Discover. Oncology最新文献

The prognosis and treatment efficacy of lung adenocarcinoma (LUAD), a disease with a high incidence, remains unsatisfactory. Identifying new biomarkers and therapeutic targets for LUAD is essential. Chromosomal assembly factor 1B (CHAF1B), a p60 component of the CAF-1 complex, is closely linked to tumor incidence and cell proliferation. However, CHAF1B's biological role and molecular mechanism in LUAD remain unclear. Here, CHAF1B expression in LUAD was examined using the GEPIA2 and UALCAN databases. Using The Cancer Genome Atlas (TCGA) LUAD database, we analyzed the diagnostic and prognostic significance of CHAF1B and its association with immune infiltration and immunological checkpoints. Gene ontology (GO) enrichment and single-cell function analyses were employed to investigate CHAF1B's possible biological roles. Drug sensitivity analysis predicted CHAF1B's effect on chemotherapeutic drug sensitivity. We also predicted lncRNAs-miRNA-CHAF1B axis to explore the molecular mechanism of CHAF1B in LUAD. Preliminary in vitro studies using qRT-PCR, CCK8, Transwell, glucose, and lactate metabolism confirmed CHAF1B's expression and role in LUAD. Its expression is associated with drug sensitivity, immunological checkpoints, and immune cell infiltration. We predicted that three miRNAs (miR-29c-3p, miR-145-5p, miR-1247-5p) and three lncRNAs (AL139287.1, NEAT1, SHG1) may be target miRNAs and target lncRNAs that regulate CHAF1B. In vitro tests showed that CHAF1B suppression decreased LUAD's migration, invasion, proliferation, and glycolysis. Overall, CHAF1B may be an innovative biomarker and therapeutic target for LUAD.

Background: Thyroid carcinoma (THCA) is the most common cancer of the endocrine system. Natural killer (NK) cell play an important role in tumor immune surveillance. The aim of this study was to explore the possible molecular mechanisms involved in NK cell in THCA to help the management and treatment of the disease.

Methods: All data were downloaded from public databases. Candidate hub genes associated with NK cell in THCA were identified by limma, WGCNA and singleR packages. Functional enrichment analysis was performed on the candidate hub genes. Hub genes associated with NK cell were identified by Pearson correlation analysis. The mRNA-miRNA-lncRNA and transcription factors (TF) networks were constructed and the drug was predicted.

Results: The infiltration level of NK cell in THCA tissues was higher than that in paracancerous tissues. KEGG functional enrichment analysis only obtained two signaling pathways, thyroid hormone synthesis and mineral absorption. CTSC, FN1, SLC34A2 and TMSB4X identified by Pearson correlation analysis were considered as the hub genes. Receiver operating characteristic analysis suggested that hub genes may be potential diagnostic biomarkers. In mRNA-miRNA-lncRNA network, FN1 had the highest correlation with IQCH-AS1, and IQCH-AS1 was also correlated with hsa-miR-543. In addition, FN1 and RUNX1 were also found to have the highest correlation in TF network. Finally, NK cell-related drugs belinostat and vorinostat were identified based on ASGARD.

Conclusion: The identification of important signaling pathways, molecules and drugs provides potential research directions for further research in THCA and contributes to the development of diagnostic and therapeutic approaches for this disease.

Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with poor prognosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective therapeutic strategies remain elusive due to the tumor's genetic complexity and heterogeneity.

Methods: This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM. Five publicly available gene expression datasets were analyzed to identify differentially expressed genes (DEGs) associated with GBM. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify GBM-related gene modules. Further, gene set enrichment and variation analyses were conducted to explore the biological pathways involved. The machine learning models were evaluated using Receiver Operating Characteristic (ROC) curves and confusion matrices to assess their predictive accuracy, with the best-performing model validated across external datasets. MR analysis was performed to establish causal relationships between genetically predicted gene expression levels and GBM outcomes.

Results: The study identified 286 DEGs between GBM and adjacent normal tissues across five datasets. WGCNA highlighted the yellow module as the most relevant to GBM, containing key genes such as KLHL3, FOXO4, and MAP1A. Of the 113 machine learning models tested, Ridge regression achieved the highest area under the curve (AUC) of 0.92, demonstrating robust predictive accuracy. Validation using external datasets confirmed the model's reliability, with a classification accuracy of 89.5% in the training set and 85.3% in the validation sets. MR analysis provided strong evidence of a causal relationship between the expression levels of the identified genes and GBM risk.

Conclusions: This study demonstrates the power of combining machine learning and Mendelian Randomization to uncover novel genetic markers for GBM. The identified genes offer promising potential as biomarkers for GBM diagnosis and therapy, providing new avenues for personalized treatment strategies.

Background: A recent study revealed the oncogenic role of box C/D small nucleolar RNA 52 (SNORD52) in hepatocellular carcinoma (HCC) by facilitating the aggressive phenotypes of hepatoma cells. However, the potential role of exosomal SNORD52 in macrophage polarization during HCC progression remains poorly understood.

