Understanding Cervical Cancer through Proteomics

Overexpression of carbonyl reductase 1 in ovarian cancer cells suppresses proliferation and activates the eIF2 signaling pathway

High expression of carbonyl reductase 1 (CBR1) protein in ovarian cancer cells inhibits tumor growth and metastasis. However, the underlying mechanism is unknown. To investigate the mechanism by which CBR1 suppresses tumor growth, the present study generated ovarian cancer cells that constitutively overexpress human CBR1 (hCBR1) protein. Ovarian cancer cell lines (OVCAR-3 and SK-OV-3) were transfected with a plasmid encoding hCBR1, followed by selection with G418 to isolate hCBR1-overexpressing lines. The proliferation rates of hCBR1-overexpressing cells were then compared with those of negative control and wild-type cells. Overexpression of hCBR1 led to significant inhibition of proliferation (P<0.05). Subsequently, to investigate changes in intracellular signaling pathways, cellular proteins were extracted and subjected to proteome analysis using liquid chromatography followed by mass spectrometry. There was an inverse correlation between CBR1 protein expression and cell proliferation. In addition, Ingenuity Pathway Analysis of hCBR1-overexpressing cell lines was performed, which revealed changes in the expression of proteins involved in signaling pathways related to growth regulation. Of these, the eukaryotic translation initiation factor 2 (eIF2) signaling pathway was upregulated most prominently. Thus, alterations in multiple tumor-related signaling pathways, including eIF2 signaling, may lead to growth suppression. Taken together, the present data may lead to the development of new drugs that target CBR1 and related signaling pathways, thereby improving outcomes for patients with ovarian cancer.

Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma

Background

Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechanism of co-morbidity. This study aims to explore the key genes, pathways, and immune cells that may link psoriasis and cervical squamous cell carcinoma (CESC).

Methods

The cervical squamous cell carcinoma dataset (GSE63514) was downloaded from the Gene Expression Omnibus (GEO). Two psoriasis-related datasets (GSE13355 and GSE14905) were merged into one comprehensive dataset after removing batch effects. Differentially expressed genes were identified using Limma and co-expression network analysis (WGCNA), and machine learning random forest algorithm (RF) was used to screen the hub genes. We analyzed relevant gene enrichment pathways using GO and KEGG, and immune cell infiltration in psoriasis and CESC samples using CIBERSORT. The miRNA-mRNA and TFs-mRNA regulatory networks were then constructed using Cytoscape, and the biomarkers for psoriasis and CESC were determined. Potential drug targets were obtained from the cMAP database, and biomarker expression levels in hela and psoriatic cell models were quantified by RT-qPCR.

Results

In this study, we identified 27 key genes associated with psoriasis and cervical squamous cell carcinoma. NCAPH, UHRF1, CDCA2, CENPN and MELK were identified as hub genes using the Random Forest machine learning algorithm. Chromosome mitotic region segregation, nucleotide binding and DNA methylation are the major enrichment pathways for common DEGs in the mitotic cell cycle. Then we analyzed immune cell infiltration in psoriasis and cervical squamous cell carcinoma samples using CIBERSORT. Meanwhile, we used the cMAP database to identify ten small molecule compounds that interact with the central gene as drug candidates for treatment. By analyzing miRNA-mRNA and TFs-mRNA regulatory networks, we identified three miRNAs and nine transcription factors closely associated with five key genes and validated their expression in external validation datasets and clinical samples. Finally, we examined the diagnostic effects with ROC curves, and performed experimental validation in hela and psoriatic cell models.

Conclusions

We identified five biomarkers, NCAPH, UHRF1, CDCA2, CENPN, and MELK, which may play important roles in the common pathogenesis of psoriasis and cervical squamous cell carcinoma, furthermore predict potential therapeutic agents. These findings open up new perspectives for the diagnosis and treatment of psoriasis and squamous cell carcinoma of the cervix.

