Tumor Mutational Burden Research Articles

Single-cell and bulk transcriptomic datasets enable the development of prognostic models based on dynamic changes in the tumor immune microenvironment in patients with hepatocellular carcinoma and portal vein tumor thrombus

BackgroundHepatocellular carcinoma (HCC) patients exhibiting portal vein tumor thrombosis (PVTT) face a high risk of rapid malignant progression and poor outcomes, with this issue being compounded by a lack of effective treatment options. The integration of bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) datasets focused on samples from HCC patients with PVTT has the potential to yield unprecedented insight into the dynamic changes in the tumor microenvironment (TME) and associated immunological characteristics in these patients, providing an invaluable tool for the reliable prediction of disease progression and treatment responses.MethodsscRNA-seq data from both primary tumor (PT) and PVTT cells were downloaded from the Gene Expression Omnibus (GEO) database, while the International Cancer Genome Consortium (ICGC) and Cancer Genome Atlas (TCGA) databases were used to access bulk RNA-seq datasets. scRNA-seq, clustering, GSVA enrichment, mutational profiling, and predictive immunotherapeutic treatment analyses were conducted using these data with the goal of systematically assessing the heterogeneity of PT and PVTT cells and establishing a model capable of predicting immunotherapeutic and prognostic outcomes in patients with HCC.ResultsThese analyses revealed that PVTT cells exhibited patterns of tumor proliferation, stromal activation, and low levels of immune cell infiltration, presenting with immune desert and immune rejection-like phenotypes. PT cells, in contrast, were found to exhibit a pattern of immunoinflammatory activity. Core PVTT-associated genes were clustered into three patterns consistent with the tumor immune rejection and immune desert phenotypes. An established clustering model was capable of predicting tumor inflammatory stage, subtype, TME stromal activity, and patient outcomes. PVTT signature genes were further used to establish a risk model, with the risk scores derived from this model providing a tool to evaluate patient clinicopathological features including clinical stage, tumor differentiation, histological subtype, microsatellite instability status, and tumor mutational burden. These risk scores were also able to serve as an independent predictor of patient survival outcomes, responses to adjuvant chemotherapy, and responses to immunotherapy. In vitro experiments were used to partially validate the biological prediction results.ConclusionThese results offer new insight into the biological and immunological landscape of PVTT in HCC patients, By utilizing individual patient risk scores, providing an opportunity to guide more effective immunotherapeutic interventional efforts.

Clinicopathogenomic analysis of PI3K/AKT/PTEN-altered luminal metastatic breast cancer in Japan.

This rapid communication highlights the correlation between protein kinase B alpha (AKT1)-phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA)- phosphatase and tensin homolog (PTEN) alterations and clinicopathological factors in Japanese patients with metastatic recurrent breast cancer (mBC). This study analyzed 1967 patients with luminal-type breast cancer who underwent cancer gene panel testing. The results demonstrated that AKT pathway alterations, including PI3K/AKT/PTEN, occurred in 1038 (52.8%)cases. Patients with AKT pathway mutations were older (p = 0.002) and had a higher rate of invasive lobular carcinoma (ILC) histology (p = 0.001), progesterone receptor (PgR) positivity (p = 0.006), and bone metastases (p = 0.001), and a lower rate of germline BRCA2 (p < 0.001). Comprehensive genomic profile results demonstrated a higher tumor mutational burden (TMB) (< 0.001) and lower tumor BRCA1/2 expression (< 0.001) in patients with mutations in the AKT pathway. These results are crucial for characterizing candidates for AKT pathway-targeted molecular therapies and conceptualizing optimal treatment strategies. Clinical trial registration: This study is an observational study and is therefore not registered with the clinical trials registration.

