The role of network-forming collagens in cancer progression

Understanding the matrix: collagen modifications in tumors and their implications for immunotherapy

Tumors are highly complex and heterogenous ecosystems where malignant cells interact with healthy cells and the surrounding extracellular matrix (ECM). Solid tumors contain large ECM deposits that can constitute up to 60% of the tumor mass. This supports the survival and growth of cancerous cells and plays a critical role in the response to immune therapy. There is untapped potential in targeting the ECM and cell-ECM interactions to improve existing immune therapy and explore novel therapeutic strategies. The most abundant proteins in the ECM are the collagen family. There are 28 different collagen subtypes that can undergo several post-translational modifications (PTMs), which alter both their structure and functionality. Here, we review current knowledge on tumor collagen composition and the consequences of collagen PTMs affecting receptor binding, cell migration and tumor stiffness. Furthermore, we discuss how these alterations impact tumor immune responses and how collagen could be targeted to treat cancer.

Structural abnormality of hepatic glycogen in rat liver with diethylnitrosamine-induced carcinogenic injury

Growing evidence confirms associations between glycogen metabolic re-wiring and the development of liver cancer. Previous studies showed that glycogen structure changes abnormally in liver diseases such as cystic fibrosis, diabetes, etc. However, few studies focus on glycogen molecular structural characteristics during liver cancer development, which is worthy of further exploration. In this study, a rat model with carcinogenic liver injury induced by diethylnitrosamine (DEN) was successfully constructed, and hepatic glycogen structure was characterized. Compared with glycogen structure in the healthy rat liver, glycogen chain length distribution (CLD) shifts towards a short region. In contrast, glycogen particles were mainly present in small-sized β particles in DEN-damaged carcinogenic rat liver. Comparative transcriptomic analysis revealed significant expression changes of genes and pathways involved in carcinogenic liver injury. A combination of transcriptomic analysis, RT-qPCR, and western blot showed that the two genes, Gsy1 encoding glycogen synthase and Gbe1 encoding glycogen branching enzyme, were significantly altered and might be responsible for the structural abnormality of hepatic glycogen in carcinogenic liver injury. Taken together, this study confirmed that carcinogenic liver injury led to structural abnormality of hepatic glycogen, which provided clues to the future development of novel drug targets for potential therapeutics of carcinogenic liver injury.

The collagen landscape in cancer: profiling collagens in tumors and in circulation reveals novel markers of cancer-associated fibroblast subtypes

Cancer-associated fibroblasts (CAFs) deposit and remodel collagens in the tumor stroma, impacting cancer progression and efficacy of interventions. CAFs are the focus of new therapeutics with the aim of normalizing the tumor microenvironment. To do this, a better understanding of CAF heterogeneity and collagen composition in cancer is needed. In this study, we sought to profile the expression of collagens at multiple levels with the goal of identifying cancer biomarkers. We investigated the collagen expression pattern in various cell types and CAF subtypes in a publicly available single-cell RNA sequencing (RNA-seq) dataset of pancreatic ductal adenocarcinoma. Next, we investigated the collagen expression profile in tumor samples across cancer types from The Cancer Genome Atlas (TCGA) database and evaluated if specific patterns of collagen expression were associated with prognosis. Finally, we profiled circulating collagen peptides using a panel of immunoassays to measure collagen fragments in the serum of cancer patients. We found that pancreatic stellate cells and fibroblasts were the primary producers of collagens in the pancreas. COL1A1, COL3A1, COL5A1, COL6A1 were expressed in all CAF subtypes, whereas COL8A1, COL10A1, COL11A1, COL12A1 were specific to myofibroblast CAFs (myCAF) and COL14A1 specific to inflammatory CAFs (iCAF). In TCGA database, myCAF collagens COL10A1 and COL11A1 were elevated across solid tumor types, and multiple associations between high expression and worse survival were found. Finally, circulating collagen biomarkers were elevated in the serum of patients with cancer relative to healthy controls with COL11A1 (myCAF) having the best diagnostic accuracy of the markers measured. In conclusion, CAFs express a noncanonical collagen profile with specific collagen subtypes associated with iCAFs and myCAFs in PDAC. These collagens are deregulated at the cellular, tumor, and systemic levels across different solid tumors and associate with survival. These findings could lead to new discoveries such as novel biomarkers and therapeutic targets. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Construction of an Exudative Age-Related Macular Degeneration Diagnostic and Therapeutic Molecular Network Using Multi-Layer Network Analysis, a Fuzzy Logic Model, and Deep Learning Techniques: Are Retinal and Brain Neurodegenerative Disorders Related?

