Tumor Mutational Burden Research Articles

IMMU-40. INVESTIGATING THE ROLE OF MUTATIONAL BURDEN IN TUMOR IMMUNOGENICITY USING A PRE-CLINICALMLH1-DEFICIENT GLIOBLASTOMA MODEL

Abstract BACKGROUND Although there is an established correlation between tumor mutational burden (TMB) and response to immune checkpoint inhibition (ICI) in many cancers, such an association has not been definitively shown in high-grade gliomas. Most studies of ICI therapy in gliomas, including glioblastoma (GBM), have failed to demonstrate efficacy, with the exception of hypermutated cases resulting from rare inherited defects in mismatch repair (MMR) genes. We sought to investigate the association of TMB to immune response using a syngeneic murine model with a spectrum of mutational burdens. METHODS We used CRISPR-Cas9 to knockout the MMR gene Mlh1 in the murine glioma model SB28, an ICI-resistant cell line with a very low mutational burden (108 non-synonymous mutations). RESULTS Single-cell sorted Mlh1 knockout SB28 clones revealed a two- to six-fold increase in TMB. Importantly, loss of Mlh1 also brought about global changes in immune- and inflammatory-related gene expression in vitro, without correlation to increasing TMB. While all clones had the same rate of in vitro proliferation, flank injection of a high TMB vs a low TMB SB28 Mlh1 knockout clone resulted in similar survival benefits compared to Mlh1 wildtype SB28. CONCLUSIONS These preliminary results suggest that, although disruption of the MMR system may result in heightened tumor immunogenicity, elevated TMB may not be the sole significant determinant. We are currently investigating tumor proliferation after flank injection in immunocompromised mice to confirm that slowed growth is immune-related, as well as clone-specific response to ICI treatment. We are also exploring the role of specific cytokines/chemokines in conferring this survival advantage and potential immune response. By generating a GBM model of varied mutational burdens and immune profiles and comparing to the baseline SB28 cell line, we can interrogate the relative significance of TMB in tumor immunogenicity and ICI response.

The potential of ESCO2 as a prognostic and immunotherapeutic marker of pan-cancer and its role in anti-PD1 treatment of bladder cancer

Background Establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2), a member of the EFO2 family, is implicated in the pathogenesis and progression of various cancers. However, there has been limited comprehensive pan-cancer analysis conducted on ESCO2 thus far. Methods Publicly available databases, such as the UCSC Xena database, were utilized to examine differential expression patterns across various cancer types. In addition, variations in expression levels were investigated across distinct clinical stages. Univariate Cox regression and Kaplan-Meier survival analyses were conducted to evaluate the impact on overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) at a pan-cancer level. The correlation between ESCO2 expression and immune cell infiltration was examined to gain insight into the tumor microenvironment in different cancers. The results of the bioinformatic analysis were validated using immunotherapy clinical trials and pathological specimens. CCK-8 and transwell assay experiments were performed to investigate the biological function of ESCO2. Results ESCO2 expression was found to be up-regulated in most cancers, with a correlation to TNM stages. Prognostic analysis indicated that overexpression of ESCO2 was associated with poor prognosis in various cancers. Furthermore, the correlation between ESCO2 expression and immune cell infiltration suggested its potential as a predictor for immunotherapy efficacy. Notably, ESCO2 expression showed positive associations with immunoinhibitor, immnostimulator, MHC molecule, chemokine receptor, tumor mutation burden (TMB) and microsatellite instability (MSI) levels in bladder cancer (BLCA). The validation cohort for immunotherapy corroborated these findings and substantiated that ESCO2 could function as an autonomous prognostic biomarker and a promising target for cancer treatment via immunotherapy. In addition, in vitro experiments confirmed the role of ESCO2 in influcing the proliferation, invasion and migration of BLCA cells. Conclusion ESCO2 participates in regulating the immune infiltration and affecting the prognosis of patients in many cancers, especially in BLCA. ESCO2 may serve as a prognostic and immunotherapy biomarker in future treatment of human cancer.

