Tumor Mutational Load Research Articles

Salivary biomarkers: a promising approach for predicting immunotherapy response in head and neck cancers.

Head and neck cancers, including cancers of the mouth, throat, voice box, salivary glands, and nose, are a significant global health issue. Radiotherapy and surgery are commonly used treatments. However, due to treatment resistance and disease recurrence, new approaches such as immunotherapy are being explored. Immune checkpoint inhibitors (ICIs) have shown promise, but patient responses vary, necessitating predictive markers to guide appropriate treatment selection. This study investigates the potential of non-invasive biomarkers found in saliva, oral rinses, and tumor-derived exosomes to predict ICI response in head and neck cancer patients. The tumor microenvironment significantly impacts immunotherapy efficacy. Oral biomarkers can provide valuable information on composition, such as immune cell presence and checkpoint expression. Elevated tumor mutation load is also associated with heightened immunogenicity and ICI responsiveness. Furthermore, the oral microbiota may influence treatment outcomes. Current research aims to identify predictive salivary biomarkers. Initial studies indicate that tumor-derived exosomes and miRNAs present in saliva could identify immunosuppressive pathways and predict ICI response. While tissue-based markers like PD-L1 have limitations, combining multiple oral fluid biomarkers could create a robust panel to guide treatment decisions and advance personalized immunotherapy for head and neck cancer patients.

Exploring Shared Genetic Features and Molecular Mechanisms between Non-Alcoholic Steatohepatitis and Hepatocellular Carcinoma through Bioinformatics.

Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors in the world, characterized by high incidence, high malignancy, and low survival rate. Currently, 1/4 of adults in the world suffer from Non-Alcoholic Fatty Liver Disease (NAFLD), with an incidence rate of 27% in Asia. We used TCGA and GEO public database data sets to conduct weighted gene coexpression network analysis to identify relevant gene modules, defined the intersection of tumorigenesis-related modules and NASH development-related modules as shared genes, and then used single-factor Cox, LASSO, and multivariate Cox regression analysis screened out core shared genes and verified their prognostic value. We further investigated the relationship between core shared genes and immune infiltration, tumor mutational load, and drug sensitivity. Finally, RT-qPCR was used to verify its mRNA expression in different cell lines. We identified Karyopherin α 2 (KPNA2) as the core shared gene between NASH and HCC. Patients were divided into low-risk groups and high-risk groups based on the expression of KPNA2. The prognosis of the low-risk group was significantly better than that of the highrisk group. Furthermore, we found significant differences in tumor immune cell infiltration, somatic mutations, microsatellite instability, and drug sensitivity between different expression groups. There are very few studies on the molecular mechanism of the relationship between NAFLD and HCC. Our study demonstrates that KPNA2 is a potential therapeutic target and immune-related biomarker for patients with NAFLD and HCC.

Molecular subtypes and prognostic models for predicting prognosis of lung adenocarcinoma based on miRNA-related genes.

MicroRNAs (miRNAs) are crucial in cancer development and progression, and therapies targeting miRNAs demonstrate great therapeutic promise. We sought to predict the prognosis and therapeutic response of lung adenocarcinoma (LUAD) by classifying molecular subtypes and constructing a prognostic model based on miRNA-related genes. This study was based on miRNA-mRNA action pairs and ceRNA networks in the Cancer Genome Atlas (TCGA) database. Three molecular subtypes were determined based on 64 miRNA-associated target genes identified in the ceRNA network. The S3 subtype had the best prognosis, and the S2 subtype had the worst prognosis. The S2 subtype had a higher tumor mutational load (TMB) and a lower immune score. The S2 subtype was more suitable for immunotherapy and sensitive to chemotherapy. The least absolute shrinkage and selection operator (LASSO) algorithm was performed to determine eight miRNA-associated target genes for the construction of prognostic models. High-risk patients had a poorer prognosis, lower immune score, and lower response to immunotherapy. Robustness was confirmed in the Gene-Expression Omnibus (GEO) database cohort (GSE31210, GSE50081, and GSE37745 datasets). Overall, our study deepened the understanding of the mechanism of miRNA-related target genes in LUAD and provided new ideas for classification. Such miRNA-associated target gene characterization could be useful for prognostic prediction and contribute to therapeutic decision-making in LUAD.

Identification of telomere-related lncRNAs and immunological analysis in ovarian cancer.

