Cancer Genome Research Articles

Low level exposure to BDE-47 facilitates the development of prostate cancer through TOP2A/LDHA/lactylation positive feedback circuit

2,2′,4,4′-tetra brominated diphenyl ether (BDE-47) is one of the most widely distributed congeners of polybrominated diphenyl ethers. While the relationships between BDE-47 exposure and other hormone-dependent cancers (such as breast cancer) are well established, no previous study has examined whether BDE-47 exposure is related to the development of prostate cancer (PCa). Through bulk and single-cell RNA sequencing (scRNA-seq) analyses, as well as in vitro and in vivo experiments, this study aims to investigate the effect of BDE-47 exposure on PCa progression. Herein, we found that low dose BDE-47 promoted the growth of PCa cells (PC3 and LNCaP) in a dose-dependent manner in vitro and in vivo. Based on Comparative Toxicogenomics Database (CTD) and The Cancer Genome Atlas (TCGA), we obtained 34 BDE-47-related and PCa-related genes through screening and overlapping. These genes were significantly enriched in fatty acid metabolism-related gene ontology (GO) terms, which were also enriched for genes targeting BDE-47 obtained from the UniProt. Through scRNA-seq data, certain cell type-specific expression was observed for CYP2E1, PIK3R1, FGF2, and TOP2A in PCa tissues from men. Molecular docking simulation showed that BDE-47 was tightly bound to the protein residues of AOX1, PIK3R1, FGF2, CAV2, CYP2E1 and TOP2A. Further screening in terms of patient overall survival, receiver operating characteristics curve (ROC) curve and Gleason score grading system narrowed the candidate genes down to TOP2A. Mechanistically, the growth-promoting effect of BDE-47 on PCa cells could be reversed by TOP2A inhibitor. RNA-seq followed by experimental verification demonstrated that TOP2A promoted PCa progression through upregulating LDHA and glycolysis. Furthermore, lactate upregulated TOP2A transcription through lactylation of H3K18la in PCa cells, which could be rescued by LDHA knockdown. Taken together, low dose BDE-47 triggered PCa progression through TOP2A/LDHA/lactylation positive feedback circuit, thus revealing epigenetic shifting and metabolic reprogramming underpinning BDE-47-induced carcinogenesis of the prostate.

Identification of SLC22A17 DNA methylation hotspot as a potential biomarker in cutaneous melanoma

BackgroundCancer onset and progression are driven by genetic and epigenetic alterations leading to oncogene activation and the silencing of tumor suppressor genes. Among epigenetic mechanisms, DNA methylation (methDNA) is gaining growing interest in cancer. Promoter hypomethylation is associated with oncogene activation while intragenic methDNA can be involved in transcriptional elongation, alternative spicing, and the activation of cryptic start sites. Several genes involved in the modulation of the tumor microenvironment are regulated by methDNA, including the Solute Carrier Family 22 Member 17 (SLC22A17), which is involved in iron trafficking and extracellular matrix remodeling cooperating with the Gelatinase-Associated Lipocalin (NGAL) ligand. However, the exact role of intragenic methDNA in cancer has not been fully investigated. Therefore, the aim of the present study is to explore the role of methDNA in the regulation of SLC22A17 in cutaneous melanoma (CM), used as a tumor model.MethodsCorrelation and differential analyses between SLC22A17 expression and methDNA were performed using the data contained in The Cancer Genome Atlas and Gene Expression Omnibus databases. Functional studies on melanoma cell lines treated with 5-Azacytidine (5-Aza) were conducted to assess the correlation between methDNA and SLC22A17 expression. A validation study on the diagnostic potential of the in silico-identified SLC22A17 methDNA hotspot was finally performed by analyzing tissue samples obtained from CM patients and healthy controls.ResultsThe computational analyses revealed that SLC22A17 was significantly downregulated in CM, and its expression was related to promoter hypomethylation and intragenic hypermethylation. Moreover, SLC22A17 overexpression and hypermethylation of two intragenic methDNA hotspots were associated with a better clinical outcome in CM patients. The correlation between SLC22A17 methDNA and expression was confirmed in 5-Aza-treated cells. In agreement with in silico analyses, the SLC22A17 promoter methylation hotspot showed higher methDNA levels in CM samples compared to nevi. In addition, the methDNA levels of this hotspot were positively correlated with advanced CM.ConclusionsThe SLC22A17 methDNA hotspot could represent a promising biomarker for CM, highlighting the regulatory role of methDNA on SLC22A17 expression. These results pave the way for the identification of novel epigenetic biomarkers and therapeutic targets for the management of CM patients.

