UNASSIGNED: Colorectal cancer (CRC) is the third-most prevalent cancer globally. The biological significance of telomeres in CRC carcinogenesis and progression is underscored by accumulating data. Nevertheless, not much is known about how telomere-related genes (TRGs) affect CRC prognosis. Therefore, the aim of this study was to investigate the role of TRGs in CRC prognosis.
UNASSIGNED: We retrospectively obtained the expression profiles and clinical data of CRC patients from public databases. Utilizing least absolute shrinkage and selection operator (LASSO) regression analysis, we created a telomere-related risk model to predict survival outcomes, identifying ten telomere-related differentially expressed genes (TRDEGs). Based on TRDEGs, we stratified patients from The Cancer Genome Atlas (TCGA) into low- and high-risk subsets. Subsequently, we conducted comprehensive analyses, including survival assessment, immune cell infiltration, drug sensitivity, and prediction of molecular interactions using Kaplan-Meier curves, ESTIMATE, CIBERSORT, OncoPredict, and other approaches.
UNASSIGNED: The model showed exceptional predictive accuracy for survival. Significant differences in survival were observed between the two groups of participants grouped according to the model (P<0.001), and this difference was further confirmed in the external validation set (GSE39582) (P=0.004). Additionally, compared to the low-risk group, the high-risk group exhibited significantly advanced tumor node metastasis (TNM) stages, lower proportions of activated CD4+ T cells, effector memory CD4+ T cells, and memory B cells, but increased ratios of M2 macrophages and regulatory T cells (Tregs), elevated tumor immune dysfunction and exclusion (TIDE) scores, and diminished sensitivity to dabrafenib, lapatinib, camptothecin, docetaxel, and telomerase inhibitor IX, reflecting the signature\'s capacity to distinguish clinical pathological characteristics, immune environment, and drug efficacy. Finally, we validated the expression of the ten TRDEGs (ACACB, TPX2, SRPX, PPARGC1A, CD36, MMP3, NAT2, MMP10, HIGD1A, and MMP1) through quantitative real-time polymerase chain reaction (qRT-PCR) and found that compared to normal cells, the expression levels of ACACB, HIGD1A, NAT2, PPARGC1A, and TPX2 in CRC cells were elevated, whereas those of CD36, SRPX, MMP1, MMP3, and MMP10 were reduced.
UNASSIGNED: Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction.

Gap junction protein beta 3 (GJB3) has been reported as a tumor suppressor in most tumors. However, its role in lung adenocarcinoma (LUAD) remains unknown. The purpose of this study is to explore the role of GJB3 in the prognosis and tumor microenvironment of LUAD patients. The data used in this study were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and imvigor210 cohorts. We found that GJB3 expression was increased in LUAD patients and correlated with LUAD stages. LUAD patients with high GJB3 expression exhibited a worse prognosis. A total of 164 pathways were significantly activated in the GJB3 high group. GJB3 expression was positively associated with nine transcription factors and might be negatively regulated by hsa-miR-6511b-5p. Finally, we found that immune cell infiltration and immune checkpoint expression were different between the GJB3 high and GJB3 low groups. In summary. GJB3 demonstrated high expression levels in LUAD patients, and those with elevated GJB3 expression displayed unfavorable prognoses. Additionally, there was a correlation between GJB3 and immune cell infiltration, as well as immune checkpoint expression in LUAD patients.