Emerging biomarkers and molecular targets for precision medicine in cervical cancer

Cervical cancer remains a significant global health burden, necessitating innovative approaches for improved diagnostics and personalized treatment strategies. Precision medicine has emerged as a promising paradigm, leveraging biomarkers and molecular targets to tailor therapy to individual patients. This review explores the landscape of emerging biomarkers and molecular targets in cervical cancer, highlighting their potential implications for precision medicine. By integrating these biomarkers into comprehensive diagnostic algorithms, clinicians can identify high-risk patients at an earlier stage, enabling timely intervention and improved patient outcomes. Furthermore, the identification of specific molecular targets has paved the way for the development of targeted therapies aimed at disrupting key pathways implicated in cervical carcinogenesis. In conclusion, the evolving landscape of biomarkers and molecular targets presents exciting opportunities for advancing precision medicine in cervical cancer. By harnessing these insights, clinicians can optimize treatment selection, enhance patient outcomes, and ultimately transform the management of this devastating disease.

Serum Proteomic Signatures in Cervical Cancer: Current Status and Future Directions

In 2020, the World Health Organization (WHO) reported 604,000 new diagnoses of cervical cancer (CC) worldwide, and over 300,000 CC-related fatalities. The vast majority of CC cases are caused by persistent human papillomavirus (HPV) infections. HPV-related CC incidence and mortality rates have declined worldwide because of increased HPV vaccination and CC screening with the Papanicolaou test (PAP test). Despite these significant improvements, developing countries face difficulty implementing these programs, while developed nations are challenged with identifying HPV-independent cases. Molecular and proteomic information obtained from blood or tumor samples have a strong potential to provide information on malignancy progression and response to therapy in CC. There is a large amount of published biomarker data related to CC available but the extensive validation required by the FDA approval for clinical use is lacking. The ability of researchers to use the big data obtained from clinical studies and to draw meaningful relationships from these data are two obstacles that must be overcome for implementation into clinical practice. We report on identified multimarker panels of serum proteomic studies in CC for the past 5 years, the potential for modern computational biology efforts, and the utilization of nationwide biobanks to bridge the gap between multivariate protein signature development and the prediction of clinically relevant CC patient outcomes.

Corrigendum: Recent status and trends of nanotechnology in cervical cancer: a systematic review and bibliometric analysis

[This corrects the article DOI: 10.3389/fonc.2024.1327851.].

Deciphering the potential of proteomic-based biomarkers in women's reproductive diseases: empowering precision medicine in gynecology

CONTEXT

Gynecological disorders represent a complex set of malignancies that result from a diverse array of molecular changes affecting the lives of over a million women worldwide. Ovarian, Endometrial, and Cervical cancers, Endometriosis, PCOS are the most prevalent ones that pose a grave threat to women's health. Proteomics has emerged as an invaluable tool for developing novel biomarkers, screening methods, and targeted therapeutic agents for gynecological disorders. Some of these biomarkers have been approved by the FDA, but regrettably, they have a constrained diagnostic accuracy in early-stage diagnosis as all of these biomarkers lack sensitivity and specificity. Lately, high-throughput proteomics technologies have made significant strides, allowing for identification of potential biomarkers with improved sensitivity and specificity. However, limited successes have been shown with translation of these discoveries into clinical practice.

OBJECTIVE

This review aims to provide a comprehensive overview of the current and potential protein biomarkers for gynecological cancers, endometriosis and PCOS, discusses recent advances and challenges, and highlights future directions for the field.

CONCLUSION

We propose that proteomics holds great promise as a powerful tool to revolutionize the fight against female reproductive diseases and can ultimately improve personalized patient outcomes in women's biomedicine.

