PLOD2 Is a Potent Prognostic Marker and Associates with Immune Infiltration in Cervical Cancer

PLOD2 exacerbates cervical squamous cell carcinoma by suppressing p53 by binding to YAP1

Procollagen‑lysine, 2‑oxoglutarate 5‑dioxygenase 2 (PLOD2) has been identified as an oncogene involved in the progression of several human cancers. However, its role in cervical squamous cell carcinoma (CESC) and its underlying mechanisms are not well understood. In the present study, several public databases, RT‑qPCR and western blotting were employed to detect the expression of PLOD2 and the prognosis in CESC. Cell counting kit‑8 assay, wound healing assay, Transwell assay, western blotting and flow cytometry were utilized to assess the proliferation, migration and cell apoptosis of CESC cells. Cellular senescence was examined by RT‑qPCR and β‑galactosidase staining. Prediction of PLOD2 binding to Yes‑associated protein 1 (YAP1) was assessed using BioGrid, HDock and co‑immunoprecipitation, and p53 and p21 signaling were assessed using immunofluorescence staining. The findings indicated that the expression of PLOD2 was elevated in CESC tissues and cell lines, and PLOD2 silencing caused the inhibition of CESC cell proliferation, migration and the promotion of apoptosis and senescence of CESC cells. PLOD2 was predicted to be bound to YAP1 and YAP1 overexpression reversed the effects of PLOD2 silencing on CESC cell proliferation, cell migration, apoptosis and senescence. In addition, PLOD2 facilitated CESC progression by regulating the P53 pathway through YAP1. PLOD2 exerted pro‑oncogenic effects on CESC through the p53 pathway by binding to YAP1. These findings provide new perspectives for the future study of PLOD2‑targeted therapy for CESC.

Crosstalk of non-apoptotic RCD panel in hepatocellular carcinoma reveals the prognostic and therapeutic optimization

Non-apoptotic regulated cell death (RCD) of tumor cells profoundly affects tumor progression and plays critical roles in determining response to immune checkpoint inhibitors (ICIs). Prognosis-distinctive HCC subtypes were identified by consensus cluster analysis based on the expressions of 507 non-apoptotic RCD genes obtained from databases and literature. Meanwhile, a set of bioinformatic tools was integrated to analyze the differences of the tumor immune microenvironment infiltration, genetic mutation, copy number variation, and epigenetics alternations within two subtypes. Finally, a non-apoptotic RCDRS signature was constructed and its reliability was evaluated in HCC patients' tissues. The high-RCDRS HCC subgroup showed a significantly lower overall survival and less sensitivity to ICIs compared to low-RCDRS subgroup, but higher sensitivity to cisplatin, paclitaxel, and sorafenib. Overall, we established an RCDRS panel consisting of four non-apoptotic RCD genes, which might be a promising predictor for evaluating HCC prognosis, guiding therapeutic decision-making, and ultimately improving patient outcomes.

Identification of Potential Genes and Critical Pathways in Postoperative Recurrence of Crohn's Disease by Machine Learning And WGCNA Network Analysis

Background

Crohn's disease (CD) is a chronic idiopathic inflammatory bowel disease affecting the entire gastrointestinal tract from the mouth to the anus. These patients often experience a period of symptomatic relapse and remission. A 20 - 30% symptomatic recurrence rate is reported in the first year after surgery, with a 10% increase each subsequent year. Thus, surgery is done only to relieve symptoms and not for the complete cure of the disease. The determinants and the genetic factors of this disease recurrence are also not well-defined. Therefore, enhanced diagnostic efficiency and prognostic outcome are critical for confronting CD recurrence.

Methods

We analysed ileal mucosa samples collected from neo-terminal ileum six months after surgery (M6=121 samples) from Crohn's disease dataset (GSE186582). The primary aim of this study is to identify the potential genes and critical pathways in post-operative recurrence of Crohn's disease. We combined the differential gene expression analysis with Recursive feature elimination (RFE), a machine learning approach to get five critical genes for the postoperative recurrence of Crohn's disease. The features (genes) selected by different methods were validated using five binary classifiers for recurrence and remission samples: Logistic Regression (LR), Decision tree classifier (DT), Support Vector Machine (SVM), Random Forest classifier (RF), and K-nearest neighbor (KNN) with 10-fold cross-validation. We also performed weighted gene co-expression network analysis (WGCNA) to select specific modules and feature genes associated with Crohn's disease postoperative recurrence, smoking, and biological sex. Combined with other biological interpretations, including Gene Ontology (GO) analysis, pathway enrichment, and protein-protein interaction (PPI) network analysis, our current study sheds light on the in-depth research of CD diagnosis and prognosis in postoperative recurrence.

