Translational cancer research最新文献

[This retracts the article DOI: 10.21037/tcr-20-2660.].

Background: Although Mendelian randomization (MR) studies have been conducted on the causal relationship of testosterone on colorectal cancer (CRC), the result remains controversial. We aimed to explore the genetically determined relationships between total testosterone (TT) and bioavailable testosterone (BT) with CRC using a larger sample size and more stringent methods to exclude confounding factors.

Methods: Based on genome wide association studies (GWAS) data of TT, BT and CRC, we utilized bidirectional two-sample MR methods to analyze their interrelationships. Causal relationship analysis was conducted using inverse variance weighting (IVW), MR-Egger, weighted median, simple mode and weighted mode. Sensitivity analyses were performed to examine the stability of the causal relationships.

Results: The bidirectional MR analysis revealed one standard deviation (SD) increase in genetically predicted BT increased the risk of CRC [IVW: odds ratio (OR) =1.834, 95% confidence interval (CI): 1.121-3.001, P=0.02] and there was no causal relationship of CRC on BT. There was no causal relationship between CRC and TT.

Conclusions: The findings of this study revealed a causal effect of BT on the risk of CRC, and CRC may not affect BT levels. Additionally, there was no causal relationship found between CRC and TT. Our results enhance the understanding of the real causal relationship between testosterone and CRC.

Background: Disulfidptosis and ferroptosis are emerging cell death modalities crucial to cancer progression, yet their prognostic potential in colon cancer (CC) remains underexplored. This study develops and validates a prognostic model based on DRD4 and SLC2A3, two genes involved in key biological processes in CC. DRD4 regulates cell proliferation, migration, and apoptosis, while SLC2A3 enhances glucose uptake via the Warburg effect, promoting tumor growth. High expression of both genes is linked to poor prognosis, advanced stages, and increased aggressiveness, enabling precise stratification of patients and accurate prognostic predictions.

Methods: Transcriptomic and clinical data from 476 CC samples and 41 normal colon samples were obtained from The Cancer Genome Atlas (TCGA) database, with 452 patient samples utilized for survival analysis. A training cohort and a validation cohort were generated through random allocation. Disulfidptosis-related ferroptosis genes (DRFGs) were identified using Pearson correlation analysis, and a prognostic model was built using the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. External validation was performed using the Gene Expression Omnibus (GEO) datasets (GSE17538 and GSE38832), and clinical samples were further analyzed through immunohistochemistry. Predictors in the nomogram included age, gender, tumor stage, and risk score. The C-index of the final model was used to assess its prognostic accuracy.

Results: The results were validated using external cohorts from the GEO database and immunohistochemistry experiments. A prognostic model incorporating DRD4 and SLC2A3 effectively stratified CC patients into high- and low-risk groups, revealing distinct differences in survival times, immune landscapes, and biological characteristics. High expression levels of DRD4 and SLC2A3 correlated with advanced clinicopathological stages and poor prognosis, with a C-index of 0.75 indicating strong predictive accuracy. Immunohistochemistry confirmed the upregulation of both genes in CC tissues, further validating the model's clinical relevance.

Conclusions: This DRFG-based prognostic model offers an effective tool for predicting clinical outcomes in CC and can guide personalized treatment strategies. The upregulation of DRD4 and SLC2A3 suggests their potential as therapeutic targets. Future studies should focus on elucidating the underlying mechanisms of these biomarkers to enhance their clinical application.

Background: Oxidative phosphorylation (OXPHOS) is a major energy resource occurring in mitochondria. Targeting OXPHOS-related genes has emerged as potential targets for cancer therapy. This study aimed to explore the significance of OXPHOS-related genes in breast cancer (BRCA).

Methods: Differentially expressed genes (DEGs) related to OXPHOS in BRCA were identified using packages of Limma and VennDiagram using the data from public databases. A prognostic model based on differentially expressed OXPHOS-related genes was constructed using least absolute shrinkage and selection operator Cox regression analyses and then evaluated through Kaplan-Meier and receiver operator characteristic (ROC) curves. Additionally, gene set variate analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to explore the potential pathways involved in BRCA. Furthermore, the tumor microenvironment (TME) difference between low- and high-risk BRCA groups was investigated. The prognostic significance of hub genes was then examined. We conducted a protein-protein interaction (PPI) network to uncover the potential gene interactions and identify key genes, whose expressions were validated in cells.

