Insights Into the Function and Clinical Application of HDAC5 in Cancer Management

Histone deacetylase 5 (HDAC5) is a class II HDAC. Aberrant expression of HDAC5 has been observed in multiple cancer types, and its functions in cell proliferation and invasion, the immune response, and maintenance of stemness have been widely studied. HDAC5 is considered as a reliable therapeutic target for anticancer drugs. In light of recent findings regarding the role of epigenetic reprogramming in tumorigenesis, in this review, we provide an overview of the expression, biological functions, regulatory mechanisms, and clinical significance of HDAC5 in cancer

Multi-omics analysis to identify driving factors in colorectal cancer

Aim: We aim to identify driving genes of colorectal cancer (CRC) through multi-omics analysis. Materials & methods: We downloaded multi-omics data of CRC from The Cancer Genome Atlas dataset. Integrative analysis of single-nucleotide variants, copy number variations, DNA methylation and differentially expressed genes identified candidate genes that carry CRC risk. Kernal genes were extracted from the weighted gene co-expression network analysis. A competing endogenous RNA network composed of CRC-related genes was constructed. Biological roles of genes were further investigated in vitro. Results: We identified LRRC26 and REP15 as novel prognosis-related driving genes for CRC. LRRC26 hindered tumorigenesis of CRC in vitro. Conclusion: Our study identified novel driving genes and may provide new insights into the molecular mechanisms of CRC

Additional file 3 of Lipid metabolic features of T cells in the Tumor Microenvironment

Supplementary Material

Scatter-plot between the drug responses predicted by the DBDNMF model and the original responses in CCLE.

Scatter-plot between the drug responses predicted by the DBDNMF model and the original responses in CCLE.</p

Comparison histogram of PCC_sr and RMSE_sr for the drug targets that are involved in the PI3K pathway of GDSC.

A) Comparison histogram of PCC_sr for drugs targeting the PI3K pathway; B) Comparison histogram of RMSE_sr for drugs targeting the PI3K pathway.</p

The ave_PCC (ave_PCC_sr), ave_RMSE (ave_RMSE_sr) of NeuMF vs. DBDNMF for cold-start scenarios on CCLE dataset.

The ave_PCC (ave_PCC_sr), ave_RMSE (ave_RMSE_sr) of NeuMF vs. DBDNMF for cold-start scenarios on CCLE dataset.</p

Comparison of results with and without GER preprocessing for prediction.

A) Radar plots of PCC_sr and RMSE_sr for 23 drugs in CCLE; B) Box-plots of ave_PCC (ave_PCC_sr), ave_RMSE (ave_RMSE_sr) on the GDSC.</p

The ave_PCC (ave_PCC_sr), ave_RMSE (ave_RMSE_sr) of TGSA, NeuMF vs. DBDNMF for cold-start scenarios on GDSC dataset.

The ave_PCC (ave_PCC_sr), ave_RMSE (ave_RMSE_sr) of TGSA, NeuMF vs. DBDNMF for cold-start scenarios on GDSC dataset.</p

Additional file 2 of Lipid metabolic features of T cells in the Tumor Microenvironment

Supplementary Material

Additional file 4 of Lipid metabolic features of T cells in the Tumor Microenvironment

Supplementary Material