Collagen Family as Promising Biomarkers and Therapeutic Targets in Cancer

Tumor microenvironment: Nurturing cancer cells for immunoevasion and druggable vulnerabilities for cancer immunotherapy

The tumor microenvironment (TME) is an intricate ecosystem where cancer cells thrive, encompassing a wide array of cellular and non-cellular components. The TME co-evolves with tumor progression in a spatially and temporally dynamic manner, which endows cancer cells with the adaptive capability of evading immune surveillance. To this end, diverse cancer-intrinsic mechanisms were exploited to dampen host immune system, such as upregulating immune checkpoints, impairing antigens presentation and competing for nutrients. In this review, we discuss how cancer immunoevasion is tightly regulated by hypoxia, one of the hallmark biochemical features of the TME. Moreover, we comprehensively summarize how immune evasiveness of cancer cells is facilitated by the extracellular matrix, as well as soluble components of TME, including inflammatory factors, lactate, nutrients and extracellular vesicles. Given their important roles in dictating cancer immunoevasion, various strategies to target TME components are proposed, which holds promising translational potential in developing novel therapeutics to sensitize anti-cancer immunotherapy such as immune checkpoint blockade.

OSCC-derived EVs educate fibroblasts and remodel collagen landscape

Cancer-associated myofibroblasts (mCAFs) represent a significant component of the tumor microenvironment due to their contributions to extracellular matrix (ECM) remodeling. The pro-tumor mechanisms of extracellular vesicles (EVs) by regulating mCAFs and related collagens remain poorly understood in oral squamous cell carcinoma (OSCC). In this study, through analysis of single-cell sequencing data and immunofluorescence staining, we confirmed the increased presence of mCAFs and enrichment of specific collagen types in OSCC tissues. Furthermore, we demonstrated that OSCC-derived EVs promote the transformation of fibroblasts into mCAFs, leading to tumor invasion. Proteomic analysis identified the presence of TGF-β1 in EVs and revealed its role in inducing mCAFs via the TGF-β1/SMAD signaling pathway. Experiments in vivo confirmed that EVs, particularly those carrying TGF-β1, trigger COL18high COL5high matrix deposition, thereby forming the pro-tumor ECM in OSCC. In summary, our investigation unveils the significant involvement of OSCC-derived EVs in orchestrating the differentiation of fibroblasts into mCAFs and modulating specific collagen types within the ECM. Therefore, this study provides a theoretical basis for targeting the EV-mediated TGF-β1 signaling pathway as a potential therapeutic strategy for OSCC.

Fish skin dressing for wound regeneration: A bioactive component review of omega-3 PUFAs, collagen and ECM

Wound healing is a complex biological process that involves several stages, including hemostasis, inflammation, proliferation, and remodeling. Traditional wound dressings, to a certain extent, can provide wound protection but are limited in promoting wound healing, reducing scar formation, and preventing bacterial infections. In recent years, with the advancement of research in biomedical materials, fish skin dressings have become a research hotspot in the field of tissue regeneration due to their remarkable biocompatibility and precious bioactive components. However, current research on fish skin dressings remains focused on clinical treatment. To further deepen and promote the development of fish skin dressings, we put emphasis on discussing main bioactive components in fish skin. This article has reviewed the advantages of fish skin dressings in wound regeneration, especially the promotive effects of its main bioactive components-Omega-3 polyunsaturated fatty acids, collagen derived from fish skin, and the extracellular matrix of fish skin-on the wound healing process. Besides, by critically summarizing the research issues of each bioactive component, this review assists researchers in better defining the next direction of research, thereby designing the optimal dressing for different types of wounds.

P4HA1: an important target for treating fibrosis related diseases and cancer

Fibrosis is significantly associated with a wide variety of diseases and is involved in their progression. Fibrosis activated under the influence of different combinations of factors is considered a double-edged sword. Although there has been much research on organ fibrosis in recent years, a variety of organ fibrosis diseases and cancers are not well controlled in terms of prevention, treatment, and prognosis. Clinical studies still lack exploration and discovery of effective targets for the pathogenesis of organ fibrosis. Prolyl 4-hydroxylase subunit alpha 1 (P4HA1) is a protein kinase and the synthesis and secretion of collagen are related to the sustained activation of P4HA1. As further studies are being conducted, the potential role of P4HA1 in the development of fibrosis-associated diseases and cancer is becoming clear. Consequently, we conducted a systematic review and discussion on the role of P4HA1 in the pathogenesis of various fibrosis-related diseases and cancers. We reviewed the possible strategies of P4HA1 in the diagnosis and treatment of fibrosis-related diseases and cancers, and analyzed its potential relevance as a biomarker in the diagnosis and treatment of fibrosis-related diseases and cancer.

