TP53-specific mutations serve as a potential biomarker for homologous recombination deficiency in breast cancer: a clinical next-generation sequencing study

Yongsheng Huang , Shuwei Ren , Linxiaoxiao Ding , Yuanling Jiang , Jiahuan Luo , Jinghua Huang , Xinke Yin , Jianli Zhao , Sha Fu , Jianwei Liao

Precision Clinical Medicine ›› 2024, Vol. 7 ›› Issue (2) : pbae009

PDF (1347KB)
Precision Clinical Medicine ›› 2024, Vol. 7 ›› Issue (2) :pbae009 DOI: 10.1093/pcmedi/pbae009
Research Article
research-article

TP53-specific mutations serve as a potential biomarker for homologous recombination deficiency in breast cancer: a clinical next-generation sequencing study

Author information +
History +
PDF (1347KB)

Abstract

Background: TP53 mutations and homologous recombination deficiency (HRD) occur frequently in breast cancer. However, the characteristics of TP53 pathogenic mutations in breast cancer patients with/without HRD are not clear.

Methods: Clinical next-generation sequencing (NGS) of both tumor and paired blood DNA from 119 breast cancer patients (BRCA-119 cohort) was performed with a 520-gene panel. Mutations, tumor mutation burden (TMB), and genomic HRD scores were assessed from NGS data. NGS data from 47 breast cancer patients in the HRD test cohort were analyzed for further verification.

Results: All TP53 pathogenic mutations in patients had somatic origin, which was associated with the protein expression of estrogen receptor and progestogen receptor. Compared to patients without TP53 pathologic mutations, patients with TP53 pathologic mutations had higher levels of HRD scores and different genomic alterations. The frequency of TP53 pathologic mutation was higher in the HRD-high group (HRD score ≥ 42) relative to that in the HRD-low group (HRD score < 42). TP53 has different mutational characteristics between the HRD-low and HRD-high groups. TP53-specific mutation subgroups had diverse genomic features and TMB. Notably, TP53 pathogenic mutations predicted the HRD status of breast cancer patients with an area under the curve (AUC) of 0.61. TP53-specific mutations, namely HRD-low mutation, HRD-high mutation, and HRD common mutation, predicted the HRD status of breast cancer patients with AUC values of 0.32, 0.72, and 0.58, respectively. Interestingly, TP53 HRD-high mutation and HRD common mutation combinations showed the highest AUC values (0.80) in predicting HRD status.

Conclusions: TP53-specific mutation combinations predict the HRD status of patients, indicating that TP53 pathogenic mutations could serve as a potential biomarker for poly-ADP-ribose polymerase (PARP) inhibitors in breast cancer patients.

Keywords

next-generation sequencing / homologous recombination deficiency / TP53 / breast cancer

Cite this article

Download citation ▾
Yongsheng Huang, Shuwei Ren, Linxiaoxiao Ding, Yuanling Jiang, Jiahuan Luo, Jinghua Huang, Xinke Yin, Jianli Zhao, Sha Fu, Jianwei Liao. TP53-specific mutations serve as a potential biomarker for homologous recombination deficiency in breast cancer: a clinical next-generation sequencing study. Precision Clinical Medicine, 2024, 7(2): pbae009 DOI:10.1093/pcmedi/pbae009

登录浏览全文

4963

注册一个新账户 忘记密码

Ethical declaration

The study was conducted in accordance with the Helsinki Declaration. Patient records were anonymized prior to analysis. This study was approved by the Institutional Review Board of Sun Yat-sen Memorial Hospital (NO. SYSKY-2023-458-01).

Acknowledgements

This study was supported by funding from the National Natural Science Foundation of China (Grants No. 82203435, 82203703, 82203141, and 82102865), Guangdong Basic and Applied Basic Research Foundation (Grant No. 2021A1515111138), Guangzhou Science and Technology Plan Project Support (Grant No. 2023A04J2103), and the China Postdoctoral Science Foundation (Grants No. 2022M713576 and 2022T150757).

