High expression of COL10A1 is associated with poor prognosis in colorectal cancer

Krüppel-like factor 4 modulates the miR-101/COL10A1 axis to inhibit renal fibrosis after AKI by regulating epithelial-mesenchymal transition

Acute kidney injury (AKI) can progress to renal fibrosis and chronic kidney disease (CKD), which reduces quality of life and increases the economic burden on patients. However, the molecular mechanisms underlying renal fibrosis following AKI remain unclear. This study tested the hypothesis that the Krüppel-like factor 4 (KLF4)/miR-101/Collagen alpha-1X (COL10A1) axis could inhibit epithelial-mesenchymal transition (EMT) and renal fibrosis after AKI in a mouse model of ischemia-reperfusion (I/R)-induced renal fibrosis and HK-2 cells by gene silencing, overexpression, immunofluorescence, immunohistochemistry, real-time quantitative PCR, Western blotting, dual-luciferase reporter assay, fluorescence in situ hybridization (FISH) and ELISA. Compared with the Sham group, I/R induced renal tubular and glomerular injury and fibrosis, and increased the levels of BUN, serum Scr and neutrophil gelatinase-associated lipocalin (NGAL), Col10a1 and Vimentin expression, but decreased E-cadherin expression in the kidney tissues of mice at 42 days post-I/R. Similarly, hypoxia promoted fibroblastic morphological changes in HK-2 cells and enhanced NGAL, COL10A1, Vimentin, and α-SMA expression, but reduced E-cadherin expression in HK-2 cells. These pathological changes were significantly mitigated in COL10A1-silenced renal tissues and HK-2 cells. KLF4 induces miR-101 transcription. More importantly, hypoxia upregulated Vimentin and COL10A1 expression, but decreased miR-101, KLF4, and E-cadherin expression in HK-2 cells. These hypoxic effects were significantly mitigated or abrogated by KLF4 over-expression in the HK-2 cells. Our data indicate that KLF4 up-regulates miR-101 expression, leading to the downregulation of COL10A1 expression, inhibition of EMT and renal fibrosis during the pathogenic process of I/R-related renal fibrosis.

A decentralized federated learning-based cancer survival prediction method with privacy protection

Background

Survival prediction is one of the crucial goals in precision medicine, as accurate survival assessment can aid physicians in selecting appropriate treatment for individual patients. To achieve this aim, extensive data must be utilized to train the prediction model and prevent overfitting. However, the collection of patient data for disease prediction is challenging due to potential variations in data sources across institutions and concerns regarding privacy and ownership issues in data sharing. To facilitate the integration of cancer data from different institutions without violating privacy laws, we developed a federated learning-based data integration framework called AdFed, which can be used to evaluate patients' survival while considering the privacy protection problem by utilizing the decentralized federated learning technology and regularization method.

Results

AdFed was tested on different cancer datasets that contain the patients' information from different institutions. The experimental results show that AdFed using distributed data can achieve better performance in cancer survival prediction (AUC = 0.605) than the compared federated-learning-based methods (average AUC = 0.554). Additionally, to assess the biological interpretability of our method, in the case study we list 10 identified genes related to liver cancer selected by AdFed, among which 5 genes have been proved by literature review.

Conclusions

The results indicate that AdFed outperforms better than other federated-learning-based methods, and the interpretable algorithm can select biologically significant genes and pathways while ensuring the confidentiality and integrity of data.

Sample-Treatment with the Virucidal β-Propiolactone Does Not Preclude Analysis by Large Panel Affinity Proteomics, Including the Discovery of Biomarker Candidates

Virus inactivation is a prerequisite for safe handling of high-risk infectious samples. β-Propiolactone (BPL) is an established reagent with proven virucidal efficacy. BPL primarily reacts with DNA, RNA, and amino acids. The latter may modify antigenic protein epitopes interfering with binding properties of affinity reagents such as antibodies and aptamers used in affinity proteomic screens. We investigated (i) the impact of BPL treatment on the analysis of protein levels in plasma samples using the aptamer-based affinity proteomic platform SomaScan and (ii) effects on protein detection in conditioned medium samples using the proximity extension assay-based Olink Target platform. In the former setup, BPL-treated and native plasma samples from patients with ovarian cancer (n = 12) and benign diseases (n = 12) were analyzed using the SomaScan platform. In the latter, conditioned media samples collected from cultured T cells with (n = 3) or without (n = 3) anti-CD3 antibody stimulation were analyzed using the Olink Target platform. BPL-related changes in protein detection were evaluated comparing native and BPL-treated states, simulating virus inactivation, and impact on measurable group differences was assessed. While approximately one-third of SomaScan measurements were significantly changed by the BPL treatment, a majority of antigen/aptamer interactions remained unaffected. Interaction effects of BPL treatment and disease state, potentially altering detectability of group differences, were observable for less than one percent of targets (0.6%). BPL effects on protein detection with Olink Target were also limited, affecting 3.6% of detected proteins with no observable interaction effects. Thus, effects of BPL treatment only moderately interfere with affinity proteomic detectability of differential protein expression between different experimental groups. Overall, the results prove high-throughput affinity proteomics well suited for the analysis of high-risk samples inactivated using BPL.

Type X collagen knockdown inactivate ITGB1/PI3K/AKT to suppress chronic unpredictable mild stress-stimulated triple-negative breast cancer progression

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer, has a poor prognosis and limited access to efficient targeted treatments. Chronic unpredictable mild stress (CUMS) is highly risk factor for TNBC occurrence and development. Type X collagen (COL10A1), a crucial protein component of the extracellular matrix, ranks second among all aberrantly expressed genes in TNBC, and it is significantly up-regulated under CUMS. Nevertheless, the impact of CUMS and COL10A1 on TNBC, along with the underlying mechanisms are still unclear. In this research, we studied the effect of CUMS-induced norepinephrine (NE) elevation on TNBC, and uncovered that it notably enhanced TNBC cell proliferation, migration, and invasion in vitro, and also fostering tumor growth and lung metastasis in vivo. Additionally, our investigation found that COL10A1 directly interacted with integrin subunit beta 1 (ITGB1), then activates the downstream PI3K/AKT signaling pathway, thereby promoting TNBC growth and metastasis, while it was reversed by knocking down of COL10A1 or ITGB1. Our study demonstrated that the TNBC could respond to CUMS, and advocate for COL10A1 as a pivotal therapeutic target in TNBC treatment.

Upregulation of collagen type X alpha 1 promotes the progress of triple-negative breast cancer via Wnt/β-catenin signaling

Triple-negative breast cancer (TNBC) is a malignant tumor with high degree of malignancy and lack of effective target treatment. The research aims to explore the role and mechanism of X collagen alpha-1 chain protein (COL10A1 gene) in TNBC. UALCAN and Kaplan-Meier were used to detect the expression of COL10A1 and its role in the prognosis of breast cancer patients. The cells with stably expressing high levels of COL10A1 were obtained by recombinant lentivirus infection. The expression of COL10A1 in cells was temporarily downregulated by siRNA interference fragments. Real-time quantitative polymerase chain reaction and western blot analysis were utilized to detect the changes of COL10A1 mRNA and protein expression. The biological functions of the cells were evaluated by colony formation, cell counting kit-8, cell invasion and wound healing experiments. In addition, the effect of COL10A1 on angiogenesis was investigated by tube formation assay. Xenograft tumor model was used to confirm the effect of COL10A1 on tumorigenicity in vivo and multiplex fluorescent immunohistochemistry to detect multiple proteins simultaneously. The possible molecular mechanism of the function of COL10A1 was speculated through the detection of proteins in functionally related pathways. COL10A1 is highly expressed and is significantly associated with worse overall survival (OS) and recurrence-free survival (RFS) in TNBC. Overexpression of COL10A1 increased the clone formation rate and cell migration capacity of TNBC cells. In the COL10A1 overexpression group, the clone formation rates of MD-MB-231 and BT-549 cells (21.5 ± 0.62, 27.83 ± 3.72)% were significantly higher than those in the control group(15.23 ± 2.79, 19.4 ± 1.47)%, and the relative migration ratio (47.40 ± 3.09, 41.26 ± 4.33)% were higher than those in the control group (34.48 ± 2.03, 21.80 ± 1.03)%. When the expression of COL10A1 was downregulated, the ability of clone formation and wound-healing migration capacity in TNBC cells was weakened. Upregulated COL10A1 in TNBC cells generated more junctions and longer total segments between vascular endothelial cells, and promoted angiogenesis of the cells, and thus enhanced the tumorigenesis. In TNBC, it was found that COL10A1 might affect epithelial-mesenchymal transition (EMT) of the cells through Wnt/β-catenin signaling pathway by the detection of the related pathway proteins. COL10A1 is highly expressed in TNBC, and its high expression leads to poor OS and RFS. COL10A1 may enhance TNBC cell proliferation, migration and tumor-related angiogenesis, and promote tumorigenesis in vivo via Wnt/β-catenin signaling.

