Diagnostic and prognostic values of integrin α subfamily mRNA expression in colon adenocarcinoma

M2 macrophage-derived exosomal circTMCO3 acts through miR-515-5p and ITGA8 to enhance malignancy in ovarian cancer

Tumor-associated macrophages of the M2 phenotype promote cancer initiation and progression. Importantly, M2 macrophage-derived exosomes play key roles in the malignancy of cancer cells. Here, we report that circTMCO3 is upregulated in ovarian cancer patients, and its high expression indicates poor survival. M2-derived exosomes promote proliferation, migration, and invasion in ovarian cancer, but these effects are abolished by knockdown of circTMCO3. Furthermore, circTMCO3 functions as a competing endogenous RNA for miR-515-5p to reduce its abundance, thus upregulating ITGA8 in ovarian cancer. miR-515-5p inhibits ovarian cancer malignancy via directly downregulating ITGA8. The decreased oncogenic activity of circTMCO3-silencing exosomes is reversed by miR-515-5p knockdown or ITGA8 overexpression. Exosomal circTMCO3 promotes ovarian cancer progression in nude mice. Thus, M2 macrophage-derived exosomes promote malignancy by delivering circTMCO3 and targeting the miR-515-5p/ITGA8 axis in ovarian cancer. Our findings not only provide mechanistic insights into ovarian cancer progression, but also suggest potential therapeutic targets.

Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) accounts for the majority of lung cancers, and the survival of patients with advanced LUAD is poor. The extracellular matrix (ECM) is a fundamental component of the tumor microenvironment (TME) that determines the oncogenesis and antitumor immunity of solid tumors. However, the prognostic value of extracellular matrix-related genes (ERGs) in LUAD remains unexplored. Therefore, this study is aimed to explore the prognostic value of ERGs in LUAD and establish a classification system to predict the survival of patients with LUAD.

Methods: LUAD samples from The Cancer Genome Atlas (TCGA) and GSE37745 were used as discovery and validation cohorts, respectively. Prognostic ERGs were identified by univariate Cox analysis and used to construct a prognostic signature by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. The extracellular matrix-related score (ECMRS) of each patient was calculated according to the prognostic signature and used to classify patients into high- and low-risk groups. The prognostic performance of the signature was evaluated using Kaplan–Meier curves, Cox regression analyses, and ROC curves. The relationship between ECMRS and tumor immunity was determined using stepwise analyses. A nomogram based on the signature was established for the convenience of use in the clinical practice. The prognostic genes were validated in multiple databases and clinical specimens by qRT-PCR.

Results: A prognostic signature based on eight ERGs (FERMT1, CTSV, CPS1, ENTPD2, SERPINB5, ITGA8, ADAMTS8, and LYPD3) was constructed. Patients with higher ECMRS had poorer survival, lower immune scores, and higher tumor purity in both the discovery and validation cohorts. The predictive power of the signature was independent of the clinicopathological parameters, and the nomogram could also predict survival precisely.

Conclusions: We constructed an ECM-related gene signature which can be used to predict survival and tumor immunity in patients with LUAD. This signature can serve as a novel prognostic indicator and therapeutic target in LUAD.

Emerging Roles and Mechanisms of lncRNA FOXD3-AS1 in Human Diseases

Numerous long noncoding RNAs (lncRNAs) have been identified as powerful regulators of human diseases. The lncRNA FOXD3-AS1 is a novel lncRNA that was recently shown to exert imperative roles in the initialization and progression of several diseases. Emerging studies have shown aberrant expression of FOXD3-AS1 and close correlation with pathophysiological traits of numerous diseases, particularly cancers. More importantly, FOXD3-AS1 was also found to ubiquitously impact a range of biological functions. This study aims to summarize the expression, associated clinicopathological features, major functions and molecular mechanisms of FOXD3-AS1 in human diseases and to explore its possible clinical applications.

