Discovery and validation of new potential biomarkers for early detection of colon cancer

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.

Identification and clinicopathological analysis of potential p73-regulated biomarkers in colorectal cancer via integrative bioinformatics

This study aims to decipher crucial biomarkers regulated by p73 for the early detection of colorectal cancer (CRC) by employing a combination of integrative bioinformatics and expression profiling techniques. The transcriptome profile of HCT116 cell line p53- / - p73+ / + and p53- / - p73 knockdown was performed to identify differentially expressed genes (DEGs). This was corroborated with three CRC tissue expression datasets available in Gene Expression Omnibus. Further analysis involved KEGG and Gene ontology to elucidate the functional roles of DEGs. The protein-protein interaction (PPI) network was constructed using Cytoscape to identify hub genes. Kaplan-Meier (KM) plots along with GEPIA and UALCAN database analysis provided the insights into the prognostic and diagnostic significance of these hub genes. Machine/deep learning algorithms were employed to perform TNM-stage classification. Transcriptome profiling revealed 1289 upregulated and 1897 downregulated genes. When intersected with employed CRC datasets, 284 DEGs were obtained. Comprehensive analysis using gene ontology and KEGG revealed enrichment of the DEGs in metabolic process, fatty acid biosynthesis, etc. The PPI network constructed using these 284 genes assisted in identifying 20 hub genes. Kaplan-Meier, GEPIA, and UALCAN analyses uncovered the clinicopathological relevance of these hub genes. Conclusively, the deep learning model achieved TNM-stage classification accuracy of 0.78 and 0.75 using 284 DEGs and 20 hub genes, respectively. The study represents a pioneer endeavor amalgamating transcriptomics, publicly available tissue datasets, and machine learning to unveil key CRC-associated genes. These genes are found relevant regarding the patients' prognosis and diagnosis. The unveiled biomarkers exhibit robustness in TNM-stage prediction, thereby laying the foundation for future clinical applications and therapeutic interventions in CRC management.

High expression of NXPH4 correlates with poor prognosis, metabolic reprogramming, and immune infiltration in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is a prevalent gastrointestinal malignant disease with high mortality rate, and identification of novel prognostic biomarkers and therapeutic targets is urgently needed. Although neurexophilin 4 (NXPH4) has been investigated in several tumors, its role in COAD remains unclear. The aim of this study was to explore the prognostic value and potential functions of NXPH4 in COAD.

Methods

The expression of NXPH4 in COAD were analyzed using The Cancer Genome Atlas (TCGA) and datasets from the Gene Expression Omnibus (GEO) database. The prognostic value of NXPH4 was determined using Kaplan-Meier analysis and Cox regression analysis. To investigate the possible mechanism underlying the role of NXPH4 in COAD, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were employed. The correlation between NXPH4 expression and immune cell infiltration levels was examined thorough single-sample gene set enrichment analysis (ssGSEA). Furthermore, the competing endogenous RNA (ceRNA) regulatory network that may be involved in NXPH4 in COAD was predicted and constructed through a variety of databases.

Results

NXPH4 expression was significantly higher in COAD tissue compared with normal colon tissues. Meanwhile, high expression of NXPH4 was associated with poor prognosis in COAD patients. GO-KEGG and GSEA analyses indicated that NXPH4 was associated with glycolysis and hypoxia pathway, and may promote COAD progression and metastasis by modulating metabolic reprogramming. ssGSEA analysis demonstrated that NXPH4 expression also associated with immune infiltration. Furthermore, we identified various microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) as upstream regulators of NXPH4 in COAD.

Conclusions

The present study revealed that high expression of NXPH4 is associated with tumor progression, metabolic reprogramming, and immune infiltration. These findings suggest that NXPH4 could serve as a reliable prognostic biomarker and a promising therapeutic target in COAD.

TIGD1 Is an Independent Prognostic Factor that Promotes the Progression of Colon Cancer

Background: Trigger transposable element-derived 1 (TIGD1) is a human-specific gene, but no studies have been conducted to determine its mechanism of action. Our aim is to ascertain the function and mode of action of TIGD1 in the development of colon cancer. Materials and Methods: The authors used bioinformatics to analyze the relationship between TIGD1 and the clinical characteristics of colon cancer, as well as its prognosis. A series of cell assays were conducted to assess the function of TIGD1 in the proliferation and migration of colon cancer, and flow cytometry was used to explore its effects on apoptosis and the cell cycle. Results: The authors discovered that the expression of TIGD1 was remarkably elevated in colon cancer. Clinical correlation analysis demonstrated that TIGD1 expression was elevated in the tissues of advanced-stage patients, and it was remarkably elevated in individuals with both lymph node and distant metastasis. Further, the authors found that individuals showing elevated TIGD1 expression levels had a shortened survival time. Univariate and multivariate Cox regression analyses revealed that TIGD1 was an independent prognostic factor. Overexpression of the TIGD1 gene remarkedly enhances the proliferation and metastasis of colon cancer cells and suppresses apoptosis. In addition, the overexpression of TIGD1 can enhance the transition of tumor cells from the G1 toward the S phase. Western blot results suggested that TIGD1 may promote the malignant activity of colon cancer cells via the Wnt/β-catenin signaling pathway, Bcl-2, N-cadherin, BAX, E-cadherin, CDK6, and CyclinD1. Conclusions: TIGD1 may be an independent prognostic factor in the advancement of colon cancer, and therefore function as a therapeutic target.

MEK-mediated CHPF2 phosphorylation promotes colorectal cancer cell proliferation and metastasis by activating NF-κB signaling

The cytokine tumor necrosis factor (TNF) plays a crucial role in the proliferation and metastasis of colorectal cancer (CRC) cells, but the underlying mechanisms remain poorly understood. Here, we report that chondroitin polymerizing factor 2 (CHPF2) promotes CRC cell proliferation and metastasis mediated by TNF, independently of its enzymatic activity. CHPF2 is highly expressed in CRC, and its elevated expression is associated with poor prognosis of CRC patients. Mechanistically, upon TNF stimulation, CHPF2 is phosphorylated at the T588 residue by MEK, enabling CHPF2 to interact with both TAK1 and IKKα. This interaction enhances the binding of TAK1 and IKKα, leading to increased phosphorylation of the IKK complex and activation of NF-κB signaling. As a result, the expression of early growth factors (EGR1) is upregulated to promote CRC cell proliferation and metastasis. In contrast, introduction of a phospho-deficient T588A mutation in CHPF2 weakened the interaction between CHPF2 and TAK1, thus impairing NF-κB signaling. CHPF2 T588A mutation reduced the ability of CHPF2 to promote the proliferation and metastasis of CRC in vitro and in vivo. Furthermore, the NF-κB RELA subunit promotes CHPF2 expression, further amplifying TNF-induced NF-κB signaling activation. These findings identify a moonlighting function of CHPF2 in promoting tumor cell proliferation and metastasis and provide insights into the mechanism by which CHPF2 amplifies TNF-mediated NF-κB signaling activation. Our study provides a molecular basic for the development of therapeutic strategies for CRC treatment.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

scRNA-seq of colorectal cancer shows regional immune atlas with the function of CD20+ B cells

Colorectal cancer (CRC) from different regions exhibits different histological, genetic characteristics, and molecular subtypes, even in response to conventional chemotherapies and immunotherapies. To characterize the immune landscape in different regions of CRC and search for potential therapeutic targets, we analyzed 39,484 single-cell transcription data from 19 samples of CRC and paired normal tissues from four regions to identify the immune characteristics of CRC among anatomic locations, especially in B cells. We discovered that immune cell infiltration in tumors significantly varied among different regions of CRC. B cells from right- and left-sided CRC had different development trajectories, but both had extensive interactions with myeloid cells and T cells. Survival analysis suggested that CD20+ B cells correlated with good prognosis in CRC patients, especially on the right side. Furthermore, the depletion of CD20+ B cells demonstrated that anti-CD20 promoted tumor growth progression and reversed the tumor-killing activity of anti-PD-1 treatment in vivo and in vitro. Our results highlight the characterization of the immune landscape of CRC in different regions. CD20+ B-cell infiltration has been associated with CRC patient prognosis and may promote the tumor-killing role of PD-1 antibodies.

