SPP1, analyzed by bioinformatics methods, promotes the metastasis in colorectal cancer by activating EMT pathway

Actin-like protein 8 promotes cell proliferation, colony-formation, proangiogenesis, migration and invasion in lung adenocarcinoma cells

Background

Non‐small cell lung cancer (NSCLC) is the leading cause of cancer‐associated mortality worldwide of which lung adenocarcinoma (LUAD) is the most common. The identification of oncogenes and effective drug targets is the key to individualized LUAD treatment. Actin‐like protein 8 (ACTL8), a member of the cancer/testis antigen family, is associated with tumor growth and patient prognosis in various types of cancer. However, whether ACTL8 is involved in the development of LUAD remains unknown. The aim of the present study was to demonstrate the role of ACTL8 in human LUAD cells.

Methods

The expression of ACTL8 in LUAD tissues and cell lines was assessed using immunohistochemistry and western blotting. Additionally, plasmids expressing ACTL8‐specific short hairpin RNAs were used to generate lentiviruses which were subsequently used to infect A549 and NCI‐H1975 human LUAD cells. Cell proliferation, migration, invasion and apoptosis, as well as cell cycle progression and the expression of protein markers of epithelial to mesenchymal transition were investigated. A549 cell tumor growth in nude mice was also examined.

Results

The results showed that ACTL8 was highly expressed in A549 and NCI‐H1975 LUAD cell lines. Additionally, ACTL8‐knockdown inhibited proliferation, colony formation, cell cycle progression, migration and invasion, and increased apoptosis in both cell lines. Furthermore, in vivo experiments in nude mice revealed that ACTL8‐knockdown inhibited A549 cell tumor growth.

Conclusion

These results suggest that ACTL8 serves an oncogenic role in human LUAD cells, and that ACTL8 may represent a potential therapeutic target for LUAD.

Key points

Our results suggest that ACTL8 serves an oncogenic role in human LUAD cells, and that ACTL8 may represent a potential therapeutic target for LUAD.

Association between the expression of secreted phosphoprotein - related genes and prognosis of human cancer

Background

While many studies have assessed the predictive value of secreted phosphoprotein (SPP) genes in cancer, the findings have been inconsistent. To resolve these inconsistencies, we systematically analyzed the available data to determine whether SPP1 and SPP2 are prognostic markers in the context of human cancer.

Methods

The expression of SPP1 and SPP2 was assessed by Oncomine analysis. The PrognoScan database was used to assess the prognostic value of SPP1 and SPP2, with cBioPortal used to assess copy number variations. The STRING database was used to generate a Protein - Protein Interaction (PPI) network for SPP genes.

Results

SPP1 was more likely to be over-expressed in breast, bladder, colorectal, head, neck, liver, lung, and esophageal cancers. SPP2 was expressed at lower levels in colorectal cancer, leukemia, liver cancer and pancreatic cancer. In addition, SPP1 and SPP2 mutations mainly occurred in cutaneous melanoma and endometrial cancer.

Conclusions

Our results suggest that SPP1 and SPP2 may be effective therapeutic or diagnostic targets in certain cancers. Further research is required to confirm these results and verify the value of SPP1 and SPP2 as clinical markers of cancer prognosis.

Comprehensive Analysis of Therapy-Related Messenger RNAs and Long Noncoding RNAs as Novel Biomarkers for Advanced Colorectal Cancer

Colorectal cancer (CRC) is one of the most common types of human cancers. However, the mechanisms underlying CRC progression remained elusive. This study identified differently expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs) between pre-therapeutic biopsies and post-therapeutic resections of locally advanced CRC by analyzing a public dataset, GSE94104. We identified 427 dysregulated mRNAs, 4 dysregulated lncRNAs, and 19 dysregulated snoRNAs between pre- and post-therapeutic locally advanced CRC samples. By constructing a protein–protein interaction network and co-expressing networks, we identified 10 key mRNAs, 4 key lncRNAs, and 7 key snoRNAs. Bioinformatics analysis showed therapy-related mRNAs were associated with nucleosome assembly, chromatin silencing at recombinant DNA, negative regulation of gene expression, and DNA replication. Therapy-related lncRNAs were associated with cell adhesion, extracellular matrix organization, angiogenesis, and sister chromatid cohesion. In addition, therapy-related snoRNAs were associated with DNA replication, nucleosome assembly, and telomere organization. We thought this study provided useful information for identifying novel biomarkers for CRC.