Cuproptosis-related lncRNAs emerge as a novel signature for predicting prognosis in prostate carcinoma and functional experimental validation

BackgroundProstate cancer (PCa) is one of the most common malignancies of the urinary system. Cuproptosis, a newly discovered form of cell death. The relationship between cuproptosis-related long non-coding RNAs (ClncRNAs) related to PCa and prognosis remains unclear. This study aimed to explore the clinical significance of novel ClncRNAs in the prognostic assessment of PCa.MethodsClncRNAs and differentially expressed mRNAs linked to these ClncRNAs were identified using Pearson’s correlation and differential expression analyses. A prognostic signature (risk score) comprising three ClncRNAs was established based on multivariable Cox regression analysis. The predictive performance of this ClncRNAs signature was validated using receiver operating characteristic curves and nomograms. Finally, further in vitro cell experiments were conducted for validation, including quantitative polymerase chain reaction (qPCR), western blot (WB), cell proliferation assays, cell migration assays, cell invasion assays, apoptosis, and cell cycle analysis.ResultsWe constructed a prognostic signature of ClncRNAs for PCa comprising three key differentially expressed ClncRNAs(AC010896-1, AC016394-2, and SNHG9). Multivariable Cox regression analysis indicated that clinical staging and risk scores of the ClncRNAs signature were independent prognostic factors for PCa. Compared to other clinical features, the ClncRNAs signature exhibited higher diagnostic efficiency and performed well in predicting the 1-, 3-, and 5-year progression-free intervals (PFIs) for PCa. Notably, in terms of immune activity, PCa patients with high-risk scores exhibited higher tumor mutational burden (TMB) levels, while their Tumor Immune Dysfunction and Exclusion (TIDE) scores were lower than those of PCa patients with low-risk scores. Additionally, in vitro cellular functional experiments, we knocked down SNHG9 that is the most significantly differentially expressed ClncRNA among the three key ClncRNAs. SNHG9 knockdown resulted in a significant increase in G1 phase cells and a decrease in S and G2 phases, indicating inhibition of DNA synthesis and cell cycle progression. Colony formation assays showed reduced clonogenic ability, with fewer and smaller colonies. Western blot analysis revealed the upregulation of the key cuproptosis-related mRNAs FDX1 and DLST. These findings suggested that SNHG9 promotes PCa cell proliferation, migration, and invasion.ConclusionBuilding on the three ClncRNAs, we identified a novel prognostic signature of PCa. The ClncRNA SNHG9 can promote PCa cell proliferation, migration, and invasion.

A Comprehensive Pan-Cancer Analysis of the Mitochondrial Uncoupling Protein UCP2, with a Focus on Sex and Gender-Related Aspects.

Mitochondrial uncoupling protein 2 (UCP2) plays a crucial role in regulating oxidative stress and cellular metabolism, positioning it as an important subject in oncological research. The involvement of UCP2 in cancer is complex and context-dependent, suggesting it as a potential therapeutic target. In this study, we aimed to perform a comprehensive pan-cancer analysis of UCP2, with a particular focus on gender-related malignancies such as breast (BRCA), prostate (PRAD), ovarian (OV), and testicular tumors (TGCT). We analyzed UCP2 expression in The Cancer Genome Atlas (TCGA), examining correlations with prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), immune cell infiltration, immune checkpoint genes, genes involved in steroidogenesis, sex hormone receptor genes, and drug sensitivity. Significant variability in UCP2 expression was observed across cancer types. UCP2 levels were elevated in BRCA and OV but reduced in PRAD and TGCT. High UCP2 expression was associated with a better prognosis in OV and poorer overall survival in PRAD. Furthermore, UCP2 correlated with TMB and MSI in OV, TGCT, and BRCA. UCP2 expression was also linked to immune cell infiltration, immune checkpoint genes, steroidogenic genes, and sex hormone receptor genes, with variable effects depending on cancer type and gender. Additionally, UCP2 also demonstrated sensitivity to specific anticancer drugs. Our findings highlight the interplay between UCP2, immune and hormonal pathways, and drug responseand reveal potential opportunities for new therapeutic combinations, especially in gender-related cancers.

Extramammary Paget's disease treated with of anti-programmed cell death protein 1 therapy after docetaxel therapy failure.

Extramammary Paget's disease (EMPD) is a rare skin cancer with no standard treatment for advanced-stage disease. Although docetaxel-based chemotherapy is common, no standard treatment exists. Pembrolizumab is approved for solid tumors with a high tumor mutation burden (TMB) and/or high microsatellite instability, and nivolumab was approved in Japan in February 2024 for unresectable advanced or recurrent epithelial skin malignancies. However, there is a lack of real-world data regarding the efficacy of anti-programmed cell death protein 1 (PD-1) therapy for EMPD. We present the case details of three EMPD patients treated with anti-PD-1 therapy after docetaxel treatment, with TMB values of 17.8, 14.3, and 5.0 mut/Mb, respectively, and we review similar reported cases. Even in the cases with a high TMB, the response to anti-PD-1 therapy was not sufficient. Most cases involve second-line or later treatments, so further research is needed to determine the precise effectiveness of anti-PD-1 therapy as a first-line treatment.