Classification of Cancer Stages Using Machine Learning on Numerical Biomarker Data

Cancer staging is a crucial aspect of determining appropriate treatment strategies and predicting patient outcomes. Traditional diagnostic methods rely heavily on invasive procedures and qualitative assessments, which can be time-consuming and prone to subjective errors. This research aims to address these limitations by leveraging machine learning (ML) techniques to classify cancer stages using numerical biomarker data, such as C-reactive protein (CRP), tumor mutation burden (TMB), and lactate dehydrogenase (LDH). By applying models like Random Forest, Support Vector Machines (SVM), Gradient Boosting, and Multi-Layer Perceptron (MLP), we aim to improve the accuracy of cancer stage classification. Feature selection through Recursive Feature Elimination (RFE) was performed to enhance model efficiency by identifying the most significant biomarkers. The results show that ML models can effectively predict cancer stages, with Random Forest achieving the highest accuracy at 85%. This method offers a non-invasive, rapid, and scalable alternative to conventional diagnostic approaches, potentially improving clinical decision-making and patient care.

NEK2 is a potential pan-cancer biomarker and immunotherapy target

BackgroundNEK2 is a member of the NEKs family and plays an important role in cell mitosis. Increasing evidence suggests that NEK2 is associated with the development of multiple tumors, but systematic studies of NEK2 in cancer are still lacking. Therefore, we evaluated the prognostic value of NEK2 in 33 cancers to elucidate the potential function of NEK2 in pan-cancers.MethodsWe investigated the role of NEK2 in pan-cancers utilizing The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. Additionally, we analyzed the association between NEK2 gene expression across various cancers, protein expression, the tumor microenvironment (TME), and drug sensitivity using several software and web platforms.The potential oncogenic role of NEK2 was initially explored using bioinformatics methods. Furthermore, we conducted in vitro experiments to preliminarily validate the function of NEK2 in cervical cancer.ResultsNEK2 is overexpressed in almost all tumors, and mutation of NEK2 are associated with a poorer tumor prognosis. In addition, the correlation between NEK2 and immune features such as immune cell infiltration, immune checkpoint genes, tumor mutational burden (TMB), Microsatellite instability(MSI) etc. suggest that NEK2 could potentially be applied in the immunotherapy of tumors.ConclusionNEK2 may be a potential pan-cancer biomarker and immunotherapeutic target for improving the efficacy of tumor therapy.

The Prognostic Value and Immunotherapeutic Characteristics of GFPT2 in Pan-cancer

Purpose: The purpose of this study is to investigate the underlying relationship of diagnosis and therapy between glutamine-fructose-6-phosphate transaminase 2 (GFPT2) and various cancers. Methods: The Cancer Genome Atlas (TCGA) database was utilized to get gene expression RNAseq and clinical data for 33 tumors. The immunotherapeutic cohorts, including GSE35640, GSE78220, GSE67501, GSE181815, and IMvigor210, were derived from the Gene Expression Omnibus database (GEO) and a previously released article. Differential expression analysis of GFPT2 was performed using several clinical factors, and prognostic analysis was performed using Cox proportional hazard regression. In addition, the Cell type Identification By Estimating Relative Subsets Of RNA transcripts (CIBERSORT) and the Estimation of STromal and Immune cells in MAlignant Tumor tissues utilizing Expression data (ESTIMATE) algorithms were used to investigate the connection between GFPT2 and the tumor microenvironment. This approach additionally incorporated dynamic immunological indicators, such as tumor mutational burden (TMB) and microsatellite instability (MSI). In addition, a correlation between GFPT2 expression and the effectiveness of anticancer drugs was plotted for discussion. Results: GFPT2 expression significantly differed in 11 out of 33 cancers. Although the distinct correlation between GFPT2 expression and clinical parameters had no wide distribution in pan-cancer, it demonstrated the potential prognostic validity of gene expression. GFPT2 demonstrated a strong correlation with immune infiltration, immune modulators, and immunerelated biomarkers. Furthermore, a variance analysis demonstrated a significant relationship between GFPT2 and the efficacy of immunotherapy. In addition, GFPT2 was associated with increased sensitivity of drugs such as Olaparib and Lenvatinib and decreased sensitivity of drugs such as Nilotinib. Conclusion: Collectively, GFPT2 is potentially useful as a biomarker for prognostic prediction and immune infiltration in a variety of malignancies ,and could lead to exciting new approaches to personalized oncotherapy.

