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Mechanical phenotyping of breast cancer using MEMS: a method to demarcate benign and cancerous breast tissues.

ABSTRACT: The mechanical properties of tissue change significantly during the progression from healthy to malignant. Quantifying the mechanical properties of breast tissue within the tumor microenvironment can help to delineate benign from cancerous stages. In this work, we study high-grade invasive ductal carcinoma in comparison with their matched tumor adjacent areas, which exhibit benign morphology. Such paired tissue cores obtained from eight patients were indented using a MEMS-based piezoresistive microcantilever, which was positioned within pre-designated epithelial and stromal areas of the specimen. Field emission scanning electron microscopy studies on breast tissue cores were performed to understand the microstructural changes from benign to malignant. The normal epithelial tissues appeared compact and organized. The appearance of cancer regions, in comparison, not only revealed increased cellularity but also showed disorganization and increased fenestration. Using this technique, reliable discrimination between epithelial and stromal regions throughout both benign and cancerous breast tissue cores was obtained. The mechanical profiling generated using this method has the potential to be an objective, reproducible, and quantitative indicator for detecting and characterizing breast cancer.

SUBMITTER: Pandya HJ

PROVIDER: S-EPMC4224189 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Mechanical phenotyping of breast cancer using MEMS: a method to demarcate benign and cancerous breast tissues.

Pandya Hardik J HJ Chen Wenjin W Goodell Lauri A LA Foran David J DJ Desai Jaydev P JP

Lab on a chip 20140930 23

The mechanical properties of tissue change significantly during the progression from healthy to malignant. Quantifying the mechanical properties of breast tissue within the tumor microenvironment can help to delineate benign from cancerous stages. In this work, we study high-grade invasive ductal carcinoma in comparison with their matched tumor adjacent areas, which exhibit benign morphology. Such paired tissue cores obtained from eight patients were indented using a MEMS-based piezoresistive mi ...[more]

PMID: 25267099

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Project description:BackgroundTechnologies for quick and label-free diagnosis of malignancies from breast tissues have the potential to be a significant adjunct to routine diagnostics. The biophysical phenotypes of breast tissues, such as its electrical, thermal, and mechanical properties (ETM), have the potential to serve as novel markers to differentiate between normal, benign, and malignant tissue.ResultsWe report a system-of-biochips (SoB) integrated into a semi-automated mechatronic system that can characterize breast biopsy tissues using electro-thermo-mechanical sensing. The SoB, fabricated on silicon using microfabrication techniques, can measure the electrical impedance (Z), thermal conductivity (K), mechanical stiffness (k), and viscoelastic stress relaxation (%R) of the samples. The key sensing elements of the biochips include interdigitated electrodes, resistance temperature detectors, microheaters, and a micromachined diaphragm with piezoresistive bridges. Multi-modal ETM measurements performed on formalin-fixed tumour and adjacent normal breast biopsy samples from N = 14 subjects were able to differentiate between invasive ductal carcinoma (malignant), fibroadenoma (benign), and adjacent normal (healthy) tissues with a root mean square error of 0.2419 using a Gaussian process classifier. Carcinoma tissues were observed to have the highest mean impedance (110018.8 ± 20293.8 Ω) and stiffness (0.076 ± 0.009 kNm-1) and the lowest thermal conductivity (0.189 ± 0.019 Wm-1 K-1) amongst the three groups, while the fibroadenoma samples had the highest percentage relaxation in normalized load (47.8 ± 5.12%).ConclusionsThe work presents a novel strategy to characterize the multi-modal biophysical phenotype of breast biopsy tissues to aid in cancer diagnosis from small-sized tumour samples. The methodology envisions to supplement the existing technology gap in the analysis of breast tissue samples in the pathology laboratories to aid the diagnostic workflow.

Project description:BackgroundBenign breast disease (BBD) is a risk factor for breast cancer (BC); however, little is known about the genetic alterations present at the time of BBD diagnosis and how these relate to risk of incident BC.MethodsA subset of a long-term BBD cohort was selected to examine DNA variation across three BBD groups (42 future estrogen receptor-positive (ER+) BC, 36 future estrogen receptor-negative (ER-) BC, and 42 controls cancer-free for at least 16 years post-BBD). DNA extracted from archival formalin fixed, paraffin-embedded (FFPE) tissue blocks was analyzed for presence of DNA alterations using a targeted panel of 93 BC-associated genes. To address artifacts frequently observed in FFPE tissues (e.g., C>T changes), we applied three filtering strategies based on alternative allele frequencies and nucleotide substitution context. Gene-level associations were performed using two types of burden tests and adjusted for clinical and technical covariates.ResultsAfter filtering, the variant frequency of SNPs in our sample was highly consistent with population allele frequencies reported in 1 KG/ExAC (0.986, p < 1e-16). The top ten genes found to be nominally associated with later cancer status by four of 12 association methods(p < 0.05) were MED12, MSH2, BRIP1, PMS1, GATA3, MUC16, FAM175A, EXT2, MLH1 and TGFB1, although these were not statistically significant in permutation testing. However, all 10 gene-level associations had OR < 1 with lower mutation burden in controls compared to cases, which was marginally statistically significant in permutation testing (p = 0.04). Comparing between the three case groups, BBD ER+ cases were closer to controls in mutation profile, while BBD ER- cases were distinct. Notably, the variant burden was significantly higher in controls than in either ER+ or ER- cases. CD45 expression was associated with mutational burden (p < 0.001).ConclusionsSomatic mutations were more frequent in benign breast tissue from women who did not develop cancer, opening questions of clonal diversity or immune-mediated restraint on future cancer development. CD45 expression was positively associated with mutational burden, most strongly in controls. Further studies in both normal and premalignant tissues are needed to better understand the role of somatic gene mutations and their contribution to future cancer development.

Dataset Information

Mechanical phenotyping of breast cancer using MEMS: a method to demarcate benign and cancerous breast tissues.

Publications

Mechanical phenotyping of breast cancer using MEMS: a method to demarcate benign and cancerous breast tissues.

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