Cancer Genome Research Articles

EPID-22. MUTATIONAL SIGNATURE ASSOCIATED WITH HALOALKANE EXPOSURE ENRICHED IN FIREFIGHTERS IN THE ADULT GLIOMA STUDY

Abstract Using data from The Cancer Genome Atlas (TCGA) and Glioma Longitudinal Analysis (GLASS), we identified specific environmentally related mutational signatures in glioma including a signature associated with haloalkane exposure (SBS42) from the Catalogue of Somatic Mutational Signatures (COSMIC). Haloalkanes are widely used commercially including in flame retardants and fire extinguishants and are an intriguing finding given an observed increased glioma risk in firefighters. To validate our findings, we use new study participants with data on occupation (not available in either TCGA/GLASS) from the University of California, San Francisco Adult Glioma Study (AGS) to compare mutational signatures in tumors from 17 persons with glioma and documented occupational exposure to firefighting with those of 18 matched glioma patients without history of firefighting. Using whole exome sequencing, we identified environmental exposure signatures in tumor tissue from firefighters as well as in non-firefighters who had other relevant occupational exposure (e.g. auto/truck mechanic work). In these data, glioma is largely associated with aging and mutational signatures relating to endogenous mutational processes that correlate with age, such as spontaneous or enzymatic deamination of 5-methylcytosine. However, some gliomas have detectable signatures associated with exogenous mutational processes, such as SBS42 haloalkanes. Thus, we confirm detection of haloalkane signatures in persons likely highly exposed, i.e. long-term firefighters. Identifying exogenous mutational processes in cancers are important as they may inform public health intervention strategy to reduce mutagenesis and prevent cancer inception. Identifying occupational correlates with SBS42, associated with occupational exposure to haloalkanes, will pinpoint occupational hazards that may be avoidable. This is especially important for glioma and other cancers where exogenous mutagenesis is not well established.

Reduced expression of FOXE1 in differentiated thyroid cancer, the contribution of CPG methylation, and their clinical relevance

IntroductionForkhead box E1 (FOXE1) is a transcription factor with a crucial role in thyroid morphogenesis and differentiation. Promoter hypermethylation downregulates FOXE1 expression in different tumor types; nevertheless, its expression and relationship with methylation status in differentiated thyroid cancer (DTC) remain unclear.MethodsA total of 33 pairs of matched samples of PTC tumors and non-tumors were included. Tumor cell cultures were treated with either 5-Aza-2′-deoxycytidine demethylating agent or dimethyl sulfoxide (DMSO). A real-time polymerase chain reaction (RT-PCR) and Western blotting were performed to assess FOXE1 expression. The methylation status was quantified using bisulfite sequencing. A luciferase gene assay was used to determine CpG-island functionality. Gene expression and promoter methylation of FOXE1 and FOXE1-regulated genes were also analyzed with data from The Cancer Genome Atlas (TCGA) thyroid samples.ResultsAfter demethylating treatment, increased FOXE1 mRNA was observed concomitantly with reduced promoter methylation of CpGisland2. A negative correlation between mRNA downregulation and an increased methylation level of CpGisland2 was observed in tumors. Diminished protein expression was also detected in some DTC cell lines and in some tumor samples, suggesting the involvement of post-transcriptional regulatory mechanisms. CPGisland2 was proved to be an enhancer. TCGA data analysis showed low FOXE1 mRNA expression in tumors with a negative correlation with methylation status and a positive correlation with the expression of most of its target genes. Reduced FOXE1 expression, accompanied by a high methylation level, was associated with PTC aggressiveness (tall cell variant, advanced extra thyroid extension, T4 American Joint Committee on Cancer (AJCC) classification), age at diagnosis (over 45 years old), and presence of a BRAFV600E mutation.ConclusionFOXE1 mRNA was downregulated in DTC compared with non-tumors, followed by high CpGisland methylation. A coupling of low mRNA expression and high methylation status was related to characteristics of aggressiveness in DTC tumors.

