Abstract
Lung cancer leads to a series of physiological abnormalities. The remodeling of extracellular matrix (especially elastin and collagen fibers) has been drawing increasing attention as it is suggested to be a hallmark of tumorigenesis. However, the interaction between these crucial matrix components, together with their relationship to mechanical changes, remains poorly understood. Here, we develop a quantitative multiphoton microscopy system to elucidate the relationship between tissue stiffening and elastin-collagen interplay in lung cancer. Based on label-free images of both fibers, we establish a metric termed resemblance metric (RM) to characterize their interaction by quantifying the similarity of their morpho-structural distributions. Specifically, RM is found to increase with lung tumorigenesis, and exhibits superior sensitivity in identifying human lung cancer through ex vivo quantitative imaging. Nanoindentation results suggest a strong correlation between tissue stiffness and inter-channel interaction, notably greater than that between stiffness and any individual morpho-structural feature of either fiber type. Finally, the translational potential of RM-based imaging is demonstrated through tumor boundary identification via in vivo imaging within a mouse model harboring human lung cancer.
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Data availability
All data supporting the findings of this study are available within the paper and its Supplementary Information. The source data that make up all graphs in the paper are shown in Supplementary Data 1. The source data for animal tumor experiments are provided in Supplementary Data 2. Any further data that support the findings of this study are available from the corresponding authors upon reasonable request.
Code availability
Custom MATLAB (R2023a) source code including illustrative example data for the calculation of RM has been deposited on GitHub (https://github.com/dukeotter/Resemblance_Index_Demo_Availability), and on the Zenodo platform65.
References
Bray, F. et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 74, 229–263 (2024).
De Zuani, M. et al. Single-cell and spatial transcriptomics analysis of non-small cell lung cancer. Nat. Commun. 15, 4388 (2024).
Tomic, K., Krpina, K., Baticic, L., Samarzija, M. & Vranic, S. Comprehensive molecular and clinical insights into non-small cell lung cancer transformation to small cell lung cancer with an illustrative case report. J. Drug Target. 32, 499–509 (2024).
Perez-Moreno, P., Brambilla, E., Thomas, R. & Soria, J. C. Squamous cell carcinoma of the lung: molecular subtypes and therapeutic opportunities. Clin. Cancer Res. 18, 2443–2451 (2012).
Herbst, R. S., Morgensztern, D. & Boshoff, C. The biology and management of non-small cell lung cancer. Nature 553, 446–454 (2018).
Wang, M. N., Herbst, R. S. & Boshoff, C. Toward personalized treatment approaches for non-small-cell lung cancer. Nat. Med. 27, 1345–1356 (2021).
Megyesfalvi, Z. et al. Clinical insights into small cell lung cancer: tumor heterogeneity, diagnosis, therapy, and future directions. CA Cancer J. Clin. 73, 620–652 (2023).
Woodard, G. A., Jones, K. D. & Jablons, D. M. Lung Cancer Staging and Prognosis in Lung Cancer: Treatment and Research (ed. Reckamp, K. L.) 47–75 (Springer International Publishing, 2016).
Zappa, C. & Mousa, S. A. Non-small cell lung cancer: current treatment and future advances. Transl. Lung Cancer Res. 5, 288–300 (2016).
Tsim, S., O’Dowd, C. A., Milroy, R. & Davidson, S. Staging of non-small cell lung cancer (NSCLC): a review. Respir. Med. 104, 1767–1774 (2010).
Wieder, T., Eigentler, T., Brenner, E. & Röcken, M. Immune checkpoint blockade therapy. J. Allergy Clin. Immunol. 142, 1403–1414 (2018).
Grupp, S. A. & June, C. H. Adoptive cellular therapy. Curr. Top. Microbiol. 344, 149–172 (2011).
Fukuhara, H., Ino, Y. & Todo, T. Oncolytic virus therapy: a new era of cancer treatment at dawn. Cancer Sci. 107, 1373–1379 (2016).
Melief, C. J. M., van Hall, T., Arens, R., Ossendorp, F. & van der Burg, S. H. Therapeutic cancer vaccines. J. Clin. Investig. 125, 3401–3412 (2015).
Rahbari, N. N. et al. Anti-VEGF therapy induces ECM remodeling and mechanical barriers to therapy in colorectal cancer liver metastases. Sci. Transl. Med. 8, 360ra135 (2016).
Humphrey, J. D., Dufresne, E. R. & Schwartz, M. A. Mechanotransduction and extracellular matrix homeostasis. Nat. Rev. Mol. Cell Bio. 15, 802–812 (2014).
Huang, J. et al. Extracellular matrix and its therapeutic potential for cancer treatment. Signal Transduct. Target. Ther. 6, 153 (2021).
Levental, K. R. et al. Matrix crosslinking forces tumor progression by enhancing integrin signaling. Cell 139, 891–906 (2009).
