Tumor Evolution Inferred by Patterns of microRNA Expression through the Course of Disease, Therapy, and Recurrence in Breast Cancer

Breast cancer is the most common solid malignancy diagnosed in females worldwide, and approximately 70% of these tumors express estrogen receptor α (ERα), the main biomarker of endocrine therapy. Unfortunately, despite the use of long-term anti-hormone adjuvant treatment, which has significantly reduced patient mortality, resistance to the endocrine treatments often develops, leading to disease recurrence and limiting clinical benefits. Emerging evidence indicates that extracellular vesicles (EVs), nanosized particles that are released by all cell types and responsible for local and systemic intercellular communications, might represent a newly identified mechanism underlying endocrine resistance. Unraveling the role of EVs, released by transformed cells during the tumor evolution under endocrine therapy, is still an open question in the cancer research area and the molecular mechanisms involved should be better defined to discover alternative therapeutic approaches to overcome resistance. In this review, we will provide an overview of recent findings on the involvement of EVs in sustaining hormonal resistance in breast cancer and discuss opportunities for their potential use as biomarkers to monitor the therapeutic response and disease progression.

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MicroRNA expression signatures for the prediction of BRCA1/2 mutation-associated hereditary breast cancer in paraffin-embedded formalin-fixed breast tumors

International Journal of Cancer ◽

10.1002/ijc.29021 ◽

2014 ◽

pp. n/a-n/a ◽

Cited By ~ 4

Author(s):

Miljana Tanic ◽

Kira Yanowski ◽

Gonzalo Gómez-López ◽

María Socorro Rodriguez-Pinilla ◽

Iván Marquez-Rodas ◽

...

Keyword(s):

Breast Cancer ◽

Hereditary Breast Cancer ◽

Breast Tumors ◽

Microrna Expression ◽

Formalin Fixed

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Loss of HER2 Positivity after Trastuzumab in HER2-Positive Gastric Cancer: Is Change in HER2 Status Significantly Frequent?

Case Reports in Gastrointestinal Medicine ◽

10.1155/2015/132030 ◽

2015 ◽

Vol 2015 ◽

pp. 1-6 ◽

Cited By ~ 3

Author(s):

Yu Ishimine ◽

Akira Goto ◽

Yoshito Watanabe ◽

Hidetaka Yajima ◽

Suguru Nakagaki ◽

...

Keyword(s):

Breast Cancer ◽

Gastric Cancer ◽

Residual Tumor ◽

Her2 Status ◽

Resected Specimen ◽

Her2 Positive ◽

Curative Intent ◽

Course Of Disease ◽

Trastuzumab Therapy ◽

Her2 Positivity

Trastuzumab has recently been introduced as a treatment for HER2-positive metastatic and/or unresectable gastric cancer (MUGC); however, compared with breast cancer, some issues concerning HER2 and trastuzumab therapy for gastric cancer remain unclear. A 74-year-old woman received trastuzumab-containing chemotherapy for HER2-positive MUGC. She had a marked response to 8 months of chemotherapy, and gastrectomy and hepatic metastasectomy with curative intent were performed. The resected specimen showed complete loss of HER2 positivity in the residual tumor. For MUGC, a change in HER2 status during the course of the disease with or without chemotherapy has rarely been reported. However, in breast cancer, a significant frequency of change in HER2 status during the course of disease has been reported, and reevaluation of HER2 positivity in metastatic/recurrent sites is recommended. The choice of trastuzumab for MUGC is currently based on the HER2 status of the primary tumor at the time of initial diagnosis, without reassessment of HER2 status during the course of disease and/or in metastatic/recurrent sites, on the assumption that HER2 status is stable. However, our case casts doubt on the stability of HER2 in gastric cancer.

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Altered MicroRNA Expression Confined to Specific Epithelial Cell Subpopulations in Breast Cancer

Cancer Research ◽

10.1158/0008-5472.can-07-5019 ◽

2007 ◽

Vol 67 (24) ◽

pp. 11612-11620 ◽

Cited By ~ 396

Author(s):

L. F. Sempere ◽

M. Christensen ◽

A. Silahtaroglu ◽

M. Bak ◽

C. V. Heath ◽

...

