Checkpoint Genes Research Articles

Identifying an Inversin as a Novel Prognostic Marker in Patients with Clear-Cell Renal Cell Carcinoma

Precision medicine is a developing trend in oncology, and it includes the prognosis and treatment of advanced-stage ccRCC. New predictive factors and therapeutic targets for this disease are steadily needed. The aim of this study was to explore the tumor expression of inversin as a potential prognostic factor and/or therapeutic target in ccRCC. We compared the expression of inversin between primary ccRCC and normal renal tissues by using immunohistochemistry and rtPCR in our cohort, and we also analyzed publicly available data from the TCGA-KIRC cohort. We found that the expression of inversin was significantly lower in primary tumor tissue, in comparison to solid normal tissue. Data from the KIRC study confirmed that a lower INVS expression level in ccRCC was significantly related with the overall and disease-specific survival, as well as with a shorter progression-free interval (p < 0.05). Four out of ten inversin interactome partners were significantly related with the overall and disease-specific survival in ccRCC. A lower expression of ANKS6 was a negative survival predictor, while a higher expression of NPHP3, DVL1, or DVL3 was related with a lower survival. The expression of INVS and its interactome partners in ccRCC was correlated with the differentiation of the tumor and metastasis. The expression of INVS and its partners was also correlated with tumor leukocyte infiltration and the expression of immune checkpoint genes. The results of this study point to inversin and a distinguished group of its interactome partners as potential prognostic factors in ccRCC, with their predominant involvement in the modulation of the inflammatory infiltration of the tumor microenvironment and a strong relationship with the metastatic potential of the tumor.

TMOD-01. EGFR AMPLIFICATION ACCOMPANIES ADAPTATION TO MITOGEN-INDUCED DEFECTIVE MITOSIS IN PDGFA

Abstract Using a newly described in vitro murine model of GBM [Bohm et al., Neuro-Oncol 2020 and Omairi et al., Neuro-Oncol 2023] in which P53 null neural progenitor cells (NPCs) divide abnormally and evolve a GBM-like genome during exposure to Platelet-Derived Growth Factor-AA (PDGFA), we asked how a brain-abundant mitogen could transform NPCs. By analyzing gene and protein expression over time, we found that PDGFA fails to induce the transcription of kinetochore and spindle assembly checkpoint genes, while simultaneously driving NPCs to enter mitosis. These dual effects caused chromosome miss-segregation in continuously dividing NPCs; moreover, they occurred in both WT and null NPCs, although only null cells survived defective mitosis. These surviving cells gradually expanded in PDGFA accumulating both random and clonal chromosomal re-arrangements. Transcriptome analysis of NPCs in PDGFA revealed significant under-expression of Foxm1, the major regulator of kinetochore transcription, together with over-expression and phosphorylation of the immediate early response gene, FOS. Analysis of signalling downstream of PDGFRα identified the Ras-MAPK pathway, especially ERK, as responsible for FOS activation. As surviving null cells gradually expanded, they accumulated random and recurrent chromosomal rearrangements. Expansion and subsequent PDGFA-independent proliferation and tumorigenicity were associated with re-expression of Foxm1 and kinetochore proteins, and accompanied by over-expression of Egfr, an RTK-signature that defines human GBM. By stimulating proliferation without setting the stage for error-free mitosis, exposure to PDGFA transforms p53 null NPCs and generates Egfr amplified GBM-like cancer cells.

Targeting LLT1 as a potential immunotherapy option for cancer patients non-responsive to existing checkpoint therapies in multiple solid tumors