COL6A1 Inhibits the Malignant Development of Bladder Cancer by Regulating FBN1

Bladder cancer (BLCA) is a prevalent malignancy worldwide with a high recurrence rate. Collagen Type VI Alpha 1 (COL6A1) plays a key role in several cancer types. In this study, we aimed to explore the role of COL6A1 in BLCA. COL6A1 expression in BLCA was determined using The Cancer Genome Atlas database and real-time quantitative polymerase chain reaction (RT-qPCR). Counting Kit-8, wound-healing, and transwell assays were used to assess the effect of COL6A1 on T24 and 5637 cells. Apoptosis in BLCA cell lines was explored using western blotting and flow cytometry. Co-immunoprecipitation was performed to determine interactions between proteins. The role of COL6A1 in tumor growth in nude mice was evaluated by hematoxylin-eosin, immunohistochemical, and terminal deoxynucleotidyl transferase dUTP Nick-End Labeling. In BLCA, COL6A1 expression was downregulated. Moreover, the COL6A1 overexpression suppressed the viability, migration, and invasion, while promoting apoptosis of BLCA cell lines, with increased Caspase-3, Bax, and p53, and decreased Bcl-2. Conversely, silencing of COL6A1 promoted proliferation, migration, and invasion, while inhibiting apoptosis in BLCA cell lines. In vivo, COL6A1 inhibits tumor growth and progression. Fibrillin-1 (FBN1) was positively correlated with COL6A1 expression. COL6A1 could bind to FBN1 in BLCA cell lines. The expression of FBN1 in BLCA cell lines decreased after COL6A1 silencing, whereas COL6A1 overexpression upregulated FBN1 expression. COL6A1 was downregulated and exerted an inhibitory effect on the development of BLCA, and its expression was positively correlated with the expression of FBN1.

Machine learning-based diagnostics of capsular invasion in thyroid nodules with wide-field second harmonic generation microscopy

Papillary thyroid carcinoma (PTC) is one of the most common, well-differentiated carcinomas of the thyroid gland. PTC nodules are often surrounded by a collagen capsule that prevents the spread of cancer cells. However, as the malignant tumor progresses, the integrity of this protective barrier is compromised, and cancer cells invade the surroundings. The detection of capsular invasion is, therefore, crucial for the diagnosis and the choice of treatment and the development of new approaches aimed at the increase of diagnostic performance are of great importance. In the present study, we exploited the wide-field second harmonic generation (SHG) microscopy in combination with texture analysis and unsupervised machine learning (ML) to explore the possibility of quantitative characterization of collagen structure in the capsule and designation of different capsule areas as either intact, disrupted by invasion, or apt to invasion. Two-step k-means clustering showed that the collagen capsules in all analyzed tissue sections were highly heterogeneous and exhibited distinct segments described by characteristic ML parameter sets. The latter allowed a structural interpretation of the collagen fibers at the sites of overt invasion as fragmented and curled fibers with rarely formed distributed networks. Clustering analysis also distinguished areas in the PTC capsule that were not categorized as invasion sites by the initial histopathological analysis but could be recognized as prospective micro-invasions after additional inspection. The characteristic features of suspicious and invasive sites identified by the proposed unsupervised ML approach can become a reliable complement to existing methods for diagnosing encapsulated PTC, increase the reliability of diagnosis, simplify decision making, and prevent human-related diagnostic errors. In addition, the proposed automated ML-based selection of collagen capsule images and exclusion of non-informative regions can greatly accelerate and simplify the development of reliable methods for fully automated ML diagnosis that can be integrated into clinical practice.

The Mclust Analysis of Tumor Budding Unveils the Role of the Collagen Family in Cervical Cancer Progression

In RNA-seq data analysis, condensing the gene count matrix size is pivotal for downstream investigations, particularly pathway analysis. For this purpose, harnessing machine learning attracts increasing interest, while conventional methodologies depend on p-value comparisons. In this study, 20 tissue samples from real-world cervical cancers were subjected to sequencing, followed by the application of the Mclust algorithm to delineate an optimal cluster. By stratifying tumor budding into high and low groups and quantifying the epithelial-to-mesenchymal transition (EMT) score to scrutinize tumor budding, we discerned 24 EMT-related genes, with 5 showing strong associations with cervical cancer prognosis. Our observations elucidate a biological flow wherein EMT, Matrix Metallopep-tidase 2 (MMP2), and extracellular matrix (ECM) degradation are interconnected, ultimately leading to collagen type VI and exacerbating the prognosis of cervical cancer. The present study underscores an alternative method for selecting useful EMT-related genes by employing an appropriate clustering algorithm, thereby avoiding classical methods while unveiling novel insights into cervical cancer etiology and prognosis. Moreover, when comparing high and low tumor budding, collagen type VI emerges as a potential gene marker for the prognosis of cervical cancer.

