Identification of MMP1 as a Potential Prognostic Biomarker and Correlating with Immune Infiltrates in Cervical Squamous Cell Carcinoma

MMP1, IL-1β, sTNFR-1, and IL-6 are prognostic factors for patients with unresectable or metastatic renal cell carcinoma treated with immune checkpoint inhibitors

BACKGROUND

Few studies have reported reliable prognostic factors for immune checkpoint inhibitors (ICIs) in renal cell carcinoma (RCC). Therefore, we investigated prognostic factors in patients treated with ICIs for unresectable or metastatic RCC.

METHODS

We included 43 patients who received ICI treatment for RCC between January 2018 and October 2021. Blood samples were drawn before treatment, and 73 soluble factors in the plasma were analyzed using a bead-based multiplex assay. We examined factors associated with progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAE) using the Chi-squared test, Kaplan-Meier method, and the COX proportional hazards model.

RESULTS

Patients exhibited a median PFS and OS of 212 and 783 days, respectively. Significant differences in both PFS and OS were observed for MMP1 (PFS, p < 0.001; OS, p = 0.003), IL-1β (PFS, p = 0.021; OS, p = 0.008), sTNFR-1 (PFS, p = 0.017; OS, p = 0.005), and IL-6 (PFS, p = 0.004; OS, p < 0.001). Multivariate analysis revealed significant differences in PFS for MMP1 (hazard ratio [HR] 5.305, 95% confidence interval [CI], 1.648-17.082; p = 0.005) and OS for IL-6 (HR 23.876, 95% CI, 3.426-166.386; p = 0.001). Moreover, 26 patients experienced irAE, leading to ICI discontinuation or withdrawal. MMP1 was significantly associated with irAE (p = 0.039).

CONCLUSION

MMP1 may be associated with severe irAE, and MMP1, IL-1β, sTNFR-1, and IL-6 could serve as prognostic factors in unresectable or metastatic RCC treated with ICIs. MMP1 and IL-6 were independent predictors of PFS and OS, respectively. Thus, inhibiting these soluble factors may be promising for enhancing antitumor responses in patients with RCC treated with ICIs.

Elucidating the molecular mechanisms of pterostilbene against cervical cancer through an integrated bioinformatics and network pharmacology approach

Pterostilbene (PTE), a natural phenolic compound, has exhibited promising anticancer properties in the preclinical treatment of cervical cancer (CC). This study aims to comprehensively investigate the potential targets and mechanisms underlying PTE's anticancer effects in CC, thereby providing a theoretical foundation for its future clinical application and development. To accomplish this, we employed a range of methodologies, including network pharmacology, bioinformatics, and computer simulation, with specific techniques such as WGCNA, PPI network construction, ROC curve analysis, KM survival analysis, GO functional enrichment, KEGG pathway enrichment, molecular docking, MDS, and single-gene GSEA. Utilizing eight drug target prediction databases, we have identified a total of 532 potential targets for PTE. By combining CC-related genes from the GeneCards disease database with significant genes derived from WGCNA analysis of the GSE63514 dataset, we obtained 7915 unique CC-related genes. By analyzing the intersection of the 7915 CC-related genes and the 2810 genes that impact overall survival time in CC, we identified 690 genes as crucial for CC. Through the use of a Venn diagram, we discovered 36 overlapping targets shared by PTE and CC. We have constructed a PPI network and identified 9 core candidate targets. ROC and KM curve analyses subsequently revealed IL1B, EGFR, IL1A, JUN, MYC, MMP1, MMP3, and ANXA5 as the key targets modulated by PTE in CC. GO and KEGG pathway enrichment analyses indicated significant enrichment of these key targets, primarily in the MAPK and IL-17 signaling pathways. Molecular docking analysis verified the effective binding of PTE to all nine key targets. MDS results showed that the protein-ligand complex between MMP1 and PTE was the most stable among the nine targets. Additionally, GSEA enrichment analysis suggested a potential link between elevated MMP1 expression and the activation of the IL-17 signaling pathway. In conclusion, our study has identified key targets and uncovered the molecular mechanism behind PTE's anticancer activity in CC, establishing a firm theoretical basis for further exploration of PTE's pharmacological effects in CC therapy.