Unveiling Collagen's Role in Breast Cancer: Insights into Expression Patterns, Functions and Clinical Implications

Collagen, the predominant protein constituent of the mammalian extracellular matrix (ECM), comprises a diverse family of 28 members (I-XXVIII). Beyond its structural significance, collagen is implicated in various diseases or cancers, notably breast cancer, where it influences crucial cellular processes including proliferation, metastasis, apoptosis, and drug resistance, intricately shaping cancer progression and prognosis. In breast cancer, distinct collagens exhibit differential expression profiles, with some showing heightened or diminished levels in cancerous tissues or cells compared to normal counterparts, suggesting specific and pivotal biological functions. In this review, we meticulously analyze the expression of individual collagen members in breast cancer, utilizing Transcripts Per Million (TPM) data sourced from the GEPIA2 database. Through this analysis, we identify collagens that deviate from normal expression patterns in breast cancer, providing a comprehensive overview of their expression dynamics, functional roles, and underlying mechanisms. Our findings shed light on recent advancements in understanding the intricate interplay between these aberrantly expressed collagens and breast cancer. This exploration aims to offer valuable insights for the identification of potential biomarkers and therapeutic targets, thereby advancing the prospects of more effective interventions in breast cancer treatment.

COL10A1 as a Prognostic Biomarker in Association with Immune Infiltration in Prostate Cancer

BACKGROUND

The collagen type X alpha 1 (COL10A1) has recently been found to play an important role in the development and progression of cancer. However, the link between COL10A1 and the tumor immune microenvironment remains understood scantily.

METHODS

In the current study, the pan-cancer data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used to investigate the expression mode, the clinical prognostic and diagnostic value of COL10A1 in different tumors. We used TCGA data to assess the correlations between COL10A1 and clinical symptoms of prostate cancer. The R packages "edgR" and "clusterProfiler" were used for differential expression gene and enrichment analysis of COL10A1. Immunohistochemistry was further employed to corroborate the expression of COL10A1 gene in prostate cancer. After that, we used TIMER to evaluate the pertinence of COL10A1 expression to immune infiltration level in prostate cancer.

RESULTS

On the whole, COL10A1 was expressed at significantly higher levels in a variety of tumor tissues than in the corresponding normal tissues. Besides, significant correlations with tumor prognosis and relative exactitude in predicting tumors show that COL10A1 may be a probable prognostic and diagnostic biomarker of prostate cancer. In addition, the evidence indicates a significant correlation between COL10A1 and clinical symptoms of prostate cancer. Furthermore, the main molecular functions of COL10A1 included humoral immune response, complement activation, immunoglobulin, regulation of complement activation, and regulation of humoral immune response. Finally, we found that COL10A1 expression is positively correlated with enhanced macrophage and M2 macrophage infiltration in prostate cancer.

CONCLUSION

The study indicates that COL10A1 might participate in M2 macrophage polarization in prostate cancer. COL10A1 might be an innovative biomarker to evaluate tumor microenvironment immune cell infiltration and prognosis in prostate cancer.

Experimental validation and pan-cancer analysis identified COL10A1 as a novel oncogene and potential therapeutic target in prostate cancer

BACKGROUND

Type X collagen (COL10) is a homologous trimeric non-fibrillar collagen found in the extracellular matrix of human tissues, and it exhibits a distinctive white appearance. Type X collagen α1 chain (COL10A1) is a specific cleaved fragment of type X collagen. However, the expression, prognostic significance, clinicopathological attributes and immune-related associations of COL10A1 in prostate cancer as well as in pan-cancer contexts remain poorly understood.

METHODS

Using bioinformatic analysis of data from the most recent databases (TCGA, GTEx and GEO databases), we have extensively elucidated the role played by COL10A1 in terms of its expression patterns, prognostic implications, and immune efficacy across a pan-cancer spectrum. Subsequently, the biological functions of COL10A1 in prostate cancer were elucidated by experimental validation.

RESULTS

Our findings have confirmed that COL10A1 was highly expressed in most cancers and was associated with poorer prognosis in cancer patients. Immune correlation analysis of COL10A1 in various cancers showed its significant correlation with Tumor mutational burden (TMB), microsatellite instability (MSI) and immune cell infiltration. In addition, knockdown of COL10A1 in prostate cancer resulted in a substantial reduction in the proliferation, migration, and invasive potential of prostate cancer cells.

CONCLUSION

Our pan-cancer analysis of COL10A1 gene provided novel insights into its pivotal role in cancer initiation, progression, and therapeutic implications, underscoring its potential significance in prognosis and immunotherapeutic interventions for cancer, particularly prostate cancer.

COL10A1 promotes tumorigenesis by modulating CD276 in pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PAAD) is a lethal malignant tumour. Further study is needed to determine the molecular mechanism and identify novel biomarkers of PAAD.

METHODS

Gene expression data from the GSE62165 microarray were analysed with the online software Morpheus to identify differentially expressed genes (DEGs). The STRING database was used to generate a protein‒protein interaction (PPI) network for these DEGs. Hub genes were identified with Cytoscape. COL10A1 expression in PAAD was analysed via the GEPIA database. COL10A1 expression in pancreatic cancer cell lines was measured by using qRT‒PCR. The LinkedOmics database was utilized to perform survival analysis of pancreatic adenocarcinoma patients grouped based on COL10A1 expression level. CCK-8, wound healing, and Transwell assays were used to study the role of COL10A1 in pancreatic cancer cell viability, migration, and invasion. Differentially expressed genes that were related to COL10A1 in PAAD were analysed via the LinkedOmics portal. After COL10A1 was knocked down, CD276 expression was assessed by western blotting.

RESULTS

COL10A1 was identified as one of the hub genes in PAAD by bioinformatics analysis of the GSE62165 microarray with Morpheus, the STRING database and Cytoscape. GEPIA revealed elevated expression of COL10A1 in PAAD samples vs. normal samples. COL10A1 expression was also increased in pancreatic cancer cells vs. control cells. Survival analysis of PAAD patients via LinkedOmics revealed that high expression of COL10A1 was associated with a poorer prognosis. Knockdown of COL10A1 inhibited the proliferation, migration, and invasion of cells in functional assays. Furthermore, mechanistic studies indicated that CD276 was a target of COL10A1 and that knockdown of COL10A1 decreased CD276 expression. Overexpression of CD276 in cells reversed COL10A1 knockdown-induced repression of proliferation and migration.

CONCLUSIONS

Our research suggests that COL10A1 promotes pancreatic adenocarcinoma tumorigenesis by regulating CD276. This study provides new insight into biomarkers and possible targets for pancreatic cancer treatment.

COL10A1 is a potential immunotherapy biomarker associated with immune infiltration and deficient mismatch repair in colon cancer

Aim: Our study aimed to identify the role of COL10A1 in colon cancer, including interaction with immune infiltrates and somatic mutations. Methods: COL10A1 expression and prognostic value were assessed. Correlations between COL10A1 and various immune parameters were conducted by bioinformatic analysis. Results: Our study demonstrated that COL10A1 is overexpressed in colon cancer and correlates with poor patient survival. The expression level of COL10A1 is significantly associated with mismatch repair deficiency and immune infiltration. High expression of COL10A1 may confer greater sensitivity to anti-PD-1 treatment in colon cancer patients. Conclusion: COL10A1 is a potential diagnostic biomarker associated with deficient mismatch repair and immune infiltration in colon cancer.

Deep immunophenotyping reveals clinically distinct cellular states and ecosystems in large-scale colorectal cancer

Determining the diverse cell types in the tumor microenvironment (TME) and their organization into cellular communities, is critical for understanding the biological heterogeneity and therapy of cancer. Here, we deeply immunophenotype the colorectal cancer (CRC) by integrative analysis of large-scale bulk and single cell transcriptome of 2350 patients and 53,137 cells. A rich landscape of 42 cellular states and 7 ecosystems in TMEs is uncovered and extend the previous immune classifications of CRC. Functional pathways and potential transcriptional regulators analysis of cellular states and ecosystems reveal cancer hallmark-related pathways and several critical transcription factors in CRC. High-resolution characterization of the TMEs, we discover the potential utility of cellular states (i.e., Monocytes/Macrophages and CD8 T cell) and ecosystems for prognosis and clinical therapy selection of CRC. Together, our results expand our understanding of cellular organization in TMEs of CRC, with potential implications for the development of biomarkers and precision therapies.

Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods

Breast cancer is one of the most prevalent types of cancer diagnosed globally and continues to have a significant impact on the global number of cancer deaths. Despite all efforts of epidemiological and experimental research, therapeutic concepts in cancer are still unsatisfactory. Gene expression datasets are widely used to discover the new biomarkers and molecular therapeutic targets in diseases. In the present study, we analyzed four datasets using R packages with accession number GSE29044, GSE42568, GSE89116, and GSE109169 retrieved from NCBI-GEO and differential expressed genes (DEGs) were identified. Protein-protein interaction (PPI) network was constructed to screen the key genes. Subsequently, the GO function and KEGG pathways were analyzed to determine the biological function of key genes. Expression profile of key genes was validated in MCF-7 and MDA-MB-231 human breast cancer cell lines using qRT-PCR. Overall expression level and stage wise expression pattern of key genes was determined by GEPIA. The bc-GenExMiner was used to compare expression level of genes among groups of patients with respect to age factor. OncoLnc was used to analyze the effect of expression levels of LAMA2, TIMP4, and TMTC1 on the survival of breast cancer patients. We identified nine key genes, of which COL11A1, MMP11, and COL10A1 were found up-regulated and PCOLCE2, LAMA2, TMTC1, ADAMTS5, TIMP4, and RSPO3 were found down-regulated. Similar expression pattern of seven among nine genes (except ADAMTS5 and RSPO3) was observed in MCF-7 and MDA-MB-231 cells. Further, we found that LAMA2, TMTC1, and TIMP4 were significantly expressed among different age groups of patients. LAMA2 and TIMP4 were found significantly associated and TMTC1 was found less correlated with breast cancer occurrence. We found that the expression level of LAMA2, TIMP4, and TMTC1 was abnormal in all TCGA tumors and significantly associated with poor survival.

Identification of molecularly unique tumor-associated mesenchymal stromal cells in breast cancer patients

The tumor microenvironment is a complex mixture of cell types that bi-directionally interact and influence tumor initiation, progression, recurrence, and patient survival. Mesenchymal stromal cells (MSCs) of the tumor microenvironment engage in crosstalk with cancer cells to mediate epigenetic control of gene expression. We identified CD90+ MSCs residing in the tumor microenvironment of patients with invasive breast cancer that exhibit a unique gene expression signature. Single-cell transcriptional analysis of these MSCs in tumor-associated stroma identified a distinct subpopulation characterized by increased expression of genes functionally related to extracellular matrix signaling. Blocking the TGFβ pathway reveals that these cells directly contribute to cancer cell proliferation. Our findings provide novel insight into communication between breast cancer cells and MSCs that are consistent with an epithelial to mesenchymal transition and acquisition of competency for compromised control of proliferation, mobility, motility, and phenotype.

Identification of functional gene modules by integrating multi-omics data and known molecular interactions

Multi-omics data integration has emerged as a promising approach to identify patient subgroups. However, in terms of grouping genes (or gene products) into co-expression modules, data integration methods suffer from two main drawbacks. First, most existing methods only consider genes or samples measured in all different datasets. Second, known molecular interactions (e.g., transcriptional regulatory interactions, protein-protein interactions and biological pathways) cannot be utilized to assist in module detection. Herein, we present a novel data integration framework, Correlation-based Local Approximation of Membership (CLAM), which provides two methodological innovations to address these limitations: 1) constructing a trans-omics neighborhood matrix by integrating multi-omics datasets and known molecular interactions, and 2) using a local approximation procedure to define gene modules from the matrix. Applying Correlation-based Local Approximation of Membership to human colorectal cancer (CRC) and mouse B-cell differentiation multi-omics data obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomics Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO) and ProteomeXchange database, we demonstrated its superior ability to recover biologically relevant modules and gene ontology (GO) terms. Further investigation of the colorectal cancer modules revealed numerous transcription factors and KEGG pathways that played crucial roles in colorectal cancer progression. Module-based survival analysis constructed four survival-related networks in which pairwise gene correlations were significantly correlated with colorectal cancer patient survival. Overall, the series of evaluations demonstrated the great potential of Correlation-based Local Approximation of Membership for identifying modular biomarkers for complex diseases. We implemented Correlation-based Local Approximation of Membership as a user-friendly application available at https://github.com/free1234hm/CLAM.

Mining TCGA Database for Genes with Prognostic Value in Breast Cancer

The aim of the study was to use transcriptomics data to identify genes associated with advanced/aggressive breast cancer and their effect on survival outcomes. We used the publicly available The Cancer Genome Atlas (TCGA) database to obtain RNA sequence data from patients with less than five years survival (Poor Prognosis, n = 101), patients with greater than five years survival (Good Prognosis, n = 200), as well as unpaired normal tissue data (normal, n = 105). The data analyses performed included differential expression between groups and selection of subsets of genes, gene ontology, cell enrichment analysis, and survival analyses. Gene ontology results showed significantly reduced enrichment in gene sets related to tumor immune microenvironment in Poor Prognosis and cell enrichment analysis confirmed significantly reduced numbers of macrophages M1, CD8 T cells, plasma cells and dendritic cells in samples in the Poor Prognosis samples compared with Good Prognosis. A subset of 742 genes derived from differential expression analysis as well as genes coding for immune checkpoint molecules was evaluated for their effect on overall survival. In conclusion, this study may contribute to the better understanding of breast cancer transcriptomics and provide possible targets for further research and eventual therapeutic interventions.

Synergistic effect of sodium butyrate and oxaliplatin on colorectal cancer

BACKGROUND

Oxaliplatin (OXA) is a chemotherapy agent commonly used in the treatment of colorectal cancer (CRC). Sodium butyrate (NaB) has an antitumor effect.

METHODS

In total, 30 patients in stage III who completed 8 cycles of chemotherapy regimens were recruited for this study. The patients were divided into good and bad groups based on the chemotherapy efficacy. Gas chromatography-mass spectrometry (GC/MS) was used to detect microbial metabolites in stool samples from CRC patients. Cell counting kit-8 (CCK-8), Annexin-V APC/7-AAD double staining, Transwell assays, scratch-wound assays, and EdU assays were used to detect cell proliferation, apoptosis, invasion and migration, respectively. Fluoroelectron microscopy was used to observe the cell structures. To verify the inhibitory effect of NaB and OXA at animal level, a subcutaneous transplanted tumor model was established. Finally, 16S sequencing technology was used to detect intestinal bacteria. GC-MS was used to detect metabolites in mouse stools.

RESULTS

NaB was a differential metabolite that affected the efficacy of OXA. NAB and oxaliplatin can synergically inhibit cell proliferation, migration and invasion, and induce cell apoptosis. Animal experiments confirmed the inhibitory effect of oxaliplatin and sodium butyrate on tumor in mice. In addition, the intestinal microbe detection and microbial metabolite detection in fecal samples from mice showed significant differences between butyrate-producing bacteria and NaB.

CONCLUSION

NaB and OXA can synergistically inhibit the proliferation, invasion and metastasis of CRC cells and promote the apoptosis of CRC cells. NaB, as an OXA synergist, has the potential to become a new clinical adjuvant in CRC chemotherapy.

COL10A1-DDR2 axis promotes the progression of pancreatic cancer by regulating MEK/ERK signal transduction

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant tumors with a poor prognosis. Type X collagen α 1 chain (COL10A1), a member of the collagen family, is a gene associated with the progression of a variety of human tumors, but the specific function and molecular mechanism of COL10A1 in pancreatic cancer remain unclear. Our study found that COL10A1 is highly expressed in pancreatic cancer cells and tissues, and its high expression is related to poor prognosis and some clinicopathological features, such as tumor size and differentiation. Biological functional experiments showed that overexpression of COL10A1 enhanced the proliferation and migration of PDAC cells. Interestingly, discoid protein domain receptor 2 (DDR2), the receptor of COL10A1, is regulated by COL10A1. We found that the COL10A1-DDR2 axis activates the mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway, which leads to epithelial-mesenchymal transformation (EMT) and accelerates the progression of pancreatic cancer. In summary, COL10A1 regulates PDAC cell proliferation and MEK/ERK signaling pathways by binding to DDR2 to promote migration, invasion and EMT. Our study suggested that COL10A1 might be a critical factor in promoting PDAC progression. More research is needed to confirm COL10A1 as a potential biomarker and therapeutic target for PDAC.

Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer

Colorectal cancer (CRC) is a leading cause of death from cancer in Canada. Early detection of CRC remains crucial in managing disease prognosis and improving patient survival. It can also facilitate prevention, screening, and treatment before the disease progresses to a chronic stage. In this study, we developed a strategy for identifying colon cancer biomarkers from both gene expression and gene pair correlation. Using the RNA-Seq dataset TCGA-COAD, a panel of 71 genes, including the 20 most upregulated genes, 20 most downregulated genes and 31 genes involved in the most significantly altered gene pairs, were selected as potential biomarkers for colon cancer. This signature set of genes could be used for early diagnosis. Furthermore, this strategy could be applied to other types of cancer.