Integrating single cell and bulk RNA sequencing data identifies RBM17 as a novel response biomarker for immunotherapy in bladder cancer.

Checkpoint inhibitors (CPIs) have been widely applied in the treatment of patients with bladder cancer (BLCA). However, there is still unmet need to dissect response predict biomarkers. To uncover CPI response-related marker genes in cancer cells, we utilized SCISSOR, integrating single-cell RNA and bulk RNA sequencing data. Transcriptomic and clinical data from IMvigor210, UNC-108, and BCAN/HCRN datasets were collected to evaluate and validate the identified biomarkers and signatures. Additionally, we analyzed TCGA-BLCA and local-BLCA RNA-seq data to investigate alternative splicing events (ASEs). Cell viability was assessed in T24 and UMUC3 cells with RBM17 upregulation or downregulation. Through SCISSOR analysis, we discovered that the expression levels of RBM17, TAP1, and PSMB8 were significantly associated with CPI response. Since PSMB8 displayed a highly positive correlation with TAP1, we developed a CPI response score (CRS) signature based on the expression profiles of RBM17 and TAP1. The CRS demonstrated robust predictive capacity in IMvigor210, UNC-108, and BCAN/HCRN datasets and was associated with higher tumor mutational burden (TMB), PD-L1 expression, and unique genomic features. Notably, RBM17 was not linked to the clinical outcomes of BLCA patients but positively correlated with BLCA cell proliferation in vitro. In the meantime, RBM17 was correlated with higher activity in core biological pathways, including antigen processing machinery, CD8 + T effector cells, cell cycle, DNA damage repair, epithelial-mesenchymal transition, histone regulation, and immune checkpoints. Moreover, the high-RBM17 group showed enrichment of LumU/Ba/sq subtypes but fewer FGFR3 alterations. Lastly, RBM17 significantly upregulated ASEs in BLCA samples, leading to higher neoantigen levels, a more inflamed tumor microenvironment, and improved CPI response. RBM17 is associated with higher ASEs and neoantigen levels, thereby potentiating the efficacy of CPI in BLCA. The established predictive signature, utilizing only two genes, has the potential to streamline clinical applications, providing a cost-effective alternative to expensive genomic, transcriptomic, and biological feature tests.

Identification and validation of M2 macrophage-related gene signature as a novel prognostic model for head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor. Commonly used tumor staging don’t sufficiently and accurately assess the prognosis of HNSCC patients, resulting in a lack of guidance for clinical treatment decisions. M2 macrophage infiltration has been shown to be strongly associated with the tumor prognosis. In this study, we used the Cancer Genome Atlas (TCGA) data to screen for genes co-expressed with M2 macrophages in HNSCC. We used univariate Cox regression to screen out the genes associated with HNSCC prognosis, and constructed a HNSCC prognosis model by Lasso regression analysis. The results confirmed that the model had good predictive value and accuracy for the prognosis of HNSCC patients by survival analysis, ROC curve and nomogram. We divided the HNSCC samples into high-risk and low-risk groups according to the risk score, and the results showed that patients in the high-risk group were more prone to genetic mutations and had a higher tumor mutational burden. In addition, there were significant differences between risk groups in terms of immune cell infiltration and drug sensitivity. The HNSCC prognostic model established in this study may provide guidance for clinical therapeutic decision-making and provide a theoretical foundation for the development of new immunotherapy methods.

