Fraction and Spatial Organization of Tumor-Infiltrating Lymphocytes Correlating with Bladder Cancer Patient Survival

AbstractRecent studies based on deep learning on pathology images have shown the potential prognostic role of Tumor-infiltrating lymphocytes (TILs) in many cancer types. In general, most of these studies focused on detecting, quantifying and identifying TILs and spatial organization in entire whole slide images (WSIs) including both non-cancer and cancer regions. In this work, we hypothesize that TILs present in cancer regions not entire WSIs could have prognostic values. Here we present an automatic technique based on convolutional neural networks (CNN) that detects both cancer and TILs regions, and explores fraction and spatial organization of TILs in the detected cancer region from WSIs. A novel set of quantitative histological image features reflecting TILs fraction and spatial organization is extracted and used to stratify patients with distinct survival outcomes. In experiments using 277 different patient pathology slides selected from The Cancer Genome Atlas (TCGA) bladder cancer cohort, we show that bladder cancer patient survival is significantly correlated with our designed TIL-related image features, with a log-rank test p value below 0.05. Our method is extensible to histopathology images of other organs for predicting patient survival via TIL analysis.

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Spatial heterogeneity and organization of tumor mutation burden and immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer

10.1101/554527 ◽

2019 ◽

Cited By ~ 5

Author(s):

Hongming Xu ◽

Sunho Park ◽

Jean René Clemenceau ◽

Jinhwan Choi ◽

Nathan Radakovich ◽

...

Keyword(s):

Bladder Cancer ◽

Spatial Heterogeneity ◽

Tumor Cells ◽

Tumor Infiltrating Lymphocytes ◽

The Cancer Genome Atlas ◽

Mutation Burden ◽

Prognostic Utility ◽

Cancer Genome Atlas ◽

Infiltrating Lymphocytes ◽

Whole Slide Images

AbstractHigh-TMB (TMB-H) could result in an increased number of neoepitopes from somatic mutations expressed by a patient’s own tumor cell which can be recognized and targeted by neighboring tumor-infiltrating lymphocytes (TILs). Deeper understanding of spatial heterogeneity and organization of tumor cells and their neighboring immune infiltrates within tumors could provide new insights into tumor progression and treatment response. Here we developed and applied computational approaches using digital whole slide images (WSIs) to investigate spatial heterogeneity and organization of regions harboring TMB-H tumor cells and TILs within tumors, and its prognostic utility. In experiments using WSIs from The Cancer Genome Atlas bladder cancer (BLCA), our findings show that WSI-based approaches can reliably predict patient-level TMB status and delineate spatial TMB heterogeneity and co-organization with TILs. TMB-H patients with low spatial heterogeneity enriched with high TILs show improved overall survival indicating a prognostic role of spatial TMB and TILs information in BLCA.

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Optimization of hidden layer in a neural network used to predict bladder-cancer patient-survival

Signal Processing Algorithms, Architectures, Arrangements, and Applications SPA 2007 ◽

10.1109/spa.2007.5903302 ◽

2007 ◽

Cited By ~ 1

Author(s):

Marta Kolasa ◽

Wojciech Jozwicki ◽

Ryszard Wojtyna ◽

Piotr Jarzemski

Keyword(s):

Neural Network ◽

Bladder Cancer ◽

Cancer Patient ◽

Patient Survival ◽

Bladder Cancer Patient ◽

Hidden Layer

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Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data

JCO Clinical Cancer Informatics ◽

10.1200/cci.19.00126 ◽

2020 ◽

pp. 480-490 ◽

Cited By ~ 2

Author(s):

Zixiao Lu ◽

Siwen Xu ◽

Wei Shao ◽

Yi Wu ◽

Jie Zhang ◽

...

Keyword(s):

Breast Cancer ◽

Strong Association ◽

Tumor Infiltrating Lymphocytes ◽

Genetic Alterations ◽

Image Features ◽

Cancer Immunology ◽

The Cancer Genome Atlas ◽

Breast Cancer Subtypes ◽

Cancer Subtypes ◽

Infiltrating Lymphocytes

PURPOSE Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers. However, fully automatic assessment of TILs on WSIs currently remains a great challenge because of the heterogeneity and large size of WSIs. We present an automatic pipeline based on a cascade-training U-net to generate high-resolution TIL maps on WSIs. METHODS We present global cell-level TIL maps and 43 quantitative TIL spatial image features for 1,000 WSIs of The Cancer Genome Atlas patients with breast cancer. For more specific analysis, all the patients were divided into three subtypes, namely, estrogen receptor (ER)–positive, ER-negative, and triple-negative groups. The associations between TIL scores and gene expression and somatic mutation were examined separately in three breast cancer subtypes. Both univariate and multivariate survival analyses were performed on 43 TIL image features to examine the prognostic value of TIL spatial patterns in different breast cancer subtypes. RESULTS The TIL score was in strong association with immune response pathway and genes (eg, programmed death-1 and CLTA4). Different breast cancer subtypes showed TIL score in association with mutations from different genes suggesting that different genetic alterations may lead to similar phenotypes. Spatial TIL features that represent density and distribution of TIL clusters were important indicators of the patient outcomes. CONCLUSION Our pipeline can facilitate computational pathology-based discovery in cancer immunology and research on immunotherapy. Our analysis results are available for the research community to generate new hypotheses and insights on breast cancer immunology and development.