BACKGROUND: Organoids are approved by the US FDA as an alternative to animal experiments to guide drug development and for sensitivity screening. Stable organoids models of gastric cancer are desirable for personalized medicine and drug screening.
METHODS: Tumor tissues from a primary cancer of the stomach and metastatic cancer of the lymph node were collected for 3D culture. By long-term culture for over 50 generations in vitro, we obtained stably growing organoid lines. We analyzed short tandem repeats (STRs) and karyotypes of cancer cells, and tumorigenesis of the organoids in nude mice, as well as multi-omics profiles of the organoids. A CCK8 method was used to determine the drugs sensitivity to fluorouracil (5-Fu), platinum and paclitaxel.
RESULTS: Paired organoid lines from primary cancer (SPDO1P) and metastatic lymph node (SPDO1LM) were established with unique STRs and karyotypes. The organoid lines resulted in tumorigenesis in vivo and had clear genetic profiles. Compared to SPDO1P from primary cancer, upregulated genes of SPDO1LM from the metastatic lymph node were enriched in pathways of epithelial-mesenchymal transition and angiogenesis with stronger abilities of cell migration, invasion, and pro-angiogenesis. Based on drug sensitivity analysis, the SOX regimen (5-Fu plus oxaliplatin) was used for chemotherapy with an optimal clinical outcome.
CONCLUSIONS: The organoid lines recapitulate the drug sensitivity of the parental tissues. The paired organoid lines present a step-change toward living biobanks for further translational usage.

UNASSIGNED: The prognosis and therapeutic response of patients with liver hepatocellular carcinoma (LIHC) can be predicted based on programmed cell death (PCD) as PCD plays a crucial role during tumor progression. We developed a PCD-related gene signature to evaluate the therapeutic response and prognosis for patients with LIHC.
UNASSIGNED: Molecular subtypes of LIHC were classified using ConsensusClusterPlus according to the gene biomarkers related to PCD. To predict the prognosis of high- and low-risk LIHC patients, a risk model was established by LASSO regression analysis based on the prognostic genes. Functional enrichment analysis was conducted using clusterProfiler package, and relative abundance of immune cells was quantified applying CIBERSORT package. Finally, to determine drug sensitivity, oncoPredict package was employed.
UNASSIGNED: PCD was correlated with the clinicopathologic features of LIHC. Then, we defined four molecular subtypes (C1-C4) of LIHC using PCD-related prognostic genes. Specifically, subtype C1 had the worst prognosis with enriched T cells regulatory (Tregs) and Macrophage_M0 and higher expression of T cell exhaustion markers, meanwhile, C1 also had a relatively higher TIDE score and metastasis potential. A risk model was established using 5 prognostic genes. High-risk patients tended to have higher expression of T cell exhaustion markers and TIDE score and unfavorable outcomes, and they were more sensitive to small molecule drug 5.Fluorouracil.
UNASSIGNED: A PCD-related gene signature was developed and verified to be able to accurately predict the prognosis and drug sensitivity of LIHC patients.

OBJECTIVE: To analyze the isolation rate, prevalence trends, species distribution, and drug sensitivity of non-tuberculous mycobacteria (NTM) in Anhui Province, providing a reference for diagnosis and treatment strategies.
METHODS: Specimens from suspected mycobacterial infection patients at Anhui Chest Hospital (including outpatients and inpatients) from January 2021 to December 2023 were cultured. Identified NTM strains were analyzed for species distribution and drug sensitivity.
RESULTS: Of 10,519 mycobacteria strains cultured, 1,589 were NTM (15.11%). The top four species were Mycobacterium intracellulare (75.36%), Mycobacterium abscessus (11.78%), Mycobacterium kansasii (7.09%), and Mycobacterium avium (2.85%). NTM strains showed high sensitivity to amikacin and clarithromycin (≥90%) and significant sensitivity to rifabutin, moxifloxacin, and rifampicin (89.03%-79.61%). They exhibited high resistance to imipenem/cilastatin, sulfamethoxazole, minocycline, and doxycycline (≥95%).
CONCLUSIONS: NTM isolation rates in Anhui have remained stable, with the predominant species being M. intracellulare, M. kansasii, M. abscessus, and M. avium. NTM strains are highly sensitive to amikacin, clarithromycin, rifabutin, moxifloxacin, and rifampicin. These findings can guide diagnosis, treatment strategies, and drug selection for NTM disease in Anhui Province.