Ubiquitin-related gene markers predict immunotherapy response and prognosis in patients with epithelial ovarian carcinoma

Epithelial ovarian carcinoma (EOC) is the most fatal among female reproductive system tumors. The immune tumor microenvironment and ubiquitin-proteasome pathway are closely related to the proliferation, invasion, and response to chemotherapy in EOC. However, their specific roles in EOC have not been fully elucidated. Therefore, we aimed to recognize potential prognostic markers and novel therapeutic targets for EOC. We constructed the ubiquitin-related signature risk model comprising HSP90AB1, FBXO9, SIGMAR1, STAT1, SH3KBP1, EPB41L2, DNAJB6, VPS18, PPM1G, AKAP12, FRK, and PYGB, specifically for patients with EOC. The high-risk model presented a worse prognosis, primarily associated with the B-cell receptor signaling pathway, ECM receptor interaction, focal adhesion, and actin cytoskeleton regulations. Analysis of the immune landscape revealed a higher abundance of B cells, M2 macrophages, neutrophil CD4 T cells, cancer-associated fibroblasts, macrophage neutrophils, and fibroblasts in the high-risk group. It also exhibited lower tumor mutation burden, mRNAsi, and EREG-mRNAsi and reduced sensitivity to other chemotherapy drugs, except dasatinib. These findings serve as a valuable indicator for personalized treatment strategies and clinical stratification in managing patients with EOC. Additionally, our study will serve as a foundation for future mechanistic research to explore the association between the ubiquitin-proteasome pathway and EOC.

Prognosis prediction of head and neck squamous cell carcinoma through the basement membrane-related lncRNA risk model

BackgroundHead and neck squamous cell carcinoma (HNSCC) ranks among the most widespread and significantly heterogeneous malignant tumors globally. Increasing evidence suggests that the basement membrane (BM) and associated long non-coding RNAs (lncRNA) are correlated with the onset of HNSCC and its prognosis. Our study aims to construct a basement membrane-associated lncRNAs (BMlncRNAs) marker to accurately predict the prognosis of HNSCC patients and find novel immunotherapy targets.MethodsThe Cancer Genome Atlas (TCGA) database was accessed to acquire the transcriptome expression matrices, somatic mutation data, and clinical follow-up data of HNSCC patients. Utilizing co-expression analysis, the BMlncRNAs were identified and the differentially expressed lncRNAs (DEBMlncRNA) were then filtered, The filtering thresholds are FDR&amp;lt;0.05 and |log2FC|≥1. Furthermore, univariate analysis, least absolute shrinkage and selection operator (LASSO), and multivariable Cox regression were utilized to develop the risk model. The model then underwent thorough evaluation across diverse perspectives, encompassing tumor immune infiltration, tumor mutation burden (TMB), functional enrichment, and chemotherapy sensitivity.ResultsThe risk assessment model consists of 14 BMlncRNA pairs. The acquired data is indicative of the reliability of the risk score in its capacity as a prognostic factor. Individuals at high risk exhibited a poorer prognosis, and a statistically significant variance was noted in TMB and tumor immune infiltration compared to the low-risk group. Additionally, heightened sensitivity to paclitaxel and docetaxel was evident in the patients at high risk.ConclusionWe have established a BMLncRNA-based prognostic model that can provide clinical guidance for future laboratory and clinical studies of HNSCC.

Locoregional event or dyssynchronous distant metastasis: clinicopathological and molecular analysis of contralateral axillary lymph node metastasis in breast cancer patients.

Contralateral axillary lymph node metastasis (CAM) is a rare clinical condition in patients with breast cancer (BC). CAM can be either a locoregional event or a distant metastasis. Molecular application for clonal evolution in BC has not been reported in CAM cases. We studied six patients with CAM with clinical, pathological and/or molecular evidence of distant metastasis; those patients had poor outcomes. Two cases with molecular analysis of paired primary and CAM established clonal evolution of the CAM with its corresponding primary with additional molecular alteration, increased tumour mutation burden, and copy number variations (CNVs) in the CAMs. Four cases containing alterations from genes potentially modulate chromatin organization, supporting chromatin and subsequent transcriptional signature changes are essential in CAM. Molecular analysis is critical to establish the connection between CAM and its primary counterpart. Distant CAM shows clonal evolution compared with its corresponding primary with additional molecular alterations, increased mutation burden and/or copy number variations. CAM should be evaluated individually and handled in a personalized fashion. Evidence of a true metastatic CAM can be supported by distant metastasis to other organs, specific morphological features and/or clonal evolution.