Prognosis and immunotherapy significances of a cancer-associated fibroblasts-related gene signature in bladder urothelial carcinoma.

The biological significance of cancer-associated fibroblasts (CAFs) in bladder urothelial carcinoma (BUC) warrants further investigation. There is an urgent need to explore the predictive utility of CAF-related genes for prognosis in BUC. The transcriptome and clinical data of 407BUC patients in The Cancer Genome Atlas (TCGA) database were analyzed and a prognostic model was established. A total of 476 BUC cases from the E-MTAB-4321 database were used for validation. A risk model was constructed utilizing CAF-related genes through LASSO Cox regression, investigating its association with prognosis, gene mutations, immune cell infiltration, and drug sensitivity in BUC. We identified five CAF-related genes (EGFL6, NRSN2, SEMA3D, TM4SF1 and TPST1) in both the TCGA and E-MTAB-4321 datasets, and established a prognostic model using LASSO Cox regression. The high-risk group showed a significant correlation with poor survival. Furthermore, the low-risk group exhibited higher tumor mutational burden and lower levels of immune cell infiltration, and this model holds promise for guiding drug selection in BUC patients. These findings underscore the pivotal role of CAF-related genes in prognostic prediction for BUC patients. Clinical decision-making and tailored therapeutics stand to benefit from these results, providing a valuable reference for future research endeavors.

Exploration on the construction of a bladder cancer prognostic model based on disulfidptosis-related lncRNAs and its clinical significance.

Disulfidptosis is a novel programmed cell death mode that has been reported to play a role in oncogenesis. Increasing evidences suggest that the long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of bladder cancer (BLCA). However, the role and prognostic value of disulfidptosis-related lncRNAs in BLCA remain unknown.The aim of this study was to construct and validate a disulfidptosis-related lncRNA risk model for predicting the prognosis of BLCA patients. A risk model consisting of 5 disulfidptosis-related lncRNAs was developed to predict the prognosis of BLCA patients. The overall survival (OS) of BLCA patients in the high-risk group was significantly shorter than that in the low-risk group (P < 0.05). The effectiveness of this model was validated using the receiver operating characteristic (ROC) curve analysis, and this model proved superior in prognostic accuracy compared with other clinical features. Furthermore, the tumor immune dysfunction and exclusion (TIDE) score in the high-risk group was significantly higher than that in the low-risk group, suggesting that the high-risk group had a less favorable response to immunotherapy. Simultaneously, patients in the low-risk group exhibited significantly higher sensitivity to CTLA-4 monoclonal antibody therapy compared to those in the high-risk group, suggesting potential benefits of immunotherapy for patients in the low-risk group. The combination of high risk and low tumor mutational burden (TMB) could further shortened the OS of BLCA patients. Lastly, the drug sensitivity analysis revealed that the BLCA cells in the high-risk group showed an increased sensitivity to cisplatin, sunitinib, cetuximab, axitinib, docetaxel, saracatinib, vinblastine and pazopanib compared with those in the low-risk group. According to the Quantitative real time PCR results, we found that five lncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line. The disulfidptosis-related lncRNA risk model has a valuable effect in assessing the prognosis of BLCA patients.

Association between tumour somatic mutations and venous thromboembolism in the 100,000 Genomes Project cancer cohort: a study protocol

Venous thromboembolism (VTE) is a common cause of morbidity and mortality in patients with cancer. There is evidence that specific aberrations in tumour biology contribute to the pathophysiology of this condition. We plan to examine the association between tumour somatic mutations and VTE in an existing cohort of patients with cancer, who were enrolled to the flagship Genomics England 100,000 Genomes Project. Here, we outline an a-priori analysis plan to address this objective, including details on study cohort selection, exposure and outcome definitions, annotation of genetic variants and planned statistical analyses. We will assess the effect of 1) deleterious somatic DNA variants in each gene; 2) tumour mutational burden and 3) tumour mutational signatures on the rate of VTE (outcome) in a pan-cancer cohort. Sensitivity analyses will be performed to examine the robustness of any associations, including adjustment for potentially correlated co-variates: tumour type, stage and systemic anti-cancer therapy. We hope that results from this study may help to identify key genes which are implicated in the development of cancer associated thrombosis, which may shed light on related mechanistic pathways and/or provide data which can be integrated into genetic risk prediction models for these patients.

