Expression profiling of cervical cancers in Indian women at different stages to identify gene signatures during progression of the disease

Human Papillomavirus-Associated Tumor Extracellular Vesicles in HPV+ Tumor Microenvironments

Most infections with human papillomaviruses (HPVs) are self-resolving and asymptomatic. However, some infections can lead to the development of cancer at different mucosal sites, such as the cervix and the head and neck. Head and neck cancers (HNCs) are dichotomized into HPV-positive (HPV+) or HPV-negative (HPV-) based on their respective etiologies. Notably, the tumor microenvironment (TME) of the HPV+ subtype has an immune landscape characterized with increased immune infiltration, higher levels of T cell activation, and higher levels of immunoregulatory stimuli compared to their HPV- counterparts. Both enveloped and nonenveloped viruses hijack the extracellular vesicle (EV) biogenesis pathway to deploy a "trojan horse" strategy with a pseudoviral envelope to enhance infectivity and evade inflammation. EVs derived from HPV-infected tumor cells could allow for the stealth transport of viral cargo to neighboring nonmalignant cellular populations or infiltrating immune cells within the TME. Furthermore, viral cargo or altered cellular cargo from HPV-associated tumor EVs (HPV-TEVs) could alter the functional state or biological responses of the recipient cellular populations, which could shape the distinctive HPV+ TME. This review will cover the impact of EVs released from HPV-infected cells on HPV-induced carcinogenesis, their role in shaping the distinctive HPV+ tumor microenvironment, and current efforts to develop a painless EV-based liquid biopsy for HPV+ cancers.

Eight Aging-Related Genes Prognostic Signature for Cervical Cancer

This study searched for aging-related genes (ARGs) to predict the prognosis of patients with cervical cancer (CC). All data were obtained from Molecular Signatures Database, Cancer Genome Atlas, Gene Expression Integration, and Genotype Organization Expression. The R software was used to screen out the differentially expressed ARGs (DE-ARGs) between CC and normal tissues. A protein-protein interaction network was established by the DE-ARGs. The univariate and multivariate Cox regression analyses were conducted on the first extracted Molecular Complex Detection component, and a prognostic model was constructed. The prognostic model was further validated in the testing set and GSE44001 dataset. Prognosis was analyzed by Kaplan-Meier curves, and accuracy of the prognostic model was assessed by receiver operating characteristic area under the curve analysis. An independent prognostic analysis of risk score and some clinicopathological factors of CC was also performed. The copy-number variant (CNV) and single-nucleotide variant (SNV) of prognostic ARGs were analyzed by the BioPortal database. A clinical practical nomogram was established to predict individual survival probability. Finally, we carried out cell experiment to further verify the prognostic model. An eight-ARG prognostic signature for CC was constructed. High-risk CC patients had significantly shorter overall survival than low-risk patients. The receiver operating characteristic (ROC) curve validated the good performance of the signature in survival prediction. The Figo_stage and risk score served as independent prognostic factors. The eight ARGs mainly enriched in growth factor regulation and cell cycle pathway, and the deep deletion of FN1 was the most common CNV. An eight-ARG prognostic signature for CC was successfully constructed.

Overexpression of Secreted Phosphoprotein 1 (SPP1) predicts poor survival in HPV positive cervical cancer

Cervical cancer (CC) is the most prevalent malignant gynecological tumor with limited treatments. The present study describes the role of SPP1 in cancer progression, SPP1 emerged as one of the most overexpressed genes identified through clariom D transcriptome microarray. This investigation aims towards identifying a potential gene with significant prognostic value for detection and early diagnosis of cervical cancer. The elevated expression of SPP1 in cervical squamous cell carcinoma tissue was validated across GEO (Gene Expression Omnibus) microarray data sets, TCGA (The Cancer Genome Atlas), and Oncomine databases. SPP1 expression was found to be prognostically significant, showing association with poor survival rate of the patients. Our study intended to assess the expression of secreted phosphoprotein (SPP1) gene at mRNA and protein levels, and to explore the association of single nucleotide polymorphisms of SPP1 with risk of CC. Further, receiver operating characteristics (ROC) curve was plotted to determine the levels of SPP1 to differentiate CC against control. Results revealed significant (p < 0.01) stage-wise upregulation of SPP1 in CC compared to the normal cervical tissue and this was further confirmed using Immunohistochemistry and real-time PCR. The ROC for SPP1 demonstrated good selective power to differentiate malignant CC and non-malignant cervical tissues. The SPP1 gene -443 T > C promoter polymorphisms are found to be significantly predominant in the disease group and Insilico analysis by the TRANSFAC software confirms its association with loss of STAT6 transcription factor binding site leading to overexpression of the SPP1.

The intricate roles of RCC1 in normal cells and cancer cells

RCC1 (regulator of chromosome condensation 1) is a highly conserved chromatin-binding protein and the only known guanine-nucleotide exchange factor of Ran (a nuclear Ras homolog). RCC1 plays an essential role in the regulation of cell cycle-related activities such as nuclear envelope formation, nuclear pore complex and spindle assembly, and nucleocytoplasmic transport. Over the last decade, increasing evidence has emerged highlighting the potential relevance of RCC1 to carcinogenesis, especially cervical, lung, and breast cancer. In this review, we briefly discuss the roles of RCC1 in both normal and tumor cells based on articles published in recent years, followed by a brief overview of future perspectives in the field.

