Value Of Tumor Mutation Burden Research Articles

Predictive value of PD-L1 and TMB for short-term efficacy prognosis in non-small cell lung cancer and construction of prediction models.

To investigate the correlation between programmed death ligand 1(PD-L1), tumor mutation burden (TMB) and the short-term efficacy and clinical characteristics of anti-PD-1 immune checkpoint inhibitor combination chemotherapy in NSCLC patients. The efficacy of the prediction model was evaluated. A total of 220 NSCLC patients receiving first-line treatment with anti-PD-1 immune checkpoint inhibitor combined with chemotherapy were retrospectively collected. The primary endpoint was short-term efficacy ORR. The correlation between short-term efficacy, PD-L1, TMB, and clinical characteristics using χ2 test or t-test was evaluated. Screen the independent prognostic factors using univariate and multivariate logistic regression analyses, and construct a nomogram prediction model using the "rms" package in R software. Using receiver operating characteristic (ROC) curve analysis to evaluate the independent Prognostic factors and the prediction model. Using decision curve analysis (DCA) to verify the superiority of the prediction model. The mean values of PD-L1, TMB, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, and albumin were the highest in the ORR group, PD-L1 expression and TMB correlated with epidermal growth factor receptor expression. Multivariate analyses showed that PD-L1, TMB, and neutrophil were independent prognostic factors for ORR. The area under the ROC curve (AUC) values of the ROC constructed based on these three indicators were 0.7104, 0.7139, and 0.7131, respectively. The AUC value under the ROC of the nomogram model was 0.813. The DCA of the model showed that all three indicators used together to build the prediction model of the net return were higher than those of the single indicator prediction model. PD-L1, TMB, and neutrophils are independent prognostic factors for short-term efficacy. The nomogram prediction model constructed using these three indicators can further improve predictive efficacy of ICIs in patients with NSCLC.

Abstract 2522: Predictive value of tumor mutational burden (TMB) in patients with metastatic microsatellite-stable (MSS) colorectal cancer (CRC) given first-line oxaliplatin-based chemotherapy and immune checkpoint blockade (ICB)

Abstract Purpose: Most CRC patients harbor primarily non-immunogenic MSS tumor. The randomized METIMMOX trial (NCT03388190) examined if patients with previously untreated, unresectable abdominal metastases from MSS-CRC may achieve therapeutic efficacy from short-course oxaliplatin-based chemotherapy (FLOX) and sequential ICB (nivolumab) repeatedly. Half of study patients assigned to this experimental treatment had significantly extended progression-free survival (PFS) while the other half had shortened PFS, compared to the control-group patients given standard FLOX chemotherapy with median PFS 9.3 months. Here we explored if somatic mutations (mut) unveiled by next-generation sequencing might provide insights into responsiveness to the METIMMOX regimen. Procedures: Patients had MSS-CRC with infradiaphragmatic metastases deemed unresectable and were eligible for first-line oxaliplatin-based therapy. They were randomly assigned to the control group of FLOX (oxaliplatin, 5-fluorouracil, folinic acid) Q2W or the experimental group of alternating 2 cycles each of FLOX Q2W and nivolumab Q2W, with prespecified break periods. Radiologic response assessment was done every 8 weeks with PFS as the primary endpoint. Diagnostic tumor biopsies and baseline metastasis biopsies were sequenced with the TruSight Oncology 500 assay. TMB was calculated using only coding, non-synonymous single-nucleotide variants and insertions/deletions with variant allele frequency ≥5% and sequencing depth ≥50 ×, applying the effective panel size as the megabases (Mb) denominator. Results: Sequencing data were acquired from 20 experimental-group patients with median PFS 7.9 months (minimum 2.0, maximum 41.6). Median TMB was 5.1 mut/Mb (minimum 0.8, maximum 11.8), concordant in patient-paired primary tumor and metastasis specimens. The TMB was associated with treatment outcome; the higher TMB, the better PFS with hazard ratio 0.83 (95% confidence interval (CI) 0.70-0.98; p = 0.026, Cox regression) for a PFS event with increasing TMB. TMB cut-off as low as 5.0 mut/Mb distinguished between patient groups (p = 0.007, log-rank test) with median PFS 34.9 months (95% CI 10.6-59.2; TMB>5, n = 10) and median PFS 4.6 months (95% CI 2.7-6.5; TMB≤5, n = 10). In the TMB>5 group, 8/10 were KRAS- or BRAF-mutant cases. In the TMB≤5 group, 9/10 metastasis specimens were RAS/BRAF-wildtype cases. Conclusions: TMB >5 mut/Mb was associated with tumor KRAS or BRAF driver mutation and remarkably long PFS in first-line treatment of patients with abdominal metastases from MSS-CRC with alternating short-course oxaliplatin-based chemotherapy and ICB. Citation Format: Anne Hansen Ree, Paula A. Bousquet, Hilde L. Nilsen, Torben Lüders, Shixiong Wang, Tina Visnovska, Diana L. Bordin, Eirik Høye, Hanne M. Hamre, Christian Kersten, Eva Hofsli, Marianne G. Guren, Halfdan Sorbye, Kjersti Flatmark, Sebastian Meltzer. Predictive value of tumor mutational burden (TMB) in patients with metastatic microsatellite-stable (MSS) colorectal cancer (CRC) given first-line oxaliplatin-based chemotherapy and immune checkpoint blockade (ICB) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2522.

