Abnormal lipid metabolism is the sign of tumour cells. Previous researches have revealed that the lipolytic pathway may contribute to the progression of colorectal cancer (CRC). However, adipose triglyceride lipase (ATGL) role in CRC cells remains unclear. Here, we find that elevated ATGL positively correlates with CRC clinical stages and negatively associates with overall survival. Overexpression of ATGL significantly promotes CRC cell proliferation, while knockdown of ATGL inhibits the proliferation and promotes the apoptosis of CRC cells in vitro. Moreover, in vivo experiments, ATGL promotes the growth of CRC cells. Mechanistically, ATGL enhances the carcinogenic function of CRC cells via promoting sphingolipid metabolism and CoA biosynthesis pathway‐related gene levels by degrading triglycerides, which provides adequate nutrition for the progression of CRC. Our researches clarify for the first time that ATGL is a novel oncogene in CRC and may provide an important prognostic factor and therapeutic target for CRC.

Effective biomarkers for the diagnosis of colorectal cancer (CRC) are essential for improving prognosis. Imbalance in regulation of N6-methyladenosine (m⁶A) RNA has been associated with a variety of cancers. However, whether the m⁶A RNA levels of peripheral blood can serve as a diagnostic biomarker for CRC is still unclear. In this research, we found that the m⁶A RNA levels of peripheral blood immune cells were apparently elevated in the CRC group compared with those in the normal controls (NCs) group. Furthermore, the m⁶A levels arose as CRC progressed and metastasized, while these levels decreased after treatment. The area under the curve (AUC) of the m⁶A levels was 0.946, which was significantly higher than the AUCs for carcinoembryonic antigen (CEA; 0.817), carbohydrate antigen 125 (CA125; 0.732), and carbohydrate antigen 19-9 (CA19-9; 0.771). Moreover, the combination of CEA, CA125, and CA19-9 with m⁶A levels improved the AUC to 0.977. Bioinformatics and qRT-PCR analysis further confirmed that the expression of m⁶A modifying regulator IGF2BP2 was markedly elevated in peripheral blood of CRC patients. Gene set variation analysis (GSVA) implied that monocyte was the most abundant m⁶A-modified immune cell type in CRC patients’ peripheral blood. Additionally, m⁶A modifications were negatively related to the immune response of monocytes. In conclusion, our results revealed that m⁶A RNA of peripheral blood immune cells was a prospective non-invasive diagnostic biomarker for CRC patients and might provide a valuable therapeutic target.

Objectives: The absence of non-invasive biomarkers for the early diagnosis of colorectal cancer (CRC) has contributed to poor prognosis. Extracellular vesicles (EVs) have emerged as promising candidates for cancer monitoring using liquid biopsy. However, the complexity of EVs isolation procedures and the absence of clear targets for detecting serum-derived EVs have hindered the clinical application of EVs in early CRC diagnosis. Methods: In the discovery phase, we conducted a comprehensive 4D-DIA proteomic analysis of serum-derived EVs samples from 37 individuals, performing an initial screening of EVs surface proteins. In the technical validation phase, we developed an extraction-free CRC-EVArray microarray to assess the expression of these potential EVs surface proteins in a multi-centre study comprising 404 individuals. In the application phase, the authors evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. Results: Through 4D-DIA proteomic analysis, the authors identified seven potential EVs surface proteins showing significantly differential expression in CRC patients compared to healthy controls. Utilizing our developed high-throughput CRC-EVArray microarray, we further confirmed the differential expression of three EVs surface proteins, FIBG, PDGF-β and TGF-β, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an area under the curve (AUC) of 0.882 in the train set and 0.937 in the test set. Additionally, we predicted the functions and potential origins of these EVs-derived proteins through a series of multi-omics approaches. Conclusions: Our systematic exploration of surface protein expression profiles on serum-derived EVs has identified FIBG, PDGF-β, and TGF-β as novel diagnostic biomarkers for CRC. The development of CRC-EVArray diagnostic model based on these findings provided an effective tool for the large-scale CRC screening, thus facilitating its translation into clinical practice.

Background: Non-small cell lung cancer (NSCLC) was a disease with poor outcomes, partly because there were no high-efficiency non-invasive diagnostic biomarkers. The RNA modification status of 5-Methylcytosine (m⁵C) has been shown to be a biomarker for various diseases, but its potentiality to be a diagnostic biomarker for NSCLC remained inconclusive.