Targeting HSP47 for cancer treatment

Heat shock protein 47 (HSP47) serves as an endoplasmic reticulum residing collagen-specific chaperone and plays an important role in collagen biosynthesis and structural assembly. HSP47 is encoded by the SERPINH1 gene, which is located on chromosome 11q13.5, one of the most frequently amplified regions in human cancers. The expression of HSP47 is regulated by multiple cellular factors, including cytokines, transcription factors, microRNAs, and circular RNAs. HSP47 is frequently upregulated in a variety of cancers and plays an important role in tumor progression. HSP47 promotes tumor stemness, angiogenesis, growth, epithelial-mesenchymal transition, and metastatic capacity. HSP47 also regulates the efficacy of tumor therapies, such as chemotherapy, radiotherapy, and immunotherapy. Inhibition of HSP47 expression has antitumor effects, suggesting that targeting HSP47 is a feasible strategy for cancer treatment. In this review, we highlight the function and expression of regulatory mechanisms of HSP47 in cancer progression and point out the potential development of therapeutic strategies in targeting HSP47 in the future.

The Potential of the lncRNAs ADAMTSL4-AS1, AC067931 and SOCS2-AS1 in Peripheral Blood Mononuclear Cells as Novel Diagnostic Biomarkers for Hepatitis B Virus-Associated Hepatocellular Carcinoma

Purpose

Long noncoding RNAs (lncRNAs) might be closely associated with hepatocellular carcinoma (HCC) progression and could serve as diagnostic and prognostic markers. This study aimed to investigate lncRNA-based diagnostic biomarkers for hepatitis B virus (HBV)-associated HCC.

Materials and Methods

High-throughput transcriptome sequencing was conducted on the liver tissues of 15 patients with HBV-associated liver diseases (5 with chronic hepatitis B [CHB], 5 with liver cirrhosis [LC], and 5 with HCC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze lncRNA expressions. Potential diagnostic performance for HBV-associated HCC screening was evaluated.

Results

Through trend analysis and functional analysis, we found that 8 lncRNAs were gradually upregulated and 1 lncRNA was progressively downregulated by regulation of target mRNAs and downstream HCC-associated signaling pathways. The validation of dysregulated lncRNAs in peripheral blood mononuclear cells (PBMCs) and HCC tissues by qRT-PCR revealed that ADAMTSL4-AS1, SOCS2-AS1, and AC067931 were significantly increased in HCC compared with CHB and cirrhosis. Moreover, differentially expressed lncRNAs were aberrantly elevated in Huh7, Hep3B, HepG2, and HepG2.215 cells compared with LX2 cells. Furthermore, ADAMTSL4-AS1, SOCS2-AS1, and AC067931 were identified as novel biomarkers for HBV-associated HCC. For distinguishing HCC from CHB, ADAMTSL4-AS1, AC067931, and SOCS2-AS1 combined with alpha-fetoprotein (AFP) had an area under the curve (AUC) of 0.945 (sensitivity, 83.9%; specificity, 89.8%). Similarly, for distinguishing HCC from LC, this combination had an AUC of 0.871 (sensitivity, 91.1%; specificity, 68.2%). Furthermore, this combination showed the highest diagnostic ability to distinguish HCC from CHB and LC (AUC, 0.905; sensitivity, 91.1%; specificity, 75.3%). In particular, this combination identified AFP-negative (AFP < 20 ng/mL) (AUC = 0.814), small (AUC = 0.909), and early stage (AUC = 0.863) tumors.

Conclusion

ADAMTSL4-AS1, SOCS2-AS1, and AC067931 combined with AFP in PBMCs may serve as a noninvasive diagnostic biomarker for HBV-associated HCC, especially AFP-negative, small, and early stage HCC.

Construction and analysis of a reliable five-gene prognostic signature for colon adenocarcinoma associated with the wild-type allelic state of the COL6A6 gene

Background

Tumors emerge by acquiring a number of mutations over time. The first mutation provides a selective growth advantage compared to adjacent epithelial cells, allowing the cell to create a clone that can outgrow the cells that surround it. Subsequent mutations determine the risk of the tumor progressing to metastatic cancer. Some secondary mutations may inhibit the aggressiveness of the tumor while still increasing the survival of the clone. Meaningful mutations in genes may provide a strong molecular foundation for developing novel therapeutic strategies for cancer.