AEG-1 as a Novel Therapeutic Target in Colon Cancer: A Study from Silencing AEG-1 in BALB/c Mice to Large Data Analysis

BACKGROUND

Astrocyte elevated gene-1 (AEG-1) is overexpressed in various malignancies. Exostosin-1 (EXT-1), a tumor suppressor, is an intermediate for malignant tumors. Understanding the mechanism behind the interaction between AEG-1 and EXT-1 may provide insights into colon cancer metastasis.

METHODS

AOM/DSS was used to induce tumor in BALB/c mice. Using an in vivo-jetPEI transfection reagent, transient transfection of AEG-1 and EXT-1 siRNAs were achieved. Histological scoring, immunohistochemical staining, and gene expression studies were performed from excised tissues. Data from the Cancer Genomic Atlas and GEO databases were obtained to identify the expression status of AEG-1 and itsassociation with the survival.

RESULTS

In BALB/c mice, the AOM+DSS treated mice developed necrotic, inflammatory and dysplastic changes in the colon with definite clinical symptoms such as loss of goblet cells, colon shortening, and collagen deposition. Administration of AEG-1 siRNA resulted in a substantial decrease in the disease activity index. Mice treated with EXT-1 siRNA showed diffusely reduced goblet cells. In vivo investigations revealed that PTCH-1 activity was influenced by upstream gene AEG-1, which in turn may affect EXT-1 activity. Data from The Cancer Genomic Atlas and GEO databases confirmed the upregulation of AEG-1 and downregulation of EXT-1 in cancer patients.

CONCLUSIONS

This study revealed that AEG-1 silencing might alter EXT-1 expression indirectly through PTCH-1, influencing cell-ECM interactions, and decreasing dysplastic changes, proliferation and invasion.

Current advances in detecting genetic and epigenetic biomarkers of colorectal cancer

Colorectal carcinoma (CRC) is the third most common cancer in terms of diagnosis and the second in terms of mortality. Recent studies have shown that various proteins, extracellular vesicles (i.e., exosomes), specific genetic variants, gene transcripts, cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and altered epigenetic patterns, can be used to detect, and assess the prognosis of CRC. Over the last decade, a plethora of conventional methodologies (e.g., polymerase chain reaction [PCR], direct sequencing, enzyme-linked immunosorbent assay [ELISA], microarray, in situ hybridization) as well as advanced analytical methodologies (e.g., microfluidics, electrochemical biosensors, surface-enhanced Raman spectroscopy [SERS]) have been developed for analyzing genetic and epigenetic biomarkers using both optical and non-optical tools. Despite these methodologies, no gold standard detection method has yet been implemented that can analyze CRC with high specificity and sensitivity in an inexpensive, simple, and time-efficient manner. Moreover, until now, no study has critically reviewed the advantages and limitations of these methodologies. Here, an overview of the most used genetic and epigenetic biomarkers for CRC and their detection methods are discussed. Furthermore, a summary of the major biological, technical, and clinical challenges and advantages/limitations of existing techniques is also presented.

The diagnostic or prognostic values of FADD in cancers based on pan‑cancer analysis

Previous studies have determined that aberrant expression of the fas-associated death domain (FADD) contributes to the development of cancer. However, no pan-cancer analysis has been reported to explore the relationship between FADD and various cancers. Multiple databases were screened to identify cancer datasets for the present study and to validate the expression of FADD in various tumors. The association of FADD alteration with cancer prognosis, clinical features and tumor immunity was also evaluated. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to confirm the expression of FADD in breast, colon, liver and gastric cancer cells. Analysis of Gene Expression Omnibus database and The Cancer Genome Atlas database indicated that FADD was highly expressed in breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD) and prostate adenocarcinoma, whereas RT-qPCR results revealed that FADD was highly expressed in breast cancer and colon cancer. Further analyses demonstrated that FADD expression was significantly altered in ESCA, head and neck squamous cell carcinoma (HNSC), lung squamous cell carcinoma and BRCA. FADD expression was observed to be a risk factor of the overall survival in patients with HNSC, LIHC and LUAD as demonstrated by Kaplan-Meier and Cox regression analyses. The results of the present study demonstrated that FADD is highly expressed in numerous malignancies and can be utilized as a biomarker for the diagnosis of BRCA, COAD, LIHC and stomach adenocarcinoma. Moreover, FADD expression is a predictive risk factor for the development of HNSC, LIHC and LUAD and can potentially be used as a prognostic marker for these cancers.

Insilco prediction of the role of the FriZZled5 gene in colorectal cancer

INTRODUCTION

In this study, we aimed to elucidate the crosstalk between the Wnt/β-catenin signaling pathway and colorectal cancer (CRC) associated with inflammatory bowel disease (IBD) using a bioinformatics analysis of putative common biomarkers and a systems biology approach.

MATERIALS AND METHODS

The following criteria were used to search the GEO and ArrayExpress databases for terms related to CRC and IBD: 1. The dataset containing the transcriptomic data, and 2. Untreated samples by medications or drugs. A total of 42 datasets were selected for additional analysis. The GEO2R identified the differentially expressed genes. The genes involved in the Wnt signaling pathway were extracted from the KEGG database. Enrichment analysis and miRNA target prediction were conducted through the ToppGene online tool.

RESULTS

In CRC datasets, there were 1168 up- and 998 down-regulated probes, whereas, in IBD datasets, there were 256 up- and 200 down-regulated probes. There were 65 upregulated and 57 downregulated genes shared by CRC and IBD. According to KEGG, there were 166 genes in the Wnt pathway. FriZZled5 (FZD5) was a down-regulated gene in both CRC and IBD, as determined by the intersection of CRC- and IBD-related DEGs with the Wnt pathway. It was also demonstrated that miR-191, miR-885-5p, miR-378a-3p, and miR-396-3p affect the FriZZled5 gene expression.

CONCLUSION

It is possible that increased expression of miR-191 and miR-885-5p, or decreased expression of miR-378a -3p and miR396-3, in IBD and CRC results in decreased expression of the FZD5 gene. Based on the function of this gene, FZD5 may be a potential therapeutic target in IBD that progresses to CRC.