KDM4B Histone Demethylase Inhibition Attenuates Tumorigenicity of Malignant Melanoma Cells by Overriding the p53-Mediated Tumor Suppressor Pathway.

Despite significant advances in the treatment of cutaneous melanoma (hereaftermelanoma), the prognosis remains less favorable due to therapeutic resistance, which is presumably linked to epigenetic dysregulation. We hypothesized that the histone lysine demethylase KDM4B could play a pivotal role in controlling therapy-resistant melanoma. To validate our hypothesis, we retrieved RNA sequencing data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA)program and observed upregulation of KDM4B in both primary and metastatic melanoma, which was associated with poor survival. To explore its role, we used murine B16, human SK-MEL-5, and G-361 melanoma cells as in vitro models of melanoma. We found that KDM4B inhibition using NCGC00244536 increased global levels of H3K9me3 and downregulated the expressions of cell cycle progression-related genes Cdk1, Cdk4, Ccnb1, and Ccnd1. Moreover, genetic ablation of KDM4B or its chemical inhibition using NCGC00244536 reduced p53 production by upregulating MDM2, which enhances the proteolytic degradation of p53. Interestingly, despite the reduction of p53, these interventions augmented apoptosis and senescence-induced cell death by activating pathways downstream of p53, as evidenced by reduced levels of pro-survival Bcl-2 and Bcl-xL proteins and increased production of pro-apoptotic cleaved caspase-3, caspase-7, Bax, and the senescence inducer Cdkn1a. Compared to the FDA-approved anti-melanoma agent dacarbazine, NCGC00244536 exhibited more pronounced cytotoxic and antiproliferative effects in melanoma cells. Importantly, NCGC00244536 demonstrated minimal cytotoxicity to low Kdm4b-expressing mouse embryonic fibroblasts. In conclusion, our findings suggest that KDM4B inhibition can override the antitumor effect of p53, and potentially serve as a therapeutic strategy for melanoma.

Exploring the Mechanism of Sempervirine Inhibiting Glioblastoma Invasion Based on Network Pharmacology and Bioinformatics

Background: Invasion is an important characteristic of the malignancy of glioblastoma (GBM) and a significant prognostic factor. Sempervirine (SPV), a yohimbine-type alkaloid, has been proven to inhibit GBM cells proliferation in previous research and found to have a potential effect in anti-invasion, but its mechanism of anti-invasion is still unknown. Methods: To explore its pharmacodynamics in inhibiting GBM cell invasion in this study, we combined network pharmacology and bioinformatics to comprehensive exploratory analysis of SPV and verified the mechanism in vitro. Results: Firstly, targets of SPV and invasion-related genes were collected from public databases. Moreover, GBM samples were obtained to analyze differentially expressed genes (DEGs) from The Cancer Genome Atlas (TCGA). Then, the relevant targets of SPV inhibiting GBM invasion (SIGI) were obtained through the intersection of the three gene sets. Further, GO and KEGG analysis showed that the targets of SIGI were heavily enriched in the AKT signaling pathway. Subsequently, based on the method of machine learning, a clinical prognostic model of the relevant targets of SIGI was constructed using GBM samples from TCGA and the Gene Expression Omnibus (GEO). A four-genes model (DUSP6, BMP2, MMP2, and BMP2) was successfully constructed, and Vina Scores of MMP2 and MMP13 in molecular docking were higher, which may be the main targets of SIGI. Then, the effect of SIGI was confirmed via functional experiments on invasion, migration, and adhesion assay, and the effect involved changes in the expressions of p-AKT, MMP2 and MMP13. Finally, combined with AKT activator (SC79) and inhibitor (MK2206), we further confirmed that SPV inhibits GBM invasion through AKT phosphorylation. Conclusions: This study provides valuable and an expected point of view into the regulation of AKT phosphorylation and inhibition of GBM invasion by SPV.