Author contributions

Study administration, validation, and design: J.Z., S.F., and J.L. Methodology, acquisition, and interpretation of data: all authors. Writing-original manuscript: Y.H. Study supervision: J.L. All authors read and approved the final manuscript.

Supplementary data

Supplementary data is available at PCMEDI online.

Conflict of interest

None declared.

References

[1]

Lord CJ, Ashworth A. PARP inhibitors: synthetic lethality in the clinic. Science 2017;355:1152-8. https://doi.org/10.1126/science.aam7344.

[2]

Menezes MCS, Raheem F, Mina L et al. PARP inhibitors for breast cancer: germline BRCA1/2 and beyond. Cancers 2022;14:4332. https://doi.org/10.3390/cancers14174332.

[3]

Nguyen L, Martens JWM, Van Hoeck A et al. Pan-cancer landscape of homologous recombination deficiency. Nat Commun 2020;11:5584. https://doi.org/10.1038/s41467-020-19406-4.

[4]

Shahbandi A, Nguyen HD, Jackson JG. TP 53 Mutations and outcomes in breast cancer: reading beyond the headlines. Trends Cancer 2020;6:98-110. https://doi.org/10.1016/j.trecan.2020.01.007.

[5]

Cosgrove N, Varešlija D, Keelan S et al. Mapping molecular subtype specific alterations in breast cancer brain metastases identifies clinically relevant vulnerabilities. Nat Commun 2022;13:514. https://doi.org/10.1038/s41467-022-27987-5.

[6]

Abuhamad AY, Mohamad Zamberi NN, Sheen L et al. Reverting TP53 mutation in breast cancer cells: prime editing workflow and technical considerations. Cells 2022;11:1612. https://doi.org/10.3390/cells11101612.

[7]

Wang Y, Xu Y, Chen J et al. TP 53 mutations are associated with higher rates of pathologic complete response to anthracycline/cyclophosphamide-based neoadjuvant chemotherapy in operable primary breast cancer. Int J Cancer 2016;138:489-96. https://doi.org/10.1002/ijc.29715.

[8]

Vodicka P, Andera L, Opattova A et al. The interactions of DNA repair, telomere homeostasis, and p53 mutational status in solid cancers: risk, prognosis, and prediction. Cancers 2021;13:479. https://doi.org/10.3390/cancers13030479.

[9]

Lieberman HB, Panigrahi SK, Hopkins KM et al. p53 and RAD9, the DNA damage response, and regulation of transcription networks. Radiat Res 2017;187:424-32. https://doi.org/10.1667/RR003CC.1.

[10]

Danovi S. TP53-dependent genomic instability. Nat Genet 2022;54:1584. https://doi.org/10.1038/s41588-022-01216-7.

[11]

Murai J, Pommier Y. BRCAness,homologous recombination deficiencies, and synthetic lethality. Cancer Res 2023;83:1173-4. https://doi.org/10.1158/0008-5472.CAN-23-0628.

[12]

De Summa S, Pinto R, Sambiasi D et al. BRCAness: a deeper insight into basal-like breast tumors. Ann Oncol 2013;24:viii13-21. https://doi.org/10.1093/annonc/mdt306.

[13]

Knijnenburg TA, Wang L, Zimmermann MT et al. Genomic and molecular landscape of DNA damage repair deficiency across the cancer genome atlas. Cell Rep 2018;23:239-254.e236. https://doi.org/10.1016/j.celrep.2018.03.076.

[14]

Huang Y, Liao J, Liang F et al. A 25-gene panel predicting the benefits of immunotherapy in head and neck squamous cell carcinoma. Int Immunopharmacol 2022;110:108846. https://doi.org/10.1016/j.intimp.2022.108846.

[15]

Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009;25:1754-60. https://doi.org/10.1093/bioinformatics/btp324.