DNA methylation-driven genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma

In this study, we performed a comprehensively analysis of gene expression and DNA methylation data to establish diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC).

Methods: We collected gene expression and DNA methylation datasets for over 1,200 clinical samples. Integrated analyses of RNA-sequencing and DNA methylation data were performed to identify DNA methylation-driven genes. These genes were utilized in univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to build a prognostic model. Recurrence and diagnostic models for HCC were also constructed using the same genes.

Results: A total of 123 DNA methylation-driven genes were identified. Two of these genes (SPP1 and LCAT) were chosen to construct the prognostic model. The high-risk group showed a markedly unfavorable prognosis compared to the low-risk group in both training (HR = 2.81; P < 0.001) and validation (HR = 3.06; P < 0.001) datasets. Multivariate Cox regression analysis indicated the prognostic model to be an independent predictor of prognosis (P < 0.05). Also, the recurrence model successfully distinguished the HCC recurrence rate between the high-risk and low-risk groups in both training (HR = 2.22; P < 0.001) and validation (HR = 2; P < 0.01) datasets. The two diagnostic models provided high accuracy for distinguishing HCC from normal samples and dysplastic nodules in the training and validation datasets, respectively.

Conclusions: We identified and validated prognostic, recurrence, and diagnostic models that were constructed using two DNA methylation-driven genes in HCC. The results obtained by integrating multidimensional genomic data offer novel research directions for HCC biomarkers and new possibilities for individualized treatment of patients with HCC.

Identification and analysis of genes associated with head and neck squamous cell carcinoma by integrated bioinformatics methods

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide, exhibiting high morbidity and mortality. The prognosis of HNSCC patients has remained poor, though considerable efforts have been made to improve the treatment of this cancer. Therefore, identifying significant differentially expressed genes (DEGs) involved in HNSCC progression and exploiting them as novel biomarkers or potential therapeutic targets for HNSCC is highly valuable.

Methods

Overlapping differentially expressed genes (DEGs) were screened out from three independent gene expression omnibus (GEO) datasets and subjected to GO and kyoto encyclopedia of genes and genomes pathway enrichment analyses. The protein–protein interactions network of DEGs was constructed in the STRING database, and the top ten hub genes were selected using cytoHubba. The relative expression of hub genes was detected in GEPIA, Oncomine, and human protein atlas (HPA) databases. Furthermore, the relationship of hub genes with the overall survival and disease‐free survival in HNSCC patients was investigated using the cancer genome atlas data.

Results

The top ten hub genes (SPP1, POSTN, COL1A2, FN1, IGFBP3, APP, MMP3, MMP13, CXCL8, and CXCL12) could be utilized as potential diagnostic indicators for HNSCC. The relative levels of FN1, APP, SPP1, and POSTN could be associated with the prognosis of HNSCC patients. The mRNA expression of APP and COL1A2 was validated in HNSCC samples.

Conclusion

This study identified effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting novel and essential therapeutic targets for HNSCC.

Leveraging the Role of the Metastatic Associated Protein Anterior Gradient Homologue 2 in Unfolded Protein Degradation: A Novel Therapeutic Biomarker for Cancer

Effective diagnostic, prognostic and therapeutic biomarkers can help in tracking disease progress, predict patients’ survival, and considerably affect the drive for successful clinical management. The present review aims to determine how the metastatic-linked protein anterior gradient homologue 2 (AGR2) operates to affect cancer progression, and to identify associated potential diagnostic, prognostic and therapeutic biomarkers, particularly in central nervous system (CNS) tumors. Studies that show a high expression level of AGR2, and associate the protein expression with the resilience to chemotherapeutic treatments or with poor cancer survival, are reported. The primary protein structures of the seven variants of AGR2, including their functional domains, are summarized. Based on experiments in various biological models, this review shows an orchestra of multiple molecules that regulate AGR2 expression, including a feedback loop with p53. The AGR2-associated molecular functions and pathways including genomic integrity, proliferation, apoptosis, angiogenesis, adhesion, migration, stemness, and inflammation, are detailed. In addition, the mechanisms that can enable the rampant oncogenic effects of AGR2 are clarified. The different strategies used to therapeutically target AGR2-positive cancer cells are evaluated in light of the current evidence. Moreover, novel associated pathways and clinically relevant deregulated genes in AGR2 high CNS tumors are identified using a meta-analysis approach.