High expression COL10A1 promotes breast cancer progression and predicts poor prognosis

Background

As a common malignant disease in females, breast cancer (BCa) causes increasing numbers of cancer-related death. Collagen X alpha 1 chain (COL10A1) plays a critical role in the oncogenesis and progression of malignant tumors. However, a systematic analysis of COL10A1 in BCa has not been conducted.

Methods

The COL10A1 expression level and prognostic value in BCa were defined through the Cancer Genome Atlas (TCGA) as well as the Kaplan-Meier plotter data respectively. The expression pattern of COL10A1 was subsequently confirmed on tissue microarray (TMA) by immunochemistry (IHC) staining. Moreover, cellular functional assays which aimed to evaluate cell proliferation, migration, invasion, and apoptosis, were conducted to investigate the oncogenic activity of COL10A1 in BCa. Then, Tumor Immune Estimation Resource (TIMER) was adopted to determine the association between COL10A1 expression and immune cell infiltration.

Results

Bioinformatics analysis revealed that COL10A1 was significantly overexpressed and had notable prognostic value, especially for distant metastasis-free survival (DMFS) in BCa. Moreover, IHC analysis of 140 BCa tissues on TMA chips exhibited the overexpression of COL10A1 was correlated to advanced clinical stage, poor overall survival (OS), and worse recurrence-free survival (RFS). Besides, knockdown of COL10A1 remarkably suppressed cell proliferation, migration, and invasion in BCa cells, and notably promoted cell apoptosis as well. Furthermore, COL10A1 was positively associated with immune cell infiltration including B cell, CD8⁺ T cell, CD4⁺ T cell, macrophage, neutrophil, and dendritic cell.

Conclusion

The results revealed that COL10A1 is a novel oncogene and could serve as a potential prognostic biomarker in BCa. Besides, the downregulation of COL10A1 could inhibit BCa progression, which could be a potential target for BCa therapy.

Collagen Family as Promising Biomarkers and Therapeutic Targets in Cancer

Despite advances in cancer detection and therapy, it has been estimated that the incidence of cancers will increase, while the mortality rate will continue to remain high, a fact explained by the large number of patients diagnosed in advanced stages when therapy is often useless. Therefore, it is necessary to invest knowledge and resources in the development of new non-invasive biomarkers for the early detection of cancer and new therapeutic targets for better health management. In this review, we provided an overview on the collagen family as promising biomarkers and on how they may be exploited as therapeutic targets in cancer. The collagen family tridimensional structure, organization, and functions are very complex, being in a tight relationship with the extracellular matrix, tumor, and immune microenvironment. Moreover, accumulating evidence underlines the role of collagens in promoting tumor growth and creating a permissive tumor microenvironment for metastatic dissemination. Knowledge of the molecular basis of these interactions may help in cancer diagnosis and prognosis, in overcoming chemoresistance, and in providing new targets for cancer therapies.

High Expression of COL10A1 Is an Independent Predictive Poor Prognostic Biomarker and Associated with Immune Infiltration in Advanced Gastric Cancer Microenvironment

Medical technology has become more and more sophisticated recently, which, however, fails to contribute to a better prognosis for patients suffering advanced gastric cancer (GC). Hence, new biomarkers specific to GC diagnosis and prognosis shall be identified urgently. This study screened differentially expressed genes (DEGs) between 375 GC samples and 32 paracancer tissue samples from TCGA datasets. The expression of Collagen type X alpha 1 (COL10A1) in GC was analyzed. The chi-square test assisted in analyzing the relevance of COL10A1 to the clinicopathologic characteristics. The Kaplan-Meier method helped to assess the survival curves and log-rank tests assisted in the examination of the differences. The Cox proportional hazard regression model served for analyzing the risk factors for GC. Then, we developed a nomogram that contained the COL10A1 expression and clinical information. Finally, how COL10A1 expression was associated with the immune infiltration was also evaluated. In this study, 7179 upregulated and 3771 downregulated genes were identified. Among them, COL10A1 expression was distinctly increased in GC specimens compared with nontumor specimens. High COL10A1 expression exhibited an obvious relation to tumor T and pathologic stage. ROC assays confirmed the diagnostic value of COL10A1 expression in screening GC samples from normal samples. Survival data displayed that patients with high COL10A1 expression exhibited a shorter OS and DSS than those with low COL10A1 expression. We obtained a predictive nomogram, which could better predict the COL10A1 expression by virtue of discrimination and calibration. The prognostic value of COL10A1 expression was further confirmed in GSE84426 datasets. Immune assays revealed that COL10A1 expression was associated with tumor-filtrating immune cells, like CD8 T cells, cytotoxic cells, DC, eosinophils, iDC, macrophages, mast cells, NK CD56dim cells, NK cells, pDC, T helper cells, Tem, Th1 cells, Th17 cells, and Treg. Overall, we firstly proved that COL10A1 may be a novel and valuable prognostic and diagnostic factor for GC patients. In addition, COL10A1 has potential to be an immune indicator in GC.

Cancer-Associated Fibroblasts Hinder Lung Squamous Cell Carcinoma Oxidative Stress-Induced Apoptosis via METTL3 Mediated m6A Methylation of COL10A1

Background. Cancer-associated fibroblasts (CAFs) within the tumor microenvironment are key players in tumorigenesis and tumor development. Nevertheless, the regulatory mechanisms of CAFs on lung squamous cell carcinoma- (LUSC-) associated remain poorly elucidated. Methods. The microarray dataset GSE22874, containing 30 specimens of primary culture of normal fibroblasts (NFs) and 8 specimens of cancer-associated fibroblasts (CAFs) samples derived from LUSC, was retrieved from the Gene Expression Omnibus (GEO) database and then calculated by using the R language (limma package) to identify differentially expressed genes (DEGs). CAF-conditioned medium (CAF-CM) was collected and used to culture LUSC cells, followed by assessment of cell proliferation, apoptosis, and oxidative stress levels by using CCK-8, annexin V-FITC/PI double staining and ELISA assays. Subsequently, COL10A1 was knocked down in CAFs to assess the role of COL10A1 in CAF regulation of LUSC behavior. Bioinformatics online analysis and MeRIP were applied to predict and test the m6A modification of COL10A1 mRNA and the regulatory relationship with METTL3. Rescue experiments were next performed to explore the effects of METTL3 and COL10A1 in CAFs on LUSC cell proliferation, apoptosis, and oxidative stress. LUSC tumor cells with or without (COL10A1-silenced) CAFs were subcutaneously inoculated in nude mice to evaluate the effect of COL10A1 in CAFs on LUSC tumor growth. Results. Elevated expression of COL10A1 was found in LUSC-derived CAFs by GSE22874 dataset analysis. We discovered that COL10A1 and METTL3 was expressed in both LUSC cells and matched CAFs, while COL10A1 expression was prominently higher in CAFs than in LUSC cells. CAF-CM memorably encouraged LUSC cell proliferation and suppressed apoptosis-induced oxidative stress, which was reversed by interfering with COL10A1 expression in CAFs, suggesting that COL10A1 might be secreted by CAFs into the culture medium to exert its effects inside LUSC cells. Global m6A modification was decreased in METTL3 knocked down CAFs. M6A modification, expression levels, and stability of COL10A1 mRNA were impaired upon METTL3 knockdown in CAFs. Overexpression of COL10A1 in CAFs partially reversed the effect of METTL3 knockdown on the malignant behavior of LUSC cells. In vivo studies confirmed that CAFs accelerated LUSC tumor growth, and this effect was counteracted by COL10A1 silencing. Conclusions. COL10A1 secreted by CAFs could facilitate LUSC cell proliferation and repress apoptosis-induced oxidative stress, and the mechanism was due to elevated expression mediated by METTL3 promoting its mRNA m6A modification, thereby accelerating tumor growth.

COL10A1 allows stratification of invasiveness of colon cancer and associates to extracellular matrix and immune cell enrichment in the tumor parenchyma

Background

Treatment options for metastatic colorectal cancer (CRC) are mostly ineffective. We present new evidence that tumor tissue collagen type X alpha 1 (COL10A1) is a relevant candidate biomarker to improve this dilemma.

Methods

Several public databases had been screened to observe COL10A1 expression in transcriptome levels with cell lines and tissues. Protein interactions and alignment to changes in clinical parameters and immune cell invasion were performed, too. We also used algorithms to build a novel COL10A1-related immunomodulator signature. Various wet-lab experiments were conducted to quantify COL10A1 protein and transcript expression levels in disease and control cell models.

Results

COL10A1 mRNA levels in tumor material is clinical and molecular prognostic, featuring upregulation compared to non-cancer tissue, increase with histomorphological malignancy grading of the tumor, elevation in tumors that invade perineural areas, or lymph node invasion. Transcriptomic alignment noted a strong positive correlation of COL10A1 with transcriptomic signature of cancer-associated fibroblasts (CAFs) and populations of the immune compartment, namely, B cells and macrophages. We verified those findings in functional assays showing that COL10A1 are decreased in CRC cells compared to fibroblasts, with strongest signal in the cell supernatant of the cells.

