Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer

被引:4
作者
Cosgrove, Nicola [1 ]
Eustace, Alex J. [2 ]
O'Donovan, Peter [1 ]
Madden, Stephen F. [3 ]
Moran, Bruce [4 ]
Crown, John [5 ]
Moulton, Brian [6 ]
Morris, Patrick G. [7 ]
Grogan, Liam [7 ]
Breathnach, Oscar [7 ]
Power, Colm [8 ]
Allen, Michael [8 ]
Walshe, Janice M. [5 ]
Hill, Arnold D. [8 ]
Blumel, Anna [9 ]
O'Connor, Darren [9 ]
Das, Sudipto [9 ]
Milewska, Malgorzata [10 ]
Fay, Joanna [11 ]
Kay, Elaine [12 ]
Toomey, Sinead [10 ]
Hennessy, Bryan T. [7 ,10 ]
Furney, Simon J. [1 ]
机构
[1] RCSI Univ Med & Hlth Sci, Dept Physiol & Med Phys, Genom Oncol Res Grp, Dublin, Ireland
[2] Dublin City Univ, Natl Inst Cellular Biotechnol, Sch Biotechnol, Dublin, Ireland
[3] RCSI Univ Med & Hlth Sci, Data Sci Ctr, Dublin, Ireland
[4] Univ Coll Dublin, Conway Inst, Dublin, Ireland
[5] St Vincents Univ Hosp, Dept Med Oncol, Dublin, Ireland
[6] Clin Oncol Dev Europe, Dublin, Ireland
[7] Beaumont Hosp, Dept Med Oncol, Dublin, Ireland
[8] RCSI Univ Med & Hlth Sci, Dept Surg, Dublin, Ireland
[9] RCSI Univ Med & Hlth Sci, Sch Pharm & Biomol Sci, Dublin, Ireland
[10] Royal Coll Surgeons Ireland, Dept Mol Med, Med Oncol Grp, Dublin, Ireland
[11] RCSI Univ Med & Hlth Sci, Beaumont Hosp, RCSI Biobank Serv, Dublin, Ireland
[12] RCSI Univ Med & Hlth Sci, Beaumont Hosp, Dept Pathol, Dublin, Ireland
基金
英国惠康基金;
关键词
PATHOLOGICAL COMPLETE RESPONSE; OPEN-LABEL; TRASTUZUMAB RESISTANCE; CHEMOTHERAPY; LAPATINIB; MULTICENTER; NEOALTTO; IMMUNE; HETEROGENEITY; ACTIVATION;
D O I
10.1038/s41523-023-00572-9
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
HER2-positive (HER2+) breast cancer accounts for 20-25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical trial (ICORG10-05/NCT01485926) whole exome DNA sequencing was carried out on normal-tumour pairs collected from 22 patients. Here we report predictive modelling of neoadjuvant therapy response using clinicopathological and genomic features of pre-treatment tumour biopsies identified age, estrogen receptor (ER) status and level of immune cell infiltration may together be important for predicting response. Clonal evolution analysis of longitudinally collected tumour samples show subclonal diversity and dynamics are evident with potential therapy resistant subclones detected. The sources of greater pre-treatment immunogenicity associated with a pathological complete response is largely unexplored in HER2+ tumours. However, here we point to the possibility of APOBEC associated mutagenesis, specifically in the ER-neg/HER2+ subtype as a potential mediator of this immunogenic phenotype.
引用
收藏
页数:16
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