A Five-Genes-Based Prognostic Signature for Cervical Cancer Overall Survival Prediction

ITM2A inhibits the progression of bladder cancer by downregulating the phosphorylation of STAT3

Bladder cancer stands as one of the prevalent malignancies in urological clinics, highlighting the pressing need to uncover prognostic or therapeutic avenues. ITM2A, a transmembrane protein, has been identified as a suppressor in tumor progression recently. Our study underscored a significant correlation between low ITM2A expression in bladder cancer tissues and high tumor grade, AJCC stage, and poor overall survival time. Additionally, our findings demonstrated that reinstating ITM2A expression impeded cell proliferation, migration, and invasion, while conversely, its suppression enhanced these malignant behaviors. Furthermore, we elucidated that ITM2A could suppress malignant phenotypes of bladder cancer cells via inhibiting activation of the STAT3 induced by IL-6. In conclusion, our research unveiled the mechanistic role of ITM2A in inhibiting tumor progression, shedding light on its potential as a prognostic predictor and therapeutic target in bladder cancer management.

Prediction of Cervical Cancer Patients' Survival Period with Machine Learning Techniques

OBJECTIVES

The objective of this research is to apply machine learning (ML) algorithms to predict the survival of cervical cancer patients. The aim was to address the limitations of traditional statistical methods, which often fail to provide accurate answers due to the complexity of the problem.

METHODS

This research employed visualization techniques for initial data understanding. Subsequently, ML algorithms were used to develop both classification and regression models for survival prediction. In the classification models, we trained the algorithms to predict the time interval between the initial diagnosis and the patient's death. The intervals were categorized as "<6 months," "6 months to 3 years," "3 years to 5 years," and ">5 years." The regression model aimed to predict survival time (in months). We used attribute weights to gain insights into the model, highlighting features with a significant impact on predictions and offering valuable insights into the model's behavior and decision-making process.

RESULTS

The gradient boosting trees algorithm achieved an 81.55% accuracy in the classification model, while the random forest algorithm excelled in the regression model, with a root mean square error of 22.432. Notably, radiation doses around the affected areas significantly influenced survival duration.

CONCLUSIONS

Machine learning demonstrated the ability to provide high-accuracy predictions of survival periods in both classification and regression problems. This suggests its potential use as a decision-support tool in the process of treatment planning and resource allocation for each patient.

Desmoglein-2 as a cancer modulator: friend or foe?

Desmoglein-2 (DSG2) is a calcium-binding single pass transmembrane glycoprotein and a member of the large cadherin family. Until recently, DSG2 was thought to only function as a cell adhesion protein embedded within desmosome junctions designed to enable cells to better tolerate mechanical stress. However, additional roles for DSG2 outside of desmosomes are continuing to emerge, particularly in cancer. Herein, we review the current literature on DSG2 in cancer and detail its impact on biological functions such as cell adhesion, proliferation, migration, invasion, intracellular signaling, extracellular vesicle release and vasculogenic mimicry. An increased understanding of the diverse repertoire of the biological functions of DSG2 holds promise to exploit this cell surface protein as a potential prognostic biomarker and/or target for better patient outcomes. This review explores the canonical and non-canonical functions of DSG2, as well as the context-dependent impacts of DSG2 in the realm of cancer.

Multidimensional outlook on the pathophysiology of cervical cancer invasion and metastasis

