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Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells
BACKGROUND: Standard Breast Cancer (BC) risk prediction models based only on epidemiologic factors generally have quite poor performance, and there have been a number of risk scores proposed to improve them, such as AI-based mammographic information, polygenic risk scores and pathogenic variants. Ev...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350237/ https://www.ncbi.nlm.nih.gov/pubmed/37461559 http://dx.doi.org/10.21203/rs.3.rs-3093360/v1 |
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author | Okunola, Hazeem L. Shuryak, Igor Repin, Mikhail Wu, Hui-Chen Santella, Regina M. Terry, Mary Beth Turner, Helen C. Brenner, David J. |
author_facet | Okunola, Hazeem L. Shuryak, Igor Repin, Mikhail Wu, Hui-Chen Santella, Regina M. Terry, Mary Beth Turner, Helen C. Brenner, David J. |
author_sort | Okunola, Hazeem L. |
collection | PubMed |
description | BACKGROUND: Standard Breast Cancer (BC) risk prediction models based only on epidemiologic factors generally have quite poor performance, and there have been a number of risk scores proposed to improve them, such as AI-based mammographic information, polygenic risk scores and pathogenic variants. Even with these additions BC risk prediction performance is still at best moderate. In that decreased DNA repair capacity (DRC) is a major risk factor for development of cancer, we investigated the potential to improve BC risk prediction models by including a measured phenotypic DRC assay: METHODS: Using blood samples from the Breast Cancer Family Registry we assessed the performance of phenotypic markers of DRC in 46 matched pairs of individuals, one from each pair with BC (with blood drawn before BC diagnosis) and the other from controls matched by age and time since blood draw. We assessed DRC in thawed cryopreserved peripheral blood mononuclear cells (PBMCs) by measuring γ-H2AX yields (a marker for DNA double-strand breaks) at multiple times from 1 to 20 hrs after a radiation challenge. The studies were performed using surface markers to discriminate between different PBMC subtypes. RESULTS: The parameter [Formula: see text] , the residual damage signal in PBMC B cells at 20 hrs post challenge, was the strongest predictor of breast cancer with an AUC (Area Under receiver-operator Curve) of 0.89 [95% Confidence Interval: 0.84–0.93] and a BC status prediction accuracy of 0.80. To illustrate the combined use of a phenotypic predictor with standard BC predictors, we combined [Formula: see text] in B cells with age at blood draw, and found that the combination resulted in significantly greater BC predictive power (AUC of 0.97 [95% CI: 0.94–0.99]), an increase of 13 percentage points over age alone. CONCLUSIONS: If replicated in larger studies, these results suggest that inclusion of a fingerstick-based phenotypic DRC blood test has the potential to markedly improve BC risk prediction. |
format | Online Article Text |
id | pubmed-10350237 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-103502372023-07-17 Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells Okunola, Hazeem L. Shuryak, Igor Repin, Mikhail Wu, Hui-Chen Santella, Regina M. Terry, Mary Beth Turner, Helen C. Brenner, David J. Res Sq Article BACKGROUND: Standard Breast Cancer (BC) risk prediction models based only on epidemiologic factors generally have quite poor performance, and there have been a number of risk scores proposed to improve them, such as AI-based mammographic information, polygenic risk scores and pathogenic variants. Even with these additions BC risk prediction performance is still at best moderate. In that decreased DNA repair capacity (DRC) is a major risk factor for development of cancer, we investigated the potential to improve BC risk prediction models by including a measured phenotypic DRC assay: METHODS: Using blood samples from the Breast Cancer Family Registry we assessed the performance of phenotypic markers of DRC in 46 matched pairs of individuals, one from each pair with BC (with blood drawn before BC diagnosis) and the other from controls matched by age and time since blood draw. We assessed DRC in thawed cryopreserved peripheral blood mononuclear cells (PBMCs) by measuring γ-H2AX yields (a marker for DNA double-strand breaks) at multiple times from 1 to 20 hrs after a radiation challenge. The studies were performed using surface markers to discriminate between different PBMC subtypes. RESULTS: The parameter [Formula: see text] , the residual damage signal in PBMC B cells at 20 hrs post challenge, was the strongest predictor of breast cancer with an AUC (Area Under receiver-operator Curve) of 0.89 [95% Confidence Interval: 0.84–0.93] and a BC status prediction accuracy of 0.80. To illustrate the combined use of a phenotypic predictor with standard BC predictors, we combined [Formula: see text] in B cells with age at blood draw, and found that the combination resulted in significantly greater BC predictive power (AUC of 0.97 [95% CI: 0.94–0.99]), an increase of 13 percentage points over age alone. CONCLUSIONS: If replicated in larger studies, these results suggest that inclusion of a fingerstick-based phenotypic DRC blood test has the potential to markedly improve BC risk prediction. American Journal Experts 2023-06-27 /pmc/articles/PMC10350237/ /pubmed/37461559 http://dx.doi.org/10.21203/rs.3.rs-3093360/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Okunola, Hazeem L. Shuryak, Igor Repin, Mikhail Wu, Hui-Chen Santella, Regina M. Terry, Mary Beth Turner, Helen C. Brenner, David J. Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells |
title | Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells |
title_full | Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells |
title_fullStr | Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells |
title_full_unstemmed | Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells |
title_short | Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells |
title_sort | improved prediction of breast cancer risk based on phenotypic dna damage repair capacity in peripheral blood b cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10350237/ https://www.ncbi.nlm.nih.gov/pubmed/37461559 http://dx.doi.org/10.21203/rs.3.rs-3093360/v1 |
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