Methods

The somatic mutation and prognosis in colon adenocarcinoma (COAD) were analyzed. The copy number variation (CNV) and differentially expressed genes (DEGs) between the collagen type VI alpha 6 chain (COL6A6) mutation (COL6A6-MUT) and the COL6A6 wild-type (COL6A6-WT) subgroups were evaluated. The independent prognostic signatures based on COL6A6-allelic state were determined to construct a Cox model. The biological characteristics and the immune microenvironment between the two risk groups were compared.

Results

COL6A6 was found to be highly mutated in COAD at a frequency of 9%. Patients with COL6A6-MUT had a good overall survival (OS) compared to those with COL6A6-WT, who had a different CNV pattern. Significant differences in gene expression were established for 593 genes between the COL6A6-MUT and COL6A6-WT samples. Among them, MUC16, ASNSP1, PRR18, PEG10, and RPL26P8 were determined to be independent prognostic factors. The internally validated prognostic risk model, constructed using these five genes, demonstrated its value by revealing a significant difference in patient prognosis between the high-risk and low-risk groups. Specifically, patients in the high-risk group exhibited a considerably worse prognosis than did those in the low-risk group. The high-risk group had a significantly higher proportion of patients over 60 years of age and patients in stage III. Moreover, the tumor immune dysfunction and exclusion (TIDE) score and the expression of human leukocyte antigen (HLA) family genes were all higher in the high-risk group than that in the low-risk group.

Conclusions

The allelic state of COL6A6 and the five associated DEGs were identified as novel biomarkers for the diagnosis and prognosis of COAD and may be therapeutic targets in COAD.

Factors Affecting the Diagnostic Discordance Between Frozen and Permanent Sections in Mucinous Ovarian Tumors

Purpose

To investigate the accuracy of intraoperative frozen section (FS) diagnosis for predicting the permanent section (PS) diagnosis of mucinous ovarian tumors and evaluate the factors affecting the diagnostic discordance.

Patients and Methods

This retrospective cohort study was performed in Tianjin Medical University General Hospital. All women who underwent ovarian surgery with FS between January 2011 and December 2022 were identified, and those with a diagnosis of mucinous ovarian tumor (MOT) by FS or PS were reviewed. Clinical and pathologic data were extracted.

Results

A total of 180 women were included, of which 141 (78.33%) had diagnostic concordance between FS and PS, yielding a sensitivity of 83.43% and a positive predictive value (PPV) of 92.76%. Under- and over-diagnosis occurred in 28 cases (15.56%) and 11 cases (6.11%). Tumor size > 13cm (OR 3.79, 95% CI 1.12-12.73) was an independent risk factor for under-diagnosis, and tumor size ≤ 13cm (OR 16.78, 95% CI 0.01-0.49), laparoscopic surgery (OR 0.14, 95% CI 0.02-0.92), the combination of other tumor components (including serous, Brenner tumor, and chocolate cyst; OR 7.00, 95% CI 1.19-41.12) were independently associated with over-diagnosis. The Kaplan-Meier survival curves and the Log rank test showed no significant difference between misdiagnosed and accurately diagnosed patients (all P > 0.05).

Conclusion

Intraoperative frozen pathology of MOT is problematic for under- and over-diagnosis. The incorrect diagnosis of FS was related to determining the extent of surgery but had no impact on the patients' long-term recurrence and survival outcomes. In future clinical practice, surgeons need to obtain material accurately and enhance communication with pathologists during the operation to improve the accuracy of FS diagnosis.

Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality

BACKGROUND

Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.

METHODS

CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.

RESULTS

A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).

CONCLUSION

We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

Analysis of the effects of M2 macrophage-derived PDE4C on the prognosis, metastasis and immunotherapy benefit of osteosarcoma

Tumour-associated macrophages (TAMs), encompassing M1 and M2 subtypes, exert significant effects on osteosarcoma (OS) progression and immunosuppression. However, the impacts of TAM-derived biomarkers on the progression of OS remains limited. The GSE162454 profile was subjected to single-cell RNA (scRNA) sequencing analysis to identify crucial mediators between TAMs and OS cells. The clinical features, effects and mechanisms of these mediators on OS cells and tumour microenvironment were evaluated via biological function experiments and molecular biology experiments. Phosphodiesterase 4C (PDE4C) was identified as a pivotal mediator in the communication between M2 macrophages and OS cells. Elevated levels of PDE4C were detected in OS tissues, concomitant with M2 macrophage level, unfavourable prognosis and metastasis. The expression of PDE4C was observed to increase during the conversion process of THP-1 cells to M2 macrophages, which transferred the PDE4C mRNA to OS cells through exosome approach. PDE4C increased OS cell proliferation and mobility via upregulating the expression of collagens. Furthermore, a positive correlation was observed between elevated levels of PDE4C and increased TIDE score, decreased response rate following immune checkpoint therapy, reduced TMB and diminished PDL1 expression. Collectively, PDE4C derived from M2 macrophages has the potential to enhance the proliferation and mobility of OS cells by augmenting collagen expression. PDE4C may serve as a valuable biomarker for prognosticating patient outcomes and response rates following immunotherapy.