Cervical cancer being one of the primary causes of high mortality rates among women is an area of concern, especially with ineffective treatment strategies. Extensive studies are carried out to understand various aspects of cervical cancer initiation, development and progression; however, invasive cervical squamous cell carcinoma has poor outcomes. Moreover, the advanced stages of cervical cancer may involve lymphatic circulation with a high risk of tumor recurrence at distant metastatic sites. Dysregulation of the cervical microbiome by human papillomavirus (HPV) together with immune response modulation and the occurrence of novel mutations that trigger genomic instability causes malignant transformation at the cervix. In this review, we focus on the major risk factors as well as the functionally altered signaling pathways promoting the transformation of cervical intraepithelial neoplasia into invasive squamous cell carcinoma. We further elucidate genetic and epigenetic variations to highlight the complexity of causal factors of cervical cancer as well as the metastatic potential due to the changes in immune response, epigenetic regulation, DNA repair capacity, and cell cycle progression. Our bioinformatics analysis on metastatic and non-metastatic cervical cancer datasets identified various significantly and differentially expressed genes as well as the downregulation of potential tumor suppressor microRNA miR-28-5p. Thus, a comprehensive understanding of the genomic landscape in invasive and metastatic cervical cancer will help in stratifying the patient groups and designing potential therapeutic strategies.

IL-8 correlates with nonresponse to neoadjuvant nivolumab in HPV positive HNSCC via a potential extracellular vesicle miR-146a mediated mechanism

Therapy using anti-PD-1 immune checkpoint inhibitors (ICI) has revolutionized the treatment of many cancers including head and neck squamous cell carcinomas (HNSCC), but only a fraction of patients respond. To better understand the molecular mechanisms driving resistance, we performed extensive analysis of plasma and tumor tissues before and after a 4-week neoadjuvant trial in which HNSCC patients were treated with the anti-PD-1 inhibitor, nivolumab. Luminex cytokine analysis of patient plasma demonstrated that HPVpos nonresponders displayed high levels of the proinflammatory chemokine, interleukin-8 (IL-8), which decreased after ICI treatment, but remained higher than responders. miRNAseq analysis of tetraspanin-enriched small extracellular vesicles (sEV) purified from plasma of HPVpos nonresponders demonstrated significantly lower levels of seven miRNAs that target IL-8 including miR-146a. Levels of the pro-survival oncoprotein Dsg2, which has been to down-regulate miR-146a, are elevated with HPVpos tumors displaying higher levels than HPVneg tumors. Dsg2 levels decrease significantly following ICI in responders but not in nonresponders. In cultured HPVpos cells, restoration of miR-146a by forced expression or treatment with miR-146a-loaded sEV, reduced IL-8 level, blocked cell cycle progression, and promoted cell death. These findings identify Dsg2, miR-146a, and IL-8 as potential biomarkers for ICI response and suggest that the Dsg2/miR-146a/IL-8 signaling axis negatively impacts ICI treatment outcomes and could be targeted to improve ICI responsiveness in HPVpos HNSCC patients.

Bioinformatics and cheminformatics approaches to identify pathways, molecular mechanisms and drug substances related to genetic basis of cervical cancer

Cervical cancer (CC) is a global threat to women and our knowledge is frighteningly little about its underlying genomic contributors. Our research aimed to understand the underlying molecular and genetic mechanisms of CC by integrating bioinformatics and network-based study. Transcriptomic analyses of three microarray datasets identified 218 common differentially expressed genes (DEGs) within control samples and CC specimens. KEGG pathway analysis revealed pathways in cell cycle, drug metabolism, DNA replication and the significant GO terms were cornification, proteolysis, cell division and DNA replication. Protein-protein interaction (PPI) network analysis identified 20 hub genes and survival analyses validated CDC45, MCM2, PCNA and TOP2A as CC biomarkers. Subsequently, 10 transcriptional factors (TFs) and 10 post-transcriptional regulators were detected through TFs-DEGs and miRNAs-DEGs regulatory network assessment. Finally, the CC biomarkers were subjected to a drug-gene relationship analysis to find the best target inhibitors. Standard cheminformatics method including in silico ADMET and molecular docking study substantiated PD0325901 and Selumetinib as the most potent candidate-drug for CC treatment. Overall, this meticulous study holds promises for further in vitro and in vivo research on CC diagnosis, prognosis and therapies. Communicated by Ramaswamy H. Sarma.