Results

PLOD2, ZNF165, BOK, CX3CR1, and ARMCX4, are the important genes identified from the machine learning approach. These genes are reported to be involved in the viral protein interaction with cytokine and cytokine receptors, lysine degradation, and apoptosis. They are also linked with various cellular and molecular functions such as Peptidyl-lysine hydroxylation, Central nervous system maturation, G protein-coupled chemoattractant receptor activity, BCL-2 homology (BH) domain binding, Gliogenesis and negative regulation of mitochondrial depolarization. WGCNA identified a gene co-expression module that was primarily involved in mitochondrial translational elongation, mitochondrial translational termination, mitochondrial translation, mitochondrial respiratory chain complex, mRNA splicing via spliceosome pathways, etc.; Both the analysis result emphasizes that the mitochondrial depolarization pathway is linked with CD recurrence leading to oxidative stress in promoting inflammation in CD patients.

Conclusion

These key genes serve as the novel diagnostic biomarker for the postoperative recurrence of Crohn's disease. Thus, among other treatment options present until now, these biomarkers would provide success in both diagnosis and prognosis, aiming for a long-lasting remission to prevent further complications in CD.

Prognostic model based on telomere-related genes predicts the risk of oral squamous cell carcinoma

BACKGROUND

This study investigated a potential prognostic model based on telomere-related genes (TRGs) for the clinical prediction of oral squamous cell carcinoma (OSCC).

METHODS

Gene expression data and associated clinical phenotypes were obtained from online databases. Differentially expressed (DE)-TRGs were identified between OSCC and normal samples, followed by protein-protein interaction and enrichment analyses. Subsequently, the prognostic genes explored based on the DE-TRGs and survival data were applied in the establishment of the current prognostic model, and an integrated analysis was performed between high- and low-risk groups using a prognostic model. The expression of certain prognostic genes identified in the present study was validated using qPCR analysis and/or western blot in OSCC cell lines and clinical samples.

RESULTS

169 DE-TRGs were identified between the OSCC samples and controls. DE-TRGs are mainly involved in functions such as hypoxia response and pathways such as the cell cycle. Eight TRGs (CCNB1, PDK4, PLOD2, RACGAP1, MET, PLK1, KPNA2, and CCNA2) associated with OSCC survival and prognosis were used to construct a prognostic model. qPCR analysis and western blot showed that most of the eight prognostic genes were consistent with the current bioinformatics results. Analysis of the high- and low-risk groups for OSCC determined by the prognostic model showed that the current prognostic model was reliable.

CONCLUSIONS

A novel prognostic model for OSCC was constructed by TRGs. PLOD2 and APLK1 may participate in the progression of OSCC via responses to hypoxia and cell cycle pathways, respectively. TRGs, including KPNA2 and CCNA2, may serve as novel prognostic biomarkers for OSCC.

Comprehensive Analysis of the Expression, Prognosis, and Biological Significance of PLOD Family in Bladder Cancer

Background

Large numbers of studies have identified that procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) family members play important roles in tumorigenesis and tumor progression in various cancers. However, the expression pattern, clinical value and function of PLOD family have yet to be analyzed systematically and comprehensively in bladder urothelial carcinoma (BLCA).

Methods

We investigated the transcriptional levels, genetic alteration, biological function, immune cell infiltration, data on survival of PLODs in patients with BLCA based on UALCAN, the Cancer Genome Atlas (TCGA) database, Gene Expression Profiling Interactive Analysis (GEPIA), TIMER, STRING, cBioPortal and GSCALite databases. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software using the Cluster Profiler Bioconductor package. Protein-protein interaction (PPI) network was established by STRING and visualized by using R version (3.6.3) software. Survival analysis was performed using the packages "survminer".

Results

The mRNA and protein expression patterns of PLOD family members were noticeably increased in BLC compared with normal tissue. The mRNA expression levels of PLOD1-2 genes were significantly correlated with histological subtypes and PLOD1 was significantly correlated with pathological stage. Furthermore, the high expression levels of PLOD1-2 were remarkably associated with poor overall survival (OS) in BLCA patients, meanwhile high expression levels of PLOD1 and PLOD3 were markedly associated with poor progression-free interval (PFI). In co-expression gene analysis, 50 genes were primarily associated with the differentially expressed PLODs in BLCA. Functional enrichment analysis revealed that protein hydroxylation, collagen fibril organization, and lysine degradation were key biological functions of PLODs in BLCA. Moreover, PLOD family genes were identified as being associated with the activities of tumor-infiltrating immune cells and closely associated with immune responses in BLCA.

Conclusion

PLOD family members might serve as potential therapeutic targets and prognostic markers for BLCA patients' survival.

PLOD Family: A Novel Biomarker for Prognosis and Personalized Treatment in Soft Tissue Sarcoma

Despite various treatment attempts, the heterogenous group of soft tissue sarcomata (STS) with more than 100 subtypes still shows poor outcomes. Therefore, effective biomarkers for prognosis prediction and personalized treatment are of high importance. The Procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenase (PLOD) gene family, which is related to multiple cancer entities, consists of three members which encode important enzymes for the formation of connective tissue. The relation to STS, however, has not yet been explored. In this study, data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to analyze the role of PLOD1–3 in STS. It was found that an overexpression of PLOD family members correlates with poor prognosis, which might be due to an increased infiltration of immune-related cells in the tumor microenvironment. In STS, the expression of PLOD genes could be a novel biomarker for prognosis and a personalized, more aggressive treatment in these patients.