Conclusion

COL10A1 abundance in CRC tissue predicts metastatic and immunogenic properties of the disease. COL10A1 transcription may mediate tumor cell interaction with its stromal microenvironment.

Modulation of the extracellular matrix by Streptococcus gallolyticus subsp. gallolyticus and importance in cell proliferation

Streptococcus gallolyticus subspecies gallolyticus (Sgg) has a strong clinical association with colorectal cancer (CRC) and actively promotes the development of colon tumors. Previous work showed that this organism stimulates CRC cells proliferation and tumor growth. However, the molecular mechanisms underlying these activities are not well understood. Here, we found that Sgg upregulates the expression of several type of collagens in HT29 and HCT116 cells, with type VI collagen (ColVI) being the highest upregulated type. Knockdown of ColVI abolished the ability of Sgg to induce cell proliferation and reduced the adherence of Sgg to CRC cells. The extracellular matrix (ECM) is an important regulator of cell proliferation. Therefore, we further examined the role of decellularized matrix (dc-matrix), which is free of live bacteria or cells, in Sgg-induced cell proliferation. Dc-matrix prepared from Sgg-treated cells showed a significantly higher pro-proliferative activity than that from untreated cells or cells treated with control bacteria. On the other hand, dc-matrix from Sgg-treated ColVI knockdown cells showed no difference in the capacity to support cell proliferation compared to that from untreated ColVI knockdown cells, suggesting that the ECM by itself is a mediator of Sgg-induced cell proliferation. Furthermore, Sgg treatment of CRC cells but not ColVI knockdown CRC cells resulted in significantly larger tumors in vivo, suggesting that ColVI is important for Sgg to promote tumor growth in vivo. These results highlight a dynamic bidirectional interplay between Sgg and the ECM, where Sgg upregulates collagen expression. The Sgg-modified ECM in turn affects the ability of Sgg to adhere to host cells and more importantly, acts as a mediator for Sgg-induced CRC cell proliferation. Taken together, our results reveal a novel mechanism in which Sgg stimulates CRC proliferation through modulation of the ECM.

Bioinformatics-Based Analysis: Noncoding RNA-Mediated COL10A1 Is Associated with Poor Prognosis and Immune Cell Infiltration in Pancreatic Cancer

Background. Collagen type X alpha 1 (COL10A1) is a structural component of the extracellular matrix that is aberrantly expressed in a variety of cancer tissues. However, its role in pancreatic cancer progression is not well understood. Methods. The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Gene Expression Profiling Interaction Analysis (GEPIA) data were employed to explore the expression of COL10A1 in normal and tumor tissues and its prognostic value in pancreatic adenocarcinoma. The clinical data of pancreatic cancer in TCGA were used to explore the relationship between COL10A1 and clinical features. Genes coexpressed with COL10A1 were explored using multiple databases and analyzed for functional enrichment. In addition, the lncRNA/miRNA/COL10A1 axis that may be involved in COL10A1 regulation in pancreatic cancer was explored by constructing a competitive endogenous RNA (ceRNA) regulatory axis. Finally, COL10A1 was analyzed for correlation with immune cell infiltration and various immune checkpoint molecules in pancreatic cancer. Results. It was found that the expression of COL10A1 was significantly increased in pancreatic cancer tissues. High expression of COL10A1 was related to the clinicopathological characteristics and the worse prognosis of pancreatic cancer patients. The TUG1/miR-144-3p/COL10A1 axis was identified as the most likely upstream noncoding RNA pathway for COL10A1 in pancreatic cancer. Besides, in pancreatic adenocarcinoma, the expression level of COL10A1 showed a significant positive correlation with tumor immune cell infiltration, biomarkers of immune cells, and expression of immune checkpoint molecules. Conclusion. COL10A1 is an early diagnostic marker, and its high expression correlates with immune infiltration in pancreatic cancer. The TUG1/miR-144-3p/COL10A1 axis was identified as the most likely upstream noncoding RNA pathway for COL10A1 in pancreatic cancer.

High COL10A1 expression potentially contributes to poor outcomes in gastric cancer with the help of LEF1 and Wnt2

Background

COL10A1 is a secreted, short‐chain collagen found in several types of cancer. Studies have shown that COL10A1 aberrant expression is considered an oncogenic factor. However, its underlying mechanisms and regulation of gastric cancer remain undefined.

Methods

The data on the expression of COL10A1, clinicopathological characteristics, and outcome of patients with GC were obtained from The Cancer Genome Atlas. The ALGGEN‐PROMO database defined the related transcription factors. Quantitative real‐time reverse transcription‐polymerase chain reaction and western blotting analysis were used to identify the differential expression levels of COL10A1 and related transcription factors.

Results

We found that high COL10A1 expression is an independent risk factor for gastric cancer. Upregulation of LEF1 and Wnt2 was also observed in gastric cancer, suggesting a potential correlation between LEF1/COL10A1 regulation in the Wnt2 signaling pathway.

Conclusion

High COL10A1 expression may contribute to poor outcomes via upregulation of LEF1 and Wnt2 in gastric cancer.

Mechanisms for Host Immune Evasion Mediated by Plasmodium falciparum-Infected Erythrocyte Surface Antigens

Plasmodium falciparum infection causes the most severe form of malaria. It has been hypothesized that P. falciparum directly suppresses host immune responses because sufficient acquired immunity is often not induced even by repeated P. falciparum infections in malaria-endemic areas. It is known that many kinds of P. falciparum-derived proteins are expressed on the surface of P. falciparum-infected erythrocytes (IEs), and these proteins have long been thought to be a key to the elucidation of the host immune evasion mechanisms. Our recent studies have revealed that the P. falciparum-derived erythrocyte surface antigen, RIFIN, the largest multiple gene family protein in the P. falciparum genome, suppresses host immune cell activation through direct interaction with human inhibitory immune receptors. In this review, we will discuss the molecular mechanisms for host immune evasion by P. falciparum-infected erythrocyte surface antigens. In addition, we will discuss the recently identified host immune response to P. falciparum using specialized antibodies that target host-P. falciparum-derived molecule interactions.

Collagen type X alpha 1 promotes proliferation, invasion and epithelial-mesenchymal transition of cervical cancer through activation of TGF-β/Smad signaling

Background

Collagen type X alpha 1 (COL10A1) belongs to the collagen family and constitutes the main component of the interstitial matrix. COL10A1 was found to be dysregulated in various cancers, and to participate in tumorigenesis. However, the role of COL10A1 in cervical cancer (CC) remains unclear.

Methods

Expression of COL10A1 in CC cells and tissues was detected by western blot and qRT-PCR. CC cells were transfected with pcDNA-COL10A1 or si-COL10A1, and the effect of COL10A1 on cell proliferation of CC was assessed by MTT and colony formation assays. Cell metastasis was detected by wound healing and transwell assays. Western blot was applied to evaluate epithelial-mesenchymal transition.

Results

COL10A1 was significantly elevated in CC tissues and cells (P < 0.001). Over-expression of COL10A1 increased cell viability of CC (P < 0.001), and enhanced the number of colonies (P < 0.001). However, knockdown of COL10A1 reduced the cell proliferation of CC (P < 0.001). Over-expression of COL10A1 also promoted cell migration (P < 0.001) and invasion (P < 0.001) of CC, whereas silencing of COL10A1 suppressed cell metastasis (P < 0.001). Protein level of E-cadherin in CC was reduced (P < 0.05), whereas N-cadherin and vimentin were enhanced by COL10A1 over-expression (P < 0.001). Silencing of COL10A1 reduced the protein level of TGF-β1 (P < 0.01), and down-regulated the phosphorylation of Smad2 and Smad3 in CC (P < 0.001).

Conclusion

Down-regulation of COL10A1 suppressed cell proliferation, metastasis, and epithelial-mesenchymal transition of CC through inactivation of TGF-β/Smad signaling.