Single-cell RNA-seq dissecting heterogeneity of tumor cells and comprehensive dynamics in tumor microenvironment during lymph nodes metastasis in gastric cancer

Lymph node metastasis is the common metastasis route of gastric cancer. However, until now, heterogeneities of tumor cells and tumor microenvironment in primary tumors (PT) and metastatic lymph nodes (MLN) of gastric cancer (GC) remains uncharacterized. In this study, scRNA-seq was performed on tissues from PT and MLN of gastric cancer. Trajectory analysis and function enrichment analyses were conducted to decode the underlying mechanisms contributing to LN metastasis of gastric cancer. Heterogeneous composition of immune cells and distant intercellular interactions in PT and MLN were analyzed. Based on the generated single cell transcriptome profiles, dynamics of gene expressions in cancer cells between PT and MLN were characterized. Moreover, we reconstructed the developmental trajectory of GC cells' metastasis to LN and identified two sub-types of GC cells with distinct potentials of having malignant biological behaviors. We characterized the repression of neutrophil polarization associated genes, like LCN2, which would contribute to LN metastasis, and histochemistry experiments validated our findings. Additionally, heterogeneity in neutrophils, rather than macrophages, was characterized. Immune checkpoint associated interaction of SPP1 was found active in MLN. In conclusion, we decode the dynamics of tumor cells during LN metastasis in GC and to identify a sub-type of GC cells with potentials of LN metastasis. Our data indicated that the disordering the neutrophils polarization and maturation and the activation of immune checkpoint SPP1 might contribute to LN metastasis in GC, providing a novel insight on the mechanism and potential therapeutic targets of LN metastasis in GC. This article is protected by copyright. All rights reserved.

The EPH/Ephrin System in Gynecological Cancers: Focusing on the Roots of Carcinogenesis for Better Patient Management

Gynecological cancers represent some of the most common types of malignancy worldwide. Erythropoietin-producing hepatocellular receptors (EPHs) comprise the largest subfamily of receptor tyrosine kinases, binding membrane-bound proteins called ephrins. EPHs/ephrins exhibit widespread expression in different cell types, playing an important role in carcinogenesis. The aim of the current review was to examine the dysregulation of the EPH/ephrin system in gynecological cancer, clarifying its role in ovarian, endometrial, and cervical carcinogenesis. In order to identify relevant studies, a literature review was conducted using the MEDLINE and LIVIVO databases. The search terms ephrin, ephrin receptor, ovarian cancer, endometrial cancer, and cervical cancer were employed and we were able to identify 57 studies focused on gynecological cancer and published between 2001 and 2021. All researched ephrins seemed to be upregulated in gynecological cancer, whereas EPHs showed either significant overexpression or extensive loss of expression in gynecological tumors, depending on the particular receptor. EPHA2, the most extensively studied EPH in ovarian cancer, exhibited overexpression both in ovarian carcinoma cell lines and patient tissue samples, while EPHB4 was found to be upregulated in endometrial cancer in a series of studies. EPHs/ephrins were shown to exert their role in different stages of gynecological cancer and to influence various clinicopathological parameters. The analysis of patients’ gynecological cancer tissue samples, most importantly, revealed the significant role of the EPH/ephrin system in the development and progression of gynecological cancer, as well as overall patient survival. In conclusion, the EPH/ephrin system represents a large family of biomolecules with promising applications in the fields of diagnosis, prognosis, disease monitoring, and treatment of gynecological cancer, with an established important clinical impact.