Establishment of potential lncRNA-related hub genes involved competitive endogenous RNA in lung adenocarcinoma

Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, the associations between lncRNA-related hub genes (LRHGs) expression and the corresponding outcomes have not been fully understood in lung adenocarcinoma (LUAD). Here, a total of 71 patients diagnosed with LUAD and 60 healthy volunteers at The First Affiliated Hospital of Huzhou University from April, 2023 to December, 2023 were enrolled in the present study. A LRHGs model was established using least absolute shrinkage and selection operator analyses of The Cancer Genome Atlas-LUAD datasets. The underlying mechanisms of the LRHGs were investigated via Gene Set Enrichment Analysis and Gene Set Variation Analysis. Additionally, the diagnostic role of serum HOXD cluster antisense RNA 2 (HOXD-AS2) was assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples were divided into high- and low-HOXD-AS2 expression groups based on the median expression. The associations between HOXD-AS2 expression and miR-4538 as well as Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels were conducted through Pearson correlation analysis. A comprehensive analysis identified 141 differentially expressed lncRNAs between 539 LUAD tissues and 59 normal samples. A prognostic marker for overall survival was established by constructing a predictive signature consisting of 9 LRHGs. Subsequently, 474 LUAD samples were categorized into a high or low-risk group based on the median of the risk score. An independent prognostic model was constructed to confirm the validity of this categorization. Further comparisons of the clinicopathological features and LRHG-related pathways were performed between the two groups. Examinations of LRHG expression in two LUAD clusters and of the association between LRHG expression and immune infiltration were also conducted. HOXD-AS2 expression was shown to be elevated in LUAD tissues compared with matched normal tissues, and the serum HOXD-AS2 level was also notably increased in LUAD samples compared with healthy controls. The results of the ROC analysis indicated that the sensitivity and specificity of HOXD-AS2 were higher than that of cytokeratin-19 fragment (CYFRA21-1), which is a serum marker for LUAD. Pearson analyses indicated that miR-4538 level was negatively associated with HOXD-AS2 expression, but CAMK2B level showed positive correlation in LUAD. The results of the present study therefore indicated that the constructed LRHG model, particularly HOXD-AS2, could independently diagnose and predict the prognosis of LUAD, which suggested the underlying mechanism of the HOXD-AS2/miR-4538/CAMK2B, and might offer efficient strategies for LUAD treatment.

RNF4 mediated degradation of PDHA1 promotes colorectal cancer metabolism and metastasis

This study investigates the role of RNF4-mediated ubiquitination and degradation of PDHA1 in colorectal cancer (CRC) metabolism and metastasis. Integrating (The Cancer Genome Atlas) TCGA and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, proteomic, clinical, and metabolomic analyses were performed, revealing PDHA1 as a prognostic marker in CRC. Immunohistochemical staining confirmed lower PDHA1 expression in metastatic CRC tissues. In vitro experiments demonstrated that PDHA1 overexpression inhibited CRC cell proliferation, migration, and invasion. RNF4 was identified as a key mediator in the ubiquitination degradation of PDHA1, influencing glycolytic pathways in CRC cells. Metabolomic analysis of serum samples from metastatic CRC patients further supported these findings. In vivo experiments, including xenograft and metastasis models, validated that RNF4 knockdown stabilized PDHA1, inhibiting tumor formation and metastasis. This study highlights the critical role of RNF4-mediated PDHA1 ubiquitination in promoting glycolytic metabolism, proliferation, and metastasis in CRC.

TRIM47 drives gastric cancer cell proliferation and invasion by regulating CYLD protein stability

