Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1) Are Associated with Progression and Prognosis of Esophageal Cancer as Identified by Integrated Expression Profiles Analysis

Decoding dysregulated genes, molecular pathways and microRNAs involved in cervical cancer

BACKGROUND

The present study aimed to identify dysregulated genes, molecular pathways, and regulatory mechanisms in human papillomavirus (HPV)-associated cervical cancers. We have investigated the disease-associated genes along with the Gene Ontology, survival prognosis, transcription factors and the microRNA (miRNA) that are involved in cervical carcinogenesis, enabling a deeper comprehension of cervical cancer linked to HPV.

METHODS

We used 10 publicly accessible Gene Expression Omnibus (GEO) datasets to examine the patterns of gene expression in cervical cancer. Differentially expressed genes (DEGs), which showed a clear distinction between cervical cancer and healthy tissue samples, were analyzed using the GEO2R tool. Additional bioinformatic techniques were used to carry out pathway analysis and functional enrichment, as well as to analyze the connection between altered gene expression and HPV infection.

RESULTS

In total, 48 DEGs were identified to be differentially expressed in cervical cancer tissues in comparison to healthy tissues. Among DEGs, CCND1, CCNA2 and SPP1 were the key dysregulated genes involved in HPV-associated cervical cancer. The five common miRNAs that were identified against these genes are miR-7-5p, miR-16-5p, miR-124-3p, miR-10b-5p and miR-27a-3p. The hub-DEGs targeted by miRNA hsa-miR-27a-3p are controlled by the common transcription factor SP1.

CONCLUSIONS

The present study has identified DEGs involved in HPV-associated cervical cancer progression and the various molecular pathways and transcription factors regulating them. These findings have led to a better understanding of cervical cancer resulting in the development and identification of possible therapeutic and intervention targets, respectively.

SPP1 promotes tumor progression in esophageal carcinoma by activating focal adhesion pathway

Background

Recurrence and metastasis are the major obstacles affecting the therapeutic efficacy and clinical outcomes for patients with esophageal carcinoma (ESCA). Secreted phosphoprotein 1 (SPP1) is considered as a hub gene in ESCA and is negatively associated with disease-free survival (DFS) in ESCA. However, the exact roles and underlying mechanisms remain elusive. This study aims to examine the roles of SPP1 on ESCA, and elucidate the potential mechanisms.

Methods

Bioinformatics were used to analyze the expression of SPP1 in ESCA tissues, and its relations with clinicopathological characteristics and clinical prognosis in patients with ESCA based on The Cancer Genome Atlas (TCGA) dataset. Loss-of-function was conducted to examine the roles of SPP1 on malignant behaviors of ESCA cells by cell counting kit-8 (CCK8), plate clone, wound healing, and transwell assays. Gene set enrichment analysis (GSEA) was conducted to screen the pathways associated with SPP1 in ESCA. Then, the enriched pathway and the underlying mechanism were elucidated by western blotting, cell adhesion, and cell spreading assays. Lastly, Y15 [a specific inhibitor of focal adhesion kinase (FAK)] was used to examine its potential to inhibit tumor growth in ESCA cells.

Results

SPP1 was upregulated in ESCA tissues compared to the adjacent nontumorous tissues, which was closely associated with clinical stage, lymph node metastasis, histological subtype, and p53 mutation. A high expression of SPP1 indicated a poor clinical prognosis in patients with ESCA. The knockdown of SPP1 inhibited cell proliferative, migratory, and invasive capacities in ESCA cells. GSEA indicated that the focal adhesion pathway was closely related with SPP1 in ESCA. Further studies confirmed that the knockdown of SPP1 suppressed cell adhesion ability and reduced the expression of p-FAK and p-Erk in ESCA cells. In addition, Y15 inhibited FAK autophosphorylation and dramatically inhibited cell proliferation, migration, and invasion in ESCA cells.

Conclusions

SPP1 promotes tumor progression in ESCA by activating FAK/Erk pathway, and FAK is a potential therapeutic target to overcome tumor recurrence and metastasis of ESCA.

Immune cell related signature predicts prognosis in esophageal squamous cell carcinoma based on single-cell and bulk-RNA sequencing

Background

It has been reported that tumor immune microenvironment performs a vital role in tumor progress. However, acting mechanism of immune cell related genes (IRGs) in esophageal squamous cell carcinoma (ESCC) is uncertain.

Methods

TCGA-ESCC, GSE23400, GSE26886, GSE75241, and GSE196756 datasets were gained via public databases. First, differentially expressed genes (DEGs) between ESCC and control samples from GSE23400, GSE26886, and GSE75241 were screened out by differential expression analysis, and overlapping DEGs were identified. Single-cell transcriptome data of GSE196756 were applied to explore immune cells that might be involved in regulation of ESCC. Then, weighted gene co-expression network analysis was applied to screen IRGs. Next, differentially expressed IRGs (DE-IRGs) were identified by overlapping IRGs and DEGs, and were incorporated into univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox to acquire prognosis-related genes, and ESCC samples were grouped into high-/low-risk groups on the basis of median risk score. Finally, the role of prognosis model in immunotherapy was analyzed.

