Hydrogen sulfide-mediated persulfidation regulates homocysteine metabolism and enhances ferroptosis in non-small cell lung cancer.

Hydrogen sulfide (H₂S), a metabolite of the transsulfuration pathway, has been implicated in ferroptosis, a unique form of cell death caused by lipid peroxidation. While the exact mechanisms controlling ferroptosis remain unclear, our study reveals that H₂S sensitizes human non-small cell lung cancer (NSCLC) cells to this process, particularly when cysteine levels are low. Combining H₂S with cystine depletion significantly enhances the effectiveness of ferroptosis-based cancer therapy.

ATF3-CBS signaling axis coordinates ferroptosis and tumorigenesis in colorectal cancer.

The induction of ferroptosis is promising for cancer therapy. However, the mechanisms enabling cancer cells to evade ferroptosis, particularly in low-cystine environments, remain elusive. Our study delves into the intricate regulatory mechanisms of Activating transcription factor 3 (ATF3) on Cystathionine β-synthase (CBS) under cystine deprivation stress, conferring resistance to ferroptosis in colorectal cancer (CRC) cells.

METTL17 coordinates ferroptosis and tumorigenesis by regulating mitochondrial translation in colorectal cancer.

Ferroptosis, an iron-dependent lipid peroxidation-induced form of regulated cell death, shows great promise as a cancer therapy strategy. Despite the critical role of mitochondria in ferroptosis regulation, the underlying mechanisms remain elusive. This study reveals that the mitochondrial protein METTL17 governs mitochondrial function in colorectal cancer (CRC) cells through epigenetic modulation.

CovidShiny: An Integrated Web Tool for SARS-CoV-2 Mutation Profiling and Molecular Diagnosis Assay Evaluation In Silico.

The coronavirus disease 2019 (COVID-19) pandemic is still ongoing, with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continuing to evolve and accumulate mutations. While various bioinformatics tools have been developed for SARS-CoV-2, a well-curated mutation-tracking database integrated with in silico evaluation for molecular diagnostic assays is currently unavailable. To address this, we introduce CovidShiny, a web tool that integrates mutation profiling, in silico evaluation, and data download capabilities for genomic sequence-based SARS-CoV-2 assays and data download.

A qualitative transcriptional prognostic signature for patients with stage I-II pancreatic ductal adenocarcinoma.

Accurately prognostic evaluation of patients with stage I-II pancreatic ductal adenocarcinoma (PDAC) is of importance to treatment decision and patient management. Most previously reported prognostic signatures were based on risk scores summarized from quantitative expression measurements of signature genes, which are susceptible to experimental batch effects and impractical for clinical applications. Based on the within-sample relative expression orderings of genes, we developed a robust qualitative transcriptional prognostic signature, consisting of 64 gene pairs (64-GPS), to predict the overall survival (OS) of 161 stage I-II PDAC patients in the training dataset who were treated with surgery only.

Identification of Common and Subtype-Specific Mutated Sub-Pathways for a Cancer.

The heterogeneity of cancer is a big obstacle for cancer diagnosis and treatment. Prioritizing combinations of driver genes that mutate in most patients of a specific cancer or a subtype of this cancer is a promising way to tackle this problem. Here, we developed an empirical algorithm, named PathMG, to identify common and subtype-specific mutated sub-pathways for a cancer.

Identifying reproducible cancer-associated highly expressed genes with important functional significances using multiple datasets.

Identifying differentially expressed (DE) genes between cancer and normal tissues is of basic importance for studying cancer mechanisms. However, current methods, such as the commonly used Significance Analysis of Microarrays (SAM), are biased to genes with low expression levels. Recently, we proposed an algorithm, named the pairwise difference (PD) algorithm, to identify highly expressed DE genes based on reproducibility evaluation of top-ranked expression differences between paired technical replicates of cells under two experimental conditions.