Unknown

Dataset Information

0

Genomic landscape of ductal carcinoma in situ and association with progression.


ABSTRACT: PURPOSE:The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS. METHODS:Targeted exon sequencing with a custom panel of 223 genes/regions was performed for 125 DCIS cases. Among them, 60 were from cases having concurrent or subsequent invasive breast cancer (IBC) (DCIS?+?IBC group), and 65 from cases with no IBC development over a median follow-up of 13 years (DCIS-only group). Copy number alterations in chromosome 1q32, 8q24, and 11q13 were analyzed using fluorescence in situ hybridization (FISH). Multivariable logistic regression models were fit to the outcome of DCIS progression to IBC as functions of demographic and clinical features. RESULTS:We observed recurrent variants of known IBC-related mutations, and the most commonly mutated genes in DCIS were PIK3CA (34.4%) and TP53 (18.4%). There was an inverse association between PIK3CA kinase domain mutations and progression (Odds Ratio [OR] 10.2, p?

SUBMITTER: Lin CY 

PROVIDER: S-EPMC6800639 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications

Genomic landscape of ductal carcinoma in situ and association with progression.

Lin Chieh-Yu CY   Vennam Sujay S   Purington Natasha N   Lin Eric E   Varma Sushama S   Han Summer S   Desa Manisha M   Seto Tina T   Wang Nicholas J NJ   Stehr Henning H   Troxell Megan L ML   Kurian Allison W AW   West Robert B RB  

Breast cancer research and treatment 20190817 2


<h4>Purpose</h4>The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS.<h4>Methods</h4>Targeted exon sequenci  ...[more]

Similar Datasets

| S-EPMC7017577 | biostudies-literature
| S-EPMC4480702 | biostudies-literature
| S-ECPF-GEOD-33692 | biostudies-other
| S-EPMC5637904 | biostudies-literature
| S-EPMC4630168 | biostudies-literature
| S-EPMC5528459 | biostudies-other
| S-EPMC7072653 | biostudies-literature
2012-03-31 | E-GEOD-33692 | biostudies-arrayexpress
| S-ECPF-GEOD-11042 | biostudies-other
2012-04-01 | GSE33692 | GEO