ECM-Receptor Regulatory Network and Its Prognostic Role in Colorectal Cancer

Interactions of the extracellular matrix (ECM) and cellular receptors constitute one of the crucial pathways involved in colorectal cancer progression and metastasis. With the use of bioinformatics analysis, we comprehensively evaluated the prognostic information concentrated in the genes from this pathway. First, we constructed a ECM-receptor regulatory network by integrating the transcription factor (TF) and 5'-isomiR interaction databases with mRNA/miRNA-seq data from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD). Notably, one-third of interactions mediated by 5'-isomiRs was represented by noncanonical isomiRs (isomiRs, whose 5'-end sequence did not match with the canonical miRBase version). Then, exhaustive search-based feature selection was used to fit prognostic signatures composed of nodes from the network for overall survival prediction. Two reliable prognostic signatures were identified and validated on the independent The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) cohort. The first signature was made up by six genes, directly involved in ECM-receptor interaction: AGRN, DAG1, FN1, ITGA5, THBS3, and TNC (concordance index 0.61, logrank test p = 0.0164, 3-years ROC AUC = 0.68). The second hybrid signature was composed of three regulators: hsa-miR-32-5p, NR1H2, and SNAI1 (concordance index 0.64, logrank test p = 0.0229, 3-years ROC AUC = 0.71). While hsa-miR-32-5p exclusively regulated ECM-related genes (COL1A2 and ITGA5), NR1H2 and SNAI1 also targeted other pathways (adhesion, cell cycle, and cell division). Concordant distributions of the respective risk scores across four stages of colorectal cancer and adjacent normal mucosa additionally confirmed reliability of the models.

Exploration of the Proteomic Landscape of Small Extracellular Vesicles in Serum as Biomarkers for Early Detection of Colorectal Neoplasia

Background

Patient participation in colorectal cancer (CRC) screening via a stool test and colonoscopy is suboptimal, but participation can be improved by the development of a blood test. However, the suboptimal detection abilities of blood tests for advanced neoplasia, including advanced adenoma (AA) and CRC, limit their application. We aimed to investigate the proteomic landscape of small extracellular vesicles (sEVs) from the serum of patients with colorectal neoplasia and identify specific sEV proteins that could serve as biomarkers for early diagnosis.

Materials and Methods

We enrolled 100 patients including 13 healthy subjects, 12 non-AAs, 13 AAs, and 16 stage-I, 15 stage-II, 16 stage-III, and 15 stage-IV CRCs. These patients were classified as normal control, early neoplasia, and advanced neoplasia. The sEV proteome was explored by liquid chromatography-tandem mass spectrometry. Generalized association plots were used to integrate the clustering methods, visualize the data matrix, and analyze the relationship. The specific sEV biomarkers were identified by a decision tree via Orange3 software. Functional enrichment analysis was conducted by using the Ingenuity Pathway Analysis platform.

Results

The sEV protein matrix was identified from the serum of 100 patients and contained 3353 proteins, of which 1921 proteins from 98 patients were finally analyzed. Compared with the normal control, subjects with early and advanced neoplasia exhibited a distinct proteomic distribution in the data matrix plot. Six sEV proteins were identified, namely, GCLM, KEL, APOF, CFB, PDE5A, and ATIC, which properly distinguished normal control, early neoplasia, and advanced neoplasia patients from each other. Functional enrichment analysis revealed that APOF⁺ and CFB⁺ sEV associated with clathrin-mediated endocytosis signaling and the complement system, which have critical implications for CRC carcinogenesis.

Conclusion

Patients with colorectal neoplasia had a distinct sEV proteome expression pattern in serum compared with those patients who were healthy and did not have neoplasms. Moreover, the six identified specific sEV proteins had the potential to discriminate colorectal neoplasia between early-stage and advanced neoplasia. Collectively, our study provided a six-sEV protein biomarker panel for CRC diagnosis at early or advanced stages. Furthermore, the implication of the sEV proteome in CRC carcinogenesis via specific signaling pathways was explored.