The expression of TRIM47, a member of the TRIM protein and E3 ubiquitin ligase families, is elevated in various cancers, such as non-small cell lung cancer and colorectal cancer, and is linked to poor prognosis. This study aimed to investigate the role of TRIM47 in gastric cancer development. Using The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) dataset and analysis of 20 patient samples from our center, TRIM47 was found to be significantly up-regulated in gastric cancer tissues and associated with advanced N-stage and poor prognosis. We constructed stable TRIM47 knockdown and overexpressing gastric cancer cell lines. CCK8, EDU, colony formation, wound healing, and Transwell tests were used to evaluate the effects on cell proliferation, invasion, and migration. The results showed that TRIM47 knockdown inhibited the proliferation, migration and invasion of gastric cancer cells, while TRIM47 overexpression promoted these behaviors. These results were further confirmed in vivo. In the mechanism part, we found that TRIM47 interacts with CYLD protein. Moreover, TRIM47 promotes K48-linked ubiquitination, leading to the degradation of CYLD by the proteasome, thereby activating the NF-κB pathway and regulating the biological behavior of gastric cancer cells. Taken together, our study demonstrated that TRIM47 is involved in the proliferation and metastasis of gastric cancer through the CYLD/NF-κB pathway.

OSU-T315 overcomes immunosuppression in triple-negative breast cancer by targeting the ILK/NF-κB signaling pathway to enhance immunotherapeutic efficacy

Triple negative breast cancer (TNBC) is an aggressive and immunogenic subtype of breast cancer. The absence of biomarker has given immune checkpoint inhibitors (ICIs) a broad prospect in this type of breast cancer. The infiltration of regulatory T cells (Tregs) expressing transcription factor forkhead box P3 (Foxp3) in the tumor microenvironment (TME) is the key factor leading to ICIs resistance. Therefore, elimination of tumor antigen-specific Tregs may be an important aspect of improving ICIs efficacy. In this study, it based on the Gene Expression Omnibus and The Cancer Genome Atlas database, along with in vivo and in vitro experimental models, to verified that the high expression of integrin-linked kinase (ILK) in TNBC is the key differential factor leading to the high infiltration of Foxp3+-Tregs in the TME. Then, we selected ILK-specific inhibitor, OSU-T315, to intervene in vitro and vivo. Importantly, we found that OSU-T315 blocked the secretion of CCL17/CCL22 in tumor cells by inhibiting the ILK/NF-κB pathway, resulting in the apoptosis of Foxp3+-Tregs and decreased programmed cell death-1 (PD-1) expression. Therefore, our findings indicate a novel mechanism of OSU-T315 with potential therapeutic application in TNBC.

Lactate dehydrogenase A is a diagnostic biomarker associated with immune infiltration, m6A modification and ferroptosis in endometrial cancer

BackgroundLactate dehydrogenase A (LDHA) has been confirmed as a tumor promoter in various cancers, but its role in endometrial cancer remains unclear.MethodsThe Cancer Genome Atlas (TCGA), quantitative real-time polymerase chain reaction and the Human Protein Atlas were utilized to analyzed the LDHA expression in EC. The LDHA levels of patients with different clinical features were compared based on the TCGA cohort. The Genome Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis of LDHA-related genes were conducted by R language. The influence of LDHA knockdown on cell proliferation, apoptosis, migration and invasion was detected by in vitro experiment. The relationship between LDHA expression and immune infiltration was explored by Tumor Immune Estimation Resource 2.0 and Gene Expression Profiling Interactive Analysis. The association of LDHA level with N6-methyladenosine (m6A) modification and ferroptosis was investigated based on the TCGA-UCEC and the GEO cohort.ResultsThe LDHA was overexpressed in EC tissues and EC cell lines, and had high predictive accuracy for the EC diagnosis. The LDHA level was associated with age, histological type, histologic grade, and radiation therapy. LDHA-related genes participated in multiple biological functions and signaling pathways. LDHA downregulation significantly promoted cell apoptosis and inhibited the proliferation, migration, and invasion of EC cells. LDHA expression was connected to multiple tumor-infiltrating lymphocytes (TILs), m6A-related genes, and ferroptosis-related genes.ConclusionLDHA has the potential to work as an EC biomarker associated with TILs, m6A modification, and ferroptosis in EC.

