Elevated FBXL6 expression in hepatocytes activates VRK2-transketolase-ROS-mTOR-mediated immune evasion and liver cancer metastasis in mice

Prognostic value and drug sensitivity of F‑box and leucine‑rich repeat protein 6 in glioma

Gliomas are highly malignant and invasive tumors lacking clear boundaries. Previous bioinformatics and experimental analyses have indicated that F-box and leucine-rich repeat protein 6 (FBXL6), a protein crucial for the cell cycle and tumorigenesis, is highly expressed in certain types of tumors. The high expression level of FBXL6 is reported to promote tumor growth and adversely affect patient survival. However, the molecular mechanism, prognostic value and drug sensitivity of FBXL6 in glioma remain unclear. To address this, the present study analyzed FBXL6 expression in gliomas, utilizing data from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. Analysis of FBXL6 mRNA expression levels, combined with patient factors such as age, sex and tumor grade using Kaplan-Meier plots and nomograms, demonstrated a strong correlation between FBXL6 expression and glioma progression. Co-expression networks provided further insights into the biological function of FBXL6. Additionally, using CIBERSORT and TISDB tools, the correlation between FBXL6 expression correlation tumor-infiltrating immune cells and immune genes was demonstrated to be statistically significant. These findings were validated by examining FBXL6 mRNA and protein levels in glioma tissues using various techniques, including western blot, reverse transcription-quantitative PCR and immunohistochemistry. These assays demonstrated the role of FBXL6 in glioma progression. Furthermore, drug sensitivity analysis demonstrated a strong correlation between FBXL6 expression and various drugs, which indicated that FBXL6 may potentially act as a future promising therapeutic target in glioma treatment. Therefore, the present study identified FBXL6 as a diagnostic and prognostic marker in patients with gliomas and highlighted its potential role in glioma progression.

Robust machine-learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer

BACKGROUND

A minute fraction of patients stands to derive substantial benefits from immunotherapy, primarily attributable to immune evasion. Our objective was to formulate a predictive signature rooted in genes associated with cytotoxic T lymphocyte evasion (CERGs), with the aim of predicting outcomes and discerning immunotherapeutic response in colorectal cancer (CRC).

METHODS

101 machine learning algorithm combinations were applied to calculate the CERGs prognostic index (CERPI) under the cross-validation framework, and patients with CRC were separated into high- and low-CERPI groups. Relationship between immune cell infiltration levels, immune-related scores, malignant phenotypes and CERPI were further analyzed. Various machine learning methods were used to identify key genes related to both patient survival and immunotherapy benefits. Expression of HOXC6, G0S2, and MX2 was evaluated and the effects of HOXC6 and G0S2 on the viability and migration of a CRC cell line were in-vitro verified.

RESULTS

The CERPI demonstrated robust prognostic efficacy in predicting the overall survival of CRC patients, establishing itself as an independent predictor of patient outcomes. The low-CERPI group exhibited elevated levels of immune cell infiltration and lower scores for tumor immune dysfunction and exclusion, indicative of a greater potential benefit from immunotherapy. Moreover, there was a positive correlation between CERPI levels and malignant tumor phenotypes, suggesting that heightened CERPI expression contributes to both the occurrence and progression of tumors. Thirteen key genes were identified, and their expression patterns were scrutinized through the analysis of single-cell datasets. Notably, HOXC6, G0S2, and MX2 exhibited upregulation in both CRC cell lines and tissues. Subsequent knockdown experiments targeting G0S2 and HOXC6 resulted in a significant suppression of CRC cell viability and migration.

CONCLUSION

We developed the CERPI for effectively predicting survival and response to immunotherapy in patients, and these results may provide guidance for CRC diagnosis and precise treatment.