Unveiling diagnostic and therapeutic strategies for cervical cancer: biomarker discovery through proteomics approaches and exploring the role of cervical cancer stem cells

Cervical cancer (CC) is a major global health problem and leading cause of cancer deaths among women worldwide. Early detection through screening programs has reduced mortality; however, screening compliance remains low. Identifying non-invasive biomarkers through proteomics for diagnosis and monitoring response to treatment could improve patient outcomes. Here we review recent proteomics studies which have uncovered biomarkers and potential drug targets for CC. Additionally, we explore into the role of cervical cancer stem cells and their potential implications in driving CC progression and therapy resistance. Although challenges remain, proteomics has the potential to revolutionize the field of cervical cancer research and improve patient outcomes.

REST/NRSF Silencing Modifies Neuronal Gene Expression in siRNA-Treated HeLa Cells: A Preliminary Exploration in the Search for Neuronal Biomarkers of Cervical Cancer

Background and Objectives: REST (RE1-silencing transcription factor) diminution is associated with transcriptional relaxation, neuropeptide overexpression, and phenotype redefinition in neuroendocrine cancers, but this effect has barely been studied in cervical cancer (CC). We previously reported reduced expressions of REST in samples with premalignant lesions and CC; however, the transcriptional consequences for neural genes associated with reduced REST expression in CC are unknown. Therefore, the objective of this work was to evaluate the expression of neuronal genes in cancerous cells with reduced expression levels of REST. Materials and Methods: Here, we monitored levels of REST by immunostaining along the premalignant lesions and in invasive cervical squamous cell carcinoma (SCC) and endocervical adenocarcinoma (ADC) in tissue samples from female patients from southern Mexico and the derivative cell lines SiHa and HeLa, respectively. Next, we selected REST target genes in silico and explored the effect of REST silencing by RT-PCR in siRNA-treated HeLa cells. Results: The results show a REST diminution in premalignant lesions, SCC, ADC, and cancerous cell lines. Further REST silencing in HeLa cells altered the expression of genes containing the RE1 (Restrictive Element 1) sequence, including CgA (chromogranin A), CHRNβ2 (cholinergic receptor nicotinic β 2 subunit), BDNF (brain-derived neurotrophic factor), CRF (corticotropin-releasing factor), and RASSF1A (Ras association domain family 1). Conclusions: This work provides preliminary evidence of the role of REST loss in the transcriptional regulation of its target genes in HeLa cells, which could have positive implications for the search for new biomarkers of cervical cancer.

Silencing DTX3L Inhibits the Progression of Cervical Carcinoma by Regulating PI3K/AKT/mTOR Signaling Pathway

Cervical carcinoma (CC) is the second most prevalent gynecologic cancer in females across the world. To obtain a better understanding of the mechanisms underlying the development of CC, high-resolution label-free mass spectrometry was performed on CC and adjacent normal tissues from eight patients. A total of 2631 proteins were identified, and 46 significant differently expressed proteins (DEPs) were found between CC and normal tissues (p < 0.01, fold change >10 or <0.1). Ingenuity pathway analysis revealed that the majority of the proteins were involved in the regulation of eIF4 and p70S6K signaling and mTOR signaling. Among 46 DEPs, Integrinβ6 (ITGB6), PPP1CB, TMPO, PTGES3 (P23) and DTX3L were significantly upregulated, while Desmin (DES) was significantly downregulated in CC tissues compared with the adjacent normal tissues. In in vivo and in vitro experiments, DTX3L knockdown suppressed CC cell proliferation, migration, invasion and xenograft tumorigenesis, and enhanced cell apoptosis. Combination of silencing DTX3L and cisplatin treatment induced higher apoptosis percentage compared to cisplatin treatment alone. Moreover, DTX3L silencing inhibited the PI3K/AKT/mTOR signal pathway. Thus, our results suggested DTX3L could regulate CC progression through the PI3K/AKT/mTOR signal pathway and is potentially a novel biomarker and therapeutic target for CC.