The Ten-Eleven Translocation (TET) family genes are implicated in a wide array of biological functions across various human cancers. Nonetheless, there is a scarcity of studies that comprehensively analyze the correlation between TET family members and the molecular phenotypes and clinical characteristics of different cancers. Leveraging updated public databases and employing several bioinformatics analysis methods, we assessed the expression levels, somatic variations, methylation levels, and prognostic values of TET family genes. Additionally, we explored the association between the expression of TET family genes and pathway activity, tumor microenvironment (TME), stemness score, immune subtype, clinical staging, and drug sensitivity in pan-cancer. Molecular biology and cytology experiments were conducted to validate the potential role of TET3 in tumor progression. Each TET family gene displayed distinct expression patterns across at least ten detected tumors. The frequency of Single Nucleotide Variant (SNV) in TET genes was found to be 91.24%, primarily comprising missense mutation types, with the main types of copy number variant (CNV) being heterozygous amplifications and deletions. TET1 gene exhibited high methylation levels, whereas TET2 and TET3 genes displayed hypomethylation in most cancers, which correlated closely with patient prognosis. Pathway activity analysis revealed the involvement of TET family genes in multiple signaling pathways, including cell cycle, apoptosis, DNA damage response, hormone AR, PI3K/AKT, and RTK. Furthermore, the expression levels of TET family genes were shown to impact the clinical staging of tumor patients, modulate the sensitivity of chemotherapy drugs, and thereby influence patient prognosis by participating in the regulation of the tumor microenvironment, cellular stemness potential, and immune subtype. Notably, TET3 was identified to promote cancer progression across various tumors, and its silencing was found to inhibit tumor malignancy and enhance chemotherapy sensitivity. These findings shed light on the role of TET family genes in cancer progression and offer insights for further research on TET3 as a potential therapeutic target for pan-cancer.

The current study aimed to investigate the status of genes with prognostic DNA methylation sites in bladder cancer (BLCA). We obtained bulk transcriptome sequencing data, methylation data, and single-cell sequencing data of BLCA from public databases. Initially, Cox survival analysis was conducted for each methylation site, and genes with more than 10 methylation sites demonstrating prognostic significance were identified to form the BLCA prognostic methylation gene set. Subsequently, the intersection of marker genes associated with epithelial cells in single-cell sequencing analysis was obtained to acquire epithelial cell prognostic methylation genes. Utilizing ten machine learning algorithms for multiple combinations, we selected key genes (METRNL, SYT8, COL18A1, TAP1, MEST, AHNAK, RPP21, AKAP13, RNH1) based on the C-index from multiple validation sets. Single-factor and multi-factor Cox analyses were conducted incorporating clinical characteristics and model genes to identify independent prognostic factors (AHNAK, RNH1, TAP1, Age, and Stage) for constructing a Nomogram model, which was validated for its good diagnostic efficacy, prognostic prediction ability, and clinical decision-making benefits. Expression patterns of model genes varied among different clinical features. Seven immune cell infiltration prediction algorithms were used to assess the correlation between immune cell scores and Nomogram scores. Finally, drug sensitivity analysis of Nomogram model genes was conducted based on the CMap database, followed by molecular docking experiments. Our research offers a reference and theoretical basis for prognostic evaluation, drug selection, and understanding the impact of DNA methylation changes on the prognosis of BLCA.