Analysis of cancer-associated fibroblasts related genes identifies COL11A1 associated with lung adenocarcinoma prognosis

BACKGROUND

The treatment of lung adenocarcinoma is difficult due to the limited therapeutic options. Cancer-associated fibroblasts play an important role in the development of cancers. This study aimed to identify a promising molecular target associated with cancer-associated fibroblasts for the treatment of lung adenocarcinoma.

METHODS

The Cancer Genome Atlas lung adenocarcinoma dataset was used to screen hub genes associated with cancer-associated fibroblasts via the EPIC algorithm and Weighted Gene Co-expression Network Analysis. Multiple databases were used together with our data to verify the differential expression and survival of COL11A1. Functional enrichment analysis and the single-cell TISCH database were used to elucidate the mechanisms underlying COL11A1 expression. The correlation between COL11A1 and immune checkpoint genes in human cancers was also evaluated.

RESULTS

Using the EPIC algorithm and Weighted Gene Co-expression Network Analysis, 13 hub genes associated with cancer-associated fibroblasts in lung adenocarcinoma were screened. Using the GEPIA database, Kaplan-Meier Plotter database, GSE72094, GSE75037, GSE32863, and our immunohistochemistry experiment data, we confirmed that COL11A1 overexpresses in lung adenocarcinoma and that high expression of COL11A1 is associated with a poor prognosis. COL11A1 has a genetic alteration frequency of 22% in patients with lung adenocarcinoma. COL11A1 is involved in the extracellular matrix activities of lung adenocarcinoma. Using the TISCH database, we found that COL11A1 is mainly expressed by cancer-associated fibroblasts in the tumor microenvironment rather than by lung adenocarcinoma cells. Finally, we found that COL11A1 is positively correlated with HAVCR2(TIM3), CD274 (PD-L1), CTLA4, and LAG3 in lung adenocarcinoma.

CONCLUSION

COL11A1 may be expressed and secreted by cancer-associated fibroblasts, and a high expression of COL11A1 may result in T cell exhaustion in the tumor microenvironment of lung adenocarcinoma. COL11A1 may serve as an attractive biomarker to provide new insights into cancer therapeutics.

Lactate-driven type I collagen deposition facilitates cancer stem cell-like phenotype of head and neck squamous cell carcinoma

Lactate is known to play a crucial role in the progression of malignancies. However, its mechanism in regulating the malignant phenotype of head and neck squamous cell carcinoma (HNSCC) remains unclear. This study found that lactate increases cancer stem cell (CSC) characteristics of HNSCC by influencing the deposition of type I collagen (Col I). Lactate promotes Col I deposition through two distinct pathways. One is to convert lactate to pyruvate, a substrate for Col I hydroxylation. The other is the activation of HIF1-α and P4HA1, the latter being a rate-limiting enzyme for Col I synthesis. Inhibition of these two pathways effectively counteracts lactate-induced enhanced cell stemness. Further studies revealed that Col I affects CSC properties by regulating cell cycle dynamics. In conclusion, our research proposes that lactate-driven Col I deposition is essential for the acquisition of CSC properties, and lactate-centric Col I deposition may be an effective target for CSCs.

Integrated bioinformatics analysis reveals upregulated extracellular matrix hub genes in pancreatic cancer: Implications for diagnosis, prognosis, immune infiltration, and therapeutic strategies

BACKGROUND

Pancreatic cancer (PC) stands out as one of the most formidable malignancies and exhibits an exceptionally unfavorable clinical prognosis due to the absence of well-defined diagnostic indicators and its tendency to develop resistance to therapeutic interventions. The primary objective of this present study was to identify extracellular matrix (ECM)-related hub genes (HGs) and their corresponding molecular signatures, with the intent of potentially utilizing them as biomarkers for diagnostic, prognostic, and therapeutic applications.

