Molecular Signature of Pregnancy Associated Breast Cancer (PABC)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Harvell DM
PROVIDER: S-ECPF-GEOD-31192 | biostudies-other | 2013 Jun
REPOSITORIES: biostudies-other
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Project description:Malignant epithelia and tumor-associated stroma of PABC and Non-PABC were isolated by laser capture microdissection and gene expression profiled. Additionally, normal breast epithelia and stroma adjacent to the two tumor types were profiled. Lastly, subsets of previously identified E- and P-regulated genes were defined in all tissues. Breast cancers have been obtained from women whose tumors arose while they were pregnant or within 1 year of delivery and from age-matched controls who had never been pregnant. Malignant epithelial cells were separated by laser capture microdissection (LCM) of frozen sections. RNA was isolated and analyzed by expression profiling using Affymetrix U133 2plus Human Gene Chips
2013-06-26 | E-GEOD-31192 | biostudies-arrayexpress
Project description:Malignant epithelia and tumor-associated stroma of PABC and Non-PABC were isolated by laser capture microdissection and gene expression profiled. Additionally, normal breast epithelia and stroma adjacent to the two tumor types were profiled. Lastly, subsets of previously identified E- and P-regulated genes were defined in all tissues.
2013-06-26 | GSE31192 | GEO
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2018-01-08 | GSE108565 | GEO
Project description:PURPOSE:Previously, we developed a radiosensitivity molecular signature [radiosensitivity index (RSI)] that was clinically validated in 3 independent datasets (rectal, esophageal, and head and neck) in 118 patients. Here, we test RSI in radiotherapy (RT)-treated breast cancer patients. EXPERIMENTAL DESIGN:RSI was tested in 2 previously published breast cancer datasets. Patients were treated at the Karolinska University Hospital (n = 159) and Erasmus Medical Center (n = 344). RSI was applied as previously described. RESULTS:We tested RSI in RT-treated patients (Karolinska). Patients predicted to be radiosensitive (RS) had an improved 5-year relapse-free survival when compared with radioresistant (RR) patients (95% vs. 75%, P = 0.0212), but there was no difference between RS/RR patients treated without RT (71% vs. 77%, P = 0.6744), consistent with RSI being RT-specific (interaction term RSI × RT, P = 0.05). Similarly, in the Erasmus dataset, RT-treated RS patients had an improved 5-year distant metastasis-free survival over RR patients (77% vs. 64%, P = 0.0409), but no difference was observed in patients treated without RT (RS vs. RR, 80% vs. 81%, P = 0.9425). Multivariable analysis showed RSI is the strongest variable in RT-treated patients (Karolinska, HR = 5.53, P = 0.0987, Erasmus, HR = 1.64, P = 0.0758) and in backward selection (removal ? of 0.10), RSI was the only variable remaining in the final model. Finally, RSI is an independent predictor of outcome in RT-treated ER(+) patients (Erasmus, multivariable analysis, HR = 2.64, P = 0.0085). CONCLUSIONS:RSI is validated in 2 independent breast cancer datasets totaling 503 patients. Including prior data, RSI is validated in 5 independent cohorts (621 patients) and represents, to our knowledge, the most extensively validated molecular signature in radiation oncology.
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Project description:Breast cancer diagnosed during pregnancy (BCP) is a rare and highly challenging disease. To investigate the impact of pregnancy on the biology of breast cancer, we conducted a comparative analysis of a cohort of BCP patients and non-pregnant control patients by integrating gene expression, copy number alterations and whole genome sequencing data. We showed that BCP exhibit unique molecular characteristics including an enrichment of non-silent mutations, a higher frequency of mutations in mucin gene family and an enrichment of mismatch repair deficiency mutational signature. This provides important insights into the biology of BCP and suggests that these features may be implicated in promoting tumor progression during pregnancy. In addition, it provides an unprecedented resource for further understanding the biology of breast cancer in young women and how pregnancy could modulate tumor biology.
