Identification of Candidate Plasma Protein Biomarkers for Cervical Cancer Using the Multiplex Proximity Extension Assay

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.

A Prospective Study on the Progression, Recurrence, and Regression of Cervical Lesions: Assessing Various Screening Approaches

(1) Background: The prediction of cervical lesion evolution is a challenge for clinicians. This prospective study aimed to determine and compare the predictive accuracy of cytology, HPV genotyping, and p16/Ki67 dual staining alone or in combination with personal risk factors in the prediction of progression, regression, or persistence of cervical lesions in human papillomavirus (HPV)-infected patients; (2) Methods: This prospective study included HPV-positive patients with or without cervical lesions who underwent follow-up in a private clinic. We calculated the predictive performance of individual tests (cervical cytology, HPV genotyping, CINtecPlus results, and clinical risk factors) or their combination in the prediction of cervical lesion progression, regression, and persistence; (3) Results: The highest predictive performance for the progression of cervical lesions was achieved by a model comprising a Pap smear suggestive of high-grade squamous intraepithelial lesion (HSIL), the presence of 16/18 HPV strains, a positive p16/Ki67 dual staining result along with the presence of at least three clinical risk factors, which had a sensitivity (Se) of 74.42%, a specificity of 97.92%, an area under the receiver operating curve (AUC) of 0.961, and an accuracy of 90.65%. The prediction of cervical lesion regression or persistence was modest when using individual or combined tests; (4) Conclusions: Multiple testing or new biomarkers should be used to improve HPV-positive patient surveillance, especially for cervical lesion regression or persistence prediction.

Assay methods based on proximity-enhanced reactions for detecting non-nucleic acid molecules

Accurate and reliable detection of biological molecules such as nucleic acids, proteins, and small molecules is essential for the diagnosis and treatment of diseases. While simple homogeneous assays have been developed and are widely used for detecting nucleic acids, non-nucleic acid molecules such as proteins and small molecules are usually analyzed using methods that require time-consuming procedures and highly trained personnel. Recently, methods using proximity-enhanced reactions (PERs) have been developed for detecting non-nucleic acids. These reactions can be conducted in a homogeneous liquid phase via a single-step procedure. Herein, we review three assays based on PERs for the detection of non-nucleic acid molecules: proximity ligation assay, proximity extension assay, and proximity proteolysis assay.

Analytical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis

PURPOSE

To characterize and analytically validate the MSDA Test, a multi-protein, serum-based biomarker assay developed using Olink^® PEA methodology.

EXPERIMENTAL DESIGN

Two lots of the MSDA Test panel were manufactured and subjected to a comprehensive analytical characterization and validation protocol to detect biomarkers present in the serum of patients with multiple sclerosis (MS). Biomarker concentrations were incorporated into a final algorithm used for calculating four Disease Pathway scores (Immunomodulation, Neuroinflammation, Myelin Biology, and Neuroaxonal Integrity) and an overall Disease Activity score.

RESULTS

Analytical characterization demonstrated that the multi-protein panel satisfied the criteria necessary for a fit-for-purpose validation considering the assay's intended clinical use. This panel met acceptability criteria for 18 biomarkers included in the final algorithm out of 21 biomarkers evaluated. VCAN was omitted based on factors outside of analytical validation; COL4A1 and GH were excluded based on imprecision and diurnal variability, respectively. Performance of the four Disease Pathway and overall Disease Activity scores met the established acceptability criteria.

CONCLUSIONS AND CLINICAL RELEVANCE

Analytical validation of this multi-protein, serum-based assay is the first step in establishing its potential utility as a quantitative, minimally invasive, and scalable biomarker panel to enhance the standard of care for patients with MS.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Insights into the Relationship between Pentraxin-3 and Cancer

