Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors.

TitleSpatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict clinical benefit for immune checkpoint inhibitors.
Publication TypeJournal Article
Year of Publication2022
AuthorsWang X, Barrera C, Bera K, Viswanathan VSankar, Azarianpour-Esfahani S, Koyuncu C, Velu P, Feldman MD, Yang M, Fu P, Schalper KA, Mahdi H, Lu C, Velcheti V, Madabhushi A
JournalSci Adv
Volume8
Issue22
Paginationeabn3966
Date Published2022 Jun 03
ISSN2375-2548
Abstract

Immune checkpoint inhibitors (ICIs) show prominent clinical activity across multiple advanced tumors. However, less than half of patients respond even after molecule-based selection. Thus, improved biomarkers are required. In this study, we use an image analysis to capture morphologic attributes relating to the spatial interaction and architecture of tumor cells and tumor-infiltrating lymphocytes (TILs) from digitized H&E images. We evaluate the association of image features with progression-free (PFS) and overall survival in non-small cell lung cancer (NSCLC) (N = 187) and gynecological cancer (N = 39) patients treated with ICIs. We demonstrated that the classifier trained with NSCLC alone was associated with PFS in independent NSCLC cohorts and also in gynecological cancer. The classifier was also associated with clinical outcome independent of clinical factors. Moreover, the classifier was associated with PFS even with low PD-L1 expression. These findings suggest that image analysis can be used to predict clinical end points in patients receiving ICI.

DOI10.1126/sciadv.abn3966
Alternate JournalSci Adv
PubMed ID35648850
PubMed Central IDPMC9159577
Grant ListUL1 TR001863 / TR / NCATS NIH HHS / United States
Related Faculty: 
Priya Velu, M.D., Ph.D.

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