A detailed understanding of the COL10A1 and SOX9 genes interaction based on potentially damaging mutations in gastric cancer using computational techniques

Abstract

Gastric cancer (GC) has limited effective treatment options and is followed up with biomarkers that have insufficient sensitivity and specificity. Recent studies on Collagen Type X Alpha 1 Chain (COL10A1) show that the COL10A1 gene may be a diagnostic and/or prognostic biomarker for different cancer types. Moreover, its relationship with the Sex determining Region Y (SRY)-related High-Mobility Group (HMG) box (SOX9) gene which is also a transcription factor, was discovered recently, and co-expression of these two genes are associated with the development of GC. However, to the best of our knowledge, there is no study in the literature on how potential damaging mutations in the SOX9 and COL10A1 genes can affect their interactions. The aim of this study is to investigate the interactions of wild-type and potentially damaging mutated structures of COL10A1 and SOX9 genes. Thus, outputs for drug development and therapeutic strategies for GC can be obtained. For this purpose, structure validation and energy minimization analyses as well as docking and binding affinity calculations were performed. As a result, it was found that all investigated mutations (P563S, I588L, T624A, H165R and N110T) increased the binding affinity between the COL10A1-SOX9 complex, especially the N110T and H165R mutants in SOX9. As a conclusion, the N110T and H165R mutants in SOX9 may contribute to tumor progression. Therefore, it is important to consider these mutations for future therapeutic strategies.

Communicated by Ramaswamy H. Sarma

Keywords:

• Gastric cancer
• molecular dynamics simulation
• COL10A1
• SOX9
• mutation

Acknowledgements

The authors thank Esin AKI-YALCIN and the research group for technical assistance. The data used in our study are obtained from the public database the TCGA Research Network: https://www.cancer.gov/tcga. We thank the TCGA and GEPIA databases for the availability of the data.

Disclosure statement

The authors declare that there is no conflict of interests.

Data availability statement

The data sets generated and analyzed during the current study are available in TGCA database (https://www.cancer.gov/tcga) and The cBio Cancer Genomics Portal (http://www.cbioportal.org/).