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.

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.

Utility of Tumor Mutational Burden as a Biomarker for Response to Immune Checkpoint Inhibition in the VA Population.

Immune checkpoint inhibitors (ICIs) are used for an increasing number of indications across various tumor types, as well as several tumor-agnostic indications in patients with advanced cancer. Although many patients benefit from ICI therapy, others do not, highlighting a need for better predictive biomarkers. Tumor mutational burden (TMB) reflects the global number of mutations within a tumor and has been widely explored as a predictive biomarker of ICI response. The current tumor type-agnostic US Food and Drug Administration approval of pembrolizumab for metastatic solid tumors defines high TMB (TMB-H) as ≥10 mut/Mb as measured by FoundationOne CDx. This fixed cutoff may not be the ideal value across all solid tumors. We performed a retrospective analysis of the association of survival outcomes with TMB in patients treated with ICI for five major cancer types, using real-world data from the VA. Survival was measured from initiation of ICI, and Kaplan-Meier survival curves were compared by log-rank test. Overall survival (OS) was significantly longer for patients with TMB-H versus TMB low tumors in non-small-cell lung cancer (NSCLC; n = 1,593), head and neck (H&N) cancer (n = 222), and urothelial cancer (n = 332). OS was not significantly different based on TMB status in melanoma (n = 207) or esophageal/gastric cancer (n = 248). Consistent with previous studies, a predictive value of TMB ≥10 mut/Mb for ICI response was found in NSCLC and H&N, but not in esophageal/gastric cancer. Although inconclusive in the literature, significant association was found in urothelial cancer. The predictive value of TMB in melanoma was inconclusive. Our analysis does not support the use of a fixed threshold for TMB as a standalone predictive biomarker for ICI across all solid tumors.

A study of tumor neoantigen burden and HLA-LOH by whole-exome sequencing to characterize immune biomarkers of lung cancer.