Comprehensive Analysis and Verification of the Prognostic Significance of Cuproptosis-Related Genes in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is a frequently occurring and lethal cancer. Cuproptosis is an emerging type of cell death, and the underlying pathways involved in this process in COAD remain poorly understood. Transcriptomic and clinical data for COAD patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We investigated alterations in DNA and chromatin of cuproptosis-related genes (CRGs) in COAD. In order to identify predictive differentially expressed genes (DEGs) and various molecular subtypes, we used consensus cluster analysis. Through univariate, multivariate, and Lasso Cox regression analyses, four CRGs were identified. A risk prognostic model for cuproptosis characteristics was constructed based on four CRGs. This study also examined the association between the risk score and the tumor microenvironment (TME), the immune landscape, and drug sensitivity. We distinguished two unique molecular subtypes using consensus clustering analysis. We discovered that the clinical characteristics, prognosis, and TME cell infiltration characteristics of patients with multilayer CRG subtypes were all connected. The internal and external evaluations of the predicted accuracy of the prognostic model built using data derived from a cuproptosis risk score were completed at the same time. A nomogram and a clinical pathological analysis make it more useful in the field of medicine. A significant rise in immunosuppressive cells was observed in the high cuproptosis risk score group, with a correlation identified between the cuproptosis risk score and immune cell infiltration. Despite generally poor prognoses, the patients with a high cuproptosis risk but low tumor mutation burden (TMB), cancer stem cell (CSC) index, or microsatellite instability (MSI) may still benefit from immunotherapy. Furthermore, the cuproptosis risk score positively correlated with immune checkpoint gene expression. Analyzing the potential sensitivity to medications could aid in the development of clinical chemotherapy regimens and decision-making. CRGs are the subject of our in-depth study, which exposed an array of regulatory mechanisms impacting TME. In addition, we performed additional data mining into clinical features, prognosis effectiveness, and possible treatment medications. COAD’s molecular pathways will be better understood, leading to more precise treatment options.

Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.

Viruses are widely recognized to be intricately associated with both solid and hematological malignancies in humans. The primary goal of this research is to elucidate the interplay of genes between SARS-CoV-2 infection and lung adenocarcinoma (LUAD), with a preliminary investigation into their clinical significance and underlying molecular mechanisms. Transcriptome data for SARS-CoV-2 infection and LUAD were sourced from public databases. Differentially expressed genes (DEGs) associated with SARS-CoV-2 infection were identified and subsequently overlapped with TCGA-LUAD DEGs to discern the crosstalk genes (CGs). In addition, CGs pertaining to both diseases were further refined using LUAD TCGA and GEO datasets. Univariate Cox regression was conducted to identify genes associated with LUAD prognosis, and these genes were subsequently incorporated into the construction of a prognosis signature using 10 different machine learning algorithms. Additional investigations, including tumor mutation burden assessment, TME landscape, immunotherapy response assessment, as well as analysis of sensitivity to antitumor drugs, were also undertaken. We discovered the risk stratification based on the prognostic signature revealed that the low-risk group demonstrated superior clinical outcomes (p < 0.001). Gene set enrichment analysis results predominantly exhibited enrichment in pathways related to cell cycle. Our analyses also indicated that the low-risk group displayed elevated levels of infiltration by immunocytes (p < 0.001) and superior immunotherapy response (p < 0.001). In our study, we reveal a close association between CGs and the immune microenvironment of LUAD. This provides preliminary insight for further exploring the mechanism and interaction between the two diseases.