Identification of DLL3-related genes affecting the prognosis of patients with colon adenocarcinoma

Background: Delta-like ligand 3 (DLL3) is one of the NOTCH family of ligands, which plays a pro- or anti-carcinogenic role in some cancers. But the role of DLL3 in colon adenocarcinoma (COAD) has not been studied in depth. Materials and methods: First, we used Kaplan-Meier (K-M) curve to evaluate the effect of DLL3 on the prognosis of COAD in The Cancer Genome Atlas (TCGA), which was further validated in clinical samples for immunohistochemistry. Then we screened for differentially expressed genes (DEGs) of DLL3 by analyzing datasets of COAD samples from Gene Expression Omnibus (GEO) and TCGA. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and Gene Set Enrichment Analysis (GSEA) were conducted to explore the underlying mechanisms of DLL3-related in the development and prognosis of COAD. On the basis of DLL3-related signature genes, a prognostic model and a nomogram were constructed. Finally, CIBERSORT was applied to assess the proportion of immune cell types in COAD sample. Results: Survival analysis showed a significant difference in overall survival between high- and low-expression group (p = 0.0092), with COAD patients in the high-group having poorer 5-year survival rate. Gene functional enrichment analysis revealed that DLL3-related DEGs were mainly enriched in tumor- and immunity-related signaling pathways, containing AMPK pathway and mitophagy-animal. The comparison of COAD tumor and normal, DLL3 high- and low-expression groups by GSEA found that AMPK signaling pathway and mitophagy-animal were inhibited. Nomogram constructed from DLL3-related signature genes had a good predictive effect on the prognosis of COAD. We found the highest correlation between DLL3 and interstitial dendritic cell (iDC), natural killer (NK) cell and Interstitial dendritic cell (Tem). DLL3 was also revealed to be diagnostic for COAD. In clinical sample, we identified higher DLL3 expression in colon cancer tissue than in adjacent control (p < 0.0001) and in metastasis than in primary lesion (p = 0.0056). DLL3 expression was associated with stage and high DLL3 expression was observed to predict poorer overall survival (p = 0.004). Conclusion: It suggested that DLL3 may offer prognostic value and therapeutic potential for individualized treatment of COAD, and that it may has a diagnostic role in COAD.

Prognostic value of COL10A1 and its correlation with tumor-infiltrating immune cells in urothelial bladder cancer: A comprehensive study based on bioinformatics and clinical analysis validation

Introduction

Bladder cancer (BLCA) is one of the most lethal diseases. COL10A1 is secreted small-chain collagen in the extracellular matrix associated with various tumors, including gastric, colon, breast, and lung cancer. However, the role of COL10A1 in BLCA remains unclear. This is the first research focusing on the prognostic value of COL10A1 in BLCA. In this research, we aimed to uncover the association between COL10A1 and the prognosis, as well as other clinicopathological parameters in BLCA.

Methods

We obtained gene expression profiles of BLCA and normal tissues from the TCGA, GEO, and ArrayExpress databases. Immunohistochemistry staining was performed to investigate the protein expression and prognostic value of COL10A1 in BLCA patients. GO and KEGG enrichment along with GSEA analyses were performed to reveal the biological functions and potential regulatory mechanisms of COL10A1 based on the gene co-expression network. We used the “maftools” R package to display the mutation profiles between the high and low COL10A1 groups. GIPIA2, TIMER, and CIBERSORT algorithms were utilized to explore the effect of COL10A1 on the tumor immune microenvironment.

Results

We found that COL10A1 was upregulated in the BLCA samples, and increased COL10A1 expression was related to poor overall survival. Functional annotation of 200 co-expressed genes positively correlated with COL10A1 expression, including GO, KEGG, and GSEA enrichment analyses, indicated that COL10A1 was basically involved in the extracellular matrix, protein modification, molecular binding, ECM-receptor interaction, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling pathway. The most commonly mutated genes of BLCA were different between high and low COL10A1 groups. Tumor immune infiltrating analyses showed that COL10A1 might have an essential role in recruiting infiltrating immune cells and regulating immunity in BLCA, thus affecting prognosis. Finally, external datasets and biospecimens were used, and the results further validated the aberrant expression of COL10A1 in BLCA samples.

Conclusions

In conclusion, our study demonstrates that COL10A1 is an underlying prognostic and predictive biomarker in BLCA.

CD163 as a Potential Biomarker in Colorectal Cancer for Tumor Microenvironment and Cancer Prognosis: A Swedish Study from Tissue Microarrays to Big Data Analyses

(1) Background: CD163, a specific macrophage receptor, affects the progression of malignant tumors. Unfortunately, the regulation and expression of CD163 are poorly understood. In this study, we determined the expressions of CD163 in TMA samples from CRC patients and combined them with patient data from several Swedish hospitals. (2) Methods: The expressions of CD163 in tissue samples from CRC patients were examined. After combining 472 CRC patients’ gene expression and 438 CRC patients’ clinical data with the TCGA database, 964 cases from the GEO database, and experimental expression data from 1247 Swedish CRC patients, we selected four genes (PCNA, LOX, BCL2, and CD163) and analyzed the tumor-infiltrating immune cells (TICs) and CRC prognosis. (3) Results: Based on histopathological TMA analysis, CD163 was strongly expressed in the stroma of both normal and cancer tissues, and the expressions in normal and cancer cells varied from negative to strong. The results from public databases show decreased expression of CD163 in cancer tissue compared to normal mucosa (|log FC| > 1 and FDR < 0.01), and it is a negative prognostic factor for CRC patients (p-value < 0.05). Through tumor microenvironment (TME) analysis, we found a potential influence of CD163 on immune cell infiltration. Furthermore, the enrichment analysis indicated the possible interaction with other proteins and biological pathways. (4) Conclusions: CD163 is expressed differently in CRC tissue and is a negative prognostic factor. Its expression is associated with the TME and tumor purity of CRC. Considering all results, CD163 has the potential to be a predictive biomarker in the investigation of CRC.

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.

Association of Adiponectin Receptors with Metabolic and Immune Homeostasis Parameters in Colorectal Cancer: In Silico Analysis and Observational Findings

Adiponectin (ADIPOQ) as both a regulator of metabolic homeostasis and a protein involved in immune response might be of particular interest to contemporary laboratory medicine, especially in terms of minimally invasive diagnostics. The diverse roles of ADIPOQ with regard to the immune and metabolic aspects of colorectal carcinogenesis have been proposed. However, the expression of its receptors ADIPOR1 and ADIPOR2 is scarcely explored in peripheral blood mononuclear cells (PBMCs). Moreover, ADIPORs' relationships with the immune response mediator TNF-α have not been previously investigated in the PBMCs of CRC patients. This study used both in silico and observational case-control analyses with the aim of exploring the association of ADIPOR gene expression and ADIPOQ single nucleotide polymorphisms (SNPs) with the inflammatory marker TNF-α and lipid status parameters in patients with CRC. Publicly available transcriptomic datasets (GSE47756, GSE44076) obtained from analyses of monocytes and CRC tissue samples were employed for the in silico evaluation of ADIPORs' specific genetic traits. GSE47756 and GSE44076 datasets were processed with GSEA software to provide a genetic fingertip of different signaling pathways associated with ADIPORs' mRNA levels. The case-control aspect of the study included the PBMC samples of 73 patients diagnosed with CRC and 80 healthy volunteers. The PCR method was carried out for the PBMC gene expression analysis (ADIPOR1, ADIPOR2, TNF-α mRNA levels) and for the subjects' genotyping (ADIPOQ rs266729, ADIPOR1 rs7539542). GSEA showed significant associations of ADIPOR mRNA expression with gene sets related to metabolic and immune homeostasis in both datasets. The case-control study revealed the association of ADIPOR1 rs7539542 with reduced lipid status parameters in CRC. In addition, PBMC ADIPOR1 mRNA levels decreased in CRC (p < 0.001), whereas ADIPOR2 mRNA did not differ between the groups (p = 0.442). A reduction in PBMC TNF-α mRNA levels was noted in CRC (p < 0.05). Our results indicate that ADIPOR1 and ADIPOR2 play a significant role in the alteration of both metabolic and immune homeostasis during the progression of CRC. For the first time, ADIPOR1 is shown to be a specific receptor for mediating ADIPOQ's effects in the PBMCs of CRC patients.

