinct between two groups. The prognosis-related hub genes (CHGB, INHBA, LCN1 and VEGFC) screened were associated with poor prognosis.ConclusionThis study reveals the mutation status and immune cell infiltration of SCCs at different anatomical sites. TMB is closely related to the prognosis of SCCs, and its effects on prognosis are diverse in different SCCs, which might result from the situation of immune cell infiltration. These findings contribute to the exploration of biomarkers for predicting the efficacy of immunotherapy in SCCs and providing innovative insights for accurate application of immunotherapy.

Tumor mutational burden (TMB) in immune checkpoint inhibitor (ICI)-naïve and -experienced patients with metastatic melanoma treated with lifileucel, a tumor-infiltrating lymphocyte (TIL) cell therapy.

9524 Background: Cutaneous melanoma is characterized by high TMB, which is associated with increased tumor-specific neoantigen expression (Schumacher Science 2015) and an increased response rate to ICI (Yarchoan NEJM 2019). The TMB in tumors that recur/progress after ICI is not well defined. Lifileucel is a one-time, autologous TIL cell therapy under investigation for treatment of patients (pts) with advanced melanoma. We conducted a matched case-control study of prospectively enrolled pts with advanced melanoma treated with lifileucel in the ICI-naïve (IOV-COM-202 trial, Cohort 1A [C1A]) and post-ICI (C-144-01 trial, Cohort 2 [C2]) setting to investigate the potential association between prior ICI therapy, TMB, and response to lifileucel. Methods: All pts had unresectable or metastatic melanoma. Available cases from C1A (ICI-naïve pts receiving lifileucel + pembrolizumab [pembro]) were matched to controls from C2 (pts receiving lifileucel alone after progression on anti–PD-1/PD-L1 therapy); 3 controls per case were matched at least for BRAF status and disease stage at study entry, and if possible, for anatomic site of tumor harvest. Lifileucel regimen was similar in C1A and C2. In C1A, 1 dose of pembro was given after tumor harvest and before nonmyeloablative lymphodepletion and resumed after lifileucel per standard treatment, for up to 2 y. Objective response rate (ORR) was assessed by investigators per RECIST v1.1. TMB of the resected tumor was measured using the ImmunoID NeXT (C1A) or PGDx elio (C2) platform; a validated conversion factor was used to compare TMB between platforms (Vega Ann Oncol 2021). High TMB was defined as ≥10 mut/MB. Results: Seven pts in C1A and 21 in C2 were included in the case-control study and had ORR of 71.4% and 38.1%, respectively. The percentage of pts with high TMB was 57.1% in C1A and 19.0% in C2 ( P = 0.1). ORR in the low and high TMB groups was 66.7% and 75.0%, respectively, in C1A and 41.1% and 25.0% in C2; 60% of responders in C1A and 12.5% in C2 had high TMB. In logistic regression analysis adjusted for cohort, TMB was not associated with response to lifileucel (odds ratio, 1.0; 95% CI, 0.9–1.1; P = 0.8). Data on tumor mutations and neoantigens, T-cell receptor repertoire, and tumor microenvironment profile will be presented. Conclusions: Our preliminary data indicate that the efficacy (ORR) of lifileucel may be independent of TMB, regardless of treatment setting, consistent with its proposed immune checkpoint pathway-independent mechanism of action. The percentage of patients with high TMB tended to be lower in tumors with prior ICI exposure than in those that were ICI-naïve. Clinical trial information: NCT03645928; NCT02360579.

Predicting Differences in Treatment Response and Survival Time of Lung Adenocarcinoma Patients Based on a Prognostic Risk Model of Glycolysis-Related Genes