Ovarian cancer (OC) is a global malignancy characterized by metastatic invasiveness and recurrence. Long non-coding RNAs (lncRNAs) and Telomeres are closely connected with several cancers, but their potential as practical prognostic markers in OC is less well-defined. Relevant mRNA and clinical data for OC were sourced from The Cancer Genome Atlas (TCGA) database. The telomere-related lncRNAs (TRLs) prognostic model was established by univariate/LASSO/multivariate regression analyses. The effectiveness of the TRLs model was evaluated and measured via the nomogram. Additionally, immune infiltration, tumor mutational load (TMB), and drug sensitivity were evaluated. We validated the expression levels of prognostic genes. Subsequently, PTPRD-AS1 knockdown was utilized to perform the CCK8 assay, colony formation assay, transwell assay, and wound healing assay of CAOV3 cells. A six-TRLs prognostic model (PTPRD-AS1, SPAG5-AS1, CHRM3-AS2, AC074286.1, FAM27E3, and AC018647.3) was established, which can effectively predict patient survival rates and was successfully validated using external datasets. According to the nomogram, the model could effectively predict prognosis. Furthermore, we detected the levels of regulatory T cells and M2 macrophages were comparatively higher in the high-risk TRLs group, but the levels of activated CD8 T cells and monocytes were the opposite. Finally, the low-risk group was more sensitive to anti-cancer drugs. The mRNA levels of PTPRD-AS1, SPAG5-AS1, FAM27E3, and AC018647.3 were significantly over-expressed in OC cell lines (SKOV3, A2780, CAOV3) in comparison to normal IOSE-80 cells. AC074286.1 were over-expressed in A2780 and CAOV3 cells and CHRM3-AS2 only in A2780 cells. PTPRD-AS1 knockdown decreased the proliferation, cloning, and migration of CAOV3 cells. Our study identified potential biomarkers for the six-TRLs model related to the prognosis of OC.

APOBEC family reshapes the immune microenvironment and therapy sensitivity in clear cell renal cell carcinoma

Emerging evidence suggests that the APOBEC family is implicated in multiple cancers and might be utilized as a new target for cancer detection and treatment. However, the dysregulation and clinical implication of the APOBEC family in clear cell renal cell cancer (ccRCC) remain elusive. TCGA multiomics data facilitated a comprehensive exploration of the APOBEC family across cancers, including ccRCC. Remodeling analysis classified ccRCC patients into two distinct subgroups: APOBEC family pattern cancer subtype 1 (APCS1) and subtype 2 (APCS2). The study investigated differences in clinical parameters, tumor immune microenvironment, therapeutic responsiveness, and genomic mutation landscapes between these subtypes. An APOBEC family-related risk model was developed and validated for predicting ccRCC patient prognosis, demonstrating good sensitivity and specificity. Finally, the overview of APOBEC3B function was investigated in multiple cancers and verified in clinical samples. APCS1 and APCS2 demonstrated considerably distinct clinical features and biological processes in ccRCC. APCS1, an aggressive subtype, has advanced clinical stage and a poor prognosis. APCS1 exhibited an oncogenic and metabolically active phenotype. APCS1 also exhibited a greater tumor mutation load and immunocompromised condition, resulting in immunological dysfunction and immune checkpoint treatment resistance. The genomic copy number variation of APCS1, including arm gain and loss, was much more than that of APCS2, which may help explain the tired immune system. Furthermore, the two subtypes have distinct drug sensitivity patterns in clinical specimens and matching cell lines. Finally, we developed a predictive risk model based on subtype biomarkers that performed well for ccRCC patients and validated the clinical impact of APOBEC3B. Aberrant APOBEC family expression patterns might modify the tumor immune microenvironment by increasing the genome mutation frequency, thus inducing an immune-exhausted phenotype. APOBEC family-based molecular subtypes could strengthen the understanding of ccRCC characterization and guide clinical treatment. Targeting APOBEC3B may be regarded as a new therapeutic target for ccRCC.