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.

Endoplasmic reticulum-resident protein Sec62 drives colorectal cancer metastasis via MAPK/ATF2/UCA1 axis

OBJECTIVE

Metastasis is responsible for the poor prognosis of patients with colorectal cancer (CRC), and the role of aberrant expression of endoplasmic reticulum (ER) receptors in tumour metastasis has not been fully elucidated. The aim of the study is to ensure the role of ER-resident protein Sec62 in CRC metastasis and illuminate associated molecular mechanisms.

MATERIALS AND METHODS

Bioinformatics analysis, qRT-PCR, western blot and immunohistochemistry assays were performed to evaluate the expression level and clinical significance of Sec62 in CRC. The specific role of Sec62 in CRC was identified by a series of functional experiments. We conducted RNA sequencing and rescue experiments to analyse the differentially expressed genes and identified UCA1 as a novel pro-metastasis target of Sec62 in CRC. Besides, the efficacy of MAPK/JNK inhibitor or agonist on Sec62-mediated CRC metastasis was evaluated by trans-well and wound healing assays. Finally, luciferase reporter and ChIP assay were employed to further explore the potential mechanisms.

RESULTS

The abnormally elevated expression of Sec62 predicted poor prognosis of CRC patients and facilitated malignant metastasis of CRC cells. Mechanistically, Sec62 enhanced UCA1 expression through activating MAPK/JNK signalling pathway. And the p-JNK activating ATF2 could transcriptionally regulate UCA1 expression. Furthermore, blocking or activating MAPK/JNK signalling with JNK inhibitor or agonist potently suppressed or enhanced Sec62 mediated CRC metastatic process.

CONCLUSIONS

Our study reports for the first time that the Sec62/MAPK/ATF2 /UCA1 axis exists in CRC metastatic process, which could be a potential treatment target of metastatic CRC.

Identification of CPT2 as a prognostic biomarker by integrating the metabolism-associated gene signature in colorectal cancer

BACKGROUND

The incidence of colorectal cancer (CRC) is considered to be the third-highest malignant tumor among all carcinomas. The alterations in cellular bioenergetics (metabolic reprogramming) are associated with several malignant phenotypes in CRC, such as tumor cell proliferation, invasion, metastasis, chemotherapy resistance, as well as promotes its immune escape. However, the expression pattern of metabolism-associated genes that mediate metabolic reprogramming in CRC remains unknown.

METHODS

In this study, we screened out CPT2 by investigating the function of a series of metabolism-related genes in CRC progression by integrating the data from the TCGA and GEO databases. Next, we collected CRC tissues (n = 24) and adjacent non-tumor tissues (n = 8) and analyzed mRNA levels by qRT-PCR, and proteins levels of CPT2 in CRC cell lines by western blotting. CCK-8 assay, colony formation assay, Edu assay and flow cytometry assay were performed to assess the effects of CPT2 on proliferation in vitro.

RESULTS

We identified 236 metabolism-related genes that are differentially expressed in colorectal cancer, of which 49 up-regulated and 187 down-regulated, and found CPT2 as the most significant gene associated with favorable prognosis in CRC. It was revealed that CPT2 expression was consistently down-regulated in CRC cell lines and tissues. Moreover, knockdown of CPT2 could promote the proliferative ability of CRC cells, whereas over-expression of CPT2 significantly suppressed the cell growth.

CONCLUSION

In summary, CPT2 can provide new insights about the progression and occurrence of the tumor as it acts as an independent prognostic factor in CRC sufferers.

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.

COLONOMICS - integrative omics data of one hundred paired normal-tumoral samples from colon cancer patients

Colonomics is a multi-omics dataset that includes 250 samples: 50 samples from healthy colon mucosa donors and 100 paired samples from colon cancer patients (tumor/adjacent). From these samples, Colonomics project includes data from genotyping, DNA methylation, gene expression, whole exome sequencing and micro-RNAs (miRNAs) expression. It also includes data from copy number variation (CNV) from tumoral samples. In addition, clinical data from all these samples is available. The aims of the project were to explore and integrate these datasets to describe colon cancer at molecular level and to compare normal and tumoral tissues. Also, to improve screening by finding biomarkers for the diagnosis and prognosis of colon cancer. This project has its own website including four browsers allowing users to explore Colonomics datasets. Since generated data could be reuse for the scientific community for exploratory or validation purposes, here we describe omics datasets included in the Colonomics project as well as results from multi-omics layers integration.

Identification of Six Genes as Diagnostic Markers for Colorectal Cancer Detection by Integrating Multiple Expression Profiles

Background

Many studies have demonstrated the promising utility of DNA methylation and miRNA as biomarkers for colorectal cancer (CRC) early detection. However, mRNA is rarely reported. This study aimed to identify novel fecal-based mRNA signatures.

Methods

The differentially expressed genes (DEGs) were first determined between CRCs and matched normal samples by integrating multiple datasets. Then, Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to reduce the number of candidates of aberrantly expressed genes. Next, the potential functions were investigated for the candidate signatures and their ability to detect CRC and pan-cancers was comprehensively evaluated.

Results

We identified 1841 common DEGs in two independent datasets. Functional enrichment analysis revealed they were mainly related to extracellular structure, biosynthesis, and cell adhesion. The CRC classifier was established based on six genes screened by LASSO regression. Sensitivity, specificity, and area under the ROC curve (AUC) for CRC detection were 79.30%, 80.40%, and 0.85 (0.76–0.92) in the training set, and these indexes achieved 93.20%, 41.80%, and 0.73 (0.65–0.83) in the testing set. For validation set, the sensitivity, specificity, and AUC were 98.90%, 98.00%, and 0.97 (0.94–0.99). The average sensitivities exceeded 90.00% for CRCs with different clinical features. For adenomas detection, the sensitivity and specificity were 74.50% and 64.00%. Besides, the six genes obtained an average AUC of 0.855 for pan-cancer detection.

Conclusion

The six-gene signatures showed ability to detect CRC and pan-cancer samples, which could be served as potential diagnostic markers.

Skin Cancer Research Goes Digital: Looking for Biomarkers within the Droplets

Skin cancer, which includes the most frequent malignant non-melanoma carcinomas (basal cell carcinoma, BCC, and squamous cell carcinoma, SCC), along with the difficult to treat cutaneous melanoma (CM), pose important worldwide issues for the health care system. Despite the improved anti-cancer armamentarium and the latest scientific achievements, many skin cancer patients fail to respond to therapies, due to the remarkable heterogeneity of cutaneous tumors, calling for even more sophisticated biomarker discovery and patient monitoring approaches. Droplet digital polymerase chain reaction (ddPCR), a robust method for detecting and quantifying low-abundance nucleic acids, has recently emerged as a powerful technology for skin cancer analysis in tissue and liquid biopsies (LBs). The ddPCR method, being capable of analyzing various biological samples, has proved to be efficient in studying variations in gene sequences, including copy number variations (CNVs) and point mutations, DNA methylation, circulatory miRNome, and transcriptome dynamics. Moreover, ddPCR can be designed as a dynamic platform for individualized cancer detection and monitoring therapy efficacy. Here, we present the latest scientific studies applying ddPCR in dermato-oncology, highlighting the potential of this technology for skin cancer biomarker discovery and validation in the context of personalized medicine. The benefits and challenges associated with ddPCR implementation in the clinical setting, mainly when analyzing LBs, are also discussed.