Identification of three subtypes of ovarian cancer and construction of prognostic models based on immune-related genes

BackgroundImmunotherapy has revolutionized the treatment of ovarian cancer (OC), but different immune microenvironments often constrain the efficacy of immunotherapeutic interventions. Therefore, there is an imperative to delineate novel immune subtypes for development of efficacious immunotherapeutic strategies.MethodsThe immune subtypes of OC were identified by consensus cluster analysis. The differences in clinical features, genetic mutations, mRNA stemness (mRNAsi) and immune microenvironments were analyzed among subtypes. Subsequently, prognostic risk models were constructed based on differentially expressed genes (DEGs) of the immune subtypes using weighted correlation network analysis.ResultsOC patients were classified into three immune subtypes with distinct survival rates and clinical features. Different subtypes exhibited varying tumor mutation burdens, homologous recombination deficiencies, and mRNAsi levels. Significant differences were observed among immune subtypes in terms of immune checkpoint expression and immunogenic cell death. Prognostic risk models were validated as independent prognostic factors demonstrated great predictive performance for survival of OC patients.ConclusionIn this study, three distinct immune subtypes were identified based on gene sets related to vaccine response, with the C2 subtype exhibiting significantly worse prognosis. While no statistically significant differences in tumor mutation burden (TMB) were observed across the three subtypes, the homologous recombination deficiency (HRD) score and mRNA stemness index (mRNAsi) were notably elevated in the C2 group compared to the others. Immune infiltration analysis indicated that the C2 subtype may have an increased presence of regulatory T (Treg) cells, potentially contributing to a more favorable response to combination therapies involving PARP inhibitors and immunotherapy. These findings offer a precision medicine approach for tailoring immunotherapy in ovarian cancer patients. Moreover, the C3 subtype demonstrated significantly lower expression levels of immune checkpoint genes, a pattern validated by independent datasets, and associated with a better prognosis. Further investigation revealed that the immune-related gene FCRL5 correlates with ovarian cancer prognosis, with in vitro experiments showing that it influences the proliferation and migration of the ovarian cancer cell line SKOV3.

Comprehensive multi-omics integration uncovers mitochondrial gene signatures for prognosis and personalized therapy in lung adenocarcinoma

The therapeutic efficacy of lung adenocarcinoma (LUAD), the most prevalent histological subtype of primary lung cancer, remains inadequate, with accurate prognostic assessment posing significant challenges. This study sought to elucidate the prognostic significance of mitochondrial-related genes in LUAD through an integrative multi-omics approach, aimed at developing personalized therapeutic strategies. Utilizing transcriptomic and single-cell RNA sequencing (scRNA-seq) data, alongside clinical information from publicly available databases, we first applied dimensionality reduction and clustering techniques to the LUAD single-cell dataset, focusing on the subclassification of fibroblasts, epithelial cells, and T cells. Mitochondrial-related prognostic genes were subsequently identified using TCGA-LUAD data, and LUAD cases were stratified into distinct molecular subtypes through consensus clustering, allowing for the exploration of gene expression profiles and clinical feature distributions across subtypes. By leveraging an ensemble of machine learning algorithms, we developed an Artificial Intelligence-Derived Prognostic Signature (AIDPS) model based on mitochondrial-related genes and validated its prognostic accuracy across multiple independent datasets. The AIDPS model demonstrated robust predictive power for LUAD patient outcomes, revealing significant differences in responses to immunotherapy and chemotherapy, as well as survival outcomes between risk groups. Furthermore, we conducted comprehensive analyses of tumor mutation burden (TMB), immune microenvironment characteristics, and genome-wide association study (GWAS) data, providing additional insights into the mechanistic roles of mitochondrial-related genes in LUAD pathogenesis. This study not only offers a novel approach to improving prognostic assessments in LUAD but also establishes a strong foundation for the development of personalized therapeutic interventions.

Non-B DNA-informed mutation burden as a marker of treatment response and outcome in cancer.

Genomic instability is crucial in tumorigenesis, with Tumour Mutation Burden (TMB) being a biomarker to indicate therapeutic effectiveness, particularly in immunotherapy. However, TMB is not always a reliable predictor and displays heterogeneity. Non-B DNA, susceptible to mutations, play a significant role in cancer development, indicating their potential merit when combined with mutation for enhanced markers in cancer. We assessed mutations and non-B DNA interplay as biomarkers. Our methodology quantifies tumour mutations and their co-localization with non-B DNA, using survival and drug sensitivity assessments for clinical relevance. We introduce two novel markers, 'nbTMB' (non-B-informed tumour mutation burden) and 'mlTNB' (mutation-localised tumour non-B burden). In case studies: (1) nbTMB informs on survival heterogeneity among TMB-high patients undergoing immunotherapy whereas TMB is unable to further differentiate; (2) nbTMB informs on altered cisplatin sensitivity among ovarian cancer cell lines whereas TMB is unable to differentiate; and (3) mlTNB informs on survival heterogeneity among early-stage pancreatic cancer progressors in whom other markers of genomic instability fail to differentiate. These novel markers offer a nuanced approach to enhance our understanding of treatment responses and outcomes in cancer, underscoring the need for a comprehensive exploration of the interplay between non-B and B-DNA features.

