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Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast.

ABSTRACT: In a substantial number of patients, ductal carcinoma in situ (DCIS) of the breast will never progress to invasive ductal carcinoma, and these patients are often overtreated under the current clinical criteria. Although various candidate markers are available, relevant markers for delineating risk categories have not yet been established. In this study, we analyzed the clinical characteristics of 431 patients with DCIS and performed whole-exome sequencing analysis in a 21-patient discovery cohort and targeted deep sequencing analysis in a 72-patient validation cohort. We determined that age <45 years, HER2 amplification, and GATA3 mutation are possible indicators of relapse. PIK3CA mutation negativity and PgR negativity were also suggested to be risk factors. Spatial transcriptome analysis further revealed that GATA3 dysfunction upregulates epithelial-to-mesenchymal transition and angiogenesis, followed by PgR downregulation. These results reveal the existence of heterogeneous cell populations in DCIS and provide predictive markers for classifying DCIS and optimizing treatment.

SUBMITTER: Nagasawa S

PROVIDER: S-EPMC8016951 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

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Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast.

Nagasawa Satoi S Kuze Yuta Y Maeda Ichiro I Kojima Yasuyuki Y Motoyoshi Ai A Onishi Tatsuya T Iwatani Tsuguo T Yokoe Takamichi T Koike Junki J Chosokabe Motohiro M Kubota Manabu M Seino Hibiki H Suzuki Ayako A Seki Masahide M Tsuchihara Katsuya K Inoue Eisuke E Tsugawa Koichiro K Ohta Tomohiko T Suzuki Yutaka Y

Communications biology 20210401 1

In a substantial number of patients, ductal carcinoma in situ (DCIS) of the breast will never progress to invasive ductal carcinoma, and these patients are often overtreated under the current clinical criteria. Although various candidate markers are available, relevant markers for delineating risk categories have not yet been established. In this study, we analyzed the clinical characteristics of 431 patients with DCIS and performed whole-exome sequencing analysis in a 21-patient discovery cohor ...[more]

PMID: 33795819

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Project description:Background The dramatic increase in incidence of ductal carcinoma in situ (DCIS) associated with mammographic screening for breast cancer has given emphasis to the challenges of managing this important clinical entity. Unlike invasive breast cancer, there is no established histopathologic grading system for DCIS, nor are there biological markers of prognosis to guide clinical management. The aim of this study is to use molecular profiling to identify robust and clinically applicable indicators of DCIS malignant potential. Methods Areas of intraduct carcinoma, atypical ductal hyperplasia and benign epithelium were isolated from 46 well-characterised invasive breast cancers by laser capture microdissection. Microarray based gene expression profiling was used to identify genes differentially expressed between DCIS associated with grade 1 and grade 3 invasive carcinoma (‘grade associated genes’). The expression profile of these genes was then determined in all samples and used to define ‘molecular grade’ categories. The genomic basis of gene expression derived categories was examined by array-based comparative genomic hybridisation (CGH). Results DCIS samples could be divided into two subgroups, designated low and high molecular grade (MG) on the basis of expression at 173 grade associated oligonucleotide probes. The low MG subgroup included 21 DCIS samples of low (n=10) and intermediate (n=11) nuclear grade as well as all samples of ADH (n=4) and benign epithelium (n=7). The high MG subgroup included 27 DCIS samples of intermediate (n=7) and high (n=19) nuclear grade. Array CGH revealed distinct differences in the character and degree of genomic aberration associated with MG and the clinical significance of MG was verified by a strong correlation with survival in two independent invasive breast cancer gene expression datasets (n=295 and n=186). MG categories were strongly associated with histopathologic and biomarker features of DCIS. Using a classification tree model, DCIS MG could be accurately predicted in 44/46 (95.7%) of samples using a combination of nuclear grade and Ki67 score. Conclusions Molecular profiling indicates a binary grading scheme for DCIS that is both biologically relevant and clinically informative. The low and high MG DCIS classification could be recapitulated by a novel combination of routinely accessible features. This practical approach has potential to immediately improve clinical evaluation and management of DCIS. Keywords: Paired gene expression and CGH Paired CGH and Gene Expression on DCIS of the breast

Dataset Information

Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast.

Publications

Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast.

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