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning

BACKGROUND

A limitation of traditional differential expression analysis on small datasets involves the possibility of false positives and false negatives due to sample variation. Considering the recent advances in deep learning (DL) based models, we wanted to expand the state-of-the-art in disease biomarker prediction from RNA-seq data using DL. However, application of DL to RNA-seq data is challenging due to absence of appropriate labels and smaller sample size as compared to number of genes. Deep learning coupled with transfer learning can improve prediction performance on novel data by incorporating patterns learned from other related data. With the emergence of new disease datasets, biomarker prediction would be facilitated by having a generalized model that can transfer the knowledge of trained feature maps to the new dataset. To the best of our knowledge, there is no Convolutional Neural Network (CNN)-based model coupled with transfer learning to predict the significant upregulating (UR) and downregulating (DR) genes from both trained and untrained datasets.

RESULTS

We implemented a CNN model, DEGnext, to predict UR and DR genes from gene expression data obtained from The Cancer Genome Atlas database. DEGnext uses biologically validated data along with logarithmic fold change values to classify differentially expressed genes (DEGs) as UR and DR genes. We applied transfer learning to our model to leverage the knowledge of trained feature maps to untrained cancer datasets. DEGnext's results were competitive (ROC scores between 88 and 99[Formula: see text]) with those of five traditional machine learning methods: Decision Tree, K-Nearest Neighbors, Random Forest, Support Vector Machine, and XGBoost. DEGnext was robust and effective in terms of transferring learned feature maps to facilitate classification of unseen datasets. Additionally, we validated that the predicted DEGs from DEGnext were mapped to significant Gene Ontology terms and pathways related to cancer.

CONCLUSIONS

DEGnext can classify DEGs into UR and DR genes from RNA-seq cancer datasets with high performance. This type of analysis, using biologically relevant fine-tuning data, may aid in the exploration of potential biomarkers and can be adapted for other disease datasets.

Upregulation of CCT3 promotes cervical cancer progression through FN1

The mechanisms underlying cervical cancer progression have not yet been fully elucidated; thus, further investigations are required. Chaperonin containing TCP1 subunit 3 (CCT3) expression was found to be upregulated in several types of human cancer. However, the roles of CCT3 in cervical cancer remain poorly understood. Thus, the present study aimed to determine the roles of CCT3 in the progression of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). For this purpose, the Tumor Immune Estimation Resource and Gene Expression Profiling Interactive Analysis databases were used to analyze the mRNA and protein expression levels of CCT3 in CESC samples. The effects of CCT3 on the proliferation and migration of CESC in vitro were determined using various experiments, including proliferation, Transwell and flow cytometric assays. The results revealed that CCT3 expression was significantly upregulated in CESC, which was associated with a poor prognosis. The silencing of CCT3 suppressed CESC cell proliferation, migration and invasiveness in vitro. Additionally, CCT3-knockdown promoted CESC cell apoptosis and cell cycle arrest, and suppressed fibronectin 1 (FN1) protein expression. Furthermore, rescue assays demonstrated that CCT3 promoted CESC proliferation and migration via FN1. In conclusion, the findings of the present study demonstrated that CCT3 is closely associated with the progression of CESC. Thus, CCT3 may be considered a novel, promising biomarker, and a possible therapeutic target for CESC.

Integrative and Comprehensive Pancancer Analysis of Regulator of Chromatin Condensation 1 (RCC1)

Regulator of Chromatin Condensation 1 (RCC1) is the only known guanine nucleotide exchange factor that acts on the Ras-like G protein Ran and plays a key role in cell cycle regulation. Although there is growing evidence to support the relationship between RCC1 and cancer, detailed pancancer analyses have not yet been performed. In this genome database study, based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases, the potential role of RCC1 in 33 tumors' entities was explored. The results show that RCC1 is highly expressed in most human malignant neoplasms in contrast to healthy tissues. RCC1 expression is closely related to the prognosis of a broad variety of tumor patients. Enrichment analysis showed that some tumor-related pathways such as "cell cycle" and "RNA transport" were involved in the functional mechanism of RCC1. In particular, the conducted analysis reveals the relation of RCC1 to multiple immune checkpoint genes and suggests that the regulation of RCC1 is closely related to tumor infiltration of cancer-associated fibroblasts and CD8⁺ T cells. Coherent data demonstrate the association of RCC1 with the tumor mutation burden and microsatellite instability in various tumors. These findings provide new insights into the role of RCC1 in oncogenesis and tumor immunology in various tumors and indicate its potential as marker for therapy prognosis and targeted treatment strategies.

Exosomes from cervical cancer cells facilitate pro-angiogenic endothelial reconditioning through transfer of Hedgehog-GLI signaling components

BACKGROUND

Angiogenic switch is a hallmark feature of transition from low-grade to high-grade cervical intraepithelial neoplasia (CIN) in cervical cancer progression. Therefore, early events leading to locally-advanced cervical metastatic lesions demand a greater understanding of the underlying mechanisms. Recent leads indicate the role of tumor-derived exosomes in altering the functions of endothelial cells in cervical cancer, which needs further investigation.

METHODS

Exosomes isolated from cervical cancer cell lines were assessed for their angiogenic effect on the human umbilical vein endothelial cells (HUVEC) using tube formation and wound healing assay. The exosomal uptake by HUVEC cells was monitored using PKH-67 labelling followed by fluorescence microscopy. Alterations in Hh-GLI signaling components, PTCH1 and GLI1, in HUVEC were measured by immunoblotting. Changes in angiogenesis-related transcripts of vascular endothelial growth factor VEGF-A, VEGF-B, VEGFR2 and angiopoietin-1, angiopoietin-2, osteopontin were measured in exosome-treated HUVEC and in the exosomal RNA by RT-PCR.

