Skip to main content
Top
Published in: Journal of Translational Medicine 1/2022

Open Access 01-12-2022 | Breast Cancer | Research

Integration of radiogenomic features for early prediction of pathological complete response in patients with triple-negative breast cancer and identification of potential therapeutic targets

Authors: Ying Zhang, Chao You, Yuchen Pei, Fan Yang, Daqiang Li, Yi-zhou Jiang, Zhimin Shao

Published in: Journal of Translational Medicine | Issue 1/2022

Login to get access

Abstract

Background

We established a radiogenomic model to predict pathological complete response (pCR) in triple-negative breast cancer (TNBC) and explored the association between high-frequency mutations and drug resistance.

Methods

From April 2018 to September 2019, 112 patients who had received neoadjuvant chemotherapy were included. We randomly split the study population into training and validation sets (2:1 ratio). Contrast-enhanced magnetic resonance imaging scans were obtained at baseline and after two cycles of treatment and were used to extract quantitative radiomic features and to construct two radiomics-only models using a light gradient boosting machine. By incorporating the variant allele frequency features obtained from baseline core tissues, a radiogenomic model was constructed to predict pCR. Additionally, we explored the association between recurrent mutations and drug resistance.

Results

The two radiomics-only models showed similar performance with AUCs of 0.71 and 0.73 (p = 0.55). The radiogenomic model had a higher predictive ability than the radiomics-only model in the validation set (p = 0.04), with a corresponding AUC of 0.87 (0.73–0.91).
Two highly frequent mutations were selected after comparing the mutation sites of pCR and non-pCR populations. The MED23 mutation p.P394H caused epirubicin resistance in vitro (p < 0.01). The expression levels of γ-H2A.X, p-ATM and p-CHK2 in MED23 p.P394H cells were significantly lower than those in wild type cells (p < 0.01). In the HR repair system, the GFP positivity rate of MED23 p.P394H cells was higher than that in wild-type cells (p < 0.01).