[16]

McKenna A, Hanna M, Banks E et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010;20:1297-303. https://doi.org/10.1101/gr.107524.110.

[17]

Koboldt DC, Zhang Q, Larson DE et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 2012;22:568-76. https://doi.org/10.1101/gr.129684.111.

[18]

Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 2010;38:e164. https://doi.org/10.1093/nar/gkq603.

[19]

Cingolani P, Platts A, Wang LL et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 2012;6:80-92. https://doi.org/10.4161/fly.19695.

[20]

Newman AM, Bratman SV, Stehr H et al. FACTERA: a practical method for the discovery of genomic rearrangements at breakpoint resolution. Bioinformatics 2014;30:3390-3. https://doi.org/10.1093/bioinformatics/btu549.

[21]

Robinson JT, Thorvaldsdóttir H, Winckler W et al. Integrative genomics viewer. Nat Biotechnol 2011;29:24-6. https://doi.org/10.1038/nbt.1754.

[22]

Miller DT, Lee K, Chung WK et al. ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2021;23:1381-90. https://doi.org/10.1038/s41436-021-01172-3.

[23]

Richards S, Aziz N, Bale S et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015;17:405-24. https://doi.org/10.1038/gim.2015.30.

[24]

Li Q, Wang K. InterVar: clinical interpretation of genetic variants by the 2015 ACMG-AMP Guidelines. Am J Hum Genet 2017;100:267-80. https://doi.org/10.1016/j.ajhg.2017.01.004.

[25]

Danos AM, Krysiak K, Barnell EK et al. Standard operating procedure for curation and clinical interpretation of variants in cancer. Genome Med 2019;11:76. https://doi.org/10.1186/s13073-019-0687-x.

[26]

Horak P, Griffith M, Danos AM et al. Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC). Genet Med 2022;24:986-98. https://doi.org/10.1016/j.gim.2022.01.001.

[27]

Feng J, Lan Y, Liu F et al. Combination of genomic instability score and TP 53 status for prognosis prediction in lung adenocarcinoma. NPJ Precis Oncol 2023;7:110. https://doi.org/10.1038/s41698-023-00465-x.

[28]

Abkevich V, Timms KM, Hennessy BT et al. Patterns of genomic loss of heterozygosity predict homologous recombination repair defects in epithelial ovarian cancer. BrJ Cancer 2012;107:1776-82. https://doi.org/10.1038/bjc.2012.451.

[29]

Popova T, Manié E, Rieunier G et al. Ploidy and large-scale genomic instability consistently identify basal-like breast carcinomas with BRCA1/2 inactivation. Cancer Res 2012;72:5454-62. https://doi.org/10.1158/0008-5472.CAN-12-1470.

[30]

Birkbak NJ, Wang ZC, Kim JY et al. Telomeric allelic imbalance indicates defective DNA repair and sensitivity to DNA-damaging agents. Cancer Discov 2012;2:366-75. https://doi.org/10.1158/2159-8290.CD-11-0206.

[31]

Sztupinszki Z, Diossy M, Krzystanek M et al. Migrating the SNP array-based homologous recombination deficiency measures to next generation sequencing data of breast cancer. NPJ Breast Cancer 2018;4:16. https://doi.org/10.1038/s41523-018-0066-6.

[32]

Telli ML, Timms KM, Reid J et al. Homologous recombination deficiency (HRD) score predicts response to platinum-containing neoadjuvant chemotherapy in patients with triple-negative breast cancer. Clin Cancer Res 2016;22:3764-73. https://doi.org/10.1158/1078-0432.CCR-15-2477.

[33]

Thorsson V, Gibbs DL, Brown SD et al. The Immune Landscape of cancer. Immunity 2018;48:812-830.e814. https://doi.org/10.1016/j.immuni.2018.03.023.