8527 Background: Lung cancer is a leading cause of cancer-related death worldwide. Precision immunotherapy, such as the use of immune checkpoint inhibitors (ICIs), has been shown to improve the survival of lung cancer patients. Cancer cells with high amount of neoantigens are more likely to be captured by immune cells and thus patients with high Tumor Mutation Burden(TMB) and high Tumor Neoantigen Burden(TNB) are estimated to be prone to ICIs treatment. HLA class Ⅰ is one of the main factors affecting the prognosis of ICI in treatment. Studies have indicated that patients with highly heterozygous HLA-I are more likely to have better responses to ICI treatment. Some specific HLA-Ⅰ genotypes and somatic mutations can affect the prognosis of ICIs treatment. Methods: In this study, we performed whole-exome sequencing (WES) of 200 pairs of tumor and gDNA samples from lung cancer patients. Tumor sample comes from tumor tissue or paraffin-embedded tissue and gDNA is extracted from white blood cells from peripheral blood. We analyze the WES data to obtain the TMB and HLA types of each sample. Then the peptide affinity of MHC-I genes were quantified based on IC50(nM) by netMHCpan software, and the level of neoantigen affinity were classified as strong (IC50≤50nM), weak (50nM < IC50≤500nM), and negative (IC50 > 500nM). TNB is defined as the number of high- affinity neoantigens per megabase of interrogated genomic sequence. Then we conducted linear regression analysis to study the statistical relationship between TMB and TNB. Finally, we analyzed the LOH status at the major region of HLA (HLA-A, HLA-B, and HLA-C) and classified the individuals who have LOH at all three types of HLA as HLA-LOH strong positive, samples with one or two LOH among the three HLA types as weak positive, and samples have no LOH are classified as HLA-LOH negative. Results: Among the 200 samples, the median value of TMB and TNB is 3.25 Muts/Mb and 1.09 Neos/Mb, respectively. 8.5% of the sample have high TMB(TMB≥10). TMB and TNB are also significantly positively correlated (p-value < 0.0001). For HLA typing, 82.0% HLA-A, 96.0% HLA-B, and 92.5% HLA-C are heterozygous. The dominant HLA types are: (A*11:01), (A*02:01), (B*46:01), (B*40:01), (C*01:02), and (C*07:02). As for LOH status among the three HLA types, 14.57% of the individuals are HLA-LOH strong positive, 31.66% are HLA-LOH weak positive, and 53.77% of the samples are HLA-LOH negative. Lastly, the average numbers of detected high-affinity neoantigens are statistically significantly related to the occurrence of HLA-LOH (Analysis of Variance p-value < 0.01). Conclusions: HLA-LOH occurs in nearly half of our lung cancer samples, and it is associated with TMB-High and TNB-High. The analysis of HLA-LOH refines the prediction of neoantigen and gain understanding of drug resistance and immunotherapy.

Abstract 4405: Tumor mutational burden, as a potential predictive marker for the efficacy of immunotherapy in advanced gastric cancer

Abstract Background: The optimal value of tumor mutational burden (TMB) for predicting treatment response of immunotherapy in advanced gastric cancer (AGC) is still unclear. We aimed to establish the optimal cut-off value of TMB, and evaluate the efficacy of immunotherapy in AGC according to TMB and other markers. Method: From October 1, 2020, to July 27, 2021, at Samsung medical center in Korea, patients with AGC, who received pembrolizumab or nivolumab were included. TMB was measured by next-generation sequencing (NGS)-based assays, and PD-L1 is tested using immune-histochemical assay 22C3 pharmDx. Based on receiver operating characteristic analysis, the cut-point value of TMB was determined as the point where the Youden’s index is maximum. Result: A total of 53 patients were analyzed. The cut-off value of TMB for predicting the overall response of immune checkpoint inhibitors was defined as 13.31 mutations/megabase (mt/mb), with 56% of sensitivity and 95% of specificity. Under this definition of TMB, 7 patients were TMB-high group (≥13.31 mt/mb), while 46 patients were TMB-low group (<13.31 mt/mb). The overall response rate (ORR) had a statistically significant difference between TMB-low (8.7%, n=4/46) and TMB-high patients (71.4%, n=5/7; p=0.001). The progression-free survival (PFS) and overall survival (OS) for 53 patients were 1.93 months (95% CI, 1.600-2.268) and 4.26 months (95% CI, 2.992-5.532). The OS was longer in the TMB-high group with the median of 20.8 months (95% CI, 2.292-39.281) compared to the TMB-low group with the median of 3.31 months (95% CI, 1.604-5.019; p=0.049). The ORR of the patients whose PD-L1 CPS was 1 or above was not different from the patients whose PD-L1 CPS was lower than 1. Conclusion: In this study, the optimal value of TMB for predicting the objective response rate of immunotherapy in AGC was determined as 13.31 mt/mb. TMB-high (≥13.31 mt/mb) was associated with a better objective response rate, and TMB-high patients exhibited better overall survival. TMB has the potential for predicting therapeutic response to immunotherapy in advanced gastric cancer. Citation Format: Jaeyeon Jang, Youngkyung Jeon, Sun Young Jeong, Ye Ji Jung, Daeho Choi, Joohyun Hong, Jeeyun Lee, Won Ki Kang, Seung Tae Kim. Tumor mutational burden, as a potential predictive marker for the efficacy of immunotherapy in advanced gastric cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4405.

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.