MEF2C is a Potential Prognostic Biomarker and is Correlated with Immune Infiltrates in Lung Adenocarcinoma.

The role of Myocyte Enhancer Factor 2 C (MEF2C) in lung adenocarcinoma (LUAD) is unclear. To address this gap in knowledge, we employed bioinformatics analysis and experimental validation in this study. This study investigated MEF2C expression across a spectrum of cancers, with a specific focus on lung adenocarcinoma (LUAD), utilizing Cancer Genome Atlas (TCGA) data to assess its potential as a diagnostic marker. The study also investigated correlations between MEF2C expression and clinical traits and prognostic indicators of LUAD. Additionally, this study also delved into the regulatory mechanisms of MEF2C, examining its connections to immune system interactions, immune checkpoint genes, tumor mutational burden (TMB), and the sensitivity of LUAD to various drugs. Through single-cell sequencing of LUAD cells and genetic variation of MEF2C in LUAD, we explored the expression of MEF2C in cell lines and verified it by quantitative real-time PCR (qRT-PCR). MEF2C exhibited aberrant expression in both pan-cancer and LUAD. In individuals with LUAD, diminished levels of MEF2C expression were notably linked to the effectiveness of primary therapy outcome (p = 0.025), gender (p < 0.001), and the subdivision of anatomic neoplasms 2 (p = 0.011). A decline in MEF2C levels was also found to be significantly related to reduced overall survival (OS) in LUAD patients (p = 0.026). The presence of MEF2C was recognized as a standalone factor predictive of prognosis in LUAD (p = 0.029). MEF2C was found to be involved in multiple biological pathways, such as those involving cell adhesion molecules. Additionally, its expression was correlated with the extent of immune cell presence, the activity of immune checkpoint genes, and TMB in LUAD. Notably, an inverse relationship was observed between MEF2C expression and the sensitivity to several agents, including Topotecan, Irinotecan, Panobinostat, Nilotinib, and Tp38-279, within the context of LUAD. Furthermore, MEF2C was found to be significantly negatively regulated in LUAD cell lines. The results imply that MEF2C could be a valuable indicator for predicting outcomes and a possible target for immunotherapy for LUAD patients.

MRI-based radiomics model for predicting endometrial cancer with high tumor mutation burden.

To evaluate the performance of MRI-based radiomics in predicting endometrial cancer (EC) with a high tumor mutation burden (TMB-H). A total of 122 patients with pathologically confirmed EC (40 TMB-H, 82 non-TMB-H) were included in this retrospective study. Patients were randomly divided into training and testing cohorts in a ratio of 7:3. Radiomics features were extracted from sagittal T2-weighted images and contrast-enhanced T1-weighted images. Then, the logistic regression (LR), random forest (RF), and support vector machine (SVM) algorithms were used to construct radiomics models. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic performance of each model, and decision curve analysis was used to determine their clinical application value. Four radiomics features were selected to build the radiomics models. The three models had similar performance, achieving 0.771 (LR), 0.892 (RF), and 0.738 (SVM) in the training cohort, and 0.787 (LR), 0.798 (RF), and 0.777 (SVM) in the testing cohort. The decision curve demonstrated the good clinical application value of the LR model. The MRI-based radiomics models demonstrated moderate predictive ability for TMB-H EC and thus may be a tool for preoperative, noninvasive prediction of TMB-H EC.

Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma

BackgroundAberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited.MethodsWe developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA). This signature was validated using six independent LUAD datasets from the Gene Expression Omnibus (GEO). Patients were classified into high- and low-risk groups, and overall survival (OS) was compared by Kaplan-Meier analysis. The signature’s independence as a prognostic indicator was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis validated the signature. Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.ResultsLow-risk group patients exhibited decreased OS. The signature was an independent prognostic indicator and demonstrated strong risk-stratification utility for disease relapse/progression. ROC analysis confirmed the signature’s validity across validation sets. TIME analysis revealed higher infiltration of CD8+ T cells, natural killers, and B cells, and lower tumor purity, stemness index, and tumor mutation burden (TMB) in low-risk patients. These patients also showed elevated T cell receptor richness and diversity, along with reduced immune cell senescence. High-risk patients exhibited enrichment in pathways related to resistance to immune checkpoint blockades, such as DNA repair, hypoxia, epithelial-mesenchymal transition, and the G2M checkpoint. LUAD patients receiving anti-PD-1 treatment had lower risk scores among responders compared to non-responders. MOGAT2 was expressed at higher levels in low-risk LUAD patients. Functional assays revealed that MOGAT2 knockdown in H1299 cells promoted proliferation and migration, induced G2 cell cycle arrest, and decreased apoptosis.ConclusionsThis FAM-related gene signature provides a valuable tool for prognostic stratification and monitoring of TIME and immunotherapy responses in LUAD. MOGAT2 is identified as a potential anti-tumor regulator, offering new insights into its role in LUAD pathogenesis.

Cyclin-Dependent Kinase 4/6 Inhibition as a Novel Therapy for Peritoneal Mucinous Carcinomatosis With GNAS Mutations.

Mucinous neoplasms of the gastrointestinal tract are characterized by a propensity for metastasis to the peritoneum, resulting in peritoneal mucinous carcinomatosis (PMC). A subset of these tumors, most often originating in the appendix, harbor mutations in the GNAS oncogene. While the natural history of GNAS-mutant PMC varies, patient outcomes are generally poor, as is response to cytotoxic chemotherapy. The purpose of this study was to evaluate the clinical efficacy of single-agent palbociclib, a cyclin-dependent kinase (CDK)4/6 inhibitor, in patients with GNAS-mutant PMC. We enrolled 16 patients with PMC in a single-arm personalized cancer therapy trial. For all patients, tumor tissue and/or circulating tumor DNA genomic profiling using next-generation sequencing and, when possible, PD-L1 expression, tumor mutational burden, and microsatellite instability status was assessed. Twelve of 16 patients had previous disease progression on at least one previous line of chemotherapy. The primary tumor was appendix in 13 patients, unknown in two patients, and pancreas in one patient. Eleven cases were classified as low grade, and five as high grade. In 13 of 16 patients, we observed a decrease in carcinoembryonic antigen (CEA), and in six patients, the CEA declined by >50%. As measured by clinical and modified peritoneal RECIST criteria, 50% of evaluable patients had stable disease after 12 months of palbociclib. At a median follow-up of 17.6 months, median survival has not been reached. Clinical response to CDK4/6 inhibition was mirrored in tumors with GNAS mutation and mucinous histology using an ex vivo preclinical platform. CDK4/6 inhibition with palbociclib had clinical activity in PMC characterized by mutations in GNAS that was superior to that previously reported with cytotoxic chemotherapy. CDK4/6 inhibition is a novel therapeutic strategy worthy of further evaluation in this subgroup of gastrointestinal neoplasms.

Pan-cancer analysis of Sp1 with a focus on immunomodulatory roles in gastric cancer

BackgroundSp1, a transcription factor, regulates essential cellular processes and plays important tumorigenic roles across diverse cancers. However, comprehensive pan-cancer analyses of its expression and potential immunomodulatory roles remain unexplored.MethodsUtilizing bioinformatics tools and public datasets, we examined the expression of Sp1 across normal tissues, tumors, and immune cells, and screened for pre- and post-transcriptional modifications, including genetic alterations, DNA methylation, and protein phosphorylation, affecting its expression or function. The association of Sp1 expression with immune cell infiltration, tumor mutational burden, and immune checkpoint signaling was also investigated. Single-cell transcriptome data was used to assess Sp1 expression in immune cells in gastric cancer (GC), and findings were corroborated using immunohistochemistry and multiplex immunofluorescence in an immunotherapy-treated patient cohort. The prognostic value of Sp1 in GC patients receiving immunotherapy was evaluated with Cox regression models.ResultsElevated Sp1 levels were observed in various cancers compared to normal tissues, with notable prominence in GC. High Sp1 expression correlated with advanced stage, poor prognosis, elevated tumor mutational burden (TMB), and microsatellite instability (MSI) status, particularly in GC. Significant correlations between Sp1 levels and CD8+ T cell and the M1 phenotype of tumor-associated macrophages were further detected upon multiplex immunofluorescence in GC samples. Interestingly, we verified that GC patients with higher Sp1 levels exhibited improved response to immunotherapy. Moreover, Sp1 emerged as a prognostic and predictive biomarker for GC patients undergoing immunotherapy.ConclusionsOur pan-cancer analysis sheds light on the multifaceted role of Sp1 in tumorigenesis and underscores its potential as a prognostic and predictive biomarker for patients with GC undergoing immunotherapy.