Crosstalk between T lymphocyte and extracellular matrix in tumor microenvironment

The extracellular matrix (ECM) is a complex three-dimensional structure composed of proteins, glycans, and proteoglycans, constituting a critical component of the tumor microenvironment. Complex interactions among immune cells, extracellular matrix, and tumor cells promote tumor development and metastasis, consequently influencing therapeutic efficacy. Hence, elucidating these interaction mechanisms is pivotal for precision cancer therapy. T lymphocytes are an important component of the immune system, exerting direct anti-tumor effects by attacking tumor cells or releasing lymphokines to enhance immune effects. The ECM significantly influences T cells function and infiltration within the tumor microenvironment, thereby impacting the behavior and biological characteristics of tumor cells. T cells are involved in regulating the synthesis, degradation, and remodeling of the extracellular matrix through the secretion of cytokines and enzymes. As a result, it affects the proliferation and invasive ability of tumor cells as well as the efficacy of immunotherapy. This review discusses the mechanisms underlying T lymphocyte-ECM interactions in the tumor immune microenvironment and their potential application in immunotherapy. It provides novel insights for the development of innovative tumor therapeutic strategies and drug.

MMP11 and MMP17 are potential biomarkers for uterine corpus endometrial carcinoma prognosis

BACKGROUND

Matrix metalloproteinases (MMP) are important proteases that degrade the extracellular matrix (ECM) and thus essentially mediate tumor vascularization, metastasis, and invasion. However, their potential roles in uterine corpus endometrial carcinoma (UCEC) are not fully understood.

PATIENTS AND METHODS

The expression, prognostic value, and correlation of UCEC patients with MMP were investigated using data from The Cancer Genome Atlas (TCGA) and other databases. Furthermore, differentially expressed genes (DEGs) were identified and their biological functions and correlations with infiltrating immune cells were analyzed.

RESULTS

A total of 22 MMPs were found to be abnormally expressed in UCEC tumor tissues, and high expression of MMP11 and MMP17 were associated with a better UCEC prognosis. MMP11 and MMP17 were observed to be significantly enriched in tumor tissue ECM and were associated with pathways involving degradation, glycolytic metabolism, and PI3K-Akt signaling. Infiltration of natural killer (NK), mast, and NK CD56bright cells was enhanced in tumor tissues with high MMP11 and MMP17 expression.

CONCLUSION

MMP11 and MMP17 may affect UCEC prognosis by influencing immune cell infiltration and may be potential UCEC biomarkers.

Roles of peroxisome proliferator-activated receptors in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the main pathological type of liver cancer, is linked to risk factors such as viral hepatitis, alcohol intake and non-alcoholic fatty liver disease (NAFLD). Recent advances have greatly improved our understanding that NAFLD is playing a major risk factor for HCC. Peroxisome proliferator-activated receptors (PPARs) are a class of transcription factors divided into three subtypes: PPARα (PPARA), PPARδ/β (PPARD) and PPARγ (PPARG). As important nuclear receptors, PPARs are involved in many physiological processes, and PPARs can improve NAFLD by regulating lipid metabolism, accelerating fatty acid oxidation and inhibiting inflammation. In recent years, some studies have shown that PPARs can participate in the occurrence and development of HCC by regulating metabolic pathways. In addition, PPAR modulators have been reported to inhibit the proliferation and metastasis of HCC cells and can enhance the curative effect of conventional treatments. This article reviews the role of PPARs in the occurrence and development of HCC, as well as its value in the diagnosis, treatment and prognosis of HCC, in order to provide directions for future research.

Metabolism-associated molecular classification of cervical cancer

OBJECTIVE

This study aimed to explore metabolic abnormalities in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) for metabolism-related genes.

METHODS

We downloaded expression data for metabolism-related genes, performed differential expression analysis, and applied weighted gene co-expression network analysis (WGCNA) to identify metabolism-related functional modules. We obtained normalised miRNA expression data and identified master methylation regulators for metabolism-related genes. Cox regression of data on metabolism-related genes was performed to screen for genes that affect the prognosis of patients with CESC. Furthermore, we selected key genes for validation.

RESULTS

Our results identified 3620 metabolism-related genes in CESC, 2493 of which contained related mutations. The co-occurrence of CUBN, KALRN, and HERC1 was related to the prognosis of CESC. The fraction of genome altered (FGA) closely correlated with overall survival. In expression analysis, 374 genes were related to the occurrence and prognosis of CESC. We then identified four metabolic pathway modules in WGCNA. Further analysis revealed that glycolysis/gluconeogenesis was related to endothelial cells and that arachidonic acid metabolism was related to cell proliferation. These four modules were also related to the prognosis of CESC. Among CESC-related metabolic genes, two genes were found to be regulated by microRNAs (miRNAs) and methylation, whereas another two genes were coregulated by miRNAs and mutations.

CONCLUSIONS

Among metabolism-related genes, 15 genes were related to the prognosis of CESC. The co-occurrence of CUBN/KALRN/HERC1 was associated with CESC prognosis. Glycolysis/gluconeogenesis was related to endothelial cells, and arachidonic acid metabolism was related to cell proliferation.