Collagen Family and Other Matrix Remodeling Proteins Identified by Bioinformatics Analysis as Hub Genes Involved in Gastric Cancer Progression and Prognosis

Gastric cancer has remained in the top five cancers for over ten years, both in terms of incidence and mortality due to the shortage of biomarkers for disease follow-up and effective therapies. Aiming to fill this gap, we performed a bioinformatics assessment on our data and two additional GEO microarray profiles, followed by a deep analysis of the 40 differentially expressed genes identified. PPI network analysis and MCODE plug-in pointed out nine upregulated hub genes coding for proteins from the collagen family (COL12A1, COL5A2, and COL10A1) or involved in the assembly (BGN) or degradation of collagens (CTHRC1), and also associated with cell adhesion (THBS2 and SPP1) and extracellular matrix degradation (FAP, SULF1). Those genes were highly upregulated at the mRNA and protein level, the increase being correlated with pathological T stages. The high expression of BGN (p = 8 × 10⁻¹²), THBS2 (p = 1.2 × 10⁻⁶), CTHRC1 (p = 1.1 × 10⁻⁴), SULF1 (p = 3.8 × 10⁻⁴), COL5A1 (p = 1.3 × 10⁻⁴), COL10A1 (p = 5.7 × 10⁻⁴), COL12A1 (p = 2 × 10⁻³) correlated with poor overall survival and an immune infiltrate based especially on immunosuppressive M2 macrophages (p-value range 4.82 × 10⁻⁷–1.63 × 10⁻¹³). Our results emphasize that these genes could be candidate biomarkers for GC progression and prognosis and new therapeutic targets.

COL10A1 is a novel factor in the development of choroidal neovascularization

With the dramatic rise in the aging population, researching age-related macular degeneration (AMD), especially the severe form neovascular AMD (nAMD), has become more important than ever. In this study, we found that collagen type X was increased in retina-choroid tissue of mice with laser-induced choroidal neovascularization (CNV) based on immunohistofluorescence. RNA sequencing and bioinformatic analyses were performed to compare the retina-choroid tissue complex of the CNV mouse model to normal controls. Collagen type X alpha 1 chain (Col10a1) was among the most significantly upregulated genes, and the results were validated with an animal model at the mRNA and protein levels by quantitative real-time polymerase chain reaction (qPCR) and western blotting, respectively. COL10A1 was also upregulated in human retinal microvascular endothelial cells (HRMECs), human umbilical vein endothelial cells (HUVECs), RPE19 cells and RF/6A cells under hypoxic conditions. Next, in vitro and in vivo experiments were performed to study the effect of COL10A1 on neovascularization. siRNA knockdown of COL10A1 suppressed the proliferation and tube formation ability of HRMECs under hypoxic conditions. Snail family transcriptional repressor 1 (SNAIL1) and angiopoietin-2 (ANGPT2) were downregulated in COL10A1 knockdown HRMECs under hypoxic conditions and thus were potential downstream genes. Significant decreases in CNV leakage and CNV lesion area, as assessed by fundus fluorescein angiography (FFA) and immunofluorescence of choroidal flat mounts, respectively, were observed in a mouse model intravitreally injected with anti-collagen X monoclonal antibody (mAb) compared to the controls. In conclusion, COL10A1 promotes CNV formation and may represent a new candidate target for the treatment and diagnosis of nAMD and other neovascular diseases.

Spatial immunophenotypes predict response to anti-PD1 treatment and capture distinct paths of T cell evasion in triple negative breast cancer

Only a subgroup of triple-negative breast cancer (TNBC) responds to immune checkpoint inhibitors (ICI). To better understand lack of response to ICI, we analyze 681 TNBCs for spatial immune cell contextures in relation to clinical outcomes and pathways of T cell evasion. Excluded, ignored and inflamed phenotypes can be captured by a gene classifier that predicts prognosis of various cancers as well as anti-PD1 response of metastatic TNBC patients in a phase II trial. The excluded phenotype, which is associated with resistance to anti-PD1, demonstrates deposits of collagen-10, enhanced glycolysis, and activation of TGFβ/VEGF pathways; the ignored phenotype, also associated with resistance to anti-PD1, shows either high density of CD163+ myeloid cells or activation of WNT/PPARγ pathways; whereas the inflamed phenotype, which is associated with response to anti-PD1, revealed necrosis, high density of CLEC9A+ dendritic cells, high TCR clonality independent of neo-antigens, and enhanced expression of T cell co-inhibitory receptors.

Screening and identification of key biomarkers in alimentary tract cancers: A bioinformatic analysis

BACKGROUND

Alimentary tract cancers (ATCs) are the most malignant cancers in the world. Numerous studies have revealed the tumorigenesis, diagnosis and treatment of ATCs, but many mechanisms remain to be explored.

METHODS

To identify the key genes of ATCs, microarray datasets of oesophageal cancer, gastric cancer and colorectal cancer were obtained from the Gene Expression Omnibus (GEO) database. In total, 207 differentially expressed genes (DEGs) were screened. KEGG and GO function enrichment analyses were conducted, and a protein-protein interaction (PPI) network was generated and gene modules analysis was performed using STRING and Cytoscape.

RESULTS

Five hub genes were screened, and the associated biological processes indicated that these genes were mainly enriched in cellular processes, protein binding and metabolic processes. Clinical survival analysis showed that COL10A1 and KIF14 may be significantly associated with the tumorigenesis or pathology grade of ATCs. In addition, relative human ATC cell lines along with blood samples and tumour tissues of ATC patients were obtained. The data proved that high expression of COL10A1 and KIF14 was associated with tumorigenesis and could be detected in blood.

CONCLUSION

In conclusion, the identification of hub genes in the present study helped us to elucidate the molecular mechanisms of tumorigenesis and identify potential diagnostic indicators and targeted treatment for ATCs.

Cancer immunotherapy by NC410, a LAIR-2 Fc protein blocking human LAIR-collagen interaction

Collagens are a primary component of the extracellular matrix and are functional ligands for the inhibitory immune receptor leukocyte-associated immunoglobulin-like receptor (LAIR)-1. LAIR-2 is a secreted protein that can act as a decoy receptor by binding collagen with higher affinity than LAIR-1. We propose that collagens promote immune evasion by interacting with LAIR-1 expressed on immune cells, and that LAIR-2 releases LAIR-1-mediated immune suppression. Analysis of public human datasets shows that collagens, LAIR-1 and LAIR-2 have unique and overlapping associations with survival in certain tumors. We designed a dimeric LAIR-2 with a functional IgG1 Fc tail, NC410, and showed that NC410 increases human T cell expansion and effector function in vivo in a mouse xenogeneic-graft versus-host disease model. In humanized mouse tumor models, NC410 reduces tumor growth that is dependent on T cells. Immunohistochemical analysis of human tumors shows that NC410 binds to collagen-rich areas where LAIR-1⁺ immune cells are localized. Our findings show that NC410 might be a novel strategy for cancer immunotherapy for immune-excluded tumors.

Establishment of a prognostic model of four genes in gastric cancer based on multiple data sets

Gastric cancer (GC) is a kind of malignancy with a high mortality and recurrence. An effective prediction model based on ideal biomarkers to assess prognosis could benefit patients for optimization of treatment. Bioinformatics has played an increasingly important role in the study of cancer diseases. Therefore, this study started with bioinformatics to establish a reliable prognostic model of gastric cancer. The gene expression data and clinical data of GC tissues and normal tissues were obtained from the Gene Expression Omnibus (GEO), Genotype‐Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) profile database. We finally identified a four gene signature and constructed a prognostic model. The results of internal and external validation showed that the model is highly reliable. In addition, we also constructed a nomogram based on the model, which was verified by a calibration curve to show its predicted accuracy. Comprehensive analysis indicated that the four genes in the model are related to the occurrence and development of tumors, perhaps they are potential targets for tumor treatment. Generally, this prognostic model can bring potential benefits to patients with gastric cancer.

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer

Background: Collagen type X alpha 1 (COL10A1) is overexpressed in diverse tumors and displays vital roles in tumorigenesis. However, the prognostic value of COL10A1 in breast cancer remains unclear.

Methods: The expression of COL10A1 was analyzed by the Oncomine database and UALCAN cancer database. The relationship between COL10A1 expression level and clinical indicators including prognostic data in breast cancer were analyzed by the Kaplan–Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases.

Results: COL10A1 was up-regulated in different subtypes of breast cancer. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) status and nodal status were positively correlated with COL10A1 expression. Conversely, age, the Scarff–Bloom–Richardson (SBR) grade, basal-like status, and triple-negative status were negatively related to COL10A1 level in breast cancer samples compared with normal tissues. Patients with increased COL10A1 expression level showed worse overall survival (OS), relapse-free survival (RFS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). COL10A1 was positively correlated with metastatic relapse-free survival. GSEA analysis revealed that enrichment of TGF-β signaling pathway. 15-leucine-rich repeat containing membrane protein (LRRC15) is a correlated gene of COL10A1.

Conclusion: Bioinformatics analysis revealed that COL10A1 might be considered as a predictive biomarker for prognosis of breast cancer. Further experiments and clinical trials are essential to elucidate the value of COL10A1 in breast cancer treatment.