Unveiling Tim-3 immune checkpoint expression in hepatocellular carcinoma through abdominal contrast-enhanced CT habitat radiomics

IntroductionImmune checkpoint inhibitors (ICIs) are important systemic therapeutic agents for hepatocellular carcinoma (HCC), among which T-cell immunoglobulin and mucin-domain containing protein 3 (Tim-3) is considered an emerging target for ICI therapy. This study aims to evaluate the prognostic value of Tim-3 expression and develop a predictive model for Tim-3 infiltration in HCC.MethodsWe collected data from 424 HCC patients in The Cancer Genome Atlas (TCGA) and data from 102 pathologically confirmed HCC patients from our center for prognostic analysis. Multivariate Cox regression analyses were performed on both datasets to determine the prognostic significance of Tim-3 expression. In radiomics analysis, we used the K-means algorithm to cluster regions of interest in arterial phase enhancement and venous phase enhancement images from patients at our center. Radiomic features were extracted from three subregions as well as the entire tumor using pyradiomics. Five machine learning methods were employed to construct Habitat models based on habitat features and Rad models based on traditional radiomic features. The predictive performance of the models was compared using ROC curves, DCA curves, and calibration curves.ResultsMultivariate Cox analyses from both our center and the TCGA database indicated that high Tim-3 expression is an independent risk factor for poor prognosis in HCC patients. Higher levels of Tim-3 expression were significantly associated with worse prognosis. Among the ten models evaluated, the Habitat model constructed using the LightGBM algorithm showed the best performance in predicting Tim-3 expression status (training set vs. test set AUC 0.866 vs. 0.824).DiscussionThis study confirmed the importance of Tim-3 as a prognostic marker in HCC. The habitat radiomics model we developed effectively predicted intratumoral Tim-3 infiltration, providing valuable insights for the evaluation of ICI therapy in HCC patients.

DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment

Cellular deconvolution via bulk RNA sequencing (RNA-seq) presents a cost-effective and efficient alternative to experimental methods such as flow cytometry and single-cell RNA-seq (scRNA-seq) for analyzing the complex cellular composition of tumor microenvironments. Despite challenges due to heterogeneity within and among tumors, our innovative deep learning–based approach, DeSide, shows exceptional accuracy in estimating the proportions of 16 distinct cell types and subtypes within solid tumors. DeSide integrates biological pathways and assesses noncancerous cell types first, effectively sidestepping the issue of highly variable gene expression profiles (GEPs) associated with cancer cells. By leveraging scRNA-seq data from six cancer types and 185 cancer cell lines across 22 cancer types as references, our method introduces distinctive sampling and filtering techniques to generate a high-quality training set that closely replicates real tumor GEPs, based on The Cancer Genome Atlas (TCGA) bulk RNA-seq data. With this model and high-quality training set, DeSide outperforms existing methods in estimating tumor purity and the proportions of noncancerous cells within solid tumors. Our model precisely predicts cellular compositions across 19 cancer types from TCGA and proves its effectiveness with multiple additional external datasets. Crucially, DeSide enables the identification and analysis of combinatorial cell type pairs, facilitating the stratification of cancer patients into prognostically significant groups. This approach not only provides deeper insights into the dynamics of tumor biology but also highlights potential therapeutic targets by underscoring the importance of specific cell type or subtype interactions.

Identifying colorectal cancer subtypes and establishing a prognostic model using metabolic plasticity and ferroptosis genes

Metabolic plasticity and ferroptosis are essential for colorectal cancer (CRC) progression. The effects and prognostic value of metabolic plasticity- and ferroptosis-related genes (MPFRGs) in CRC remain unclear. We established a prognostic model for CRC patients by identifying important genes in metabolic plasticity and ferroptosis. Data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus; MPFRG data were obtained from GeneCards and FerrDb. We performed functional (to explore differences between the two metabolic subtypes) and single-sample gene set (to assess the immune environment) enrichment analyses. Immunophenotype, tumor immunological dysfunction, and exclusion scores were assessed to determine patient immune responses. A least absolute shrinkage and selection operator-Cox regression model comprising 10 significant differentially expressed genes of metabolic plasticity and ferroptosis (MPFDEGs) was constructed using TCGA training cohort and validated using the GSE17536 and GSE39582 datasets. We established a nomogram comprising metabolic plasticity- and ferroptosis-based signatures, revealing the clinical application and potential molecular mechanisms underlying the role of MPFRGs in CRC. Our model (developed based on 10 MPFDEGs) is efficient for calculating the overall survival of CRC patients. Our findings provide new strategies for the clinical management and individualized treatment of these patients.