Navab, R. et al. Integrin α11β1 regulates cancer stromal stiffness and promotes tumorigenicity and metastasis in non-small cell lung cancer. Oncogene 35, 1899–1908 (2016).
Buehler, M. J. Nature designs tough collagen: explaining the nanostructure of collagen fibrils. Proc. Natl. Acad. Sci. USA 103, 12285–12290 (2006).
Meng, J. et al. Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning. J. Biomed. Opt. 28, 045001 (2023).
Lu, P. F., Weaver, V. M. & Werb, Z. The extracellular matrix: a dynamic niche in cancer progression. J. Cell Biol. 196, 395–406 (2012).
Cox, T. R. & Erler, J. T. Remodeling and homeostasis of the extracellular matrix: implications for fibrotic diseases and cancer. Dis. Model. Mech. 4, 165–178 (2011).
Peinado, H. et al. Lysyl oxidase-like 2 as a new poor prognosis marker of squamous cell carcinomas. Cancer Res. 68, 4541–4550 (2008).
Wang, Y., Song, E. C. & Resnick, M. B. Elastin in the Tumor Microenvironment in Tumor Microenvironment : Extracellular Matrix Components – Part B (ed. Birbrair, A.) 1–16 (Springer International Publishing, 2020).
Xu, S. et al. The role of collagen in cancer: from bench to bedside. J. Transl. Med. 17, 309 (2019).
Conklin, M. W. et al. Aligned collagen is a prognostic signature for survival in human breast carcinoma. Am. J. Pathol. 178, 1221–1232 (2011).
Xi, G. Q. et al. Large-scale tumor-associated collagen signatures identify high-risk breast cancer patients. Theranostics 11, 3229–3243 (2021).
Stylianou, A., Voutouri, C., Mpekris, F. & Stylianopoulos, T. Pancreatic cancer presents distinct nanomechanical properties during progression. Ann. Biomed. Eng. 51, 1602–1615 (2023).
Chen, J. et al. Optical characterization of lesions and identification of surgical margins in pancreatic metastasis from renal cell carcinoma by using two-photon excited fluorescence microscopy. Laser Phys. 24, 115603 (2014).
Burns-Cox, N., Avery, N. C., Gingell, J. C. & Bailey, A. J. Changes in collagen metabolism in prostate cancer: a host response that may alter progression. J. Urol. 166, 1698–1701 (2001).
Garcia, A. M. et al. Second harmonic generation imaging of the collagen architecture in prostate cancer tissue. Biomed. Phys. Eng. Express 4, 025026 (2018).
Birk, J. W. et al. Second harmonic generation imaging distinguishes both high-grade dysplasia and cancer from normal colonic mucosa. Dig. Dis. Sci. 59, 1529–1534 (2014).
Cox, T. R. et al. LOX-mediated collagen crosslinking is responsible for fibrosis-enhanced metastasis. Cancer Res. 73, 1721–1732 (2013).
Thomas, P. et al. VATS is an adequate oncological operation for stage I non-small cell lung cancer. Eur. J. Cardio Thorac. 21, 1094–1099 (2002).
Ma, J. L. et al. Robot-assisted thoracic surgery versus video-assisted thoracic surgery for lung lobectomy or segmentectomy in patients with non-small cell lung cancer: a meta-analysis. BMC Cancer 21, 498 (2021).
Wallace, M. B. et al. Minimally invasive endoscopic staging of suspected lung cancer. J. Am. Med. Assoc. 299, 540–546 (2008).
Gu, B. H., Madison, M. C., Corry, D. & Kheradmand, F. Matrix remodeling in chronic lung diseases. Matrix Biol. 73, 52–63 (2018).
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).
Gan, Z. et al. Vimentin intermediate filaments template microtubule networks to enhance persistence in cell polarity and directed migration. Cell Syst. 3, 252–263 (2016).
McDonald, S., Saslow, D. & Alciati, M. H. Performance and reporting of clinical breast examination: a review of the literature. CA Cancer J. Clin. 54, 345–361 (2004).
Butcher, D. T., Alliston, T. & Weaver, V. M. A tense situation: forcing tumour progression. Nat. Rev. Cancer 9, 108–122 (2009).
Provenzano, P. P. et al. Collagen density promotes mammary tumor initiation and progression. BMC Med. 6, 11 (2008).
Pankova, D. et al. RASSF1A controls tissue stiffness and cancer stem-like cells in lung adenocarcinoma. EMBO J. 38, e100532 (2019).
Pinheiro, L. C. L. et al. Deposition of collagen III and alterations in basement membrane integrity as candidate prognostic markers in prostate cancer. Exp. Cell Res. 439, 114077 (2024).
Deng, B. et al. Biological role of matrix stiffness in tumor growth and treatment. J. Transl. Med. 20, 540 (2022).