Tumor mutational burden as a potential predictive marker for the efficacy of immunotherapy in advanced gastric cancer.

324 Background: Tumor mutational burden (TMB) is known as an independent predictive factor in predicting treatment response of immunotherapy. We aimed to evaluate the efficacy of immunotherapy in advanced gastric cancer (AGC) according to TMB and other markers. Methods: The patients with AGC, aged ≥ 18, who received pembrolizumab or nivolumab from October 1, 2020, to July 27, 2021, at Samsung medical center in Korea, were analyzed retrospectively. TMB was measured by next-generation sequencing-based assays, and PD-L1 is tested using immunohistochemical assay 22C3 pharmDx. Referring to the results of previous studies, TMB-high was defined as 14.31 mutations/megabase (mt/Mb) or above. Results: A total of 54 AGC patients who were treated with immunotherapy, pembrolizumab or nivolumab, were analyzed. Seven patients were TMB-high, and 47 patients were TMB-low. Compared to TMB-low group, TMB-high group showed higher overall response rate (ORR) (42.9% vs 6.4%, p=0.023), and disease control rate (66.7% vs. 22.9%; p=0.033). The median OS was longer in the TMB-high group with 22.4 months (95% CI, 19.738-25.115), while the TMB-low group with 3.6 months (95% CI, 2.109-5.104; p=0.020). In addition to TMB, microsatellite status was statistically significantly associated with the efficacy of immunotherapy in AGC. Microsatellite instability group had better ORR (n=3/4, 75%) compared to microsatellite stable group (n=4/50, 8.0%; p=0.005). Other than that, the ORR of the patients whose PD-L1 CPS was 1 or above did not differ from the patients whose PD-L1 CPS was lower than 1. Although there was no statistical significance, among TMB-low patients, PD-L1 CPS ≥1 group numerically exhibited a higher overall response rate (13.0% vs 4.0%; p=0.338). Conclusions: In our analysis, the cut-off value of TMB was set to 14.31mb/Mt, and TMB-high was associated with the better ORR and OS of immunotherapy in AGC. TMB could be a potential predicting marker for a therapeutic response of immunotherapy in AGC.[Table: see text]

Prognostic value of tumor mutation burden in patients with advanced gastric cancer receiving first-line chemotherapy.

Tumor mutation burden (TMB) is a promising biomarker positively associated with the benefit of immunotherapy and that might predict the outcome of chemotherapy. We described the prognostic value of TMB in advanced gastric cancer and explored the underlying mechanism. We enrolled 155 TMB-evaluated advanced gastric cancer patients and analyzed the relationship between clinicopathological characteristics and both overall survival (OS) and progression-free survival (PFS) among 40 patients treated with first-line chemotherapy. We further verified the distribution of TMB and analyzed the potential mechanism underlying the prognosis based on The Cancer Genome Atlas (TCGA) database. Among the 155 patients, 29 (18.7%) were TMB-high (TMB ≥ 10), roughly the same as the proportion in the TCGA data. Of the 40 patients receiving first-line chemotherapy, the median OS (7.9 vs. 12.1 months; HR 3.18; p = 0.0056) and PFS (4.4 vs. 6.2 months; HR 2.94; p = 0.0099) of the tissue-tested TMB (tTMB)-high patients were inferior to those of the tTMB-low patients. Similarly, unfavorable median OS (9.9 vs. 12.1 months; HR 2.11; p = 0.028) and PFS (5.3 vs. 6.5 months; HR 2.49; p = 0.0054) were shown in the blood-tested TMB (bTMB)-high than in the bTMB-low patients. The Cox analysis demonstrated that both tTMB-high and bTMB-high were significant independent predictors of dreadful OS and PFS. The differentially expressed genes (DEGs) according to TMB status were most significantly enriched in the downregulated metabolic pathway among the TMB-high patients. TMB-high advanced gastric cancer patients accounted for around one-sixth and had a poorer prognosis than TMB-low patients when treated with first-line chemotherapy. The potential mechanism might be the downregulated metabolic activity in TMB-high patients.

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.