RESULTS

Enhanced tube formation, with an increased number of nodes and branching was observed in HUVEC's treated with exosomes derived from different cervical cancer cell lines. HPV-positive (SiHa and HeLa) cells' exosomes were more angiogenic. Exosome-treated HUVEC showed increased migration rate. PKH-67 labelled exosomes were found internalized in HUVEC. A high level of PTCH1 protein was detected in the exosome-treated endothelial cells. Subsequent RT-PCR analysis showed increased transcripts of Hh-GLI downstream target genes VEGF-A, VEGFR2, angiopoietin-2, and decreased expression of VEGF-B, and angiopoietin-1, suggestive of active Hh-GLI signaling. These effects were more pronounced in HUVEC's treated with exosomes of HPV-positive cells. However, these effects were independent of tumor-derived VEGF-A as exosomal cargo lacked VEGF-A transcripts or proteins.

CONCLUSION

Overall, the data showed cervical cancer exosomes promote pro-angiogenic response in endothelial cells via upregulation of Hh-GLI signaling and modulate downstream angiogenesis-related target genes. The study provides a novel exosome-mediated mechanism potentially favoring cervical angiogenesis and thus identifies the exosomes as potential pharmacological targets against locally-advanced metastatic cervical lesions.

Predictive significance of STK17A in patients with gastric cancer and association with gastric cancer cell proliferation and migration

Gastric cancer (GC) is one of the most frequently diagnosed types of cancer worldwide, and exploring its potential therapeutic targets is particularly important for improving the prognosis of patients with GC. The aim of the present study was to investigate the association between serine/threonine kinase 17a (STK17A) expression and GC prognosis. STK17A expression was measured by quantitative real-time PCR, western blotting and immunohistochemical staining. Standard stable transfection technology was also used to construct overexpression and knockdown cell lines. Wound healing, Transwell, Cell Counting Kit-8 and colony formation assays, as well as other methods, were used to explore the function and underlying molecular mechanism of STK17A in GC. The results indicated that STK17A overexpression significantly promoted the proliferation and migration of GC cells. The clinical significance of STK17A in a cohort of 102 cases of GC was assessed by clinical correlation and Kaplan-Meier analyses. Overexpression of STK17A was demonstrated to be associated with tumor invasion depth (P<0.001), lymph node metastasis (P<0.001) and poor prognosis in terms of 5-year survival (P<0.001). In addition, Cox multivariate analysis revealed that STK17A expression was an independent risk factor for overall and progress-free survival (P<0.001). Therefore, STK17A may be a valuable biomarker for the prognosis of patients with GC.

Identification of Differentially Expressed Genes in Cervical Cancer Patients by Comparative Transcriptome Analysis

Cervical cancer is one of the most malignant reproductive diseases seen in women worldwide. The identification of dysregulated genes in clinical samples of cervical cancer may pave the way for development of better prognostic markers and therapeutic targets. To identify the dysregulated genes (DEGs), we have retrospectively collected 10 biopsies, seven from cervical cancer patients and three from normal subjects who underwent a hysterectomy. Total RNA isolated from biopsies was subjected to microarray analysis using the human Clariom D Affymetrix platform. Based on the results of principal component analysis (PCA), only eight samples are qualified for further studies; GO and KEGG were used to identify the key genes and were compared with TCGA and GEO datasets. Identified genes were further validated by quantitative real-time PCR and receiver operating characteristic (ROC) curves, and the highest Youden index was calculated in order to evaluate cutoff points (COPs) that allowed distinguishing of tissue samples of cervical squamous carcinoma patients from those of healthy individuals. By comparative microarray analysis, a total of 108 genes common across the six patients' samples were chosen; among these, 78 genes were upregulated and 26 genes were downregulated. The key genes identified were SPP1, LYN, ARRB2, COL6A3, FOXM1, CCL21, TTK, and MELK. Based on their relative expression, the genes were ordered as follows: TTK > ARRB2 > SPP1 > FOXM1 > LYN > MELK > CCL21 > COL6A3; this generated data is in sync with the TCGA datasets, except for ARRB2. Protein-protein interaction network analysis revealed that TTK and MELK are closely associated with SMC4, AURKA, PLK4, and KIF18A. The candidate genes SPP1, FOXM1, LYN, COL6A3, CCL21, TTK and MELK at mRNA level, emerge as promising candidate markers for cervical cancer prognosis and also emerge as potential therapeutic drug targets.

Screening of Therapeutic Candidate Genes of Quercetin for Cervical Cancer and Analysis of Their Regulatory Network

Purpose

To explore the therapeutic targets and regulatory mechanisms of the antitumor drug quercetin in the treatment of cervical cancer.

Methods

Cervical cancer (HeLa) cells were treated with quercetin and subjected to RNA sequencing using the BGISEQ-500 platform. By combined analysis of GEO database and RNA-seq results, the differentially expressed genes (DEGs) (namely, the genes in the GEO database that were upregulated/downregulated in cervical cancer compared with normal cervix and downregulated/upregulated after quercetin treatment) were identified. Functional enrichment and protein–protein interaction analyses were carried out for the DEGs. The candidate genes were identified using the Gentiscape2.2 and MCODE plug-ins for Cytoscape software, and the upstream miRNAs, lncRNAs, and circRNAs of the candidate genes were predicted using the online tools MirDIP, TarBase, and ENCORI. Finally, the regulatory network was constructed using Cytoscape software.

Results

Quercetin significantly inhibited the proliferation of cervical cancer cells. The combined analyses of the GEO database and RNA-seq results obtained 74 DEGs, and the functional enrichment analysis of the DEGs identified 861 biological processes, 32 cellular components, 50 molecular functions, and 56 KEGG pathways. Five therapeutic candidate genes, including EGFR, JUN, AR, CD44, and MUC1, were selected, and 10 miRNAs, 1 lncRNA, and 71 circRNAs upstream of these genes were identified. Finally, a lncRNA/circRNA-miRNA-mRNA-pathway regulatory network was constructed.