BackgroundHigh levels of LLT1 expression have been found in several cancers, where it interacts with CD161 on NK cells to facilitate tumor immune escape. Targeting LLT1 could potentially relieve this inhibitory signal and enhance anti-tumor responses mediated through NK cells. Using the ‘The Cancer Genome Atlas’ (TCGA) database, we investigated the role of LLT1 in the tumor microenvironment (TME) across various cancers. Identifying such biomarkers could create new therapeutic options for patients in addition to complementing existing immunotherapies.MethodsLLT1 expression was evaluated in 33 cancers using TCGA transcriptome data. Univariate Cox regression analysis was employed to assess the correlation of LLT1 expression with patient survival. The relationship between LLT1 expression with immune infiltrates, immune gene signatures, and cancer genomic biomarkers (TMB, MSI, and MMR) was also investigated. Immunofluorescence studies were conducted to validate LLT1 expression in tumors. Furthermore, using the CRI iAtlas data, we evaluated LLT1 distribution and its correlation with other immune checkpoint genes in patients non-responsive to existing immune checkpoint therapies across multiple solid cancers.ResultsHigh expression of LLT1 was observed in 12 cancers, including BRCA, CHOL, ESCA, GBM, HNSC, KIRC, KIRP, LIHC, LUAD, STAD, SARC, and PCPG. In certain cancers like COAD, KICH, and KIRC, high LLT1 expression was associated with poor prognosis. Further analysis revealed that upregulated LLT1 was associated with an abundance of NK and T cell infiltrates in the TME, as well as exhaustive immune biomarkers, and inversely associated with pro-inflammatory and tumor suppressor signatures. High LLT1 expression is also positively correlated with genomic biomarkers in certain cancers. Immunofluorescence studies confirmed moderate to high LLT1 expression in immune-resistant prostate cancer, glioma, ovarian cancer, and immune-sensitive liver cancer cell lines. An independent assessment of clinical cohorts from CRI iAtlas showed a correlation of upregulated LLT1 with multiple immunosuppressive genes in patients non-responsive to current ICIs.ConclusionsThe biomarker analysis revealed a clear association between elevated LLT1 expression and an immunosuppressive TME in patient cohorts from TCGA and clinical databases. Therefore, this study provides a foundation for utilizing LLT1 as a potential target to improve clinical responses in ICI non-responsive patients with upregulated LLT1.

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.

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.

SGSM2 in Uveal Melanoma: Implications for Survival, Immune Infiltration, and Drug Sensitivity.

The abnormal expression of small G protein signaling modulator 2 (SGSM2) is related to the occurrence of thyroid cancer and breast cancer. However, the role of SGSM2 in uveal melanoma (UVM) is unclear. To elucidate this ambiguity, our study utilized bioinformatics analysis and experimental validation. The expression of SGSM2 was detected in UVM cell lines through quantitative real-- time PCR (qRT-PCR). We utilized the Cancer Genome Atlas (TCGA) database to assess the relationship between SGSM2 expression and clinical characteristics, as well as its prognostic significance in UVM. Furthermore, the study examined potential regulatory networks involving SGSM2 in relation to immune infiltration, immune checkpoint genes, microsatellite instability (MSI), and drug sensitivity in UVM. The study also examined SGSM2 expression in UVM single-cell sequencing data. SGSM2 was highly expressed in UVM cell lines. Moreover, elevated levels of SGSM2 in UVM patients were significantly linked to poorer overall survival (OS) (p < 0.001), progress- free survival (PFS) (p < 0.001), and disease-specific survival (DSS) (p < 0.001). Additionally, SGSM2 expression was identified as an independent prognostic factor in UVM patients (p < 0.001). SGSM2 was associated with several pathways, including the calcium signaling pathway, natural killer cell-mediated cytotoxicity, cell adhesion molecules (CAMs), and others. The study revealed that SGSM2 expression in UVM is linked to immune infiltration, immune checkpoint genes, and MSI. Additionally, a significant inverse correlation was observed between SGSM2 expression and the compounds GSK690693, TL-2-105, PHA-793887, Tubastatin A, and SB52334 in UVM patients. SGSM2 may not only serve as an important indicator for prognostic assessment. Still, it may also be a key target for the development of new therapeutic approaches, providing new perspectives on the treatment of UVM patients.

Identification of PSMD2 as a promising biomarker for pancreatic cancer patients based on comprehensive bioinformatics and in vitro studies

