Literature DB >> 32542588

Rapid Cancer Diagnosis and Early Prognosis of Metastatic Risk Based on Mechanical Invasiveness of Sampled Cells.

Y Merkher1, Y Horesh1, Z Abramov1, G Shleifer1, O Ben-Ishay2,3, Y Kluger2,3, D Weihs4.   

Abstract

We provide an innovative, bioengineering, mechanobiology-based approach to rapidly (2-h) establish the in vivo metastatic likelihood of patient tumor-samples, where results are in direct agreement with clinical histopathology and patient outcomes. Cancer-related mortality is mostly due to local recurrence or to metastatic disease, thus early prediction of tumor-cell-fate may critically affect treatment protocols and survival rates. Metastasis and recurrence risks are currently predicted by lymph-node status, tumor size, histopathology and genetic testing, however, these are not infallible and results may require days/weeks. We have previously observed that subpopulations of invasive cancer-cells will rapidly (1-2 h) push into the surface of physiological-stiffness, synthetic polyacrylamide gels, reaching to cell-scale depths, while normal or noninvasive cells do not considerably indent gels. Here, we evaluate the mechanical invasiveness of established breast and pancreatic cell lines and of tumor-cells from fresh, suspected pancreatic cancer tumors. The mechanical invasiveness matches the in vitro metastatic potential in cell lines as determined with Boyden chamber assays. Moreover, the mechanical invasiveness directly agrees with the clinical histopathology in primary-site, pancreatic-tumors. Thus, the rapid, patient-specific, early prediction of metastatic likelihood, on the time-scale of initial resection/biopsy, can directly affect disease management and treatment protocols.

Entities:  

Keywords:  Early prognosis; Mechanobiology; Metastasis prognosis; Pancreatic cancer

Year:  2020        PMID: 32542588     DOI: 10.1007/s10439-020-02547-4

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  2 in total

1.  Breast cancer stem cells: mechanobiology reveals highly invasive cancer cell subpopulations.

Authors:  Martha B Alvarez-Elizondo; Daphne Weihs
Journal:  Cell Mol Life Sci       Date:  2022-02-16       Impact factor: 9.261

Review 2.  Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology.

Authors:  Anum S Kazerouni; Manasa Gadde; Andrea Gardner; David A Hormuth; Angela M Jarrett; Kaitlyn E Johnson; Ernesto A B F Lima; Guillermo Lorenzo; Caleb Phillips; Amy Brock; Thomas E Yankeelov
Journal:  iScience       Date:  2020-11-13
  2 in total

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