Identification of E3 ubiquitin ligase-associated prognostic genes and construction of a prediction model for uterine cervical cancer based on bioinformatics analysis

E3 ligases are engaged in a variety of physiological processes within cells and use ubiquitin-labeled substrates to control their activity and stability. Although some research has indicated that E3 ligases or particular substrates have an impact on the treatment that cervical cancer patients get after their diagnosis, The exact purpose of these enzymes in the occurrence and evolution of cancer of the cervical region (CC) is not clear. In order to extract and analyze relevant mRNA gene expression data as well as clinical patient data, we used open databases. A reliable risk prediction model was developed by applying the least absolute shrinkage and selection operator (LASSO) technique in conjunction with Cox regression analysis. Column-line plots were combined to analyze the predictive model, and the GSE44001 dataset served as an external validation.Four gene models:proteasome (prosome, macropain) 26S subunit, non-ATPase, 14(PSMD14),proteasome (prosome, macropain) subunit, alpha type, 4(PSMA4,),zinc finger and BTB domain containing 16(ZBTB16),and ankyrin repeat domain 9(ANKRD9). Gene expression levels in both healthy and cancerous tissues have been confirmed by the HPA database. Next, the investigation focused on immunological state and tumor mutation load. The high-risk group and Cluster B had distinct levels of immune cell infiltration and a worse prognosis. Additionally, KEGG and GO analyses of differentially expressed genes (DEGs) between the high- and low-risk groups were performed, as well as tumor microenvironment (TME) investigations. Targeting E3 ligases may be an efficient strategy to treat cervical cancer (CC), according to a novel and comprehensive E3 ubiquitination ligase-associated gene model that has been presented.

PLCG2, A Regulator of Lung Adenocarcinoma Proliferation and Migration Associated with Immune Infiltration.

Results from the TCGA database showed that phosphatidylinositol-specific phospholipase Cγ2 (PLCG2) expression level in Lung Adenocarcinoma (LUAD) was notably decreased compared to adjacent tissues, so we unveiled its role of LUAD. This study aims to explore the expression and clinical significance of Phosphatidyl-inositol-specific phospholipase Cγ2 (PLCG2) in lung adenocarcinoma (LUAD) cells and its role in cell proliferation and metastasis. Differential PLCG2 mRNA and protein levels between LUAD tissues and adjacent tissues were analyzed from the TCGA database, TIMER, and UALCAN database. Differentially expressed genes were screened for patients in the high and low PLCG2 mRNA expression groups by the R package as well as GSEA. The expression level of PLCG2 in LUAD cells was detected using qRT-PCR and CCK8, clone formation, Transwell, and Western blot assays. PLCG2 was lowly expressed in LUAD and did not significantly correlate with the prognosis of LUAD. PLCG2 expression levels varied significantly in terms of patients' gender, age, T, N, and pathological stage. GO/KEGG enrichment analysis showed that co-expression of PLCG2 was mainly associated with the immune response- regulating cell-surface receptors, and so on. GSEA analysis showed enrichment pathways of PLCG2-related differential gees were primarily associated with the olfactory transduction pathway, ribosome, etc. R software analysis revealed a significant correlation between PLCG2 expression and six types of immune-infiltrat-ing cells, positively correlated with immune checkpoint-related genes and negatively regulated by tumor mutational load. Overexpressing PLCG2 showed reduced LUAD cell proliferation, clone formation, cell migration and invasion, and epithelial-mesenchymal transition-associated proteins, compared with the control group. PLCG2 is lowly expressed in LUAD tissues and is involved in immune infiltration of LUAD, inhibiting LUAD cell proliferation and metastasis.

Gefitinib (an EGFR tyrosine kinase inhibitor) plus anlotinib (an multikinase inhibitor) for untreated, EGFR-mutated, advanced non-small cell lung cancer (FL-ALTER): a multicenter phase III trial

Dual inhibition of vascular endothelial growth factor and epidermal growth factor receptor (EGFR) signaling pathways offers the prospect of improving the effectiveness of EFGR-targeted therapy. In this phase 3 study (ClinicalTrial.gov: NCT04028778), 315 patients with treatment-naïve, EGFR-mutated, advanced non-small cell lung cancer (NSCLC) were randomized (1:1) to receive anlotinib or placebo plus gefitinib once daily on days 1–14 per a 3-week cycle. At the prespecified final analysis of progression-free survival (PFS), a significant improvement in PFS was observed for the anlotinib arm over the placebo arm (hazards ratio [HR] = 0.64, 95% CI, 0.48–0.80, P = 0.003). Particularly, patients with brain metastasis and those harboring EGFR amplification or high tumor mutation load gained significant more benefits in PFS from gefitinib plus anlotinib. The incidence of grade 3 or higher treatment-emergent adverse events was 49.7% of the patients receiving gefitinib plus anlotinib versus 31.0% of the patients receiving gefitinib plus placebo. Anlotinib plus gefitinib significantly improves PFS in patients with treatment-naïve, EGFR-mutated, advanced NSCLC, with a manageable safety profile.