Conclusions

The proposed radiogenomic model has the potential to accurately predict pCR in TNBC patients. Epirubicin resistance after MED23 p.P394H mutation might be affected by HR repair through regulation of the p-ATM-γ-H2A.X-p-CHK2 pathway.
Appendix
Available only for authorised users
Literature
2.
go back to reference Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384(9938):164–72.CrossRefPubMed Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, Bonnefoi H, Cameron D, Gianni L, Valagussa P, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384(9938):164–72.CrossRefPubMed
3.
go back to reference von Minckwitz G, Untch M, Blohmer JU, Costa SD, Eidtmann H, Fasching PA, Gerber B, Eiermann W, Hilfrich J, Huober J, et al. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol. 2012;30(15):1796–804.CrossRef von Minckwitz G, Untch M, Blohmer JU, Costa SD, Eidtmann H, Fasching PA, Gerber B, Eiermann W, Hilfrich J, Huober J, et al. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol. 2012;30(15):1796–804.CrossRef
4.
go back to reference Sikov WM, Berry DA, Perou CM, Singh B, Cirrincione CT, Tolaney SM, Kuzma CS, Pluard TJ, Somlo G, Port ER, et al. Impact of the addition of carboplatin and/or bevacizumab to neoadjuvant once-per-week paclitaxel followed by dose-dense doxorubicin and cyclophosphamide on pathologic complete response rates in stage II to III triple-negative breast cancer: CALGB 40603 (Alliance). J Clin Oncol. 2015;33(1):13–21.CrossRefPubMed Sikov WM, Berry DA, Perou CM, Singh B, Cirrincione CT, Tolaney SM, Kuzma CS, Pluard TJ, Somlo G, Port ER, et al. Impact of the addition of carboplatin and/or bevacizumab to neoadjuvant once-per-week paclitaxel followed by dose-dense doxorubicin and cyclophosphamide on pathologic complete response rates in stage II to III triple-negative breast cancer: CALGB 40603 (Alliance). J Clin Oncol. 2015;33(1):13–21.CrossRefPubMed
5.
go back to reference Zhang K, Li J, Zhu Q, Chang C. Prediction of pathologic complete response by ultrasonography and magnetic resonance imaging after neoadjuvant chemotherapy in patients with breast cancer. Cancer Manag Res. 2020;12:2603–12.CrossRefPubMedPubMedCentral Zhang K, Li J, Zhu Q, Chang C. Prediction of pathologic complete response by ultrasonography and magnetic resonance imaging after neoadjuvant chemotherapy in patients with breast cancer. Cancer Manag Res. 2020;12:2603–12.CrossRefPubMedPubMedCentral
6.
go back to reference Coudert B, Pierga JY, Mouret-Reynier MA, Kerrou K, Ferrero JM, Petit T, Kerbrat P, Dupre PF, Bachelot T, Gabelle P, et al. Use of [(18)F]-FDG PET to predict response to neoadjuvant trastuzumab and docetaxel in patients with HER2-positive breast cancer, and addition of bevacizumab to neoadjuvant trastuzumab and docetaxel in [(18)F]-FDG PET-predicted non-responders (AVATAXHER): an open-label, randomised phase 2 trial. Lancet Oncol. 2014;15(13):1493–502.CrossRefPubMed Coudert B, Pierga JY, Mouret-Reynier MA, Kerrou K, Ferrero JM, Petit T, Kerbrat P, Dupre PF, Bachelot T, Gabelle P, et al. Use of [(18)F]-FDG PET to predict response to neoadjuvant trastuzumab and docetaxel in patients with HER2-positive breast cancer, and addition of bevacizumab to neoadjuvant trastuzumab and docetaxel in [(18)F]-FDG PET-predicted non-responders (AVATAXHER): an open-label, randomised phase 2 trial. Lancet Oncol. 2014;15(13):1493–502.CrossRefPubMed
7.
go back to reference Dialani V, Chadashvili T, Slanetz PJ. Role of imaging in neoadjuvant therapy for breast cancer. Ann Surg Oncol. 2015;22(5):1416–24.CrossRefPubMed Dialani V, Chadashvili T, Slanetz PJ. Role of imaging in neoadjuvant therapy for breast cancer. Ann Surg Oncol. 2015;22(5):1416–24.CrossRefPubMed
8.
