RESUMO
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 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 multicenter study comprising 404 individuals. In the application phase, we evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. RESULTS: Through 4D-DIA proteomic analysis, we identified 7 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 3 EVs surface proteins, FIBG, PDGF-ß and TGF-ß, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an 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-ß, and TGF-ß as novel diagnostic biomarkers for CRC. And 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.
RESUMO
Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Complementarity-determining region 3 (CDR3) of B-cell receptors (BCRs) and T-cell receptors are the major site of antigen recognition, which determines a unique clone type, and are considered to be the representative of the disease. In the present study, high-throughput sequencing was used to analyze the association of characteristics of the BCR immunoglobulin heavy chain (IGH) and the T-cell receptor ß chain (TRB) CDR3 genes in PTC and corresponding pericarcinous tissues from patients. A difference of CDR3 length distributions of total IGH CDR3 sequences between the two groups was revealed. IGHV3-11/IGHJ6, TRBV2/TRBJ1-2 and TRBV2/TRBJ1-1 may be biomarkers for the development of PTC. Furthermore, it was revealed that the extent of the common clonotype expressions at the amino acid level was slightly higher compared with the nucleotide level. The Shannon entropy demonstrated a diversity reduction in PTC compared with the pericarcinous group, and the highly expended clone (HEC) expression of PTC was higher compared with that of the corresponding pericarcinous group. Additionally, the highest clone frequency percentage of IGH and TRB was at 0.1-1.0% degree of expansion, as HEC expression was higher in PTC compared with the matched group. There was no shared clone of HECs in the two groups either at the amino acid level or at the nucleotide expression level. The differential expression of CDR3 sequences of PTC have been identified in the present study. Further research is required for assessing the immune repertoire size, diversity, cloning tracking and finding public clones of T-cell and B-cell populations in the development of PTC.