Identification of Key Pathways and Establishment of a Seven-Gene Prognostic Signature in Cervical Cancer

Cervical cancer (CC) remains high morbidity and mortality. We aimed to identify critical pathways underlying cervical carcinogenesis and establish a prognostic signature. Six datasets from the gene expression omnibus (GEO) database were used to screen the differentially expressed genes (DEGs) between CC and normal tissues. We used the unions of the DEGs to perform functional analysis. The 108 overlapped DEGs were analyzed to determine a prognostic signature by Cox regression and Lasso analysis based on The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Immune Cell Abundance Identifier (ImmuCellAI) were used to determine the relationships between the signature and biological functions. The PI3K-Akt signaling pathway, the Ras signaling pathway, and the viral carcinogenesis pathway may be critical for CC development. We identified seven genes (PLOD2, DSG2, SPP1, CXCL8, MCM5, HLTF, and KLF4) to construct a risk score formula. Survival analysis showed that the high-risk group indicated a worse prognosis than the low-risk group $\left(p<0.0001\right)$ . The AUC of the prognostic signature was 0.7449, 0.7641, and 0.8146 at 1, 3, and 5 years. We also identified that the signature is an independent prognostic factor. GSEA showed five pathways were relevant to the signature, such as the adherens junction pathway. The signature also affected the abundances of various types of immune cells, such as B cell, CD4+ T cell, and CD8+ T cell. Further, we found that SPP1 was co-expressed with HK3, CD163, CCL3, CLEC5A, MMP8, TREM1, OLR1, and TREM2. The results of Gene Ontology analysis showed that SPP1 and its co-expressed related proteins mainly affected metabolic process, multicellular organismal process, cell communication, cell proliferation, protein binding, and transporter activity. In conclusion, the present study explored the key pathways for CC development and the seven-gene signature can effectively make the prognosis evaluation of CC patients.

Integral membrane protein 2A enhances sensitivity to chemotherapy via notch signaling pathway in cervical cancer

As the second most common cancer among women, cervical cancer is a huge threat to their health all over the world. Integral membrane protein 2A (ITM2A), a member of the Type II Integral Membrane protein (ITM2) family, has been reported to act as a tumor suppressor in breast cancer and ovarian cancer. Moreover, the low expression of ITM2A was associated with cervical adenocarcinoma. However, the function of ITM2A in drug resistance in cervical cancer remains unclear. Here, we used bioinformatics methods to screen differentially expressed genes (DEGs) closely related to chemotherapeutic relapse cervical carcinoma. ITM2A is downregulated in cervical tumor tissues and is associated with poor survival. Furthermore, ITM2A is also downregulated in cervical cancer cells with cisplatin resistance. Overexpression of ITM2A increases the cisplatin sensitivity of cervical cancer cells. Mechanically, ITM2A upregulation mediates the sensitivity of cervical cancer cell through Notch signaling pathway. Our study suggests that ITM2A may serve as a target in mediating cisplatin-resistant cervical cancer.

A novel lncRNA-mRNA-miRNA signature predicts recurrence and disease-free survival in cervical cancer

Cervical cancer (CC) patients have a poor prognosis due to the high recurrence rate. However, there are still no effective molecular signatures to predict the recurrence and survival rates for CC patients. Here, we aimed to identify a novel signature based on three types of RNAs [messenger RNA (mRNAs), microRNA (miRNAs), and long non-coding RNAs (lncRNAs)]. A total of 763 differentially expressed mRNAs (DEMs), 46 lncRNAs (DELs), and 22 miRNAs (DEMis) were identified between recurrent and non-recurrent CC patients using the datasets collected from the Gene Expression Omnibus (GSE44001; training) and The Cancer Genome Atlas (RNA- and miRNA-sequencing; testing) databases. A competing endogenous RNA network was constructed based on 23 DELs, 15 DEMis, and 426 DEMs, in which 15 DELs, 13 DEMis, and 390 DEMs were significantly associated with disease-free survival (DFS). A prognostic signature, containing two DELs (CD27-AS1, LINC00683), three DEMis (hsa-miR-146b, hsa-miR-1238, hsa-miR-4648), and seven DEMs (ARMC7, ATRX, FBLN5, GHR, MYLIP, OXCT1, RAB39A), was developed after LASSO analysis. The built risk score could effectively separate the recurrence rate and DFS of patients in the high- and low-risk groups. The accuracy of this risk score model for DFS prediction was better than that of the FIGO (International Federation of Gynecology and Obstetrics) staging (the area under receiver operating characteristic curve: training, 0.954 vs 0.501; testing, 0.882 vs 0.656; and C-index: training, 0.855 vs 0.539; testing, 0.711 vs 0.508). In conclusion, the high predictive accuracy of our signature for DFS indicated its potential clinical application value for CC patients.