Neovascular age-related macular degeneration (nAMD) is a leading cause of irreversible visual impairment in the elderly. The current management of nAMD is limited and involves regular intravitreal administration of anti-vascular endothelial growth factor (anti-VEGF). However, the effectiveness of these treatments is limited by overlapping and compensatory pathways leading to unresponsiveness to anti-VEGF treatments in a significant portion of nAMD patients. Therefore, a system view of pathways involved in pathophysiology of nAMD will have significant clinical value. The aim of this study was to identify proteins, miRNAs, long non-coding RNAs (lncRNAs), various metabolites, and single-nucleotide polymorphisms (SNPs) with a significant role in the pathogenesis of nAMD. To accomplish this goal, we conducted a multi-layer network analysis, which identified 30 key genes, six miRNAs, and four lncRNAs. We also found three key metabolites that are common with AMD, Alzheimer's disease (AD) and schizophrenia. Moreover, we identified nine key SNPs and their related genes that are common among AMD, AD, schizophrenia, multiple sclerosis (MS), and Parkinson's disease (PD). Thus, our findings suggest that there exists a connection between nAMD and the aforementioned neurodegenerative disorders. In addition, our study also demonstrates the effectiveness of using artificial intelligence, specifically the LSTM network, a fuzzy logic model, and genetic algorithms, to identify important metabolites in complex metabolic pathways to open new avenues for the design and/or repurposing of drugs for nAMD treatment.

Immunohistochemical Analysis of Lung Adenocarcinoma in Russian Mayak Nuclear Workers

Specimens of lung adenocarcinoma (AdCa) from Russian nuclear workers (n = 54) exposed to alpha particles and gamma rays and from individuals non-exposed to radiation (n = 21) were examined using immunohistochemistry. Estimated significant associations with alpha dose were negative for Ki-67 and collagen IV in AdCa. Associations with gamma-ray dose were negative for tissue inhibitor of matrix metalloproteinase 2 and caspase 3 and positive for matrix metalloproteinase 2 and leukemia inhibiting factor in AdCa. The findings provide some evidence supporting alterations in apoptosis, cell proliferation and extracellular matrix in lung tissues affected by chronic radiation exposure that can contribute to radiogenic cancerogenesis.

Tumor collagens predict genetic features and patient outcomes

The extracellular matrix (ECM) is a critical determinant of tumor fate that reflects the output from myriad cell types in the tumor. Collagens constitute the principal components of the tumor ECM. The changing collagen composition in tumors along with their impact on patient outcomes and possible biomarkers remains largely unknown. The RNA expression of the 43 collagen genes from solid tumors in The Cancer Genome Atlas (TCGA) was clustered to classify tumors. PanCancer analysis revealed how collagens by themselves can identify the tissue of origin. Clustering by collagens in each cancer type demonstrated strong associations with survival, specific immunoenvironments, somatic gene mutations, copy number variations, and aneuploidy. We developed a machine learning classifier that predicts aneuploidy, and chromosome arm copy number alteration (CNA) status based on collagen expression alone with high accuracy in many cancer types with somatic mutations, suggesting a strong relationship between the collagen ECM context and specific molecular alterations. These findings have broad implications in defining the relationship between cancer-related genetic defects and the tumor microenvironment to improve prognosis and therapeutic targeting for patient care, opening new avenues of investigation to define tumor ecosystems.

