Background: Ovarian cancers (OC) and cervical cancers (CC) have poor survival rates. Tumor-infiltrating lymphocytes (TILs) play a pivotal role in prognosis, but shared immune mechanisms remain elusive.
Methods: We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore immune regulation in OC and CC, focusing on the PI3K/AKT pathway and FLT3 as key modulators. Seurat and Harmony were employed for batch correction and dimensionality reduction. FLT3 expression was mapped with spatial data from 10 × Genomics.
Results: FLT3, identified as a regulator through the PI3K/AKT pathway, showed positive correlations with T cells, NK cells, and B cells. FLT3-high regions exhibited increased immune infiltration, particularly in CC, enhancing survival outcomes.
Conclusion: This study provides the first spatially resolved evidence of FLT3's immune-modulatory role in OC and CC, positioning it as a promising immunotherapeutic target. FLT3-targeted strategies may offer new options for patients resistant to conventional therapies.
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http://dx.doi.org/10.1186/s13048-025-01592-8 | DOI Listing |
J Ovarian Res
January 2025
Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, #128 Shenyang Road, Shanghai, 200090, People's Republic of China.
Background: Ovarian cancers (OC) and cervical cancers (CC) have poor survival rates. Tumor-infiltrating lymphocytes (TILs) play a pivotal role in prognosis, but shared immune mechanisms remain elusive.
Methods: We integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore immune regulation in OC and CC, focusing on the PI3K/AKT pathway and FLT3 as key modulators.
Sci Rep
January 2025
Department of Biomedical Engineering, School of Life Science and Technology, Changchun University of Science and Technology, Changchun, 130022, China.
The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical cancer patients. Addressing the issue of low accuracy in cervical cell classification, a deep convolutional neural network A2SDNet121 is proposed. A2SDNet121 takes DenseNet121 as the backbone network.
View Article and Find Full Text PDFBMJ Open
January 2025
University Research Clinic for Cancer Screening, Randers Regional Hospital, Randers, Denmark.
Objective: This study explored and compared stakeholder perspectives on enhancements to cervical cancer screening for vulnerable women across seven European countries.
Design: In a series of Collaborative User Boards, stakeholders were invited to collaborate on identifying facilitators to improve cervical cancer screening.
Setting: This study was part of the CBIG-SCREEN project which is funded by the European Union and targets disparities in cervical cancer screening for vulnerable women (www.
Am J Obstet Gynecol
January 2025
Division of Gynecologic Oncology, Mount Sinai Medical Center, Miami Beach, Florida, USA.
Background: Black women and other minorities have higher age adjusted incidence risk for cervical and endometrial cancer than White women. However, the extent of racial and ethnic disparities in clinical trial enrollment among studies performed mainly in North America and Europe for gynecologic malignancy is unknown.
Objective: This study analyzed enrollment rates by race/ethnicity in trials that led to Food and Drug Administration (FDA) approvals for gynecological cancers from 2010 to 2024.
Viruses
December 2024
Department of Rehabilitation and Regenerative Medicine, College of Physicians and Surgeons, Columbia University, HHSC-1518, 701 W. 168th Street, New York, NY 10032, USA.
This study explores the effects of plant compounds on human papillomavirus (HPV)-induced W12 cervical precancer cells and bioelectric signaling. The aim is to identify effective phytochemicals, both individually and in combination, that can prevent and treat HPV infection and HPV associated cervical cancer. Phytochemicals were tested using growth inhibition, combination, gene expression, RT PCR, and molecular docking assays.
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