Keyword(s):

Breast Cancer ◽

Epithelial Cell ◽

Microrna Expression ◽

Cell Subpopulations

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Breast cancer ER, PR, and HER2 expression variance by germline cancer predisposition genes.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.10526 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 10526-10526

Author(s):

Grace Wei ◽

Marilin Rosa ◽

Maxine Chang ◽

Brian J. Czerniecki ◽

Xia Wang

Keyword(s):

Breast Cancer ◽

Cancer Diagnosis ◽

Breast Cancer Diagnosis ◽

Cancer Predisposition ◽

Tumor Evolution ◽

Breast Cancers ◽

Her2 Expression ◽

Expression Levels ◽

Genetic Test Results ◽

Predisposition Genes

10526 Background: The association between breast cancer characteristics and survival with estrogen receptor (ER) and progesterone receptor (PR) expression has been primarily studied via binomial categories, ER-positive and ER-negative. In order to better characterize germline genetic influences on these markers, we investigated their IHC expression semi-quantitatively in cancer predisposition germline pathogenic variant (PV) carriers of the following genes: BRCA1, BRCA2, PALB2, TP53, PTEN, CDH1, ATM, CHEK2, and Lynch syndrome genes. The HER2 expression was also analyzed. Methods: We conducted a retrospective chart review of patients with germline panel genetic testing for cancer predisposition genes at Moffitt Cancer Center’s GeneHome clinic. Inclusion criteria included 1) women ≥18 years old, 2) breast cancer diagnosis, 3) cancer predisposition germline panel genetic test results, 4) available ER and PR expression levels, and 5) available HER expression and/or amplification status. ER, PR, and HER2 status were compared between PV carriers and non-PV carriers via Mann-Whitney U at p>0.05. Results: A total of 847 cases were reviewed for the study. Among 658 patients with a breast cancer diagnosis and complete ER PR data, 365 cases (55.5%) were non-PV carriers and 293 cases (44.5%) carried a PV in at least one of the genes listed above. Among 635 cases with available HER2 expression/amplification status, 355 (55.9%) cases were non-PV carriers and 288 (45.4%) cases were PV-carriers. When compared with non-PV carrier controls, BRCA1 PV carriers’ breast tumors had significantly lower ER and/or PR expression. Further, BRCA2 and TP53 PV tumors also displayed moderately lower ER expression. Contrarily, CHEK2 tumors displayed higher ER and PR expression compared to controls. Further, BRCA1 and BRCA2 PV carriers were more likely to have HER2- breast cancers. Conclusions: Differences in ER, PR, HER2 expression levels were observed in germline PV carrier breast cancers, signaling differential impacts by germline PVs on the tumor evolution process. It is likely that tumor differences in PV carriers influence responses to therapies, including hormone therapy, anti-HER2 therapy, and subsequent survival.[Table: see text]

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Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support a Linear Evolutionary Model of Breast Cancer

10.1101/667303 ◽

2019 ◽

Author(s):

Runpu Chen ◽

Steve Goodison ◽

Yijun Sun

Keyword(s):

Breast Cancer ◽

Cancer Progression ◽

Evolutionary Model ◽

Metastatic Tumor ◽

Cancer Diagnostics ◽

Tumor Evolution ◽

Paired Data ◽

Cancer Subtypes ◽

Cancer Data ◽

Progression Model

AbstractThe interpretation of accumulating genomic data with respect to tumor evolution and cancer progression requires integrated models. We developed a computational approach that enables the construction of disease progression models using static sample data. Application to breast cancer data revealed a linear, branching evolutionary model with two distinct trajectories for malignant progression. Here, we used the progression model as a foundation to investigate the relationships between matched primary and metastasis breast tumor samples. Mapping paired data onto the model confirmed that molecular breast cancer subtypes can shift during progression, and supported directional tumor evolution through luminal subtypes to increasingly malignant states. Cancer progression modeling through the analysis of available static samples represents a promising breakthrough. Further refinement of a roadmap of breast cancer progression will facilitate the development of improved cancer diagnostics, prognostics and targeted therapeutics.

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