Bioinformatics Analysis of Prognosis-Related Genes and Expression of CXCL8 in Colorectal Cancer

Background

Colorectal cancer (CRC), one of the main causes of death, remains a leading cause of mortality in gastrointestinal cancer and tends to affect the younger generation. However, the pathological process of colorectal cancer is unclear. Exploring potential pathogenesis and therapeutic targets of CRC is significant as its high prevalence and high mortality. Nowadays, the rapid development of bioinformatics provides us an opportunity to explore potential molecular markers of CRC.

Materials and Methods

First, three CRC gene chips with paracancerous controls were downloaded from the Gene Expression Omnibus (GEO) database. Second, after combining and batch correcting the three chips using the R language and Perl language, the differentially expressed genes (DEGs) were selected to investigate how they affect the CRC occurrence and development by GO and KEGG enrichment analysis. Third, based on the STRING website and the Cytoscape software, the protein-protein interaction (PPI) network was constructed and the core genes were screened out. Finally, through polymerase chain reaction (PCR) and immunohistochemistry (IHC), the expression and function of the core gene CXCL8 in CRC were explored.

Results

GSE10950, GSE44076, and GSE75970, including 126 intestinal cancer samples and 126 paracancer samples, were screened as the datasets. 192 DEGs were screened, including 43 upregulated genes and 149 downregulated genes. Through the DEGs screened out, GO enrichment analysis, KEGG enrichment analysis, and the construction of PPI interaction network were carried out. Finally, according to the nodes and edges in the PPI network, the DEGs were sorted and the core genes were selected. Through basic experiments, the first ranked CXCL8 was further studied, and the results suggest that the expression of CXCL8 is related to the proliferation, migration, invasion, and even distant metastasis of CRC.

Conclusion

The present study showed that DEGs of CRC are associated with multiple tumor-related biological processes and signaling pathways. The core gene CXCL8 has the potential to be a new therapeutic target for CRC.

Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is among the most common digestive system malignancies worldwide, and its pathogenesis and gene signatures remain unclear. This study explored the genetic characteristics and molecular mechanisms underlying colon cancer development. Three gene expression data sets were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was used to determine differentially expressed genes (DEGs) between COAD and normal tissues. Then, the intersection of the data sets was obtained. Metascape was used to perform the functional enrichment analyses. Next, STRING was used to build protein-protein interaction (PPI) networks. Hub genes were identified and analysed using Cytoscape. Next, survival analysis and expression analysis of the hub genes were performed. ROC curve analysis was performed for further test of the diagnostic efficacy. Finally, alterations in the hub genes were predicted and analysed by cBioPortal. Altogether, 436 DEGs were detected. The DEGs were mainly enriched in cell cycle phase transition, nuclear division, meiotic nuclear division, and cytokinesis. Based on PPI networks, 20 hub genes were selected. Among them, 6 hub genes (CCNB1, CCNA2, AURKA, NCAPG, DLGAP5, and CENPE) showed significant prognostic value in colon cancer (P < 0.05), while 5 hub genes (CDK1, CCNB1, CCNA2, MAD2L1, and DLGAP5) were associated with early colon cancer diagnosis and ROC curve analysis showed good diagnostic accuracy. In conclusion, integrated bioinformatics analysis was used to identify hub genes that reveal the potential mechanism of carcinogenesis and progression of colon cancer. The hub genes might be novel biomarkers for early diagnosis, treatment, and prognosis of colon cancer.

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.

Predictive value of collagen in cancer

Cancer is a complex disease and a significant cause of mortality worldwide. Over the course of nearly all cancer types, collagen within the tumor microenvironment influences emergence, progression, and metastasis. This review discusses collagen regulation within the tumor microenvironment, pathological involvement of collagen, and predictive values of collagen and related extracellular matrix components in main cancer types. A survey of predictive tests leveraging collagen assays using clinical cohorts is presented. A conclusion is that collagen has high predictive value in monitoring cancer processes and stratifying by outcomes. New approaches should be considered that continue to define molecular facets of collagen related to cancer.

Identification of four novel hub genes as monitoring biomarkers for colorectal cancer

Background

It must be admitted that the incidence of colorectal cancer (CRC) was on the rise all over the world, but the related treatment had not caught up. Further research on the underlying pathogenesis of CRC was conducive to improving the survival status of current CRC patients.

Methods

Differentially expressed genes (DEGs) screening were conducted based on “limma” and “RobustRankAggreg” package of R software. Weighted gene co-expression network analysis (WGCNA) was performed in the integrated DEGs that from The Cancer Genome Atlas (TCGA), and all samples of validation were from Gene Expression Omnlbus (GEO) dataset.

Results

The terms obtained in the functional annotation for primary DEGs indicated that they were associated with CRC. The MEyellow stand out whereby showed the significant correlation with clinical feature (disease), and 4 hub genes, including ABCC13, AMPD1, SCNN1B and TMIGD1, were identified in yellow module. Nine datasets from Gene Expression Omnibus database confirmed these four genes were significantly down-regulated and the survival estimates for the low-expression group of these genes were lower than for the high-expression group in Kaplan-Meier survival analysis section. MEXPRESS suggested that down-regulation of some top hub genes may be caused by hypermethylation. Receiver operating characteristic curves indicated that these genes had certain diagnostic efficacy. Moreover, tumor-infiltrating immune cells and gene set enrichment analysis for hub genes suggested that there were some associations between these genes and the pathogenesis of CRC.

Conclusion

This study identified modules that were significantly associated with CRC, four novel hub genes, and further analysis of these genes. This may provide a little new insights and directions into the potential pathogenesis of CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-021-00216-7.

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.

Low expression of bestrophin-2 is associated with poor prognosis in colon cancer

OBJECTIVES

The purpose of this research was to confirm the prognostic value of bestrophin-2 (BEST2), one of the hub genes in colon cancer, via bioinformatics analysis and validation in public databases and immunohistochemistry detection.

METHODS

The GEO2R online tool and Venn diagram software were utilized to identify differentially expressed genes (DEGs) from expression profiles, including GSE20916, GSE44861 and GSE74602, from the Gene Expression Omnibus (GEO). The overall survival (OS) and disease-free survival (DFS) of colon cancer patients from The Cancer Genome Atlas (TCGA) were analyzed through Kaplan-Meier survival curves. Verification of the significance of BEST2 in colon cancer was based on TCGA, Genotype Tissue Expression (GTEx) and 10 datasets from GEO. BEST2 expression was detected with immunohistochemistry (IHC) in 330 colon tissue samples on microarrays including 165 colon cancerand 165 adjacent normal tissues. For further validation, comprehensive analysis from tissue microarrays and multiple datasets was performed by the summarizing of receiver operating characteristic (SROC) curves and the standard mean differences (SMDs). BEST2 expression in various kinds of colon cancer tissues and cell lines in the context of pancancer was obtained from the Expression Atlas database. The CBioPortal database was queried to identify BEST2 gene alterations and mutation status in colon cancer. Correlated genes (CEGs) with BEST2 and DEGs from public database data were assembled for functional and pathway enrichment analysis.