Genomic and transcriptomic landscape of human gastrointestinal stromal tumors

Gastrointestinal stromal tumor (GISTs) are clinically heterogenous exhibiting varying degrees of disease aggressiveness in individual patients. We comprehensively describe the genomic and transcriptomic landscape of a cohort of 117 GISTs including 31 low-risk, 18 intermediate-risk, 29 high-risk, 34 metastatic and 5 neoadjuvant GISTs from 105 patients. GISTs have notably low tumor mutation burden but widespread copy number variations. Aggressive GISTs harbor remarkably more genomic aberrations than low-/intermediate-risk GISTs. Complex genomic alterations, chromothripsis and kataegis, occur selectively in aggressive GISTs. Despite the paucity of mutations, recurrent inactivating YLPM1 mutations are identified (10.3%, 7 of 68 patients), enriched in high-risk/metastatic GIST and functional study further demonstrates YLPM1 inactivation promotes GIST proliferation, growth and oxidative phosphorylation. Spatially and temporally separated GISTs from individual patients demonstrate complex tumor heterogeneity in metastatic GISTs. Finally, four prominent subtypes are proposed with different genomic features, expression profiles, immune characteristics, clinical characteristics and subtype-specific treatment strategies. This large-scale analysis depicts the landscape and provides further insights into GIST pathogenesis and precise treatment.

Comprehensive Analysis and Experimental Validation of HEPACAM2 as a Potential Prognosis Biomarker and Immunotherapy Target in Colorectal Cancer.

The role of HEPACAM family member 2 (HEPACAM2) is unclear in colorectal cancer (CRC). The objective of this study was to perform an extensive examination of HEPACAM2 and validate it experimentally in CRC. This study investigated the significance of HEPACAM2 in CRC and its potential diagnostic utility utilizing data from the Cancer Genome Atlas (TCGA) database. Additionally, the study examined potential regulatory networks involving HEPACAM2, including its associations with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB), microsatellite instability (MSI), mRNA expression-based stemness index (mRNAsi), and drug sensitivity in CRC. The expression of HEPACAM2 was further validated using the GSE89076 dataset, and quantitative reverse transcription PCR (qRT-PCR) was employed to confirm HEPACAM2 expression levels in six pairs of CRC tissue samples. HEPACAM2 exhibited abnormal expression patterns in various types of cancer, including CRC. A decrease in HEPACAM2 expression levels in CRC was found to be significantly correlated with the T stage (p < 0.001). Reduced HEPACAM2 expression in CRC patients was also linked to poorer overall survival (OS) (p = 0.007). The expression levels of HEPACAM2 in CRC patients were identified as an independent prognostic factor (p = 0.016). Furthermore, HEPACAM2 was associated with TCF-dependent signaling in response to WNT, G2/M checkpoints, and other pathways. The expression of HEPACAM2 in CRC was found to be associated with immune infiltration, immune checkpoint genes, TMB / MSI, and mRNAsi. Additionally, the expression of HEPACAM2 in CRC was significantly and inversely correlated with the drug sensitivities to gw772405x and 6-phenyl-6h-indeno[1,2-c]isoquinoline-5,11-dione. qRT-PCR confirmed that the expression level of HEPACAM2 was found to be lowly expressed in CRC tissues. These findings suggest that HEPACAM2 may serve as a potential prognostic biomarker and immunotherapeutic target for CRC patients.

Co-mutation of TP53 and TTN is Correlated with the Efficacy of Immunotherapy in Lung Squamous Cell Carcinoma.

Immunotherapy has been a promising treatment in advanced lung cancer. However, only a few patients could benefit from it. Herein, we aimed to explore mutationrelated predictive biomarkers in lung squamous cell carcinoma (LUSC), which could help develop clinical immunotherapy strategies and screen beneficial populations. Co-occurrence and mutually exclusive analysis was conducted on the TCGA-LUSC cohort. Correlations between the gene mutation status and tumor mutation burden (TMB) levels, and neo-antigen levels were analyzed by Wilcoxon test. Kaplan-Meier method was employed to analyze the progression-free survival (PFS) of lung cancer patients with immunotherapy. Gene set enrichment analysis (GSEA) was used to investigate the functional changes affected by TP53mut/TTNmut. The immune cell infiltration landscape in co-mutation subgroups was analyzed using CIBERSORT. 1) TP53, TTN, CSMD3, MUC16, RYR2, LRP1B, USH2A, SYNE1, ZFHX4, FAM135B, KMT2D, and NAV3 were frequently mutated in LUSC patients. 2) TMB levels in highly mutated groups were higher than that in wild type groups. 3) There were higher neoantigen levels in mutation group compared to the wild-type group, and LUSC patients in mutation group had longer PFS. 4) TP53mut/TTNmut co-mutation group exhibited higher TMB levels and better response to immunotherapy. 5) A host of immune-related signaling pathways was inhibited in TP53mut/TTNmut subgroup. 6) There were more T follicular helper cells and NK cells were in TP53mut/TTNmut subgroup than in the WT subgroup. The LUSC patients with TP53 and TTN co-mutation had higher TMB levels and better response to immunotherapy. The TP53 and TTN co-mutation is a promising novel biomarker to assist LUSC immunotherapy evaluation.