Results

Totally 248 DEGs were yielded by overlapping 3,915 DEGs in GSE26886, 459 DEGs in GSE23400, and 1,641 DEGs in GSE75241. Single-cell analysis found that B cells, dendritic cells, monocytes, neutrophils, natural killer cells, and T cells were involved in ESCC development. Besides, MEred, MEblack, MEpink, MEblue and MEbrown modules were considered as key modules because of their highest correlations with immune cell subtypes. A total of 154 DE-IRGs were yielded by taking intersection of DEGs and genes in key modules. Moreover, CTSC, ALOX12, and RMND5B were identified as prognosis-related genes in ESCC. Obviously, Exclusion and TIDE scores were notably lower in high-risk group than in the other one, indicating that high-risk group was more responsive to immunotherapy.

Conclusions

Through bioinformatic analysis, we identified a prognosis model consisting of IRGs (CTSC, ALOX12, and RMND5B) in ESCC, providing new ideas for studies related to treatment and prognosis of ESCC.

Low RCAN1.2 mRNA Expression Is Associated with Poor Prognosis of Patients with Esophageal Squamous Cell Carcinoma

Background: This study aims to explore the role of RCAN1 in esophageal squamous cell carcinoma (ESCC) cells, determine the mRNA level of three RCAN1 isoforms in ESCC tissue, and evaluate the prognostic value of three RCAN1 isoforms. Methods: Colony-forming assay, Wound-healing assay and Transwell assay were used to evaluate the effect of RCAN1 on cell proliferation, migration and invasion. The mRNA expression of three RCAN1 isoforms was detected in paired tumor and normal tissues from 100 ESCC patients by real-time PCR. Kaplan-Meier survival curves and Cox proportional hazards model were used to evaluate the prognostic value of three RCAN1 isoforms. A nomogram was used to predict the probability of 2-year and 5-year overall survival (OS). Results: In vitro, knockdown of RCAN1 could promote ESCC cell proliferation, migration and invasion abilities. Compared to the paired normal tissues, RCAN1 isoform 1 (RCAN1.1, P=0.0027) and RCAN1 isoform 2 (RCAN1.2, P=0.0006) were significantly decreased in tumor tissues. The low expression of RCAN1.2 mRNA was associated with advanced stage (P=0.0176) and lymph node metastasis (LNM, P=0.0219). ESCC patients with low RCAN1.2 mRNA levels had shorter survival time compared to those with high RCAN1.2 levels (P=0.007). Multivariate COX analysis indicated that RCAN1.2 mRNA level was an independent prognostic indicator of OS of patients with ESCC (hazard ratio=0.5266, P=0.03554). The concordance index of nomogram to predict OS was 0.693 based on LNM, RCAN1.2, tumor stage and patients' age. Conclusion: These findings show that RCAN1 gene play a role in preventing proliferation, migration, and invasive activity of ESCC cells. RCAN1.2 mRNA level is a novel prognostic marker in ESCC, targeting RCAN1.2 may provide a potential therapeutic approach in ESCC.

Comprehensive Analysis of Histone Modifications in Hepatocellular Carcinoma Reveals Different Subtypes and Key Prognostic Models

Histone modification, an important epigenetic mechanism, is related to the carcinogenesis of hepatocellular carcinoma (HCC). In three datasets, we screened 88 epigenetic-dysregulated PCGs (epi-PCGs) , which were significantly associated with HCC survival and could cluster HCC into three molecular subtypes. These subtypes were associated with prognosis, immunomodulatory alterations, and response to different treatment strategies. Based on 88 epi-PCGs in the TCGA training set, a risk prediction model composed of 4 epi-PCGs was established. The model was closely related to the clinicopathological features and showed a strong predictive ability in different clinical subgroups. In addition, the risk prediction model was an independent prognostic factor for patients with HCC. The significance of epi-PCGs in HCC is revealed by our data analysis.

SPP1 promotes radiation resistance through JAK2/STAT3 pathway in esophageal carcinoma

BACKGROUND

Therapeutic resistance to radiotherapy is one of the major obstacles in clinical practice that significantly affect the therapeutic efficiency and prognosis of human esophageal carcinoma (ESCA). Thus, it is critical to understand the molecular mechanisms of radiation resistance in ESCA. Secreted phosphoprotein 1 (SPP1) plays an essential role in various human cancers, but its role in radiation resistance remains unclear.

