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Molecular Profiling of Inflammatory and Myofibroblast Cancer-Associated Fibroblast Subtypes Derived from Human

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Cancer-associated fibroblasts (CAFs) are diverse. Raman spectroscopy distinguishes CAF subtypes in pancreatic cancer by their unique chemical signatures, aiding research and therapy.

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Area of Science:

  • Oncology
  • Biochemistry
  • Spectroscopy

Background:

  • Cancer-associated fibroblasts (CAFs) are key components of the pancreatic tumor microenvironment.
  • CAF heterogeneity and plasticity are significant, making subtype differentiation crucial for understanding pancreatic tumorigenesis.
  • Developing non-invasive methods to distinguish CAFs from normal fibroblasts is vital for therapeutic advancements.

Purpose of the Study:

  • To chemically characterize and differentiate between human primary pancreas stellate cells (HPaSCs), inflammatory CAFs (iCAFs), and myofibroblastic CAFs (myCAFs) using Raman spectroscopy.
  • To establish a label-free analytical method for molecular profiling of CAF subpopulations.
  • To validate Raman spectroscopy findings with transcriptomic and lipidomic analyses.

Main Methods:

  • Utilized Raman spectroscopy for label-free chemical characterization and molecular profiling of HPaSCs, iCAFs, and myCAFs.
  • Performed transcriptomic and lipidomic analyses to validate Raman spectroscopy data.
  • Applied multivariate spectral analyses, including partial least squares discriminant analysis (PLS-DA), for subtype classification.

Main Results:

  • Successfully differentiated between HPaSC, iCAF, and myCAF subtypes based on their intrinsic chemical signatures.
  • Demonstrated that Raman spectroscopy provides distinct molecular profiles for each fibroblastic subtype.
  • Achieved 95% accuracy in CAF subtype classification using multivariate spectral analysis and PLS-DA.

Conclusions:

  • CAF subpopulations possess unique intrinsic molecular signatures that can be quantitatively distinguished using Raman spectroscopy.
  • Label-free Raman spectroscopy offers a promising approach for identifying and characterizing CAFs without the need for fluorescence or specific biomarkers.
  • This methodology holds potential for advancing pancreatic cancer research and the development of targeted therapies.