Aneuploidy as a driver of human cancer.

Aneuploidy, an abnormal chromosome composition, is a major contributor to cancer development and progression and an important determinant of cancer therapeutic responses and clinical outcomes. Despite being recognized as a hallmark of human cancer, the exact role of aneuploidy as a 'driver' of cancer is still largely unknown. Identifying the specific genetic elements that underlie the recurrence of common aneuploidies remains a major challenge of cancer genetics. In this Review, we discuss recurrent aneuploidies and their function as drivers of tumor development. We then delve into the context-dependent identification and functional characterization of the driver genes underlying driver aneuploidies and examine emerging strategies to uncover these driver genes using cancer genomics data and cancer models. Lastly, we explore opportunities for targeting driver aneuploidies in cancer by leveraging the functional consequences of these common genetic alterations.

The Evolving Role of Genomics in Colorectal Cancer

Approximately 75% of colorectal cancers (CRCs) harbour an identifiable driver mutation, 5% of these being heritable. These drivers have recognised implications for prognosis and therapy selection. In addition, potential germline mutations require investigations to inform testing of relatives, as well as surveillance for other malignancies. With increasing numbers of targeted drugs being approved, judicious testing is required to ensure sufficient tumour is available for testing and at the right point in the cancer pathway. Liquid biopsy with circulating tumour DNA (ctDNA) in the blood presents an exciting adjunct to tumour tissue testing for molecular drivers, as well as escalation and de-escalation of therapy. We review the most frequent molecular alterations in CRC, how genomic testing should be integrated into the treatment pathway for CRC, and sources of further education.

BZW2 is a potential regulator of non-small cell lung cancer progression

BackgroundPersonalized targeted therapy has become an important strategy for cancer treatment owing to its remarkable therapeutic efficacy and safety. However, drug resistance remains the primary cause of treatment failure. Basic leucine zipper and W2 domain 2 (BZW2), which is aberrantly expressed in cancer, has been implicated in tumor progression and may serve as a new therapeutic target. Therefore, the role of BZW2 in non-small cell lung cancer (NSCLC) requires further investigation. MethodsThe expression and genetic alterations of BZW2 in pan-cancers were explored using The Cancer Genome Atlas (TCGA) PanCancer databases. The mRNA and protein levels of BZW2 in patients with NSCLC were verified in our cohort. Functional experiments including CCK8, colony formation, and transwell assays were performed to evaluate the impact of BZW2 on the proliferative, migratory, and invasive capacities of SK-MES-1 cells. Gene Set Enrichment Analysis was used to identify underlying biological processes and pathways. Single-cell RNA (scRNA) sequencing data were employed to investigate the tumor microenvironment of NSCLC and the co-expression of BZW2 and stemness-related genes. ResultsDysregulated BZW2 expression was observed in various malignant tumors. BZW2 expression was found to be significantly elevated in NSCLC. BZW2 depletion inhibited the growth, mobility, and invasive abilities of lung squamous cell carcinoma SK-MES-1 cells. BZW2 may be related to signaling pathways such as nucleotide excision repair, ubiquitin-mediated proteolysis, and the P53 signaling pathway. Biological processes, including translational initiation, tRNA processing, and RNA methylation, were observed to be enriched in the high-BZW2 group. Furthermore, there was a positive correlation between BZW2 and the m6A- and m5C-related genes. scRNA analysis revealed a co-expression relationship between BZW2 and stemness-related genes such as CD44, SOX9, and CD133. ConclusionsElevated BZW2 expression is associated with the proliferation, migration, and invasion of NSCLC, and BZW2 may be a potential therapeutic target for NSCLC.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways “BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation” and “AMAN pathway”. In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