METHOD

Cell culture and transfection; Cell Counting Kit-8 (CCK-8) assays; EdU incorporation assays; Patient sample collection and medical records review; Transwell assays; Colony formation assays; Wound healing assays; Western blot; Immunofluorescence; Immunohistochemistry; Irradiation; Flow cytometry; Animal studies; Human Apoptosis Array Kit; Bioinformatics.

RESULT

In the current study, we reported the novel phenomenon that radiation-treated human ESCA cells upregulated SPP1 expression, which in turn contributed to the ESCA resistance to radiotherapy. We also reported the tumor-promoting effect of SPP1 in ESCA systematically and comprehensively. Furthermore, subsequent studies by knocking down or overexpressing SPP1 in human ESCA cells showed that SPP1 could facilitate the repair of DNA damage and the survival of tumor cells post-radiation in ESCA, which might contribute to the development of radiation resistance during the radiotherapy process. More detailed investigations on the downstream molecular pathway suggested that radiation could increase the phosphorylation level of JAK2 and STAT3 by increasing SPP1 expression. Further in vivo validation using a mouse ESCA xenograft model showed that SPP1 overexpression significantly increased tumor volume while either SPP1 knockdown or pharmacological inhibition of the JAK2-STAT3 pathway reduced tumor volume in a synergistic manner with radiotherapy.

CONCLUSION

Collectively, these findings suggested that the SPP1/JAK2/STAT3 axis is a critical player in ESCA progression and radiation resistance, which is a potential therapeutic target for combined therapy with the standard radiotherapy regimen to improve curative effect and increase patients' survival with ESCA.

The Overexpression of Fibronectin 1 Promotes Cancer Progression and Associated with M2 Macrophages Polarization in Head and Neck Squamous Cell Carcinoma Patients

Purpose

This study aimed to investigate the biological roles of fibronectin 1 (FN1) in head and neck squamous cell carcinoma (HNSCC) and its effects on macrophage M2 polarization.

Methods

We analyzed FN1 expression pattern and examined its clinical relevance in HNSCC progression by bioinformatic analysis. Small interfering RNA (siRNA) was utilized to silence FN1 in HNSCC cells. Cell counting kit-8 (CCK-8) assay, colony formation assay, Transwell assay and wound healing assay were performed to reveal the effect of FN1 on malignant behaviors of HNSCC cells. Moreover, a co-culture model of macrophages and HNSCC cells was established to investigate whether FN1 induce macrophage M2 polarization. Finally, we used bioinformatic methods to explore the possible FN1-related pathways in HNSCC.

Results

FN1 is significantly overexpressed in HNSCC patients and has been obviously correlated with higher pathological stage and poor prognosis. Downregulation of FN1 suppressed the proliferation, migration and invasion of HNSCC cells, and inhibited macrophage M2 polarization in vitro. In addition, “PI3K-Akt” and “MAPK” signaling pathways may be involved in the malignant process of FN1 in HNSCC.

Conclusion

The overexpression of FN1 promotes HNSCC progression and induces macrophages M2 polarization. FN1 may serve as a promising prognostic biomarker and therapeutic target in HNSCC.

Three-Dimensional Growth of Prostate Cancer Cells Exposed to Simulated Microgravity

Prostate cancer metastasis has an enormous impact on the mortality of cancer patients. Factors involved in cancer progression and metastasis are known to be key players in microgravity (µg)-driven three-dimensional (3D) cancer spheroid formation. We investigated PC-3 prostate cancer cells for 30 min, 2, 4 and 24 h on the random positioning machine (RPM), a device simulating µg on Earth. After a 24 h RPM-exposure, the cells could be divided into two groups: one grew as 3D multicellular spheroids (MCS), the other one as adherent monolayer (AD). No signs of apoptosis were visible. Among others, we focused on cytokines involved in the events of metastasis and MCS formation. After 24 h of exposure, in the MCS group we measured an increase in ACTB, MSN, COL1A1, LAMA3, FN1, TIMP1, FLT1, EGFR1, IL1A, IL6, CXCL8, and HIF1A mRNA expression, and in the AD group an elevation of LAMA3, COL1A1, FN1, MMP9, VEGFA, IL6, and CXCL8 mRNAs compared to samples subjected to 1 g conditions. Significant downregulations in AD cells were detected in the mRNA levels of TUBB, KRT8, IL1B, IL7, PIK3CB, AKT1 and MTOR after 24 h. The release of collagen-1α1 and fibronectin protein in the supernatant was decreased, whereas the secretion of IL-6 was elevated in 24 h RPM samples. The secretion of IL-1α, IL-1β, IL-7, IL-2, IL-8, IL-17, TNF-α, laminin, MMP-2, TIMP-1, osteopontin and EGF was not significantly altered after 24 h compared to 1 g conditions. The release of soluble factors was significantly reduced after 2 h (IL-1α, IL-2, IL-7, IL-8, IL-17, TNF-α, collagen-1α1, MMP-2, osteopontin) and elevated after 4 h (IL-1β, IL-2, IL-6, IL-7, IL-8, TNF-α, laminin) in RPM samples. Taken together, simulated µg induced 3D growth of PC-3 cancer cells combined with a differential expression of the cytokines IL-1α, IL-1β, IL-6 and IL-8, supporting their involvement in growth and progression of prostate cancer cells.