The prognostic value of tumor mutational burden related 6-gene-based Risk Score in laryngeal cancer patients

BackgroundLaryngeal cancer (LC) is the second frequent malignant head and neck cancer around world, while LC patients’ prognosis is unsatisfactory. This study aims to investigate the prognostic value of tumor mutation burden (TMB)-related genes in LC.MethodsLC data was downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. TMB values of all samples were calculated basing on mutation data. The differentially expressed genes (DEGs) between LC samples with distinct TMB were subjected to univariate and LASSO Cox regression analysis to build Risk Score. Immune cell infiltration analysis was conducted in CIBERSORT.ResultsBetween high and low TMB LC samples, we identified 210 DEGs. Of which, six optimal genes were included to construct Risk Score, comprising FOXJ1, EPO, FGF5, SPOCK1, KCNF1 and PSG5. High risk LC patients had significantly poorer overall survival than low risk patients. The nomogram model constructed basing on Risk Score and gender showed good performance in predicting LC patients’ survival probability.ConclusionsThe prognostic Risk Score model, basing on six TMB-related genes (FOXJ1, EPO, FGF5, SPOCK1, KCNF1 and PSG5), was a reliable prognostic model to separate LC patients with different prognoses.

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.

High tumor mutation burden indicates better prognosis in colorectal cancer patients with KRAS mutations.

Colorectal cancer (CRC) is a common type of malignant tumor of the digestive tract. Tumor mutation burden (TMB) is a potential prognostic indicator of numerous malignant tumors. This study investigated the prognostic value of TMB in CRC. This study analyzed the clinical and somatic mutation data of patients with CRC from the Memorial Sloan Kettering Cancer Center (MSKCC) and The Cancer Genome Atlas (TCGA) cohorts. The genetic landscape was visualized using the maftools package in R software. Survival curves were constructed using the Kaplan-Meier method, and Cox regression analysis was performed to confirm that TMB is an independent prognostic indicator. A nomogram was developed to construct the prognostic model, which was evaluated using the C-index, calibration curve, and decision curve analysis. In patients with CRC, APC mutations indicated longer overall survival (OS), whereas KRAS mutations indicated shorter OS. For all included patients, there was no significant difference in the OS between the TMB-high and TMB-low groups. For patients with KRAS mutations, the OS in the TMB-high group was longer than that in the TMB-low group. Cox regression analysis showed that TMB was an independent prognostic factor in CRC patients with KRAS mutations. This explains the good accuracy of the nomogram prognostic model using TMB and indicates its good prospect in clinical applications. A high TMB indicates better prognosis in CRC patients with KRAS mutations, thus confirming the value of TMB in clinical applications.

Systematic assessment and optimizing algorithm of tumor mutational burden calculation and their implications in clinical decision-making.

Tumor mutation burden (TMB) has been validated as a biomarker to predict the response of immune checkpoint inhibitors (ICIs) treatment in various cancers. However, the effects of different sequencing platforms, cancer types, and calculation algorithms on TMB as well as its cut-off value for predicting immunotherapy efficacy in the East Asian population still need to be further investigated. In this study, the data of 4126 samples generated by targeted panel sequencing or whole-exome sequencing (WES) in different platforms and public sequencing data from 3680 samples that contained targeted panel sequencing, WES and whole-genome sequencing (WGS) were obtained. The impact of different sequencing platforms and methods on TMB calculation was assessed. No significant bias was found in TMB calculated by different platforms. However, TMB calculated from WGS was significantly lower than those calculated from targeted panel sequencing and WES. The distribution of TMB at different sequencing depths and tumor purity were analyzed. There was no significant difference in the distribution of TMB when the sequencing depth was greater than 500, the tumor purity estimated by hematoxylin-eosin (HE) staining was between 0.1-1.0 or estimated by next-generation sequencing (NGS) was greater than 0.4. In addition, the somatic-germline-zygosity (SGZ) algorithm was optimized to calculate TMB from tumor-only sequencing samples in the East Asian population. The correlation coefficient of TMB calculated with the optimized SGZ algorithm and paired normal-tumor sequencing is 0.951. Furthermore, the optimal cut-off value of TMB in East Asian lung cancer patients treated with ICIs was determined to be 7 mut/Mb instead of 10 mut/Mb through the ROC curve and Log-rank analysis in the training cohort and validated in the test cohort. Patients with TMB ≥ 7 mut/Mb had better outcomes than patients with TMB<7 mut/Mb. In conclusion, this study systematically analyzed the factors that influenced the TMB calculation and optimized the SGZ algorithm to calculate TMB from tumor-only sequencing samples in the East Asian population. More importantly, the cut-off value of TMB for predicting immunotherapy efficacy was determined to be 7 mut/Mb instead of 10 mut/Mb in East Asian lung cancer patients, which can help in clinical decision-making.