Methods: Exosomes were isolated from hepatoma cells. Western blotting and flow cytometry were performed to determine the levels of M2 macrophage polarization markers. SNORD52 expression was assessed using qRT-PCR. The levels of JAK2/STAT6 pathway-related proteins were analyzed using western blotting.

Results: SNORD52 was enriched in exosomes derived from hepatoma cells and in plasma samples from patients with HCC. Hepatoma cell-derived exosomal SNORD52 was internalized by THP-1 macrophages. SNORD52 overexpression increased the levels of M2 macrophage polarization markers and JAK2/STAT6 pathway-related proteins Additionally, hepatoma cell-derived exosomal SNORD52 interacted with the JAK2/STAT6 pathway to mediate M2 macrophage polarization.

Conclusions: Our findings revealed that hepatoma cell-derived exosomal SNORD52 induces M2 macrophage polarization by activating the JAK2/STAT6 pathway.

Purpose: Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.

Patients and methods: Differentially expressed genes (DEGs) of glioma were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The potential biomarkers were identified using weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression. The prognostic ability of the potential biomarkers was evaluated by Cox regression and survival curve. CellMiner was used to access the correlation between the expression of potential biomarkers and anticancer drug sensitivity. We then explored the association of potential biomarkers and tumor immune infiltration by single-sample GSEA (ssGSEA) and CIBERSORT. Immune staining in glioma patient samples and cell experiments of potential biomarkers further verified their expression and function.

Results: Ultimately, we identified three potential biomarkers: SLC8A2, ATP2B3, and SRCIN1. These 3 genes were found significantly correlated with clinicopathological features (age, WHO grade, IDH mutation status, 1p19q codeletion status). Furthermore, the overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were found to be positively correlated with high expression of these 3 potential biomarkers. Besides, there was a substantial relationship between the sensitivity of anticancer drugs and these biomarkers expression. More importantly, the negative association between the 3 genes with most tumor immune cells was also established. Moreover, the decreased expression of the biomarkers was also verified in glioma patient samples. Finally, we confirmed that these 3 genes might promotes glioma proliferation and migration in vitro.

Conclusion: SLC8A2, ATP2B3, and SRCIN1 were identified as underlying biomarkers for glioma associated with prognosis assessments and personal immunotherapy.

Purpose: RING Finger 187 (RNF187) has recently emerged as a potential contributor to tumorigenesis. However, a comprehensive pan-cancer analysis of RNF187 in human tumors has not been undertaken until now.

Methods: Our study aims to investigate RNF187 expression across 33 different types of human tumors, utilizing data from the TCGA and GTEx databases.

Results: The pan-cancer analysis revealed significant upregulation of RNF187 in 27 types of cancers, contrasting with only low expression in LAML, with no statistical differences in OV and SARC. Notably, discernible associations were identified between RNF187 expression and the prognosis of cancer patients. Our investigation also unveiled correlations between RNA modification of RNF187 across various cancer types. Further exploration indicated a positive correlation between RNF187 levels and the presence of cancer-associated fibroblasts (CAFs) in numerous tumor types. Additionally, RNF187 exhibited correlations with a majority of immune inhibitory and stimulatory genes, as well as chemokines, receptors, MHC molecules, immunoinhibitors, and immunostimulators in various cancers. The findings highlighted associations between RNF187 expression and Tumor Mutational Burden (TMB), Microsatellite Instability (MSI) and Homologous Recombination Deficiency (HRD) in specific tumors. Finally, RNF187 showed a significant positive association with five genes (ALKBH4, FAM134A, MLST8, SANP47 and TMEM9) across the majority of tumors. GO enrichment and KEGG pathway analyses suggested that RNF187 may play a role in the pathogenesis of cancer through processes such as "bounding membrane of organelle," "macroautophagy," "proton-transporting V-type ATPase complex," "autophagy," "Ubiquitin mediated proteolysis," "Ferroptosis," "Phagosome," and etc. CONCLUSION: Our inaugural pan-cancer study aims to provide a profound understanding of RNF187 in tumorigenesis across diverse types of tumors.

Background: Plasma proteins contribute to the identification, diagnosis, and prognosis of human illnesses, which may be conducive to understanding the molecular mechanism and diagnosis of Lung adenocarcinoma (LUAD).

Methods: We collected plasma samples from 28 healthy individuals (H) and 56 LUAD patients and analyzed them using LC-MS/MS-based proteomics to determine differential expression plasma proteins (DEPPs). Then, the DEPPs were subjected to a two-sample Mendelian randomization (MR) study based on an "Inverse variance weighted (IVW)" approach to investigate the causal relationships between DEPPs and LUAD. Logistic regression analysis was conducted to develop a diagnostic model for LUAD.

Results: 317 plasma proteins were found in proteomics, and 19 DEPPs were identified. The MR study revealed that IL20RB (odds ratio (OR) = 1.600, 95% Confidence Interval (CI) [1.098, 2.331], P = 0.014) and SAA2 (OR = 1.048, 95%CI [1.012, 1.081], P = 0.017) were highly related to LUAD. A diagnostic model was established with IL20RB and SAA2. The AUC of this diagnostic model was 0.858.

