Fibroblast-derived matrix models desmoplastic properties and forms a prognostic signature in cancer progression

Abstract

The desmoplastic reaction observed in many cancers is a hallmark of disease progression and prognosis, particularly in breast and pancreatic cancer. Stromal-derived extracellular matrix (ECM) is significantly altered in desmoplasia, and as such plays a critical role in driving cancer progression. Using fibroblast-derived matrices (FDMs), we show that cancer cells have increased growth on cancer associated FDMs, when compared to FDMs derived from non-malignant tissue (normal) fibroblasts. We assess the changes in ECM characteristics from normal to cancer-associated stroma at the primary tumor site. Compositional, structural, and mechanical analyses reveal significant differences, with an increase in abundance of core ECM proteins, coupled with an increase in stiffness and density in cancer-associated FDMs. From compositional changes of FDM, we derived a 36-ECM protein signature, which we show matches in large part with the changes in pancreatic ductal adenocarcinoma (PDAC) tumor and metastases progression. Additionally, this signature also matches at the transcriptomic level in multiple cancer types in patients, prognostic of their survival. Together, our results show relevance of FDMs for cancer modelling and identification of desmoplastic ECM components for further mechanistic studies.

Keywords: breast cancer; desmoplasia; extracellular matrix; fibroblasts; mechanics; models; pancreatic cancer.

Figure 1

CAF FDM promotes breast and pancreatic cancer cells proliferation. (A) Representative images of 4T1-H2B-GFP breast cancer and KPCmT4-zsGreen pancreatic cancer cells on plastic, mNF1, and mCAF1 FDMs. Day 3 post-seeding in 2% FBS DMEM. Staining with phalloidin (F-actin) and DAPI (nuclei). (B) Adhesion (1 hour) and proliferation (1-5 days) of 4T1-H2B-GFP and KPCmT4-zsGreen cells seeded on plastic, mNF1, mCAF1 FDMs. Normalized or raw cell count based on DAPI and GFP. n=3 repeats. One-way ANOVA test. ns, p-value > 0.05; ***p-value < 0.001, ****p-value < 0.0001. Scale bars 100 μm.

Figure 2

CAF FDM is compositionally and structurally different from NF FDM. (A) Volcano plot showing ECM composition difference between mCAF1 vs mNF1 FDMs. n= 3 samples per condition. (B) Validation of mCAF1 vs mNF1 upregulated proteins (Per - periostin, ColIV - collagen IV, Col XII - -collagen XII) by immunofluorescent staining of FDMs. (C) Validation of mCAF1 vs mNF1 upregulated proteins (ColXII, ColXIV - collagen XIV, LOX - lysyl oxidase) by western blotting.(D) Representative images of mNF1 and mCAF1 FDMs imaged by second harmonic generation (SHG). Maximum intensity projection and y-z projection. (E) mNF1 and mCAF1 FDMs density (based on single plane analysis). n= 3 repeats. (F) mNF1 and mCAF1 FDMs thickness (based in y-z projection analysis). n=3 repeats. (G) mNF1 and mCAF1 FDMs stiffness based on the atomic force microscopy measurements. n = 5-7 matrices. Unpaired t-test- ****p-value <0.0001. Scale bars 100 um, except z-axis images with 10um scale bar.

Figure 3

Mammary CAFs deposit compositionally complex matrix reflecting desmoplastic changes in primary and metastatic pancreatic cancer. (A) Scheme of the mass spectrometry samples generation for mNF1, mCAF1 FDMs dataset and PDAC dataset, including healthy age-matched tissues and tumors, spontaneous liver metastases from PanIN to PDAC stages and healthy livers age-matched with experimental KPC liver metastases. (B) Venn diagram showing an overlap in robustly detected proteins between the datasets. Color-coding is used for depicting matrisome categories (Core matrisome: blue – Collagens, red – Glycoproteins, green – Proteoglycans; Matrisome-associated: dark violet – ECM-affiliated, black – ECM regulators, dark blue – Secreted factors). (C) Heatmap of the ECM proteins’ fold changes significantly upregulated (p < 0.05), cutoff logFC >1.59 in mCAF1 vs mNF1 FDMs, compared to the PDAC dataset (tumor conditions vs healthy ones). n=3 samples per group. Grey colored are non-detected proteins. PanIN – pancreatic intraepithelial neoplasia, transition to tumor; Pancreatic tumor presented from the early group. In bold are highlighted genes of the short signature - matched to increasing with progression in the in vivo dataset.

Figure 4

Full CAF FDM signature is enriched in multiple cancer types in human and is prognostic of cancer patients’ survival. (A) Difference in the signature expression score (box plots summarize median with min and max). Circles mark cancer types for which high expression of the signature defines poor survival, shown in b (based on TGCA dataset). (B) Kaplan-Meier plots of cancer types which show significantly different probability of patients’ survival based on the signature expression. LAML, Acute Myeloid Leukemia; ACC, Adrenocortical carcinoma; BLCA, Bladder Urothelial Carcinoma; LGG, Brain Lower Grade Glioma; BRCA, Breast invasive carcinoma; CESC, Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL, Cholangiocarcinoma; COAD, Colon adenocarcinoma; ESCA, Esophageal carcinoma; GBM, Glioblastoma multiforme; HNSC, Head and Neck squamous cell carcinoma; KICH, Kidney Chromophobe; KIRC, Kidney renal clear cell carcinoma; KIRP, Kidney renal papillary cell carcinoma; LIHC, Liver hepatocellular carcinoma; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma; DLBC, Lymphoid Neoplasm Diffuse Large B-cell Lymphoma; MESO, Mesothelioma; OV, Ovarian serous cystadenocarcinoma; PAAD, Pancreatic adenocarcinoma; PCPG, Pheochromocytoma and Paraganglioma; PRAD, Prostate adenocarcinoma; READ, Rectum adenocarcinoma; SARC, Sarcoma; SKCM, Skin Cutaneous Melanoma; STAD, Stomach adenocarcinoma; TGCT, Testicular Germ Cell Tumors; THYM, Thymoma; THCA, Thyroid carcinoma; UCS, Uterine Carcinosarcoma; UCEC, Uterine Corpus Endometrial Carcinoma; UVM, Uveal Melanoma.