ZNF695, A Potential Prognostic Biomarker, Correlates with Im mune Infiltrates in Cervical Squamous Cell Carcinoma and Endoce rvical Adenocarcinoma: Bioinformatic Analysis and Experimental Verification.

The role of Zinc Finger Protein 695 (ZNF695) is unclear in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The objective of this study was to conduct a comprehensive analysis and experimental validation of ZNF695 in CESC. The study investigated the expression of ZNF695 in both pan-cancer and CESC, utilizing data from The Cancer Genome Atlas (TCGA) database to assess its diagnostic value. The present study investigated the association between ZNF695 expression levels and clinical characteristics, as well as prognosis, in patients with CESC. The study explored potential regulatory networks involving ZNF695, including its association with immune infiltration, immune score, stemness index based on mRNA expression (mRNAsi), and drug sensitivity in CESC. We explored the expression of ZNF695 in CESC single cells. ZNF695 expression was validated using GSE29570. ZNF695 was found to be aberrantly expressed in pan-cancer and CESC. There was a significant correlation observed between an elevated level of ZNF695 expression in patients with CESC and histological grade (p = 0.017). Furthermore, a strong association was found between high ZNF695 expression in CESC patients and poorer overall survival (OS) (HR: 1.87; 95% CI: 1.17-3.00; p = 0.009), Progression-free Survival (PFS) (HR: 1.86; 95% CI: 1.16-2.98; p = 0.010), and Disease-specific Survival (DSS) (HR: 1.98; 95% CI: 1.15-3.42; p = 0.014). The expression of ZNF695 in CESC patients (p = 0.006) was identified as an independent prognostic determinant. ZNF695 was associated with steroid hormone biosynthesis, oxidative phosphorylation, and so on. ZNF695 expression correlated with immune infiltration, immune score, and mRNAsi in CESC. ZNF695 expression significantly and negatively correlated with AICA ribonucleotide, BIX02189, QL-XI-92, STF-62247, and SNX-2112 in CESC. ZNF695 gene was upregulated in CESC tissues and cell lines. ZNF695 was significantly upregulated in the CESC cell lines. ZNF695 may be a potential prognostic biomarker and immunotherapeutic target for CESC patients.

SNRPB2 in the pan-cancer landscape: A bioinformatics exploration and validation in hepatocellular carcinoma

Aberrant splicing is a significant contributor to gene expression abnormalities in cancer. SNRPB2, a component of U2 small nuclear ribonucleoprotein particles (snRNPs), contributes to the assembly of the spliceosome, the molecular machinery responsible for splicing. To date, few studies have investigated the role of SNRPB2 in tumorigenesis. We examined data sourced from various public databases, such as The Cancer Genome Atlas(TCGA), the Clinical Proteomic Tumor Analysis Consortium(CPTAC), and Gene Expression Omnibus(GEO). Our investigation included gene expression, genomic and epigenomic scrutiny, gene set enrichment assessment(GSEA), and immune cell infiltration evaluation. Furthermore, we performed empirical validation to ascertain the impact of SNRPB2 suppression on the proliferation and migration of liver cancer cells. Analysis of gene expression revealed widespread upregulation of SNRPB2 across a spectrum of cancer types, with heightened levels of SNRPB2 expression in numerous tumors linked to unfavorable prognosis. Genomic and epigenomic assessments revealed connections between SNRPB2 expression and variations in SNRPB2 copy number, DNA methylation patterns, and RNA modifications. Through gene set enrichment analysis, the involvement of SNRPB2 in vital biological processes and pathways related to cancer was identified. Furthermore, scrutiny of immune cell infiltration suggested a potential relationship between SNRPB2 and the tumor microenvironment, which was reinforced by multiple single-cell sequencing profiles. Subsequent experimental validation revealed that silencing SNRPB2 effectively impeded the proliferation and migration of liver cancer cells. Taken together, these findings underscore the prospective utility of SNRPB2 as a prognostic biomarker and a promising candidate for immunotherapy in cancer. It is necessary to engage in additional exploration into its underlying mechanisms and clinical treatment potential.