Genome-wide analysis reveals alcohol dehydrogenase 1C and secreted phosphoprotein 1 for prognostic biomarkers in lung adenocarcinoma

To seek out novel promising biomarkers for predicting lung adenocarcinoma (LUAD) prognosis, we conducted this study. First, 279 upregulated and 37 downregulated differentially expressed genes were obtained from LUAD and para-carcinoma tissues by the Affymetrix GeneChip Human Transcriptome Array. Then, we randomly classified samples of LUAD data set GSE31210 as training and testing sets in a 1:1 ratio. Alcohol dehydrogenase 1C (ADH1C) and secreted phosphoprotein 1 (SPP1) were finally identified correlating with the LUAD survival through least absolute shrinkage and selection operator penalized Cox proportion hazards regression model, and applied to build a 2-gene signature related to prognosis in training set. Univariate and multivariable survival analyses suggested that overall survival (OS) and relapse-free survival (RFS) in the 2-gene signature low-risk group were better than the high-risk group. Kaplan-Meier curves proved that elevated ADH1C expression and reduced SPP1 expression were related to better OS and RFS. Besides, the SPP1 expressed higher in LUAD than para-carcinoma tissues using quantitative reverse transcription polymerase chain reaction assay. Finally, the association between the two genes and clinicopathological parameters in 80 LUAD were analyzed, it is suggested that SPP1 was relevant to epidermal growth factor receptor mutation. These findings indicated that ADH1C and SPP1 might be novel promising biomarkers for predicting LUAD prognosis.

Identification of SERPINE1, PLAU and ACTA1 as biomarkers of head and neck squamous cell carcinoma based on integrated bioinformatics analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the six leading cancer by incidence worldwide. The 5-year survival rate of HNSCC patients remains less than 65% due to lack of symptoms in the early stage. Hence, biomarkers which can improve detection of HNSCC should improve clinical outcome.

METHODS

Gene expression profiles (GSE6631, GSE58911) and the Cancer Genome Atlas (TCGA) HNSCC data were used for integrated bioinformatics analysis; the differentially expressed genes (DEGs) were then subjected to functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction. Subsequently, module analysis of the PPI network was performed and overall survival (OS) analysis of hub genes in subnetwork was studied. Finally, immunohistochemistry was used to verify the selected markers.

RESULTS

A total of 52 up-regulated and 80 down-regulated DEGs were identified, which were mainly associated with ECM-receptor interaction and focal adhesion signaling pathways. Importantly, a set of prognostic signatures including SERPINE1, PLAU and ACTA1 were screened from DEGs, which could predict OS in HNSCC patients from TCGA cohort. Experiment of clinical samples further successfully validated that these three signature genes were aberrantly expressed in the oral epithelial dysplasia and HNSCC, and correlated with aggressiveness of HNSCC patients.

CONCLUSIONS

SERPINE1, PLAU and ACTA1 played important roles in regulating the initiation and progression of HNSCC, and could be identified as key biomarkers for precise diagnosis and prognosis of HNSCC, which will provide potential targets for clinical therapies.

NPTX2 promotes colorectal cancer growth and liver metastasis by the activation of the canonical Wnt/β-catenin pathway via FZD6

Accumulating evidence from clinical and epidemiological studies has highlighted the close correlation between the individual risk of cancer and nervous system diseases. The expression of neuronal pentraxin 2 (NPTX2) is absent in Alzheimer's disease, anxiety, and depression. Herein, we found that NPTX2 mRNA and protein expression was significantly upregulated in colorectal carcinoma (CRC). NPTX2 expression level gradually increased with CRC progression and was closely associated with poor prognosis. In vitro and in vivo studies demonstrated that NPTX2 promoted CRC proliferation and metastasis through the activation of the Wnt/β-catenin signaling pathway. As NPTX2 receptors are absent on CRC cells, NPTX2 was shown to physically interact with frizzled class receptor 6 (FZD6) to promote β-catenin translocation into the cell nucleus, resulting in an increase in the expression of MYC, cyclin D1, snail, and N-cadherin along with a decrease in the expression of E-cadherin. Knockdown of FZD6 expression with a small-interfering RNA almost completely reversed the proliferative effects of NPTX2 on CRC development. In conclusion, NPTX2, a molecule related to nervous system diseases, promotes CRC cell proliferation and metastasis through the activation of the Wnt/β-catenin pathway via direct interaction with FZD6.