Circulating Tumor Cells in Cancer Diagnostics and Prognostics by Single-Molecule and Single-Cell Characterization

Circulating tumor cells (CTCs) represent an interesting source of biomarkers for diagnosis, prognosis, and the prediction of cancer recurrence, yet while they are extensively studied in oncobiology research, their diagnostic utility has not yet been demonstrated and validated. Their scarcity in human biological fluids impedes the identification of dangerous CTC subpopulations that may promote metastatic dissemination. In this Perspective, we discuss promising techniques that could be used for the identification of these metastatic cells. We first describe methods for isolating patient-derived CTCs and then the use of 3D biomimetic matrixes in their amplification and analysis, followed by methods for further CTC analyses at the single-cell and single-molecule levels. Finally, we discuss how the elucidation of mechanical and morphological properties using techniques such as atomic force microscopy and molecular biomarker identification using nanopore-based detection could be combined in the future to provide patients and their healthcare providers with a more accurate diagnosis.

Heterogeneity and versatility of the extracellular matrix during the transition from pleomorphic adenoma to carcinoma ex pleomorphic adenoma: cumulative findings from basic research and new insights

Pleomorphic adenoma (PA) is the most common salivary gland tumor, accounting for 50%-60% of these neoplasms. If untreated, 6.2% of PA may undergo malignant transformation to carcinoma ex-pleomorphic adenoma (CXPA). CXPA is a rare and aggressive malignant tumor, whose prevalence represents approximately 3%-6% of all salivary gland tumors. Although the pathogenesis of the PA-CXPA transition remains unclear, CXPA development requires the participation of cellular components and the tumor microenvironment for its progression. The extracellular matrix (ECM) comprises a heterogeneous and versatile network of macromolecules synthesized and secreted by embryonic cells. In the PA-CXPA sequence, ECM is formed by a variety of components including collagen, elastin, fibronectin, laminins, glycosaminoglycans, proteoglycans, and other glycoproteins, mainly secreted by epithelial cells, myoepithelial cells, cancer-associated fibroblasts, immune cells, and endothelial cells. Like in other tumors including breast cancer, ECM changes play an important role in the PA-CXPA sequence. This review summarizes what is currently known about the role of ECM during CXPA development.

Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma

Background

The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. Immunotherapy strategies are the most effective approach for patients who have developed metastases, but not all cases have been successful due to the complex and variable mechanisms of melanoma response to immune checkpoint inhibition.

Methods

We synthesized collagen-coding gene expression data (second-generation and single-cell sequencing) from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2).

Results

Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells.

Conclusion

We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.

PI3K/AKT/mTOR-Targeted Therapy for Breast Cancer

Phosphatidylinositol 3-kinase (PI3K), protein kinase B (PKB/AKT) and mechanistic target of rapamycin (mTOR) (PAM) pathways play important roles in breast tumorigenesis and confer worse prognosis in breast cancer patients. The inhibitors targeting three key nodes of these pathways, PI3K, AKT and mTOR, are continuously developed. For breast cancer patients to truly benefit from PAM pathway inhibitors, it is necessary to clarify the frequency and mechanism of abnormal alterations in the PAM pathway in different breast cancer subtypes, and further explore reliable biomarkers to identify the appropriate population for precision therapy. Some PI3K and mTOR inhibitors have been approved by regulatory authorities for the treatment of specific breast cancer patient populations, and many new-generation PI3K/mTOR inhibitors and AKT isoform inhibitors have also been shown to have good prospects for cancer therapy. This review summarizes the changes in the PAM signaling pathway in different subtypes of breast cancer, and the latest research progress about the biomarkers and clinical application of PAM-targeted inhibitors.