Advancing Precision Oncology: Whole-Exome Sequencing in Endometrial Cancer Liquid-Based Cytology.

Diagnostic strategies for endometrial cancer have been evolving, with cytologic analysis being considered a key method in integrated oncologic diagnostics because of its less invasive nature and adaptability to various assessments. Liquid-based cytology (LBC) has emerged as a promising method for intact DNA preservation; it exhibits improved efficiency in advanced sequencing applications such as next-generation sequencing. However, despite the use of LBC in panel assays, its application in whole-exome sequencing (WES) for comprehensive genomic profiling remains underexplored. To investigate whether molecular classification is possible based on WES using DNA derived from LBC specimens. We combined WES with targeted gene panel analysis to compare genomic findings of LBC and traditional tissue samples obtained from 7 cases of endometrial cancer. We investigated pathogenic mutations, tumor mutational burden, and microsatellite instability, and achieved molecular classification with high accuracy. We found a substantial concordance between LBC and traditional tissue samples in terms of pathogenic mutation detection, with a 95% match in the LBC samples and 94% in the tissue samples. Notably, our results highlight the importance of combining WES with panel-based analysis in identifying the ultramutated status of a case that had been missed during panel analysis. Our findings emphasize the potential of LBC samples in the precise and noninvasive genomic analysis of cases of endometrial cancer and offer a new avenue for developing diagnostic and therapeutic strategies in precision oncology.

Obesity and survival in advanced non-small cell lung cancer patients treated with chemotherapy, immunotherapy, or chemoimmunotherapy: a multicenter cohort study

BackgroundThe association of body mass index (BMI) with survival outcomes in patients with advanced non-small cell lung cancer (NSCLC) treated with first-line chemotherapy, immunotherapy, or chemoimmunotherapy is controversial. We aimed to investigate these associations, including associations in male and female patients specifically, in a multicenter cohort study.MethodsWe retrospectively analyzed data from seven cohorts comprising 7021 advanced non-small cell lung cancer patients who received chemotherapy (three cohorts), immunotherapy (two cohorts), and chemoimmunotherapy (two cohorts) from five data sources, including a de-identified nationwide (US-based) NSCLC clinico-genomic database and two randomized, double-blind, phase 3 clinical trials. BMI was categorized as underweight, normal weight, overweight, or obese. Underweight patients were excluded because of their small proportion. The primary endpoints were the associations between BMI and progression-free survival (PFS) and overall survival (OS) stratified by treatment type and sex, which were assessed using Kaplan–Meier methods and adjusted Cox modeling. Meta-analyses were performed to combine the adjusted hazard ratios.ResultsIn the pooled analysis, obesity was significantly associated with improved OS in patients receiving chemotherapy (hazard ratios [HR] = 0.84, 95% confidence interval (CI) 0.76–0.93), but there was no association with PFS (HR = 0.91, 95% CI 0.82–1.02). The association of BMI with OS for patients receiving chemotherapy differed by sex, with an inverse association in men (HR = 0.74, 95% CI 0.64–0.84), but no association observed in women (HR = 0.96, 95% CI 0.81–1.13, Pinteraction = 0.018). No impact of BMI on OS or PFS was detected in patients receiving immunotherapy or chemoimmunotherapy. Obese patients had the lowest level of tumor mutational burden, similar level of programmed death-ligand 1 expression and ESTIMATE scores.ConclusionsObesity may be associated with an increased overall survival among male patients treated with chemotherapy, whereas not associated with the outcomes in patients treated with immunotherapy or chemoimmunotherapy.