Computer extracted features related to the spatial arrangement of tumor-infiltrating lymphocytes predict overall survival in epithelial ovarian cancer

2020 ◽  
Author(s):  
Sepideh Azarianpour ◽  
German Corredor ◽  
Kaustav Bera ◽  
Patrick Leo ◽  
Nathaniel Braman ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Epithelial Ovarian Cancer ◽  
Tumor Infiltrating Lymphocytes ◽  
Spatial Arrangement ◽  
Infiltrating Lymphocytes

Combination of tumor multinucleation and spatial arrangement of tumor-infiltrating lymphocytes to predict overall survival in oropharyngeal squamous cell carcinoma: A multisite study.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 6566-6566
Author(s):  
Can Koyuncu ◽  
Germán Corredor ◽  
Cheng Lu ◽  
Paula Toro ◽  
Kaustav Bera ◽  
...  
Keyword(s):  
Overall Survival ◽  
Squamous Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Univariate Analysis ◽  
Tumor Infiltrating Lymphocytes ◽  
Spatial Arrangement ◽  
Risk Scores ◽  
Infiltrating Lymphocytes

6566 Background: Oropharyngeal squamous cell carcinoma patients can have major morbidity from current treatment regimens, necessitating accurate identification of patients with aggressive versus indolent tumors. In this study, we sought to evaluate whether the combination of computer extracted features of tumor cell multinucleation (MN) and spatial interplay of tumor-infiltrating lymphocytes (TILs) is prognostic of overall survival (OS) in OPSCC patients. Methods: OPSCC specimens from 688 patients were retrospectively collected from 3 different sites. 141 patients from site 1 formed the training set (D1) and 322 patients from site 2 and 225 patients from site 3 formed the independent validation cohort (D2, n = 547). A machine learning (ML) model was employed to automatically calculate a Multi-nucleation risk index (MNI), which is the ratio of the number of MN to the number of epithelial cells, to each patient. A separate ML model was also used to capture measurements related to the interplay between TILs and tumor cells (SpaTIL), which were then used to compute a risk score using a Cox regression model. The median value of both the MNIs and the SpaTIL risk scores in D2 were used to identify patients as either low- or high-risk. A definitive label was assigned to each patient by combining the class labels obtained from the MNI and SpaTIL models using a logical AND operation. Results: In D2, the patients with high-risk scores had statistically significantly worse survival in univariate analysis. The univariate analysis yielded an HR = 1.91 (95% CI: 1.25-2.93, p = 0.0027) for D. Multivariate analysis controlling the effect of different clinical variables is shown in the table. Conclusions: We presented a computational pathology approach to prognosticate disease outcome in OPSCC by combining features relating to density of multinucleation and spatial arrangement of TILs and validated the approach on a large multi-site dataset. With additional validation the approach could potentially help identify OPSCC patients who could benefit from de-escalation of therapy. [Table: see text]

scholarly journals Clinical Significance of Tumor Infiltrating Lymphocytes in Association with Hormone Receptor Expression Patterns in Epithelial Ovarian Cancer

2021 ◽  
Vol 22 (11) ◽  
pp. 5714
Author(s):  
Gwan Hee Han ◽  
Ilseon Hwang ◽  
Hanbyoul Cho ◽  
Kris Ylaya ◽  
Jung-A Choi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Signaling Pathways ◽  
Hormone Receptor ◽  
Expression Patterns ◽  
Tumor Infiltrating Lymphocytes ◽  
Receptor Expression ◽  
Dominant Group ◽  
Hormone Receptor Expression ◽  
Infiltrating Lymphocytes

Hormone receptor expression patterns often correlate with infiltration of specific lymphocytes in tumors. Specifically, the presence of specific tumor-infiltrating lymphocytes (TILs) with particular hormone receptor expression is reportedly associated with breast cancer, however, this has not been revealed in epithelial ovarian cancer (EOC). Therefore, we investigated the association between hormone receptor expression and TILs in EOC. Here we found that ERα, AR, and GR expression increased in EOC, while PR was significantly reduced and ERβ expression showed a reduced trend compared to normal epithelium. Cluster analysis indicated poor disease-free survival (DFS) in AR+/GR+/PR+ subgroup (triple dominant group); while the Cox proportional-hazards model highlighted the triple dominant group as an independent prognostic factor for DFS. In addition, significant upregulation of FoxP3+ TILs, PD-1, and PD-L1 was observed in the triple dominant group compared to other groups. NanoString analyses further suggested that tumor necrosis factor (TNF) and/or NF-κB signaling pathways were activated with significant upregulation of RELA, MAP3K5, TNFAIP3, BCL2L1, RIPK1, TRAF2, PARP1, and AKT1 in the triple dominant EOC group. The triple dominant subgroup correlates with poor prognosis in EOC. Moreover, the TNF and/or NF-κB signaling pathways may be responsible for hormone-mediated inhibition of the immune microenvironment.

scholarly journals Higher Numbers of T-Bet+ Tumor-Infiltrating Lymphocytes Associate with Better Survival in Human Epithelial Ovarian Cancer

2017 ◽  
Vol 41 (2) ◽  
pp. 475-483 ◽  
Author(s):  
Yun Xu ◽  
Lujun Chen ◽  
Bin Xu ◽  
Yuqi Xiong ◽  
Min Yang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Flow Cytometry ◽  
Epithelial Ovarian Cancer ◽  
Cancer Patients ◽  
Tumor Infiltrating Lymphocytes ◽  
Lymphoid Cells ◽  
Type I ◽  
Flow Cytometry Analysis ◽  
Cancer Tissues ◽  
Infiltrating Lymphocytes

Background/Aims: T-bet, a member of the T-box family of transcription factors, is a key marker of type I immune response within the tumor microenvironment, and has been previously reported by us to serve as an important prognostic indicator for human gastric cancer patients and a potential biomarker for immunotherapy. In the present study, we aimed to assess the clinical significance and prognostic value of T-bet+ tumor-infiltrating lymphocytes in human epithelial ovarian cancer. Methods: The immunohistochemistry was used to analyze the infiltration density of T-bet+ lymphoid cells in human epithelial ovarian cancer tissues, and the flow cytometry analysis was used to further analyze the presence of T-bet+ tumor-infiltrating lymphocytes subgroups in cancer tissues. Results: Our immunohistochemistry analysis showed increased number of T-bet+ lymphoid cells in the human epithelial ovarian cancer tissues, and the flow cytometry analysis further demonstrated the presence of T-bet+ tumor-infiltrating lymphocytes subgroups including CD4+ , CD8+ T cells and NK cells. In addition, we also observed a significant association of T-bet+ tumor-infiltrating lymphocytes density in the tumor nest of cancer with not only serum CA125 levels but also with distant metastasis. However no association was observed with other characteristics like patients' age, pathological type, FIGO stage, tumor site and tumor size. Furthermore, the survival analysis showed that higher density of T-bet+ tumor-infiltrating lymphocytes both in tumor nest and tumor stroma of cancer tissues was significantly associated with better patient survival. In addition, the density of T-bet+ tumor-infiltrating lymphocytes in tumor nest appeared to be an independent risk factor for predicting patients’ postoperative prognoses. Conclusions: Our data indicated that the key transcription factor T-bet might play an important role in the type I immune cells mediated antitumor response, and the density of T-bet+ lymphocytes in human epithelial ovarian cancer tissues could serve as a prognostic predictor for ovarian cancer patients.

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