Activation of hepatocyte growth factor/MET signaling initiates oncogenic transformation and enhances tumor aggressiveness in the murine prostate

Emerging evidence has shown that the hepatocyte growth factor (HGF) and its receptor, MET proto-oncogene, receptor tyrosine kinase (MET), promote cell proliferation, motility, morphogenesis, and angiogenesis. Whereas up-regulation of MET expression has been observed in aggressive and metastatic prostate cancer, a clear understanding of MET function in prostate tumorigenesis remains elusive. Here, we developed a conditional Met transgenic mouse strain, H11 ^Met/+ :PB-Cre4, to mimic human prostate cancer cells with increased MET expression in the prostatic luminal epithelium. We found that these mice develop prostatic intraepithelial neoplasia after HGF administration. To further assess the biological role of MET in prostate cancer progression, we bred H11 ^Met/+ /Pten^LoxP/LoxP:PBCre4 compound mice, in which transgenic Met expression and deletion of the tumor suppressor gene Pten occurred simultaneously only in prostatic epithelial cells. These compound mice exhibited accelerated prostate tumor formation and invasion as well as increased metastasis compared with Pten^LoxP/LoxP:PB-Cre4 mice. Moreover, prostatic sarcomatoid carcinomas and lesions resembling the epithelial-to-mesenchymal transition developed in tumor lesions of the compound mice. RNA-Seq and qRT-PCR analyses revealed a robust enrichment of known tumor progression and metastasis-promoting genes in samples isolated from H11 ^Met/+ /Pten^LoxP/LoxP:PB-Cre4 compound mice compared with those from Pten^LoxP/LoxP:PB-Cre4 littermate controls. HGF-induced cell proliferation and migration also increased in mouse embryonic fibroblasts (MEFs) from animals with both Met transgene expression and Pten deletion compared with Pten-null MEFs. The results from these newly developed mouse models indicate a role for MET in hastening tumorigenesis and metastasis when combined with the loss of tumor suppressors.

Bioinformatics Analysis Reveals Most Prominent Gene Candidates to Distinguish Colorectal Adenoma from Adenocarcinoma

Colorectal cancer (CRC) is one of the leading causes of death by cancer worldwide. Bowel cancer screening programs enable us to detect early lesions and improve the prognosis of patients with CRC. However, they also generate a significant number of problematic polyps, e.g., adenomas with epithelial misplacement (pseudoinvasion) which can mimic early adenocarcinoma. Therefore, biomarkers that would enable us to distinguish between adenoma with epithelial misplacement (pseudoinvasion) and adenoma with early adenocarcinomas (true invasion) are needed. We hypothesized that the former are genetically similar to adenoma and the latter to adenocarcinoma and we used bioinformatics approach to search for candidate genes that might be potentially used to distinguish between the two lesions. We used publicly available data from Gene Expression Omnibus database and we analyzed gene expression profiles of 252 samples of normal mucosa, colorectal adenoma, and carcinoma. In total, we analyzed 122 colorectal adenomas, 59 colorectal carcinomas, and 62 normal mucosa samples. We have identified 16 genes with differential expression in carcinoma compared to adenoma: COL12A1, COL1A2, COL3A1, DCN, PLAU, SPARC, SPON2, SPP1, SULF1, FADS1, G0S2, EPHA4, KIAA1324, L1TD1, PCKS1, and C11orf96. In conclusion, our in silico analysis revealed 16 candidate genes with different expression patterns in adenoma compared to carcinoma, which might be used to discriminate between these two lesions.

Daylight photodynamic therapy for field cancerization: lessons from molecular biology

Actinic keratoses (AKs) represent in-situ squamous cell carcinomas that potentially invade subepidermal structures and may metastasize. Until now, it is unpredictable to determine which AK lesions show this aggressive behavior. As AKs usually occur in large sun exposed areas, field-directed treatments have become the standard treatment regimen. Among these, conventional photodynamic therapy (cPDT) with 5-aminolaevulinic acid (ALA) or methyl-aminolevulinate (MAL) using red light is particularly effective in the treatment of AKs, but acceptance of the therapy is impaired by severe pain during treatment. Daylight PDT (dPDT) has demonstrated to be an equally effective alternative treatment option which is less painful. Recent attempts to determine the risk of AKs that demonstrate particular aggressive biological behavior by implementation of clinical and histological characteristics of AKs have not lead to conclusive results. Therefore, a look at the molecular biology of AKs could serve as a useful tool to develop a risk profiling for separation of those patients that are of particular risk to develop invasive tumor and, by this, to facilitate a more effective and adapted treatment option.

Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

Background

The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms.

Results

The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs) and were deeply analyzed by bioinformatics methods. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI) networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the tumor signaling pathway. The 17 most closely related genes among DEGs were identified from the PPI network.

Conclusion

This study indicates that screening for DEGs and pathways in ovarian cancer using integrated bioinformatics analyses could help us understand the molecular mechanism underlying the development of ovarian cancer, be of clinical significance for the early diagnosis and prevention of ovarian cancer, and provide effective targets for the treatment of ovarian cancer.

SPP1 promotes ovarian cancer progression via Integrin β1/FAK/AKT signaling pathway

OBJECTIVES

Ovarian cancer is one of the most lethal malignant tumors in women. Secreted phosphoprotein 1 (SPP1) plays an important role in some cancer types. Therefore, the role of SPP1 in ovarian cancer was determined and the potential mechanism was elucidated.

MATERIALS AND METHODS

The expression of SPP1 in ovarian cancer was determined by immunohistochemistry in ovarian cancer tissues and normal ovarian tissues. Cellular proliferation, migration, and invasion were determined by cell counting kit-8 assay, wound healing assay, and Matrigel invasion assay in SKOV3 and A2780 cells. The protein expression of SPP1, integrin subunit β1 (Integrin β1), focal adhesion kinase (FAK), and phosphorylation protein kinase B (p-AKT) was detected by Western blotting in SKOV3 cells after silencing SPP1. The expression of SPP1 was determined in SKOV3 cells after transfecting with miR-181a mimics or inhibitors. The growth of SKOV3 cells in vivo was determined in a nude mouse model of ovarian cancer after silencing SPP1.

RESULTS

The expression of SPP1 was higher in epithelial ovarian cancer tissues than in normal ovarian tissues. Silencing SPP1 decreased the cell proliferation, migration, and invasion. Ectopic expression of SPP1 increased the cell proliferation, migration, and invasion. Silencing SPP1 prevented ovarian cancer growth in mice. Silencing SPP1 inhibited Integrin β1/FAK/AKT pathway. In agreement, ectopically expressed SPP1 activated Integrin β1/FAK/AKT pathway. Also, SPP1 was regulated by miR-181a.

CONCLUSION

SPP1 is a biomarker for the prognosis of ovarian cancer. It is also oncogenic and a potential target for ovarian cancer therapy.

Long non-coding RNA TCF7 predicts the progression and facilitates the growth and metastasis of colorectal cancer

Long non-coding RNA (lnc)TCF7 has been reported to promote the self‑renewal of human cancer stem cells, and enhance the aggressiveness of human non‑small cell lung cancer and hepatocellular carcinoma cells. However, the effect of lncTCF7 on colorectal cancer (CRC) tumorigenesis and progression is currently unclear. In the present study, reverse transcription‑quantitative polymerase chain reaction results demonstrated that lncTCF7 expression was higher in CRC tissues compared with adjacent normal tissues and was significantly associated with tumor size, differentiation degree, tumor‑node‑metastasis grade, lymph node metastasis and invasion depth. In addition, lncTCF7 demonstrated a high sensitivity and specificity for diagnosing CRC, as determined by receiver operating characteristic curve analysis. Furthermore, lncTCF7 silencing in SW‑620 and HT29 CRC cell lines inhibited the proliferation, cell cycle, migration and invasion of cells, as determined by Cell Counting Kit‑8 assays, propidium iodide (PI) staining and flow cytometry, wound healing assays and Transwell invasion assays, respectively; however, Annexin V/PI double staining and flow cytometry indicated that lncTCF7 silencing did not significantly affect the apoptosis of CRC cells. These results indicate that lncTCF7 may predict the progression, and promote the growth and metastasis, of CRC, and may therefore be a novel diagnostic marker and therapeutic target for CRC treatment.