ZWINT promotes the proliferation, migration, and invasion of cervical cancer cells by regulating the p53/p21 signaling pathway

Cervical cancer leads to 300,000 deaths annually and the mechanism of cervical carcinogenesis remains unclear. Zeste White 10-interacting kinetochore protein (ZWINT) is uniquely elevated in malignancies, promoting proliferation, migration, and colony formation of cancer cells. To investigate the role of ZWINT in proliferation, migration, invasion of cervical cancer, and evaluate the potential ability of ZWINT as a therapeutic target. First, ZWINT expression in cervical cancer was analyzed using the bioinformatic methods and assessed in several cervical cancer cell lines. The cell viability and colony formation assays were used to evaluate cell proliferation. Then, transwell assay was performed to investigate cell migration and invasion. Moreover, western blot was used to measure the expression level of ZWINT, matrix metalloproteinase 9 (MMP-9), N-cadherin, E-cadherin, p53 and p21 in CaSki and HeLa cells with ZWINT overexpression or knockdown. The bioinformatic analysis and western blot assay revealed the expression of ZWINT was significantly increased in cervical cancer. The cell viability and colony formation analysis illustrated that cell proliferation could be promoted by ZWINT overexpression and suppressed by ZWINT knockdown. Moreover, ZWINT promoted migration and invasion of CaSki and HeLa cells, through regulating the expression of MMP-9, N-cadherin, and E-cadherin. Furthermore, ZWINT attenuated the expression of p53 and p21 in cervical cancer cells. In summary, ZWINT functions in promoting cell proliferation, migration, and invasion of cervical cancer cells by suppressing p53/p21 signaling pathway, which indicated ZWINT is a potential therapeutic target for cervical cancer treatment.

Ginsenoside Rg1 as a promising adjuvant agent for enhancing the anti-cancer functions of granulocytes inhibited by noradrenaline

Introduction

In recent years, numerous studies have confirmed that chronic stress is closely related to the development of cancer. Our previous research showed that high levels of stress hormones secreted in the body during chronic stress could inhibit the cancer-killing activity of granulocytes, which could further promote the development of cancer. Therefore, reversing the immunosuppressive effect of stress hormones on granulocytes is an urgent problem in clinical cancer treatment. Here, we selected noradrenaline (NA) as a representative stress hormone.

Methods and results

After screening many traditional Chinese herbal medicine active ingredients, a promising compound, ginsenoside Rg1, attracted our attention. We verified the immunoprotective effect of ginsenoside Rg1 on granulocytes in vitro and ex vivo, and attempted to understand its potential immunoprotective mechanism. We confirmed the immunoprotective effect of ginsenoside Rg1 on granulocytes using cell and animal experiments. Cell counting kit-8 (CCK-8) and ex vivo experiments were performed to investigate the immunoprotective effects of ginsenoside Rg1 on the anti-cancer function of granulocytes inhibited by NA. Transcriptome sequencing analysis and qRT-PCR showed that NA elevated the mRNA expression of ARG2, MMP1, S100A4, and RAPSN in granulocytes, thereby reducing the anti-cancer function of granulocytes. In contrast, ginsenoside Rg1 downregulated the mRNA expression of ARG2, MMP1, S100A4, and RAPSN, and upregulated the mRNA expression of LAMC2, DSC2, KRT6A, and FOSB, thereby enhancing the anti-cancer function of granulocytes inhibited by NA. Transwell cell migration experiments were performed to verify that ginsenoside Rg1 significantly enhanced the migration capability of granulocytes inhibited by NA. Tumor-bearing model mice were used to verify the significant immunoprotective effects in vivo. Finally, CCK-8 and hematoxylin and eosin staining experiments indicated that ginsenoside Rg1 exhibited high biosafety in vitro and in vivo.

Discussion

In future clinical treatments, ginsenoside Rg1 may be used as an adjuvant agent for cancer treatment to alleviate chronic stress-induced adverse events in cancer patients.

A pan-cancer analysis of the prognostic and immunological roles of matrix metalloprotease-1 (MMP1) in human tumors

Objective

Cancer remains the leading killer of human health worldwide. It has been shown that matrix metalloproteinase-1(MMP1) is related to poor prognosis in cancers such as BRCA, CESC and COAD. However, systematic pan-cancer analysis about the prognostic and immunological roles of MMP1 has not been explored. Here, the purpose of this study was to investigate the prognostic and immunological roles of MMP1 in pan-cancer and confirm cancer-promoting effect in pancreatic cancer.

Methods

In our study, bioinformatics were first used to analyze data from multiple databases. Then, several bioinformatics tools were utilized to investigate the role of MMP1 in 33 tumor types. Finally, molecular biology experiments were carried out to prove the cancer-promoting effect of MMP1 in pancreatic cancer.

