Mengjie Chen

Distribution and maturity of tertiary lymphoid structures predict recurrence-free survival in cervical cancer

Reliable biomarkers are needed to predict outcomes in patients with cervical cancer treated with immune checkpoint inhibitors. This study aimed to develop a novel immune classification system based on tertiary lymphoid structure maturation to stratify prognosis and PD-1 inhibitor response. Surgical specimens from 451 patients with cervical cancer were analyzed to evaluate tertiary lymphoid structure spatial distribution (tumor region vs invasive margin) and maturity. Using machine learning, 4 parameters-tumor region score, invasive margin score, and tertiary lymphoid structure maturity in both regions-were integrated to establish an Immune Score-based classification (immune class I, immune class II, and immune class III). The model was validated in an external cohort of 58 PD-1 inhibitor-treated patients and compared with the International Federation of Gynecology and Obstetrics staging and combined positive score. Tertiary lymphoid structure positivity was more frequent in the invasive margin (58.2%) than in the tumor region (44.6%). All 4 tertiary lymphoid structure parameters independently predicted recurrence-free survival. The immune classification categorized patients into 3 groups with distinct 5-year recurrence-free survival rates (immune class I: 52.4%; immune class II: 78.1%; immune class III: 91.3%), outperforming International Federation of Gynecology and Obstetrics staging. In the PD-1 inhibitor cohort, higher immune class correlated with improved objective response rates (immune class I: 26.3%; immune class II: 56.3%; immune class III: 87.5%) and showed better predictive accuracy than the combined positive score. Immune class remained the only independent prognostic factor across all patient cohorts. This first tertiary lymphoid structure-based immune classification system effectively stratifies recurrence-free survival and PD-1 inhibitor response in cervical cancer, surpassing conventional staging methods. It underscores the clinical relevance of tertiary lymphoid structure organization and maturation, providing a practical tool for personalizing immunotherapy strategies.

Establishment of multifactor predictive models for the occurrence and progression of cervical intraepithelial neoplasia

Abstract Background To study the risk factors involved in the occurrence and progression of cervical intraepithelial neoplasia (CIN) and to establish predictive models. Methods Genemania was used to build a gene network. Then, the core gene-related pathways associated with the occurrence and progression of CIN were screened in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) experiments were performed to verify the differential expression of the identified genes in different tissues. R language was used for predictive model establishment. Results A total of 10 genes were investigated in this study. A total of 30 cases of cervical squamous cell cancer (SCC), 52 cases of CIN and 38 cases of normal cervix were enrolled. Compared to CIN cases, the age of patients in the SCC group was older, the number of parities was greater, and the percentage of patients diagnosed with CINII+ by TCT was higher. The expression of TGFBR2, CSKN1A1, PRKCI and CTBP2 was significantly higher in the SCC groups. Compared to patients with normal cervix tissue, the percentage of patients who were HPV positive and were diagnosed with CINII+ by TCT was significantly higher. FOXO1 expression was significantly higher in CIN tissue, but TGFBR2 and CTBP2 expression was significantly lower in CIN tissue. The significantly different genes and clinical factors were included in the models. Conclusions Combination of clinical and significant genes to establish the random forest models can provide references to predict the occurrence and progression of CIN.

A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause.

The fallopian tube undergoes extensive molecular changes during the menstrual cycle and menopause. We use single-cell RNA and ATAC sequencing to construct a comprehensive cell atlas of healthy human fallopian tubes during the menstrual cycle and menopause. Our scRNA-seq comparison of 85,107 pre- and 46,111 post-menopausal fallopian tube cells reveals substantial shifts in cell type frequencies, gene expression, transcription factor activity, and cell-to-cell communications during menopause and menstrual cycle. Menstrual cycle dependent hormonal changes regulate distinct molecular states in fallopian tube secretory epithelial cells. Postmenopausal fallopian tubes show high chromatin accessibility in transcription factors associated with aging such as Jun, Fos, and BACH1/2, while hormone receptors were generally downregulated, a small proportion of secretory epithelial cells had high expression of ESR2, IGF1R, and LEPR. While a pre-menopausal secretory epithelial gene cluster is enriched in the immunoreactive molecular subtype, a subset of genes expressed in post-menopausal secretory epithelial cells show enrichment in the mesenchymal molecular type of high-grade serous ovarian cancer.