Transcriptome analysis of potential candidate genes and molecular pathways in colitis-associated colorectal cancer of Mkp-1-deficient mice

BACKGROUND

The nuclear phosphatase mitogen-activate protein kinase phosphatase-1 (MKP-1) is a key negative regulator of the innate immune response through the regulation of the biosynthesis of proinflammatory cytokines. In colorectal cancer (CRC), which is induced mainly by chronic inflammation, Mkp-1 overexpression was found in addition to disturbances in Mkp-1 functions, which may play a role in cancer development in different types of tumors. However, the potential molecular mechanisms by which Mkp-1 influences CRC development is not clear. Here, we performed global gene expression profiling of Mkp-1 KO mice using RNA sequencing (RNA-seq) to explore the role of Mkp-1 in CRC progression using transcriptome analysis.

METHODS

Azoxymethane/dextran sodium sulfate (AOM/DSS) mouse models were used to examine the most dramatic molecular and signaling changes that occur during different phases of CRC development in wild-type mice and Mkp-1 KO mice. Comprehensive bioinformatics analyses were used to elucidate the molecular processes regulated by Mkp-1. Differentially expressed genes (DEGs) were identified and functionally analyzed by Gene Ontology (GO), Kyoto Enrichment of Genes and Genomes (KEGG). Then, protein-protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software.

RESULTS

Persistent DEGs were different in adenoma and carcinoma stage (238 & 251, respectively) and in WT and MKp-1 KO mice (221& 196, respectively). Mkp-1 KO modulated key molecular processes typically activated in cancer, in particular, cell adhesion, ion transport, extracellular matrix organization, response to drug, response to hypoxia, and response to toxic substance. It was obvious that these pathways are closely associated with cancer development and metastasis. From the PPI network analyses, nine hub genes associated with CRC were identified.

CONCLUSION

These findings suggest that MKp-1 and its hub genes may play a critical role in cancer development, prognosis, and determining treatment outcomes. We provide clues to build a potential link between Mkp-1 and colitis-associated tumorigenesis and identify areas requiring further investigation.

Emerging technologies provide insights on cancer extracellular matrix biology and therapeutics

Recent engineering technologies have transformed traditional perspectives of cancer to include the important role of the extracellular matrix (ECM) in recapitulating the malignant behaviors of cancer cells. Novel biomaterials and imaging technologies have advanced our understanding of the role of ECM density, structure, mechanics, and remodeling in tumor cell-ECM interactions in cancer biology and have provided new approaches in the development of cancer therapeutics. Here, we review emerging technologies in cancer ECM biology and recent advances in engineered systems for evaluating cancer therapeutics and provide new perspectives on how engineering tools present an opportunity for advancing the modeling and treatment of cancer. This review offers the cell biology and cancer cell biology communities insight into how engineering tools can improve our understanding of cancer ECM biology and therapeutic development.

Investigation and verification of the clinical significance and perspective of natural killer group 2 member D ligands in colon adenocarcinoma

This study investigated and verified the diagnostic and prognostic values of natural killer group 2 member D ligand (NKG2DL) genes in colon adenocarcinoma (COAD). We downloaded NKG2DLs expression data and corresponding clinical parameters from The Cancer Genome Atlas (TCGA) and used bioinformatics techniques to investigate the values of NKG2DLs in COAD. Then, we used the GSE40967 cohort to verify the prognostic value of NKG2DLs. Finally, we verified the ULBP2 expression level in tissues, and also investigated the diagnostic and prognostic values of ULBP2 in COAD. The diagnostic receiver operating characteristic curves showed that ULBP1, ULBP2, ULBP3, and RAET1L had high diagnostic values in COAD [Area Under Curve (AUC) > 0.9]. In TCGA cohort, the univariate and multivariate survival analyses suggested that ULBP2 was correlated with the prognosis of COAD recurrence-free survival (RFS) and overall survival (OS). In GSE40967 cohort, ULBP2 was associated with CC RFS and OS. Reverse transcription-quantitative polymerase chain reaction and immunohistochemistry results showed that ULBP2 was highly expressed in COAD tumor tissues (P < 0.05) and both had diagnostic values (AUC > 0.7). Validated survival analysis showed that the high expression of ULBP2 had a worse prognosis in COAD OS and RFS. Thus, ULBP2 might be an independent diagnostic and prognostic biomarker of COAD.