Results

MMP1 expression was higher in tumor tissues than in control tissues in most tumor types. High expression of MMP1 was associated with poor overall survival (OS) and disease-free survival (DFS) in some tumor types. Further analysis of MMP1 gene mutation data showed that MMP1 mutations significantly influenced the prognosis of STAD. In addition, MMP1 expression was closely related to cancer-associated fibroblast (CAFs) infiltration in a variety of cancers and played an important role on immune infiltration score, tumor mutational burden (TMB) and microsatellite instability (MSI). Gene Ontology enrichment analysis indicated that these 20 genes were mainly related to extracellular structure organization/extracellular matrix organization/extracellular matrix disassembly/collagen metabolic process in the enriched biological processes. Finally, molecular biology experiments confirmed the cancer-promoting effect of MMP1 in pancreatic cancer.

Conclusions

Our pan-cancer analysis comprehensively proved that MMP1 expression is related with clinical prognosis and tumor immune infiltration, and MMP1 can become a prognostic and immunological biomarker.

MMP1 Overexpression Promotes Cancer Progression and Associates with Poor Outcome in Head and Neck Carcinoma

Matrix metalloproteinase-1 (MMP1) has been reported to play key roles in a variety of cancers by degrading the extracellular matrix. However, its carcinogenic roles have not been shown yet in head and neck squamous cell carcinoma (HNSCC). This study aimed to elucidate its expression pattern and functional roles as well as clinical significance in HNSCC. The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and immunohistochemistry (IHC) were utilized to determine the MMP1 expression pattern and the associations between its expression and patients' outcome in HNSCC. Mice tongue squamous cell carcinoma model induced by 4-nitroquinoline 1-oxide (4NQO) and siRNA-mediated cellular assay in vitro were utilized to evaluate the oncogenic role of MMP1. The biological functions and cancer-related pathways involved in MMP1-related genes were found through bioinformatics analysis. Both mRNA and protein abundance of MMP1 were highly increased in HNSCC as compared to its non-tumor counterparts. MMP1 overexpression positively correlated with advanced tumor size, cervical node metastasis, and advanced pathological grade and lower patients' survival. In the 4NQO-induced animal model, MMP1 expression increased along with the progression of the disease. In HNSCC cells, siRNA-mediated knockdown of MMP1 significantly inhibited cell proliferation, migration, and invasion and activated apoptosis and epithelia-mesenchymal transition (EMT). GSEA, GO, and KEGG analyses showed that MMP1 expression was significantly related to cancer-related pathways and cancer-related functions. Together, our results demonstrated MMP1 serves as a novel prognostic biomarker and putative oncogene in HNSCC.

Comprehensive bioinformatic analysis of MMP1 in hepatocellular carcinoma and establishment of relevant prognostic model

Matrix metalloproteinase 1 (MMP1) encodes endopeptidases associated with degradation of multiple components of the extracellular matrix. This function has increasingly been considered to play a major proteolysis role in tumor invasion and metastasis. However, the relationship between MMP1 gene expression, tumor-immune microenvironment and prognosis in hepatocellular carcinoma patients remains mostly unclear. This study focused on a comprehensive analysis of MMP1 in hepatocellular carcinoma, specifically the prognosis and tumor-immune microenvironment. MMP1 expression was analyzed using TCGA database and clinical samples. MMP1 associated mechanisms, pathways, mutations and prognosis in hepatocellular carcinoma were evaluated. We also analyzed the tumor-immune microenvironment and corresponding treatments. Our research demonstrated that MMP1 expression was upregulated in patients with hepatocellular carcinoma and correlated with poor survival. A prognostic model was established and its performance evaluated. We also found and report various correlations between MMP1 and immune-related cells/genes, as well the potential therapeutic agents. These findings indicate that MMP1 can potentially be a promising prognostic biomarker and indicator of the tumor-immune microenvironment status in hepatocellular carcinoma.

Uncovering of potential molecular markers for cervical squamous cell carcinoma (CESC) based on analysis of methylated-differentially expressed genes

OBJECTIVE

Cervical squamous cell carcinoma (CESC) is a cancer with high mortality caused by human papillomavirus. The aim of this study was to uncover potential CESC biomarkers to help early diagnosis and treatment.

MATERIALS AND METHODS

The mRNA transcriptome data and DNA methylation data were downloaded from database for the identification of differentially expressed mRNAs (DEmRNAs) and DNA methylation analysis. Functional analysis was used to reveal the molecular functions. Then, the association between differential methylation and DEmRNA was analyzed. Protein-protein interaction (PPI) network analysis was performed on the selected differentially methylated genes (DEGs). Subsequently, we analyzed the prognosis and constructed a prognostic risk model. We also performed diagnostic analyses of risk model genes. In addition, we verified the protein expression level of identified DEGs.

