LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach
Abstract Background The 2020 cancer report states that breast cancer remains a significant cause of death for females, despite the use of various strategies for early detection and treatment. However, there are still gaps in the fight against this disease. Researchers are exploring the hippo pathway...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-79688-2 |
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| author | Sadaf Mubashir Zafar Sheersh Massey Abdulaziz A Aloliqi Sadaf Anwar Abrar Ali Malik Asif Hussain Tulika Bhardwaj Kapil Dev |
| author_facet | Sadaf Mubashir Zafar Sheersh Massey Abdulaziz A Aloliqi Sadaf Anwar Abrar Ali Malik Asif Hussain Tulika Bhardwaj Kapil Dev |
| author_sort | Sadaf |
| collection | DOAJ |
| description | Abstract Background The 2020 cancer report states that breast cancer remains a significant cause of death for females, despite the use of various strategies for early detection and treatment. However, there are still gaps in the fight against this disease. Researchers are exploring the hippo pathway, one of eight significant pathways involved in cancer progression, for potential biomarkers to use in personalized therapeutics. Methods The current study used bioinformatic tools such as DEGs analysis, Methsurv, Km Plotter to generate data that can predict molecular biomarkers associated with hippo pathway in breast cancer development and treatment. The protein-protein interaction pathway was generated using the STRING database to find associations of hippo pathway genes with other dysregulated genes in breast cancer datasets. A disease enrichment study was also done to explore the potential of the hippo pathway in various aspects. Results LATS2 and FAT4 genes of the hippo pathway have shown an interesting association with overall survival, hypermethylation, genetic alterations, and decreased expression levels in the breast cancer cohort. Our findings suggest that both of these genes are associated with breast cancer progression and diagnosis and can be utilized as predictive biomarkers by oncologists for personalized therapy in patients. |
| format | Article |
| id | doaj-art-cb119f6d778246d7938bdc018622da06 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-cb119f6d778246d7938bdc018622da062025-08-20T02:22:20ZengNature PortfolioScientific Reports2045-23222024-11-0114111110.1038/s41598-024-79688-2LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approachSadaf0Mubashir Zafar1Sheersh Massey2Abdulaziz A Aloliqi3Sadaf Anwar4Abrar Ali5Malik Asif Hussain6Tulika Bhardwaj7Kapil Dev8Department of Biotechnology, Jamia Millia IslamiaDepartment of Family and Community Medicine, College of Medicine, University of Ha’ilDepartment of Biosciences, Jamia Millia IslamiaDepartment of Basic health Sciences, College of Applied Medical Sciences, Qassim UniversityDepartment of Biochemistry, College of Medicine, University of Ha’ilDepartment of Ophthalmology, College of Medicine, University of Ha’ilDepartment of Pathology, College of Medicine, University of Ha’ilDepartment of Biological Sciences, University of CalgaryDepartment of Biotechnology, Jamia Millia IslamiaAbstract Background The 2020 cancer report states that breast cancer remains a significant cause of death for females, despite the use of various strategies for early detection and treatment. However, there are still gaps in the fight against this disease. Researchers are exploring the hippo pathway, one of eight significant pathways involved in cancer progression, for potential biomarkers to use in personalized therapeutics. Methods The current study used bioinformatic tools such as DEGs analysis, Methsurv, Km Plotter to generate data that can predict molecular biomarkers associated with hippo pathway in breast cancer development and treatment. The protein-protein interaction pathway was generated using the STRING database to find associations of hippo pathway genes with other dysregulated genes in breast cancer datasets. A disease enrichment study was also done to explore the potential of the hippo pathway in various aspects. Results LATS2 and FAT4 genes of the hippo pathway have shown an interesting association with overall survival, hypermethylation, genetic alterations, and decreased expression levels in the breast cancer cohort. Our findings suggest that both of these genes are associated with breast cancer progression and diagnosis and can be utilized as predictive biomarkers by oncologists for personalized therapy in patients.https://doi.org/10.1038/s41598-024-79688-2 |
| spellingShingle | Sadaf Mubashir Zafar Sheersh Massey Abdulaziz A Aloliqi Sadaf Anwar Abrar Ali Malik Asif Hussain Tulika Bhardwaj Kapil Dev LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach Scientific Reports |
| title | LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach |
| title_full | LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach |
| title_fullStr | LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach |
| title_full_unstemmed | LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach |
| title_short | LATS2 and FAT4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer: an in-silico approach |
| title_sort | lats2 and fat4 as key candidate genes of hippo pathway associated with the risk and progression of breast cancer an in silico approach |
| url | https://doi.org/10.1038/s41598-024-79688-2 |
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