METHODS

Three microarray datasets were sourced from the NCBI database to acquire upregulated differentially expressed genes (DEGs), while MatrisomeDB was employed for filtering ECM-related genes. Subsequently, a protein-protein interaction (PPI) network was established using the STRING database. The created network was visually inspected through Cytoscape, and HGs were identified using the CytoHubba plugin tool. Furthermore, enrichment analysis, expression pattern analysis, clinicopathological correlation, survival analysis, immune cell infiltration analysis, and examination of chemical compounds were carried out using Enrichr, GEPIA2, ULCAN, Kaplan Meier plotter, TIMER2.0, and CTD web platforms, respectively. The diagnostic and prognostic significance of HGs was evaluated through the ROC curve analysis.

RESULTS

Ten genes associated with ECM functions were identified as HGs among 131 DEGs obtained from microarray datasets. Notably, the expression of these HGs exhibited significantly (p < 0.05) higher in PC, demonstrating a clear association with tumor advancement. Remarkably, higher expression levels of these HGs were inversely correlated with the likelihood of patient survival. Moreover, ROC curve analysis revealed that identified HGs are promising biomarkers for both diagnostic (AUC > 0.75) and prognostic (AUC > 0.64) purposes. Furthermore, we observed a positive correlation between immune cell infiltration and the expression of most HGs. Lastly, our study identified nine compounds with significant interaction profiles that could potentially act as effective chemical agents targeting the identified HGs.

CONCLUSION

Taken together, our findings suggest that COL1A1, KRT19, MMP1, COL11A1, SDC1, ITGA2, COL1A2, POSTN, FN1, and COL5A1 hold promise as innovative biomarkers for both the diagnosis and prognosis of PC, and they present as prospective targets for therapeutic interventions aimed at impeding the progression PC.

B7-H3 is associated with the armored-cold phenotype and predicts poor immune checkpoint blockade response in melanoma

Melanoma is the most suitable tumor type for immunotherapy, but not all melanoma patients could respond to immunotherapy. B7 homolog 3 (B7-H3) belongs to the B7 family and is overexpressed in a number of malignant tumors, but the expression pattern of B7-H3 in melanoma has not been well summarized. The expression of B7-H3 was investigated in melanoma and its correlations with features of the tumor microenvironment (TME) by using various public databases, including the Cancer Genome Atlas (TCGA), the GEPIA, and the Human Protein Atlas databases. In addition, the in-house melanoma tissue microarray was applied to validate the results from public databases. Based on the public and in-house cohorts, we found that B7-H3 was overexpressed in melanoma tumor tissues and high B7-H3 expression was related to poor clinical outcome. Moreover, B7-H3 was negatively correlated with levels of tumor-infiltrating lymphocytes (TILs) and positively correlated with collagen infiltration. With clinical translational value, the predictive value of B7-H3 for conventional immunotherapy was detected using the Kaplan-Meier plotter tool, and the results showed that melanoma patients with high B7-H3 expression were insensitive to anti-PD-1 and anti-CTLA-4 immunotherapy. In conclusion, we first investigate the expression of B7-H3 in melanoma and its correlations with the TME features, and indicate B7-H3 as a promising therapeutic target in melanoma patients that are insensitive to conventional immunotherapy.

Label-free quantification of imaging features in the extracellular matrix of left and right-sided colon cancer tissues

The molecular pathogenesis of colorectal cancer is known to differ between the right and left side of the colon. Several previous studies have focussed on the differences in clinicopathological features, proteomic and genetic biomarkers, the composition of gut microbiota, response to therapy, and the characteristics of the tumour microenvironment. However, the morphology and density of collagen in the extracellular matrix (ECM) have not been studied intensively. In this study, we employed 2-photon laser scanning microscopy (2PLSM) to visualise the intrinsic second-harmonic generation (SHG) signal emitted by collagen fibres in the heterogeneous ECM of human colon tumour tissues. Through texture analysis of the SHG signal, we quantitatively distinguished the imaging features generated by structural differences of collagen fibres in healthy colon and cancers and found marked differences. The fibres inside of tumours exhibited a loss of organisation, particularly pronounced in right-sided colon cancer (RSCC), where the chaotic regions were significantly increased. In addition, a higher collagen content was found in left-sided colon cancer (LSCC). In future, this might aid in subclassification and therapeutic decisions or even in designing new therapy regimens by taking into account the differences between collagen fibres features between colon tumours located at different sides.