Genomic and transcriptomic profiling indicates the prognosis significance of mutational signature for TMB-high subtype in Chinese patients with gastric cancer

IntroductionGastric cancer (GC)is the third leading cause of cancer-related deaths in China and immunotherapy emerging as a revolutionary treatment for GC recently. Tumor mutational burden (TMB) is a predictive biomarker of immunotherapy in multiple cancers. However, the prognostic significance and subtype of TMB in GC is not fully understood. ObjectivesThis study aims to evaluate the prognostic value of TMB in Chinese GC and further classify TMB-high GC (GCTMB-H) patients combing with mutational signatures. MethodsGenomic profiling of 435 cancer-gene panel was performed using 206 GC samples from Chinese people. Actionable genetic alterations were compared across all the samples to generate actionable subtyping. The prognostic value of TMB in Chinese GC was evaluated. Mutational signatures were analyzed on TMB-H subtype to stratify the prognosis of TMB. Transcriptomic analysis was applied to compare the distributed immunocytes among different subtypes. Results88.3% (182/206) of GC samples had at least one mutation, while 45.1% (93/206) had at least one somatic copy number alteration (SCNA). 29.6% (61/206) of GC samples were TMB-H, including 13 MSI-H and 48 MSS tumors. According to distinct genetic alteration profiles of 69 actionable genes, we classified GC samples into eight molecular subtypes, including TMB-H, ERBB2 amplified, ATM mutated, BRCA2 mutated, CDKN2A/B deleted, PI3KCA mutated, KRAS mutated, and less-mutated subtype. TMB-H subtype presented a remarkable immune-activated phenotype as determined by transcriptomic analysis that was further validated in the TCGA GC cohort. GCTMB-H patients exhibited significantly better survival (P = 0.047). But Signature 1-high GCTMB-H patients had relatively worse prognosis (P = 0.0209, HR = 2.571) than Signature 1-low GCTMB-H patients from Chinese GC cohort, also validated in TCGA GC cohort, presenting highly activated carbohydrate, fatty acid or lipid metabolism. ConclusionThe Signature 1-high GCTMB-H could be a marker of poor prognosis and is associated with metabolism disorder.

New methodology of TMB assessment from tissue and liquid biopsy in NSCLC.

Immunotherapy has dramatically influenced and changed therapeutical approach in non-small cell lung cancer (NSCLC) in recent five years. Even though we can reach long-term response to this treatment in approximately 20% of patients with NSCLC, we are still not able to identify this cohort of patients based on predictive biomarkers. In our study we have focused on tumor mutation burden (TMB), one of the potential biomarkers which could predict effectiveness of check-point inhibitors, but has several limitations, especially in multiple approaches to TMB quantification and ununiform threshold. We determined the value of TMB in tumor tissue (tTMB) and blood (bTMB) in 20 patients with early stage NSCLC using original custom gene panel LMB_TMB1. We evaluated various possibilities of TMB calculation and concluded that TMB should be counted from both somatic non-synonymous and synonymous mutations. Considering various factors, we established cut-offs of tTMB in/excluding HLA genes as ≥22 mut/Mb and 12 mut/Mb respectively, and cut-offs of bTMB were defined as ≥21 mut/Mb and ≥5 mut/Mb, respectively. We also observed trend in correlation of somatic mutations in HLA genes with overall survival of patients.

PRLHR Immune Genes Associated With Tumor Mutation Burden can be Used as Prognostic Markers in Patients With Gliomas.