RESULTS

We identified 85 DEGs from the three datasets and screened out BEST2 as a prognostic predictor via the TCGA database. Colon cancer patients with high expression of BEST2 had better survival than patients with low BEST2 (HR = 0.5, P = 0.006) as shown in Kaplan-Meier survival curves in GEPIA. In all, 1463 colon cancer tissues and 1023 colon normal tissues were gathered via public databases as well as in-house tissue microarrays. The comprehensiveexpression analysis suggested low-expression of BEST2 in colon cancer (SMD = -2.48, 95% CI [-3.15- -1.80]) and the notable efficacy of BEST2 expression in differentiating colon cancer from noncancer samples (AUC = 0.97). Gene alteration status of BEST2 occurred in 5% of colon cancer cases, mostly missense mutations and deep deletions. Genes positively correlated with BEST2 and DEGs primarily aggregated in pathways such as anion absorption, digestive juice secretion, cAMP signaling and so on (P < 0.05).

CONCLUSION

Ampleevidencesupportsthe role of BEST2 in distinguishing colon cancer from normal tissues in this research. Low expression of BEST2 is correlated with a shorter OS, which implies that BEST2 can be employed as a potential biomarker and therapeutictarget in colon cancer.

Current advances in prognostic and diagnostic biomarkers for solid cancers: Detection techniques and future challenges

Solid cancers are one of the leading causes of cancer related deaths, characterized by rapid growth of tumour, and local and distant metastases. Current advances on multimodality care have substantially improved local control and metastasis-free survival of patients by resection of primary tumour. The major concern in disease prognosis is the timely detection of resectable or metastatic tumour, thus reinforcing the need for identification of biomarkers for premalignant lesions of solid cancer. This ultimately improves the outcome for the patients. Therefore, the purpose of this review is to update the recent advancements on prognostic and diagnostic biomarkers to enhance early detection of common solid cancers including, breast, lung, colorectal, prostate and stomach cancer. We also provide an insight into Food and Drug Administration (FDA)-approved solid cancers biomarkers; various conventional techniques used for detection of prognostic and diagnostic biomarkers and discuss approaches to turn challenges in this field into opportunities.

Extracellular Matrix Biomarkers in Colorectal Cancer

The cellular microenvironment composition and changes therein play an extremely important role in cancer development. Changes in the extracellular matrix (ECM), which constitutes a majority of the tumor stroma, significantly contribute to the development of the tumor microenvironment. These alterations within the ECM and formation of the tumor microenvironment ultimately lead to tumor development, invasion, and metastasis. The ECM is composed of various molecules such as collagen, elastin, laminin, fibronectin, and the MMPs that cleave these protein fibers and play a central role in tissue remodeling. When healthy cells undergo an insult like DNA damage and become cancerous, if the ECM does not support these neoplastic cells, further development, invasion, and metastasis fail to occur. Therefore, ECM-related cancer research is indispensable, and ECM components can be useful biomarkers as well as therapeutic targets. Colorectal cancer specifically, is also affected by the ECM and many studies have been conducted to unravel the complex association between the two. Here we summarize the importance of several ECM components in colorectal cancer as well as their potential roles as biomarkers.

Machine learning and network-based models to identify genetic risk factors to the progression and survival of colorectal cancer

Colorectal cancer (CRC) is one of the most common and lethal malignant lesions. Determining how the identified risk factors drive the formation and development of CRC could be an essential means for effective therapeutic development. Aiming this, we investigated how the altered gene expression resulting from exposure to putative CRC risk factors contribute to prognostic biomarker identification. Differentially expressed genes (DEGs) were first identified for CRC and other eight risk factors. Gene set enrichment analysis (GSEA) through the molecular pathway and gene ontology (GO), as well as protein-protein interaction (PPI) network, were then conducted to predict the functions of these DEGs. Our identified genes were explored through the dbGaP and OMIM databases to compare with the already identified and known prognostic CRC biomarkers. The survival time of CRC patients was also examined using a Cox Proportional Hazard regression-based prognostic model by integrating transcriptome data from The Cancer Genome Atlas (TCGA). In this study, PPI analysis identified 4 sub-networks and 8 hub genes that may be potential therapeutic targets, including CXCL8, ICAM1, SOD2, CXCL2, CCL20, OIP5, BUB1, ASPM and IL1RN. We also identified seven signature genes (PRR5.ARHGAP8, CA7, NEDD4L, GFR2, ARHGAP8, SMTN, OIP5) in independent analysis and among which PRR5. ARHGAP8 was found in both multivariate analyses and in analyses that combined gene expression and clinical information. This approach provides both mechanistic information and, when combined with predictive clinical information, good evidence that the identified genes are significant biomarkers of processes involved in CRC progression and survival.

Identification of Hub Genes in Different Stages of Colorectal Cancer through an Integrated Bioinformatics Approach

Colorectal cancer (CRC) is the third most common cancer that contributes to cancer-related morbidity. However, the differential expression of genes in different phases of CRC is largely unknown. Moreover, very little is known about the role of stress-survival pathways in CRC. We sought to discover the hub genes and identify their roles in several key pathways, including oxidative stress and apoptosis in the different stages of CRC. To identify the hub genes that may be involved in the different stages of CRC, gene expression datasets were obtained from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) common among the different datasets for each group were obtained using the robust rank aggregation method. Then, gene enrichment analysis was carried out with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Finally, the protein-protein interaction networks were constructed using the Cytoscape software. We identified 40 hub genes and performed enrichment analysis for each group. We also used the Oncomine database to identify the DEGs related to stress-survival and apoptosis pathways involved in different stages of CRC. In conclusion, the hub genes were found to be enriched in several key pathways, including the cell cycle and p53 signaling pathway. Some of the hub genes were also reported in the stress-survival and apoptosis pathways. The hub DEGs revealed from our study may be used as biomarkers and may explain CRC development and progression mechanisms.

Targeting oncogenic mutations in colorectal cancer using cryptotanshinone

Colorectal cancer (CRC) is one of the most prevalent types of cancer in the world and ranks second in cancer deaths in the US. Despite the recent improvements in screening and treatment, the number of deaths associated with CRC is still very significant. The complexities involved in CRC therapy stem from multiple oncogenic mutations and crosstalk between abnormal pathways. This calls for using advanced molecular genetics to understand the underlying pathway interactions responsible for this cancer. In this paper, we construct the CRC pathway from the literature and using an existing public dataset on healthy vs tumor colon cells, we identify the genes and pathways that are mutated and are possibly responsible for the disease progression. We then introduce drugs in the CRC pathway, and using a boolean modeling technique, we deduce the drug combinations that produce maximum cell death. Our theoretical simulations demonstrate the effectiveness of Cryptotanshinone, a traditional Chinese herb derivative, achieved by targeting critical oncogenic mutations and enhancing cell death. Finally, we validate our theoretical results using wet lab experiments on HT29 and HCT116 human colorectal carcinoma cell lines.

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.

