PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer
IntroductionEndeavors in the molecular characterization of breast cancer opened the doors to endocrine therapies in ER+/HER2- breast cancer, increasing response rates substantially. Despite that, taxane-based neoadjuvant chemotherapy is still a cornerstone for achieving breast-conserving surgery and...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1216438/full |
| _version_ | 1797735991669161984 |
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| author | Gulnihal Ozcan Gulnihal Ozcan |
| author_facet | Gulnihal Ozcan Gulnihal Ozcan |
| author_sort | Gulnihal Ozcan |
| collection | DOAJ |
| description | IntroductionEndeavors in the molecular characterization of breast cancer opened the doors to endocrine therapies in ER+/HER2- breast cancer, increasing response rates substantially. Despite that, taxane-based neoadjuvant chemotherapy is still a cornerstone for achieving breast-conserving surgery and complete tumor resection in locally advanced cancers with high recurrence risk. Nonetheless, the rate of chemoresistance is high, and deselecting patients who will not benefit from chemotherapy is a significant task to prevent futile toxicities. Several multigene assays are being used to guide decisions on chemotherapy. However, their development as prognostic assays but not predictive assays limits predictive strength, leading to discordant results. Moreover, high costs impediment their use in developing countries. For global health equity, robust predictors that can be cost-effectively incorporated into routine clinical management are essential.MethodsIn this study, we comprehensively analyzed 5 GEO datasets, 2 validation sets, and The Cancer Genome Atlas breast cancer data to identify predictors of resistance to taxane-based neoadjuvant therapy in ER+/HER2- breast cancer using efficient bioinformatics algorithms.ResultsGene expression and gene set enrichment analysis of 5 GEO datasets revealed the upregulation of 63 genes and the enrichment of CTNNB1-related oncogenic signatures in non-responsive patients. We validated the upregulation and predictive strength of 18 genes associated with resistance in the validation cohort, all exhibiting higher predictive powers for residual disease and higher specificities for ER+/HER2- breast cancers compared to one of the benchmark multi-gene assays. Cox Proportional Hazards Regression in three different treatment arms (neoadjuvant chemotherapy, endocrine therapy, and no systemic treatment) in a second comprehensive validation cohort strengthened the significance of PTCH1 and CTNNB1 as key predictors, with hazard ratios over 1.5, and 1.6 respectively in the univariate and multivariate models.DiscussionOur results strongly suggest that PTCH1 and CTNNB1 can be used as robust and cost-effective predictors in developing countries to guide decisions on chemotherapy in ER +/HER2- breast cancer patients with a high risk of recurrence. The dual function of PTCH1 as a multidrug efflux pump and a hedgehog receptor, and the active involvement of CTNNB1 in breast cancer strongly indicate that PTCH1 and CTNNB1 can be potential drug targets to overcome chemoresistance in ER +/HER2- breast cancer patients. |
| first_indexed | 2024-03-12T13:07:06Z |
| format | Article |
| id | doaj.art-29b889532bbd430eaabea7994464616f |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-12T13:07:06Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-29b889532bbd430eaabea7994464616f2023-08-28T14:00:35ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-08-011310.3389/fonc.2023.12164381216438PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancerGulnihal Ozcan0Gulnihal Ozcan1Department of Medical Pharmacology, Koç University School of Medicine, Istanbul, TürkiyeKoç University Research Center for Translational Medicine (KUTTAM), Istanbul, TürkiyeIntroductionEndeavors in the molecular characterization of breast cancer opened the doors to endocrine therapies in ER+/HER2- breast cancer, increasing response rates substantially. Despite that, taxane-based neoadjuvant chemotherapy is still a cornerstone for achieving breast-conserving surgery and complete tumor resection in locally advanced cancers with high recurrence risk. Nonetheless, the rate of chemoresistance is high, and deselecting patients who will not benefit from chemotherapy is a significant task to prevent futile toxicities. Several multigene assays are being used to guide decisions on chemotherapy. However, their development as prognostic assays but not predictive assays limits predictive strength, leading to discordant results. Moreover, high costs impediment their use in developing countries. For global health equity, robust predictors that can be cost-effectively incorporated into routine clinical management are essential.MethodsIn this study, we comprehensively analyzed 5 GEO datasets, 2 validation sets, and The Cancer Genome Atlas breast cancer data to identify predictors of resistance to taxane-based neoadjuvant therapy in ER+/HER2- breast cancer using efficient bioinformatics algorithms.ResultsGene expression and gene set enrichment analysis of 5 GEO datasets revealed the upregulation of 63 genes and the enrichment of CTNNB1-related oncogenic signatures in non-responsive patients. We validated the upregulation and predictive strength of 18 genes associated with resistance in the validation cohort, all exhibiting higher predictive powers for residual disease and higher specificities for ER+/HER2- breast cancers compared to one of the benchmark multi-gene assays. Cox Proportional Hazards Regression in three different treatment arms (neoadjuvant chemotherapy, endocrine therapy, and no systemic treatment) in a second comprehensive validation cohort strengthened the significance of PTCH1 and CTNNB1 as key predictors, with hazard ratios over 1.5, and 1.6 respectively in the univariate and multivariate models.DiscussionOur results strongly suggest that PTCH1 and CTNNB1 can be used as robust and cost-effective predictors in developing countries to guide decisions on chemotherapy in ER +/HER2- breast cancer patients with a high risk of recurrence. The dual function of PTCH1 as a multidrug efflux pump and a hedgehog receptor, and the active involvement of CTNNB1 in breast cancer strongly indicate that PTCH1 and CTNNB1 can be potential drug targets to overcome chemoresistance in ER +/HER2- breast cancer patients.https://www.frontiersin.org/articles/10.3389/fonc.2023.1216438/fullbreast cancerchemoresistancetaxane-based neoadjuvant chemotherapypredictive markersprecision medicinebioinformatics |
| spellingShingle | Gulnihal Ozcan Gulnihal Ozcan PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer Frontiers in Oncology breast cancer chemoresistance taxane-based neoadjuvant chemotherapy predictive markers precision medicine bioinformatics |
| title | PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer |
| title_full | PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer |
| title_fullStr | PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer |
| title_full_unstemmed | PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer |
| title_short | PTCH1 and CTNNB1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in ER+/HER2- breast cancer |
| title_sort | ptch1 and ctnnb1 emerge as pivotal predictors of resistance to neoadjuvant chemotherapy in er her2 breast cancer |
| topic | breast cancer chemoresistance taxane-based neoadjuvant chemotherapy predictive markers precision medicine bioinformatics |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1216438/full |
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