Identification of immune-associated genes for the diagnosis of ulcerative colitis-associated carcinogenesis via integrated bioinformatics analysis

BackgroundUC patients suffer more from colorectal cancer (CRC) than the general population, which increases with disease duration. Early colonoscopy is difficult because ulcerative colitis-associated colorectal cancer (UCAC) lesions are flat and multifocal. Our study aimed to identify promising UCAC biomarkers that are complementary endoscopy strategies in the early stages.MethodsThe datasets may be accessed from the Gene Expression Omnibus and The Cancer Genome Atlas databases. The co-expressed modules of UC and CRC were determined via weighted co-expression network analysis (WGCNA). The biological mechanisms of the shared genes were exported for analysis using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. To identify protein interactions and hub genes, a protein-protein interaction network and CytoHubba analysis were conducted. To evaluate gene expression, external datasets and experimental validation of human colon tissues were utilized. The diagnostic value of core genes was examined through receiver operating characteristic (ROC) curves. Immune infiltration analysis was employed to investigate the associations between immune cell populations and hub genes.ResultsThree crucial modules were identified from the WGCNA of UC and CRC tissues, and 33 coexpressed genes that were predominantly enriched in the NF-κB pathway were identified. Two biomarkers (CXCL1 and BCL6) were identified via Cytoscape and validated in external datasets and human colon tissues. CRC patients expressed CXCL1 at the highest level, whereas UC and CRC patients showed higher levels than the controls. The UC cohort expressed BCL6 at the highest level, whereas the UC and CRC cohorts expressed it more highly than the controls. The hub genes exhibited significant diagnostic potential (ROC curve > 0.7). The immune infiltration results revealed a correlation among the hub genes and macrophages, neutrophils and B cells.ConclusionsThe findings of our research suggest that BCL6 and CXCL1 could serve as effective biomarkers for UCAC surveillance. Additionally, they demonstrated a robust correlation with immune cell populations within the CRC tumour microenvironment (TME). Our findings provide a valuable insight about diagnosis and therapy of UCAC.

Overexpression of CDCA8 predicts poor prognosis and drug insensitivity in lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) accounts for the highest proportion of lung cancers; however, specific biomarkers are lacking for diagnosis, treatment, and prognostic assessment. Cell division cycle-associated 8 (CDCA8) is a cell cycle regulator with elevated expression in various cancers. However, the association between CDCA8 expression and LUAD prognosis remains unclear.MethodsThe association between CDCA8 and LUAD prognosis was evaluated based on the The Cancer Genome Atlas (TCGA) dataset, and CDCA8 related functions were determined using gene enrichment and gene ontology analyses. We also analyzed the association between CDCA8 expression and immune cell infiltration. Immunohistochemistry was used to determine the differential expression of CDCA8 in tumors and controls. Finally, we evaluated the differences in the sensitivity of different levels of CDCA8 to different anticancer drugs in LUAD.ResultsCDCA8 expression was significantly higher in primary LUAD tumors than in normal tissues (P < 0.001). Moreover, Kaplan–Meier survival analysis demonstrated that high CDCA8 expression predicted poor survival in patients with LUAD (P = 0.006). The receiver operating characteristic (ROC) curves indicated that CDCA8 was an effective guide for the diagnosis of LUAD. Functional annotation indicated that CDCA8 might be involved in functions such as p53 stabilization, nucleotide metabolism, RNA-mediated gene silencing, and the G2/M phase checkpoint. Immune infiltration results suggested that CDCA8 was positively correlated with Th2 cells and Tgd and negatively correlated with Eosinophils and Mast cells (P < 0.01). In addition, elevated expression of CDCA8 may increase the sensitivity of patients to certain anticancer drugs.ConclusionsCDCA8 upregulation is significantly associated with poor survival and immune infiltration in patients with LUAD. Our study suggests that CDCA8 can be used as a biomarker for LUAD prognosis and a reference for personalized medication.Graphical