Conclusion

In this study, data mining was used to identify candidate genes and their regulatory network for the treatment of cervical cancer to provide a theoretical basis for targeted therapy of cervical cancer.

Combination of canstatin and arsenic trioxide suppresses the development of hepatocellular carcinoma

Complication of arsenic trioxide (ATO) and other drugs in cancer treatment has attracted much focus, but is limitedly investigated in hepatocellular carcinoma (HCC). This study aimed to explore the role of ATO combined with canstatin in HCC. HepG2 cells were treated with different concentrations of ATO with or without canstatin, CCK-8, flow cytometry, Transwell assays were conducted to determine cell proliferation, apoptosis, adhesion, migration, and invasion abilities. Besides, the protein expression or mRNA level of caspase-3, PCNA, and MMP-2 was measured using western blotting or qRT-PCR. BALB/c-nu/nu mice were used to establish nude mouse transplantation tumor model, and received ATO or canstatin treatment for 3 weeks. The results showed that ATO inhibited cell proliferation, adhesion, migration and invasion, and promoted cell apoptosis with a concentration-dependent way. Canstatin had a significantly inhibitory effect on cell proliferation, but had limited effects on the other cellular behaviors. Besides, combination with ATO and canstatin strengthened the effects of ATO alone on cell proliferation inhibition and cell apoptosis promotion. Moreover, both of ATO and canstatin increased the protein expression of caspase-3, while decreased PCNA and MMP-2, which was further strengthened upon their combination. Furthermore, both of ATO and canstatin inhibited tumor growth in vivo, which was also strengthened upon their combination. Collectively, we found that combined canstatin and ATO significantly inhibited cell proliferation, migration and adhesion abilities, and promoted cell apoptosis, and inhibited tumor growth, thus suppressed the progression of HCC.

The Multifaceted Roles of RCC1 in Tumorigenesis

RCC1 (regulator of chromosome condensation 1) is the only known guanine nucleotide exchange factor of Ran, a nuclear Ras-like G protein. RCC1 combines with chromatin and Ran to establish a concentration gradient of RanGTP, thereby participating in a series of cell physiological activities. In this review, we discuss the structure of RCC1 and describe how RCC1 affects the formation and function of the nuclear envelope, spindle formation, and nuclear transport. We mainly focus on the effect of RCC1 on the cell cycle during tumorigenesis and the recent research progress that has been made in relation to different tumor types.

Comparative transcriptomic profiling in HPV-associated cervical carcinogenesis: Implication of MHC class II and immunoglobulin heavy chain genes

AIM

We aimed to determine the biological processes and pathways involved in cervical carcinogenesis associated with high-risk human papillomavirus (HPV) infection.

MATERIALS AND METHODS

Total RNA was extracted from three formalin-fixed paraffin-embedded (FFPE) samples each of normal cervix, HPV-infected low-grade squamous intraepithelial lesion (LSIL), high-grade SIL (HSIL) and squamous cell carcinoma (SCC). Transcriptomic profiling by microarrays was conducted followed by downstream Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.

RESULTS

We examined the difference in GOs enriched for each transition stage from normal cervix to LSIL, HSIL, and SCC, and found 307 genes to be differentially expressed. In the transition from normal cervix to LSIL, the extracellular matrix (ECM) genes were significantly downregulated. The MHC class II genes were significantly upregulated in the LSIL to HSIL transition. In the final transition from HSIL to SCC, the immunoglobulin heavy locus genes were significantly upregulated and the ECM pathway was implicated.

CONCLUSION

Deregulation of the immune-related genes including MHC II and immunoglobulin heavy chain genes were involved in the transitions from LSIL to HSIL and SCC, suggesting immune escape from host anti-tumour response. The extracellular matrix plays an important role during the early and late stages of cervical carcinogenesis.

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

Aims. This study is aimed at identifying a prognostic signature for cervical cancer. Main Methods. The gene expression data and clinical information of cervical cancer and normal cervical tissues were acquired from The Cancer Genome Atlas and from three datasets of the Gene Expression Omnibus database. DESeq2 and Limma were employed to screen differentially expressed genes (DEGs). The overlapping DEGs among all datasets were considered the final DEGs. Then, the functional enrichment analysis was performed. Moreover, the Cox proportional hazards regression was performed to establish a prognostic signature of the DEGs. The Kaplan-Meier analysis was applied to test the model. Relationships between gene expression and clinicopathological parameters in cervical cancer, including age, HPV status, histology, stage, and lymph node metastasis, were analysed by the chi-square test. The somatic mutations of these prognostic genes were assessed through cBioPortal. The robustness of the model was verified in another two independent validation cohorts. Key Findings. In total, 169 overlapping upregulated genes and 29 overlapping downregulated genes were identified in cervical cancer compared with normal cervical tissues. Functional enrichment analysis indicated that the DEGs were mainly enriched in DNA replication, the cell cycle, and the p53 signalling pathway. Finally, a 5-gene- (ITM2A, DSG2, SPP1, EFNA1, and MMP1) based prognostic signature was built. According to this model, each patient was given a prognostic-related risk value. The Kaplan-Meier analysis showed that a higher risk was related to worse overall survival in cervical cancer, with an area under the receiver operating characteristic curve of 0.811 for 15 years. The validity of this model in the prediction of cervical cancer outcome was verified in another two independent datasets. In addition, our study also found that the low expression of ITM2A was associated with cervical adenocarcinoma. Interestingly, DSG2 was associated with the HPV status of cervical cancer. Significance. Our study constructed a prognostic model in cervical cancer and discovered two novel genes, ITM2A and DSG2, associated with cervical carcinogenesis and survival.