RESULTS

1438 DEmRNAs, 1669 differentially methylated sites (DMSs), 46 differentially methylated CpG islands and 53 differential methylation genes (DMGs) were obtained. In PPI, the highest interaction scores were MX2 and IRF8, and their interaction score was 0.928. Interestingly, 5 DMGs were found to be associated with CESC prognosis. In addition, our results demonstrated that high risk score was associated with poor prognosis of CESC. Furthermore, it was found that ZIK1, ZNRF2, HHEX, VCAM1 could be diagnostic molecular markers for CESC.

CONCLUSION

Analysis of methylated-differentially expressed genes may contribute to the identification of early diagnosis and therapeutic targets of CESC. In addition, a prognostic model based on 5 DMGs can be used to predict the prognosis of CESC.

Identification of Significant Secreted or Membrane-Located Proteins in Laryngeal Squamous Cell Carcinoma

Background. This study is aimed at investigating the expressions and prognostic values of secreted or membrane-located proteins (SMPs) in laryngeal squamous cell carcinoma (LSCC). The correlations between the expressions of SMPs and immune cells’ infiltrations were also investigated. Methods. The expression data of normal laryngeal and LSCC samples were obtained from the TCGA and GEO datasets. The differentially expressed SMPs were identified, and their prognostic values were analyzed. The biological functions of differentially expressed and worse-survival-related SMPs were explored. LASSO regression, Cox multivariate analysis, and nomogram were used to construct a model to predict the survival. Then, the infiltrations of the 24 immune cell populations were calculated using the GSVA method, and the correlations between the expression of SMPs and the immune infiltration were investigated. Results. 122 samples (12 normal and 120 LSCC) of the TCGA database and 114 samples (57 normal and 57 LSCC) of GSE127165 were included. We identified that 138 SMPs were significantly upregulated in LSCC samples of both the TCGA and GEO datasets, among which 52 SMPs were significantly correlated with worse survival. GO and KEGG analyses revealed those 52 SMPs significantly participate in tumor microenvironment and immune cells’ communication. Nine of 52 SMPs (ABCC5, ATP1B3, CLEC11A, FLNA, FSTL3, MMP1, NME1, OAS3, and PHLDB2) were included in the nomogram to effectively and accurately predict the LSCC patients’ survival. The expressions of most SMPs, such as MMP1 and FSTL3, were significantly positively correlated with the immune infiltration of LSCC. Conclusions. In this study, the expression, prognostic values, and correlations with immune infiltration of SMPs were analyzed in LSCC samples. Our analyses identified several significant SMPs differentially expressed between normal laryngeal and LSCC samples, correlated with worse survival, and related to the immune infiltration.

Hypoxia-Induced ZWINT Mediates Pancreatic Cancer Proliferation by Interacting With p53/p21

p53/p21 signaling plays a vital role in pancreatic cancer (PC) progression. ZWINT was shown to function as an oncoprotein in the progression of multiple cancers. However, the involvement of ZWINT and p53 activation in the progression of PC remains poorly understood. Bioinformatics and tissue array chip analyses were performed to evaluate ZWINT expression in pancreatic cancer. ZWINT mRNA and protein expression were evaluated in normoxia and hypoxia. CHIP was used to evaluate HIF1α interaction with the ZWINT promoter. CCK8, colony formation, EDU, and cell cycle analysis were used to examine PC cell proliferation. Immunoprecipitation and immunofluorescence were used to examine the interaction of ZWINT, MDM2, and p53. p53 activity was evaluated by q-PCR and luciferase assay. Protein degradation and ubiquitination assays were used to analyze the role of ZWINT in p53 ubiquitination. ZWINT was overexpressed in pancreatic cancer and induced in hypoxia. ZWINT promoted pancreatic cancer growth and cell cycle progression. Bioinformatic analysis revealed that ZWINT may regulate the p53 signal pathway. ZWINT interacts with p53 and promotes its ubiquitination and degradation. ZWINT promoted proliferation via p53/p21. Immunohistochemistry of clinical specimens revealed that that ZWINT expression was significantly negatively correlated with p53/p21. Our data showed that hypoxia regulates the expression of ZWINT, which activated p53/p21 signaling pathway to promote PC growth.

MMP1 and MMP9 are potential prognostic biomarkers and targets for uveal melanoma

BACKGROUND

Uveal melanoma (UVM) is the leading cause of eye-related mortality worldwide. This study aimed to explore the expression and prognostic value of matrix metalloproteinases (MMPs) in UVM.

METHODS

Gene expression levels were obtained from the Gene Expression Omnibus (GEO) and Oncomine databases. Functional and pathway enrichment analyses were performed using the Metascape database. GeneMANIA was then applied to construct a protein-protein interaction network and identify the hub genes. Moreover, overall survival (OS) and disease-free survival (DFS) analysis for the hub genes was performed using the UALCAN and Gene Expression Profiling Interactive Analysis (GEPIA) online tool. Furthermore, TRRUST was used to predict the targets of the MMPs.