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.

Comprehensive analysis of the expression and prognosis for TNFAIPs in head and neck cancer

Head and neck cancer (HNC) tumorigenesis involves a combination of multiple genetic alteration processes. Tumour necrosis factor-alpha-induced proteins (TNFAIPs) are involved in tumour development and progression, but few studies have been conducted on these factors in HNC. We aimed to analyse TNFAIPs and assess their potential as prognostic biomarkers and therapeutic targets using the Oncomine, UALCAN, Human Protein Atlas, LinkedOmics, cBioPortal, GeneMANIA, Enrichr, and Tumor IMmune Estimation Resource databases. We found that the transcript levels of TNFAIP1, TNFAIP3, EFNA1, TNFAIP6 and TNFAIP8 were increased, while those of TNFAIP8L3 and STEAP4 were reduced in HNC tissues versus normal tissues. The EFNA1, TNFAIP8 and TNFAIP8L3 expression levels were significantly correlated with the pathological stage. In HNC patients, high PTX3 and TNFAIP6 transcript levels were significantly associated with shorter overall survival (OS). Moreover, genetic alterations in TNFAIP1, TNFAIP6, and STEAP4 resulted in poorer disease-free survival, progression-free survival, and OS, respectively. TNFAIPs may mediate HNC tumorigenesis by regulating PI3K-Akt, Ras and other signalling pathways. TNFAIPs are also closely correlated with the infiltration of immune cells, including B cells, CD8⁺ T cells, CD4⁺ T cells, etc. The data above indicate that TNFAIPs may be potential biomarkers and therapeutic targets for HNC.

Paradoxical Roles of Desmosomal Components in Head and Neck Cancer

Desmosomes are intercellular adhesion complexes involved in various aspects of epithelial pathophysiology, including tissue homeostasis, morphogenesis, and disease development. Recent studies have reported that the abnormal expression of various desmosomal components correlates with tumor progression and poor survival. In addition, desmosomes have been shown to act as a signaling platform to regulate the proliferation, invasion, migration, morphogenesis, and apoptosis of cancer cells. The occurrence and progression of head and neck cancer (HNC) is accompanied by abnormal expression of desmosomal components and loss of desmosome structure. However, the role of desmosomal components in the progression of HNC remains controversial. This review aims to provide an overview of recent developments showing the paradoxical roles of desmosomal components in tumor suppression and promotion. It offers valuable insights for HNC diagnosis and therapeutics development.

Machine learning-based prediction of survival prognosis in cervical cancer

BACKGROUND

Accurately forecasting the prognosis could improve cervical cancer management, however, the currently used clinical features are difficult to provide enough information. The aim of this study is to improve forecasting capability by developing a miRNAs-based machine learning survival prediction model.

RESULTS

The expression characteristics of miRNAs were chosen as features for model development. The cervical cancer miRNA expression data was obtained from The Cancer Genome Atlas database. Preprocessing, including unquantified data removal, missing value imputation, samples normalization, log transformation, and feature scaling, was performed. In total, 42 survival-related miRNAs were identified by Cox Proportional-Hazards analysis. The patients were optimally clustered into four groups with three different 5-years survival outcome (≥ 90%, ≈ 65%, ≤ 40%) by K-means clustering algorithm base on top 10 survival-related miRNAs. According to the K-means clustering result, a prediction model with high performance was established. The pathways analysis indicated that the miRNAs used play roles involved in the regulation of cancer stem cells.