Single-sample gene set enrichment analysis reveals the clinical implications of immune-related genes in ovarian cancer.

Ovarian cancer (OC) is a common gynecological malignancy with poor prognosis and substantial tumor heterogeneity. Due to the complex tumor immune microenvironment (TIME) among ovarian cancer, only a few patients have an immune response to immunotherapy. To investigate the differences in immune function and identify potential biomarkers in OC, we established a prognostic risk scoring model (PRSM) with differential expression of immune-related genes (IRGs) to identify critical prognostic IRG signatures. Single-sample gene set enrichment analysis (ssGSEA) was used to investigate the infiltration of various immune cells in 372 OC patients. Then, COX regression analysis and Lasso regression analysis were used to screen IRGs and construct PRSM. Next, the immunotherapy sensitivity of different risk groups regarding the immune checkpoint expression and tumor mutation burden was evaluated. Finally, a nomogram was created to guide the clinical evaluation of the patient prognosis. In this study, 320 immune-related genes (IRGs) were identified, 13 of which were selectively incorporated into a Prognostic Risk Scoring Model (PRSM). This model revealed that the patients in the high-risk group were characterized as having poorer prognosis, lower expression of immune checkpoints, and decreased tumor mutation load levels compared with those in the low-risk group. The nomogram based on the risk score can distinguish the risk subtypes and individual prognosis of patients with OC. Additionally, M1 macrophages may be the critical target for immunotherapy in OC patients. With the in-depth analysis of the immune microenvironment of OC, the PRSM was constructed to predict the OC patient prognosis and identify the subgroup of the patients benefiting from immunotherapy.

The prognostic and immune significance of SLAMF9 in pan-cancer and validation of its role in colorectal cancer

SLAMF9, a member of the conserved lymphocyte activation molecules family (SLAMF), has been less investigated compared to other SLAMs, especially concerning its implications across various cancer types. In our systematic pan-cancer investigation, we observed elevated SLAMF9 expression in various tumor tissues, which was correlated with reduced patient survival across most malignancies. Correlation analyses further revealed significant associations between SLAMF9 expression and immune cell infiltrates, immune checkpoint inhibitors, tumor mutation load, microsatellite instability, and epithelial–mesenchymal transition (EMT) scores. Cell-based assays demonstrated that SLAMF9 knockdown attenuated the proliferative, motile, and invasive capacities of colorectal cancer (CRC) cells. In a nude mouse xenograft model, suppression of SLAMF9 expression substantially inhibited tumor growth. These findings highlight the potential of SLAMF9 as a prognostic and therapeutic biomarker across tumors, with notable implications for CRC cell proliferation and migration.

A novel cancer-associated fibroblasts risk score model predict survival and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Cancer-associated fibroblasts (CAFs) are a special type of fibroblasts, which play an important role in the development and immune escape of tumors. Weighted gene co-expression network analysis (WGCNA) was used to construct the co-expression module. In combination with univariate Cox regression and analysis of least absolute shrinkage operator (LASSO), characteristics associated with CAFs were developed for a prognostic model. The migration and proliferation of lung cancer cells were evaluated in vitro. Finally, the expression levels of proteins were analyzed by Western blot. LASSO Cox regression algorithm was then performed to select hub genes. Finally, a total of 2 Genes (COL5A2, COL6A2) were obtained. We then divided LUAD patients into high- and low-risk groups based on CAFs risk scores. Survival analysis, CAFs score correlation analysis and tumor mutation load analysis showed that COL5A2 and COL6A2 were high-risk genes for LUAD. Human Protein Atlas (HPA), western blot and PCR results showed that COL5A2 and COL6A2 were up-regulated in LUAD tissues. When COL5A2 and COL6A2 were knocked down, the proliferation, invasion and migration of lung cancer cells were significantly decreased. Finally, COL5A2 can affect LUAD progression through the Wnt/β-Catenin and TGF-β signaling pathways. Our CAFs risk score model offers a new approach for predicting the prognosis of LUAD patients. Furthermore, the identification of high-risk genes COL5A2 and COL6A2 and drug sensitivity analysis can provide valuable candidate clues for clinical treatment of LUAD.

Intraperitoneal Nivolumab after Debulking Surgery and Hyperthermic Intraperitoneal Chemotherapy in Advanced Ovarian Cancer: A Phase I Study with Expansion Cohort.

Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) are expected to be synergistic with intraperitoneal (IP) immunotherapy by increasing tumor antigen expression and mutational load. We assessed the feasibility and safety of IP nivolumab following complete CRS and HIPEC in pretreated patients with recurrent ovarian cancer (ClinicalTrials.gov identifier: NCT03959761). Patients received IP nivolumab (0.5, 1, or 3 mg/kg) using a 3 + 3 dose-escalation design, starting 5 to 7 days after CRS and HIPEC. Four IP Q2W (once every 2 weeks) nivolumab infusions were planned. The primary objective was to demonstrate the feasibility of IP nivolumab based on dose-limiting toxicity. Secondary objectives were to assess changes in tolerance of CRS and HIPEC. A total of 17 patients were enrolled including 10 patients in the dose escalation and 7 patients in the expansion phase. No dose-limiting toxicity was observed at any dose level in the 9 evaluable patients. Six of the 17 patients (35%) did not complete all planned infusions: 4 (23.5%) due to peritoneal catheter complications and 2 (11.8%) due to early progression. No procedure-related deaths occurred. Eleven patients (65%) experienced serious adverse events (SAE), mainly transitory grade 3 to 4 transaminase elevations (6/11) and surgery-related (9/11). Four SAEs were related to the peritoneal catheter and two to HIPEC. No SAEs/grade 3 to 4 adverse events related to IP nivolumab occurred. This is the first study demonstrating the feasibility of IP nivolumab in patients with relapsed advanced ovarian cancer. Further investigation at 3 mg/kg is warranted.

The impact of tertiary lymphoid structures on tumor prognosis and the immune microenvironment in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a common malignancy whose prognosis and treatment outcome are influenced by many factors. Some studies have found that tertiary lymphoid structures (TLSs) in cancer may contribute to prognosis and the prediction of immunotherapy efficacy However, the combined role of TLSs in NSCLC remains unclear. We accessed The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to obtain mRNA sequencing data and clinical information as the TCGA cohort, and used our own sample of 53 advanced NSCLC as a study cohort. The samples were divided into TLS+ and TLS- groups by pathological tissue sections. Patients of the TLS+ group had a better OS (p = 0.022), PFS (p = 0.042), and DSS (p = 0.004) in the TCGA cohort, and the results were confirmed by the study cohort (PFS, p = 0.012). Furthermore, our result showed that the count and size of TLSs are closely associated with the efficacy of immunotherapy. In addition, the TLS+ group was associated with better immune status and lower tumor mutation load. In the tumor microenvironment (TME), the expression levels of CD4+ T cells and CD8+ T cells of different phenotypes were associated with TLSs. Overall, TLSs are a strong predictor of survival and immunotherapeutic efficacy in advanced NSCLC, and T cell-rich TLSs suggest a more ordered and active immune response site, which aids in the decision-making and application of immunotherapy in the clinic.

Construction of prognostic markers for pancreatic adenocarcinoma based on mitochondrial fusion-related genes.

Early detection of pancreatic adenocarcinoma (PAAD) remains a pressing clinical problem. Information on the clinical prognostic value of mitochondrial fusion-related genes in PAAD remains limited. In this study, we investigated mitochondrial fusion-related genes of PAAD to establish an optimal signature plate for the early diagnosis and prognosis of PAAD. The cancer genome atlas database was used to integrate the Fragments Per Kilobase Million data and related clinical data for patients with PAAD. Least absolute shrinkage and selection operator regression, cox regression, operating characteristic curves, and cBioPortal database was used to evaluate model performance, assess the prognostic ability and sensitivity. The levels of immune infiltration were compared by CIBERSORT, QUANTISEQ, and EPIC. Chemotherapy sensitivity between the different risk groups was compared by the Genomics of Drug Sensitivity in Cancer database and the "pRRophetic" R package. At last, a total of 4 genes were enrolled in multivariate Cox regression analysis. The risk-predictive signature was constructed as: (0.5438 × BAK1) + (-1.0259 × MIGA2) + (1.1140 × PARL) + (-0.4300 × PLD6). The area under curve of these 4 genes was 0.89. Cox regression analyses indicates the signature was an independent prognostic indicator (P < .001, hazard ratio [HR] = 1.870, 95% CI = 1.568-2.232). Different levels of immune cell infiltration in the 2 risk groups were observed using the 3 algorithms, with tumor mutation load (P = .0063), tumor microenvironment score (P = .01), and Tumor Immune Dysfunction and Exclusion score (P = .0012). The chemotherapeutic sensitivity analysis also revealed that the half-maximal inhibitory concentration of 5-fluorouracil (P = .0127), cisplatin (P = .0099), docetaxel (P < .0001), gemcitabine (P = .0047), and pacilataxel (P < .0001) were lower in the high-risk groups, indicating that the high-risk group patients had a greater sensitivity to chemotherapy. In conclude, we established a gene signature plate comprised of 4 mitochondrial fusion related genes to facilitate early diagnosis and prognostic prediction of PAAD.