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Project description:Pregnancy is associated with a transient increase in risk for breast cancer. However, the mechanism underlying pregnancy-associated breast cancer (PABC) is poorly understood. Here, we identify the protease pappalysin-1 (PAPP-A) as a pregnancy-dependent oncogene. Transgenic expression of PAPP-A in the mouse mammary gland during pregnancy and involution promotes the deposition of collagen. We demonstrate that collagen facilitates the proteolysis of IGFBP-4 and IGFBP-5 by PAPP-A, resulting in increased proliferative signaling during gestation and a delayed involution. However, while studying the effect of lactation, we found that although PAPP-A transgenic mice lactating for an extended period of time do not develop mammary tumors, those that lactate for a short period develop mammary tumors characterized by a tumor-associated collagen signature (TACS-3). Mechanistically, we found that the protective effect of lactation is associated with the expression of inhibitors of PAPP-A, STC1, and STC2. Collectively, these results identify PAPP-A as a pregnancy-dependent oncogene while also showing that extended lactation is protective against PAPP-A-mediated carcinogenesis. Our results offer the first mechanism that explains the link between breast cancer, pregnancy, and breastfeeding.
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Project description:Pregnancy-associated breast cancer (PABC) is diagnosed during pregnancy or within 1 year postpartum, but the unique aspects of its etiology and pathogenesis have not been fully elucidated. This study aimed to ascertain the molecular mechanisms of PABC to facilitate diagnosis and therapeutic development. The Limma package was used to characterize the differentially expressed genes in PABC as compared to non-pregnancy-associated breast cancer (NPABC) and normal breast tissue. A total of 871 dysregulated genes were identified in the PABC versus NPABC groups and 917 in the PABC versus normal groups, with notable differences in the expression of MAGE and CXCL family genes. The dysregulated genes between the PABC and normal groups were mainly associated with signal transduction and immune response, while Kyoto Encyclopedia of Genes and Genomes analysis revealed that the dysregulated genes were enriched in immune-related pathways, including the major histocompatibility complex (MHC) class II protein complex, the type I interferon signaling pathway, regulation of α-β T-cell proliferation, and the T-cell apoptotic process. Through protein-protein interaction network construction, CD44 and BRCA1 were identified as prominent hub genes with differential expression in PABC versus NPABC. Furthermore, a cluster with eleven hub genes was identified in PABC versus normal adjacent tissues, of which the expression of EGFR, IGF1, PTGS2, FGF1, CAV1, and PLCB1 were verified to be differentially expressed in an independent cohort of PABC patients. Notably, IGF1, PTGS2, and FGF1 were demonstrated to be significantly related to patient prognosis. Our study reveals a distinctive gene expression pattern in PABC and suggests that IGF1, PTGS2, and FGF1 might serve as biomarkers for diagnosis and prognosis of PABC.
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Project description:BACKGROUND:Radiation therapy is an indispensable part of various treatment modalities for breast cancer. Specifically, for non-inflammatory locally advanced breast cancer (LABC) patients, preoperative radiotherapy (pRT) is currently indicated as a second line therapy in the event of lack of response to neoadjuvant chemotherapy. Still approximately one third of patients fails to respond favourably to pRT. The aim of this study was to explore molecular mechanisms underlying differential response to radiotherapy (RT) to identify predictive biomarkers and potential targets for increasing radiosensitivity. METHODS:The study was based on a cohort of 134 LABC patients, treated at the Institute of Oncology and Radiology of Serbia (IORS) with pRT, without previous or concomitant systemic therapy. Baseline transcriptional profiles were established using Agilent 60 K microarray platform in a subset of 23 formalin-fixed paraffin-embedded (FFPE) LABC tumour samples of which 11 radiotherapy naïve and 3 post-radiotherapy samples passed quality control and were used for downstream analysis. Biological networks and signalling pathways underlying differential response to RT were identified using Ingenuity Pathways Analysis software. Predictive value of candidate genes in the preoperative setting was further validated by qRT-PCR in an independent subset of 60 LABC samples of which 42 had sufficient quality for data analysis, and in postoperative setting using microarray data from 344 node-negative breast cancer patients (Erasmus cohort, GSE2034 and GSE5327) treated either with surgery only (20%) or surgery with RT (80%). RESULTS:We identified 192 significantly differentially expressed genes (FDR < 0.10) between pRT-responsive and non-responsive tumours, related to regulation of cellular development, growth and proliferation, cell cycle control of chromosomal replication, glucose metabolism and NAD biosynthesis II route. APOA1, MAP3K4, and MMP14 genes were differentially expressed (FDR < 0.20) between pRT responders and non-responders in preoperative setting, while MAP3K4 was further validated as RT-specific predictive biomarker of distant metastasis free survival (HR = 2.54, [95%CI:1.42-4.55], p = 0.002) in the postoperative setting. CONCLUSIONS:This study pinpoints MAP3K4 as a putative biomarker of response to RT in both preoperative and postoperative settings and a potential target for radiosensitising combination therapy, warranting further pre-clinical studies and prospective clinical validation.
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