Although cancer can be cured if detected early and treated effectively, it is still a leading cause of death worldwide. Tumor development can be limited by an appropiate immune response, but it can be promoted by chronic extensive inflammation through metabolic dysregulation and angiogenesis. In the past decade, numerous efforts have been made in order to identify novel candidates with predictive values in cancer diagnostics. In line with this, researchers have investigated the involvement of pentraxin-3 (PTX-3) in cellular proliferation and immune escape in various types of cancers, although it has not been clearly elucidated. PTX-3 is a member of the long pentraxin subfamily which plays an important role in regulating inflammation, innate immunity response, angiogenesis, and tissue remodeling. Increased synthesis of inflammatory biomarkers and activation of different cellular mechanisms can induce PTX-3 expression in various types of cells (neutrophils, monocytes, lymphocytes, myeloid dendritic cells, fibroblasts, and epithelial cells). PTX-3 has both pro- and anti-tumor functions, thus dual functions in oncogenesis. This review elucidates the potential usefulness of PTX-3 as a serum biomarker in cancer. While future investigations are needed, PTX-3 is emerging as a promising tool for cancer's diagnosis and prognosis, and also treatment monitoring.

A Targeted Proteomics Approach for Screening Serum Biomarkers Observed in the Early Stage of Type I Endometrial Cancer

Endometrial cancer (EC) is the most common gynecologic malignancy, and it arises in the inner part of the uterus. Identification of serum biomarkers is essential for diagnosing the disease at an early stage. In this study, we selected 44 healthy controls and 44 type I EC at tumor stage 1, and we used the Immuno-oncology panel and the Target 96 Oncology III panel to simultaneously detect the levels of 92 cancer-related proteins in serum, using a proximity extension assay. By applying this methodology, we identified 20 proteins, associated with the outcome at binary logistic regression, with a p-value below 0.01 for the first panel and 24 proteins with a p-value below 0.02 for the second one. The final multivariate logistic regression model, combining proteins from the two panels, generated a model with a sensitivity of 97.67% and a specificity of 83.72%. These results support the use of the proposed algorithm after a validation phase.

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.

Mass Spectrometry-Based Proteomics for Biomarker Discovery

Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.

Proteomics technologies for cancer liquid biopsies

Alterations in DNAs could not reveal what happened in proteins. The accumulated alterations of DNAs would change the manifestation of proteins. Therefore, as is the case in cancer liquid biopsies, deep proteome profiling will likely provide invaluable and clinically relevant information in real-time throughout all stages of cancer progression. However, due to the great complexity of proteomes in liquid biopsy samples and the limitations of proteomic technologies compared to high-plex sequencing technologies, proteomic discoveries have yet lagged behind their counterpart, genomic technologies. Therefore, novel protein technologies are in urgent demand to fulfill the goals set out for biomarker discovery in cancer liquid biopsies.Notably, conventional and innovative technologies are being rapidly developed for proteomic analysis in cancer liquid biopsies. These advances have greatly facilitated early detection, diagnosis, prognosis, and monitoring of cancer evolution, adapted or adopted in response to therapeutic interventions. In this paper, we review the high-plex proteomics technologies that are capable of measuring at least hundreds of proteins simultaneously from liquid biopsy samples, ranging from traditional technologies based on mass spectrometry (MS) and antibody/antigen arrays to innovative technologies based on aptamer, proximity extension assay (PEA), and reverse phase protein arrays (RPPA).

Cervical Carcinoma: Oncobiology and Biomarkers

Cervical cancer is one of the most common types of carcinomas causing morbidity and mortality in women in all countries of the world. At the moment, the oncology, oncobiology, and oncomorphology of cervical cancer are characterized by the accumulation of new information; various molecular biological, genetic, and immunohistochemical methods of investigation of the mechanisms of cervical carcinogenesis are tested and applied; targeted antitumour drugs and diagnostic, prognostic, and predictive biomarkers are being searched for. Many issues of the etiopathogenesis of cervical cancer have not been sufficiently studied, and the role of many biomarkers characterizing various stages of cervical carcinogenesis remains unclear. Therefore, the target of this review is to systematize and understand several problems in the pathogenesis of cervical cancer and to evaluate the significance and role of biomarkers in cervical carcinogenesis.

