ArticleIn vivo (Athens, Greece)
PD-L1 and PD-1 Expression in Early Stage Uterine Endometrioid Carcinoma.
Article in In vivo (Athens, Greece). 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
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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.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Impact of PD-L1 Expression on the Overall Survival of Patients With Non-small Cell Lung Cancer Treated With Single-agent Pembrolizumab.In vivo (Athens, Greece)Article
- Immune Network Construction and Prognostic Evaluation of Checkpoint Genes in Endometrial Cancer Using STRING, MCODE, and GEPIA2.Cancer diagnosis & prognosisArticle
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimImmune checkpoint inhibitors (ICI) and tumor-infiltrating lymphocytes (TILs) for cancer treatment in clinical oncology have revolutionized patient care. However, no gold standard exists for the criteria of analytical validity of TILs of different types of cancer. MATERIALS AND
methodsClinicopathological data from 60 patients with endometrioid carcinoma (EC) who had undergone surgical treatment at the Gyeongsang National University Hospital between January 2002 and December 2009, were investigated. The programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PDL1) expression levels were characterized by immunohistochemical staining patterns, and the interpretations derived from machine learning morphometric analysis (Genie) and the pathologists' assessments were compared. In solid tumors, pathologists assessed the proportion of positive cells in each core of the tissue microarray. For Genie, the proportion of positive cells in the entire core and the number of positive cells per 1 mm
resultsBoth the pathologists and Genie identified the same trend in association with tumor size, with significant differences (p=0.026, p=0.033). Genie expression showed a significant association with PD1 expression, and pathologists identified a significant association with PDL1 expression in immune cells.
conclusionThe PD1 expression levels identified in immune cells of EC specimens were similar between the pathologists and Genie, suggesting that there is little resistance to the introduction of morphometric analysis. To our knowledge, this is the first study to introduce and validate machine learning as an integrated method for predicting prognosis and treatment based on PD1 expression in EC tumor microenvironments.
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