Tumor Mutational Load: A Novel Predictor for Clinical Benefit of Pembrolizumab.

A recent study evaluated the efficacy of pembrolizumab across various cancers, classified according to tumor mutational load (TML) defined by whole-genome sequencing. Tumors exhibiting intermediate to high TML showed improved clinical benefit from pembrolizumab. This proof-of-concept study highlights clinical value of TML in patient selection, advancing precision immunotherapy and treatment strategies. See related article by Geurts et al., p. 3735.

Identification of a combined hypoxia and lactate metabolism prognostic signature in lung adenocarcinoma

BackgroundIn the tumor microenvironment (TME), a bidirectional relationship exists between hypoxia and lactate metabolism, with each component exerting a reciprocal influence on the other, forming an inextricable link. The aim of the present investigation was to develop a prognostic model by amalgamating genes associated with hypoxia and lactate metabolism. This model is intended to serve as a tool for predicting patient outcomes, including survival rates, the status of the immune microenvironment, and responsiveness to therapy in patients with lung adenocarcinoma (LUAD).MethodsTranscriptomic sequencing data and patient clinical information specific to LUAD were obtained from comprehensive repositories of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A compendium of genes implicated in hypoxia and lactate metabolism was assembled from an array of accessible datasets. Univariate and multivariate Cox regression analyses were employed. Additional investigative procedures, including tumor mutational load (TMB), microsatellite instability (MSI), functional enrichment assessments and the ESTIMATE, CIBERSORT, and TIDE algorithms, were used to evaluate drug sensitivity and predict the efficacy of immune-based therapies.ResultsA novel prognostic signature comprising five lactate and hypoxia-related genes (LHRGs), PKFP, SLC2A1, BCAN, CDKN3, and ANLN, was established. This model demonstrated that LUAD patients with elevated LHRG-related risk scores exhibited significantly reduced survival rates. Both univariate and multivariate Cox analyses confirmed that the risk score was a robust prognostic indicator of overall survival. Immunophenotyping revealed increased infiltration of memory CD4 + T cells, dendritic cells and NK cells in patients classified within the high-risk category compared to their low-risk counterparts. Higher probability of mutations in lung adenocarcinoma driver genes in high-risk groups, and the MSI was associated with the risk-score. Functional enrichment analyses indicated a predominance of cell cycle-related pathways in the high-risk group, whereas metabolic pathways were more prevalent in the low-risk group. Moreover, drug sensitivity analyses revealed increased sensitivity to a variety of drugs in the high-risk group, especially inhibitors of the PI3K-AKT, EGFR, and ELK pathways.ConclusionsThis prognostic model integrates lactate metabolism and hypoxia parameters, offering predictive insights regarding survival, immune cell infiltration and functionality, as well as therapeutic responsiveness in LUAD patients. This model may facilitate personalized treatment strategies, tailoring interventions to the unique molecular profile of each patient’s disease.

Characteristics of the immune environment in prostate cancer as an adjunct to immunotherapy.

The tumor microenvironment (TME) exerts an important role in carcinogenesis and progression. Several investigations have suggested that immune cell infiltration (ICI) is of high prognostic importance for tumor progression and patient survival in many tumors, particularly prostate cancer. The pattern of immune infiltration of PCa, on the other hand, has not been thoroughly understood. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets on PCa were obtained, and several datasets were merged into one data set using the "ComBat" algorithm. The ICI profiles of PCa patients were then to be uncovered by two computer techniques. The unsupervised clustering method was utilized to identify three ICI patterns in tumor samples, and Principal Component Analysis (PCA) was conducted to estimate the ICI score. Three different clusters of three ICIs were identified in 1341 PCa samples, which also correlated with different clinical features/characteristics and biological pathways. Patients with PCa are classified into high and low subtypes based on the ICI scores extracted from immune-associated signature genes. High ICI score subtypes are associated with a worse prognosis, which may intrigue the activation of cancer-related and immune-related pathways such as pathways involving Toll-like receptors, T-cell receptors, JAK-STAT, and natural killer cells. The ICI score was linked to tumor mutation load and immune/cancer-relevant signaling pathways, which explain prostate cancer's poor prognosis. The findings of this study not only advanced our knowledge of the mechanism of immune response in the prostate tumor microenvironment but also provided a novel biomarker, that is, the ICI score, for disease prognosis and guiding precision immunotherapy.