Expression and Prognostic Analysis of Integrins in Gastric Cancer

Background

Integrins are involved in the biological process of a variety of cancers, but their importance in the diagnosis and prognosis of gastric cancer (GC) is still unclear. Therefore, this study aimed at exploring the significance of ITG gene expression in GC to evaluate its diagnosis and prognosis.

Methods

GEPIA data were used to evaluate the mRNA expression of ITG genes in GC patients. The prognostic value of these genes was assessed by analyzing their mRNA expression using the Kaplan–Meier curve. The biological function of ITG genes was evaluated by GC tissue sequencing combined with GSEA bioinformatics. Based on the sequencing data, ITGA5 with the largest expression difference was selected for verification, and RT-PCR was used to verify its mRNA expression level in 40 pairs of GC and normal tissues.

Results

ITG (A2, A3, A4, A5, A6, A11, AE, AL, AM, AV, AX, B1, B2, B4, B5, B6, and B8) was highly expressed in GC tissues, while ITGA8 was low, compared with their expression in normal tissues. RNA-seq data shows that ITG (A2, A5, A11, AV, and B1) expression was associated with poor prognosis and overall survival. In addition, combined with the results of GC tissue mRNA sequencing, it was further found that the differentially expressed genes in the ITGs genes. ITGA5 was highly expressed in GC tissues compared with its expression in normal tissues, as evaluated by qRT–PCR (P < 0.001) and ROC (P < 0.001, AUC (95% CI) = 0.747 (0.641–0.851)), and confirmed that ITGA5 expression was a potential diagnostic marker for GC. Bioinformatics analysis revealed that the signaling pathway involved in ITGA5 was mainly enriched in focal adhesion, ECM-receptor interaction, and PI3K-AKT and was mainly involved in biological processes such as cell adhesion, extracellular matrix, and cell migration.

Conclusion

This study suggested that ITGs were associated with the diagnosis and prognosis of GC and discovered the prognostic value and biological role of ITGA5 in GC. Thus, ITGA5 might be used as a potential diagnostic marker for GC.

Progressive and Prognostic Performance of an Extracellular Matrix-Receptor Interaction Signature in Gastric Cancer

The role of an extracellular matrix- (ECM-) receptor interaction signature has not been fully clarified in gastric cancer. This study performed comprehensive analyses on the differentially expressed ECM-related genes, clinicopathologic features, and prognostic application in gastric cancer. The differentially expressed genes between tumorous and matched normal tissues in The Cancer Genome Atlas (TCGA) and validation cohorts were identified by a paired t-test. Consensus clusters were built to find the correlation between clinicopathologic features and subclusters. Then, the least absolute shrinkage and selection operator (lasso) method was used to construct a risk score model. Correlation analyses were made to reveal the relation between risk score-stratified subgroups and clinicopathologic features or significant signatures. In TCGA (26 pairs) and validation cohort (134 pairs), 25 ECM-related genes were significantly highly expressed and 11 genes were downexpressed in gastric cancer. ECM-based subclusters were slightly related to clinicopathologic features. We constructed a risk score model = 0.081∗log₂ (CD36) + 0.043∗log₂ (COL5A2) + 0.001∗log₂ (ITGB5) + 0.039∗log₂ (SDC2) + 0.135∗log₂ (SV2B) + 0.012∗log₂ (THBS1) + 0.068∗log₂ (VTN) + 0.023∗log₂ (VWF). The risk score model could well predict the outcome of patients with gastric cancer in both training (n = 351, HR: 1.807, 95% CI: 1.292-2.528, P = 0.00046) and validation (n = 300, HR: 1.866, 95% CI: 1.347-2.584, P = 0.00014) cohorts. Besides, risk score-based subgroups were associated with angiogenesis, cell adhesion molecules, complement and coagulation cascades, TGF-beta signaling, and mismatch repair-relevant signatures (P < 0.0001). By univariate (1.845, 95% CI: 1.382-2.462, P < 0.001) and multivariate (1.756, 95% CI: 1.284-2.402, P < 0.001) analyses, we regarded the risk score as an independent risk factor in gastric cancer. Our findings revealed that ECM compositions became accomplices in the tumorigenesis, progression, and poor survival of gastric cancer.