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Black/white differences in bladder cancer patient survival

Journal of Chronic Diseases ◽

10.1016/0021-9681(87)90097-x ◽

1987 ◽

Vol 40 (1) ◽

pp. 65-73 ◽

Cited By ~ 21

Author(s):

Benjamin F. Hankey ◽

Max H. Myers

Keyword(s):

Bladder Cancer ◽

Cancer Patient ◽

Patient Survival ◽

Bladder Cancer Patient

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Expression of Immune Checkpoint Regulators IDO, VISTA, LAG3, and TIM3 in Resected Pancreatic Ductal Adenocarcinoma

Cancers ◽

10.3390/cancers13112689 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2689

Author(s):

Felix Popp ◽

Ingracia Capino ◽

Joana Bartels ◽

Alexander Damanakis ◽

Jiahui Li ◽

...

Keyword(s):

Pancreatic Cancer ◽

Immune Checkpoint ◽

Patient Survival ◽

Checkpoint Inhibitors ◽

Tumor Infiltrating Lymphocytes ◽

Ductal Adenocarcinoma ◽

Lymph Node Status ◽

Clinicopathologic Parameters ◽

Survival Differences ◽

Infiltrating Lymphocytes

Pancreatic cancer features elaborate mechanisms of immune evasion. The potential of new immune molecules was explored to restore the antitumor immune response. If these immune molecules are associated with poor survival, specific drugs could take effect. Here, we analyze the expression of VISTA, LAG3, IDO, and TIM3 on tumor-infiltrating lymphocytes (TILs) and its impact on patient survival. We analyzed 153 pancreatic cancer patients from the prospectively managed database of the multicentered PANCALYZE study. Immunohistochemistry on a tissue microarray assessed VISTA, LAG3, IDO, and TIM3 expression of TILs from the patients undergoing primary resection. Complementarily, we analyzed publicly available transcriptomic data (n = 903). Successful completion of chemotherapy, and lymph node status were independent predictors of survival in the multivariate analysis of the clinicopathologic parameters. Fifteen tumors were exclusively VISTA-positive, thirteen tumors expressed VISTA together with TIM3, and ten tumors expressed VISTA together with IDO. Patients featuring tumors with high numbers of IDO-positive TILs had better patient survival (p = 0.037). VISTA, LAG3, and TIM3 expression did not correlate with survival. The analysis of publicly available data did not show survival differences. Tumors rarely co-express more than two immune molecules at the same time, and VISTA is most frequently co-expressed. Although IDO generally inhibits T-cell proliferation, a high expression of IDO was associated with improved survival. We expect immune checkpoint inhibitors against VISTA, LAG3, and TIM3 to be inefficient in a clinical application.

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Predicted CD4+ T cell infiltration levels could indicate better overall survival in sarcoma patients

Journal of International Medical Research ◽

10.1177/0300060520981539 ◽

2021 ◽

Vol 49 (1) ◽

pp. 030006052098153

Author(s):

Qing Bi ◽

Yang Liu ◽

Tao Yuan ◽

Huizhen Wang ◽

Bin Li ◽

...

Keyword(s):

Overall Survival ◽

T Cell ◽

Survival Data ◽

Tumor Infiltrating Lymphocytes ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

T Cell Infiltration ◽

Whole Exome ◽

Cancer Genome Atlas ◽

Infiltrating Lymphocytes

Objective The role of tumor-infiltrating lymphocytes (TILs) has not yet been characterized in sarcomas. The aim of this bioinformatics study was to explore the effect of TILs on sarcoma survival and genome alterations. Methods Whole-exome sequencing, transcriptome sequencing, and survival data of sarcoma were obtained from The Cancer Genome Atlas. Immune infiltration scores were calculated using the Tumor Immune Estimation Resource. Potential associations between abundance of infiltrating TILs and survival or genome alterations were examined. Results Levels of CD4+ T cell infiltration were associated with overall survival of patients with pan-sarcomas, and higher CD4+ T cell infiltration levels were associated with better survival. Somatic copy number alterations, rather than mutations, were found to correlate with CD4+ T cell infiltration levels. Conclusions This data mining study indicated that CD4+ T cell infiltration levels predicted from RNA sequencing could predict sarcoma prognosis, and higher levels of CD4+ T cells infiltration indicated a better chance of survival.

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