Glycosylation Modulates the Structure and Functions of Collagen: A Review

Collagens are fundamental constituents of the extracellular matrix and are the most abundant proteins in mammals. Collagens belong to the family of fibrous or fiber-forming proteins that self-assemble into fibrils that define their mechanical properties and biological functions. Up to now, 28 members of the collagen superfamily have been recognized. Collagen biosynthesis occurs in the endoplasmic reticulum, where specific post-translational modification-glycosylation-is also carried out. The glycosylation of collagens is very specific and adds β-d-galactopyranose and β-d-Glcp-(1→2)-d-Galp disaccharide through β-O-linkage to hydroxylysine. Several glycosyltransferases, namely COLGALT1, COLGALT2, LH3, and PGGHG glucosidase, were associated the with glycosylation of collagens, and recently, the crystal structure of LH3 has been solved. Although not fully understood, it is clear that the glycosylation of collagens influences collagen secretion and the alignment of collagen fibrils. A growing body of evidence also associates the glycosylation of collagen with its functions and various human diseases. Recent progress in understanding collagen glycosylation allows for the exploitation of its therapeutic potential and the discovery of new agents. This review will discuss the relevant contributions to understanding the glycosylation of collagens. Then, glycosyltransferases involved in collagen glycosylation, their structure, and catalytic mechanism will be surveyed. Furthermore, the involvement of glycosylation in collagen functions and collagen glycosylation-related diseases will be discussed.

Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy

Background: Collagen represents a prominent constituent of the tumor's extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions. Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer. Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells. Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.

High B7-H3 expression with low PD-L1 expression identifies armored-cold tumors in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is generally regarded as the most aggressive subtype among breast cancers, but exhibits higher chemotherapeutic and immunotherapeutic responses due to its unique immunogenicity. Thus, appropriate discrimination of subtypes is critical for guiding therapeutic options in clinical practice. In this research, using multiple in-house and public cohorts, we investigated the expression features and immuno-correlations of B7-H3 in breast cancer and checked the anti-tumor effect of the B7-H3 monoclonal antibody in a mouse model. We also developed a novel classifier combining B7-H3 and PD-L1 expression in TNBC. B7-H3 was revealed to be related to immuno-cold features and accumulated collagen in TNBC. In addition, targeting B7-H3 using the monoclonal antibody significantly suppressed mouse TNBC growth, reversed the armored-cold phenotype, and also boosted anti-PD-1 immunotherapy. In addition, patients with B7-H3 high and PD-L1 low expression showed the lowest anti-tumor immune infiltration, the highest collagen level, and the lowest therapeutic responses to multiple therapies, which mostly belong to armored-cold tumors. Overall, this research provides a novel subtyping strategy based on the combination of B7-H3/PD-L1 expression, which leads to a novel approach for the management of TNBC.

The Potential of Extracellular Matrix- and Integrin Adhesion Complex-Related Molecules for Prostate Cancer Biomarker Discovery

Prostate cancer is among the top five cancer types according to incidence and mortality. One of the main obstacles in prostate cancer management is the inability to foresee its course, which ranges from slow growth throughout years that requires minimum or no intervention to highly aggressive disease that spreads quickly and resists treatment. Therefore, it is not surprising that numerous studies have attempted to find biomarkers of prostate cancer occurrence, risk stratification, therapy response, and patient outcome. However, only a few prostate cancer biomarkers are used in clinics, which shows how difficult it is to find a novel biomarker. Cell adhesion to the extracellular matrix (ECM) through integrins is among the essential processes that govern its fate. Upon activation and ligation, integrins form multi-protein intracellular structures called integrin adhesion complexes (IACs). In this review article, the focus is put on the biomarker potential of the ECM- and IAC-related molecules stemming from both body fluids and prostate cancer tissue. The processes that they are involved in, such as tumor stiffening, bone turnover, and communication via exosomes, and their biomarker potential are also reviewed.

Quantitation of native and forced degraded collagens by capillary zone electrophoresis: Method development and validation

A new capillary zone electrophoresis method for collagen quantitation was developed and validated according to the International Council for Harmonization guideline Q2 (R1). The Sircol collagen assay and ultraviolet spectrometry were employed as reference methods. Capillary zone electrophoresis enables specific, simple, and fast determination within 9 min. It is less user-dependent and more automated than the Sircol collagen assay. With a limit of detection of 18.0 μg/mL, the new method is less sensitive than the Sircol collagen assay, which has a limit of detection of 6.5 μg/mL. Nonetheless, capillary zone electrophoresis covers a wider linearity range (50-400 μg/mL) compared to the Sircol collagen assay (5-80 μg/mL), with similar precision. Additional advantages of capillary zone electrophoresis are the ability to gain information on collagen integrity and to simultaneously determine native and denatured collagens. This approach represents a modern and legitimate alternative to the Sircol collagen assay. The developed method has been successfully applied to the study of three collagen products and samples from forced degradation.

Selenium metabolism heterogeneity in pan-cancer: insights from bulk and single-cell RNA sequencing

BACKGROUND

Selenium, a natural microelement with both nutritional and toxicological properties, is intertwined with tumorigenesis and progression. However, it is not fully understood how selenium metabolism affects immune response and cancer biology.