Prognostic and predictive roles of microRNA‑411 and its target STK17A in evaluating radiotherapy efficacy and their effects on cell migration and invasion via the p53 signaling pathway in cervical cancer

Cervical cancer is one of the most common gynecological malignancies worldwide. However, the pathogenesis of cervical cancer remains to be fully elucidated. Increasing evidence shows that microRNAs (miRNAs) may be involved in the pathogenesis of cervical cancer. The present study tested the hypothesis that the overexpression of miRNA (miR)-411 may delay, whereas the overexpression of serine/threonine kinase 17a (STK17A) may contribute to, cervical cancer development and progression through the p53 pathway. Cervical cancer tissues and adjacent normal tissues were obtained from 141 patients with cervical cancer following radiotherapy, with efficacy evaluated. The receiver operating characteristic curve was plotted to show the value of miR-411 and STK17A in predicting the efficacy of radiotherapy. Cox's proportional hazards regression model was utilized for multivariate analysis. A series of inhibitors, mimics or small interfering RNAs against STK17A were introduced to validate the regulatory mechanism of miR-411 in governing STK17A, determined with a luciferase reporter gene assay. The expression of miR-411 and STK17A, and the status of the p53 signaling pathway were evaluated. The colony forming ability, proliferation, migration, invasion and apoptosis of CaSki cells were assessed using a colony formation assay, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, Transwell assay and flow cytometry, respectively. miR-411 was upregulated but STK17A was reciprocal in cervical tissues. The overexpression of miR-411 and low expression of STK17A were correlated with high efficacy of radiotherapy. miR-411 and STK17A had predictive value for the efficacy of radiotherapy; miR-411 was the protective factor and STK17A was a risk factor for prognosis of cervical cancer. Increasing miR-411 activated the p53 signaling pathway and promoted cell apoptosis, but inhibited cell proliferation, invasion and migration. STK17A, an miR-411 target, increased following miR-411 over-expression, whereas the p53 signaling pathway was activated following STK17A inhibition. It was observed that the effect of miR-411 inhibition was lost following STK17A silencing. These findings indicate that the miR-411-mediated direct suppression of STK17A induces apoptosis and suppresses the proliferation, migration and invasion of human cervical cancer cells via the p53 signaling pathway. Additionally, miR-411 and STK17A have predictive value for the efficacy of radiotherapy.

Key Molecular Events in Cervical Cancer Development

Cervical cancer is the fourth most common cancer among women. Infection by high-risk human papillomavirus (HPV) is the main aetiology for the development of cervical cancer. Infection by high-risk human papillomavirus (HPV) and the integration of the HPV genome into the host chromosome of cervical epithelial cells are key early events in the neoplastic progression of cervical lesions. The viral oncoproteins, mainly E6 and E7, are responsible for the initial changes in epithelial cells. The viral proteins inactivate two main tumour suppressor proteins, p53, and retinoblastoma (pRb). Inactivation of these host proteins disrupts both the DNA repair mechanisms and apoptosis, leading to rapid cell proliferation. Multiple genes involved in DNA repair, cell proliferation, growth factor activity, angiogenesis, as well as mitogenesis genes become highly expressed in cervical intraepithelial neoplasia (CIN) and cancer. This genomic instability encourages HPV-infected cells to progress towards invasive carcinoma. The key molecular events involved in cervical carcinogenesis will be discussed in this review.

Novel Genomic Biomarker Candidates for Cervical Cancer As Identified by Differential Co-Expression Network Analysis

Cervical cancer is the second most common malignancy and the third reason for mortality among women in developing countries. Although infection by the oncogenic human papilloma viruses is a major cause, genomic contributors are still largely unknown. Network analyses, compared with candidate gene studies, offer greater promise to map the interactions among genomic loci contributing to cervical cancer risk. We report here a differential co-expression network analysis in five gene expression datasets (GSE7803, GSE9750, GSE39001, GSE52903, and GSE63514, from the Gene Expression Omnibus) in patients with cervical cancer and healthy controls. Kaplan-Meier Survival and principle component analyses were employed to evaluate prognostic and diagnostic performances of biomarker candidates, respectively. As a result, seven distinct co-expressed gene modules were identified. Among these, five modules (with sizes of 9-45 genes) presented high prognostic and diagnostic capabilities with hazard ratios of 2.28-11.3, and diagnostic odds ratios of 85.2-548.8. Moreover, these modules were associated with several key biological processes such as cell cycle regulation, keratinization, neutrophil degranulation, and the phospholipase D signaling pathway. In addition, transcription factors ETS1 and GATA2 were noted as common regulatory elements. These genomic biomarker candidates identified by differential co-expression network analysis offer new prospects for translational cancer research, not to mention personalized medicine to forecast cervical cancer susceptibility and prognosis. Looking into the future, we also suggest that the search for a molecular basis of common complex diseases should be complemented by differential co-expression analyses to obtain a systems-level understanding of disease phenotype variability.

