TY - JOUR
T1 - The Prognostic Value of ASPHD1 and ZBTB12 in Colorectal Cancer
T2 - A Machine Learning-Based Integrated Bioinformatics Approach
AU - Asadnia, Alireza
AU - Nazari, Elham
AU - Goshayeshi, Ladan
AU - Zafari, Nima
AU - Moetamani-Ahmadi, Mehrdad
AU - Goshayeshi, Lena
AU - Azari, Haneih
AU - Pourali, Ghazaleh
AU - Khalili-Tanha, Ghazaleh
AU - Abbaszadegan, Mohammad Reza
AU - Khojasteh-Leylakoohi, Fatemeh
AU - Bazyari, MohammadJavad
AU - Kahaei, Mir Salar
AU - Ghorbani, Elnaz
AU - Khazaei, Majid
AU - Hassanian, Seyed Mahdi
AU - Gataa, Ibrahim Saeed
AU - Kiani, Mohammad Ali
AU - Peters, Godefridus J.
AU - Ferns, Gordon A.
AU - Batra, Jyotsna
AU - Lam, Alfred King-yin
AU - Giovannetti, Elisa
AU - Avan, Amir
N1 - Funding Information: This research was funded by National Institute for Medical Research and Development (NIMAD 962782AA); NHMRC—National Health and Medical Research Council (2029788AA), Tour the Cure (AA-RSP-163-2024); AIRC (associazione Italian per la ricerca sul Cancro)—IG-grant 24444; CCA (Cancer Center Amsterdam) Foundation (Elisa Giovannetti); Advance Queensland Industry Research Fellowship (JB). Funding Information: The work was supported by Mashhad University of Medical Sciences (Amir Avan) and the National Institute for Medical Research and Development (NIMAD 962782, AA); AIRC (associazione Italian per la ricerca sul Cancro)—IG-grant 24444; CCA (Cancer Center Amsterdam) Foundation (EG); Advance Queensland Industry Research Fellowship (JB). Publisher Copyright: © 2023 by the authors.
PY - 2023/9/1
Y1 - 2023/9/1
N2 - Introduction: Colorectal cancer (CRC) is a common cancer associated with poor outcomes, underscoring a need for the identification of novel prognostic and therapeutic targets to improve outcomes. This study aimed to identify genetic variants and differentially expressed genes (DEGs) using genome-wide DNA and RNA sequencing followed by validation in a large cohort of patients with CRC. Methods: Whole genome and gene expression profiling were used to identify DEGs and genetic alterations in 146 patients with CRC. Gene Ontology, Reactom, GSEA, and Human Disease Ontology were employed to study the biological process and pathways involved in CRC. Survival analysis on dysregulated genes in patients with CRC was conducted using Cox regression and Kaplan–Meier analysis. The STRING database was used to construct a protein–protein interaction (PPI) network. Moreover, candidate genes were subjected to ML-based analysis and the Receiver operating characteristic (ROC) curve. Subsequently, the expression of the identified genes was evaluated by Real-time PCR (RT-PCR) in another cohort of 64 patients with CRC. Gene variants affecting the regulation of candidate gene expressions were further validated followed by Whole Exome Sequencing (WES) in 15 patients with CRC. Results: A total of 3576 DEGs in the early stages of CRC and 2985 DEGs in the advanced stages of CRC were identified. ASPHD1 and ZBTB12 genes were identified as potential prognostic markers. Moreover, the combination of ASPHD and ZBTB12 genes was sensitive, and the two were considered specific markers, with an area under the curve (AUC) of 0.934, 1.00, and 0.986, respectively. The expression levels of these two genes were higher in patients with CRC. Moreover, our data identified two novel genetic variants—the rs925939730 variant in ASPHD1 and the rs1428982750 variant in ZBTB1—as being potentially involved in the regulation of gene expression. Conclusions: Our findings provide a proof of concept for the prognostic values of two novel genes—ASPHD1 and ZBTB12—and their associated variants (rs925939730 and rs1428982750) in CRC, supporting further functional analyses to evaluate the value of emerging biomarkers in colorectal cancer.
AB - Introduction: Colorectal cancer (CRC) is a common cancer associated with poor outcomes, underscoring a need for the identification of novel prognostic and therapeutic targets to improve outcomes. This study aimed to identify genetic variants and differentially expressed genes (DEGs) using genome-wide DNA and RNA sequencing followed by validation in a large cohort of patients with CRC. Methods: Whole genome and gene expression profiling were used to identify DEGs and genetic alterations in 146 patients with CRC. Gene Ontology, Reactom, GSEA, and Human Disease Ontology were employed to study the biological process and pathways involved in CRC. Survival analysis on dysregulated genes in patients with CRC was conducted using Cox regression and Kaplan–Meier analysis. The STRING database was used to construct a protein–protein interaction (PPI) network. Moreover, candidate genes were subjected to ML-based analysis and the Receiver operating characteristic (ROC) curve. Subsequently, the expression of the identified genes was evaluated by Real-time PCR (RT-PCR) in another cohort of 64 patients with CRC. Gene variants affecting the regulation of candidate gene expressions were further validated followed by Whole Exome Sequencing (WES) in 15 patients with CRC. Results: A total of 3576 DEGs in the early stages of CRC and 2985 DEGs in the advanced stages of CRC were identified. ASPHD1 and ZBTB12 genes were identified as potential prognostic markers. Moreover, the combination of ASPHD and ZBTB12 genes was sensitive, and the two were considered specific markers, with an area under the curve (AUC) of 0.934, 1.00, and 0.986, respectively. The expression levels of these two genes were higher in patients with CRC. Moreover, our data identified two novel genetic variants—the rs925939730 variant in ASPHD1 and the rs1428982750 variant in ZBTB1—as being potentially involved in the regulation of gene expression. Conclusions: Our findings provide a proof of concept for the prognostic values of two novel genes—ASPHD1 and ZBTB12—and their associated variants (rs925939730 and rs1428982750) in CRC, supporting further functional analyses to evaluate the value of emerging biomarkers in colorectal cancer.
KW - bioinformatics
KW - biomarker
KW - colorectal cancer
KW - machine learning
KW - prognosis
UR - http://www.scopus.com/inward/record.url?scp=85170257330&partnerID=8YFLogxK
U2 - https://doi.org/10.3390/cancers15174300
DO - https://doi.org/10.3390/cancers15174300
M3 - Article
C2 - 37686578
SN - 2072-6694
VL - 15
JO - Cancers
JF - Cancers
IS - 17
M1 - 4300
ER -