Background: Multiple factors influence the survival of patients with lung adenocarcinoma (LUAD). Specifically, the therapeutic outcomes of treatments and the probability of recurrence of the disease differ among patients with the same stage of LUAD. Therefore, effective prognostic predictors need to be identified. Methods: Based on the tumor mutation burden (TMB) data obtained from The Cancer Genome Atlas (TCGA) database, LUAD patients were divided into high and low TMB groups, and differentially expressed glycolysis-related genes between the two groups were screened. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to obtain a prognostic model. A receiver operating characteristic (ROC) curve and a calibration curve were generated to evaluate the nomogram that was constructed based on clinicopathological characteristics and the risk score. Two data sets (GSE68465 and GSE11969) from the Gene Expression Omnibus (GEO) were used to verify the prognostic performance of the gene. Furthermore, differences in immune cell distribution, immune-related molecules, and drug susceptibility were assessed for their relationship with the risk score. Results: We constructed a 5-gene signature (FKBP4, HMMR, B4GALT1, SLC2A1, STC1) capable of dividing patients into two risk groups. There was a significant difference in overall survival (OS) times between the high-risk group and the low-risk group (p < 0.001), with the low-risk group having a better survival outcome. Through multivariate Cox analysis, the risk score was confirmed to be an independent prognostic factor (HR = 2.709, 95% CI = 1.981–3.705, p < 0.001), and the ROC curve and nomogram exhibited accurate prediction performance. Validation of the data obtained in the GEO database yielded similar results. Furthermore, there were significant differences in sensitivity to immunotherapy, cisplatin, paclitaxel, gemcitabine, docetaxel, gefitinib, and erlotinib between the low-risk and high-risk groups. Conclusion: Our results reveal that glycolysis-related genes are feasible predictors of survival and the treatment response of patients with LUAD.

Development of Tumor Mutation Burden-Related Prognostic Model and Novel Biomarker Identification in Stomach Adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) is one of the most common tumors. Tumor mutation burden (TMB) has been linked to immunotherapy response. We wanted to see if there was any link between TMB and cancer prognosis. Methods: The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to obtain mutation data, gene expression profiles, and clinical data. We looked at the differences in gene expression and immune markers between low and high TMB groups, built an immune prognostic model, and created a dynamic nomograph App that may be used in the clinic. Simultaneously, We ran the immunotherapy prediction and model comparison at the same time. Finally, model gene mutation and copy number variation (CNV) were displayed. The cellular functional experiments were used to investigate the potential role of GLP2R in gastric cancer. Results: Firstly, basic mutation information and differences in immune infiltration in STAD are revealed. Secondly, the prognostic model developed by us has good accuracy, and the corresponding dynamic nomograph Apps online and immunotherapy prediction facilitate clinical transformation. Furthermore, GLP2R knockdown significantly inhibited the proliferation, migration of gastric cancer cells in vitro. Conclusion: Our findings imply that TMB plays a significant role in the prognosis of STAD patients from a biological perspective. GLP2R may serve as a potential target for gastric cancer.

Identification and validation of a tumor mutation burden-related signature combined with immune microenvironment infiltration in adrenocortical carcinoma.

Tumor mutation burden (TMB), an emerging molecular determinant, is accompanied by microsatellite instability and immune infiltrates in various malignancies. However, whether TMB is related to the prognosis or immune responsiveness of adrenocortical carcinoma (ACC) remains to be elucidated. This paper aims to investigate the impact of TMB on the prognosis and immune microenvironment infiltration in ACC. The somatic mutation data, gene expression profile, and corresponding clinicopathological information were retrieved from TCGA. The mutation landscape was summarized and visualized with the waterfall diagram. The ACC patients were divided into low and high TMB groups based on the median TMB value and differentially expressed genes (DEGs) between the two groups were identified. Diverse functional analyses were conducted to determine the functionality of the DEGs. The immune cell infiltration signatures were evaluated based on multiple algorithms. Eventually, a TMB Prognostic Signature (TMBPS) was established and its predictive accuracy for ACC was evaluated. Single nucleotide polymorphism and C > T were found to be more common than other missense mutations. In addition, lower TMB levels indicated improved survival outcomes and were correlated with younger age and earlier clinical stage. Functional analysis suggested that DEGs were primarily related to the cell cycle, DNA replication, and cancer progression. Additionally, significant differences in infiltration levels of activated CD4+ T cells, naive B cells, and activated NK cells were observed in two TMB groups. We also found that patients with higher TMBPS showed worse survival outcomes, which was validated in the Gene Expression Omnibus database. Our study systematically analyzed the mutation and identified a TMBPS combined with immune microenvironment infiltration in ACC. It is expected that this paper can promote the development of ACC treatment strategies.

Identifying GNG4 might play an important role in colorectal cancer TMB.