Periostin regulates autophagy through integrin α5β1 or α6β4 and an AKT-dependent pathway in colorectal cancer cell migration

Colorectal cancer (CRC) is one of the most fatal cancers with highly invasive properties. The progression of CRC is determined by the driving force of periostin (PN) from cancer‐associated fibroblasts (CAFs) in the tumour microenvironment. This present work aims to investigate autophagy‐mediated CRC invasion via the receptor integrin (ITG) by PN. The level of PN in 410 clinical CRC tissues was found increased and was an independent poor prognosis marker (HR = 2.578, 95% CI = 1.218‐5.457, P‐value = .013) with a significant correlation with overall survival time (P‐value < .001). PN activated proliferation, migration and invasion of CRC cells, but with reduced autophagy. Interestingly, the reduction of LC3 autophagic protein corresponded to the increased ability of CRC cell migration. The siITGα5‐treated HT‐29 and siITGβ4‐treated HCT‐116 CRC cells attenuated epithelial‐to‐mesenchymal transitions (EMT)‐related genes and pAKT compared with those in siITG‐untreated cells. The reduction of pAKT by a PI3K inhibitor significantly restored autophagy in CRC cells. These evidences confirmed the effect of PN through either ITGα5β1 or ITGα6β4 and the AKT‐dependent pathway to control autophagy‐regulated cell migration. In conclusion, these results exhibited the impact of PN activation of ITGα5β1 or ITGα6β4 through pAKT in autophagy‐mediated EMT and migration in CRC cells.

Estrogen receptor α is involved in the regulation of ITGA8 methylation in estrogen receptor-positive breast cancer

Background

Integrin subunit α 8 (ITGA8) methylation has been associated with the development of several cancers, but its contribution to breast cancer remains unclear. The present study aimed to investigate the methylation status of ITGA8, and the underlying regulatory mechanisms of ITGA8 methylation in breast cancer.

Methods

ITGA8 expression was investigated using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database and the Breast Cancer Gene-Expression Miner v.4.4 (bc-GenExMiner v4.4). The association between ITGA8 expression levels and the survival rate of breast cancer patients was evaluated using The Cancer Genome Atlas (TCGA) database and Gene Expression-based Outcome for Breast Cancer Online (GOBO): Gene Set Analysis. Methylation-specific PCR (MSP) was used to detect the methylation of ITGA8. Protein level of ITGA8 was determined by Western blot analysis.

Results

ITGA8 was expressed at low levels in human breast cancer cells compared to non-tumorigenic breast cells and breast tissue, and was upregulated in estrogen receptor (ER)-positive tissue compared with ER-negative tissue (P<0.01). ITGA8 gene expression was negatively associated with breast tumor stage and survival rate in all breast cancer patients. However, ER-positive patients with low ITGA8 expression showed poorer distant metastasis-free survival (DMFS) and recurrence-free survival (RFS) rates than patients with high ITGA8 expression. This was not observed in the ER-negative population. Mechanistically speaking, hypermethylation of ITGA8 was discovered in ER-positive breast cancer cells. Administration of the methylation inhibitor, 5-aza-2’-deoxycytidine (5-aza-dC), significantly elevated protein expression of ITGA8 in ER-positive breast cancer cells compared to ER-negative cells. The positive association between ITGA8 status and methylation was also observed in clinical tissue specimens. When treated with 17-beta-estradiol, an antagonist of ERα, 5-aza-dC-induced upregulation of ITGA8 in ER-positive breast cancer cells was no longer observed.

Conclusions

Low ITGA8 expression in ER-positive breast cancer might be caused by the hypermethylation of ITGA8, a process dependent on ERα. Our findings provide an important foundation for investigations into ITGA8-targeted treatment strategies for ER-positive breast cancer.