A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer
Abstract The proliferation-specific oncogenic transcription factor, FOXM1 is overexpressed in primary and recurrent breast tumors across all breast cancer (BC) subtypes. Intriguingly, FOXM1 overexpression was found to be highest in Triple-negative breast cancer (TNBC), the most aggressive BC with th...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-85100-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841544632580702208 |
|---|---|
| author | Prarthana Chatterjee Satarupa Banerjee |
| author_facet | Prarthana Chatterjee Satarupa Banerjee |
| author_sort | Prarthana Chatterjee |
| collection | DOAJ |
| description | Abstract The proliferation-specific oncogenic transcription factor, FOXM1 is overexpressed in primary and recurrent breast tumors across all breast cancer (BC) subtypes. Intriguingly, FOXM1 overexpression was found to be highest in Triple-negative breast cancer (TNBC), the most aggressive BC with the worst prognosis. However, FOXM1-mediated TNBC pathogenesis is not completely elucidated. Single nucleotide polymorphisms (SNPs) are the most common genetic variations causing functional and structural aberrations in proteins enhancing cancer susceptibility. This computational investigation attempted to identify the malignant FOXM1 non-synonymous SNPs (nsSNPs) and evaluate their role in affecting the conformational and functional stability, evolutionary conservation, post-translational modifications, and malignant susceptibility of the protein. Out of a huge data pool of 8826 FOXM1 SNPs using several in-silico sequence-based tools and structural approaches, four SNPs viz. E235Q, R256C, G429E and S756P were identified as pathogenic nsSNPs and among the shortlisted variants molecular dynamics simulations identified E235Q as the most damaging malignant SNP, followed by S756P. Additionally, the defective drug and DNA binding motif of E235Q and S756P were also determined in our study. Thus, although further in-vitro validations are awaited the findings of this in-silico work can be used as a blueprint for malignant nsSNP identification of FOXM1 aiding in clinical TNBC therapeutics. |
| format | Article |
| id | doaj-art-f3141c00c0534d5bbeb0132238a7f20b |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-f3141c00c0534d5bbeb0132238a7f20b2025-01-12T12:23:54ZengNature PortfolioScientific Reports2045-23222025-01-0115111610.1038/s41598-024-85100-wA computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancerPrarthana Chatterjee0Satarupa Banerjee1School of BioSciences and Technology, Vellore Institute of TechnologySchool of BioSciences and Technology, Vellore Institute of TechnologyAbstract The proliferation-specific oncogenic transcription factor, FOXM1 is overexpressed in primary and recurrent breast tumors across all breast cancer (BC) subtypes. Intriguingly, FOXM1 overexpression was found to be highest in Triple-negative breast cancer (TNBC), the most aggressive BC with the worst prognosis. However, FOXM1-mediated TNBC pathogenesis is not completely elucidated. Single nucleotide polymorphisms (SNPs) are the most common genetic variations causing functional and structural aberrations in proteins enhancing cancer susceptibility. This computational investigation attempted to identify the malignant FOXM1 non-synonymous SNPs (nsSNPs) and evaluate their role in affecting the conformational and functional stability, evolutionary conservation, post-translational modifications, and malignant susceptibility of the protein. Out of a huge data pool of 8826 FOXM1 SNPs using several in-silico sequence-based tools and structural approaches, four SNPs viz. E235Q, R256C, G429E and S756P were identified as pathogenic nsSNPs and among the shortlisted variants molecular dynamics simulations identified E235Q as the most damaging malignant SNP, followed by S756P. Additionally, the defective drug and DNA binding motif of E235Q and S756P were also determined in our study. Thus, although further in-vitro validations are awaited the findings of this in-silico work can be used as a blueprint for malignant nsSNP identification of FOXM1 aiding in clinical TNBC therapeutics.https://doi.org/10.1038/s41598-024-85100-wTriple-negative breast cancerFOXM1Single nucleotide polymorphismsMolecular dynamic simulations |
| spellingShingle | Prarthana Chatterjee Satarupa Banerjee A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer Scientific Reports Triple-negative breast cancer FOXM1 Single nucleotide polymorphisms Molecular dynamic simulations |
| title | A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer |
| title_full | A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer |
| title_fullStr | A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer |
| title_full_unstemmed | A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer |
| title_short | A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer |
| title_sort | computational and structural approach to identify malignant non synonymous foxm1 single nucleotide polymorphisms in triple negative breast cancer |
| topic | Triple-negative breast cancer FOXM1 Single nucleotide polymorphisms Molecular dynamic simulations |
| url | https://doi.org/10.1038/s41598-024-85100-w |
| work_keys_str_mv | AT prarthanachatterjee acomputationalandstructuralapproachtoidentifymalignantnonsynonymousfoxm1singlenucleotidepolymorphismsintriplenegativebreastcancer AT satarupabanerjee acomputationalandstructuralapproachtoidentifymalignantnonsynonymousfoxm1singlenucleotidepolymorphismsintriplenegativebreastcancer AT prarthanachatterjee computationalandstructuralapproachtoidentifymalignantnonsynonymousfoxm1singlenucleotidepolymorphismsintriplenegativebreastcancer AT satarupabanerjee computationalandstructuralapproachtoidentifymalignantnonsynonymousfoxm1singlenucleotidepolymorphismsintriplenegativebreastcancer |