Unveiling the Enigmatic Role of SLC35F3 in Lung Adenocarcinoma.

The role of solute carrier family 35 member F3 (SLC35F3) in lung adenocarcinoma (LUAD) remains unclear. To address this gap, we conducted a study employing bioinformatics analysis and experimental validation. This study aimed to examine the expression patterns of SLC35F3 in various cancer types, particularly focusing on LUAD, by analyzing data from the Cancer Genome Atlas (TCGA) database to evaluate its clinical relevance. The research also explored potential regulatory mechanisms of SLC35F3, including its interactions with immune infiltration, tumor mutational burden (TMB), and drug sensitivity in LUAD. The investigation included analyzing SLC35F3 expression in single-cell sequencing of LUAD cells, examining genetic variations of SLC35F3 in LUAD, and assessing SLC35F3 expression in cell lines using quantitative real-time PCR (qRT-PCR). The aberrant expression of SLC35F3 was observed in both pan-cancer and LUAD. In LUAD patients, a statistically significant increase in SLC35F3 expression was correlated with gender (p < 0.001) and was associated with poorer overall survival (OS) (p = 0.020). The expression of SLC35F3 was identified as an independent prognostic determinant in patients with LUAD (p = 0.032). SLC35F3 exhibited associations with various pathways, including cell cycle and more. SLC35F3 expression demonstrated correlations with immune infiltration, TMB, and some drugs in LUAD. Results indicated significant upregulation of SLC35F3 in both LUAD tissues and cell lines. SLC35F3 may serve as a prognostic biomarker and immunotherapeutic target for patients with LUAD. Not applicable.

Dichotomous intronic polyadenylation profiles reveal multifaceted gene functions in the pan-cancer transcriptome

Alternative cleavage and polyadenylation within introns (intronic APA) generate shorter mRNA isoforms; however, their physiological significance remains elusive. In this study, we developed a comprehensive workflow to analyze intronic APA profiles using the mammalian target of rapamycin (mTOR)-regulated transcriptome as a model system. Our investigation revealed two contrasting effects within the transcriptome in response to fluctuations in cellular mTOR activity: an increase in intronic APA for a subset of genes and a decrease for another subset of genes. The application of this workflow to RNA-seq data from The Cancer Genome Atlas demonstrated that this dichotomous intronic APA pattern is a consistent feature in transcriptomes across both normal tissues and various cancer types. Notably, our analyses of protein length changes resulting from intronic APA events revealed two distinct phenomena in proteome programming: a loss of functional domains due to significant changes in protein length or minimal alterations in C-terminal protein sequences within unstructured regions. Focusing on conserved intronic APA events across 10 different cancer types highlighted the prevalence of the latter cases in cancer transcriptomes, whereas the former cases were relatively enriched in normal tissue transcriptomes. These observations suggest potential, yet distinct, roles for intronic APA events during pathogenic processes and emphasize the abundance of protein isoforms with similar lengths in the cancer proteome. Furthermore, our investigation into the isoform-specific functions of JMJD6 intronic APA events supported the hypothesis that alterations in unstructured C-terminal protein regions lead to functional differences. Collectively, our findings underscore intronic APA events as a discrete molecular signature present in both normal tissues and cancer transcriptomes, highlighting the contribution of APA to the multifaceted functionality of the cancer proteome.

