Candidate genes involved in metastasis of colon cancer identified by integrated analysis

Zhou, Yiming; Zang, Yiwen; Yang, Yi; Xiang, Jianbin; Chen, Zongyou

doi:10.1002/cam4.2071

Cited by 30 publications

(27 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast, there are some differences in our research results, which are mainly due to the design of the scheme. We also have some similar results, which prove the feasibility of our scheme 22 . In addition, gene expression-based subtyping is widely accepted as a relevant source of cancer stratification.…”

Section: Discussionsupporting

confidence: 73%

<p>Analysis of risk factors for colon cancer progression</p>

Zhou

Chen

et al. 2019

OTT

View full text Add to dashboard Cite

Purpose: This study aimed to find risk factors for colon cancer progression with bioinformatics methods, and validated by clinical patients. Methods: Differentially expressed genes (DEGs) between colon cancer tissues and normal colon tissues were extracted from The Cancer Genome Atlas (TCGA) database using R software, amounted to 8,051. DEGs between pathologic stage I+II and stage III+IV amounted to 373, and were compared with DEGs of cancer/normal analyzed above to get the intersection of both. Ninety-six intersected DEGs were identified and defined as progressive DEGs of colon cancer. Then these 96 progressive DEGs were studied by Gene ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis using the DAVID database and visualizing by R software. A protein–protein interaction (PPI) network and functional modules were established using the STRING database. Further, an overall survival (OS) curve was drawn via the GEPIA website based on the CGA database and six progressive DEGs were found to be involved with OS of colon cancer patients. The Linkedomics website was used for detailed analysis of specific subsets of TNM. Results: Pregnancy specific glycoprotein (PSG), vitamin digestion, and absorption were confirmed to promote the progression of colon cancer. Furthermore, NTF4 was found to be associated with both OS and each subset of TNM; therefore, defined as a key risk factor for colon cancer progression. Further analysis of NTF4 expression using clinical data showed it acted as a key risk factor and diagnosis marker for colon cancer progression. Conclusion: NTF4 is a risk factor contributing to colon cancer progression and associated with overall survival.

show abstract

Section: Discussionsupporting

confidence: 73%

<p>Analysis of risk factors for colon cancer progression</p>

Zhou

Chen

et al. 2019

OTT

View full text Add to dashboard Cite

show abstract

“…However, no consensus was reached regarding the surveillance protocols of RCC, and no available tumor-associated biomarkers can predict recurrence in patients who may have benefited from earlier therapy [8]. Previous studies in colorectal cancer proposed several gene signatures and proved to be useful in predicting prognosis [9–11]. In this study, we divided patients from the Cancer Genome Atlas database into a non-metastasis group and a metastasis group in order to screen the differently expressed genes.…”

Section: Introductionmentioning

confidence: 99%

Identification of a 5-Gene Signature Predicting Progression and Prognosis of Clear Cell Renal Cell Carcinoma

et al. 2019

View full text Add to dashboard Cite

Background Although the mortality rates of clear cell renal cell carcinoma (ccRCC) have decreased in recent years, the clinical outcome remains highly dependent on the individual patient. Therefore, identifying novel biomarkers for ccRCC patients is crucial. Material/Methods In this study, we obtained RNA sequencing data and clinical information from the TCGA database. Subsequently, we performed integrated bioinformatic analysis that includes differently expressed genes analysis, gene ontology and KEGG pathway analysis, protein-protein interaction analysis, and survival analysis. Moreover, univariate and multivariate Cox proportional hazards regression models were constructed. Results As a result, we identified a total of 263 dysregulated genes that may participate in the metastasis of ccRCC, and established a predictive signature relying on the expression of OTX1, MATN4, PI3, ERVV-2, and NFE4, which could serve as significant progressive and prognostic biomarkers for ccRCC. Conclusions We identified differentially expressed genes that may be involved in the metastasis of ccRCC. Moreover, a predictive signature based on the expression of OTX1, MATN4, PI3, ERVV-2, and NFE4 could be an independent prognostic factor for ccRCC.

show abstract

“…Expression of SLC22A8 was considered as a valuable biomarker for the lung cancer treatment [42]. The NEUROD2 gene was related to the metastasis and the survival for colon cancer [43]. The SLC2A1 gene was related to the metabolic shift of colon cancer [44], and the HCN4 gene was correlated with low survival rate of multiple cancers [45].…”

Section: Discussionmentioning

confidence: 99%

Chromogranin-A Expression as a Novel Biomarker for Early Diagnosis of Colon Cancer Patients

Zhang

Shen

Sun

2019

IJMS

View full text Add to dashboard Cite

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.

show abstract

Candidate genes involved in metastasis of colon cancer identified by integrated analysis

Cited by 30 publications

References 34 publications

<p>Analysis of risk factors for colon cancer progression</p>

<p>Analysis of risk factors for colon cancer progression</p>

Identification of a 5-Gene Signature Predicting Progression and Prognosis of Clear Cell Renal Cell Carcinoma

Chromogranin-A Expression as a Novel Biomarker for Early Diagnosis of Colon Cancer Patients

Contact Info

Product

Resources

About