Serine Threonine Kinase 17A Maintains the Epithelial State in Colorectal Cancer Cells

Serine threonine kinase 17A (STK17A) is a ubiquitously expressed kinase originally identified as a regulator of apoptosis; however, whether it functionally contributes to colorectal cancer has not been established. Here, we have analyzed STK17A in colorectal cancer and demonstrated decreased expression of STK17A in primary tumors, which is further reduced in metastatic lesions, indicating a potential role in regulating the metastatic cascade. Interestingly, changes in STK17A expression did not modify proliferation, apoptosis, or sensitivity of colorectal cancer cell lines to treatment with the chemotherapeutic 5-fluorouracil. Instead, STK17A knockdown induced a robust mesenchymal phenotype consistent with the epithelial-mesenchymal transition, including spindle-like cell morphology, decreased expression of adherens junction proteins, and increased migration and invasion. Additionally, overexpression of STK17A decreased cell size and induced widespread membrane blebbing, a phenotype often associated with activation of cell contractility. Indeed, STK17A-overexpressing cells displayed heightened phosphorylation of myosin light chain in a manner dependent on STK17A catalytic activity. Finally, patient-derived tumor organoid cultures were used to more accurately determine STK17A's effect in primary human tumor cells. Loss of STK17A induced morphologic changes, decreased E-cadherin, increased invasion, and augmented organoid attachment on 2D substrates, all together suggesting a more metastatic phenotype. Collectively, these data indicate a novel role for STK17A in the regulation of epithelial phenotypes and indicate its functional contribution to colorectal cancer invasion and metastasis. IMPLICATIONS: Loss of serine threonine kinase 17A occurs in colorectal cancer metastasis, induces mesenchymal morphologies, and contributes to tumor cell invasion and migration in colorectal cancer.

Identification of potential biomarkers in cervical cancer with combined public mRNA and miRNA expression microarray data analysis

Cervical cancer is the fourth most prevalent malignancy in females worldwide. Early diagnosis is key to improving survival rates. Molecular biomarkers are an important method for diagnosing a number of types of cancer, including cervical cancer. The present study utilized public data from three mRNA microarray datasets and one microRNA dataset to analyze the key genes involved in cervical cancer. The mRNA and microRNA expression profile datasets (GSE9750, GSE46857, GSE67522 and GSE30656) were downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) and microRNAs (DEMs) were screened using the online tool GEO2R. By using the DEGs consistent across the three mRNA datasets, a functional and pathway enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was constructed and module analysis performed using the Search Tool for the Retrieval of Interacting Genes. Validated target genes of the DEMs were identified using the miRecords website. Using the identified target genes of the DEMs, a survival analysis was performed using the OncoLnc online tool. A total of 73 DEGs and 19 DEMs were screened from the microarray expression profile datasets. ‘Integrin-mediated’, ‘proteolysis’ and ‘phosphoinositide 3 kinase-protein kinase 3’ signaling pathways were the most enriched in the DEGs. Three of the DEGs, including Ras homolog family member B (RhoB), stathmin 1 (STMN1) and cyclin D1 (CCNB1) were validated DEM target genes. The OncoLnc survival analysis identified that RhoB was associated with a significantly longer overall survival, whereas STMN1 was associated with a significantly reduced overall survival time in patients with cervical cancer. Finally, data from The Cancer Genome Atlas revealed an association between the mRNA expression levels of RhoB and STMN1, and the overall survival time for patients with cervical cancer. In conclusion, RhoB and STMN1 were identified as key genes that may provide potential targets for cervical cancer diagnosis and treatment.

Regulator of chromatin condensation 1 abrogates the G1 cell cycle checkpoint via Cdk1 in human papillomavirus E7-expressing epithelium and cervical cancer cells

Regulator of chromatin condensation 1 (RCC1) is a major guanine-nucleotide exchange factor for Ran GTPase and plays key roles in nucleo-cytoplasmic transport, mitosis, and nuclear envelope assembly. RCC1 is known to be a critical cell cycle regulator whose loss causes G1 phase arrest, but the molecular basis for this regulation is poorly understood. Furthermore, little is known about the relationship between RCC1 and carcinomas. Human papillomavirus (HPV) infection is highly associated with the development of cervical cancer. The expression and function of RCC1 in HPV-related cervical cancer and cell cycle regulation have not yet been explored. In this study, we first observed that RCC1 immunostaining was mildly increased in cervical cancer tissues and significantly upregulated in HPV E7-expressing cells; this localization was primarily nuclear. We showed that the transcription factor c-Jun transcriptionally upregulates RCC1 via a direct interaction with the RCC1 promoter. Moreover, siRNA-mediated knockdown of RCC1 inhibited G1/S cell cycle progression and DNA synthesis, while overexpression of RCC1 abrogated the G1 checkpoint. RCC1 knockdown downregulated the protein levels of the transcription factor E2F1, especially nuclear E2F1, by promoting its degradation in HPV E7-expressing cells. Overexpression of E2F1 rescued RCC1 knockdown-mediated inhibition of G1/S progression. Additionally, we showed that cyclin-dependent kinase 1 (Cdk1), a known target of E2F1, is involved in G1 checkpoint regulation, as Cdk1 knockdown hindered G1/S progression, while Cdk1 overexpression rescued RCC1 knockdown-mediated effect on G1 cell cycle progression. Furthermore, RCC1 knockdown reduced HPV E7 protein levels, which may in turn downregulate E2F1. Our study explores the function of RCC1 in G1/S cell cycle progression and suggests that RCC1 may be involved in HPV E7-mediated genomic instability.

Cancer cervix: Establishing an evidence-based strategy, an experience of a tertiary care centre in India

Carcinoma cervix is a common cancer among Indian women. Evidence based management is essential for best practice in treatment of carcinoma cervix for its effective control. The current imaging system like CT, MRI and PET CT scans have contributed in identifying the patients for optimal treatment and delivering treatment accurately. For stages IB2 to IV, concurrent chemoradiation is advocated with improvement in overall survival proven with randomized trials. Brachytherapy is an integral part in the radiation treatment. Imaged-guided brachytherapy using MRI is desirable, however less expensive imaging modalities such as CT and ultrasonography has been evaluated. In special situation such as for HIV positive patients and patients with neuroendocrine tumors have role of radiotherapy. For further improvement in control of cancer, it is required to integrate basic research to answer clinically relevant questions.