BackgroundPancreatic cancer patients have limited treatment options and extremely poor prognosis. Dysregulations of proteasome 26S subunit, non-ATPases (PSMDs) contribute to the development of various cancers, whereas the significance of PSMDs in pancreatic cancer is poorly understood. In the present study, we intended to explore the therapeutic potential of PSMDs in pancreatic cancer. MethodsBased on TCGA database, the expression of PSMDs was analyzed in pancreatic cancer patients. Multivariate Cox regression and Kaplan–Meier survival analyses were conducted to investigate the prognostic value of PSMDs. The correlations between the expression of PSMD2/14 and immune cell infiltration, immune checkpoint genes’ expression, enrichment of signaling pathways, and the sensitivity of chemotherapies were also evaluated. Knockdown and overexpression experiments were performed to explore the biological function of PSMD2/14. Immunoblotting was conducted to detect the downstream signaling pathway of PSMD2. ResultsMost of the PSMDs, except for PSMD5 and PSMD6, were significantly upregulated in pancreatic cancer tissues. Patients with higher grade tumor had increased mRNA levels of PSMD1/2/5/7/8/11/12/14. Survival and multivariate Cox regression analyses indicated that PSMD2 and PSMD14 were biomarkers of worse prognosis. High expression of PSMD2 and PSMD14 was positively correlated with the levels immune checkpoint genes but not with the infiltration of specific immune cell types. In vitro knockdown of PSMD2, but not PSMD14, increased the apoptosis, gemcitabine’s toxicity and inhibited the growth capacity of MIA cells. Conversely, decreased apoptosis and gemcitabine sensitivity along with accelerated cell proliferation ability were observed in PSMD2-overexpressing PANC-1 cells. Mechanistically, PSMD2 activated the AKT/mTOR signaling pathway, consistent with the findings from KEGG and GSEA analysis. The AKT specific inhibitor MK-2206 exhibited higher cytotoxicity in MIA and PANC-1 cells with high PSMD2 expression. Importantly, MK-2206 largely reversed the oncogenic functions of PSMD2 on the growth and proliferation of PANC-1 cells. ConclusionIn summary, our study provided a comprehensive bioinformatics analysis of PSMDs in pancreatic cancer. We identified that PSMD2 acted as a tumor-promoting protein in pancreatic cancer through the activation of the AKT/mTOR pathway. The overexpression of PSMD2 may be a potential biomarker that predicts the response of pancreatic cancer patients to AKT inhibitor treatments.

TPD52 is a Potential Prognostic Biomarker and Correlated with Immune Infiltration: A Pan-cancer Analysis.

Some tumors have a poor prognosis regarding TPD52 (tumor protein D52). This study aims to explore TPD52's role in the cancer process from a pan-cancer perspective. A pan-cancer analysis was conducted to investigate how TPD52 may be involved in cancer as well as its association with prognosis. A variety of human cancers express TPD52 abnormally and correlate with clinical stage. There was a significant association between low expression of TPD52 and poor survival in BRCA, KIRP, LAML, LIHC, UCEC, and UVM. TPD52 alterations were most frequently amplified in pan-cancer. The co-occurrence of 10 genes alterations was found in the TPD52 altered group. There was a significant association between TPD52 expression and MSI in four cancer types and TMB in twelve cancer types. There was a significant correlation between TPD52 expression and immunerelated cell infiltration. A significant correlation was found between TPD52 expression in many tumor types and 8 immune checkpoint genes. There were signaling pathways involved in pan-cancer caused by TPD52, including endocytosis, Fc gamma Rmediated phagocytosis, and so on. TPD52 may be involved in chemotherapy and chemoresistance. The TPD52 gene may be important for human cancer 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.

Pan-cancer analysis of IRF1 focusing on prognostic and immunological roles in non-small cell lung cancer

Interferon regulatory factor 1 (IRF1) significantly affects tumour occurrence and development. This study aimed to analyse its function as a pan-cancer prognostic indicator. We compared IRF1 expression and prognostic significance in normal and tumour samples from different databases. Accordingly, we performed in vitro experiments and immunohistochemistry (IHC) to investigate the role of IRF1 in non-small cell lung cancer (NSCLC). Our findings indicate that IRF1 expression is significantly correlated with prognosis, the tumour microenvironment, and immune cell infiltration. Furthermore, receiver operating characteristic (ROC) analysis revealed that IRF1 had high accuracy in distinguishing cancerous tissues from normal ones. Notably, IRF1 expression was linked to immune-related and immune checkpoint genes. Cell proliferation, invasion, and migration were significantly related to IRF1 expression. IHC indicated that IRF1 was downregulated in NSCLC tissues. Our study provides comprehensive bioinformatic analysis and experimental verification of IRF1, suggesting its potential as a prognostic biomarker in cancer.