Quantitative proteome profiling stratifies fibroepithelial lesions of the breast

Breast fibroepithelial lesions (FELs) include heterogeneous pathological tumors, involving indolent fibroadenoma (FAD) to potentially aggressive phyllodes tumors (PTs). The current grading system remains unreliable in differentiating these tumors due to histological heterogeneity and lack of appropriate markers to monitor the sudden and unpredictable malignant transformation of PTs. Thus, there exists an imminent need for a marker-based diagnostic approach to augment the conventional histological platform that could lead to accurate diagnosis and distinction of FELs. The high- throughput quantitative proteomic analysis suggested that FAD and PTs form distinct clusters away from borderline and malignant though there exist marked differences between them. Interestingly, over-expression of extracellular matrices (ECM) related proteins and epithelial-mesenchymal transition (EMT) markers in borderline PTs led us to hypothesize a model of deposition and degradation leading to ECM remodeling and EMT acquisition triggering its malignant transformation. We also identified three candidate biomarkers such as MUCL1, HTRA1, and VEGDF uniquely expressed in FAD, borderline, and malignant PTs, respectively, which were further validated using immunohistochemistry. The present work shed light on a brief mechanistic framework of PTs aggressive nature and present potential biomarkers to differentiate overlapping FELs that would be of practical utility in augmenting existing diagnosis and disease management for this rare tumor.

Screening and bioinformatical analysis of differentially expressed genes in nasopharyngeal carcinoma

Objective: To identify differentially expressed genes via bioinformatical analysis for nasopharyngeal carcinoma (NPC) and explore potential biomarkers for NPC.

Methods: We downloaded the NPC gene expression datasets (GSE40290, GSE53819) and obtained differentially expressed genes (DEGs) via GEO2R. Functional analysis of DEGs was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In order to explore the interaction of DEGs and screen the core genes, we established protein-protein interaction (PPI) network. Then the expression level, prognostic and diagnostic analysis of the core genes in NPC were performed to reveal their potential effects on NPC. Furthermore, we obtained the transcription factors (TF) and microRNAs of core genes to construct the coregulatory network.

Results: We obtained 124 up-regulated genes and 190 down-regulated genes in total. These genes were found to be related to signal transduction, extracellular matrix organization and cell adhesion based on GO analysis. KEGG analysis revealed that the NF-kappa B (NF-κB) signaling pathway, pathways in cancer were mainly enriched signaling pathways. 25 core genes were obtained by constructing PPI network. Then the high expression of 10 core genes in NPC were verified via GEPIA, Oncomine databases and laboratory experiments. The TF-microRNA coregulatory network of the 10 core genes was built. Survival and diagnostic analysis indicated that SPP1 had negative influence on the prognosis of NPC patients based on two datasets and nine up-regulated core genes (FN1, MMP1, MMP3, PLAU, PLAUR, SERPINE1, SPP1, COL8A1, COL10A1) might be diagnostic markers for NPC.

Conclusions: Core genes of NPC were screened out by bioinformatical analysis in the present study and these genes may serve as prognostic and diagnostic biomarkers for NPC.

Collagen biology making inroads into prognosis and treatment of cancer progression and metastasis

Progression through dissemination to tumor-surrounding tissues and metastasis development is a hallmark of cancer that requires continuous cell-to-cell interactions and tissue remodeling. In fact, metastization can be regarded as a tissue disease orchestrated by cancer cells, leading to neoplastic colonization of new organs. Collagen is a major component of the extracellular matrix (ECM), and increasing evidence suggests that it has an important role in cancer progression and metastasis. Desmoplasia and collagen biomarkers have been associated with relapse and death in cancer patients. Despite the increasing interest in ECM and in the desmoplastic process in tumor microenvironment as prognostic factors and therapeutic targets in cancer, further research is required for a better understanding of these aspects of cancer biology. In this review, published evidence correlating collagen with cancer prognosis is retrieved and analyzed, and the role of collagen and its fragments in cancer pathophysiology is discussed.

Analysis of Collagen type X alpha 1 (COL10A1) expression and prognostic significance in gastric cancer based on bioinformatics

Collagen type X alpha 1 (COL10A1) is a member of the collagen family and the main matrix component. However, COL10A1 expression and prognosis relationship remains unclear in gastric cancer (GC). Through the analysis of database of Oncomine, the Cancer Genome Atlas (TCGA) as well as the Gene Expression Omnibus (GEO), in contrast to the tissue of normal gastric, COL10A1 in gastric cancer, had been upregulated. The high expression of COL10A1 was obviously related to T stage (P = 0.025) and lymph node metastasis (P = 0.025). It has been illustrated by the analysis of logistic regression that COL10A1's heightened expression in gastric cancer had been essentially linked with pathological stage, tumor differentiation, and T classification. The Kaplan-Meier curve in the Kaplan-Meier plotter database (P = 0.0371) and GSE84437 (P = 0.002) indicate that patients with high COL10A1 expression possess poor prognosis, specifically GC patients with lymph node metastasis have it. TCGA's Multivariate analysis (P = 0.025) and GSE84437 dataset (P = 0.034) show that high expression COL10A1 is a key independent predictor of poor overall survival. Searching KEGG pathway enrichment by GSEA, the results suggested that 29 pathways were enriched. qRT-PCR technique was used for verification of the COL10A1's high expression in gastric cancer in contrast to the normal gastric tissues. In conclusion, COL10A1 is of great importance in predicting the survival rate of GC patients.

Upregulated Collagen COL10A1 Remodels the Extracellular Matrix and Promotes Malignant Progression in Lung Adenocarcinoma

Collagens are major components of the ECM in various organs, including the lungs. Ectopic expression of collagens can regulate the tumor progression and disease outcome through remodeling of the extracellular matrix (ECM). However, it remains largely unexplored whether collagens are involved in the tumor progression of lung adenocarcinoma (LUAD). Analysis of three LUAD transcriptional expression profiles showed that COL10A1 mRNA expression was up-regulated and associated with poor prognosis. Gain- and loss-of-function studies were performed to observe that up-regulated COL10A1 promotes LUAD cell proliferation and invasion in vitro and in vivo. In molecular mechanism study, we found that COL10A1 interacts with DDR2 and affects the downstream FAK signaling pathway to regulate LUAD cell progression. The expression of COL10A1 on tissue microarray (TMA) was also measured to explore the association between COL10A1 expression and patient outcome. The results addressed that COL10A1 is up-regulated and positively correlated with lymph node metastasis in lung adenocarcinoma, and the COL10A1 expression is also an independent prognostic factor. In summary, the up-regulated COL10A1 remodels the ECM and the COL10A1/DDR2/FAK axis regulates the proliferation and metastasis of LUAD cells, implying that COL10A1 is a promising therapeutic target and prognostic marker for LUAD patients.

Screening lncRNAs with diagnostic and prognostic value for human stomach adenocarcinoma based on machine learning and mRNA-lncRNA co-expression network analysis

BACKGROUND

Stomach adenocarcinoma (STAD), is one of the most lethal malignancies around the world. The aim of this study was to find the long noncoding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of STAD.

METHODS

Base on TCGA dataset, the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified between STAD and normal tissue. The machine learning and survival analysis were performed to evaluate the potential diagnostic and prognostic value of lncRNAs for STAD. We also build the co-expression network and functional annotation. The expression of selected candidate mRNAs and lncRNAs were validated by Quantitative real-time polymerase chain reaction (qRT-PCR) and GSE27342 dataset. GSE27342 dataset were also to perform gene set enrichment analysis.

RESULTS

A total of 814 DEmRNAs and 106 DElncRNAs between STAD and normal tissue were obtained. FOXD2-AS1, LINC01235, and RP11-598F7.5 were defined as optimal diagnostic lncRNA biomarkers for STAD. The area under curve (AUC) of the decision tree model, random forests model, and support vector machine (SVM) model were 0.797, 0.981, and 0.983, and the specificity and sensitivity of the three model were 75.0% and 97.1%, 96.9% and 96%, and 96.9% and 97.1%, respectively. Among them, LINC01235 was not only an optimal diagnostic lncRNA biomarkers, but also related to survival time. The expression of three DEmRNAs (ESM1, WNT2, and COL10A1) and three optimal diagnostic lncRNAs biomarkers (FOXD2-AS1, RP11-598F7.5, and LINC01235) in qRT-PCR validation was were consistent with our integrated analysis. Except for FOXD2-AS1, ESM1, WNT2, COL10A1, and LINC01235 were upregulated in STAD, which was consistent with our integration results. Gene set enrichment analysis results indicated that DNA replication, Cell cycle, ECM-receptor interaction, and P53 signaling pathway were four significantly enriched pathways in STAD.

CONCLUSION

Our study identified three DElncRNAs as potential diagnostic biomarkers of STAD. Among them, LINC01235 also was a prognostic lncRNA biomarkers.

High plasma levels of COL10A1 are associated with advanced tumor stage in gastric cancer patients

BACKGROUND

Gastric cancer (GC) remains an aggressive malignancy with a high rate of mortality, being the third leading cause of cancer-related death. More than one million newly diagnosed cases and 782685 deaths due to GC were reported in 2018. GC is characterized by limited effective treatment options and the lack of consistent biomarkers for the diagnosis and prognosis of these patients. The discovery of new biomarkers useful in the early diagnosis of GC is mandatory.