Results: Our analyses revealed 234 differentially expressed OXPHOS-related genes, from which a nine-gene (ATP5PF, FOXP3, IGF2, IREB2, MIEF2, NOTCH1, PDE12, SHC1, and UCP3) prognostic model was constructed. Patients in the high-risk group exhibited poorer survival outcomes and a suppressed immune microenvironment compared to the low-risk group. Additionally, except for IGF2, abnormal expression levels of hub genes were significantly associated with poor prognosis of BRCA patients. GSVA and GSEA highlighted the involvement of TME-related pathways, such as transforming growth factor beta (TGF-β) and mechanistic target of rapamycin (mTOR) signaling pathways. PPI network identified 4 common genes that interacted with all hub genes. The in vitro experiment on the key genes showed a consistent result with the bioinformatics finding.

Conclusions: Our study provides insights into the prognostic biomarkers and molecular mechanisms in BRCA, offering potential therapeutic avenues and guiding personalized treatment strategies for improved patient outcomes.

Background: The treatment of esophageal squamous cell carcinoma (ESCC) patients varies considerably depending upon whether lymph node metastasis (LNM) is present. Patients with ESCC can particularly benefit from neoadjuvant therapy if LNM is accurately diagnosed before surgery. Long noncoding RNA (lncRNA) has been confirmed to be closely related to the development of metastases in ESCC, but much remains unknown regarding the relationship between LNM and lncRNA. The purpose of our study was to investigate relationship between LNM and lncRNA, and create a diagnostic model for predicting LNM in ESCC before surgery.

Methods: We used quantitative real-time polymerase chain reaction (qRT-PCR) to detect the expression of LINC02381. We also verified the in vitro effect of LINC02381 on the growth and metastasis of ESCC in the KYSE510 and KYSE180 cell lines. We used the Kaplan-Meier (KM) method and the log-rank test to confirm the differences of overall survival (OS) and disease-free survival (DFS) in LINC02381 expression. We used univariate and multivariate logistic regression analyses to screen for clinical characteristics and assessed their clinical diagnostic efficacy using receiver operating characteristic (ROC) curves. The model was validated with the area under the curve (AUC) and calibration curves and visualized through a nomogram.

Results: qRT-PCR suggested a significant elevation of LINC02381 expression in ESCC tissues compared with normal esophageal epithelial tissues (P<0.001) and in ESCC tissues with LNM (P<0.001). Analysis of OS and DFS indicated that the high expression of LINC02381 and lymph node positivity were associated with poor prognosis. Combined analysis showed that patients with both a high expression of LINC02381 and lymph node positivity had the worst prognosis. High expression of LINC02381 was associated with poor differentiation, tumor-node-metastasis (TNM) staging, and LNM in ESCC. Presence of LNM was also closely associated with tumor differentiation and primary tumor staging. Univariate and multivariate logistic regression analyses identified that primary tumor staging, tumor differentiation, and LINC02381 expression were independent influencing factors. In the ROC curve analysis of the risk model, the AUC for LINC02381 expression was 0.822 and increased to 0.913 when primary tumor staging and tumor differentiation were added. We further conducted calibration curve analysis to display the calibration of our final model. A nomogram was used to display the predictive variables. The in vitro experiments demonstrated that the knockdown of LINC02381 could inhibit the growth and metastasis of ESCC.

Conclusions: LINC02381 may serve as a biomarker for predicting LNM. Our risk model can assist in predicting LNM in clinical practice, inform the decision to implement neoadjuvant therapy before surgery, and therefore improve prognosis.