RESULTS

Our results revealed that the transcriptional levels of MMP1, MMP9, MMP10, MMP11, MMP13, MMP14, and MMP17 were upregulated in UVM tissues compared to normal tissues. A protein-protein interaction (PPI) network was constructed and the top 50 hub genes were identified. The functions of MMPs and their neighboring proteins are mainly associated with ECM-receptor interaction, proteoglycans in cancer, the IL-17 signaling pathway, and microRNAs in cancer. Among the MMPs, MMP1/2/9/11/14/15/16/17/24 played significant roles in the progression of UVM from stage 3 to stage 4. We also found that the expression of MMP1, MMP2, MMP9, and MMP16 positively correlated with OS and DFS in patients with UVM. Additionally, 18 transcription factors associated with nine MMPs were identified.

CONCLUSIONS

The results of this study may provide potential biomarkers and targets for UVM. However, further studies are required to confirm these results.

Prognostic Role of Matrix Metalloproteinases in Cervical Cancer: A Meta-Analysis

OBJECTIVE

Studies have published the association between the expression of matrix metalloproteinases (MMPs) and the outcome of cervical cancer. However, the prognostic value in cervical cancer remains controversial. This meta-analysis was conducted to evaluate the prognostic functions of MMP expression in cervical cancer.

METHODS

A comprehensive search of PubMed, Embase, and Web of Science databases was conducted to identify the eligible studies according to defined selection and excluding criteria and analyzed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Fixed and random effects models were evaluated through the hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate the overall survival (OS), recurrence-free survival (RFS), and progress-free survival (PFS).

RESULTS

A total of 18 eligible studies including 1967 patients were analyzed for prognostic value. Totally 16 selected studies including 21 tests were relevant to the cervical cancer OS, 4 studies focused on RFS, and 1 study on PFS. The combined pooled HRs and 95% CIs of OS were calculated with random-effects models (HR = 1.64, 95% CI = 1.01-2.65, P = .000). In the subgroup analysis for OS, there was no heterogeneity in MMP-2 (I² = .0%, P = .880), MMP-1 (I² = .0%, P = .587), and MMP-14 (I² = 28.3%, P = .248). In MMP-7 and MMP-9, the heterogeneities were obvious (I² = 99.2% (P = .000) and I² = 77.9% (P = .000), respectively). The pooled HRs and 95% CIs of RFS were calculated with fixed-effects models (HR = 2.22, 95% CI = 1.38-3.58, P = .001) and PFS (HR = 2.29, 95% CI = 1.14-4.58, P = .035).

CONCLUSIONS

The results indicated that MMP overexpression was associated with shorter OS and RFS in cervical cancer patients. It suggested that MMP overexpression might be a poor prognostic marker in cervical cancer. Research Registry Registration Number: reviewregistry 1159.

Effects of EFNA1 on cell phenotype and prognosis of esophageal carcinoma

Background

To investigate the expression and clinical significance of EFNA1 in broad-spectrum tumors, and to evaluate its relationship with prognosis and biological functions of esophageal carcinoma (ESCA).

Methods

EFNA1 expression in various cancers was analyzed according to the data in the TCGA database. The clinical data were integrated, to analyze the relationship with ESCA clinical parameters and prognosis, and EFNA1 expression in ESCA tissue samples was detected by immunohistochemistry (IHC). Based on bioinformatics, the functional background of EFNA1 overexpression was analyzed. EFNA1 knockout cell model was established by EFNA1-shRNA transfecting ESCA cells, and the effect of knocking down EFNA1 on the proliferation of ESCA cells was detected by MTT.

Results

Among 7563 samples from TCGA, the EFNA1 gene highly expressed in 15 samples with common cancers and endangered the prognosis of patients with tumors. Its overexpression in ESCA and its influence on the prognosis were most significant. EFNA1 expression in 80 samples with ESCA and their paired samples was tested by IHC to verify its high expression (paired t test, P < 0.001) in ESCA tissues. It was found that EFNA1 expression was related to clinical factors (TNM staging, P = 0.031; lymph node metastasis, P = 0.043; infiltration, P = 0.016). Meanwhile, EFNA1 was found to be an independent risk factor based on the COX multi-factor analysis. And to further explore the importance of EFNA1 in tumors, EC-9706 and ECA109 cells were screened from 8 ESCA-related cell lines to build EFNA1 knockdown cell models. The results showed that EFNA1 knockdown significantly inhibited the proliferation of tumor cells (P < 0.05). In terms of molecular mechanism, EFNA1 related genes were significantly enriched in the proliferative pathway according to the pathway enrichment analysis. It was found that knocking down EFNA1 did inhibit cell proliferation based on cell experiments.