Emerging role of SIRT2 in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the most devastating cancer types, accounting for >80% of lung cancer cases. The median relative survival time of patients with NSCLC is <1 year. Lysine acetylation is a major post-translational modification that is required for various biological processes, and abnormal protein acetylation is associated with various diseases, including NSCLC. Protein deacetylases are currently considered cancer permissive partly due to malignant cells being sensitive to deacetylase inhibition. Sirtuin 2 (SIRT2), a primarily cytosolic nicotinamide adenine dinucleotide-dependent class III protein deacetylase, has been shown to catalyze the removal of acetyl groups from a wide range of proteins, including tubulin, ribonucleotide reductase regulatory subunit M2 and glucose-6-phosphate dehydrogenase. In addition, SIRT2 is also known to possess lysine fatty deacylation activity. Physiologically, SIRT2 serves as a regulator of the cell cycle and of cellular metabolism. It has been shown to play important roles in proliferation, migration and invasion during carcinogenesis. It is notable that both oncogenic and tumor suppressive functions of SIRT2 have been described in NSCLC and other cancer types, suggesting a context-specific role of SIRT2 in cancer progression. In addition, inhibition of SIRT2 exhibits a broad anticancer effect, indicating its potential as a therapeutic for NSCLC tumors with high expression of SIRT2. However, due to the diverse molecular and genetic characteristics of NSCLC, the context-specific function of SIRT2 remains to be determined. The current review investigated the functions of SIRT2 during NSCLC progression with regard to its regulation of metabolism, stem cell-like features and autophagy.

Identification of Candidate Protein Biomarkers for CIN2+ Lesions from Self-Sampled, Dried Cervico-Vaginal Fluid Using LC-MS/MS

Simple Summary

Cervical cancer is the fourth most common cancer among women worldwide, and screening programs increase its detection rate and survivability. The molecular screening of the presence of human papilloma viruses (HPV) as alternatives to physical examinations offers cost-efficient solutions and can be performed on self-collected samples. A persistent infection with HPV is necessary (but not sufficient) to develop cancer, and additional biomarkers are needed to increase the precision. Here, we have analysed protein biomarkers found in self-collected dried cervico–vaginal fluid (CVF) from both controls and women with cervical cancer pre-stages. Our conclusion is that protein biomarkers can be robustly detected from dried CVF and that these can aid in the detection of cervical cancer pre-stages.

Abstract

Molecular screening programs for cervical cancer detect the presence of human papilloma virus (HPV) in cell material or vaginal fluids. Persistent infection with high-risk HPV is a necessary pre-requisite, but the majority of infections do not lead to pathological states. Additional biomarkers are needed to increase the specificity of the molecular tests. Here, we have investigated the possibility of detecting protein biomarkers using mass spectrometry from dried self-sampled cervico–vaginal fluid deposited on FTA cards. We found significant intra-individual correlations (p < 2.2 × 10⁻¹⁶), although heterogenous protein profiles were obtained between individuals. Out of 3699 proteins found in total, 169 were detected in at least 95% of the samples. Using a discovery/replication design, 18 proteins were found to be significant in the discovery cohort, with higher values in those cases compared to controls. All of these were found to also have higher levels among the cases in the replication cohort, with one protein (DEAD-Box Helicase) remaining statistically significant. Finally, a predictive 7-protein multivariate model was developed with a sensitivity and specificity of 0.90 and 0.55, respectively. Our results demonstrate that robust measurements of protein biomarkers can be obtained from self-sampled dried CVF and that these could be used to predict cervical cancer pre-stages.

Targeted proteomics-derived biomarker profile develops a multi-protein classifier in liquid biopsies for early detection of esophageal squamous cell carcinoma from a population-based case-control study

BACKGROUND

Early diagnosis of esophageal squamous cell carcinoma (ESCC) remains a challenge due to the lack of specific blood biomarkers. We aimed to develop a serum multi-protein signature for the early detection of ESCC.

METHODS

We selected 70 healthy controls, 30 precancerous patients, 60 stage I patients, 70 stage II patients and 70 stage III/IV ESCC patients from a completed ESCC case-control study in a high-risk area of China. Olink Multiplex Oncology II targeted proteomics panel was used to simultaneously detect the levels of 92 cancer-related proteins in serum using proximity extension assay.

RESULTS

We found that 10 upregulated and 13 downregulated protein biomarkers in serum could distinguish the early-stage ESCC from healthy controls, which were validated by the significant dose-response relationships with ESCC pathological progression. Applying least absolute shrinkage and selection operator (LASSO) regression and backward elimination algorithm, ANXA1 (annexin A1), hK8 (kallikrein-8), hK14 (kallikrein-14), VIM (vimentin), and RSPO3 (R-spondin-3) were kept in the final model to discriminate early ESCC cases from healthy controls with an area under curve (AUC) of 0.936 (95% confidence interval: 0.899 ~ 0.973). The average accuracy rates of the five-protein classifier were 0.861 and 0.825 in training and test data by five-fold cross-validation.