T cells are essential tumor suppressors in cancer immunology, but their dysfunction induced by cancer cells can result in T cell exhaustion. Exhausted T cells (Tex) significantly influence the tumor immune environment, and thus, there is a need for their thorough investigation across different types of cancer. Here, we address the role of Tex cells in pan-cancer, focusing on the expression, mutations, methylation, immune infiltration, and drug sensitivity of a molecular signature comprising of the genes HAVCR2, CXCL13, LAG3, LAYN, TIGIT, and PDCD1across multiple cancer types, using bioinformatics analysis of TCGA data. Our analysis revealed that the Tex signature genes are differentially expressed across 14 cancer types, being correlated with patient survival outcomes, with distinct survival trends. Pathway analysis indicated that the Tex genes influence key cancer-related pathways, such as apoptosis, EMT, and DNA damage pathways. Immune infiltration analysis highlighted a positive correlation between Tex gene expression and immune cell infiltration in bladder cancer, while mutations in these genes were associated with specific immune cell enrichments in UCEC and SKCM. CNVs in Tex genes were widespread across cancers. We also highlight high LAYN methylation in most tumors and a negative correlation between methylation levels and immune cell infiltration in various cancers. Drug sensitivity analysis identified numerous correlations, with CXCL13 and HAVCR2 expressions influencing sensitivity to several drugs, including Apitolisib, Belinostat, and Docetaxel. Overall, these findings highlight the importance of reviving exhausted T cells to enhance the treatment efficacy to significantly boost anti-tumor immunity and achieve better clinical outcomes.

Patient response after treatment of renal cell cancer (RCC) with systemic agents, which include various drug categories, is generally poor and unpredictable. In this context, the ideal drug administration includes tools to predict the sensitivity of the disease to therapy. The aim of this study was to systematically summarize the reports on the predictive value of the methylation status in the systemic therapy of RCC. Only original articles reporting on the association of promoter methylation with the response of patients or cell lines to systemic agents were included in this review. We applied PRISMA recommendations to the structure and methodology of this systematic review. Our literature search concluded with 31 articles conducted on RCC cell lines and patient tissues. The majority of the studies demonstrated a methylation-dependent response to systemic agents. This correlation suggests that the methylation pattern can be used as a predictive tool in the management of RCC with various classes of systemic agents. However, although methylation biomarkers show promise for predicting response, the evidence of such correlation is still weak. More studies on the gene methylation pattern in patients under systemic therapy and its correlation with different degrees of response are needed.

UNASSIGNED: This study aimed to investigate the role of Nicotinamide N-methyltransferase (NNMT) in the drug sensitivity of non-small cell lung cancer (NSCLC) cells, with a focus on its impact on autophagy and resistance to the chemotherapeutic agent osimertinib. The study hypothesized that NNMT knockdown would enhance drug sensitivity by modifying autophagic processes, providing a potential new therapeutic target for overcoming chemoresistance in lung cancer.
UNASSIGNED: Proteomic analysis was utilized to identify changes in protein expression following NNMT knockdown in H1975 and H1975 osimertinib resistance (H1975OR) lung cancer cell lines. Gene expression patterns and their correlation with NNMT expression in lung cancer patients were analyzed using The Cancer Genome Atlas (TCGA) dataset. Additionally, a predictive model for lung cancer survival was developed via lasso regression analysis based on NNMT-associated gene expression. Drug sensitivity was assessed using the IC50 values and apoptosis ratio, and autophagy was evaluated through Western blot and flow cytometric analysis.
UNASSIGNED: Significant variations in the expression of 1,182 proteins were observed following NNMT knockdown, with a significant association with autophagy-related genes. Analysis of gene expression patterns unveiled a significant correlation between NNMT expression and specific changes in gene expression in lung cancer. The predictive model successfully forecasted lung cancer patient survival outcomes, highlighting the potential of NNMT-associated genes in predicting patient survival. Knockdown of NNMT reversed osimertinib resistance in H1975 cells, as evidenced by altered IC50 values and apoptosis ratio, and changes were observed in autophagy markers.
UNASSIGNED: Knockdown of NNMT in lung cancer cells enhances drug sensitivity by modulating autophagy, providing a promising therapeutic target to overcome chemoresistance in NSCLC. The study underscores the importance of NNMT in lung cancer pathology and underscores its potential as a predictive marker for clinical outcomes. Additionally, the developed predictive model further supports the clinical relevance of NNMT-associated gene expression in improving the prognosis of lung cancer patients.