Cross, S. E., Jin, Y. S., Rao, J. & Gimzewski, J. K. Nanomechanical analysis of cells from cancer patients. Nat. Nanotechnol. 2, 780–783 (2007).
Kwon, S., Yang, W., Moon, D. & Kim, K. S. Comparison of cancer cell elasticity by cell type. J. Cancer 11, 5403–5412 (2020).
Jiang, Y. F. et al. Targeting extracellular matrix stiffness and mechanotransducers to improve cancer therapy. J. Hematol. Oncol. 15, 34 (2022).
Piersma, B., Hayward, M. K. & Weaver, V. M. Fibrosis and cancer: a strained relationship. Bba Rev. Cancer 1873, 188356 (2020).
Shukla, V. C., Higuita-Castro, N., Nana-Sinkam, P. & Ghadiali, S. N. Substrate stiffness modulates lung cancer cell migration but not epithelial to mesenchymal transition. J. Biomed. Mater. Res. A 104, 1182–1193 (2016).
Vallet, S. D. & Ricard-Blum, S. Lysyl oxidases: from enzyme activity to extracellular matrix cross-links. Extracell. Matrix 63, 349–364 (2019).
Gao, Y. J. et al. LKB1 inhibits lung cancer progression through lysyl oxidase and extracellular matrix remodeling. Proc. Natl. Acad. Sci. USA 107, 18892–18897 (2010).
Liu, J., Ping, W., Zu, Y. K. & Sun, W. Correlations of lysyl oxidase with MMP2/MMP9 expression and its prognostic value in non-small cell lung cancer. Int. J. Clin. Exp. Pathol. 7, 6040–6047 (2014).
Fischer, F. et al. Assessing the risk of skin damage due to femtosecond laser irradiation. J. Biophotonics 1, 470–477 (2008).
Justilien, V. & Fields, A. P. Utility and applications of orthotopic models of human non-small cell lung cancer (NSCLC) for the evaluation of novel and emerging cancer therapeutics. Curr. Protoc. Pharmacol. 62, 14.27.11–14.27.17 (2013).
Wilson, A. N., Chen, B., Liu, X., Kurie, J. M. & Kim, J. A method for orthotopic transplantation of lung cancer in mice. Methods Mol. Biol. 2374, 231–242 (2022).
Liu, J. & Johnston, M. R. Animal models for studying lung cancer and evaluating novel intervention strategies. Surg. Oncol. 11, 217–227 (2002).
Qian, S. H. et al. Identification of human ovarian cancer relying on collagen fiber coverage features by quantitative second harmonic generation imaging. Opt. Express 30, 25718–25733 (2022).
Otsu, N. Threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9, 62–66 (1979).
Liu, Z. et al. Rapid three-dimensional quantification of voxel-wise collagen fiber orientation. Biomed. Opt. Express 6, 2294–2310 (2015).
Liu, Z. Y. et al. Automated quantification of three-dimensional organization of fiber-like structures in biological tissues. Biomaterials 116, 34–47 (2017).
Qian, S. H. et al. Mapping organizational changes of fiber-like structures in disease progression by multiparametric, quantitative imaging. Laser Photon. Rev. 16, 2100576 (2022).
Meng, J. et al. Mapping physiological and pathological functions of cortical vasculature through aggregation-induced emission nanoprobes assisted quantitative, in vivo NIR-II imaging. Biomater. Adv. 136, 212760 (2022).
Wang, C. Code used for assessing 3D Resemblance Metric of fiber-like structures [software]. Preprint at Zenodo, https://doi.org/10.5281/zenodo.18948142 (2026).
Acknowledgements
This work was supported by the National Natural Science Foundation of China (62275232 to Z.L., 62375104 to S.Z., 32371411 to X.W., and 62575254 to Z.D.) and the Natural Science Foundation of Zhejiang Province (LZ25F050007 to Z.L.).
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Z.L., S.Z., X.W., Z.D., K.S., and C.W. conceived the idea. C.W., S.Q., L.Z., J.M., and R.J. performed the experiments and imaging. C.W., S.Q., J.M., L.Z., L.C., and B.N. conducted the simulation experiments. C.W., S.Q., L.Z., L.C. and Z.L. performed data analysis with conceptual support from all authors. X.W., W.L., and C.W. conducted the nanoindentation experiments. C.W., Z.L., and S.Q. drafted the main manuscript, with suggestions from all authors. All authors discussed the results and commented on the manuscript.
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Wang, C., Qian, S., Li, W. et al. Interpreting tissue stiffening with lung tumorigenesis by imaging architectural resembling of extracellular matrix components. Commun Biol (2026). https://doi.org/10.1038/s42003-026-10004-6
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DOI: https://doi.org/10.1038/s42003-026-10004-6


