Publications by authors named "Sundus Shalabi"

Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers.

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Pulmonary metastasectomy (PM) is consensually performed in a parenchyma-sparing manner to preserve functionally healthy lung tissue. However, this may increase the risk of local recurrence at the surgical margin. Laser assisted pulmonary metastasectomy (LPM) is a relatively recent innovation that is especially useful to resect multiple metastatic pulmonary nodules.

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Microenvironment signals are potent determinants of cell fate and arbiters of tissue homeostasis, however understanding how different microenvironment factors coordinately regulate cellular phenotype has been experimentally challenging. Here we used a high-throughput microenvironment microarray comprised of 2640 unique pairwise signals to identify factors that support proliferation and maintenance of primary human mammary luminal epithelial cells. Multiple microenvironment factors that modulated luminal cell number were identified, including: HGF, NRG1, BMP2, CXCL1, TGFB1, FGF2, PDGFB, RANKL, WNT3A, SPP1, HA, VTN, and OMD.

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Tissues comprise ordered arrangements of cells that can be surprisingly disordered in their details. How the properties of single cells and their microenvironment contribute to the balance between order and disorder at the tissue-scale remains poorly understood. Here, we address this question using the self-organization of human mammary organoids as a model.

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Women with germline BRCA1 mutations (BRCA1) have increased risk for hereditary breast cancer. Cancer initiation in BRCA1 is associated with premalignant changes in breast epithelium; however, the role of the epithelium-associated stromal niche during BRCA1-driven tumor initiation remains unclear. Here we show that the premalignant stromal niche promotes epithelial proliferation and mutant BRCA1-driven tumorigenesis in trans.

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There is a plethora of recognized risk factors for breast cancer (BC) with poorly understood or speculative biological mechanisms. The lack of prevention options highlights the importance of understanding the mechanistic basis of cancer susceptibility and finding new targets for breast cancer prevention. Until now, we have understood risk and cancer susceptibility primarily through the application of epidemiology and assessing outcomes in large human cohorts.

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During aging in the human mammary gland, luminal epithelial cells lose lineage fidelity by expressing markers normally expressed in myoepithelial cells. We hypothesize that loss of lineage fidelity is a general manifestation of epithelia that are susceptible to cancer initiation. In the present study, we show that histologically normal breast tissue from younger women who are susceptible to breast cancer, as a result of harboring a germline mutation in , or genes, exhibits hallmarks of accelerated aging.

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A robust breast cancer prevention strategy requires risk assessment biomarkers for early detection. We show that expression of , a transcription factor critical for normal mammary development, is downregulated in mammary luminal epithelia with age. DNA methylation of the promoter is negatively correlated with expression in an age-dependent manner.

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Preventing breast cancer before it is able to form is an ideal way to stop breast cancer. However, there are limited existing options for prevention of breast cancer. Changes in the breast tissue resulting from the aging process contribute to breast cancer susceptibility and progression and may therefore provide promising targets for prevention.

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Purpose: Here we aim to review the association between mammographic density, collagen structure and breast cancer risk.

Findings: While mammographic density is a strong predictor of breast cancer risk in populations, studies by Boyd show that mammographic density does not predict breast cancer risk in individuals. Mammographic density is affected by age, parity, menopausal status, race/ethnicity, and body mass index (BMI).

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