1.A novel non-invasive mRNA-lncRNA biomarker panel for accurate prediction of cervical squamous cell carcinoma and adenocarcinoma
Yixuan CEN ; Mengyan TU ; Yanan ZHANG ; Yan REN ; Junfen XU
Journal of Gynecologic Oncology 2025;36(5):e81-
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 robustly discriminated precancerous lesion and cervical cancer patients from nondisease controls in a blood-based validation set (30 normal, 25 HSIL and 50 cervical cancer) with an AUC value of 0.9320. This study presents a non-invasive, efficient diagnostic panel for cervical cancer screening.
2.Single-cell transcriptomics reveals tumor landscape in ovarian carcinosarcoma
Journal of Zhejiang University. Science. B 2024;25(8):686-699,中插1-中插4
Objective:The present study used single-cell RNA sequencing(scRNA-seq)to characterize the cellular composition of ovarian carcinosarcoma(OCS)and identify its molecular characteristics.Methods:scRNA-seq was performed in resected primary OCS for an in-depth analysis of tumor cells and the tumor microenvironment.Immunohistochemistry staining was used for validation.The scRNA-seq data of OCS were compared with those of high-grade serous ovarian carcinoma(HGSOC)tumors and other OCS tumors.Results:Both malignant epithelial and malignant mesenchymal cells were observed in the OCS patient of this study.We identified four epithelial cell subclusters with different biological roles.Among them,epithelial subcluster 4 presented high levels of breast cancer type 1 susceptibility protein homolog(BRCA1)and DNA topoisomerase 2-α(TOP2A)expression and was related to drug resistance and cell cycle.We analyzed the interaction between epithelial and mesenchymal cells and found that fibroblast growth factor(FGF)and pleiotrophin(PTN)signalings were the main pathways contributing to communication between these cells.Moreover,we compared the malignant epithelial and mesenchymal cells of this OCS tumor with our previous published HGSOC scRNA-seq data and OCS data.All the epithelial subclusters in the OCS tumor could be found in the HGSOC samples.Notably,the mesenchymal subcluster C14 exhibited specific expression patterns in the OCS tumor,characterized by elevated expression of cytochrome P450 family 24 subfamily A member 1(CYP24A1),collagen type XXIII α1 chain(COL23A1),cholecystokinin(CCK),bone morphogenetic protein 7(BMP7),PTN,Wnt inhibitory factor 1(WIF1),and insulin-like growth factor 2(IGF2).Moreover,this subcluster showed distinct characteristics when compared with both another previously published OCS tumor and normal ovarian tissue.Conclusions:This study provides the single-cell transcriptomics signature of human OCS,which constitutes a new resource for elucidating OCS diversity.

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