go back to reference Kai C, Ishimaru M, Uchiyama Y, Shiraishi J, Shinohara N, Fujita H. Selection of radiomic features for the classification of triple-negative breast cancer based on radiogenomics. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2019;75(1):24–31.CrossRefPubMed Kai C, Ishimaru M, Uchiyama Y, Shiraishi J, Shinohara N, Fujita H. Selection of radiomic features for the classification of triple-negative breast cancer based on radiogenomics. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2019;75(1):24–31.CrossRefPubMed
9.
go back to reference Cain EH, Saha A, Harowicz MR, Marks JR, Marcom PK, Mazurowski MA. Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set. Breast Cancer Res Treat. 2019;173(2):455–63.CrossRefPubMed Cain EH, Saha A, Harowicz MR, Marks JR, Marcom PK, Mazurowski MA. Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set. Breast Cancer Res Treat. 2019;173(2):455–63.CrossRefPubMed
10.
go back to reference Liu Z, Li Z, Qu J, Zhang R, Zhou X, Li L, Sun K, Tang Z, Jiang H, Li H, et al. Radiomics of multiparametric mri for pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study. Clin Cancer Res. 2019;25(12):3538–47.CrossRefPubMed Liu Z, Li Z, Qu J, Zhang R, Zhou X, Li L, Sun K, Tang Z, Jiang H, Li H, et al. Radiomics of multiparametric mri for pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study. Clin Cancer Res. 2019;25(12):3538–47.CrossRefPubMed
11.
go back to reference Mirestean CC, Volovat C, Iancu RI, Iancu DPT. Radiomics in triple negative breast cancer: new horizons in an aggressive subtype of the disease. J Clin Med. 2022;11(3):616.CrossRefPubMedPubMedCentral Mirestean CC, Volovat C, Iancu RI, Iancu DPT. Radiomics in triple negative breast cancer: new horizons in an aggressive subtype of the disease. J Clin Med. 2022;11(3):616.CrossRefPubMedPubMedCentral
12.
13.
go back to reference Bodalal Z, Trebeschi S, Nguyen-Kim TDL, Schats W, Beets-Tan R. Radiogenomics: bridging imaging and genomics. Abdom Radiol. 2019;44(6):1960–84.CrossRef Bodalal Z, Trebeschi S, Nguyen-Kim TDL, Schats W, Beets-Tan R. Radiogenomics: bridging imaging and genomics. Abdom Radiol. 2019;44(6):1960–84.CrossRef
14.
go back to reference Sporikova Z, Koudelakova V, Trojanec R, Hajduch M. Genetic markers in triple-negative breast cancer. Clin Breast Cancer. 2018;18(5):e841–50.CrossRefPubMed Sporikova Z, Koudelakova V, Trojanec R, Hajduch M. Genetic markers in triple-negative breast cancer. Clin Breast Cancer. 2018;18(5):e841–50.CrossRefPubMed
15.
go back to reference Jiang YZ, Ma D, Suo C, Shi J, Xue M, Hu X, Xiao Y, Yu KD, Liu YR, Yu Y, et al. Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies. Cancer Cell. 2019;35(3):428-440 e45.CrossRefPubMed Jiang YZ, Ma D, Suo C, Shi J, Xue M, Hu X, Xiao Y, Yu KD, Liu YR, Yu Y, et al. Genomic and transcriptomic landscape of triple-negative breast cancers: subtypes and treatment strategies. Cancer Cell. 2019;35(3):428-440 e45.CrossRefPubMed
16.
go back to reference Guolin Ke QM. Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu: LightGBM: A Highly Efficient Gradient Boosting Decision Tree. Adv Neural Inf Process Syst. 2017;30:3149–57. Guolin Ke QM. Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu: LightGBM: A Highly Efficient Gradient Boosting Decision Tree. Adv Neural Inf Process Syst. 2017;30:3149–57.
17.
go back to reference Lang GT, Jiang YZ, Shi JX, Yang F, Li XG, Pei YC, Zhang CH, Ma D, Xiao Y, Hu PC, et al. Characterization of the genomic landscape and actionable mutations in Chinese breast cancers by clinical sequencing. Nat Commun. 2020;11(1):5679.CrossRefPubMedPubMedCentral Lang GT, Jiang YZ, Shi JX, Yang F, Li XG, Pei YC, Zhang CH, Ma D, Xiao Y, Hu PC, et al. Characterization of the genomic landscape and actionable mutations in Chinese breast cancers by clinical sequencing. Nat Commun. 2020;11(1):5679.CrossRefPubMedPubMedCentral
18.