CONCLUSION

A miRNAs-based machine learning cervical cancer survival prediction model was developed that robustly stratifies cervical cancer patients into high survival rate (5-years survival rate ≥ 90%), moderate survival rate (5-years survival rate ≈ 65%), and low survival rate (5-years survival rate ≤ 40%).

EFNA1 is a potential key gene that correlates with immune infiltration in low-grade glioma

EFNA1 is a key gene that is associated with the pathogenesis of several human cancers. However, the prognostic role of EFNA1 in many cancers and the relationship between EFNA1 and tumor-infiltrating lymphocytes in different cancers remain unclear.The expression levels of EFNA1 in 33 types of cancer in the TCGA (The Cancer Genome Atlas) database were collected via the UCSC Xena browser. The clinical data of LGG (low grade glioma) patients were downloaded from the TCGA database. The glioma data from the CGGA (Chinese Glioma Genome Atlas) database were also downloaded to verify the results. Kaplan-Meier and Cox regression analyses were used to investigate the prognostic value of EFNA1 in different cancers using R software. We verified the differential expression of EFNA1 in glioma and normal brain tissue via gene expression profiling interactive analysis. We evaluated the relationship between the expression level of EFNA1 and the clinicopathological features of LGG patients via the Wilcoxon signed-rank test. The immune infiltration levels were evaluated via tumor immune estimation resource (TIMER) and CIBERSORT, and the correlations between EFNA1 and immune cell levels were investigated via TIMER. Finally, we conducted gene set enrichment analysis (GSEA) to explore the potential mechanisms.Data from the TCGA database showed that EFNA1 was differentially expressed in many kinds of cancers when compared with normal tissues. Upregulated EFNA1 expression in esophageal carcinoma (ESCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and LGG correlated with shorter patient overall survival (OS) times. The Cox regression analysis revealed that the expression of EFNA1 was also a risk factor for the disease-specific survival (DSS) and progression-free interval (PFI) of LGG patients. The multiple Cox regression analysis revealed that EFNA1 was an independent prognostic factor for LGG patients. In addition, EFNA1 expression was increased in the WHO grade III group and the 1p19q non-codeletion group. Moreover, EFNA1 expression was positively correlated with the levels of infiltrating CD4+ T cells, myeloid dendritic cells and neutrophils in LGG. GSEA suggested that several GO and kyoto encyclopedia of genes and genomes (KEGG) items associated with nervous system function and apoptotic pathway were significantly enriched in the EFNA1-low and EFNA1-high expression phenotypes.EFNA1 may play a pivotal role in the development of LGG and may serve as a potential marker for LGG prognosis and therapy.

Identification of immune subtypes of cervical squamous cell carcinoma predicting prognosis and immunotherapy responses

Background

The main limitation of current immune checkpoint inhibitors (ICIs) in the treatment of cervical cancer comes from the fact that it benefits only a minority of patients. The study aims to develop a classification system to identify immune subtypes of cervical squamous cell carcinoma (SCC), thereby helping to screen candidates who may respond to ICIs.

Methods

A real-world cervical SCC cohort of 36 samples were analyzed. We used a nonnegative matrix factorization (NMF) algorithm to separate different expression patterns of immune-related genes (IRGs). The immune characteristics, potential immune biomarkers, and somatic mutations were compared. Two independent data sets containing 555 samples were used for validation.

Results

Two subtypes with different immunophenotypes were identified. Patients in sub1 showed favorable progression-free survival (PFS) and overall survival (OS) in the training and validation cohorts. The sub1 was remarkably related to increased immune cell abundance, more enriched immune activation pathways, and higher somatic mutation burden. Also, the sub1 group was more sensitive to ICIs, while patients in the sub2 group were more likely to fail to respond to ICIs but exhibited GPCR pathway activity. Finally, an 83-gene classifier was constructed for cervical SCC classification.

