Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

LINC00571 drives tricarboxylic acid cycle metabolism in triple-negative breast cancer through HNRNPK/ILF2/IDH2 axis.

BACKGROUND: Triple-negative breast cancer is a complex breast malignancy subtype characterized by poor prognosis. The pursuit of effective therapeutic approaches for this subtype is considerably challenging. Notably, recent research has illuminated the key role of the tricarboxylic acid cycle in cancer metabolism and the complex landscape of tumor development. Concurrently, an emerging body of evidence underscores the noteworthy role that long non-coding RNAs play in the trajectory of breast cancer development. Despite this growing recognition, the exploration of whether long non-coding RNAs can influence breast cancer progression by modulating the tricarboxylic acid cycle has been limited. Moreover, the underlying mechanisms orchestrating these interactions have not been identified. METHODS: The expression levels of LINC00571 and IDH2 were determined through the analysis of the public TCGA dataset, transcriptome sequencing, qRT‒PCR, and Western blotting. The distribution of LINC00571 was assessed using RNA fluorescence in situ hybridization. Alterations in biological effects were evaluated using CCK-8, colony formation, EdU, cell cycle, and apoptosis assays and a tumor xenograft model. To elucidate the interaction between LINC00571, HNRNPK, and ILF2, RNA pull-down, mass spectrometry, coimmunoprecipitation, and RNA immunoprecipitation assays were performed. The impacts of LINC00571 and IDH2 on tricarboxylic acid cycle metabolites were investigated through measurements of the oxygen consumption rate and metabolite levels. RESULTS: This study revealed the complex interactions between a novel long non-coding RNA (LINC00571) and tricarboxylic acid cycle metabolism. We validated the tumor-promoting role of LINC00571. Mechanistically, LINC00571 facilitated the interaction between HNRNPK and ILF2, leading to reduced ubiquitination and degradation of ILF2, thereby stabilizing its expression. Furthermore, ILF2 acted as a transcription factor to enhance the expression of its downstream target gene IDH2. CONCLUSIONS: Our study revealed that the LINC00571/HNRNPK/ILF2/IDH2 axis promoted the progression of triple-negative breast cancer by regulating tricarboxylic acid cycle metabolites. This discovery provides a novel theoretical foundation and new potential targets for the clinical treatment of triple-negative breast cancer.