A proteomic classifier panel for early screening of colorectal cancer: a case control study.

BACKGROUND: Diagnosis of colorectal cancer (CRC) during early stages can greatly improve patient outcome. Although technical advances in the field of genomics and proteomics have identified a number of candidate biomarkers for non-invasive screening and diagnosis, developing more sensitive and specific methods with improved cost-effectiveness and patient compliance has tremendous potential to help combat the disease. METHODS: We enrolled three cohorts of 479 subjects, including 226 CRC cases, 197 healthy controls, and 56 advanced precancerous lesions (APC). In the discovery cohort, we used quantitative mass spectrometry to measure the expression profile of plasma proteins and applied machine-learning to select candidate proteins. We then developed a targeted mass spectrometry assay to measure plasma concentrations of seven proteins and a logistic regression classifier to distinguish CRC from healthy subjects. The classifier was further validated using two independent cohorts. RESULTS: The seven-protein panel consisted of leucine rich alpha-2-glycoprotein 1 (LRG1), complement C9 (C9), insulin-like growth factor binding protein 2 (IGFBP2), carnosine dipeptidase 1 (CNDP1), inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3), serpin family A member 1 (SERPINA1), and alpha-1-acid glycoprotein 1 (ORM1). The panel classified CRC and healthy subjects with high accuracy, since the area under curve (AUC) of the training and testing cohort reached 0.954 and 0.958. The AUC of the two independent validation cohorts was 0.905 and 0.909. In one validation cohort, the panel had an overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 89.9%, 81.8%, 89.2%, and 82.9%, respectively. In another blinded validation cohort, the panel classified CRC from healthy subjects with a sensitivity of 81.5%, specificity of 97.9%, and overall accuracy of 92.0%. Finally, the panel was able to detect APC with a sensitivity of 49%. CONCLUSIONS: This seven-protein classifier is a clear improvement compared to previously published blood-based protein biomarkers for detecting early-stage CRC, and is of translational potential to develop into a clinically useful assay.

ETV1 Positively Correlated With Immune Infiltration and Poor Clinical Prognosis in Colorectal Cancer.

Objective: Numerous studies recently suggested that the immune microenvironment could influence the development of colorectal cancer (CRC). These findings implied that the infiltration of immune cells could be a promising prognostic biomarker for CRC. Methods: Furthermore, the Oncomine database and R2 platform analysis were applied in our research to validate CRC clinical prognosis via expression levels of polyoma enhancer activator 3 (PEA3) members. We explored the correlation of ETV1, ETV4, and ETV5 with tumor-infiltrating immune cells (TIICs) in CRC tumor microenvironments via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). Immunohistochemistry (IHC) was used to validate our CRC clinical data. Results: Our findings indicated that the upregulation of PEA3 members including ETV1 and ETV5 was positively associated with poor prognosis in CRC patients. Meanwhile, ETV1 and ETV5 may play significant roles in the development progress of CRC. Furthermore, ETV1 tends to be associated with immune infiltration of CRC, especially with cancer-associated fibroblasts and M2 macrophages. Conclusion: These findings revealed that ETV1 and ETV5 played significant roles in the development of CRC. Moreover, ETV1 was significantly associated with the infiltration of cancer-associated fibroblasts and M2 macrophages in CRC. Targeting ETV1 can be a potential auspicious approach for CRC treatment.

Fecal Fusobacterium nucleatum as a predictor for metachronous colorectal adenoma after endoscopic polypectomy.

BACKGROUND AND AIM: Fusobacterium nucleatum is increasingly being recognized as an important risk factor in colorectal cancer and colorectal adenoma. Endoscopic polypectomy is associated with a decreased incidence of colorectal cancer; however, patients still suffer from a risk of metachronous adenoma. Currently, there are few effective non-invasive factors that may predict metachronous colorectal adenoma. Here, we evaluated the performance of F. nucleatum in predicting metachronous adenoma. METHODS: Fecal samples and clinical information of patients before endoscopic polypectomy were collected from 367 patients in a retrospective cohort, and 238 patients in a prospective cohort. The abundance of fecal F. nucleatum was measured via quantitative polymerase chain reaction. Surveillance colonoscopies were conducted between 1 and 3 years after polypectomy (average follow-up 27.07 months for the retrospective cohort & 22.57 months for the prospective cohort) to identify metachronous adenoma. Candidate predictive factors and cut-off value of F. nucleatum abundance were identified from the retrospective cohort and then validated in the prospective cohort. RESULTS: A high abundance of fecal F. nucleatum was found to be an independent risk factor for metachronous adenomas (odds ratio, 6.38; P < 0.001) in the retrospective cohort and was validated in the prospective cohort with a specificity of 65.00%, and a sensitivity of 73.04%, and an overall performance with the area under the curve of 0.73. CONCLUSION: Fecal abundance of F. nucleatum may be a reliable predictor for metachronous adenoma after endoscopic polypectomy.