Investigation of RBM10 mutation and its associations with clinical and molecular characteristics in EGFR-mutant and EGFR-wildtype lung adenocarcinoma

BackgroundRBM10 is commonly mutated in lung adenocarcinoma (LUAD). However, its role in the pathogenesis of LUAD remains undefined. EGFR-mutant LUAD represents a distinct subset of non-small cell lung cancer (NSCLC). The function of RBM10 in tumor pathogenesis is supposed to differ between EGFR-mutant and EGFR-wt LUAD. This study aimed to interrogate the prevalence of RBM10 mutation in a large cohort of Chinese patients with LUAD and investigate the association of RBM10 mutation with clinical and molecular characteristics of EGFR-mutant and EGFR-wt LUAD. MethodsTumor sequencing data from 2848 Chinese patients with LUAD were retrospectively reviewed and analyzed. The prevalence of RBM10 was also compared with other three cohorts: OrigMed (n = 1222), MSKCC (n = 1267), and TCGA (n = 566). The associations of RBM10 mutation with clinical and molecular characteristics were assessed. An external cohort of 182 patients with LUAD who received PD-1 inhibitor were used to investigate the association of RBM10 mutation with clinical outcomes upon immunotherapy. ResultsOur cohort showed a higher prevalence of RBM10 in EGFR-mutant LUAD than in EGFR-wt LUAD (14.8 % vs. 6.5 %, p < 0.001). The enrichment of RBM10 mutations in EGFR-mutant LUAD was also seen in another Chinese cohort (OrigMed: 14.9 % vs. 7.8 %, p < 0.001), but not in the two western cohorts (MSKCC: 7.4 % vs. 9.5 %, p = 0.272; TCGA: 8.1 % vs. 6.7 %, p = 0.624). RBM10 mutations co-occurred more frequently with EGFR L858R mutations (23.7 %) than with other types of EGFR mutations (19 del: 7.7 %; other: 7.1 % in others, p < 0.001). In EGFR-mutant LUAD, RBM10 mutations were more commonly found in stage I (18.2 %) and II (21.8 %) vs. stage III (9.4 %) and IV (11.3 %) tumors (p < 0.001). The proportion of PD-L1 positive expression in EGFR-mutant LUAD with concomitant RBM10 mutation was not different from that those without RBM10 mutations (41.8 % vs. 47.9 %, p = 0.566). In contrast, RBM10 mutation occurred more frequently in EGFR-wt LUAD at stage II-IV (stage II: 12.0 %, stage III: 8.7 %, stage IV: 6.6 %) than at stage I (2.8 %). EGFR-wt LUAD with concomitant RBM10 mutations had higher proportions of PD-L1 expression positivity (78.9 % vs. 61.9 %, p = 0.014) and higher tumor mutational load (8.97 vs. 2.99 muts/Mb, p < 0.001) than those without. Patients with EGFR-wt LUAD who also harbored RBM10 loss of function (LOF) mutations had a longer median PFS upon immunotherapy than those with RBM10 non-LOF mutations (7.15 m vs. 2.60 m, HR = 4.83 [1.30–17.94], p = 0.010). ConclusionWe comprehensively investigated RBM10 mutations in a Chinese cohort with LUAD. Compared to western cohorts, a significant enrichment of RBM10 mutations in EGFR-mutant LUAD compared to EGFR-wildtype LUAD in the Chinese population. RBM10 mutation shows different associations with clinical and molecular characteristics between EGFR-mutant and EGFR-wt LUAD, suggesting a divergent mechanism between these two subsets via which RBM10 deficiency contribute to tumor pathogenesis. The findings contribute to our understanding of the molecular landscape of LUAD and highlight the importance of considering population-specific factors in cancer genomics research.

Immune cell infiltration and prognostic index in cervical cancer: insights from metabolism-related differential genes.

