TY - JOUR

T1 - Transcriptomic signatures of tumors undergoing T cell attack

AU - Gokuldass, Aishwarya

AU - Schina, Aimilia

AU - Lauss, Martin

AU - Harbst, Katja

AU - Chamberlain, Christopher Aled

AU - Draghi, Arianna

AU - Westergaard, Marie Christine Wulff

AU - Nielsen, Morten

AU - Papp, Krisztian

AU - Sztupinszki, Zsofia

AU - Csabai, Istvan

AU - Svane, Inge Marie

AU - Szallasi, Zoltan

AU - Jönsson, Göran

AU - Donia, Marco

N1 - Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

PY - 2022

Y1 - 2022

N2 - Background: Studying tumor cell–T cell interactions in the tumor microenvironment (TME) can elucidate tumor immune escape mechanisms and help predict responses to cancer immunotherapy. Methods: We selected 14 pairs of highly tumor-reactive tumor-infiltrating lymphocytes (TILs) and autologous short-term cultured cell lines, covering four distinct tumor types, and co-cultured TILs and tumors at sub-lethal ratios in vitro to mimic the interactions occurring in the TME. We extracted gene signatures associated with a tumor-directed T cell attack based on transcriptomic data of tumor cells. Results: An autologous T cell attack induced pronounced transcriptomic changes in the attacked tumor cells, partially independent of IFN-γ signaling. Transcriptomic changes were mostly independent of the tumor histological type and allowed identifying common gene expression changes, including a shared gene set of 55 transcripts influenced by T cell recognition (Tumors undergoing T cell attack, or TuTack, focused gene set). TuTack scores, calculated from tumor biopsies, predicted the clinical outcome after anti-PD-1/anti-PD-L1 therapy in multiple tumor histologies. Notably, the TuTack scores did not correlate to the tumor mutational burden, indicating that these two biomarkers measure distinct biological phenomena. Conclusions: The TuTack scores measure the effects on tumor cells of an anti-tumor immune response and represent a comprehensive method to identify immunologically responsive tumors. Our findings suggest that TuTack may allow patient selection in immunotherapy clinical trials and warrant its application in multimodal biomarker strategies.

AB - Background: Studying tumor cell–T cell interactions in the tumor microenvironment (TME) can elucidate tumor immune escape mechanisms and help predict responses to cancer immunotherapy. Methods: We selected 14 pairs of highly tumor-reactive tumor-infiltrating lymphocytes (TILs) and autologous short-term cultured cell lines, covering four distinct tumor types, and co-cultured TILs and tumors at sub-lethal ratios in vitro to mimic the interactions occurring in the TME. We extracted gene signatures associated with a tumor-directed T cell attack based on transcriptomic data of tumor cells. Results: An autologous T cell attack induced pronounced transcriptomic changes in the attacked tumor cells, partially independent of IFN-γ signaling. Transcriptomic changes were mostly independent of the tumor histological type and allowed identifying common gene expression changes, including a shared gene set of 55 transcripts influenced by T cell recognition (Tumors undergoing T cell attack, or TuTack, focused gene set). TuTack scores, calculated from tumor biopsies, predicted the clinical outcome after anti-PD-1/anti-PD-L1 therapy in multiple tumor histologies. Notably, the TuTack scores did not correlate to the tumor mutational burden, indicating that these two biomarkers measure distinct biological phenomena. Conclusions: The TuTack scores measure the effects on tumor cells of an anti-tumor immune response and represent a comprehensive method to identify immunologically responsive tumors. Our findings suggest that TuTack may allow patient selection in immunotherapy clinical trials and warrant its application in multimodal biomarker strategies.

KW - Adaptive immune resistance

KW - Anti-PD-1

KW - Anti-PD-L1

KW - Immunotherapy biomarkers

KW - Patient selection

KW - Transcriptomics

U2 - 10.1007/s00262-021-03015-1

DO - 10.1007/s00262-021-03015-1

M3 - Journal article

C2 - 34272988

AN - SCOPUS:85110860501

VL - 71

SP - 553

EP - 563

JO - Cancer Immunology, Immunotherapy

JF - Cancer Immunology, Immunotherapy

SN - 0340-7004

IS - 3

ER -