CD1a affects the recurrence and prognosis of ovarian cancer

AbstractObjectiveExplored the correlation between CD1a expression in recurrence and prognosis of ovarian cancer (OV).MethodsThe CD1a expression profile in OV, recurrent OV, and normal tissues, as well as corresponding clinical data, were obtained from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Gene Expression Omnibus (GEO), and Genotype Tissue Expression (GTEx) databases. Meanwhile, immunohistochemical detection of CD1a expression in normal and OV tissues. Kaplan–Meier curves were plotted to estimate the hazard ratio (HR) of survival in OV. In addition, the correlation between CD1a and immune cells in OV, as well as the CD1a expression profile and corresponding survival time in pan‐cancer were obtained from TCGA database.ResultsCD1a was overexpressed in OV and was significantly under‐expressed in recurrent OV (TCGA‐OV, p &lt; 0.0001 and ICGC‐OV, p &lt; 0.0001). CD1a immunohistochemistry is significantly overexpressed in OV compared to normal tissue (p &lt; 0.05). Recurrent OV (ICGC, p &lt; 0.001; GSE17260, p &lt; 0.001; GSE32062, p &lt; 0.05). The prognosis in OV was significantly better when CD1a is overexpressed compared to under‐expressed (HR [low], 1.426: 95% confidence interval [CI], 0.912–2.128; p = 0.050). Meanwhile, the overexpression of CD1a has a better prognosis than low expression in OV and recurrent OV (p = 0.004, HR [low] = 2.462, 95%CI [1.346–4.504] and p = 0.011, HR [low] = 2.199, 95%CI [1.202–4.024]). In addition, CD1a expression was closely correlated with immune cells, the CD8+ T cells, macrophages, and NK cells, while uncharacterized cells were significantly different (p = 2.65e−6, p = 7.52e−13, p = 8.28e−12, and p = 5.89e−8, respectively). Moreover, CD1a expression affected the prognosis in various other cancers.ConclusionsCD1a expression affected the recurrence and prognosis of OV and is closely related to various immune cell levels.

E‐selectin affinity glycoproteomics reveals neuroendocrine proteins and the secretin receptor as a poor‐prognosis signature in colorectal cancer

Colorectal cancer (CRC) cells express sialylated Lewis antigens (sLe), crucial for metastasis via E‐selectin binding. However, these glycoepitopes lack cancer specificity, and E‐selectin‐targeted glycoproteins remain largely unknown. Here, we established a framework for identifying metastasis‐linked glycoproteoforms. More than 70% of CRC tumors exhibited overexpression of sLeA/X, yet without discernible associations with metastasis or survival. However, The Cancer Genome Atlas (TCGA) analysis unveiled differing expression patterns of sLeA/X‐related glycogenes correlating with disease severity, indicating context‐dependent regulation by distinct glycosyltransferases. Deeper exploration of metastatic tumor sialoglycoproteome identified nearly 600 glycoproteins, greatly expanding our understanding of the metastasis‐related glycoproteome. These glycoproteins were linked to cell adhesion, oncogenic pathways, and neuroendocrine functions. Using an in‐house algorithm, the secretin receptor (SCTR) emerged as a top‐ranked targetable glycoprotein. Tumor screening confirmed SCTR's association with poor prognosis and metastasis, with N‐glycosylation adding cancer specificity to this glycoprotein. Prognostic links were reinforced by TCGA‐based investigations. In summary, SCTR, a relatively unknown CRC glycoprotein, holds potential as a biomarker of poor prognosis and as an E‐selectin ligand, suggesting an unforeseen role in disease dissemination. Future investigations should focus on this glycoprotein's biological implications for clinical applications.