Re-engineering of peptides with high binding affinity to develop an advanced electrochemical sensor for colon cancer diagnosis

Colorectal cancer (CRC) develops from polyps in the inner large intestine or rectum and an increasing incidence and high mortality rate has been observed in humans. Currently, colonoscopy is the preferred modality for early CRC diagnosis. However, this technique has several limitations, such as high medical costs and intricate procedures, leading to increasing demands for the development of a new, simple, and affordable diagnostic method. In this study, an advanced electrochemical biosensor based on rationally designed affinity peptides was developed for discriminating adenoma to carcinoma progression. Amino acid-substituted and rationally designed synthetic peptides (BP3-1 to BP3-8) based on in silico modeling studies were chemically synthesized, and covalently immobilized onto a gold electrode using aromatic ring compounds through surface chemistry techniques. The binding performance of the developed sensor system was observed using square wave voltammetry (SWV). The peptide BP3-2 was selected depending on its relative binding affinity; SWV indicated the limit of detection of BP3-2 for LRG1 to be 0.025 μg/mL. This sensor could distinguish the adenoma-carcinoma transition with improved binding abilities (specificity and selectivity), and stability in plasma samples spiked with LRG1 and real samples from patients with CRC. These results indicate that this electrochemical sensor system can be used for early monitoring of the colorectal adenoma to carcinoma progression.

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.

Mechanical Cues Affect Migration and Invasion of Cells From Three Different Directions

Cell migration and invasion is a key driving factor for providing essential cellular functions under physiological conditions or the malignant progression of tumors following downward the metastatic cascade. Although there has been plentiful of molecules identified to support the migration and invasion of cells, the mechanical aspects have not yet been explored in a combined and systematic manner. In addition, the cellular environment has been classically and frequently assumed to be homogeneous for reasons of simplicity. However, motility assays have led to various models for migration covering only some aspects and supporting factors that in some cases also include mechanical factors. Instead of specific models, in this review, a more or less holistic model for cell motility in 3D is envisioned covering all these different aspects with a special emphasis on the mechanical cues from a biophysical perspective. After introducing the mechanical aspects of cell migration and invasion and presenting the heterogeneity of extracellular matrices, the three distinct directions of cell motility focusing on the mechanical aspects are presented. These three different directions are as follows: firstly, the commonly used invasion tests using structural and structure-based mechanical environmental signals; secondly, the mechano-invasion assay, in which cells are studied by mechanical forces to migrate and invade; and thirdly, cell mechanics, including cytoskeletal and nuclear mechanics, to influence cell migration and invasion. Since the interaction between the cell and the microenvironment is bi-directional in these assays, these should be accounted in migration and invasion approaches focusing on the mechanical aspects. Beyond this, there is also the interaction between the cytoskeleton of the cell and its other compartments, such as the cell nucleus. In specific, a three-element approach is presented for addressing the effect of mechanics on cell migration and invasion by including the effect of the mechano-phenotype of the cytoskeleton, nucleus and the cell's microenvironment into the analysis. In precise terms, the combination of these three research approaches including experimental techniques seems to be promising for revealing bi-directional impacts of mechanical alterations of the cellular microenvironment on cells and internal mechanical fluctuations or changes of cells on the surroundings. Finally, different approaches are discussed and thereby a model for the broad impact of mechanics on cell migration and invasion is evolved.

Immune-Related Gene Expression and Cytokine Secretion Is Reduced Among African American Colon Cancer Patients

Background: Colorectal cancer is the third most deadly cancer among African Americans (AA). When compared to Caucasian Americans (CA), AA present with more advanced disease and lower survival rates. Here, we investigated if differences in tumor immunology could be contributive to disparities observed between these populations.

Methods: We examined gene expression of tumor and non-tumor adjacent tissues from AA and CA by whole transcriptome sequencing, and generated scores for immune cell populations by NanoString. In addition, we utilized “The Cancer Genome Atlas” (TCGA) database from AA and CA as a validation cohort. Finally, we measured the secretion of cytokines characteristic of effector T helper cell (T_h) subsets by ELISA using plasma from each AA and CA participant.

Results: Colon tumors from AA patients showed significant fold-change increase in gene expression when compared to CA for FOXP3 (6.22 vs. 3.22), IL1B (103 vs. 11.4) and IL8 (220 vs. 28.9) (p < 0.05). In contrast, among CA we observed statistically higher gene expression of markers associated with antitumor activity such as GZMB (Granzyme B), IFNG and the immunotherapy targets PDL1 (CD274) and CTLA4 (p < 0.05). TCGA data validated our observed higher gene expression of GZMB and PDL1 in CA patients when compared to AA. Notably, our observations on immune cell populations show that AA tumors have significantly higher number of exhausted CD8+ cells (p < 0.01), mast cells (p < 0.02) and increased T regulatory cells when compared to CA. AA colon cancer patients differed from CA in cytokine production patterns in plasma (i.e., reduced IL-12).

Conclusions: Our study demonstrates significant differences of the immunological profiles of colon tumors from AA compared to CA that suggest a deficiency of appropriate immune defense mechanisms in terms of gene expression, recruitment of immune cells and systemic secretion of cytokines. As such, these immune differences could be mitigated through population-specific therapeutic approaches.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Human Microphysiological Models of Intestinal Tissue and Gut Microbiome

The gastrointestinal (GI) tract is a complex system responsible for nutrient absorption, digestion, secretion, and elimination of waste products that also hosts immune surveillance, the intestinal microbiome, and interfaces with the nervous system. Traditional in vitro systems cannot harness the architectural and functional complexity of the GI tract. Recent advances in organoid engineering, microfluidic organs-on-a-chip technology, and microfabrication allows us to create better in vitro models of human organs/tissues. These micro-physiological systems could integrate the numerous cell types involved in GI development and physiology, including intestinal epithelium, endothelium (vascular), nerve cells, immune cells, and their interplay/cooperativity with the microbiome. In this review, we report recent progress in developing micro-physiological models of the GI systems. We also discuss how these models could be used to study normal intestinal physiology such as nutrient absorption, digestion, and secretion as well as GI infection, inflammation, cancer, and metabolism.

METTL14-mediated N6-methyladenosine modification of SOX4 mRNA inhibits tumor metastasis in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the leading causes of tumor-related death worldwide, and its main cause of death is distant metastasis. Methyltransferase-like 14(METTL14), a major RNA N6-adenosine methyltransferase, is involved in tumor progression via regulating RNA function. The goal of the study is to uncover the biological function and molecular mechanism of METTL14 in CRC.

METHODS

Quantitative real-time PCR (qRT-PCR), western blot and immunohistochemical (IHC) assays were employed to detect METTL14 and SOX4 in CRC cell lines and tissues. The biological functions of METTL14 were demonstrated using in vitro and in vivo experiments. Chromatin immunoprecipitation (ChIP), Transcrptomic RNA sequencing (RNA-Seq), m6A-RNA immunoprecipitation sequencing (MeRIP-Seq), RNA immunoprecipitation and luciferase reporter assays were used to explore the mechanism of METTL14 action.

RESULTS

METTL14 expression was significantly downregulated in CRC and decreased METTL14 was associated with poor overall survival (OS). Both the univariate and multivariate Cox regression analysis indicated that METTL14 was an independent prognostic factor in CRC. Moreover, lysine-specific histone demethylase 5C(KDM5C)-mediated demethylation of histone H3 lysine 4 tri-methylation(H3K4me3) in the promoter of METTL14 inhibited METTL14 transcription. Functionally, we verified that METTL14 inhibited CRC cells migration, invasion and metastasis through in vitro and in vivo assays, respectively. Furthermore, we identified SRY-related high-mobility-group box 4(SOX4) as a target of METTL14-mediated m6A modification. Knockdown of METTL14 markedly abolished SOX4 mRNA m6A modification and elevated SOX4 mRNA expression. We also revealed that METTL14-mediated SOX4 mRNA degradation relied on the YTHDF2-dependent pathway. Lastly, we demonstrated that METTL14 might inhibit CRC malignant process partly through SOX4-mediated EMT process and PI3K/Akt signals.

