Identification of UBE2I as a Novel Biomarker in ccRCC Based on a Large-Scale CRISPR-Cas9 Screening Database and Immunohistochemistry

Increased Immune Infiltration and Improved Prognosis of Head and Neck Squamous Cell Carcinoma Associated with Reduced Ancient Ubiquitous Protein 1 Gene Expression

This study aimed to explore the molecular mechanism underlying the prognostic role of ancient ubiquitous protein 1 (AUP1) in head and neck squamous cell carcinoma (HNSCC) and its relationship with the tumor immune microenvironment. Various web resources were used to analyze the differential expression of AUP1 and its role in the HNSCC pathogenesis. A nomogram aimed at predicting 1-, 3-, and 5-year survival rates was developed based on the patient's clinicopathological characteristics and AUP1 expression pattern. Several algorithms and analytical tools were used to explore the correlation between AUP1 expression and sensitivity to immune checkpoint gene therapy by evaluating infiltrating immune cells in patients with HNSCC. Higher AUP1 mRNA and protein expression levels were observed in most tumors and HNSCC than in the normal tissues. High AUP1 expression was an independent predictive risk factor for the overall survival of patients as it was closely associated with the patients' T, M, clinical, and pathological stages and lymphovascular invasion in HNSCC. In conclusion, AUP1 is involved in the occurrence and progression of HNSCC, may be used as an independent prognostic factor in patients with HNSCC, and could serve as a potential intervention target to improve immunotherapy sensitivity in HNSCC.

Establishment of a SUMO pathway related gene signature for predicting prognosis, chemotherapy response and investigating the role of EGR2 in bladder cancer

Background: Bladder cancer is a prevalent malignancy with significant clinical implications. Small Ubiquitin-like Modifier (SUMO) pathway related genes (SPRG) have been implicated in the development and progression of cancer. Methods: In this study, we conducted a comprehensive analysis of SPRG in bladder cancer. We analyzed gene expression and prognostic value of SPRG and developed a SPRG signature (SPRGS) prognostic model based on four genes (HDAC4, TRIM27, EGR2, and UBE2I) in bladder cancer. Furthermore, we investigated the relationship between SPRGS and genomic alterations, tumor microenvironment, chemotherapy response, and immunotherapy. Additionally, we identified EGR2 as a key SPRG in bladder cancer. The expression of EGR2 in bladder cancer was detected by immunohistochemistry, and the cell function experiment clarified the effect of knocking down EGR2 on the proliferation, invasion, and migration of bladder cancer cells. Results: Our findings suggest that SPRGS hold promise as prognostic markers and predictive biomarkers for chemotherapy response and immunotherapy efficacy in bladder cancer. The SPRGS prognostic model exhibited high predictive accuracy for bladder cancer patient survival. We also observed correlations between SPRG and genomic alterations, tumor microenvironment, and response to chemotherapy. Immunohistochemical results showed that EGR2 was highly expressed in bladder cancer tissues, and its overexpression was associated with poor prognosis. Knockdown of EGR2 inhibited bladder cancer cell proliferation, invasion, and migration. Conclusion: This study provides valuable insights into the landscape of SPRGS in bladder cancer and their potential implications for personalized treatment strategies. The identification of EGR2 as a key SPRG and its functional impact on bladder cancer cells further highlights its significance in bladder cancer development and progression. Overall, SPRGS may serve as important prognostic markers and predictive biomarkers for bladder cancer patients, guiding treatment decisions and improving patient outcomes.

A novel pipeline for prioritizing cancer type-specific therapeutic vulnerabilities using DepMap identifies PAK2 as a target in head and neck squamous cell carcinomas

There is limited guidance on exploiting the genome-wide loss-of-function CRISPR screens in cancer Dependency Map (DepMap) to identify new targets for individual cancer types. This study integrated multiple tools to filter these data in order to seek new therapeutic targets specific to head and neck squamous cell carcinoma (HNSCC). The resulting pipeline prioritized 143 targetable dependencies that represented both well-studied targets and emerging target classes like mitochondrial carriers and RNA-binding proteins. In total, 14 targets had clinical inhibitors used for other cancers or nonmalignant diseases that hold near-term potential to repurpose for HNSCC therapy. Comparing inhibitor response data that were publicly available for 13 prioritized targets between the cell lines with high vs. low dependency on each target uncovered novel therapeutic potential for the PAK2 serine/threonine kinase. PAK2 gene dependency was found to be associated with wild-type p53, low PAK2 mRNA, and diploid status of the 3q amplicon containing PAK2. These findings establish a generalizable pipeline to prioritize clinically relevant targets for individual cancer types using DepMap. Its application to HNSCC highlights novel relevance for PAK2 inhibition and identifies biomarkers of PAK2 inhibitor response.