A novel cervix carcinoma biomarker: Pathological-epigenomics, integrated analysis of MethylMix algorithm and pathology for predicting response to cancer immunotherapy

Herein, A non-invasive pathomics approach was developed to reveal the methylation status in patients with cervical squamous cell carcinoma and predict clinical outcomes and treatment response. Using the MethylMix algorithm, 14 methylation-driven genes were selected for further analysis. We confirmed that methylation-driven genes were differentially expressed in immune, stromal, and tumor cells. In addition, we constructed a methylation-driven model and explored the alterations in immunocyte infiltration between the different models. The methylation-driven subtypes identified in our investigation could effectively predict the clinical outcomes of cervical cancer. To further evaluate the level of methylation-driven patterns, we constructed a risk model with four genes. Significant correlations were observed between the score and immune response markers, including PD1 and CTLA4. Multiple immune infiltration algorithms evaluated the level of immunocyte infiltration between the high- and low-risk groups, while the components of anti-tumor immunocytes in the low-risk group were significantly increased. Subsequently, a total of 205 acquired whole-slide imaging (WSI) images were processed to capture image signatures, and the pathological algorithm was employed to construct an image prediction model based on the risk score classification. The model achieved an area under the curve (AUC) of 0.737 and 0.582 for the training and test datasets, respectively. Moreover, we conducted vitro assays for validation of hub risk gene. The proposed prediction model is a non-invasive method that combines pathomics features and genomic profiles and shows satisfactory performance in predicting patient survival and treatment response. More interdisciplinary fields combining medicine and electronics should be explored in the future.

Exploration of biomarkers for the diagnosis, treatment and prognosis of cervical cancer: a review

As the fourth most diagnosed cancer, cervical cancer (CC) is one of the major causes of cancer-related mortality affecting females globally, particularly when diagnosed at advanced stage. Discoveries of CC biomarkers pave the road to precision medicine for better patient outcomes. High throughput omics technologies, characterized by big data production further accelerate the process. To date, various CC biomarkers have been discovered through the advancement in technologies. Despite, very few have successfully translated into clinical practice due to the paucity of validation through large scale clinical studies. While vast amounts of data are generated by the omics technologies, challenges arise in identifying the clinically relevant data for translational research as analyses of single-level omics approaches rarely provide causal relations. Integrative multi-omics approaches across different levels of cellular function enable better comprehension of the fundamental biology of CC by highlighting the interrelationships of the involved biomolecules and their function, aiding in identification of novel integrated biomarker profile for precision medicine. Establishment of a worldwide Early Detection Research Network (EDRN) system helps accelerating the pace of biomarker translation. To fill the research gap, we review the recent research progress on CC biomarker development from the application of high throughput omics technologies with sections covering genomics, transcriptomics, proteomics, and metabolomics.

Cervical Cancer Prophylaxis—State-of-the-Art and Perspectives

Background: Each year 604,127 new cases of cervical cancer (CC) are diagnosed, and 341,831 individuals die from the disease. It is the fourth most common cancer among women and the fourth most common cause of death from female cancers worldwide. The pathogenesis of CC is associated with human papillomavirus (HPV) infections and consists of several steps involving cell proliferation outside the human body’s control mechanisms. Strategies to prevent CC are based on screening and vaccination. Scope of the Review: The aim of this paper was to collect and analyze the available literature on the issue of CC prevention and the impact of the COVID-19 pandemic on its implementation. For this purpose, PubMed and Google Scholar databases were searched using keywords, such as “cervical cancer”; “HPV”; “prevention”; “prophylaxis”; “vaccination”; “screening” and “COVID-19” in different variations. Only articles published since 2018 were included in the study. Conclusions: Selected European countries have different CC prevention programs funded by national budgets. This translates into observed differences in the risk of death from CC (age-standardized rate Malta = 1.1, Poland = 5.9). COVID-19 pandemic due to disruption of CC screening may exacerbate these differences in the future. To improve the situation, new screening methods, such as p16/Ki67, HPV self-testing, and the use of artificial intelligence in colposcopic assessment, should be disseminated, as well as free HPV vaccination programs implemented in all countries. The search for new solutions is not without significance and entails ultra-sensitive screening tests for risk groups (mRNA E6/E7, SOX1/SOX14), HPV vaccines with shorter dosing schedules, and new therapeutic pathways using nanotheranostics.

