4.7 Article

The expression changes of transcription factors including ANKZF1, LEF1, CASZ1, and ATOH1 as a predictor of survival rate in colorectal cancer: a large-scale analysis

Journal

CANCER CELL INTERNATIONAL
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12935-022-02751-3

Keywords

Gene expression; Survival rate; Biomarkers; Master genes

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This study analyzed the abnormal expression of transcription factors in colorectal cancer (CRC) and their impact on patient prognosis and related pathways. The findings showed that certain transcription factors were associated with poor prognosis, while others were associated with good prognosis. A predictive model based on the expression of these transcription factors accurately predicted patient survival rates. Additionally, co-expression network analysis revealed the involvement of these transcription factors in metastatic pathways and apoptotic pathways.
Introduction Transcription factors (TFs) are essential for many biological processes and regulate the expression of several genes. This study's objective was to analyze the abnormalities in TF expression, their impact on patient prognosis, and related pathways in colorectal cancer (CRC). Method The expression alterations of all TFs were investigated using the cancer genome atlas and GSE39582 data. Clinical data were also used to study the association between TFs expression and patient prognosis through the Cox regression test, and a predictive model of CRC patient survival was constructed based on TFs expression. Co-expression network was used to discover TF-related pathways. To validate the findings, the RT-qPCR method was applied to CRC samples and adjacent normal tissue. Results The findings revealed that ANKZF1, SALL4, SNAI1, TIGD1, LEF1, FOXS1, SIX4, and ETV5 expression levels increased in both cohorts and were linked to the poor prognosis. NR3C2, KLF4, CASZ1, FOXD2, ATOH1, SALL1, and RORC expression, on the other hand, exhibited a significant decrease, and their increase was related to the good prognosis of patients. The patient mortality risk model based on expression of mentioned TFs revealed that, independent of clinical characteristics, the expression of ANKZF1, LEF1, CASZ1, and ATOH1 could accurately predict patient survival rates. According to the co-expression network, increased transcription factors were linked to metastatic pathways, while decreasing TFs were involved to apoptotic pathways. RT-qPCR findings showed that FOXS1 expression was markedly overexpressed in CRC samples. However, in CRC samples, the expression of CASZ1 decreased. Conclusion In CRC, TFs expression of ANKZF1, LEF1, CASZ1 and ATOH1 are deregulated, which are associated with prognosis in patients. According to our findings, changes in the expression of the mentioned TFs have the potential to be considered diagnostic and prognostic biomarkers for CRC patients.

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