go back to reference Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, Fitzgibbons PL, Francis G, Goldstein NS, Hayes M, et al. American society of clinical oncology/college of American pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol. 2010;28(16):2784–95.CrossRefPubMedPubMedCentral Hammond ME, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, Fitzgibbons PL, Francis G, Goldstein NS, Hayes M, et al. American society of clinical oncology/college of American pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol. 2010;28(16):2784–95.CrossRefPubMedPubMedCentral
19.
go back to reference Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 2016;44(16):e131.CrossRefPubMedPubMedCentral Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 2016;44(16):e131.CrossRefPubMedPubMedCentral
20.
go back to reference Scott AD, Huang KL, Weerasinghe A, Mashl RJ, Gao Q, Martins Rodrigues F, Wyczalkowski MA, Ding L. CharGer: clinical characterization of Germline variants. Bioinformatics. 2019;35(5):865–7.CrossRefPubMed Scott AD, Huang KL, Weerasinghe A, Mashl RJ, Gao Q, Martins Rodrigues F, Wyczalkowski MA, Ding L. CharGer: clinical characterization of Germline variants. Bioinformatics. 2019;35(5):865–7.CrossRefPubMed
21.
go back to reference Gunn A, Stark JM. I-SceI-based assays to examine distinct repair outcomes of mammalian chromosomal double strand breaks. Methods Mol Biol. 2012;920:379–91.CrossRefPubMed Gunn A, Stark JM. I-SceI-based assays to examine distinct repair outcomes of mammalian chromosomal double strand breaks. Methods Mol Biol. 2012;920:379–91.CrossRefPubMed
22.
go back to reference Carey L, Winer E, Viale G, Cameron D, Gianni L. Triple-negative breast cancer: disease entity or title of convenience? Nat Rev Clin Oncol. 2010;7(12):683–92.CrossRefPubMed Carey L, Winer E, Viale G, Cameron D, Gianni L. Triple-negative breast cancer: disease entity or title of convenience? Nat Rev Clin Oncol. 2010;7(12):683–92.CrossRefPubMed
23.
24.
go back to reference Schettini F, Giuliano M, De Placido S, Arpino G. Nab-paclitaxel for the treatment of triple-negative breast cancer: Rationale, clinical data and future perspectives. Cancer Treat Rev. 2016;50:129–41.CrossRefPubMed Schettini F, Giuliano M, De Placido S, Arpino G. Nab-paclitaxel for the treatment of triple-negative breast cancer: Rationale, clinical data and future perspectives. Cancer Treat Rev. 2016;50:129–41.CrossRefPubMed
25.
go back to reference Li Y, Chen X, Zhu Q, Chen R, Xu L, Li S, Shi X, Xu H, Xu Y, Zhang W, et al. Retrospective comparisons of nanoparticle albumin-bound paclitaxel and docetaxel neoadjuvant regimens for breast cancer. Nanomedicine. 2021;16(5):391–400.CrossRefPubMed Li Y, Chen X, Zhu Q, Chen R, Xu L, Li S, Shi X, Xu H, Xu Y, Zhang W, et al. Retrospective comparisons of nanoparticle albumin-bound paclitaxel and docetaxel neoadjuvant regimens for breast cancer. Nanomedicine. 2021;16(5):391–400.CrossRefPubMed
26.
go back to reference Maleki Dizaj S, Alipour M, Dalir Abdolahinia E, Ahmadian E, Eftekhari A, Forouhandeh H, Rahbar Saadat Y, Sharifi S, Zununi Vahed S. Curcumin nanoformulations: beneficial nanomedicine against cancer. Phytother Res. 2022;36(3):1156–81.CrossRefPubMed Maleki Dizaj S, Alipour M, Dalir Abdolahinia E, Ahmadian E, Eftekhari A, Forouhandeh H, Rahbar Saadat Y, Sharifi S, Zununi Vahed S. Curcumin nanoformulations: beneficial nanomedicine against cancer. Phytother Res. 2022;36(3):1156–81.CrossRefPubMed
27.
go back to reference Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Plecha D, Madabhushi A. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Res. 2017;19(1):57.CrossRefPubMedPubMedCentral Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Plecha D, Madabhushi A. Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Res. 2017;19(1):57.CrossRefPubMedPubMedCentral
28.