AIM

To evaluate the potential of COL10A1 as a circulating biomarker for the diagnosis and prognosis of gastric adenocarcinoma patients.

METHODS

Plasma and tissue obtained from 49 patients with gastric adenocarcinoma have been used in exploring the expression of COL10A1. Real-time PCR and western blot techniques were used to evaluate COL10A1 level in gastric tumor tissue compared to normal adjacent tissue. The circulating level of COL10A1 was also evaluated by ELISA in plasma of gastric adenocarcinoma patients. Survival analysis was made in order to evaluate the potential of COL10A1 as a biomarker for the diagnosis and prognosis of gastric adenocarcinoma patients.

RESULTS

Our results showed a significant increase in COL10A1 gene expression and protein levels in gastric tumor tissue compared to adjacent normal tissue (P < 0.05). COL10A1 seems to show an elevated expression from the beginning of carcinogenesis, in the early stages, and its increased level remains elevated during cancer progression. A significant increase of COL10A1 plasma level in gastric adenocarcinoma patients was also identified. Moreover, increased COL10A1 plasma level was associated with poor survival of the patients. Plasma COL10A1 performed a diagnostic value in GC with area under the receiver operating characteristic curve (AUC) of 0.9171 (P = 0.0002), sensitivity of 87.76%, and specificity of 100.0%. Furthermore, this study demonstrated the potential role of plasma COL10A1 in the early detection of GC, as in the early stage, we obtained an AUC of 0.8789 (P = 0.0030), sensitivity of 81.25%, and specificity of 100.0%.

CONCLUSION

Circulating expression level of COL10A1 is significantly increased in gastric adenocarcinoma patients being associated with poor survival and is a potential biomarker for early detection of GC.

Stromal ColXα1 expression correlates with tumor-infiltrating lymphocytes and predicts adjuvant therapy outcome in ER-positive/HER2-positive breast cancer

Background

The breast cancer microenvironment contributes to tumor progression and response to chemotherapy. Previously, we reported that increased stromal Type X collagen α1 (ColXα1) and low TILs correlated with poor pathologic response to neoadjuvant therapy in estrogen receptor and HER2-positive (ER+/HER2+) breast cancer. Here, we investigate the relationship of ColXα1 and long-term outcome of ER+/HER2+ breast cancer patients in an adjuvant setting.

Methods

A total of 164 cases with at least 5-year follow-up were included. Immunohistochemistry for ColXα1 was performed on whole tumor sections. Associations between ColXα1expression, clinical pathological features, and outcomes were analyzed.

Results

ColXα1 expression was directly proportional to the amount of tumor associated stroma (p = 0.024) and inversely proportional to TILs. Increased ColXα1 was significantly associated with shorter disease free survival and overall survival by univariate analysis. In multivariate analysis, OS was lower in ColXα1 expressing (HR = 2.1; 95% CI = 1.2–3.9) tumors of older patients (> = 58 years) (HR = 5.3; 95% CI = 1.7–17) with higher stage (HR = 2.6; 95% CI = 1.3–5.2). Similarly, DFS was lower in ColXα1 expressing (HR = 1.8; 95% CI = 1.6–5.7) tumors of older patients (HR = 3.2; 95% CI = 1.3–7.8) with higher stage (HR = 2.7; 95% CI = 1.6–5.7) and low TILs. In low PR+ tumors, higher ColXα1 expression was associated with poorer prognosis.

Conclusion

ColXα1 expression is associated with poor disease free survival and overall survival in ER+/HER2+ breast cancer. This study provides further support for the prognostic utility of ColXα1 as a breast cancer associated stromal factor that predicts response to chemotherapy.

Electronic supplementary material

The online version of this article (10.1186/s12885-019-6134-y) contains supplementary material, which is available to authorized users.

Exosomes derived from microRNA-101-3p-overexpressing human bone marrow mesenchymal stem cells suppress oral cancer cell proliferation, invasion, and migration

Dysregulation of microRNAs (miRNAs) has been found to disrupt the progression of oral cancer. However, which miRNAs are most effective against oral cancer and how these miRNAs should be delivered are major unanswered problems. We aimed at investigating if human bone marrow mesenchymal stem cells (hBMSCs)-derived exosomes affect oral cancer development, and the potential regulatory mechanism associated with COL10A1 and miR-101-3p. COL10A1 was upregulated, while miR-101-3p was downregulated in oral cancer, and miR-101-3p targeted COL10A1 as verified by dual-luciferase reporter gene assay. Meanwhile, exosomes derived from hBMSCs were isolated and then co-cultured with oral cancer cells to identify the role of exosomes, and the results suggested that hBMSCs-derived exosomes overexpressing miR-101-3p inhibited oral cancer progression. Furthermore, tumorigenicity assay in nude mice further confirmed the inhibitory effects of hBMSCs-derived exosomes, loaded with miR-101-3p, on oral cancer, which provides a new theoretical basis in the treatment of oral cancer.

MiR-384 induces apoptosis and autophagy of non-small cell lung cancer cells through the negative regulation of Collagen α-1(X) chain gene

The present study aims to investigate the mechanism of miR-384 in non-small cell lung cancer (NSCLC) cell apoptosis and autophagy by regulating Collagen α-1(X) chain (COL10A1). Bioinformatics methods were applied to evaluate potential miRNAs and genes that might correlate with NSCLC. Tumor tissues and adjacent tissues from 104 NSCLC patients were collected and human NSCLC A549 cell line was selected for subsequent experiments. A549 cells were treated with miR-384 mimic, miR-384 inhibitor, or knockdown of COL10A1. Quantitative real-time PCR (qRT-PCR) and Western blotting were utilized to detect the levels of miR-384, COL10A, Survivin, Bcl-2, Bax, Bcl-xl, Beclin 1, and LC3 in tissues and cells. A series of biological assays including MTT assay, Annexin V-FITC/PI (propidium iodide) staining, immunofluorescence, monodansylcadaverine (MDC) staining were conducted to investigate the effects of miR-384 and COL10A1 on NSCLC cells. Tumorigenicity assay for nude rats was applied. Results obtained from the present study indicated that miR-384 down-regulated COL10A1 by targetting it. Compared with adjacent tissues, miR-384 expression was obviously reduced while COL10A1 expression was significantly enhanced in NSCLC tissues (all P<0.05). Outcomes in vivo and in vitro suggested that cell proliferation and tumorigenicity were inhibited while cell apoptosis and autophagy were induced in NSCLC cells treated with up-regulation of miR-384 or silence of COL10A1. In miR-384 inhibitor group, cell proliferation was improved, while cell apoptosis was reduced and cell autophagy was decreased whereas tumorigenicity of cells was strengthened. Based on the findings of our study, it was established that miR-384 could down-regulate COL10A1 levels, subsequently inhibiting cell proliferation and promoting cell apoptosis and autophagy in NSCLC cells.

TGF-β1-SOX9 axis-inducible COL10A1 promotes invasion and metastasis in gastric cancer via epithelial-to-mesenchymal transition

Molecular biomarkers that predict disease progression might promote drug development and therapeutic strategies in aggressive cancers, such as gastric cancer (GC). High-throughput mRNA sequencing (RNA-seq) revealed that collagen type X alpha 1 (COL10A1) is a disease progression-associated gene. Analysis of 103 GC patients showed that high COL10A1 mRNA expression was associated with GC metastasis and reduced survival. We analyzed the COL10A1 promoter using the UCSC genome website and JASPAR database, and we found potential SOX9 binding site. Here, we demonstrated that SOX9 and COL10A1 were both up-regulated in GC. We observed a positive correlation between the expression patterns of SOX9 and COL10A1 in GC cells and tissues. The results of electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP) assay and promoter reporter indicated that SOX9 could directly bind to the COL10A1 gene promoter and activate its transcription. Biological function experiments showed that COL10A1 regulated the migration and invasion of GC cells. Knockdown COL10A1 inhibited lung and abdominal cavity metastasis in a nude mouse model. Moreover, transforming growth factor-β1 (TGF-β1) treatment up-regulated the phosphorylation of Smad2 and increased SOX9 and COL10A1 expression. COL10A1 was confirmed to be a potential inducer of epithelial-to-mesenchymal transition (EMT). SOX9 was essential for COL10A1-mediated EMT, and cell migration, invasion and metastasis. Co-expression of SOX9 and COL10A1 was associated with tumor progression and was strongly predictive of overall survival in GC patients. In summary, this study elucidated the mechanistic link between COL10A1 and the TGF-β1-SOX9 axis. These findings indicated that COL10A1 might play a crucial role in GC progression and serve as a potential biomarker and therapeutic target in GC patients.