Colorectal Cancer Biomarkers
A colorectal cancer and marker technology, applied in the field of risk biomarkers, can solve problems such as feeling uncomfortable or even aversion, and achieve the effect of convenient transportation and accurate results
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Embodiment 1
[0092] Example 1: 31 biomarkers were identified from 128 Chinese individuals and evaluated by intestinal health index their risk of colorectal cancer
[0093] 1.1 Sample collection and DNA extraction
[0094] Fecal samples from 128 subjects (the first group) including 74 colorectal patients and 54 healthy control subjects (Table 2) were collected from the Prince of Wales Hospital in Hong Kong, and informed consent was obtained from all of them. In order to meet the requirements of this study, the participating individuals need to meet the following conditions before collecting stool samples: 1) have not taken antibiotics or other drugs for at least three months, have no special diet (such as special meals for diabetics, vegetarian, etc.), and have normal life and rest (no 2) No medical intervention for at least three months; 3) No history of colorectal surgery, no cancer, no intestinal inflammation or infectious disease. Subjects collected fecal samples at home in stand...
Embodiment 2
[0122] Example 2: Validation of 31 biomarkers
[0123] The inventors verified the discriminative ability of the CRC classifier using another new independent research group, which included 19 CRC patients and 16 non-CRC controls, also from the Prince of Wales Hospital in Hong Kong.
[0124] For each sample, the methods described in Example 1 were used for DNA extraction, DNA library construction, and high-throughput sequencing. The inventors calculated the gene abundance profiles of these samples using the method described by Qin et al. (2012, supra). Thus, the relative gene abundance of each marker shown in SEQ ID NOs: 1-31 can be obtained. The index for each sample was then calculated using the following formula:
[0125]
[0126] A ij is the relative abundance of marker i in sample j, where i represents each gene marker shown in SEQ ID NOs: 1-31;
[0127] N is a subset of all markers enriched in patients and M is a subset of all markers enriched in controls;
[012...
Embodiment 3
[0138] Example 3: Identification of species markers from 128 Chinese individuals
[0139] Based on the sequenced sequences of the first population of 128 microbiota described in Example 1, the inventors examined taxonomic differences between control and CRC-associated microbiota to identify microbial taxa contributing to dysbiosis. For this, since the supporting evidence obtained by different methods will strengthen the correlation, the inventors used three different methods to analyze the obtained taxonomic profiles. First, the inventors mapped metagenomic sequencing sequences to the 4650 microbial genomes of the IMG database (version 400) and assessed the abundance of microbial species (named IMG species) contained in this database. Second, the inventors assessed the abundance of species-level molecular operational taxonomic units (mOTUs) using universal phylogenetic marker genes. Third, the inventor organized the 140,455 genes identified by MGWAS into a metagenomic linka...
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