Background: Lung cancer is the most common malignant tumor in China. In 2016, more than 800,000 new cases of lung cancer were diagnosed in China. Squamous cell carcinoma of the lung, a type of non-small cell lung cancer (NSCLC), accounts for 25-30% of all lung cancer cases, and has an overall 5-year survival rate of about 32.53%, lower than adenocarcinoma for which there have been far more therapeutic advances in the last few decades. The purpose of this study was to explore the mechanisms of the disease and to identify potential prognostic biomarkers.

Methods: This study analyzed lung squamous cell carcinoma of the lung tissues and paraneoplastic tissues to identify differentially expressed genes (DEGs). We conducted a Gene Set Enrichment Analysis and prognostic analysis by constructing competing endogenous RNA (ceRNA) networks; we performed a correlation analysis of the target genes and verified the targeting relationship of the ceRNA by cellular assays. We assessed the effects of the target genes on tumor cell proliferation, invasion and apoptosis by Cell Counting Kit-8 (CCK-8) assays, invasion assays, and caspase 3/7 assays, respectively.

Results: We identified 4,039 downregulated genes and 1,924 upregulated genes. The p53 pathway, cell-cycle pathway and mismatch-repair (MMR) pathway were activated, while the mitogen-activated protein kinase pathway was inhibited. Two ceRNA networks centered on the long non-coding RNAs (lncRNAs) MAGI2-AS3 and LINC01089 were constructed. MAGI2-AS3 was found to regulate five messenger RNAs (mRNAs) (i.e., MBNL2, ATP5L, FAM103A1, MDH1, and STXBP1) through three microRNAs (miRNAs), whereas LINC01089 was found to regulate six mRNAs (i.e., ZFP36L2, APBB2, PDLIM3, MYADM, PHF5A, and SLC26A9) through two miRNAs. The expression of these lncRNAs and mRNAs was significantly associated with prognosis (P<0.05). A significant correlation was also found between the expression of MAGI2-AS3 and MBNL2 (R=0.51), and both signatures were also significantly associated with prognosis. We also found that MAGI2-AS3 and MBNL2 had a regulatory relationship at the cellular level, for example, high expression of MBNL2 was noted to inhibit cancer cell proliferation and migration yet promote apoptosis.

Conclusions: MAGI-AS3 and MBNL2 are both differentially expressed in squamous cell carcinoma of the lung and are potential prognostic markers. A significant association was also found between MAGI2-AS3 and the expression of MBNL2 (R=0.51). High expression of MBNL2 inhibits cancer cell proliferation and migration, yet promotes cancer cell apoptosis.

Background: Tertiary lymphoid structures (TLS), consisting of T cell zones, B cell follicles, and germinal centers (GCs), are ectopic lymphoid tissue that form within non-lymphoid tissue. It has recently become a focus of attention. The TLS serve as an effective site for generating an anti-tumor inflammatory response by infiltrating immune cells, especially plasma cells. Thus, we aimed to explore the role of both TLS and plasma cells in influencing the prognosis of lung adenocarcinoma (LUAD).

Methods: Single-cell RNA sequencing (scRNA-seq) data were obtained from the Gene Expression Omnibus (GEO) database, and bulk RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Seurat R package was used to process scRNA-seq data and identify clusters by the marker genes with Kaplan-Meier (KM) curves plotted to predict the prognosis. Finally, hematoxylin and eosin (H&E) staining and multiplex immunofluorescence analysis were conducted to corroborate our suspicions.

Results: Seven clusters were identified in LUAD based on scRNA-seq data, with the number of B cells differing significantly between early and advanced cohorts. The plasma cells were also increased in advanced lung cancer (LC) and the number of TLS was significantly related to tumor stage. Then, via KM method, we confirmed that both plasma cells and TLS were associated with patient outcomes. Finally, H&E staining and multiplex immunofluorescence analysis verified the correlation between the two.

Conclusions: Plasma cells and TLS can effectively predict the prognosis of LUAD. In the tumor microenvironment (TME) of advanced tumors, plasma cells might be in a state of functional exhaustion. Comprehensive characterization of TLS and corresponding B‑cell pathways may help to activate the function of plasma cells and provide new strategies for cancer treatment.