[34]

McCabe N, Turner NC, Lord CJ et al. Deficiency in the repair of DNA damage by homologous recombination and sensitivity to poly(ADP-ribose) polymerase inhibition. Cancer Res 2006;66:8109-15. https://doi.org/10.1158/0008-5472.CAN-06-0140.

[35]

Lord CJ, Ashworth A. BRCAness revisited. Nat Rev Cancer 2016;16:110-20. https://doi.org/10.1038/nrc.2015.21.

[36]

Hewitt G, Borel V, Segura-Bayona S et al. Defective ALC1 nucleosome remodeling confers PARPi sensitization and synthetic lethality with HRD. Mol Cell 2021;81:767-783.e711. https://doi.org/10.1016/j.molcel.2020.12.006.

[37]

Zhang F, Tang H, Jiang Y et al. The transcription factor GATA3 is required for homologous recombination repair by regulating CtIP expression. Oncogene 2017;36:5168-76. https://doi.org/10.1038/onc.2017.127.

[38]

Inagaki-Kawata Y, Yoshida K, Kawaguchi-Sakita N et al. Genetic and clinical landscape of breast cancers with germline BRCA1/2 variants. Commun Biol 2020;3:578. https://doi.org/10.1038/s42003-020-01301-9.

[39]

Kaur RP, Vasudeva K, Kumar R et al. Role of p53 gene in breast cancer: focus on mutation spectrum and therapeutic strategies. Curr Pharm Des 2018;24:3566-75. https://doi.org/10.2174/1381612824666180926095709.

[40]

Silwal-Pandit L, Langerød A, Børresen-Dale AL. TP 53 Mutations in breast and ovarian cancer. Cold Spring Harb Perspect Med 2017;7:a026252. https://doi.org/10.1101/cshperspect.a026252.

[41]

Kimura M. The number of heterozygous nucleotide sites maintained in a finite population due to steady flux of mutations. Genetics 1969;61:893-903. https://doi.org/10.1093/genetics/61.4.893.

[42]

Demeulemeester J, Dentro SC, Gerstung M et al. Biallelic mutations in cancer genomes reveal local mutational determinants. Nat Genet 2022;54:128-33. https://doi.org/10.1038/s41588-021-01005-8.

[43]

Catucci I, Osorio A, Arver B et al. Individuals with FANCM biallelic mutations do not develop Fanconi anemia, but show risk for breast cancer, chemotherapy toxicity and may display chromosome fragility. Genet Med 2018;20:452-7. https://doi.org/10.1038/gim.2017.123.

[44]

Bernard E, Nannya Y, Hasserjian RP et al. Implications of TP53 allelic state for genome stability, clinical presentation and outcomes in myelodysplastic syndromes. Nat Med 2020;26:1549-56. https://doi.org/10.1038/s41591-020-1008-z.

[45]

Arora S, Balasubramaniam S, Zhang H et al. FDA approval summary: Olaparib monotherapy or in combination with Beva-cizumab for the maintenance treatment of patients with advanced ovarian cancer. Oncologist 2021;26:e164-72. https://doi.org/10.1002/onco.13551.

[46]

Ngoi NYL, Tan DSP. The role of homologous recombination deficiency testing in ovarian cancer and its clinical implications: do we need it? ESMO Open 2021;6:100144. https://doi.org/10.1016/j.esmoop.2021.100144.

[47]

Pellegrino B, Herencia-Ropero A, Llop-Guevara A et al. Preclinical In vivo validation of the RAD51 test for identification of homologous recombination-deficient tumors and patient stratification. Cancer Res 2022;82:1646-57. https://doi.org/10.1158/0008-5472.CAN-21-2409.

[48]

Schroth W, Büttner FA, Kandabarau S et al. Gene expression signatures of BRCAness and tumor inflammation define subgroups of early-stage hormone receptor-positive breast cancer patients. Clin Cancer Res 2020;26:6523-34. https://doi.org/10.1158/1078-0432.CCR-20-1923.

AI Summary AI Mindmap
PDF (1347KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/