» Articles » PMID: 27587435

Molecular Differences Between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes

Abstract

Interval breast cancer is of clinical interest, as it exhibits an aggressive phenotype and evades detection by screening mammography. A comprehensive picture of somatic changes that drive tumors to become symptomatic in the screening interval can improve understanding of the biology underlying these aggressive tumors. Initiated in April 2013, Clinical Sequencing of Cancer in Sweden (Clinseq) is a scientific and clinical platform for the genomic profiling of cancer. The breast cancer pilot study consisted of women diagnosed with breast cancer between 2001 and 2012 in the Stockholm/Gotland regions. A subset of 307 breast tumors was successfully sequenced, of which 113 were screen-detected and 60 were interval cancers. We applied targeted deep sequencing of cancer-related genes; low-pass, whole-genome sequencing; and RNA sequencing technology to characterize somatic differences in the genomic and transcriptomic architecture by interval cancer status. Mammographic density and PAM50 molecular subtypes were considered. In the univariate analyses, , and were significantly more frequently mutated in interval cancers than in screen-detected cancers. Acquired somatic copy number aberrations with a frequency difference of at least 15% between the two groups included gains in 17q23-q25.3 and losses in 16q24.2. Gene expression analysis identified 447 significantly differentially expressed genes, of which 120 were replicated in an independent microarray dataset. After adjusting for PAM50, most differences were no longer significant. Molecular differences by interval cancer status were observed, but they were largely explained by PAM50 subtypes. This work offers new insights into the biological differences between the two tumor groups. .

Citing Articles

Mapping the Temporal Landscape of Breast Cancer Using Epigenetic Entropy.

Shibata D, Monyak D, Holloway S, Gumbert G, Grimm L, Hwang S Res Sq. 2024; .

PMID: 39574883 PMC: 11581123. DOI: 10.21203/rs.3.rs-5119308/v1.


Using gene and gene-set association tests to identify lethal prostate cancer genes.

Feng B, Boyle J, Wei J, Carroll C, Snyder N, Shi Z Prostate Cancer Prostatic Dis. 2024; .

PMID: 39154125 DOI: 10.1038/s41391-024-00879-z.


Genetic landscape of interval and screen detected breast cancer.

Mills C, Sud A, Everall A, Chubb D, Lawrence S, Kinnersley B NPJ Precis Oncol. 2024; 8(1):122.

PMID: 38806682 PMC: 11133314. DOI: 10.1038/s41698-024-00618-6.


Distinct shared and compartment-enriched oncogenic networks drive primary versus metastatic breast cancer.

Jiang Z, Ju Y, Ali A, Chung P, Skowron P, Wang D Nat Commun. 2023; 14(1):4313.

PMID: 37463901 PMC: 10354065. DOI: 10.1038/s41467-023-39935-y.


Identification of a 5-gene-risk score model for predicting luminal A-invasive lobular breast cancer survival.

Chen Y, Zhang T, Liu Y, Zheng J, Lin W, Chen Y Genetica. 2022; 150(5):299-316.

PMID: 35536451 DOI: 10.1007/s10709-022-00157-7.