Tumor mutation burden (TMB) is a useful biomarker for predicting the prognosis and efficacy of immune checkpoint inhibitor (ICIs). In this study, we aimed to explore the prognostic value of TMB and TMB-related PRLHR immune genes as prognostic markers in patients with gliomas. We downloaded MAF files, RNA-seq data, and clinical information from the Cancer Genome Atlas (TCGA) database. The TMB of glioma was calculated and its correlation with clinical features and prognosis was analyzed. We found that TMB was statistically correlated with the grade and age of patients with gliomas. Kaplan-Meier curve analysis showed that low TMB was associated with better clinical outcome in patients with gliomas. Additionally, a predictive model based on five HUB genes (FABP5, VEGFA, SAA1, ADM, and PRLHR) was constructed to predict OS in patients with gliomas. Receiver operating characteristic curve analysis shows that the model is reliable in predicting the risk of survival and prognosis. Immune microenvironment analysis revealed a correlation between TMB and infiltrating immune cells. The clinical-related immune gene, PRLHR, can be used as an independent prognostic factor for patients with brain glioma, and it is negatively correlated with the grade of glioma and age of patients with glioma. We found that the higher the tumor grade and the older the age, the lower the PRLHR expression, which was verified by CGGA database and independent experimental data. These results suggest that PRLHR may be a tumor suppressor for the progression of glioma and might provide a new therapeutic target for the treatment and improvement of survival rate in patients with glioma.

Abstract 5742: The landscape of genetic alteration in Chinese lung adenosquamous carcinoma patients

Abstract Background: Lung adenosquamous carcinoma (LASC) is a mixed histologic component tumor type that contains both squamous cell carcinoma and adenocarcinoma, with each component accounting for at least 10% of tumors. The incidence of LASC is very low, only comprising 0.4-4% of all lung cancers. LASC yields a more aggressive clinical course, and its prognosis is generally worse than that of adenocarcinoma and squamous cell carcinoma of the lung. Due to the rarity of LASC, currently, there is no standard treatment. Also, to date, limited genomic data have been performed. In this study, we analyzed the genomic alterations and clinical signatures of LASC. Materials and Methods: Formalin-fixed, paraffin-embedded (FFPE) tumor tissues and matched blood samples were collected for a targeted, next-generation sequencing (NGS) assay at OrigiMed (Shanghai, China), a College of American Pathologists (CAP) accredited and Clinical Laboratory Improvement Amendments (CLIA) certified laboratory. Genomic alterations including single base substitution, indel, copy number variations, and gene fusion and rearrangement were assessed. Results: A total of 124 LASC patients were enrolled in our study, including 77 (62.1%) males and 47 (37.9%) females, with a median age of 61 years old (range 27-82). Forty-three (43, 34.68%) patients had a smoking history and half of patients possessed a Stage III/IV disease. The most commonly altered genes were TP53 (66.9%), EGFR (54.8%), CDKN2A (21%), TERT (21%), and LRP1B (18.5%). Surprisingly, 91.1% and 52.4% patients harbored at least one druggable alteration based on the solid cancer and NSCLC NCCN guides, respectively. The most frequent druggable mutation, EGFR, is comprised of 35 (51.47%) single mutations and 33 (48.53%) complexed mutations, with most containing a 19 exon deletion and EGFR amplification (12%). The median tumor mutational burden (TMB) of patients with LASC was 5.15 muts/Mb (range, 0-69.3 muts/Mb), and 33 (26.6%) patients were TMB-H (TMB ≥ 10 Muts/Mb). Patients with an ARID2, BRCA1, or KEAP1 mutation had a significantly higher value of TMB than wild type (median TMB 16.1 vs. 5 muts/Mb, 29.7 vs. 5 muts/Mb, 14.6 vs. 4.85 muts/Mb, respectively, P &amp;lt; 0.05). Patients with HRR or DDR mutations also displayed a higher TMB value than for wild type. We additionally determined that mutation signature 1 (the clock-like signature), signature 2 (the APOBEC signature), and signature 3 (the BRCA mutational signature) exhibited a higher mutational load for the entire cohort. All patients with signature 2 or 3 displayed a HLA-B heterozygous subtype. Conclusions: Our study revealed genomic profiling for the largest sample size of Chinese LASC patients to date. Profiling obtained from this study demonstrates that LASC patients have the same chance for targeted therapy and immune checkpoint inhibitors as compared to lung adenocarcinoma and lung squamous cell carcinoma, respectively. Citation Format: Hongbiao Wang, Yingcheng Lin, Jun Liu, Yuyin Cai, Xiaofang Qi, Lujia Huang. The landscape of genetic alteration in Chinese lung adenosquamous carcinoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5742.