Preface of the Special Issue on the Role of Extracellular Matrix in Development and Cancer Progression

Galectin-1 promotes gastric cancer peritoneal metastasis through peritoneal fibrosis

BACKGROUND

Peritoneal metastasis is one of the main causes of death in patients with gastric cancer (GC). Galectin-1 regulates various undesirable biological behaviors in GC and may be key in GC peritoneal metastasis.

METHODS

In this study, we elucidated the regulatory role of galectin-1 in GC cell peritoneal metastasis. GC and peritoneal tissues underwent hematoxylin-eosin (HE), immunohistochemical (IHC), and Masson trichrome staining to analyze the difference in galectin-1 expression and peritoneal collagen deposition in different GC clinical stages. The regulatory role of galectin-1 in GC cell adhesion to mesenchymal cells and in collagen expression was determined using HMrSV5 human peritoneal mesothelial cells (HPMCs). Collagen and corresponding mRNA expression were detected with western blotting and reverse transcription PCR, respectively. The promoting effect of galectin-1 on GC peritoneal metastasis was verified in vivo. Collagen deposition and collagen I, collagen III, and fibronectin 1 (FN1) expression in the peritoneum of the animal models were detected by Masson trichrome and IHC staining.

RESULTS

Galectin-1 and collagen deposition in the peritoneal tissues was correlated with GC clinical staging and were positively correlated. Galectin-1 enhanced the ability of GC cells to adhere to the HMrSV5 cells by promoting collagen I, collagen III, and FN1 expression. The in vivo experiments confirmed that galectin-1 promoted GC peritoneal metastasis by promoting peritoneal collagen deposition.

CONCLUSION

Galectin-1-induced peritoneal fibrosis may create a favorable environment for GC cell peritoneal metastasis.

Pipeline for precise insoluble matrisome coverage in tissue extracellular matrices

The extracellular matrix (ECM) is assembled by hundreds of proteins orchestrating tissue patterning and surrounding cell fates via the mechanical-biochemical feedback loop. Aberrant ECM protein production or assembly usually creates pathological niches eliciting lesions that mainly involve fibrogenesis and carcinogenesis. Yet, our current knowledge about the pathophysiological ECM compositions and alterations in healthy or diseased tissues is limited since the methodology for precise insoluble matrisome coverage in the ECM is a "bottleneck." Our current study proposes an enhanced sodium dodecyl sulfonate (E-SDS) workflow for thorough tissue decellularization and an intact pipeline for the accurate identification and quantification of highly insoluble ECM matrisome proteins. We tested this pipeline in nine mouse organs and highlighted the full landscape of insoluble matrisome proteins in the decellularized ECM (dECM) scaffolds. Typical experimental validations and mass spectrometry (MS) analysis confirmed very little contamination of cellular debris remaining in the dECM scaffolds. Our current study will provide a low-cost, simple, reliable, and effective pipeline for tissue insoluble matrisome analysis in the quest to comprehend ECM discovery proteomic studies.

A novel prognostic model based on urea cycle-related gene signature for colorectal cancer

Background

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the world. This study aimed to develop a urea cycle (UC)-related gene signature that provides a theoretical foundation for the prognosis and treatment of patients with CRC.

Methods

Differentially expressed UC-related genes in CRC were confirmed using differential analysis and Venn diagrams. Univariate Cox and least absolute shrinkage and selection operator regression analyses were performed to identify UC-related prognostic genes. A UC-related signature was created and confirmed using distinct datasets. Independent prognostic predictors were authenticated using Cox analysis. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts algorithm and Spearman method were applied to probe the linkage between UC-related prognostic genes and tumor immune-infiltrating cells. The Human Protein Atlas database was used to determine the protein expression levels of prognostic genes in CRC and normal tissues. Verification of the expression levels of UC-related prognostic genes in clinical tissue samples was performed using real-time quantitative polymerase chain reaction (qPCR).

Results

A total of 49 DEUCRGs in CRC were mined. Eight prognostic genes (TIMP1, FABP4, MMP3, MMP1, CD177, CA2, S100P, and SPP1) were identified to construct a UC-related gene signature. The signature was then affirmed using an external validation set. The risk score was demonstrated to be a credible independent prognostic predictor using Cox regression analysis. Functional enrichment analysis revealed that focal adhesion, ECM-receptor interaction, IL-17 signaling pathway, and nitrogen metabolism were associated with the UC-related gene signature. Immune infiltration and correlation analyses revealed a significant correlation between UC-related prognostic genes and differential immune cells between the two risk subgroups. Finally, the qPCR results of clinical samples further confirmed the results of the public database.

Conclusion

Taken together, this study authenticated UC-related prognostic genes and developed a gene signature for the prognosis of CRC, which will be of great significance in the identification of prognostic molecular biomarkers, clinical prognosis prediction, and development of treatment strategies for patients with CRC.