Conclusion

This study establishes a new classification to further understand the immunological diversity of cervical SCC, to assist in the selection of candidates for immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02894-3.

Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer

Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC retains its fatality rate of about half of the infected population globally. The major screening biomarkers and therapeutic target identification have now become a global concern. In the present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4643 differentially expressed genes. The up-regulatory genes mainly concentrate on immune-inflammatory responses, and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment, and we mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC and are verified by expression profile analysis. From our study, we have found that genes LILRB2 and CYBB play crucial roles in CC, as reported here for the first time. Furthermore, the survivability of the hub genes was also assessed, and among them, finally, CXCR4 has been identified as one of the most potential differentially expressed genes that might play a vital role in the survival of CC patients. Thus, CXCR4 could be used as a prognostic and/or diagnostic biomarker and a drug target for CC.

Expression Profiles Reveal Involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis

OBJECTIVE

The objective of this study was to identify key genes and shed light on the underlying molecular mechanisms of vulvar squamous cell carcinoma (VSCC).

METHODS

Bioinformatic software was utilized for the identification and characterization of key differentially expressed genes (DEGs) from microarrays GSE63678 and GSE38228, which contain VSCC and normal vulvar tissue data. These microarrays were obtained from Gene Expression Omnibus (GEO). Immunohistochemical assays (55 VSCC and 50 normal vulvar tissues) were utilized to validate the expression of VEGF, IGF1, BIRC5, and MMP1 screened from the identified DEGs. SPSS 18.0 software was used for statistical analyses of the relationships between IGF1, BIRC5, VEGF, MMP1 expression levels and patient clinicopathological characteristics.

RESULTS

A total of 141 DEGs were identified, among which 18 genes were closely correlated with the biological characteristics of VSCC. Four of the 18 genes (VEGF, IGF1, BIRC5, and MMP1) screened from the GEO database were markedly enriched in pathways in cancer (P < 0.05), and could be considered key genes in VSCC based on KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis in DAVID (Database for Annotation, Visualization and Integrated Discovery).The expression levels of these 4 hub genes, determined by immunohistochemical assays, were consistent with the bioinformatics results. Higher expression of IGF1 showed significant association with well-differentiated carcinomas (P = 0.017).BIRC5 expression levels showed a positive correlation with clinical stage (P = 0.039); compared with those in menopause for over 10 years, patients in menopause for less than 10 years at the time of diagnosis tended to have significantly higher expression of BIRC5 (P = 0.003). VEGF and MMP1 expression levels were not correlated with any of the tested clinicopathological characteristics.

CONCLUSION

VEGF, IGF1, BIRC5, and MMP1 were identified as being associated with VSCC using integrated bioinformatic methods, which may provide important insights into the pathogenesis of this disease and help to identify new biomarkers.

ITM2A as a Tumor Suppressor and Its Correlation With PD-L1 in Breast Cancer

Background

High expression of integral membrane protein 2A (ITM2A) was reported to be associated with favorable prognosis in several solid tumors including breast cancer. This study aimed to investigate the role of ITM2A in breast cancer, especially in respect to tumor microenvironment.

Methods

ITM2A expression was evaluated based on qRT-PCR results on breast cancer specimens, as well as TCGA and GEO datasets. The influence of ITM2A expression on breast cancer cell proliferation and tumor growth were evaluated by CCK-8 assay, clonogenic assay, and murine xenograft models. Transwell assay was performed to observe the changes of invasion and migration capacity in breast cancer cells. To determine the biological functions of ITM2A, differentially expressed genes (DEGs) were screened based on RNA-sequencing data of MCF-7 cells overexpressed ITM2A. Then, functional annotation on DEGs was given by Gene Ontology and KEGG analysis. The stimulation on programmed cell death ligand 1 (PD-L1) expression when ITM2A overexpressed was determined by flow cytometry. Meanwhile, the correlation on expression levels between PD-L1 and ITM2A was tested via qRT-PCR on 24 breast cancer tissues, as well as public database.