Conclusions

EFNA1 overexpression in ESCA tissue is related to the prognosis of patients. Knocking down EFNA1 can significantly inhibit the proliferation of ESCA cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02362-8.

Screening of genes related to survival prognosis of cervical squamous cell carcinoma and construction of prognosis prediction model

AIM

We aimed to screen for the genes related to survival prognosis of cervical squamous cell carcinoma (CSCC) and then constructed a prognosis prediction model.

METHODS

The GSE63514 dataset was obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). The CSCC gene dataset and the GSE44001 dataset were obtained from The Cancer Genome Atlas and NCBI GEO, respectively. The Kaplan-Meier (KM) curve was used to evaluate the association between high and low prognosis that was with the actual survival prognosis information. The Cox proportional hazards model was used to screen out the optimized prognostic-related signature differentially expressed gene (DEG) combinations. Gene set enrichment analysis was used to perform pathway enrichment annotation analysis for DEGs that were related to risk grouping.

RESULTS

In total, 16 399 DEGs were obtained and 23 gene ontology biological processes and 8 Kyoto Encyclopedia of Genes and Genomes pathways were screened. Nine optimized DEG groups related to independent prognosis were selected. The KM curves of pathologic N0 and N1 showed that low-risk group were associated with a better overall survival (p = 1.518e; p = 1.704e-01). The pathways related to risk grouping were cytokine-cytokine receptor interaction, JAK stat signaling pathway, and glycolysis-gluconeogenesis.

CONCLUSION

On the basis of this study, we established a prognostic risk model, which provided a reliable prognostic tool and was of great significance for locating the biomarkers related to survival prognosis in CSCC.

High expression of MMP28 indicates unfavorable prognosis in pancreatic cancer

To investigate the expression pattern and diagnostic performance of matrix metalloproteinase 28 (MMP28) in pancreatic cancer (PC).The RNA-seq data of PC and normal pancreas tissue were acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression. Clinical information of PC that included prognostic data was obtained from TCGA. Later, Fisher exact test was applied for comparison of different clinicopathological features between high and low expression of MMP28 in PC. Afterwards, Kaplan-Meier survival analysis and Cox analysis (univariate and multivariate analysis) were used to explore the prognostic performance of MMP28 in PC cohort. Finally, gene set enrichment analysis (GSEA) revealed the potential signaling pathways related to high expression of MMP28 in PC.Upregulation of MMP28 was identified in PC tissue compared to normal pancreas tissue (P < .001). Overexpression of MMP28 was related to histological grade (P < .001), M classification (P = .014), and survival status (P = .028). Kaplan-Meier survival analysis revealed that high level of MMP28 implied unfavorable prognosis in PC (P = .002). Multivariate analysis confirmed that MMP28 was an independent risk factor in PC (hazard rate = 1.308, P = .018). Our GSEA analysis found that signaling pathways including glycolysis, p53 pathway, notch signaling, estrogen response late, cholesterol homeostasis, estrogen response early, mitotic spindle, and transforming growth factor beta signaling were enriched in the group with higher MMP28 expression.High expression of MMP28 could be identified in PC, which also served as an independent risk element for PC.

Identification of a Potential PPAR-Related Multigene Signature Predicting Prognosis of Patients with Hepatocellular Carcinoma

Peroxisome proliferator-activated receptors (PPARs) and part of their target genes have been reported to be related to the progression of hepatocellular carcinoma (HCC). The prognosis of HCC is not optimistic, and more accurate prognostic markers are needed. This study focused on discovering potential prognostic markers from the PPAR-related gene set. The mRNA data and clinical information of HCC were collected from TCGA and GEO platforms. Univariate Cox and lasso Cox regression analyses were used to screen prognostic genes of HCC. Three genes (MMP1, HMGCS2, and SLC27A5) involved in the PPAR signaling pathway were selected as the prognostic signature of HCC. A formula was established based on the expression values and multivariate Cox regression coefficients of selected genes, that was, risk score = 0.1488∗expression value of MMP1 + (−0.0393)∗expression value of HMGCS2 + (−0.0479)∗expression value of SLC27A5. The prognostic ability of the three-gene signature was assessed in the TCGA HCC dataset and verified in three GEO sets (GSE14520, GSE36376, and GSE76427). The results showed that the risk score based on our signature was a risk factor with a HR (hazard ratio) of 2.72 (95%CI (Confidence Interval) = 1.87 ~ 3.95, p < 0.001) for HCC survival. The signature could significantly (p < 0.0001) distinguish high-risk and low-risk patients with poor prognosis for HCC. In addition, we further explored the independence and applicability of the signature with other clinical indicators through multivariate Cox analysis (p < 0.001) and nomogram analysis (C‐index = 0.709). The above results indicate that the combination of MMP1, HMGCS2, and SLC27A5 selected from the PPAR signaling pathway could effectively, independently, and applicatively predict the prognosis of HCC. Our research provided new insights to the prognosis of HCC.

Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.

A novel prognostic prediction model based on seven immune-related RNAs for predicting overall survival of patients in early cervical squamous cell carcinoma

BACKGROUND

In this study, we aimed to mine immune-related RNAs expressed in early cervical squamous cell carcinoma to construct prognostic prediction models.

METHODS

The RNA sequencing data of 309 cervical squamous cell carcinoma (CSCC) cases, including data of individuals with available clinical information, were obtained from The Cancer Genome Atlas (TCGA) database. We included 181 early-stage CSCC tumor samples with clinical survival and prognosis information (training dataset). Then, we downloaded the GSE44001 gene expression profile data from the National Center for Biotechnology Information Gene Expression Omnibus (validation dataset). Gene ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to analyze the biological functions of differentially expressed immune-related genes (DEIRGs). We established protein-protein interactions and competing endogenous RNA networks using Cytoscape. Using the Kaplan-Meier method, we evaluated the association between the high- and low-risk groups and the actual survival and prognosis information. Our univariate and multivariate Cox regression analyses screened for independent prognostic factors.

RESULTS

We identified seven prognosis-related signature genes (RBAKDN, CXCL2, ZAP70, CLEC2D, CD27, KLRB1, VCAM1), the expression of which was markedly associated with overall survival (OS) in CSCC patients. Also, the risk score of the seven-gene signature discripted superior ability to categorize CSCC patients into high-risk and low-risk groups, with a observablydifferent OS in the training and validation datasets. We screened two independent prognostic factors (Pathologic N and prognostic score model status) that correlated significantly by univariate and multivariate Cox regression analyses in the TCGA dataset. To further explore the potential mechanism of immune-related genes, we observed associated essential high-risk genes with a cytokine-cytokine receptor interaction.

CONCLUSIONS

This study established an immune-related RNA signature, which provided a reliable prognostic tool and may be of great significance for determining immune-related biomarkers in CSCC.

Prognostic significance of abnormal matrix collagen remodeling in colorectal cancer based on histologic and bioinformatics analysis

As the major component of the tumor matrix, collagen greatly influences tumor invasion and prognosis. The present study compared the remodeling of collagen and collagenase in 56 patients with colorectal cancer (CRC) using Sirius red stain and immunohistochemistry, exploring the relationship between collagen remodeling and the prognosis of CRC. Weak or strong changes in collagen fiber arrangement in birefringence were observed. With the exception of a higher density, weak changes equated to a similar arrangement in normal collagen, while strong changes facilitated cross-linking into bundles. Compared with normal tissues, collagen I (COL I) and III (COL III) deposition was significantly increased in CRC tissues, and was positively correlated with the metastasis status. In tissues without distant metastasis, collagen IV (COL IV) levels were higher than that in normal tissues, while in tissues with distant metastasis, collagen IV expression was significantly lower. Furthermore, the expression of matrix metalloproteinase (MMP)-1, MMP-2, MMP-7, MMP-9 and lysyl oxidase-like 2 (LOXL2) was found to be elevated in the cancer stroma, which contributed to the hyperactive remodeling of collagen. The association between collagen-related genes and the occurrence and prognosis of CRC were analyzed using biometric databases. The results indicated that patients with upregulated expression of a combination of coding genes for collagen and collagenase exhibited poorer overall survival times. The coding genes COL1A1-2, COL3A1, COL4A3, COL4A6 and MMP2 may therefore be used as biomarkers to predict the prognosis of patients with CRC. Furthermore, the results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggest that collagen may promote tumor development by activating platelets. Collectively, the abnormal collagen remodeling, including associated protein and coding genes is associated with the tumorigenesis and metastasis, affecting the prognosis of patients with CRC.

Role of EFNA1 in tumorigenesis and prospects for cancer therapy

Cancer is one of the major threats to human health. It is of vital importance to reveal the mechanisms of tumorigenesis, identify effective biomarkers and develop novel treatments to improve patient outcome. EFNA1 (ephrinA1) is a member of the EFN family, and it has been studied extensively since its discovery in 1990. Increasing evidence indicates that EFNA1 plays a pivotal role in the pathogenesis of tumors. We provide a detailed overview of the expression and prognostic value of EFNA1 in different types of human malignancies. We briefly discuss the mechanisms of EFNA1 induction in hypoxic environments and its pro-angiogenic function in different cancer cells. We describe the effects of EFNA1 on tumor growth, invasiveness and metastasis. We summarize recent advances in EFNA1-associated cancer therapeutics with emphasis on the prospect of novel anti-tumor methods based on EFNA1.