CONCLUSIONS

Decreased METTL14 facilitates tumor metastasis in CRC, suggesting that METTL14 might be a potential prognostic biomarker and effective therapeutic target for CRC.

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.

Serum SYPL1 is a promising diagnostic biomarker for colorectal cancer

BACKGROUND

At present, the overall sensitivity and specificity of blood biomarkers are insufficient for a diagnosis of colorectal cancer (CRC).

METHODS

We analyzed the serum synaptophysin like 1 (sSYPL1) in controls, adenoma patients, CRC patients, pre- and postoperative CRC patients by ELISA.

RESULTS

The upregulation of SYPL1 was confirmed in CRC tissues at both mRNA and protein levels. Consistently, sSYPL1 was significantly higher in CRC patients than in either controls (t = 14.50, P < 0.0001) or adenoma patients (t = 10.56, P < 0.0001) and was associated with lymph node invasion (χ² = 4.27, P = 0.039). ROC curves showed that sSYPL1 performed superbly in distinguishing CRC patients from controls (AUC: 0.9481; sensitivity: 86.09%, specificity: 91.01%) and adenoma (AUC: 0.8631; sensitivity: 98.68%, specificity: 78.08%). This performance was much better than that of carcinoembryonic antigen (CEA) or carbohydrate antigen 19-9 (CA19-9). Even for patients with low CEA levels (under 5 ng/mL), SYPL1 maintained the same high performance for identification of CRC. Furthermore, sSYPL1 levels declined significantly after radical surgery (t = 5.903, P < 0.0001).

CONCLUSION

sSYPL1 might be an outstanding marker for CRC diagnosis, especially for patients with low CEA levels.

Identification and Verification of Core Genes in Colorectal Cancer

Colorectal cancer, a malignant neoplasm that occurs in the colorectal mucosa, is one of the most common types of gastrointestinal cancer. Colorectal cancer has been studied extensively, but the molecular mechanisms of this malignancy have not been characterized. This study identified and verified core genes associated with colorectal cancer using integrated bioinformatics analysis. Three gene expression profiles (GSE15781, GSE110223, and GSE110224) were downloaded from the Gene Expression Omnibus (GEO) databases. A total of 87 common differentially expressed genes (DEGs) among GSE15781, GSE110223, and GSE110224 were identified, including 19 upregulated genes and 68 downregulated genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed for common DEGs using clusterProfiler. These common DEGs were significantly involved in cancer-associated functions and signaling pathways. Then, we constructed protein-protein interaction networks of these common DEGs using Cytoscape software, which resulted in the identification of the following 10 core genes: SST, PYY, CXCL1, CXCL8, CXCL3, ZG16, AQP8, CLCA4, MS4A12, and GUCA2A. Analysis using qRT-PCR has shown that SST, CXCL8, and MS4A12 were significant differentially expressed between colorectal cancer tissues and normal colorectal tissues (P < 0.05). Gene Expression Profiling Interactive Analysis (GEPIA) overall survival (OS) has shown that low expressions of AQP8, ZG16, CXCL3, and CXCL8 may predict poor survival outcome in colorectal cancer. In conclusion, the core genes identified in this study contributed to the understanding of the molecular mechanisms involved in colorectal cancer development and may be targets for early diagnosis, prevention, and treatment of colorectal cancer.

Functional Interplay Between Collagen Network and Cell Behavior Within Tumor Microenvironment in Colorectal Cancer

Colorectal cancer is the second most common cancer diagnosed in men and the third most commonly occurring in women worldwide. Interactions between cells and the surrounding extracellular matrix (ECM) are involved in tumor development and progression of many types of cancer. The organization of the ECM molecules provides not only physical scaffoldings and dynamic network into which cells are embedded but also allows the control of many cellular behaviors including proliferation, migration, differentiation, and survival leading to homeostasis and morphogenesis regulation. Modifications of ECM composition and mechanical properties during carcinogenesis are critical for tumor initiation and progression. The core matrisome consists of five classes of macromolecules, which are collagens, laminins, fibronectin, proteoglycans, and hyaluronans. In most tissues, fibrillar collagen is the major component of ECM. Cells embedded into fibrillar collagen interact with it through their surface receptors, such as integrins and discoidin domain receptors (DDRs). On the one hand, cells incorporate signals from ECM that modify their functionalities and behaviors. On the other hand, all cells within tumor environment (cancer cells, cancer-associated fibroblasts, endothelial cells, and immune cells) synthesize and secrete matrix macromolecules under the control of multiple extracellular signals. This cell-ECM dialog participates in a dynamic way in ECM formation and its biophysical and biochemical properties. Here, we will review the functional interplay between cells and collagen network within the tumor microenvironment during colorectal cancer progression.

Proteomic Profiling of Colon Cancer Tissues: Discovery of New Candidate Biomarkers

Colon cancer is an aggressive tumor form with a poor prognosis. This study reports a comparative proteomic analysis performed by using two-dimensional differential in-gel electrophoresis (2D-DIGE) between 26 pooled colon cancer surgical tissues and adjacent non-tumoral tissues, to identify potential target proteins correlated with carcinogenesis. The DAVID functional classification tool revealed that most of the differentially regulated proteins, acting both intracellularly and extracellularly, concur across multiple cancer steps. The identified protein classes include proteins involved in cell proliferation, apoptosis, metabolic pathways, oxidative stress, cell motility, Ras signal transduction, and cytoskeleton. Interestingly, networks and pathways analysis showed that the identified proteins could be biologically inter-connected to the tumor-host microenvironment, including innate immune response, platelet and neutrophil degranulation, and hemostasis. Finally, transgelin (TAGL), here identified for the first time with four different protein species, collectively down-regulated in colon cancer tissues, emerged as a top-ranked biomarker for colorectal cancer (CRC). In conclusion, our findings revealed a different proteomic profiling in colon cancer tissues characterized by the deregulation of specific pathways involved in hallmarks of cancer. All of these proteins may represent promising novel colon cancer biomarkers and potential therapeutic targets, if validated in larger cohorts of patients.

Gene Biomarkers Derived from Clinical Data of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common cancer of high mortality, mainly due to the difficulty in diagnosis during its clinical stage. Here we aim to find the gene biomarkers, which are of important significance for diagnosis and treatment. In this work, 3682 differentially expressed genes on HCC were firstly differentiated based on the Cancer Genome Atlas database (TCGA). Co-expression modules of these differentially expressed genes were then constructed based on the weighted correlation network algorithm. The correlation coefficient between the co-expression module and clinical data from the Broad GDAC Firehose was thereafter derived. Finally, the interactive network of genes was then constructed. Then, the hub genes were used to implement enrichment analysis and pathway analysis in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. Results revealed that the abnormally expressed genes in the module played an important role in the biological process including cell division, sister chromatid cohesion, DNA repair, and G1/S transition of mitotic cell cycle. Meanwhile, these genes also enriched in a few crucial pathways related to Cell cycle, Oocyte meiosis, and p53 signaling. Via investigating the closeness centrality of the interactive network, eight gene biomarkers including the CKAP2, TPX2, CDCA8, KIFC1, MELK, SGO1, RACGAP1, and KIAA1524 gene were discovered, whose functions had been indeed revealed to be correlated with HCC. This study, therefore, suggests that the abnormal expression of those eight genes may be taken as gene biomarkers of HCC.