Single-cell and machine learning approaches uncover intrinsic immune-evasion genes in the prognosis of hepatocellular carcinoma

Background and aimsHepatocellular carcinoma (HCC) is a tumor of high heterogeneity and complexity, which poses significant challenges to effective treatment and patient prognosis because of its immune evasion characteristics. To address these issues, single-cell technology and machine learning methods have emerged as a promising approach to identify genes associated with immune escape in HCC. This study aimed to develop a prognostic risk score model for HCC by identifying intrinsic immune-evasion genes (IIEGs) through single-cell technology and machine learning, providing insights into immune infiltration, enhancing predictive accuracy, and facilitating the development of more effective treatment strategies. Materials and methodsThe study utilized data from The Cancer Genome Atlas database to analyze gene expression profiles and clinical data related to intrinsic immune evasion in patients with HCC. Various tools, including the Human Protein Atlas, cBioPortal, single-cell analysis, machine learning, and Kaplan-Meier plot, were used to analyze IIEGs. Functional enrichment analysis was conducted to explore potential mechanisms. In addition, the abundance of infiltrating cells in the tumor microenvironment was investigated using single-sample gene set enrichment analysis, CIBERSORT, xCELL, and tumor immunophenotype algorithms. The expression of glycosylphosphatidylinositol anchor attachment 1 (GPAA1) was examined in the clinical sample of HCC by quantitative real-time polymerase chain reaction, Western blotting, and immunohistochemical staining. ResultsUnivariate Cox analysis identified 63 IIEGs associated with the prognosis of HCC. Using random forest, least absolute shrinkage and selection operator regression analysis, and support vector machine, a risk score model consisting of six IIEGs (carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD), phosphatidylinositol glycan anchor biosynthesis class U (PIGU), endoplasmic reticulum membrane protein complex subunit 3 (EMC3), centrosomal protein 55 (CEP55), autophagy-related 10 (ATG10), and GPAA1) developed, which was validated using 10 pairs of HCC and adjacent non-cancerous samples. Based on the calculated median risk score, HCC samples were categorized into high- and low-risk groups. The Kaplan-Meier curve analysis showed that the high-risk group had a worse prognosis compared with the low-risk group. Time-dependent receiver operating characteristic analysis demonstrated the accurate predictive capability of the risk score model for HCC prognosis. Furthermore, immune infiltration analysis showed a positive correlation between the risk score model and 40 immune checkpoint genes as well as Th2 cells. ConclusionsA prognostic risk score model was formulated by six IIEG signatures and showed promise in predicting the prognosis of patients diagnosed with HCC. The utilization of the IIEG risk score as a novel prognostic index, together with its significance as a valuable biomarker for immunotherapy in HCC, provides benefit for patients with HCC in determining therapeutic strategies for clinical application.

Integration of bioinformatics and cellular experiments unveils the role of SYT12 in gastric cancer

ObjectiveThis study employs integrated bioinformatics analysis and in vitro cellular experiments to elucidate the role of Synaptotagmin-12 (SYT12) in the progression of gastric cancer.MethodsWe utilized databases and platforms such as Xiantao Academic Tools, UALCAN, Kaplan-Meier plotter analysis, and The Cancer Genome Atlas (TCGA) to extract datasets on SYT12 in gastric cancer. We analyzed the relationship between SYT12 expression and the clinicopathological features, prognosis, diagnosis, and immune infiltration of stomach adenocarcinoma (STAD) patients. Verification was conducted using samples from 31 gastric cancer patients. Additionally, in vitro cellular experiments were performed to determine the role and potential mechanisms of SYT12 in the malignant behavior of gastric cancer cells.ResultsComprehensive bioinformatics analysis indicated that SYT12 is highly expressed in most cancers and is associated with promoter DeoxyriboNucleic Acid (DNA) methylation levels. SYT12 expression correlated with clinicopathological features, immune cell infiltration, immune checkpoint gene expression, and poor prognosis in STAD patients. In vitro experiments suggest that SYT12 may promote the proliferation and migration of gastric cancer cells by inducing epithelial-mesenchymal transition (EMT).ConclusionsThis study highlights the significant role of SYT12 in gastric cancer, suggesting its potential as a new target for early diagnosis, treatment, immunological, and prognostic evaluation in gastric cancer, offering new insights for precision medicine in this disease.