Expresión de EDNRB y CDX2 posibles biomarcadores en progresión al cáncer cervical

De acuerdo a la historia natural del cáncer del cuello uterino, en donde las lesiones preneoplásicas de bajo y alto grado pueden presentar fenómenos de regresión o progresión, existe gran interés en la búsqueda de biomarcadores que permita predecir la evolución de las lesiones preneoplásicas del cérvix hacia la progresión o regresión de la enfermedad. Estos biomarcadores pudieran ser de origen genético, o epigenético que alteren la expresión de los genes y que pudieran estar asociados con la carcinogénesis en diferentes tipos de tejido humano. El objetivo del estudio fue analizar la expresión del mARN de los genes SFRP1, PTPRN, CDO1, EDNRB, CDX2, EPB41L3 y HAND1 en muestras negativas para lesiones intraepiteliales cervicales (n=9), muestras con lesiones intraepiteliales de bajo grado (n=10) y alto grado (n=11). Se realizó  análisis de expresión de los genes mencionados mediante qRT-PCR y el análisis de los datos se realizó mediante la prueba no paramétrica de ANOVA. La diferencia estadística se determinó en valores p< 0,05. Para los genes EDNRB y CDX2 se observó disminución 66,7% en las muestras sin alteraciones histológicas cervicales, comparado con una disminución en la expresión del 50% en muestras con LIEBG y para el grupo de LIEAG del 36,4% para el gen EDNRB y del 27,3% para el gen CDX2 dando una diferencia estadísticamente significativa p= 0,02. Sugiriendo que EDNRB y CDX2 podrían ser útiles como posibles biomarcadores en la carcinogénesis cervical.

Human papillomavirus (HPV) genome status & cervical cancer outcome--A retrospective study

Background & objectives:

Persistent infections with high-risk (HR) human papillomaviruses such as HPV 16, 18, 31, 33 and 45 have been identified as the major aetiological factor for cervical cancer. The clinical outcome of the disease is often determined by viral factors such as viral load, physical status and oncogene expression. The aim of the present study was to evaluate the impact of such factors on clinical outcome in HPV16 positive, locally advanced cervical cancer cases.

Methods:

One hundred and thirty two pretreatment cervical tumour biopsies were selected from patients undergoing radiotherapy alone (n=63) or concomitant chemo-radiation (n=69). All the samples were positive for HPV 16. Quantitative real time-PCR was carried out to determine viral load and oncogene expression. Physical status of the virus was determined for all the samples by the ratio of E2_copies/E7_copies; while in 73 cases, the status was reanalyzed by more sensitive APOT (amplification of papillomavirus oncogene transcripts) assay. Univariate analysis of recurrence free survival was carried out using Kaplan-Meier method and for multivariate analysis the Cox proportional hazard model was used.

Results:

The median viral load was 19.4 (IQR, 1.9- 69.3), with viral integration observed in 86 per cent cases by combination of the two methodologies. Both univariate and multivariate analyses identified viral physical status as a good predictor of clinical outcome following radiation treatment, with episomal form being associated with increased recurrence free survival.

Interpretation & conclusions:

The present study results showed that viral physical status might act as an important prognostic factor in cervical cancer.

Identification and Validation of Reference Genes for RT-qPCR Studies of Hypoxia in Squamous Cervical Cancer Patients

Hypoxia is an adverse factor in cervical cancer, and hypoxia-related gene expression could be a powerful biomarker for identifying the aggressive hypoxic tumors. Reverse transcription quantitative PCR (RT-qPCR) is a valuable method for gene expression studies, but suitable reference genes for data normalization that are independent of hypoxia status and clinical parameters of cervical tumors are lacking. In the present work, we aimed to identify reference genes for RT-qPCR studies of hypoxia in squamous cervical cancer. From 422 candidate reference genes selected from the literature, we used Illumina array-based expression profiles to identify 182 genes not affected by hypoxia in cervical cancer, i.e. genes regulated by hypoxia in eight cervical cancer cell lines or correlating with the hypoxia-associated dynamic contrast-enhanced magnetic resonance imaging parameter A_Brix in 42 patients, were excluded. Among the 182 genes, nine candidates (CHCHD1, GNB2L1, IPO8, LASP1, RPL27A, RPS12, SOD1, SRSF9, TMBIM6) that were not associated with tumor volume, stage, lymph node involvement or disease progression in array data of 150 patients, were selected for further testing by RT-qPCR. geNorm and NormFinder analyses of RT-qPCR data of 74 patients identified CHCHD1, SRSF9 and TMBIM6 as the optimal set of reference genes, with stable expression both overall and across patient subgroups with different hypoxia status (A_Brix) and clinical parameters. The suitability of the three reference genes were validated in studies of the hypoxia-induced genes DDIT3, ERO1A, and STC2. After normalization, the RT-qPCR data of these genes showed a significant correlation with Illumina expression (P<0.001, n = 74) and A_Brix (P<0.05, n = 32), and the STC2 data were associated with clinical outcome, in accordance with the Illumina data. Thus, CHCHD1, SRSF9 and TMBIM6 seem to be suitable reference genes for studying hypoxia-related gene expression in squamous cervical cancer samples by RT-qPCR. Moreover, STC2 is a promising prognostic hypoxia biomarker in cervical cancer.