Gastric cancer peritoneal metastasis related signature predicts prognosis and sensitivity to immunotherapy in gastric cancer

Gastric cancer peritoneal metastases (GCPM) is a leading cause of GC-related death. Early detection of GCPM is critical for improving the prognosis of advanced GC. Differentially expressed genes (DEGs) were identified in the GSE62254 database to distinguish between GCPM and non-GCPM. The gastric cancer peritoneal metastases signature (GCPMs) was developed using DEGs. We analysed the effectiveness of GCPMs as indicators for prognosis, chemotherapy, and immune therapy response in GC patients. Subsequently, we analysed the correlation between GCPMs and immune microenvironment as well as immune escape in GC patients. Random forest model and immunohistochemistry was utilized to identify the crucial genes that can aid in the diagnosis of GCPM. We identified five DEGs and utilized their expression to construct GCPMs. Patients with high GCPMs had a higher likelihood of a poor prognosis, while those with low GCPMs appeared to potentially benefit more from chemotherapy. GCPMs were a dependable marker for predicting the response to immunotherapy. Additionally, GCPMs was found to be significantly linked to stromal score and cancer-associated fibroblasts. SYNPO2 has been identified as the gene with the highest significance in the diagnosis of GCPM. Immunohistochemistry suggests that SYNPO2-positive expression in tumour cells, fibroblasts, inflammatory cell may be associated with promoting peritoneal metastasis in GC. GCPMs have shown to be a promising biomarker for predicting the prognosis and response of GC patients to chemotherapy and immunotherapy. The use of GCPMs for individual tumour evaluation may pave the way for personalized treatment for GC patients in the future.

Modulation of AMPK Significantly Alters Uveal Melanoma Tumor Cell Viability

INTRODUCTION

Uveal melanoma (UM) responds poorly to targeted therapies or immune checkpoint inhibitors. Adenosine monophosphate-activated protein kinase (AMPK) is a pivotal serine/threonine protein kinase that coordinates vital processes such as cell growth. Targeting AMPK pathway, which represents a critical mechanism mediating the survival of UM cells, may prove to be a novel treatment strategy for UM. We aimed to demonstrate the effects of AMPK modulation on UM cells.

METHODS

In silico analyses were performed to compare UM and normal melanocyte cells via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA). The effects of AMPK modulation on cell viability and proliferation in UM cell lines with different molecular profiles (i.e., 92-1, MP46, OMM2.5, and Mel270) were investigated via XTT cell viability and proliferation assays after treating the cells with varying concentrations of A-769662 (AMPK activator) or dorsomorphin (AMPK inhibitor).

RESULTS

KEGG/GSEA studies demonstrated that genes implicated in the AMPK signaling pathway were differentially regulated in UM. Gene sets comprising genes involved in AMPK signaling and genes involved in energy-dependent regulation of mammalian target of rapamycin by liver kinase B1-AMPK were downregulated in UM. We observed gradual decreases in the numbers of viable UM cells as the concentration of A-769662 treatment increased. All UM cells demonstrated statistically significant decreases in cell viability when treated with 200 µm A-769662. Moreover, the effects of AMPK inhibition on UM cells were potent, since low doses of dorsomorphin treatment resulted in significant decreases in viabilities of UM cells. The half maximal inhibitory concentration (IC50) values confirmed the potency of dorsomorphin treatment against UM in vitro.

CONCLUSION

AMPK may act like a friend or a foe in cancer depending on the context. As such, the current study contributes to the literature in determining the effects of therapeutic strategies targeting AMPK in several UM cells. We propose a new perspective in the treatment of UM. Targeting AMPK pathway may open up new avenues in developing novel therapeutic approaches to improve overall survival in UM.

Elevated expression of LIF predicts a poor prognosis and promotes cell migration and invasion of clear cell renal cell carcinoma

Background

Renal cell carcinoma (RCC) is the seventh most common cancer in humans, of which clear cell renal cell carcinoma (ccRCC) accounts for the majority. Recently, although there have been significant breakthroughs in the treatment of ccRCC, the prognosis of targeted therapy is still poor. Leukemia inhibitory factor (LIF) is a pleiotropic protein, which is overexpressed in many cancers and plays a carcinogenic role. In this study, we explored the expression and potential role of LIF in ccRCC.

Methods

The expression levels and prognostic effects of the LIF gene in ccRCC were detected using TCGA, GEO, ICGC, and ArrayExpress databases. The function of LIF in ccRCC was investigated using a series of cell function approaches. LIF-related genes were identified by weighted gene correlation network analysis (WGCNA). GO and KEGG analyses were performed subsequently. Cox univariate and LASSO analyses were used to develop risk signatures based on LIF-related genes, and the prognostic model was validated in the ICGC and E-MTAB-1980 databases. Then, a nomogram model was constructed for survival prediction and validation of ccRCC patients. To further explore the drug sensitivity between LIF-related genes, we also conducted a drug sensitivity analysis based on the GDSC database.

Results

The mRNA and protein expression levels of LIF were significantly increased in ccRCC patients. In addition, a high expression of LIF has a poor prognostic effect in ccRCC patients. LIF knockdown can inhibit the migration and invasion of ccRCC cells. By using WGCNA, 97 LIF-related genes in ccRCC were identified. Next, a prognostic risk prediction model including eight LIF-related genes (TOB2, MEPCE, LIF, RGS2, RND3, KLF6, RRP12, and SOCS3) was developed and validated. Survival analysis and ROC curve analysis indicated that the eight LIF-related-gene predictive model had good performance in evaluating patients’ prognosis in different subgroups of ccRCC.

Conclusion

Our study revealed that LIF plays a carcinogenic role in ccRCC. In addition, we firstly integrated multiple LIF-related genes to set up a risk-predictive model. The model could accurately predict the prognosis of ccRCC, which offers clinical implications for risk stratification, drug screening, and therapeutic decision.