BOP1 Used as a Novel Prognostic Marker and Correlated with Tumor Microenvironment in Pan-Cancer

Prognostic and Immune Landscape Analysis of Ubiquitination-related Genes in Hepatocellular Carcinoma: Based on Bulk and Single-cell RNA Sequencing Data

Background: Despite significant advances in tumor immunotherapy, hepatocellular carcinoma (HCC) remains a malignancy with a challenging prognosis. The increasing research emphasizes the crucial role of ubiquitination in tumor immunotherapy. However, the establishment of prognostic signatures based on ubiquitination-related genes (UbRGs) and their role in immunotherapy are still lacking in HCC. Methods: We employed datasets from TCGA and GEO for transcriptome differential expression analysis and single-cell RNA sequencing analysis. Applying weighted gene co-expression network analysis, cox regression, lasso, selection and visualization of the most relevant features, and gradient boosting machine, we identified hub UbRGs as a gene signature to develop a prognostic model. We evaluated the predictive utility concerning clinical characteristics as well as its role in the immune landscape and immunotherapy potential. Additionally, western blotting, reverse transcription-quantitative PCR, and immunofluorescence were employed to detect the expression and sub-localization of hub genes. Results: Three hub UbRGs (BOP1, CDC20, and UBE2S) were identified as a gene signature. In particular, the high-risk group exhibited notable characteristics, including higher tumor mutation burden, enrichment in immune-related pathways, up-regulation immune checkpoint, and higher immunity scores. Treatment response to immunotherapy varied based on the expression of PD-1 and CTLA-4. Furthermore, single-cell data analysis revealed heterogeneous expression of hub UbRGs across different cell subtypes, while cytological experiments provided additional confirmation of the high expression of hub UbRGs in HCC. Conclusion: Our study provides valuable insights into the identification of novel ubiquitination-related biomarkers with potential applications for prognosis, immunotherapy prediction, and drug sensitivity in HCC.

Characterization of MYBL1 Gene in Triple-Negative Breast Cancers and the Genes' Relationship to Alterations Identified at the Chromosome 8q Loci

The MYBL1 gene is a strong transcriptional activator involved in events associated with cancer progression. Previous data show MYBL1 overexpressed in triple-negative breast cancer (TNBC). There are two parts to this study related to further characterizing the MYBL1 gene. We start by characterizing MYBL1 reference sequence variants and isoforms. The results of this study will help in future experiments in the event there is a need to characterize functional variants and isoforms of the gene. In part two, we identify and validate expression and gene-related alterations of MYBL1, VCIP1, MYC and BOP1 genes in TNBC cell lines and patient samples selected from the Breast Invasive Carcinoma TCGA 2015 dataset available at cBioPortal.org. The four genes are located at chromosomal regions 8q13.1 to 8q.24.3 loci, regions previously identified as demonstrating a high percentage of alterations in breast cancer. We identify alterations, including changes in expression, deletions, amplifications and fusions in MYBL1, VCPIP1, BOP1 and MYC genes in many of the same patients, suggesting the panel of genes is involved in coordinated activity in patients. We propose that MYBL1, VCPIP1, MYC and BOP1 collectively be considered as genes associated with the chromosome 8q loci that potentially play a role in TNBC pathogenesis.

LncRNA TYMSOS is a novel prognostic biomarker associated with immune infiltration in prostate cancer

The long noncoding RNA thymidylate synthetase opposite strand (lncRNA TYMSOS) plays an important role in cancers; however, its impact on prostate cancer (PCa) is still unclear. By analyzing the online data, we found that lncRNA TYMSOS was highly expressed in PCa and associated with T stage, Gleason score, age, and primary therapy outcome. The results of the ROC curve showed that lncRNA TYMSOS has a significant diagnostic ability. Furthermore, Kaplan-Meier analyses suggested that lncRNA TYMSOS plays an important role in progression-free survival (PFS). Increased lncRNA TYMSOS expression was an independent risk factor correlated with PFS in PCa patients. GSEA and GSVA indicated that the lncRNA TYMSOS was involved in the cell cycle, neurodegenerative diseases, oxidative phosphorylation, spliceosomes, and adaptive immune system pathways. Additionally, lncRNA TYMSOS expression was also associated with immune cell infiltrates and tumor mutational burden in PCa. Functional experiments were further conducted, and we verified that lncRNA TYMSOS played an oncogenic role in regulating PCa aggressiveness. Specifically, silencing of lncRNA TYMSOS suppressed cell proliferation, division and epithelial-mesenchymal transition (EMT) but promoted cell apoptosis in PCa cells, and conversely, lncRNA TYMSOS overexpression had the opposite effects. In summary, our study revealed that the lncRNA TYMSOS could be a biomarker and therapeutic target in PCa and participate in tumor-immune cell infiltration.

Identification of therapeutically potential targets and their ligands for the treatment of OSCC

Recent advancements in cancer biology have revealed molecular changes associated with carcinogenesis and chemotherapeutic exposure. The available information is being gainfully utilized to develop therapies targeting specific molecules involved in cancer cell growth, survival, and chemoresistance. Targeted therapies have dramatically increased overall survival (OS) in many cancers. Therefore, developing such targeted therapies against oral squamous cell carcinoma (OSCC) is anticipated to have significant clinical implications. In the current work, we have identified drug-specific sensitivity-related prognostic biomarkers (BOP1, CCNA2, CKS2, PLAU, and SERPINE1) using gene expression, Cox proportional hazards regression, and machine learning in OSCC. Dysregulation of these markers is significantly associated with OS in many cancers. Their elevated expression is related to cellular proliferation and aggressive malignancy in various cancers. Mechanistically, inhibition of these biomarkers should significantly reduce cellular proliferation and metastasis in OSCC and should result in better OS. It is pertinent to note that no effective small-molecule candidate has been identified against these biomarkers to date. Therefore, a comprehensive in silico drug design strategy assimilating homology modeling, extensive molecular dynamics (MD) simulation, and ensemble molecular docking has been applied to identify potential compounds against identified targets, and potential molecules have been identified. We hope that this study will help in deciphering potential genes having roles in chemoresistance and a significant impact on OS. It will also result in the identification of new targeted therapeutics against OSCC.