CONCLUSIONS

Our study suggested that a combination of ANXA1, hK8, hK14, VIM and RSPO3 serum proteins could be considered as a potential tool for screening and early diagnosis of ESCC, especially with the establishment of a three-level hierarchical screening strategy for ESCC control.

Proximity ligation assay: an ultrasensitive method for protein quantification and its applications in pathogen detection

It is of great significance to establish sensitive and accurate pathogen detection methods, considering the continuous emergence or re-emergence of infectious diseases seriously influences the safety of human and animals. Proximity ligation assay (PLA) is developed for the sensitive protein detection and also can be used for the detection of pathogens. PLA employs aptamer or monoclonal/polyclonal antibody-nucleic acid complexes as proximity probes. When the paired proximity probes bind to the same target protein or protein complex, they will be adjacent to each other and form an amplifiable DNA sequence through ligation. Combining the specificity of enzyme-linked immunosorbent assay (ELISA) and sensitivity of polymerase chain reaction (PCR), PLA transforms the detection of protein into the detection of DNA nucleic acid sequence. Therefore, as an ultrasensitive protein assay, PLA has great potential for quantification, localization of protein, and clinical diagnostics. In this review, we summarize the basic principles of PLA and its applications in pathogen detection. KEY POINTS: • Different forms of proximity ligation assay are introduced. • Applications of proximity ligation assay in pathogen detection are summarized. • Proximity ligation assay is an ultrasensitive method to quantify protein and pathogen.

Impact of pentraxin 3 genetic variants on uterine cervical cancer clinicopathologic characteristics

The aims of this study were to investigate the relationships among pentraxin 3 (PTX3) genetic variants and development and clinicopathological characteristics of uterine cervical cancer, and patient survival in Taiwanese women. The study enrolled 125 patients with invasive cancer and 98 patients with precancerous lesions of uterine cervix, and 325 control women. PTX3 genetic variants rs2120243, rs3816527, rs2305619 and rs1840680 were selected and their genotypic distributions were determined by real-time polymerase chain reaction. Our results indicated that patients with genotype CC in PTX3 rs2120243 and genotype GG in rs1840680 had more chance to have adenocarcinoma but not squamous cell carcinoma, as compared to those with CA/AA and those with GA/AA, respectively. No other clinicopatholgical characteristics were associated with PTX3 genetic variants. In addition, PTX3 genetic variants were not associated with 5 years survival of cervical cancer patients. In conclusions, PTX3 genetic variants are not associated with carcinogenesis and clinicopathological variables of uterine cervix and patient survival in Taiwanese women. The only independent predictor for the 5 years survival is pelvic lymph node metastasis.

Elevated plasma Sirtuin2 level predicts heart failure after acute myocardial infarction

Background

There is currently no evidence regarding the role of plasma Sirtuin2 (SIRT2) level in acute myocardial infarction (AMI) yet. This study assessed the role of plasma SIRT2 in AMI, and investigated the association of plasma SIRT2 level with major adverse cardiovascular events (MACE) and heart failure after AMI.

Methods

This is a prospective observational study. A total of 129 AMI patients (mean age: 62.2±12.7 years old, male/female: 96/33) were included. Cox proportional hazards regression models were used to estimate the association of different SIRT2 levels with MACE and heart failure after AMI.

Results

According to the 75th percentile value of plasma SIRT2 level, we divided all the AMI patients into two groups: high-level group (plasma SIRT2 level ≥109.0 pg/mL) and low-level group (plasma SIRT2 level <109.0 pg/mL). Compared with the low-level group, the high-level group had higher percentage of Killip class ≥3 (P<0.001), left ventricular ejection fraction (LVEF) <50% (P=0.007) or even <40% (P=0.012), use of breathing machine(P=0.003), and higher plasma brain natriuretic peptide (BNP) level (P=0.006). Multivariate Cox regression analysis showed that there were higher risks of MACE [hazard ratio (HR) 11.20, 95% confidence interval (CI): 3.18–39.52, P<0.001)] and heart failure (HR 27.10, 95% CI: 4.65–157.83, P<0.001) in the high-level group.