Diagnostic and prognostic significance of tetraspanin 6 and its role in facilitating glioma progression

BackgroundSeveral tetraspanin (TSPAN) proteins have been implicated in tumorigenesis and disease progression. However, the precise function of tetraspanin 6 (TSPAN6) in glioma remains unclear.MethodsIntegrated raw data from the Tumor Genome Atlas (TCGA) and Gene Expression Profiling (GEO) databases were processed using R4.2.1. Bioinformatic methods were used to analyze the gene expression levels of TSPAN6 in both glioma and normal brain tissues, correlating them with clinical characteristics. Additionally, the predictive value of TSPAN6 in relation to the immune checkpoint blockade (ICB) therapy response was assessed. In vitro experiments were conducted to investigate the effects of TSPAN6 knockdown on glioma cell proliferation, migration, cell cycle regulation, and macrophage recruitment.ResultsTSPAN6 expression was significantly upregulated in glioma tissues compared to normal tissues. Elevated TSPAN6 expression is strongly correlated with unfavorable clinical characteristics in gliomas. Bioinformatic analyses revealed a significant correlation between elevated TSPAN6 expression and reduced overall survival. Additionally, TSPAN6 was co-expressed with several immune checkpoint genes and revealed a prognostic value in the context of ICB therapy. Functional enrichment analysis revealed the involvement of TSPAN6 in cell-cycle regulation. Furthermore, TSPAN6 expression positively correlated with macrophage and neutrophil infiltration. In vitro experiments confirmed that the downregulation of TSPAN6 inhibited U251 cell proliferation, disrupted the cell cycle, diminished migratory capabilities, and reduced the recruitment of macrophages.ConclusionOur findings emphasize its potential as both a diagnostic and therapeutic target as well as a predictor of immune therapy response in gliomas.

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.

Development and verification of a novel risk model related to ubiquitination linked with prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC.

The prognostic significance of twist in pancreatic cancer and its role in cancer promotion through the regulation of the immune microenvironment and EMT mechanisms

ObjectivePancreatic cancer has a poor prognosis due to its high malignancy and rapid progression. The limited immunogenicity of pancreatic cancer (PAAD) contributes to its low responsiveness to immunotherapy, yet its underlying mechanism remains poorly understood. As a cancer promoting gene, Twist participates in EMT in various tumors and promotes tumor progression. The interplay between EMT and the tumor microenvironment (TME) emerges as a pivotal factor influencing tumor immunity and response to immunotherapy. Twist therefore has potential as a biomarker for gauging the outcome of tumour immunotherapy.This research aimed to assess the Twist's prognostic significance in PAAD and its relationship to immunotherapy response.MethodsIn this research, transcriptional data and epigenetic alterations of Twist in pancreatic cancer, along with their impact on the prognosis of PAAD patients, were analyzed using databases. Functional enrichment analysis elucidated the biological role of Twist in PAAD. Subsequently, databases including CIBERSORT and TIDE were employed to investigate the association between Twist expression and immune cell infiltration, immune checkpoint genes, and immunotherapy sensitivity within the pancreatic cancer immune microenvironment.Paraffinized specimens from patients with pancreatic ductal adenocarcinoma confirmed by postoperative pathology were selected for Twist expression verification, and the difference was analyzed by Chi-square test; uncontaminated pancreatic cancer cell lines were used for Twist expression verification, and the differences were analyzed by Student t-test.ResultsTwist mRNA expression was notably upregulated in PAAD, positively correlating with gene methylation levels. Analyses of Kaplan–Meier and Cox regression showed a correlation between better overall survival and lower Twist expression. Functional annotation indicated that Twist-associated differentially expressed genes (DEGs) were involved in EMT regulation and acute inflammation. High expression of Twist leads to a significant reduction in the infiltration of anti-tumor immune cells such as Monocytes, NKcellsactivated, and TcellsCD8, further supporting its creation of a typical immunosuppressive microenvironment in pancreatic cancer. Twist expression is positively correlated with the expression of HARVCR2, LAIR1, LGALS3 and other genes, which may be related to the treatment response to immune checkpoint inhibitors (ICIs). TIDE analysis predicts that patients with high expression of Twist will be insensitive to immunotherapy. Twist is significantly over-expressed in pancreatic cancer cell lines and tissues, and is negatively correlated with E-cadhrin expression, but positively correlated with N-cadherin,Snail, and ZEB1.ConclusionHigh Twist expression in PAAD signifies a grim prognosis. Its elevated levels not only contribute to tumor progression through EMT induction but also exert regulatory control over the immune microenvironment, leading to immunosuppression and diminished effectiveness of immunotherapy.