Colorectal carcinoma (CRC) is one of the most leading cause of cancer death all over the world. The tumor immune microenvironment is illustrated to be necessary for the progress of CRC. And the accumulating evidence indicated that tumor mutation burden (TMB) is effective in differentiating responding population of immune checkpoint inhibitor (ICI) therapies in various cancers. In this study, we aimed to evaluated the potential relationship between TMB and the recurrence risk of CRC. The transcriptomic and clinical data of CRC patients were collected from The Cancer Genome Atlas (TCGA) database (n= 382). Then the genomic analysis of tumor mutation burden and tumor purity were conducted by a computational method based on transcriptomic data. Firstly, we accessed the distribution of TMB and preferences at the gene and mutation level using somatic mutation data from TCGA data about CRC. We identified that high TMB predicted better prognosis of CRC patients. Secondly, the differentially expressed genes (DEGs) between the low TMB and high TMB group was clarified. Then the protein-protein interaction (PPI) analysis was performed, and the results confirmed ten hub genes among the DEGs. Utilizing the GEPIA web-tool, we discovered that GNG4 was up-regulated in tumor tissues, and GNG4 was related to the overall survival (OS) and tumor free survival (TFS) of CRC patients. Therefore, we considered GNG4 was essential for the tumor immune microenvironment of CRC. Furthermore, we also accessed the protein level of GNG4 in CRC and liver metastases from CRC. In this study, GNG4 was demonstrated to be the key element of the CRC TMB, which will be essential for the ICI therapy of CRC. Besides, GNG4 was up-regulated in CRC and liver metastases from CRC tissues. Thus, we thought that GNG4 might play an important role in colorectal cancer TMB and induce its metastasis in liver.

Prognostic Value of Tumor Mutational Burden Related to Immune Infiltration in Cervical Squamous Cell Carcinoma.

Cervical squamous cell carcinoma is one of the most common causes of female cancer deaths worldwide. At present, immunotherapy using immune checkpoint blockade (ICB) has improved the prognosis of many cancer patients, and neoantigens generated by mutations may serve as potential biomarkers for predicting the outcome of ICB therapy. In this study, we identified missense mutations as the most frequent in landscapes of gene mutation in cervical squamous cell carcinoma (CESC) samples. Patients with higher tumor mutation burden (TMB) presented higher overall survival (OS). In addition, there was a significant correlation between the high TMB group and fractions of most immune cells. Univariate and multivariate Cox regression analyses identified five hub genes (IFNG, SERPINA3, CCL4L2, TNFSF15, and IL1R1) that were used to build a prognostic model. In the prognostic model, the low-risk group achieved better OS. Mutations in the five hub genes mainly affected the infiltration level of CD8+ T cells and dendritic cells. In conclusion, our study is valuable for exploring the role of TMB and its relationship with immune infiltration in CESC. Moreover, the prognosis model may help predict the sensitivity of patients to immunotherapy and provide underlying biomarkers for personalized immunotherapy.

Identification of Three Core Secretome Genes Associated with Immune Infiltration in High Tumor Mutation Burden Across 14 Major Solid Tumors.

BackgroundSecretome genes, encoding proteins secreted from the cell, are involved in the tumor immune response and correlated with levels of tumor mutation burden (TMB) in multiple tumors. This study aimed to identify core secretome genes and their potential association with immunomodulators and immune infiltration in high TMB groups across 14 major solid tumors through bioinformatics analysis.MethodsMulti-omics data for 14 major solid tumors were downloaded from The Cancer Genome Atlas (TCGA) database. Patients were divided into high TMB (TMB-high) and low TMB (TMB-low) groups using the median TMB values for each of the solid tumors. The CIBERSORT algorithm was conducted to estimate the proportion of 22 tumor-infiltrating immune cells (TIICs). Kaplan–Meier analysis and the log-rank test were utilized to screened prognosis-related genes. The correlations between core secretome genes and TIICs were analyzed using Spearman correlation coefficients.ResultsIn TMB-high groups, multi-omics data analysis revealed that secretome genes were strongly associated with clinical characteristics, and 65 prognosis-related secretome genes were screened. Among the prognosis-related genes, 21 core secretome genes were identified, and strongly associated with five types of TIICs, namely activated NK cells, follicular helper T cells, CD8 T cells, and macrophages M0 and M2. Notably, three secretome genes (ADAMTS12, COL12A1, and COL5A2) were significantly related to immunomodulators and TIICs in multiple solid tumors. In addition, 12 core secretome genes were significantly differentially expressed between responding and non-responding patients receiving immunotherapy. Furthermore, core secretome genes may be involved in the PI3K/AKT signaling pathway.ConclusionWe examined the prognostic significance of secretome genes and their potential association with immunomodulators and immune infiltration across 14 major solid tumors. In summary, three secretome genes (ADAMTS12, COL12A1, and COL5A2) may be pivotal mediators of immune infiltration in TMB-high patients, which may help to identify patients who could benefit from immunotherapy.