Clinical relationships between the intratumoral microbiome and risk factors for head and neck cancer

A bioinformatic analysis is a promising approach to understand the relationship between the vast tumor microbiome and cancer development. In the present study, we studied the relationships between the intratumoral microbiome and classical clinical risk factors using bioinformatics analysis of the Cancer Genome Atlas (TCGA) and the Cancer Microbiome Atlas (TCMA) datasets involving HNSCC patients. We used TCMA database and investigated the abundance of microbes at the genus level in solid normal tissue (n=22) and the primary tumors of patients with head and neck squamous cell carcinoma (HNSCC) (n=154) and identified three major tumor microbiomes, Fusobacterium, Prevotella, and Streptococcus. The tissue level of Fusobacterium was higher in primary tumors than in solid normal tissue. However, univariate and multivariate analyses of these 3 microbes showed no significant effects on patient survival. We then extracted 43, 55, or 59 genes that were differentially expressed between the over and under the median groups for Fusobacterium, Prevotella, or Streptococcus using the criteria of >2.5, >1.5, or >2.0 fold and p<0.05 in the Mann-Whitney U-test. The results of a pathway analysis revealed the association of Fusobacterium- and Streptococcus-related genes with the IL-17 signaling pathway and Staphylococcus aureus infection, while Prevotella-associated pathways were not extracted. A protein-protein interaction analysis revealed a dense network in the order of Fusobacterium, Streptococcus, and Prevotella. An investigation of the relationships between the intratumoral microbiome and classical clinical risk factors showed that high levels of Fusobacterium were associated with a good prognosis in the absence of alcohol consumption and smoking, while high levels of Streptococcus were associated with a poor prognosis in the absence of alcohol consumption. In conclusion, intratumoral Fusobacterium and Streptococcus may affect the prognosis of patients with HNSCC, and their effects on HNSCC are modulated by the impact of drinking and smoking.

Evaluation of a Task-Specific Self-Supervised Learning Framework in Digital Pathology Relative to Transfer Learning Approaches and Existing Foundation Models

An integral stage in typical digital pathology workflows involves deriving specific features from tiles extracted from a tessellated whole-slide image. Notably, various computer vision neural network architectures, particularly the ImageNet pretrained, have been extensively used in this domain. This study critically analyzes multiple strategies for encoding tiles to understand the extent of transfer learning and identify the most effective approach. The study categorizes neural network performance into 3 weight initialization methods: random, ImageNet-based, and self-supervised learning. Additionally, we propose a framework based on task-specific self-supervised learning, which introduces a shallow feature extraction method, employing a spatial-channel attention block to glean distinctive features optimized for histopathology intricacies. Across 2 different downstream classification tasks (patch classification and weakly supervised whole-slide image classification) with diverse classification data sets, including colorectal cancer histology, Patch Camelyon, prostate cancer detection, The Cancer Genome Atlas, and CIFAR-10, our task-specific self-supervised encoding approach consistently outperforms other convolutional neural network–based encoders. The better performances highlight the potential of task-specific attention-based self-supervised training in tailoring feature extraction for histopathology, indicating a shift from using pretrained models originating outside the histopathology domain. Our study supports the idea that task-specific self-supervised learning allows domain-specific feature extraction, encouraging a more focused analysis.