Genetic Alterations in Chromatin Regulatory Genes in Upper Tract Urothelial Carcinoma and Urothelial Bladder Cancer

ABSTRACTPurposeUpper tract urothelial carcinoma (UTUC) and urothelial carcinoma of the bladder (UCB) share histomorphological and therapeutic features but distinct epidemiologic and clinicopathologic characteristics. We examined alterations of chromatin regulatory genes in molecular subtypes, clonal relatedness, and T‐cell receptor (TCR) diversity in UTUC and UCB.Materials and MethodsTargeted next‐generation sequencing or whole‐exome DNA sequencing and TCR sequencing were conducted with 34 UTUC and 49 UCB specimens from 63 patients. Tumors were subtyped based on the expression of CK5 and GATA3. Results of tissue microarray of 78 muscle‐invasive bladder cancer (MIBC) samples were used as prognostic factors of different subtypes of MIBC.ResultsChromatin regulatory genes were frequently mutated in both UTUC and UCB. Rapid relapse and progression of non‐MIBC are correlated with alterations of KMT2C and EP300. Frequency of alterations in chromatin regulatory genes is higher in UTUC patients with SBS22 and SBS2 signatures and lower in UCB patients with SBS2 and SBS6 signatures. GATA3 and CK5 double‐positive patients with higher frequencies of SMARCA4, ARID1A, and EP300 mutations have better prognoses than patients with basal subtypes. Although UTUC and UCB in the same patient can be either clonally related or developed independently, mutated genes in chromatin pathway were enriched in the related clones. Compared to UTUC, UCB had more deleterious mutations in DNA damage repair (DDR) genes, higher levels of tumor mutation burden (TMB) and copy number variations (CNVs), as well as higher TCR clonality and lower TCR diversity.ConclusionsSince genetic alterations of the chromatin pathway genes are important in both UTUC and UCB, they could serve as potential biomarkers for predicting disease progression and therapeutic targets. Differences in mutation frequencies of DDR pathway, TMB, CNV, and TCR might be the contributing factors for the distinct responses to immune checkpoint inhibitor (ICI) between UTUC and UCB.

Brief Report: Clinical Characteristics and Outcomes of Patients with Thoracic SMARCA4-Deficient Undifferentiated Tumors

IntroductionThoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UTs) are a recently-defined group of aggressive cancers in which the effectiveness of standard treatments for lung cancer is unknown. MethodsWe collected clinical, pathological, and demographic variables from 5 institutions for patients whose tumors met criteria for SMARCA4-UTs (undifferentiated morphology and loss of SMARCA4/BRG1 by immunohistochemistry). ResultsWe identified 92 patients with SMARCA4-UTs; 58 (63%) had stage IV disease at diagnosis, and 16 (17%) developed recurrent/metastatic disease after initial diagnosis. Median overall survival (OS) from metastatic diagnosis was 7.3 (95% CI: 4.6-12.8) months. Of patients with metastatic disease, 58 (78%) received first-line systemic treatment. Most commonly, patients received chemo/immunotherapy combination (41%), chemotherapy alone (33%), or immunotherapy alone (16%). Median progression-free survival (PFS) from start of systemic therapy was 1.9 (95%CI: 1.4-14.5) months for chemo/immunotherapy, 1.6 (95%CI: 1.1-5.8) months for chemotherapy, and 3.3 (95%CI: 1.2-undefined) months for immunotherapy alone. Five patients had durable responses (≥ 2 years); all received immunotherapy as part of first-line regimens. Nine (16%) of 55 tumor samples tested had PD-L1 expression ≥50%, with 24 (44%) negative samples. Tumor mutational burden was available in 48 cases (52%), median was 10.5 (range 2-48) mutations/megabase. ConclusionsThis multi-institution retrospective cohort analysis revealed a population of patients with short PFS to standard therapies and poor OS. A few patients demonstrated remarkable response to regimens including immunotherapy. Prospective clinical studies are urgently needed to identify better therapeutic approaches to treat this aggressive malignancy and this analysis may serve as a benchmark for future clinical trial design.