Conclusions

The present study suggested that plasma SIRT2 level is a promising biomarker to predict heart failure and MACE after AMI.

Comparative Analysis of Multiplex Platforms for Detecting Vitreous Biomarkers in Diabetic Retinopathy

Purpose

To evaluate the feasibility of using the Proximity Extension Assay (PEA) platform to detect biomarkers in vitreous and to compare the findings with results obtained with an electrochemiluminescent (ECL) sandwich immunoassay.

Methods

Vitreous samples from patients with proliferative diabetic retinopathy (PDR) and non-diabetic controls were tested using two different proteomics platforms. Forty-one assays were completed with the ECL platform and 459 with the PEA platform. Spearman's rank correlation coefficient (r_s) was used to determine the direction and strength of the relationship between protein levels detected by both platforms.

Results

Three hundred sixty-six PEA assays detected the tested protein in at least 25% of samples, and the difference in protein abundance between PDR and controls was statistically significant for 262 assays. Seventeen ECL assays yielded a detection rate ≥ 25%, and the difference in protein concentration between PDR and controls was statistically significant for 13 proteins. There was a subset of proteins that were detected by both platforms, and for those the Spearman's correlation coefficient was higher than 0.8.

Conclusions

PEA is suitable for the analysis of vitreous samples, showing a strong correlation with the ECL platform. The detection rate of PEA panels was higher than the panels tested with ECL. The levels of several proinflammatory and angiogenic cytokines were significantly higher in PDR vitreous compared to controls.

Translational Relevance

This study provides new information on the yields of small-volume assays that can detect proteins of interest in ocular specimens, and it identifies patterns of cytokine dysregulation in PDR.

Tumour Cell Secretome in Chemoresistance and Tumour Recurrence

Chemoresistance is a major factor driving tumour relapse and the high rates of cancer-related deaths. Understanding how cancer cells overcome chemotherapy-induced cell death is critical in promoting patient survival. One emerging mechanism of chemoresistance is the tumour cell secretome (TCS), an array of protumorigenic factors released by tumour cells. Chemotherapy exposure can also alter the composition of the TCS, known as therapy-induced TCS, and can promote tumour relapse and the formation of an immunosuppressive tumour microenvironment (TME). Here, we outline how the TCS can protect cancer cells from chemotherapy-induced cell death. We also highlight recent evidence describing how therapy-induced TCS can impact cancer stem cell (CSC) expansion and tumour-associated immune cells to enable tumour regrowth and antitumour immunity.

Overexpression and biological function of PRDX6 in human cervical cancer

Background: Our previous study demonstrated that the peroxiredoxin 6 (PRDX6) protein was downregulated in squamous cervical cancer samples after neoadjuvant chemotherapy compared with the expression level before chemotherapy. However, the effect of PRDX6 on the biological behavior of cervical cancer is still uncertain. Thus, the purpose of this study was to explore the functional impacts of PRDX6 gene on the biological behavior of cervical squamous cancer cells.

Methods: An immunofluorescence assay was applied to evaluate the expression difference of PRDX6 between cervical cancer tissue and normal cervical tissue samples. A lentivirus was used to upregulate and downregulate PRDX6 expression in SiHa cells. Furthermore, the role of PRDX6 on cell proliferation, apoptosis, migration and invasion was evaluated. Additionally, the effect of PRDX6 on the progression of the cervical cancer was investigated via a xenograft model in BALB/c nude mice that either overexpressed or underexpressed PRDX6.

Results: The expression of PRDX6 was generally increased in cervical cancer tissues. Furthermore, the overexpression of PRDX6 stimulated the proliferation, migration and invasion of cervical squamous cancer cells, and suppressed cell apoptosis. The opposite results were also obtained after successful knockdown of PRDX6. In addition, the overexpression of PRDX6 significantly promoted the growth of cervical carcinoma in vivo.

Conclusions: PRDX6 promoted the proliferation, migration and invasion, and inhibited apoptosis in cervical cancer cells, indicating that PRDX6 is an important promoter of cervical cancer tumorigenicity.