Profiling of Discrete Gynecological Cancers Reveals Novel Transcriptional Modules and Common Features Shared by Other Cancer Types and Embryonic Stem Cells

Studies on individual types of gynecological cancers (GCs), utilizing novel expression technologies, have revealed specific pathogenetic patterns and gene markers for cervical (CC), endometrial (EC) and vulvar cancer (VC). Although the clinical phenotypes of the three types of gynecological cancers are discrete, the fact they originate from a common embryological origin, has led to the hypothesis that they might share common features reflecting regression to early embryogenesis. To address this question, we performed a comprehensive comparative analysis of their profiles. Our data identified both common features (pathways and networks) and novel distinct modules controlling the same deregulated biological processes in all three types. Specifically, four novel transcriptional modules were discovered regulating cell cycle and apoptosis. Integration and comparison of our data with other databases, led to the identification of common features among cancer types, embryonic stem (ES) cells and the newly discovered cell population of squamocolumnar (SC) junction of the cervix, considered to host the early cancer events. Conclusively, these data lead us to propose the presence of common features among gynecological cancers, other types of cancers, ES cells and the pre-malignant SC junction cells, where the novel E2F/NFY and MAX/CEBP modules play an important role for the pathogenesis of gynecological carcinomas.

Multiple criteria optimization joint analyses of microarray experiments in lung cancer: from existing microarray data to new knowledge

Microarrays can provide large amounts of data for genetic relative expression in illnesses of interest such as cancer in short time. These data, however, are stored and often times abandoned when new experimental technologies arrive. This work reexamines lung cancer microarray data with a novel multiple criteria optimization‐based strategy aiming to detect highly differentially expressed genes. This strategy does not require any adjustment of parameters by the user and is capable to handle multiple and incommensurate units across microarrays. In the analysis, groups of samples from patients with distinct smoking habits (never smoker, current smoker) and different gender are contrasted to elicit sets of highly differentially expressed genes, several of which are already associated to lung cancer and other types of cancer. The list of genes is provided with a discussion of their role in cancer, as well as the possible research directions for each of them.

Integrated network analysis and logistic regression modeling identify stage-specific genes in Oral Squamous Cell Carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity but, OSCC can be difficult to detect at its earliest stage due to its molecular complexity and clinical behavior. Therefore, identification of key gene signatures at an early stage will be highly helpful.

METHODS

The aim of this study was to identify key genes associated with progression of OSCC stages. Gene expression profiles were classified into cancer stage-related modules, i.e., groups of genes that are significantly related to a clinical stage. For prioritizing the candidate genes, analysis was further restricted to genes with high connectivity and a significant association with a stage. To assess predictive power of these genes, a classification model was also developed and tested by 5-fold cross validation and on an independent dataset.

RESULTS

The identified genes were enriched for significant processes and functional pathways, and various genes were found to be directly implicated in OSCC. Forward and stepwise, multivariate logistic regression analyses identified 13 key genes whose expression discriminated early- and late-stage OSCC with predictive accuracy (area under curve; AUC) of ~0.81 in a 5-fold cross-validation strategy.

CONCLUSIONS

The proposed network-driven integrative analytical approach can identify multiple genes significantly related to an OSCC stage; the classification model that is developed with these genes may help to distinguish cancer stages. The proposed genes and model hold promise for monitoring of OSCC stage progression, and our findings may facilitate cancer detection at an earlier stage, resulting in improved treatment outcomes.

Systematic analysis to identify a key role of CDK1 in mediating gene interaction networks in cervical cancer development

OBJECTIVE

This study aims to identify corresponding differentially expressed genes in cervical cancer by comparing gene expression profiles between normal and cervical cancer samples.

METHOD

To identify differentially expressed genes in cervical cancer, two groups of Affymetrix microarray data available online were analyzed. One group consisted of 43 carcinomatous cervical epithelial cell samples, and the other was composed of 17 healthy cervical epithelial cell samples, both from the Amerindian. R packages-GO.db, KEGG.db and KEGGREST were used to detect GO categories and KEGG pathways with significant overrepresentation in differentially expressed genes comparing with the whole genome. Cytoscape was utilized to construct biological networks.

RESULTS

By comparing gene expression profile of normal and cervical cancer samples, 122 differentially expressed genes were identified including 46 up-regulated genes and 76 down-regulated genes. Using the identified differentially expressed genes, a large and a small biological network was constructed. In addition, 402 GO biological processes and 9 KEGG pathways were over-represented. Top significant biological processes included cell cycle and cell proliferation. Moreover, top significant KEGG pathways were oocyte meiosis, cell cycle and progesterone-mediated oocyte maturation. Most importantly, CDK1 frequently appeared in these processes and pathways, which indicated its significant role in the progression of cervical cancer.

CONCLUSION

CDK1 plays a comprehensive role in mediating genetic networks implicated in the progression of cervical cancer. Novel therapeutics targeting CDK1 or its related pathways might help improve prognosis of advanced stage cervical cancer.

Transcriptome-wide signatures of tumor stage in kidney renal clear cell carcinoma: connecting copy number variation, methylation and transcription factor activity

BACKGROUND

Comparative analysis of expression profiles between early and late stage cancers can help to understand cancer progression and metastasis mechanisms and to predict the clinical aggressiveness of cancer. The observed stage-dependent expression changes can be explained by genetic and epigenetic alterations as well as transcription dysregulation. Unlike genetic and epigenetic alterations, however, activity changes of transcription factors, generally occurring at the post-transcriptional or post-translational level, are hard to detect and quantify.

METHODS

Here we developed a statistical framework to infer the activity changes of transcription factors by simultaneously taking into account the contributions of genetic and epigenetic alterations to mRNA expression variations.

RESULTS

Applied to kidney renal clear cell carcinoma (KIRC), the model underscored the role of methylation as a significant contributor to stage-dependent expression alterations and identified key transcription factors as potential drivers of cancer progression.

CONCLUSIONS

Integrating copy number, methylation, and transcription factor activity signatures to explain stage-dependent expression alterations presented a precise and comprehensive view on the underlying mechanisms during KIRC progression.