Cervical Cancer Imaging Features Associated With ADRB1 as a Risk Factor for Cerebral Neurovascular Metastases

Bioinformatics tools are used to create a clinical prediction model for cervical cancer metastasis and to investigate the neurovascular-related genes that are involved in brain metastasis of cervical cancer. One hundred eighteen patients with cervical cancer were divided into two groups based on the presence or absence of metastases, and the clinical data and imaging findings of the two groups were compared retrospectively. The nomogram-based model was successfully constructed by taking into account four clinical characteristics (age, stage, N, and T) as well as one imaging characteristic (original_glszm_GrayLevelVariance Rad-score). In patients with cervical cancer, headaches and vomiting were more often reported in the brain metastasis group than in the other metastasis groups. According to the TCGA data, mRNA differential gene expression analysis of patients with cervical cancer revealed an increase in the expression of neurovascular-related gene Adrenoceptor Beta 1 (ADRB1) in the brain metastasis group. An analysis of the correlation between imaging features and ADRB1 expression revealed that ADRB1 expression was significantly higher in the low Rad-score group compared with the high Rad-score group (P = 0.025). Therefore, ADRB1 expression in cervical cancer was correlated with imaging features and was associated as a risk factor for cerebral neurovascular metastases. This study developed a nomogram prediction model for cervical cancer metastasis using age, stage, N, T and original_glszm_GrayLevelVariance. As a risk factor associated with the development of cerebral neurovascular metastases of cervical cancer, ADRB1 expression was significantly higher in brain metastases from cervical cancer.

Role of immunocytochemistry in cervical cancer screening

The cervical cancer screening has been based conventionally on cytologic analysis. With advances in understanding the role of human papillomavirus, cotesting has been applied. But most of the patients subjected to colposcopy did not benefit, except in cases with HSIL [high-grade squamous intraepithelial lesion] cytology. Because of this, a step to increase the sensitivity to detect cancers and pre-cancers but with higher specificity with minimal overdiagnosis leading to prevention of unindicated cervical biopsies is highly desired. Such triaging step in cases with abnormal screening results is expected to minimize invasive interventions because of low false positivity. With availability of methodologies leading to quantitatively and qualitatively enhanced cell-blocks from residual liquid based cytology specimens, immunostaining can be performed for multiple immunomarkers with potential objectivity to triage initial screening test results. This is enhanced further with inclusion of AV marker in the cell-blocks and application of SCIP (subtractive coordinate immunoreactivity pattern) approach. The cell-blocks are also resource for performing other ancillary studies including molecular pathology and proteomics/metabolomics as potential tests in future. This review explores application of residual liquid based cytology specimen for cell-blocking with application of ancillary studies in algorithmic manner as adjunct to ASCCP management guidelines for improved patient care.

Insights on Proteomics-Driven Body Fluid-Based Biomarkers of Cervical Cancer

Cervical cancer is one of the top malignancies in women around the globe, which still holds its place despite being preventable at early stages. Gynecological conditions, even maladies like cervical cancer, still experience scrutiny from society owing to prevalent taboo and invasive screening methods, especially in developing economies. Additionally, current diagnoses lack specificity and sensitivity, which prolong diagnosis until it is too late. Advances in omics-based technologies aid in discovering differential multi-omics profiles between healthy individuals and cancer patients, which could be utilized for the discovery of body fluid-based biomarkers. Body fluids are a promising potential alternative for early disease detection and counteracting the problems of invasiveness while also serving as a pool of potential biomarkers. In this review, we will provide details of the body fluids-based biomarkers that have been reported in cervical cancer. Here, we have presented our perspective on proteomics for global biomarker discovery by addressing several pertinent problems, including the challenges that are confronted in cervical cancer. Further, we also used bioinformatic methods to undertake a meta-analysis of significantly up-regulated biomolecular profiles in CVF from cervical cancer patients. Our analysis deciphered alterations in the biological pathways in CVF such as immune response, glycolytic processes, regulation of cell death, regulation of structural size, protein polymerization disease, and other pathways that can cumulatively contribute to cervical cancer malignancy. We believe, more extensive research on such biomarkers, will speed up the road to early identification and prevention of cervical cancer in the near future.