431 (PB419): Comprehensive analysis of the diversity of gastric cancer genomes and cancer-stromal interactions by single-cell spatial transcriptomics

431 (PB419): Comprehensive analysis of the diversity of gastric cancer genomes and cancer-stromal interactions by single-cell spatial transcriptomics

Necroptosis-related lncRNAs: biomarkers for predicting prognosis and immune response in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most prevalent types of lung cancer (LC), accounting for 50% of all LC cases. Despite therapeutic advancements, patients suffer from adverse drug reactions. Furthermore, the prognosis of LC patients remains poor. Necroptosis is a novel mode of cell death and is critically involved in regulating immunotherapy in patients. However, the correlation between the necroptosis-related long non-coding RNA (lncRNA) (necro-related lnc) signature (NecroLncSig) and the response of patients with LUAD to immunotherapy is unclear. This study developed a model using lncRNAs to predict the prognosis of patients with LUAD. We obtained the transcriptomic and clinical data of LUAD patients from The Cancer Genome Atlas (TCGA) database. Next, we conducted a co-expression analysis to identify the necro-related lnc. In addition, we constructed the NecroLncSig using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. Then we evaluated and validated the NecroLncSig using a Kaplan-Meier (KM) survival analysis, receiver operating characteristic (ROC) curves, principal component analysis (PCA), Gene Ontology (GO) enrichment analysis, a nomogram, and calibration curves. Finally, we used the NecroLncSig to predict the responses of patients to immunotherapy. We constructed the NecroLncSig based on seven necro-related lnc. The patients were classified into a high-risk group (HRG) and a low-risk group (LRG). The overall survival (OS) of patients in the HRG was significantly poorer in the training, testing, and entire sets (P<0.05) than that of the patients in the LRG. Univariate and multivariate Cox regression analyses demonstrated that the risk score could predict the OS of patients in an independent manner (P<0.001). Time-dependent ROC analysis demonstrated that the area under the curve values of the NecroLncSig for 1-, 2-, and 3-year OS were 0.689, 0.700, and 0.685, respectively, for the entire set. Furthermore, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm showed that the response of patients in the HRG to immunotherapy was better than that of patients in the LRG. Necro-related lnc can affect disease progression and patient prognosis. In addition, these lncRNAs can be used to design therapeutic strategies, such as immunotherapy, to treat patients with LUAD.

UCHL1 Overexpression Is Related to the Aggressive Phenotype of Non-small Cell Lung Cancer.

Ubiquitin C-terminal hydrolase L1 (UCHL1), which encodes thiol protease that hydrolyzes a peptide bond at the C-terminal glycine residue of ubiquitin, regulates cell differentiation, proliferation, transcriptional regulation, and numerous other biological processes and may be involved in lung cancer progression. UCHL1 is mainly expressed in the brain and plays a tumor-promoting role in a few cancer types; however, there are limited reports regarding its role in lung cancer. Single-cell RNA (scRNA) sequencing using 10X chromium v3 was performed on a paired normal-appearing and tumor tissue from surgical specimens of a patient who showed unusually rapid progression. To validate clinical implication of the identified biomarkers, immunohistochemical (IHC) analysis was performed on 48 non-small cell lung cancer (NSCLC) tissue specimens, and the correlation with clinical parameters was evaluated. We identified 500 genes overexpressed in tumor tissue compared to those in normal tissue. Among them, UCHL1, brain expressed X-linked 3 (BEX3), and midkine (MDK), which are associated with tumor growth and progression, exhibited a 1.5-fold increase in expression compared to that in normal tissue. IHC analysis of NSCLC tissues showed that only UCHL1 was specifically overexpressed. Additionally, in 48 NSCLC specimens, UCHL1 was specifically upregulated in the cytoplasm and nuclear membrane of tumor cells. Multivariable logistic analysis identified several factors, including smoking, tumor size, and high-grade dysplasia, to be typically associated with UCHL1 overexpression. Survival analyses using The Cancer Genome Atlas (TCGA) datasets revealed that UCHL1 overexpression is substantially associated with poor survival outcomes. Furthermore, a strong association was observed between UCHL1 expression and the clinicopathological features of patients with NSCLC. UCHL1 overexpression was associated with smoking, tumor size, and high-grade dysplasia, which are typically associated with a poor prognosis and survival outcome. These findings suggest that UCHL1 may serve as an effective biomarker of NSCLC.

