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<p>The current study reports the design and development of a compact photoacoustic (PA) sensor for label‑free detection of collagen degradation, a key hallmark of tumor-associated matrix remodeling. The performance of the sensor was evaluated using human type I collagen subjected to controlled enzymatic digestion upon collagenase‑A and collagenase type‑II treatment, to mimic different stages of degraded collagen (intact, mild, and extensive degradation states), and recording corresponding PA spectra. The analyses of the PA spectra revealed treatment-dependent spectral differences with progressively increased signal strengths from control to collagenase‑A and collagenase type‑II treated samples. Intact collagen exhibited comparatively weaker PA responses, whereas collagenase-treated samples demonstrated altered signal amplitudes consistent with enzymatic disruption of collagen structure. A Light Gradient Boosting Machine-based analysis of the PA spectra showed a classification accuracy of ~ 98% within the experimental conditions evaluated in this study. Further, UV-Visible, fluorescence spectroscopy, dynamic light scattering, and scanning electron microscopy experiments demonstrated a change in absorption intensity, shift in emission maxima, gradual decrease in hydrodynamic size, and surface morphology, respectively, supporting progressive collagen degradation. To obtain an initial indication of probe performance in complex biological environments, preliminary PA measurements were also performed in freshly excised murine colon, pancreas, and spleen, revealing tissue-dependent spectral variations and partial clustering through multivariate analysis. Collectively, these findings support the potential applicability of the PA sensor as a label-free analytical platform for monitoring collagen remodeling and related extracellular-matrix alterations.</p>

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Assessing collagenase-a and type-II mediated degradation of human type-I collagen by photoacoustic spectroscopy toward clinical translation in cancer progression

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Shimul Biswas,
  • Subhash Chandra,
  • Ganesh Bhat,
  • Stanley Mathew,
  • Thokur Sreepathy Murali,
  • Krishna Kishore Mahato

摘要

The current study reports the design and development of a compact photoacoustic (PA) sensor for label‑free detection of collagen degradation, a key hallmark of tumor-associated matrix remodeling. The performance of the sensor was evaluated using human type I collagen subjected to controlled enzymatic digestion upon collagenase‑A and collagenase type‑II treatment, to mimic different stages of degraded collagen (intact, mild, and extensive degradation states), and recording corresponding PA spectra. The analyses of the PA spectra revealed treatment-dependent spectral differences with progressively increased signal strengths from control to collagenase‑A and collagenase type‑II treated samples. Intact collagen exhibited comparatively weaker PA responses, whereas collagenase-treated samples demonstrated altered signal amplitudes consistent with enzymatic disruption of collagen structure. A Light Gradient Boosting Machine-based analysis of the PA spectra showed a classification accuracy of ~ 98% within the experimental conditions evaluated in this study. Further, UV-Visible, fluorescence spectroscopy, dynamic light scattering, and scanning electron microscopy experiments demonstrated a change in absorption intensity, shift in emission maxima, gradual decrease in hydrodynamic size, and surface morphology, respectively, supporting progressive collagen degradation. To obtain an initial indication of probe performance in complex biological environments, preliminary PA measurements were also performed in freshly excised murine colon, pancreas, and spleen, revealing tissue-dependent spectral variations and partial clustering through multivariate analysis. Collectively, these findings support the potential applicability of the PA sensor as a label-free analytical platform for monitoring collagen remodeling and related extracellular-matrix alterations.