Immune regulation and prognostic prediction model establishment and validation of PSMB6 in lung adenocarcinoma.

Lung cancer is one of the most common malignant tumors, and patients are often diagnosed at an advanced stage, posing a substantial risk to human health, so it is crucial to establish a model to forecast the prognosis of patients with lung cancer. Recent research has indicated that proteasome 20S subunit 6 (PSMB6) may be closely associated with anti-apoptotic pathways, and proliferation transduction signals in tumor cells of different tumors. However, the precise role of PSMB6 in the immunoregulatory processes within lung adenocarcinoma (LUAD) is yet to be elucidated. By analyzing the TCGA database, we discovered a positive correlation between the expression of PSMB6 and tumor growth trends, and lung adenocarcinoma patients with elevated PSMB6 expression levels had a worse prognosis. Our findings suggest a close correlation between PSMB6 expression levels, immune cell infiltration and immune checkpoint gene expression, which suggests that PSMB6 may become a new independent prognostic indicator. In addition, we developed a prognostic model of PSMB6-regulated immune infiltration-associated genes by analyzing the link between PSMB6 and the immune microenvironment. This model can not only predict the prognosis of lung adenocarcinoma but also forecasts the patient's reaction to immunotherapy. The validity of this research outcome has been confirmed by the GSE31210 and IMvigor210 cohorts. Analysis of the Kaplan-Meier Plotter database indicates that individuals with elevated levels of PSMB6 expression exhibit a poorer prognosis. Additionally, in vitro experiments demonstrated that knockdown of PSMB6 inhibits the proliferation, migration, and invasion of lung adenocarcinoma cells while promoting their apoptosis. Overall, our findings suggest that PSMB6 could remarkably influence the management and treatment of lung adenocarcinoma, opening new avenues for targeted immunotherapeutic strategies.

Integrated immunogenomic analyses of single-cell and bulk profiling construct a T cell-related signature for predicting prognosis and treatment response in osteosarcoma

PurposesT cells play a crucial role as regulators of anti-tumor activity within the tumor microenvironment (TME) and are closely associated with the progression of osteosarcoma (OS). Nevertheless, the specific role of T cell-related genes (TCRGs) in the pathogenesis of OS remains unclear.MethodsFirst, we processed single-cell RNA sequencing (scRNA-seq) data of OS from the public databases and performed cell annotation. We identified highly variable genes in each cell type using the "FindAllMarkers" function, explored the distribution of different clusters, and investigated inter-cellular communication patterns via the "CellChat" framework. Then, we used multivariate Cox analysis to construct a TCRG and developed a nomogram to predict survival probabilities for OS patients. Finally, we validated the aforementioned results using various cell lines and investigated the immune cell infiltration, expression of immune checkpoints, chemotherapy sensitivity, and the efficacy of targeted therapies across different risk groups.ResultsFrom the scRNA-seq data, we identified 3,000 highly variable genes, presented the top 10 genes, and validated the expression of core genes across different cell lines.Moreover, our analysis delved into interactions between T cells and other cell types. Our analyses constructed a predictive T cell-related signature (TCRS) that incorporated these prognostic TCRGs, showing a clear prognostic separation between the high-risk and low-risk OS patient groups in multiple cohorts. Survival analysis indicated better outcomes for patients classified in the high-risk group. The low-risk group exhibited elevated levels of CD4 memory resting T cells, contrasting with the higher levels of macrophage M0 observed in the high-risk group via the CIBERSORT algorithm. Furthermore, we observed that the low-risk group exhibitedAQ1 significant up-regulation of immune checkpoint genes (ICGs) and lower Tumour Immune Dysfunction and Exclusion (TIDE) scores, suggesting that they may be suitable for immunotherapy. Conversely, the high-risk group appeared more responsive to chemotherapy and targeted therapies, according to our drug sensitivity analysis.ConclusionIn conclusion, our study identified TCRGs, constructed and validated a TCRS for OS, and assessed immune response and drug sensitivity in different risk groups of OS patients. These findings provide novel insights into personalized treatment strategies for OS, potentially guiding more effective therapeutic interventions.

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.

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.