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.

KRAS mutation promotes the colonization of Fusobacterium nucleatum in colorectal cancer by down-regulating SERTAD4.

This study explores and verifies potential molecular targets through which KRAS mutations regulate the colonization of Fusobacterium nucleatum (FN) in colorectal cancer (CRC). This study combined multiple bioinformatics methods and biological assays. Through The Cancer Genome Atlas, Gene Expression Omnibus, Human Protein Atlas, immunohistochemistry, and co-culture assays, we further confirmed the differential expression of SERTAD4 in CRC. We delved deeper into examining how expression of SERTAD4 is linked with immune cell infiltration and the enrichment of potential pathways. Lastly, through bacterial phenotypic assays, we validated the function of SERTAD4. As a molecule associated with KRAS mutations and FN infection, the expression levels of SERTAD4 were downregulated in CRC. The diagnostic efficacy of SERTAD4 for CRC is not inferior to that of CEA. Low expression of SERTAD4 is associated with poorer overall survival in CRC. Correlation analysis found that increased expression of SERTAD4 is associated with various immune cell infiltrations and immune checkpoint genes. Finally, bacterial adhesion and invasion assays verify that SERTAD4 inhibits the adhesion and invasion abilities of FN in CRC. This study demonstrates that SERTAD4 exerts a protective role in CRC by inhibiting the colonization of FN.

Cuproptosis-related signature predicts prognosis and indicates tumor immune infiltration in bladder cancer.

Cuproptosis is a newly identified form of cell death that is dependent on copper (Cu) ions, termed Cu-dependent cytotoxicity. This process is distinct from other forms of cell death such as apoptosis, necrosis, and ferroptosis. The accumulation of copper is known to play a significant role in various biological processes, including angiogenesis (the formation of new blood vessels) and metastasis (the spread of cancer cells to different parts of the body). These processes are crucial for tumor growth and progression, indicating that copper and the cuproptosis-related genes (CPRGs) might be indispensable in the context of cancer development and progression. Given this background, we aimed to explore the relationship between CPRGs and both prognostic predictions and tumor microenvironment (TME) infiltration in bladder cancer (BLCA). For this study, we utilized data from The Cancer Genome Atlas (TCGA) to identify CPRGs and subsequently divided BLCA patients into three distinct molecular clusters based on these genes. To assess the proportions of various immune cell types within the TME, we employed single-sample gene set enrichment analysis (ssGSEA) and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method. These computational techniques allowed us to quantify the infiltration of different immune cells, providing insights into the immune landscape of the tumors. Furthermore, we developed a risk score model using CPRGs to predict the survival prospects of BLCA patients. Our analysis identified three molecular clusters of BLCA patients, each exhibiting unique clinical features and patterns of TME infiltration. Among these clusters, cluster 1 was associated with a poor prognosis. Interestingly, this cluster also showed significant infiltration of activated CD4+ (ssGSEA P<0.001) and CD8+ T (ssGSEA P<0.05) cells, which are crucial components of the immune response against tumors. This finding suggests a complex interaction between the immune system and the tumor, where a high presence of T cells does not necessarily correlate with better outcomes. Additionally, our risk score model revealed that the high-risk group, characterized by a specific expression pattern of CPRGs, also had enhanced infiltration of CD4+ and CD8+ T cells. This indicates that the cuproptosis-based risk model has a robust ability to predict patient prognosis and can guide immunotherapy decisions. Our study sheds light on the biological functions of CPRGs within the TME of BLCA and their correlations with clinical parameters and patient prognosis. The identification of distinct molecular clusters with varying prognoses and immune cell infiltrations highlights the heterogeneity of BLCA and underscores the potential of CPRGs as biomarkers for prognosis and therapeutic targets. These findings offer new perspectives for the development of immunotherapeutic strategies in the treatment of BLCA patients, potentially leading to more personalized and effective cancer therapies.