Conclusion: Plasma IL20RB and SAA2 levels were closely connected with LUAD.

The occurrence and progression of breast cancer (BCa) are complex processes involving multiple factors and multiple steps. The tumor microenvironment (TME) plays an important role in this process, but the functions of immune components and stromal components in the TME require further elucidation. In this study, we obtained the RNA-seq data of 1086 patients from The Cancer Genome Atlas (TCGA) database. We calculated the proportions of tumor-infiltrating immune cells (TICs) and immune and stromal components using the CIBERSORT and ESTIMATE methods, and we screened differentially expressed genes (DEGs). Univariate Cox regression analysis of overall survival was performed on the DEGs, and a protein-protein interaction network of their protein products was generated. Finally, the hub gene CD5 was obtained. High CD5 expression was found to be associated with longer survival than low expression. Gene set enrichment analysis showed that DEGs upregulated in the high-CD5 expression group were mainly enriched in tumor- and immune-related pathways, while those upregulated in the low-expression group were enriched in protein export and lipid synthesis. TIC analysis showed that CD5 expression was positively correlated with the infiltration of CD8⁺ T cells, activated memory CD4⁺ T cells, gamma delta T cells, and M1 macrophages and negatively correlated with the infiltration of M2 macrophages. CD5 can increase anticancer immune cell infiltration and reduce M2 macrophage infiltration. These results suggest that CD5 is likely a potential prognostic biomarker and therapeutic target, providing novel insights into the treatment and prognostic assessment of BCa.

Background: It is known that genomic instability contributes to cancer development. Mitotically associated long non-coding RNA (MANCR) has been reported to promote genomic stability, suggesting its involvement in cancers. Therefore, this study was conducted to investigate the role of MANCR in non-small cell lung cancer (NSCLC).

Methods: After NSCLC (n = 60) and control (healthy subjects, n = 60) plasma samples, as well as NSCLC and paired non-tumor tissues from patients were collected, the levels of MANCR expression in plasma and tissues was detected using quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Then the correlations of MANCR expression with clinical stages were confirmed. The diagnostic values of MANCR in both plasma and tissue samples for stage I/II NSCLC were analyzed using Receiver Operating Characteristic (ROC) curves. All NSCLC patients were monitored for 5 years to investigate the role of MANCR in the prediction of patients' survival.

Results: MANCR expression was downregulated in both NSCLC plasma and tissue of NSCLC patients compared to controls (P < 0.05). Decreased MANCR expression levels from stage I to IV were observed. However, MANCR expression in non-tumor tissue was not significantly different between different stages (P > 0.05). Additionally, stage I/II NSCLC patients were separated from controls using MANCR in plasma and tumor tissues as biomarkers. Lower MANCR levels in plasma and tumor were closely correlated with patients' higher mortality rate.

Conclusion: MANCR is down-expressed in NSCLC patients and may serve as a diagnostic and prognostic biomarker for NSCLC.

Purpose: New cases and deaths of gastrointestinal cancers are predicted to increase significantly by 2040. This study aims to explore cross-country inequalities and trends in global burdens of colon and rectum cancer (CRC), esophageal cancer (EC) and gastric cancer (GC).

Methods: Data from the Global Burden of Diseases Study 2019 were analyzed to examine trends in disability-adjusted life-years (DALYs) for three gastrointestinal cancers with estimated annual percentage change (EAPC) and Joinpoint analysis. Inequality in their DALYs rates was assessed with the slope index of inequality and the concentration index, based on the Socio-Demographic Index (SDI).

Results: From 1990 to 2019, the age standardized DALYs rate of CRC decreased in these countries from high and high-middle SDI regions, with the EAPC values of - 1.018% and - 0.161%, respectively, but increased among low, low-middle and middle SDI regions (EAPC = 1.035%, 0.926% and 0.406%, respectively). The age standardized DALYs rates of EC and GC decreased in all SDI regions. Moreover, the slope index changed from 358.42 (95% confidence interval 343.28 to 370.49) to 245.13 (217.47 to 271.24) for CRC, from - 63.88 (- 87.48 to - 48.28) to - 1.36 (- 32.44 to 25.87) for EC, and from 126.37 (101.97 to 146.47) to 58.04 (20.54 to 96.12) for GC. The concentration index for CRC moved from 29.56 (28.99 to 29.84) to 23.90 (23.19 to 24.26), from - 9.47 (- 10.30 to - 9.24) to - 14.64 (- 15.35 to - 14.24) for EC, and from 8.44 (7.85 to 8.72) to - 6.42 (- 7.65 to - 6.12) for GC.

Conclusion: This study suggests strong heterogeneity in global DALYs for gastrointestinal cancers across different SDI regions. Higher SDI regions faced a greater burden of CRC, while the burdens of EC and GC were more prevalent in lower SDI regions.