Abstract
Colon cancer is one of the major causes of cancer death worldwide. The five-year survival rate for the early-stage patients is more than 90%, and only around 10% for the later stages. Moreover, half of the colon cancer patients have been clinically diagnosed at the later stages. It is; therefore, of importance to enhance the ability for the early diagnosis of colon cancer. Taking advantages from our previous studies, there are several potential biomarkers which have been associated with the early diagnosis of the colon cancer. In order to investigate these early diagnostic biomarkers for colon cancer, human chromogranin-A (CHGA) was further analyzed among the most powerful diagnostic biomarkers. In this study, we used a logistic regression-based meta-analysis to clarify associations of CHGA expression with colon cancer diagnosis. Both healthy populations and the normal mucosa from the colon cancer patients were selected as the double normal controls. The results showed decreased expression of CHGA in the early stages of colon cancer as compared to the normal controls. The decline of CHGA expression in the early stages of colon cancer is probably a new diagnostic biomarker for colon cancer diagnosis with high predicting possibility and verification performance. We have also compared the diagnostic powers of CHGA expression with the typical oncogene KRAS, classic tumor suppressor TP53, and well-known cellular proliferation index MKI67, and the CHGA showed stronger ability to predict early diagnosis for colon cancer than these other cancer biomarkers. In the protein–protein interaction (PPI) network, CHGA was revealed to share some common pathways with KRAS and TP53. CHGA might be considered as a novel, promising, and powerful biomarker for early diagnosis of colon cancer.
Highlights
Colon cancer is one of the leading causes of cancer death worldwide [1]
We have used logistic regression-based meta-analysis, a quantitative review method to detect the diagnostic value of different biomarkers in medical researches [29], and a huge number of gene expression (GE) data for different populations from the Gene Expression Omnibus (GEO) database, as a well-known biomedicine database, to investigate the diagnostic value of CHGA expression as a biomarker, compared to the healthy populations and the normal mucosa from the colon cancer patients
We showed that CHGA expression might be considered as a novel biomarker for early diagnosis of colon cancer, as compared to most well-studied expressions of KRAS, TP53, and MKI67
Summary
Colon cancer is one of the leading causes of cancer death worldwide [1]. In 2018, there were more than 1,096,601 new diagnosed colon cancer cases, and around 551,269 patients were dead from the colon cancer worldwide [2]. In the CBD, we recorded 62 biomarkers concerning the diagnosis for early-stage colon cancer. We utilized the support vector machine (SVM) and regression tree to predict new potential colon cancer biomarker based on the PPI network, with high indication that CHGA expression, among several others, could be a promising significant biomarker for early diagnosis of colon cancer [28]. We have used logistic regression-based meta-analysis, a quantitative review method to detect the diagnostic value of different biomarkers in medical researches [29], and a huge number of gene expression (GE) data for different populations from the Gene Expression Omnibus (GEO) database, as a well-known biomedicine database, to investigate the diagnostic value of CHGA expression as a biomarker, compared to the healthy populations and the normal mucosa from the colon cancer patients. We showed that CHGA expression might be considered as a novel biomarker for early diagnosis of colon cancer, as compared to most well-studied expressions of KRAS, TP53, and MKI67.
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