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Proceedings Paper

Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores
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Paper Abstract

Lung adenocarcinoma (LUAD), the most common type of lung cancer, has an average 5-year survival rate of 15%. In LUAD, interaction between tumor and immune cells has been shown to be highly associated with the likelihood of disease progression and metastases. We have previously demonstrated the association between spatial architecture and arrangement of tumor-infiltrating lymphocytes (TILs) with likelihood of recurrence in early stage NSCLC. Recently, gene set enrichment analysis-derived immune scores have been found to be prognostic of outcome. However, this requires transcriptomics techniques as a precursor, which involves mechanical disruption of cells and tissues. In this work (N = 170), we extracted graph-based histomorphometric features on segmented nuclei from digitized H and E biopsy images and then performed principal component analysis (PCA) to select the most representative tiles from each patient. We then identified TILs and quantitative histomorphometric attributes of different nuclei groups (all-nuclei, TILs, non-TILs) prognostic of overall patient survival (OS) and further investigated their associations with immune scores and biological pathways implicated immune response using gene-set enrichment analysis (GSEA). We found TIL-compactness (a set of TIL density features) derived risk scores were prognostic of OS (Hazard Ratio (HR) = 3.26, p = 0.012, C-index = 0.634). The median immune score (IS) in the cohort was used as a threshold to divide the cases into low and high IS expression groups. The TIL compactness measures prognostic of OS were also statistically significantly correlated with the IS and biological pathways related to immune response (Immune System Process, Immune Response, Adaptive Immune Response, and Humoral Immune Response Mediated by Circulating Immunoglobulin).

Paper Details

Date Published: 16 March 2020
PDF: 9 pages
Proc. SPIE 11320, Medical Imaging 2020: Digital Pathology, 1132003 (16 March 2020); doi: 10.1117/12.2549588
Show Author Affiliations
Ruiwen Ding, Case Western Reserve Univ. (United States)
Prateek Prasanna, The State Univ. of New York at Stony Brook, (United States)
Germán Corredor, Case Western Reserve Univ. (United States)
Cheng Lu, Case Western Reserve Univ. (United States)
Priya Velu, Weill Cornell Medical College (United States)
Khoi Le, Case Western Reserve Univ. (United States)
Patrick Leo, Case Western Reserve Univ. (United States)
Niha Beig, Case Western Reserve Univ. (United States)
Vamsidhar Velcheti, New York Univ. (United States)
David Rimm, Yale Univ. (United States)
Kurt Schalper, Yale Univ. (United States)
Anant Madabhushi, Case Western Reserve Univ. (United States)
Louis Stokes Cleveland Veterans Administration Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 11320:
Medical Imaging 2020: Digital Pathology
John E. Tomaszewski; Aaron D. Ward, Editor(s)

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