Login / Signup

AFM assessing of nanomechanical fingerprints for cancer early diagnosis and classification: from single cell to tissue level.

Andreas StylianouMalgorzata LekkaTriantafyllos Stylianopoulos
Published in: Nanoscale (2018)
Cancer development and progression are closely associated with changes both in the mechano-cellular phenotype of cancer and stromal cells and in the extracellular matrix (ECM) structure, composition, and mechanics. In this paper, we review the use of atomic force microscopy (AFM) as a tool for assessing the nanomechanical fingerprints of solid tumors, so as to be potentially used as a diagnostic biomarker for more accurate identification and early cancer grading/classification. The development of such a methodology is expected to provide new insights and a novel approach for cancer diagnosis. We propose that AFM measurements could be employed to complement standard biopsy procedures, offering an objective, novel and quantitative diagnostic approach with the properties of a blind assay, allowing unbiased evaluation of the sample.
Keyphrases
  • atomic force microscopy
  • papillary thyroid
  • squamous cell
  • extracellular matrix
  • high speed
  • single cell
  • machine learning
  • squamous cell carcinoma
  • high resolution
  • deep learning
  • childhood cancer
  • mass spectrometry