ArticleOncology letters2023
Immunohistochemical profiling of the tumour microenvironment in borderline and malignant ovarian tumours in young women.
Article in Oncology letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- The usefulness of the follicle-preserving sign in differentiating between benign, borderline, and malignant ovarian tumors on magnetic resonance imaging.Japanese journal of radiology · 2026Article
- Profiling of Tumour-Infiltrating Lymphocytes and Tumour-Associated Macrophages in Ovarian Epithelial Cancer-Relation to Tumour Characteristics and Impact on Prognosis.International journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer is a major cause of cancer-related deaths in women. Our previous study highlighted the interaction between cancer cells and the host immune response in solid cancers. The present study aimed to analyse the proportion, density and distribution of T and B lymphocytes within the tumour and surrounding stroma, and their prognostic significance in young women with borderline and malignant ovarian surface epithelial tumours. Full clinicopathological and outcome data were collected for 57 women aged <50 years diagnosed between January 2010 and December 2015. Representative tumour sections were stained for CD3 (T cells) and CD20 (B cells) and tumour-infiltrating lymphocytes (TILs) were scored following the TILs Working Group Recommendations and described as stromal, intra-tumoural, lymphoid aggregates and touching lymphocytes. Data were statistically analysed and the association with clinicopathological variables was assessed. The median age was 41 years and the most common histological type was serous carcinoma (n=21). The risk of malignancy index was a significant predictor of ovarian cancer diagnosis (P<0.05). A total of 15 out of 34 patients with cancer died. There was significantly greater stromal infiltration of CD3 and CD20 TILs (P=0.01 and P=0.03, respectively) and higher intratumoral CD20 expression in ovarian epithelial cancers compared with borderline tumours. The highest CD3 stroma count and density were observed in serous carcinoma, which also exhibited the highest numbers of CD3 and CD20 aggregates. There was no statistically significant difference between touching lymphocytes and tumour histological subtype. There was no significant association between TIL expression and patient survival. The count, distribution and density of T and B lymphocytes in ovarian tumours varied depending on tumour type and invasiveness. Their topographic distribution within the tumour and surrounding stroma did not impact prognosis in young women with ovarian cancer. TIL analysis in an older age group of women with ovarian tumours is ongoing to determine its potential prognostic significance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.