Preliminary Identification of the Aerobic Cervicovaginal Microbiota in Mexican Women With Cervical Cancer as the First Step Towards Metagenomic Studies

Cervical cancer (CC) is considered a public health problem. Recent studies have evaluated the possible relationship between the cervicovaginal microbiome and gynecologic cancer but have not studied the relationship between aerobic bacterial communities and neoplasia. The study aimed to identify the cultivable aerobic bacterial microbiota in women with cervical cancer as a preliminary approach to the metagenomic study of the cervicovaginal microbiome associated with cervical cancer in Mexican women. An observational cross-sectional study was conducted, including 120 women aged 21-71 years, divided into two study groups, women with locally advanced CC (n=60) and women without CC (n=60). Sociodemographic, gynecological-obstetric, sexual, and habit data were collected. Cervicovaginal samples were collected by swabbing, from which standard microbiological methods obtained culturable bacteria. The strains were genetically characterized by PCR-RFLP of the 16S rRNA gene and subsequently identified by sequencing the same gene. Variables regularly reported as risk factors for the disease were found in women with CC. Differences were found in the prevalence and number of species isolated in each study group. Bacteria commonly reported in women with aerobic vaginitis were identified. There were 12 species in women with CC, mainly Corynebacterium spp. and Staphylococcus spp.; we found 13 bacterial species in the group without cancer, mainly Enterococcus spp. and Escherichia spp. The advanced stages presented a more significant number of isolates and species. This study provided a preliminary test for cervicovaginal metagenomic analysis, demonstrating the presence of aerobic cervicovaginal dysbiosis in women with CC and the need for more in-depth studies.

Tissue Characterization Using an Electrical Bioimpedance Spectroscopy-Based Multi-Electrode Probe to Screen for Cervical Intraepithelial Neoplasia

The successful management of cervical intraepithelial neoplasia (CIN) with proper screening and treatment methods could prevent cervical cancer progression. We propose a bioimpedance spectroscopic measurement device and a multi-electrode probe as an independent screening tool for CIN. To evaluate the performance of this screening method, we enrolled 123 patients, including 69 patients with suspected CIN and 54 control patients without cervical dysplasia who underwent a hysterectomy for benign disease (non-CIN). Following conization, the electrical properties of the excised cervical tissue were characterized using an electrical bioimpedance spectroscopy-based multi-electrode probe. Twenty-eight multifrequency voltages were collected through the two concentric array electrodes via a sensitivity-optimized measurement protocol based on an electrical energy concentration method. The electrical properties of the CIN and non-CIN groups were compared with the results of the pathology reports. Reconstructed resistivity tended to decrease in the CIN and non-CIN groups as frequency increased. Reconstructed resistivity from 625 Hz to 50 kHz differed significantly between the CIN and non-CIN groups (p < 0.001). Using 100 kHz as the reference, the difference between the CIN and non-CIN groups was significant. Based on the difference in reconstructed resistivity between 100 kHz and the other frequencies, this method had a sensitivity of 94.3%, a specificity of 84%, and an accuracy of 90% in CIN screening. The feasibility of noninvasive CIN screening was confirmed through the difference in the frequency spectra evaluated in the excised tissue using the electrical bioimpedance spectroscopy-based multi-electrode screening probe.