Results

We demonstrated that ITM2A was frequently downregulated in breast cancer. Patients with high expression levels of ITM2A had longer overall survival and relapse free survival. Overexpression of ITM2A inhibited proliferation and impaired cells capacity of invasion and migration in vitro and in vivo. The DEGs in breast cancer cells overexpressed ITM2A were found to be associated with immunity responses. Moreover, ITM2A was found to facilitate breast cancer cells to express PD-L1. The correlation between PD-L1 and ITM2A was verified with both qRT-PCR assay and public database. Additionally, it was found that breast cancer had higher ITM2A expression frequently had more tumor-infiltrating lymphocytes (TILs).

Conclusion

In summary, we found that high expression of ITM2A reduced the aggressivity of breast cancer cells and had a favorable effect on outcomes of patients with breast cancer. Moreover, ITM2A induced PD-L1 expression in breast cancer cells was accompanied with higher TILs numbers in tumor microenvironment.

Integrated Profiles Analysis Identified a Coding-Non-Coding Signature for Predicting Lymph Node Metastasis and Prognosis in Cervical Cancer

Accumulating evidence has shown that lymph node metastasis (LNM) is not only an important prognostic factor but also an indicator of the need for postoperative chemoradiotherapy. Therefore, identifying risk factors or molecular markers related to LNM is critical for predicting the prognosis and guiding individualized treatment of patients with cervical cancer. In this study, we used the machine learning-based feature selection approach to identify eight optimal biomarkers from the list of 250 differentially expressed protein-coding genes and long non-coding RNAs (lncRNAs) in the TCGA cohort. Then a coding-non-coding signature (named CNC8SIG) was developed using the elastic-net logistic regression approach based on the expression levels of eight optimal biomarkers, which is useful in discriminating patients with LNM from those without LNM in the discovery cohort. The predictive performance of the CNC8SIG was further validated in two independent patient cohorts. Moreover, the CNC8SIG was significantly associated with patient's survival in different patient cohorts. In silico functional analysis suggested that the CNC8SIG-associated mRNAs are enriched in known cancer-related biological pathways such as the Wnt signaling pathway, the Ras signaling pathway, Rap1 signaling pathway, and PI3K-Akt signaling pathway.

A Novel Four-Gene Prognostic Signature as a Risk Biomarker in Cervical Cancer

Background

Cervical cancer (CC) is a major malignancy affecting women worldwide, with limited treatment options for patients with advanced disease. The aim of this study was to identify novel prognostic biomarkers for CC.

Methods

RNA-Seq data from four Gene Expression Omnibus datasets (GSE5787, GSE6791, GSE26511, and GSE63514) were used to identify differentially expressed genes (DEGs) between CC and normal cervical tissues. Functional and enrichment analyses of the DEGs were performed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Oncomine database, Cytoscape software, and Kaplan-Meier survival analyses were used for in-depth screening of hub DEGs. The Cox regression was then used to develop a prognostic signature, which was in turn used to create a nomogram.

Results

A total of 207 DEGs were identified in the tissue samples, eight of which were prognostically significant in terms of overall survival (OS). Thereafter, a novel four-gene signature consisting of DSG2, MMP1, SPP1, and MCM2 was developed and validated using stepwise Cox analysis. The area under the receiver operating characteristic (ROC) curve (AUC) values were 0.785, 0.609, and 0.686 in the training, verification, and combination groups, respectively. The protein expression levels of the four genes were well validated by the western blotting. Moreover, the nomogram analysis showed that a combination of this four-gene signature plus lymph node metastasis (LNM) status effectively predicted the 1- and 3-year OS probabilities of CC patients with accuracies of 69.01% and 83.93%, respectively.

Conclusions

We developed a four-gene signature that can accurately predict the prognosis in terms of OS, of CC patients, and could be a valuable tool for designing treatment strategies.

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.