Analysis of Threshold Changes of Tumor Mutation Burden of Gastric Cancer and Its Relationship with Patients' Prognosis.

Objective Gastric cancer is a malignant tumor originating from gastric mucosal epithelium. Here, we aimed to investigate the analysis of the threshold change of gastric cancer tumor mutation burden (TMB) and its relationship with the prognosis of patients. Methods 256 patients with gastric cancer were selected as subjects. All patients were in the advanced stage and received surgical resection of D2 lymph node dissection. After the operation, a follow-up was performed for 24 months, and the disease-free survival and overall survival of patients were counted. The NGS molecular biological was detected to obtain gastric cancer tumor mutation burden (TMB) data. Pearson correlation analysis software was used to analyze the correlation between TMB threshold and disease-free survival or overall survival of patients with gastric cancer, and the multivariate logistic analysis was performed as well. Results The disease-free survival period and the overall survival period of patients in the low-to-medium TMB group were both longer than those in the high TMB group. Pearson correlation analysis results showed that the TMB threshold was negatively correlated with the disease-free survival and overall survival of gastric cancer patients. Results from multivariate logistic analysis showed that high TMB thresholds have a greater impact on disease-free survival and overall survival of patients, but the impact of medium and low TMB thresholds on disease-free survival and overall survival of patients is weakened. Conclusions The TMB threshold level has a predictive effect on the effect of surgical resection of D2 lymph node dissection, and high levels of TMB can significantly affect disease-free survival and overall survival of patients with advanced gastric cancer.

Abstract 375: High tumor mutation burden predicts unfavorable clinical outcome in EGFR-mutated lung adenocarcinoma treated with targeted therapy

Abstract Purpose: Although high tumor mutation burden (TMB) has shown association with benefit from immune checkpoint blockade therapies, its implications in lung cancer patients with driving mutations are still unclear. The objective of this study is to determine the association between TMB and treatment outcome in epidermal growth factor receptor (EGFR)-mutated lung cancer treated with tyrosine kinase inhibitors (TKIs). Methods: We evaluated TMB in EGFR-mutant, lung adenocarcinoma patients who received first-line EGFR-TKIs. TMB was estimated by next-generation sequencing with a cancer gene panel (Oncomine™ Tumor Mutation Load Assay). We compared the response rate (RR), progression-free survival (PFS), overall survival (OS), and frequency of secondary T790M mutation according to the different TMB groups. Results: Among the 131 patients who were treated with EGFR-TKIs, a total of 63 patients were eligible for the analysis. TMB was stratified by tertiles; low (≤2.13 mutations/Mb), intermediate (2.14-4.25 mutations/Mb), and high (&amp;gt;4.25 mutations/Mb). The TMB levels were not associated with any clinical parameters. The RR was significantly lower in the high TMB group than in the other groups (43.5% vs. 72.1% vs. 78.5%, all p = 0.01). In multivariate analysis, high TMB was independently associated with a shorter PFS in the overall population (hazard ratio [HR] = 2.64, p = 0.004), and associated with shorter OS in patients with exon 19 deletion (HR = 2.55, p = 0.041) compared with low TMB. The frequencies of secondary T790M mutation after TKI failure were not different among the different TMB groups. Conclusion: High TMB was associated with unfavorable clinical outcome in patients with lung adenocarcinoma treated with EGFR-TKIs. Although further large-scaled studies are required, our data suggest that high TMB may be a predictive biomarker for adverse treatment outcomes and may constitute a distinct subgroup warranting tailored therapeutic approach in this clinical setting. Citation Format: Seung Hyeun Lee, Ji-Youn Sung. High tumor mutation burden predicts unfavorable clinical outcome in EGFR-mutated lung adenocarcinoma treated with targeted therapy [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 375.