A novel non-invasive mRNA-lncRNA biomarker panel for accurate prediction of cervical squamous cell carcinoma and adenocarcinoma

Q: What diagnostic model was developed in the study?

The study refined a novel mRNA-lncRNA-based panel (SMC1B/CELSR3/FEZF1-AS1/LINC01305) using logistic regression and ROC analysis.

Q: How was the biomarker panel validated?

It was validated in multiple phases: tissue-based training and validation sets and an additional blood-based validation cohort to assess diagnostic performance.

Q: What were the reported performance metrics of the panel?

The panel showed significant discrimination for both SCC and ADC tissues with strong AUC values in training and independent validation, and it also produced an AUC value for separating blood-based groups including HSIL and cervical cancer.

Sep 23, 2026

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Squamous cell carcinoma and adenocarcinoma are major cervical cancer histological subtypes. A study used RNA-seq data from cervical SCC, cervical ADC, and normal cervix, followed by multi-phase validation across clinical tissue cohorts and independent patient sets. Differentially expressed mRNAs and lncRNAs were refined into an mRNA-lncRNA diagnostic panel using qRT-PCR and ROC analyses, supported by logistic regression. The panel distinguished SCC/ADC patients and also separated precancerous lesions and cervical cancer from controls in a blood-based validation set.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Abstract

Introduction

Results

Discussion

Methods

Funding

Conflict of Interest

Data Availability

Author Contributions

37TH ANNUAL CONFERENCE OF THE INTERNATIONAL PAPILLOMAVIRUS SOCIETY Research toward the global elimination of HPV-related diseases and cancers OCTOBER23-26, 2025 | BANGKOK, THAILAND DON’T MISS THESE IMPORTANT DATES ENJOY AN EXCLUSIVE 10% DISCOUNT [ipvconference.org | \#IPVS2025](ipvconference.org | #IPVS2025) J Gynecol Oncol. 2025 Sep;36(5):e81 [https://doi.org/10.3802/jgo.2025.36.e81](https://doi.org/10.3802/jgo.2025.36.e81)[ ](https://doi.org/10.3802/jgo.2025.36.e81)pISSN 2005-0380·eISSN 2005-0399 Original Article Received: Oct 9, 2024 Revised: Dec 15, 2024 Accepted: Feb 4, 2025 Published online: Mar 4, 2025 Correspondence to Junfen Xu Department of Gynecologic Oncology, Women’s Hospital, Zhejiang University School of Medicine; Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China. [Email: xjfzu@zju.edu.cn](Email: xjfzu@zju.edu.cn) *Yixuan Cen, Mengyan Tu and Yanan Zhang contributed equally to this work. © 2025. Asian Society of Gynecologic Oncology, Korean Society of Gynecologic Oncology, and Japan Society of Gynecologic Oncology This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ([https://](https://)[ ](https://)[creativecommons.org/licenses/by-nc/4.0/](creativecommons.org/licenses/by-nc/4.0/)) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ORCID iDs Yixuan Cen [https://orcid.org/0000-0002-2185-545X](https://orcid.org/0000-0002-2185-545X)Mengyan Tu [https://orcid.org/0000-0002-7185-0024](https://orcid.org/0000-0002-7185-0024)[ ](https://orcid.org/0000-0002-7185-0024)Yanan Zhang [https://orcid.org/0000-0002-5548-989X](https://orcid.org/0000-0002-5548-989X) A novel non-invasive mRNA-lncRNA biomarker panel for accurate prediction of cervical squamous cell carcinoma and adenocarcinoma Yixuan Cen ,1, 2,* Mengyan Tu ,2,* Yanan Zhang ,2,3,* Yan Ren ,2 Junfen Xu 1,2 1Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China 2Department of Gynecologic Oncology, Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China 3Department of Obstetrics and Gynecology Peking University People’s Hospital, Beijing, China ABSTRACT Squamous cell carcinoma (SCC) and adenocarcinoma (ADC) represent predominant histological subtypes of cervical cancer. To improve screening efficacy, we leveraged RNA sequencing data from 4 cervical SCC samples, 4 cervical ADC samples, and 8 normal cervix samples and conducted a comprehensive mRNA and long noncoding RNA (lncRNA) profiling analysis followed with a multi-phase study comprising 556 samples. Validating the RNA sequencing data in a clinical sample set comprising 45 normal cervix tissues, 45 SCC tissues, and 45 ADC tissues, we identified 9 mRNAs (SMC1B, OTX1, GRP, CELSR3, HOXC6, ITGB6, WDR62, SEPT3, and KLHL34) and 4 lncRNAs (FEZF1-AS1, LINC01305, LINC00857, and LINC00673) differentially expressed in both SCC and ADC samples. Utilizing quantitative reverse transcription polymerase chain reaction analysis and receiver operating characteristic (ROC) curve analysis in a training set (45 normal, 126 SCC, and 82 ADC tissues), we refined a novel mRNA-lncRNA-based panel (SMC1B/CELSR3/FEZF1-AS1/LINC01305). Employing logistic regression model and ROC analysis, this panel exhibited significant distinctions and promising area under the curve (AUC) values in both SCC (AUC=0.9520, p<0.0001) and ADC (AUC=0.9748, p<0.0001) tissues. Subsequent validation in an independent set (11 normal, 32 SCC, and 20 ADC tissues) demonstrated its diagnostic accuracy in both SCC (AUC=0.9659, p<0.0001) and ADC (AUC=0.9636, p<0.0001) patients. Notably, this tissue-based biomarker panel ro

FAQs

What diagnostic model was developed in the study?

The study refined a novel mRNA-lncRNA-based panel (SMC1B/CELSR3/FEZF1-AS1/LINC01305) using logistic regression and ROC analysis.

How was the biomarker panel validated?

It was validated in multiple phases: tissue-based training and validation sets and an additional blood-based validation cohort to assess diagnostic performance.

What were the reported performance metrics of the panel?

The panel showed significant discrimination for both SCC and ADC tissues with strong AUC values in training and independent validation, and it also produced an AUC value for separating blood-based groups including HSIL and cervical cancer.

Sep 23, 2026

Uploaded by McGucket