Mismatch repair deficiency and tumor mutational burden are associated with higher microbiome diversity in the reproductive tract

Mismatch repair deficiency and tumor mutational burden are associated with higher microbiome diversity in the reproductive tract

Transcriptomic profiles of myxofibrosarcoma and undifferentiated pleomorphic sarcoma correlate with clinical and genomic features.

Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) are two common and aggressive subtypes of soft tissue sarcoma. The aim of this study was to assess potential transcriptomic differences between MFS and UPS tumours and to evaluate the extent to which differences in gene expression profiles were associated with genomic and clinical features. The study included 162 patients with tumours diagnosed as MFS (N = 62) or UPS (N = 100). The patients had been diagnosed and treated at two Swedish sarcoma centres during a 30-year period. For gene expression profiling and gene fusion detection all tumours were analysed using RNA-sequencing and could be compared with data on clinical outcome (N = 155), global copy number profiles (N = 145), and gene mutations (N = 128). Gene expression profiling revealed three transcriptomic clusters (TCs) without any clear separation of MFS and UPS. One TC was associated with longer metastasis-free survival. These tumours had lower tumour mutation burden (TMB), were enriched for a copy number signature representative of focal LOH and chromosomal instability on a diploid background, and were relatively immune-depleted. MFS and UPS showed extensive genomic overlap, with whole genome doubling occurring more frequently among the latter. The results support the idea that MFS and UPS tumours have largely overlapping genomic and transcriptomic features, with UPS tumours showing more aggressive behaviour and more complex genomes. Independently of the tumour type, clinically relevant subgroups were revealed by gene expression analysis, and the finding of multiple genomic subgroups strongly suggest the existence of subgroups of relevance to treatment stratification. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Identification of oxidative stress-related hub genes for predicting prognosis in diffuse large B-cell lymphoma

BackgroundOxidative stress is a cellular characteristic that might induce the proliferation and differentiation of tumor cells and promote tumor progression in diffuse large B-cell lymphoma (DLBCL). MethodsThe DLBCL gene sequencing dataset, tumor mutation burden data, copy number variation data of Somatic cell mutation data in TCGA were downloaded for data training analysis, along with four DLBCL datasets in GEO for validation analysis. The known oxidative stress related genes (OSRGs) were collected from websites. The weighted gene co-expression network analysis (WGCNA) was conducted on the TCGA DLBCL dataset to obtain gene modules related to oxidative stress and intersected with the known OSRGs to obtain the hub genes, which were used to perform consensus clustering on the samples to obtain new phenotypes. Next, the prognosis related OSRGs were selected through regression analysis algorithms and key genes were identified. These genes were used to establish the prognostic risk model and predictive model, and to compare functional and pathway differences among different risk groups. ResultsThrough website search, we obtained 297 known OSRGs, and after intersecting with WGCNA results, we obtained 26 OSRGs. The TCGA-DLBC samples were clustered into 2 subtypes with these genes and there were significant differences in immune infiltration between subtypes. After regression analysis, we obtained a total of four key genes, BMI1, CDKN1A, NOX1, and SESN1. The risk prediction model established with these four genes as variables has accurate prognostic prediction ability. The key genes interact with 65 miRNAs, 57 TFs, 47 RBPs, and 62 drugs, respectively, and are closely related to immune infiltration of the disease. Among them, CDKN1A and SESN1 had the highest variability. ConclusionsThe key genes involved in oxidative stress could predict the prognosis of DLBCL and potentially become therapeutic targets.

