Objective: Serous tubal intra-epithelial carcinoma (STIC) lesions are thought to be precursors to high-grade serous ovarian cancer (HGSOC), but HGSOC is not always accompanied by STIC. Our study was designed to determine if there are global visual and subvisual microenvironmental differences between fallopian tubes with and without STIC lesions.
Methods: Computational image analyses were used to identify potential morphometric and topologic differences in stromal and epithelial cells in samples from three age-matched groups of fallopian tubes. The Benign group comprised normal fallopian tubes from women with benign conditions while the STIC and NoSTIC groups consisted of fallopian tubes from women with HGSOC, with and without STIC lesions, respectively. For the morphometric feature extraction and analysis of the stromal architecture, the image tiles in the STIC group were further divided into the stroma away from the STIC (AwaySTIC) and the stroma near the STIC (NearSTIC). QuPath software was used to identify and quantitate secretory and ciliated epithelial cells. A secretory cell expansion (SCE) or a ciliated cell expansion (CCE) was defined as a monolayered contiguous run of >10 secretory or ciliated cells uninterrupted by the other cell type.
Results: Image analyses of the tubal stroma revealed gradual architectural differences from the Benign to NoSTIC to AwaySTIC to NearSTIC groups. In the epithelial topology analysis, the relative number of SCE and the average number of cells within SCE were higher in the STIC group than in the Benign and NoSTIC groups. In addition, aging was associated with an increased relative number of SCE and a decreased relative number of CCE. ROC analysis determined that an average of 15 cells within SCE was the optimal cutoff value indicating the presence of a STIC lesion in the tubal epithelium.
Conclusions: Our findings suggest that global stromal alterations and age-associated reorganization of tubal secretory and ciliated cells are associated with STIC lesions. Further studies will need to determine if these alterations precede STIC lesions and provide permissible conditions for the formation of STIC.
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http://dx.doi.org/10.3389/fonc.2022.853755 | DOI Listing |
Cancer Discov
December 2024
Brigham and Women's Hospital, Boston, MA, United States.
High-Grade Serous Ovarian Cancer (HGSOC) originates from fallopian tube (FT) precursors. However, the molecular changes that occur as precancerous lesions progress to HGSOC are not well understood. To address this, we integrated high-plex imaging and spatial transcriptomics to analyze human tissue samples at different stages of HGSOC development, including p53 signatures, serous tubal intraepithelial carcinomas (STIC), and invasive HGSOC.
View Article and Find Full Text PDFDiagnostics (Basel)
November 2024
Department of Gynecology, Fondazione Policlinico Universitario Campus Bio Medico, Via Alvaro del Portillo 200, 00128 Roma, Italy.
Background: Serous tubal intraepithelial carcinoma (STIC) is an early-stage cancerous lesion found in the fallopian tubes, often at the fimbrial end. It is strongly associated with high-grade serous carcinoma (HGSC), a highly aggressive type of ovarian cancer. STIC is considered a precursor to many HGSC cases, originating in the fallopian tubes.
View Article and Find Full Text PDFCase Rep Obstet Gynecol
October 2024
Department of Obstetrics and Gynecology, Faculty of Medicine, Kyorin University, Tokyo, Japan.
J Pathol Clin Res
November 2024
Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinoma (STIC), the precursor lesion to high-grade serous ovarian carcinoma, found in the fallopian tube. However, the standalone performance of a model is insufficient to determine its value in the diagnostic setting.
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