Meta-Analysis of Esophageal Cancer Transcriptomes Using Independent Component Analysis

Independent Component Analysis is a matrix factorization method for data dimension reduction. ICA has been widely applied for the analysis of transcriptomic data for blind separation of biological, environmental, and technical factors affecting gene expression. The study aimed to analyze the publicly available esophageal cancer data using the ICA for identification and comprehensive analysis of reproducible signaling pathways and molecular signatures involved in this cancer type. In this study, four independent esophageal cancer transcriptomic datasets from GEO databases were used. A bioinformatics tool « BiODICA-Independent Component Analysis of Big Omics Data» was applied to compute independent components (ICs). Gene Set Enrichment Analysis (GSEA) and ToppGene uncovered the most significantly enriched pathways. Construction and visualization of gene networks and graphs were performed using the Cytoscape, and HPRD database. The correlation graph between decompositions into 30 ICs was built with absolute correlation values exceeding 0.3. Clusters of components-pseudocliques were observed in the structure of the correlation graph. The top 1,000 most contributing genes of each ICs in the pseudocliques were mapped to the PPI network to construct associated signaling pathways. Some cliques were composed of densely interconnected nodes and included components common to most cancer types (such as cell cycle and extracellular matrix signals), while others were specific to EC. The results of this investigation may reveal potential biomarkers of esophageal carcinogenesis, functional subsystems dysregulated in the tumor cells, and be helpful in predicting the early development of a tumor.

Identification of Key Genes and Pathways Associated With Paclitaxel Resistance in Esophageal Squamous Cell Carcinoma Based on Bioinformatics Analysis

Esophageal squamous cell carcinoma (ESCC) ranks as the fourth leading cause of cancer-related death in China. Although paclitaxel has been shown to be effective in treating ESCC, the prolonged use of this chemical will lead to paclitaxel resistance. In order to uncover genes and pathways driving paclitaxel resistance in the progression of ESCC, bioinformatics analyses were performed based on The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database including GSE86099 and GSE161533. Differential expression analysis was performed in TCGA data and two GEO datasets to obtain differentially expressed genes (DEGs). Based on GSE161533, weighted gene co-expression network analysis (WGCNA) was conducted to identify the key modules associated with ESCC tumor status. The DEGs common to the two GEO datasets and the genes in the key modules were intersected to obtain the paclitaxel resistance-specific or non-paclitaxel resistance-specific genes, which were subjected to subsequent least absolute shrinkage and selection operator (LASSO) feature selection, whereby paclitaxel resistance-specific or non-paclitaxel resistance-specific key genes were selected. Ten machine learning models were used to validate the biological significance of these key genes; the potential therapeutic drugs for paclitaxel resistance-specific genes were also predicted. As a result, we identified 24 paclitaxel resistance-specific genes and 18 non-paclitaxel resistance-specific genes. The ESCC machine classifiers based on the key genes achieved a relatively high AUC value in the cross-validation and in an independent test set, GSE164158. A total of 207 drugs (such as bevacizumab) were predicted to be alternative therapeutics for ESCC patients with paclitaxel resistance. These results might shed light on the in-depth research of paclitaxel resistance in the context of ESCC progression.

m5C RNA Methylation Primarily Affects the ErbB and PI3K-Akt Signaling Pathways in Gastrointestinal Cancer

5-Methylcytosine (m⁵C) is a kind of methylation modification that occurs in both DNA and RNA and is present in the highly abundant tRNA and rRNA. It has an important impact on various human diseases including cancer. The function of m⁵C is modulated by regulatory proteins, including methyltransferases (writers) and special binding proteins (readers). This study aims at comprehensive study of the m⁵C RNA methylation-related genes and the main pathways under m⁵C RNA methylation in gastrointestinal (GI) cancer. Our result showed that the expression of m⁵C writers and reader was mostly up-regulated in GI cancer. The NSUN2 gene has the highest proportion of mutations found in GI cancer. Importantly, in liver cancer, higher expression of almost all m⁵C regulators was significantly associated with lower patient survival rate. In addition, the expression level of m⁵C-related genes is significantly different at various pathological stages. Finally, we have found through bioinformatics analysis that m⁵C regulatory proteins are closely related to the ErbB/PI3K–Akt signaling pathway and GSK3B was an important target for m⁵C regulators. Besides, the compound termed streptozotocin may be a key candidate drug targeting on GSK3B for molecular targeted therapy in GI cancer.