METHODS

We estimated selenium metabolism by Gene Set Enrichment Analysis (GSEA) to delineate the selenium metabolism landscape using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE) and a integrated pan-cancer single-cell dataset. We systematically explored the prognostic implications of selenium metabolism and selenium-related regulatory patterns. The therapeutic value of selenium metabolism was explored through machine learning and examined in several immunotherapy cohorts. The heterogeneity and underlying mechanism of selenium metabolism were investigated by cell‒cell communication analysis at the single-cell level.

RESULTS

A GSEA analysis based on 86 genes was used to evaluate the selenium metabolism landscape. The selenium metabolism score exhibited prognostic value in predicting the lower risk of mortality, possibly due to its correlation with multiple cancer hallmarks, including a positive correlation with complement (R = 0.761, P < 0.001), inflammatory response (R = 0.663, P < 0.001), apoptosis (R = 0.626, P < 0.001), hypoxia (R = 0.587, P < 0.001), reactive oxygen species (ROS) (R = 0.558, P < 0.001), and interferon gamma response (R = 0.539, P < 0.001). We also observed heterogeneity in the relationship between selenium metabolism and immunity across different cancers. Based on selenium-related genes, we constructed a machine learning model with area under the ROC curve (AUC) of 0.82 in predicting immune checkpoint inhibitor (ICI)-based immunotherapy response. Single-cell selenium metabolism quantification revealed that adjacent and tumor tissues had higher selenium metabolism compared with normal tissues, especially in epithelial cells, fibroblasts and macrophages. The communication between high-selenium epithelium and high-selenium fibroblast was significantly higher than other cells, especially in cytokines, chemokines, collagen, Wnt, VEGF, IGF and FGF pathways.

CONCLUSION

Our study provides a comprehensive landscape of selenium metabolism levels and diverse regulatory patterns in different cancers, deepening the understanding of selenium's roles in tumorigenesis and immunity.

Targeting collagen XVIII improves the efficiency of ErbB inhibitors in breast cancer models

The tumor extracellular matrix (ECM) critically regulates cancer progression and treatment response. Expression of the basement membrane component collagen XVIII (ColXVIII) is induced in solid tumors, but its involvement in tumorigenesis has remained elusive. We show here that ColXVIII was markedly upregulated in human breast cancer (BC) and was closely associated with a poor prognosis in high-grade BCs. We discovered a role for ColXVIII as a modulator of epidermal growth factor receptor tyrosine kinase (ErbB) signaling and show that it forms a complex with ErbB1 and -2 (also known as EGFR and human epidermal growth factor receptor 2 [HER2]) and α6-integrin to promote cancer cell proliferation in a pathway involving its N-terminal portion and the MAPK/ERK1/2 and PI3K/AKT cascades. Studies using Col18a1 mouse models crossed with the mouse mammary tumor virus-polyoma virus middle T antigen (MMTV-PyMT) mammary carcinogenesis model showed that ColXVIII promoted BC growth and metastasis in a tumor cell-autonomous manner. Moreover, the number of mammary cancer stem cells was significantly reduced in the MMTV-PyMT and human cell models upon ColXVIII inhibition. Finally, ablation of ColXVIII substantially improved the efficacy of ErbB-targeting therapies in both preclinical models. In summary, ColXVIII was found to sustain the stemness properties of BC cells and tumor progression and metastasis through ErbB signaling, suggesting that targeting ColXVIII in the tumor milieu may have important therapeutic potential.

Effect of tissue fixation on the optical properties of structural components assessed by non-linear microscopy imaging

Fixation methods such as formalin are commonly used for the preservation of tissue with the aim of keeping their structure as close as possible to the native condition. However, fixatives chemically interact with tissue molecules, such as collagen in the extracellular matrix (ECM) or myosin, and may thus modify their structure. Taking advantage of the second- and third-harmonic generation (SHG and THG) emission capabilities of such components, we used nonlinear two-photon microscopy (NL2PM) to evaluate the effect that preservation methods, such as chemical fixatives, have on the nonlinear capabilities of protein components within mouse tissues. Our results show that depending on the preservation technique used, the nonlinear capabilities of collagen, lipid droplets and myosin microarchitecture are strongly affected. Parameters of collagen fibers, such as density and branch points, especially in collagen-sparse regions, e.g., in kidneys, were found to be altered upon formalin fixation. Moreover, cryo-freezing drastically reduced SHG signals from myosin. Our findings provide valuable information to select the best tissue fixation method for visualization and quantification of structural proteins, such as collagen and myosin by advanced NL2PM imaging techniques. This may advance the interpretation of the role these proteins play in disease.