go back to reference Huang YQ, Liang CH, He L, Tian J, Liang CS, Chen X, Ma ZL, Liu ZY. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer. J Clin Oncol. 2016;34(18):2157–64.CrossRefPubMed Huang YQ, Liang CH, He L, Tian J, Liang CS, Chen X, Ma ZL, Liu ZY. Development and validation of a radiomics nomogram for preoperative prediction of lymph node metastasis in colorectal cancer. J Clin Oncol. 2016;34(18):2157–64.CrossRefPubMed
29.
go back to reference Koh J, Lee E, Han K, Kim S, Kim DK, Kwak JY, Yoon JH, Moon HJ. Three-dimensional radiomics of triple-negative breast cancer: prediction of systemic recurrence. Sci Rep. 2020;10(1):2976.CrossRefPubMedPubMedCentral Koh J, Lee E, Han K, Kim S, Kim DK, Kwak JY, Yoon JH, Moon HJ. Three-dimensional radiomics of triple-negative breast cancer: prediction of systemic recurrence. Sci Rep. 2020;10(1):2976.CrossRefPubMedPubMedCentral
30.
go back to reference Ma M, Gan L, Liu Y, Jiang Y, Xin L, Liu Y, Qin N, Cheng Y, Liu Q, Xu L, et al. Radiomics features based on automatic segmented MRI images: prognostic biomarkers for triple-negative breast cancer treated with neoadjuvant chemotherapy. Eur J Radiol. 2022;146:110095.CrossRefPubMed Ma M, Gan L, Liu Y, Jiang Y, Xin L, Liu Y, Qin N, Cheng Y, Liu Q, Xu L, et al. Radiomics features based on automatic segmented MRI images: prognostic biomarkers for triple-negative breast cancer treated with neoadjuvant chemotherapy. Eur J Radiol. 2022;146:110095.CrossRefPubMed
31.
go back to reference Liu Z, Zhang XY, Shi YJ, Wang L, Zhu HT, Tang Z, Wang S, Li XT, Tian J, Sun YS. Radiomics analysis for evaluation of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Clin Cancer Res. 2017;23(23):7253–62.CrossRefPubMed Liu Z, Zhang XY, Shi YJ, Wang L, Zhu HT, Tang Z, Wang S, Li XT, Tian J, Sun YS. Radiomics analysis for evaluation of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. Clin Cancer Res. 2017;23(23):7253–62.CrossRefPubMed
32.
go back to reference Yu F, Hang J, Deng J, Yang B, Wang J, Ye X, Liu Y. Radiomics features on ultrasound imaging for the prediction of disease-free survival in triple negative breast cancer: a multi-institutional study. Br J Radiol. 2021;94(1126):20210188.CrossRefPubMed Yu F, Hang J, Deng J, Yang B, Wang J, Ye X, Liu Y. Radiomics features on ultrasound imaging for the prediction of disease-free survival in triple negative breast cancer: a multi-institutional study. Br J Radiol. 2021;94(1126):20210188.CrossRefPubMed
33.
go back to reference Hylton NM, Blume JD, Bernreuter WK, Pisano ED, Rosen MA, Morris EA, Weatherall PT, Lehman CD, Newstead GM, Polin S, et al. Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy–results from ACRIN 6657/I-SPY TRIAL. Radiology. 2012;263(3):663–72.CrossRefPubMedPubMedCentral Hylton NM, Blume JD, Bernreuter WK, Pisano ED, Rosen MA, Morris EA, Weatherall PT, Lehman CD, Newstead GM, Polin S, et al. Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy–results from ACRIN 6657/I-SPY TRIAL. Radiology. 2012;263(3):663–72.CrossRefPubMedPubMedCentral
35.
go back to reference Huang Y, Li W, Yao X, Lin QJ, Yin JW, Liang Y, Heiner M, Tian B, Hui J, Wang G. Mediator complex regulates alternative mRNA processing via the MED23 subunit. Mol Cell. 2012;45(4):459–69.CrossRefPubMedPubMedCentral Huang Y, Li W, Yao X, Lin QJ, Yin JW, Liang Y, Heiner M, Tian B, Hui J, Wang G. Mediator complex regulates alternative mRNA processing via the MED23 subunit. Mol Cell. 2012;45(4):459–69.CrossRefPubMedPubMedCentral
36.
go back to reference Yin JW, Liang Y, Park JY, Chen D, Yao X, Xiao Q, Liu Z, Jiang B, Fu Y, Bao M, et al. Mediator MED23 plays opposing roles in directing smooth muscle cell and adipocyte differentiation. Genes Dev. 2012;26(19):2192–205.CrossRefPubMedPubMedCentral Yin JW, Liang Y, Park JY, Chen D, Yao X, Xiao Q, Liu Z, Jiang B, Fu Y, Bao M, et al. Mediator MED23 plays opposing roles in directing smooth muscle cell and adipocyte differentiation. Genes Dev. 2012;26(19):2192–205.CrossRefPubMedPubMedCentral