Cervical cancer remains a significant gynecologic malignancy in both China and the United States, posing a substantial threat to women's lives and health due to its high morbidity and mortality rates. Altered energy metabolism and dysregulated mitochondrial function play crucial roles in the development, growth, metastasis, and recurrence of malignant tumors. In this study, we aimed to predict prognosis and assess efficacy of anti-tumor therapy in cervical cancer patients based on differential genes associated with mitochondrial metabolism. Transcriptomic data and clinical profiles of cervical cancer patients were retrieved from the TCGA and GEO databases. Differential gene-related cellular pathways were identified through GO, KEGG, and GSEA analyses. Prognostic indices were constructed using LASSO regression analysis. Immune cell infiltration was assessed using CIBERSORT and ssGSEA, and the correlation between immune checkpoint inhibitor genes and differential genes was examined. Tumor mutation load (TMB) and its association with prognostic indices were analyzed using nucleotide variant data from the TCGA database. Patient response to immunotherapy and sensitivity to antitumor drugs were determined using the TIDE algorithm and the oncoPredic algorithm, respectively. A prognostic index based on metabolism-related differential genes was developed to predict the clinical outcome of cervical cancer patients, enabling their classification into two distinct subtypes. The prognostic index emerged as an independent risk factor for unfavorable prognosis. The high-index group exhibited a significantly worse overall prognosis, along with elevated tumor mutation burden (TMB), increased immune cell infiltration, and lower TIDE scores, indicating a potential benefit from immunotherapy. Conversely, the low-index group demonstrated increased sensitivity to metabolism-related antitumor agents, specifically multikinase inhibitors. The aim of this study was to develop a prognostic index based on differential genes associated with mitochondrial metabolism, which could be used to predict cervical cancer patients' prognoses. When combined with TIDE and TMB analyses, this prognostic index offers insights into the immune cell infiltration landscape, as well as the potential efficacy of immunotherapy and targeted therapy. Our analysis suggests that the Iron-Sulfur Cluster Assembly Enzyme (ISCU) gene holds promise as a biomarker for cervical cancer immunotherapy.

A rare case of TFEB/6p21/VEGFA-amplified renal cell carcinoma diagnosed by whole-exome sequencing: clinicopathological and genetic feature report and literature review

BackgroundTFEB/6p21/VEGFA-amplified renal cell carcinoma (RCC) is rare and difficult to diagnose, with diverse histological patterns and immunohistochemical and poorly defined molecular genetic characteristics.Case presentationWe report a case of a 63-year-old male admitted in 2017 with complex histomorphology, three morphological features of clear cell, eosinophilic and papillary RCC and resembling areas of glomerular and tubular formation. The immunophenotype also showed a mixture of CD10 and P504s. RCC with a high suspicion of collision tumors was indicated according to the 2014 WHO classification system; no precise diagnosis was possible. The patient was diagnosed at a different hospital with poorly differentiated lung squamous cell carcinoma one year after RCC surgery. We exploited molecular technology advances to retrospectively investigate the patient’s molecular genetic alterations by whole-exome sequencing. The results revealed a 6p21 amplification in VEGFA and TFEB gene acquisition absent in other RCC subtypes. Clear cell, papillary, chromophobe, TFE3-translocation, eosinophilic solid and cystic RCC were excluded. Strong TFEB and Melan-A protein positivity prompted rediagnosis as TFEB/6p21/VEGFA-amplified RCC as per 2022 WHO classification. TMB-L (low tumor mutational load), CCND3 gene acquisition and MRE11A and ATM gene deletion mutations indicated sensitivity to PD-1/PD-L1 inhibitor combinations and the FDA-approved targeted agents Niraparib (Grade C), Olaparib (Grade C), Rucaparib (Grade C) and Talazoparib (Class C). GO (Gene Ontology) and KEGG enrichment analyses revealed major mutations and abnormal CNVs in genes involved in biological processes such as the TGF-β, Hippo, E-cadherin, lysosomal biogenesis and autophagy signaling pathways, biofilm synthesis cell adhesion substance metabolism regulation and others. We compared TFEB/6p21/VEGFA-amplified with TFEB-translocated RCC; significant differences in disease onset age, histological patterns, pathological stages, clinical prognoses, and genetic characteristics were revealed.ConclusionWe clarified the patient’s challenging diagnosis and discussed the clinicopathology, immunophenotype, differential diagnosis, and molecular genetic information regarding TFEB/6p21/VEGFA-amplified RCC via exome analysis and a literature review.