Multicenter validation of an RNA-based assay to predict anti-PD-1 disease control in patients with recurrent or metastatic head and neck squamous cell carcinoma: the PREDAPT study.

Despite advances in cancer care and detection, >65% of patients with squamous cell cancer of the head and neck (HNSCC) will develop recurrent and/or metastatic disease. The prognosis for these patients is poor with a 5-year overall survival of 39%. Recent treatment advances in immunotherapy, including immune checkpoint inhibitors like pembrolizumab and nivolumab, have resulted in clinical benefit in a subset of patients. There is a critical clinical need to identify patients who benefit from these antiprogrammed cell death protein 1 (anti-PD-1) immune checkpoint inhibitors. Here, we report findings from a multicenter observational study, PREDicting immunotherapy efficacy from Analysis of Pre-treatment Tumor biopsies (PREDAPT), conducted across 17 US healthcare systems. PREDAPT aimed to validate OncoPrism-HNSCC, a clinical biomarker assay predictive of disease control in patients with recurrent or metastatic HNSCC treated with anti-PD-1 immune checkpoint inhibitors as a single agent (monotherapy) and in combination with chemotherapy (chemo-immunotherapy). The test used RNA-sequencing data and machine learning models to score each patient and place them into groups of low, medium, or high. The OncoPrism-HNSCC prediction significantly correlated with disease control in both the monotherapy cohort (n=62, p=0.004) and the chemo-immunotherapy cohort (n=50, p=0.01). OncoPrism-HNSCC also significantly predicted progression-free survival in both cohorts (p=0.015 and p=0.037, respectively). OncoPrism-HNSCC had more than threefold higher specificity than programmed death-ligand 1 combined positive score and nearly fourfold higher sensitivity than tumor mutational burden for predicting disease control. Here, we demonstrate the clinical validity of the OncoPrism-HNSCC assay in identifying patients with disease control in response to anti-PD-1 immune checkpoint inhibitors. NCT04510129.

Somatic mutational landscape reveals mutational signatures and significantly mutated genes of cancer immunotherapeutic outcome and sex disparities

BackgroundCurrently developed molecular markers can predict the effectiveness of cancer immunotherapy and screen beneficiaries to some extent, but they are not stable enough. Therefore, there is an urgent need for discovering novel biomarkers. At the same time, sex factor plays a vital role in the response to immunotherapy, so it is particularly important to identify sex-related molecular indicators.MethodsWe integrated a pan-cancer cohort consisting of 2348 cancer patients who received immune checkpoint inhibitors and targeted sequencing. Using somatic mutation profiles, we identified mutational signatures, molecular subtypes, and frequently mutated genes, and analyzed their relationships with immunotherapeutic outcomes. We also explored sex disparities of determined biomarkers in response to treatments.ResultsWe found that male patients exhibited better immunotherapy outcomes and higher tumor mutational burden. A total of seven mutational signatures were identified, among which signatures 1 and 3 were associated with worse immunotherapy outcomes, while signatures 2 and 6 correlated with better outcomes. Gender-based analysis revealed that mutational signature 1 continued to show a worse immunotherapy outcome in female patients, whereas signature 6 demonstrated a better outcome in male patients. Based on mutational activities, we identified four potential molecular subtypes with gender differences and relevance to treatment outcomes. PI3K-AKT, RAS signaling pathways, and 68 significantly mutated genes were identified to be associated with immunotherapy outcomes, with nine genes (i.e., ATM, ATRX, DOT1L, EP300, EPHB1, NOTCH1, PBRM1, RBM10, and SETD2) exhibiting gender differences. Finally, we discovered co-mutated gene pairs and TP53 p.R282W mutations related to treatment outcomes, highlighting their gender-specific differences.ConclusionThis study identified several molecular biomarkers related to cancer immunotherapy outcomes in terms of mutational signatures, molecular subtypes, and mutated genes, and explored their gender-relatedness in order to provide clues and basis for clinical treatment efficacy evaluation and patient selection.