37.
go back to reference Yang X, Zhao M, Xia M, Liu Y, Yan J, Ji H, Wang G. Selective requirement for mediator MED23 in Ras-active lung cancer. Proc Natl Acad Sci USA. 2012;109(41):E2813-2822.CrossRefPubMedPubMedCentral Yang X, Zhao M, Xia M, Liu Y, Yan J, Ji H, Wang G. Selective requirement for mediator MED23 in Ras-active lung cancer. Proc Natl Acad Sci USA. 2012;109(41):E2813-2822.CrossRefPubMedPubMedCentral
38.
go back to reference Shi J, Liu H, Yao F, Zhong C, Zhao H. Upregulation of mediator MED23 in non-small-cell lung cancer promotes the growth, migration, and metastasis of cancer cells. Tumour Biol. 2014;35(12):12005–13.CrossRefPubMed Shi J, Liu H, Yao F, Zhong C, Zhao H. Upregulation of mediator MED23 in non-small-cell lung cancer promotes the growth, migration, and metastasis of cancer cells. Tumour Biol. 2014;35(12):12005–13.CrossRefPubMed
39.
go back to reference Guo Y, Wang J, Li H, Liu W, Chen D, Zhao K, Liang X, Zhang Q, Yang Y, Chen G. Mediator subunit 23 overexpression as a novel target for suppressing proliferation and tumorigenesis in hepatocellular carcinoma. J Gastroenterol Hepatol. 2015;30(6):1094–103.CrossRefPubMed Guo Y, Wang J, Li H, Liu W, Chen D, Zhao K, Liang X, Zhang Q, Yang Y, Chen G. Mediator subunit 23 overexpression as a novel target for suppressing proliferation and tumorigenesis in hepatocellular carcinoma. J Gastroenterol Hepatol. 2015;30(6):1094–103.CrossRefPubMed
40.
go back to reference Shi J, Han Q, Zhao H, Zhong C, Yao F. Downregulation of MED23 promoted the tumorigenecity of esophageal squamous cell carcinoma. Mol Carcinog. 2014;53(10):833–40.CrossRefPubMed Shi J, Han Q, Zhao H, Zhong C, Yao F. Downregulation of MED23 promoted the tumorigenecity of esophageal squamous cell carcinoma. Mol Carcinog. 2014;53(10):833–40.CrossRefPubMed
41.
go back to reference Stearns V, Davidson NE, Flockhart DA. Pharmacogenetics in the treatment of breast cancer. Pharmacogenomics J. 2004;4(3):143–53.CrossRefPubMed Stearns V, Davidson NE, Flockhart DA. Pharmacogenetics in the treatment of breast cancer. Pharmacogenomics J. 2004;4(3):143–53.CrossRefPubMed
42.
go back to reference Capeloa T, Benyahia Z, Zampieri LX, Blackman M, Sonveaux P. Metabolic and non-metabolic pathways that control cancer resistance to anthracyclines. Semin Cell Dev Biol. 2020;98:181–91.CrossRefPubMed Capeloa T, Benyahia Z, Zampieri LX, Blackman M, Sonveaux P. Metabolic and non-metabolic pathways that control cancer resistance to anthracyclines. Semin Cell Dev Biol. 2020;98:181–91.CrossRefPubMed
43.
go back to reference Spencer DM, Bilardi RA, Koch TH, Post GC, Nafie JW, Kimura K, Cutts SM, Phillips DR. DNA repair in response to anthracycline-DNA adducts: a role for both homologous recombination and nucleotide excision repair. Mutat Res. 2008;638(1–2):110–21.CrossRefPubMed Spencer DM, Bilardi RA, Koch TH, Post GC, Nafie JW, Kimura K, Cutts SM, Phillips DR. DNA repair in response to anthracycline-DNA adducts: a role for both homologous recombination and nucleotide excision repair. Mutat Res. 2008;638(1–2):110–21.CrossRefPubMed
Metadata
Title
Integration of radiogenomic features for early prediction of pathological complete response in patients with triple-negative breast cancer and identification of potential therapeutic targets
Authors
Ying Zhang
Chao You
Yuchen Pei
Fan Yang
Daqiang Li
Yi-zhou Jiang
Zhimin Shao
Publication date
01-12-2022
Publisher
BioMed Central
Published in
Journal of Translational Medicine / Issue 1/2022
Electronic ISSN: 1479-5876
DOI
https://doi.org/10.1186/s12967-022-03452-1

Other articles of this Issue 1/2022

Journal of Translational Medicine 1/2022 Go to the issue