A spectrum of nonsense-mediated mRNA decay efficiency along the degree of mutational constraint

Despite its importance for regulating gene expression, nonsense-mediated mRNA decay (NMD) remains poorly understood. Here, we extend the findings of a previous landmark study that proposed several factors associated with NMD efficiency using matched genome and transcriptome data from The Cancer Genome Atlas Program (TCGA) by incorporating additional data including Genotype-Tissue Expression (GTEx), gnomAD, and metrics for mutational constraints. Factors affecting NMD efficiency are analyzed using an allele-specific expression (ASE)-based measure to reduce noise caused by random variations. Additionally, by combining our data with the updated allele frequency database of gnomAD, we demonstrate the spectrum of NMD efficiency according to the degree of gene-level mutational constraints (degree of a gene-tolerating loss-of-function variants). The NMD prediction model, trained on TCGA data, shows that gene-level mutational constraint is an important predictor of NMD efficiency. Findings of this study suggest the potential role of NMD on shaping the landscape of mutational constraints.

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.

Rhomboid-like 2 correlated with TME infiltration inhibits cuproptosis-related genes and drives malignant phenotype in clear cell renal cell carcinoma

The crosstalk between cuproptosis and the tumor immune microenvironment (TIME) is vital during clear cell renal cell carcinoma (ccRCC) malignant progression. However, the underlying molecular mechanisms regulate this cross-talk remain elusive. Through tailored machine learning, we analyze clinical ccRCC data from The Cancer Genome Atlas (TCGA) to explore the critical factors that regulate the interaction among cuproptosis, TIME, and tumor progression. We found that rhomboid-like 2 (RHBDL2), critical gene affecting this process, might inhibit cuproptosis-related genes (CRGs) and promotes ccRCC progression through the Wnt/β-catenin pathway. Next, knocking down RHBDL2 expression increased the cuproptosis-related genes ferredoxin 1 (FDX1) and lipoic acid synthase (LIAS) levels but reduced forkhead box P3 (FOXP3) levels and tumor growth in vivo and in vitro models. By employing HLY78, Wnt/β-catenin pathway activator, we rescued the expression of CRGs and the malignant proliferation and metastasis capacity in ccRCC cells with RHBDL2 knockdown. Mechanistically, RHBDL2 inhibits cuproptosis and promotes malignant progression of ccRCC through the Wnt/β-catenin pathway. Abnormal RHBDL2 expression may cause the suppressive TIME formation by regulating Treg-cell infiltration, thus triggering immune escape. In summary, our results indicated that RHBDL2 is an oncogene that induces tumorigenesis and targeting RHBDL2 may be novel therapeutic direction for metastatic ccRCC.

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

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

MCM4 Promotes the Progression of Malignant Melanoma by Activating the PI3K/AKT Pathway.

This study aims to elucidate the role of minichromosome maintenance protein 4 (MCM4) in malignant melanoma (MM) and explore the underlying mechanism. Initially, data from The Cancer Genome Atlas (TCGA) database and the Molecular Signature Database (MSigDB) were used to investigate the biological impact of MCM4 on MM. Further, a prognostic model using Cox regression analysis was developed to predict the overall survival (OS) rate in the MM patients. The effects of MCM4 on the proliferation, migration, and invasion abilities of MM (B16F0 and A375) cells were demonstrated using the CCK-8, colony formation, EDU, wound scratch, and Transwell assays. In subcutaneous tumor models in C57BL/6 mice invivo, the expression levels of MCM4 in MM cells and tumors were detected using Western blot and immunofluorescence approaches. The bioinformatics analysis indicated that MCM4 was expressed higher in MM tissues than in the normal tissues (p < 0.05). The established OS prediction model could significantly contribute to devising follow-up strategies and treating MM patients. MCM4 knockdown resulted in reduced proliferation, migration, and invasion abilities of MM cells, which were reversed by MCM4 overexpression (p < 0.05). Moreover, MCM4 could activate the phosphatidylinositol 3'-kinase (PI3K)/AKT pathway in MM cells. The PI3K inhibitor (LY294002) could reverse the effects of MCM4 on MM cells. MCM4 could substantially prompt the tumor growth of MM in mice through the PI3K/AKT pathway invivo. In summary, MCM4 prompted the development and metastasis of MM by activating the PI3K/AKT pathway.