Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

Samuel S. Freeman; Moshe Sade-Feldman; Jaegil Kim; Chip Stewart; Anna L.K. Gonye; Arvind Ravi; Monica B. Arniella; Irena Gushterova; Thomas J. LaSalle; Emily M. Blaum; Keren Yizhak; Dennie T. Frederick; Tatyana Sharova; Ignaty Leshchiner; Liudmila Elagina; Oliver G. Spiro; Dimitri Livitz; Daniel Rosebrock; François Aguet; Jian Carrot-Zhang; Gavin Ha; Ziao Lin; Jonathan H. Chen; Michal Barzily-Rokni; Marc R. Hammond; Hans C. Vitzthum von Eckstaedt; Shauna M. Blackmon; Yunxin J. Jiao; Stacey Gabriel; Donald P. Lawrence; Lyn M. Duncan; Anat O. Stemmer-Rachamimov; Jennifer A. Wargo; Keith T. Flaherty; Ryan J. Sullivan; Genevieve M. Boland; Matthew Meyerson; Gad Getz; Nir Hacohen

doi:10.1016/j.xcrm.2021.100500

Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

Samuel S. Freeman, Moshe Sade-Feldman, Jaegil Kim, Chip Stewart, Anna L.K. Gonye, Arvind Ravi, Monica B. Arniella, Irena Gushterova, Thomas J. LaSalle, Emily M. Blaum, Keren Yizhak, Dennie T. Frederick, Tatyana Sharova, Ignaty Leshchiner, Liudmila Elagina, Oliver G. Spiro, Dimitri Livitz, Daniel Rosebrock, François Aguet, Jian Carrot-ZhangGavin Ha, Ziao Lin, Jonathan H. Chen, Michal Barzily-Rokni, Marc R. Hammond, Hans C. Vitzthum von Eckstaedt, Shauna M. Blackmon, Yunxin J. Jiao, Stacey Gabriel, Donald P. Lawrence, Lyn M. Duncan, Anat O. Stemmer-Rachamimov, Jennifer A. Wargo, Keith T. Flaherty, Ryan J. Sullivan, Genevieve M. Boland, Matthew Meyerson, Gad Getz, Nir Hacohen

Surgical Oncology

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMB^high and TCB^high or BCB^high have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.

Original language	English (US)
Article number	100500
Journal	Cell Reports Medicine
Volume	3
Issue number	2
DOIs	https://doi.org/10.1016/j.xcrm.2021.100500
State	Published - Feb 15 2022

Keywords

T cell receptor
TMB
cancer genomics
cancer immunotherapy
immune checkpoint blockade
integrative model
melanoma
melanoma subtype
tumor mutational burden

ASJC Scopus subject areas

General Biochemistry, Genetics and Molecular Biology
General Medicine

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Freeman, S. S., Sade-Feldman, M., Kim, J., Stewart, C., Gonye, A. L. K., Ravi, A., Arniella, M. B., Gushterova, I., LaSalle, T. J., Blaum, E. M., Yizhak, K., Frederick, D. T., Sharova, T., Leshchiner, I., Elagina, L., Spiro, O. G., Livitz, D., Rosebrock, D., Aguet, F., ... Hacohen, N. (2022). Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma. Cell Reports Medicine, 3(2), Article 100500. https://doi.org/10.1016/j.xcrm.2021.100500

Freeman, SS, Sade-Feldman, M, Kim, J, Stewart, C, Gonye, ALK, Ravi, A, Arniella, MB, Gushterova, I, LaSalle, TJ, Blaum, EM, Yizhak, K, Frederick, DT, Sharova, T, Leshchiner, I, Elagina, L, Spiro, OG, Livitz, D, Rosebrock, D, Aguet, F, Carrot-Zhang, J, Ha, G, Lin, Z, Chen, JH, Barzily-Rokni, M, Hammond, MR, Vitzthum von Eckstaedt, HC, Blackmon, SM, Jiao, YJ, Gabriel, S, Lawrence, DP, Duncan, LM, Stemmer-Rachamimov, AO, Wargo, JA, Flaherty, KT, Sullivan, RJ, Boland, GM, Meyerson, M, Getz, G & Hacohen, N 2022, 'Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma', Cell Reports Medicine, vol. 3, no. 2, 100500. https://doi.org/10.1016/j.xcrm.2021.100500

@article{40048ba9c2c741a791d5eec84ed0e863,

title = "Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma",

abstract = "Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.",

keywords = "T cell receptor, TMB, cancer genomics, cancer immunotherapy, immune checkpoint blockade, integrative model, melanoma, melanoma subtype, tumor mutational burden",

author = "Freeman, {Samuel S.} and Moshe Sade-Feldman and Jaegil Kim and Chip Stewart and Gonye, {Anna L.K.} and Arvind Ravi and Arniella, {Monica B.} and Irena Gushterova and LaSalle, {Thomas J.} and Blaum, {Emily M.} and Keren Yizhak and Frederick, {Dennie T.} and Tatyana Sharova and Ignaty Leshchiner and Liudmila Elagina and Spiro, {Oliver G.} and Dimitri Livitz and Daniel Rosebrock and Fran{\c c}ois Aguet and Jian Carrot-Zhang and Gavin Ha and Ziao Lin and Chen, {Jonathan H.} and Michal Barzily-Rokni and Hammond, {Marc R.} and {Vitzthum von Eckstaedt}, {Hans C.} and Blackmon, {Shauna M.} and Jiao, {Yunxin J.} and Stacey Gabriel and Lawrence, {Donald P.} and Duncan, {Lyn M.} and Stemmer-Rachamimov, {Anat O.} and Wargo, {Jennifer A.} and Flaherty, {Keith T.} and Sullivan, {Ryan J.} and Boland, {Genevieve M.} and Matthew Meyerson and Gad Getz and Nir Hacohen",

note = "Publisher Copyright: {\textcopyright} 2021 The Author(s)",

year = "2022",

month = feb,

day = "15",

doi = "10.1016/j.xcrm.2021.100500",

language = "English (US)",

volume = "3",

journal = "Cell Reports Medicine",

issn = "2666-3791",

publisher = "Cell Press",

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TY - JOUR

T1 - Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

AU - Freeman, Samuel S.

AU - Sade-Feldman, Moshe

AU - Kim, Jaegil

AU - Stewart, Chip

AU - Gonye, Anna L.K.

AU - Ravi, Arvind

AU - Arniella, Monica B.

AU - Gushterova, Irena

AU - LaSalle, Thomas J.

AU - Blaum, Emily M.

AU - Yizhak, Keren

AU - Frederick, Dennie T.

AU - Sharova, Tatyana

AU - Leshchiner, Ignaty

AU - Elagina, Liudmila

AU - Spiro, Oliver G.

AU - Livitz, Dimitri

AU - Rosebrock, Daniel

AU - Aguet, François

AU - Carrot-Zhang, Jian

AU - Ha, Gavin

AU - Lin, Ziao

AU - Chen, Jonathan H.

AU - Barzily-Rokni, Michal

AU - Hammond, Marc R.

AU - Vitzthum von Eckstaedt, Hans C.

AU - Blackmon, Shauna M.

AU - Jiao, Yunxin J.

AU - Gabriel, Stacey

AU - Lawrence, Donald P.

AU - Duncan, Lyn M.

AU - Stemmer-Rachamimov, Anat O.

AU - Wargo, Jennifer A.

AU - Flaherty, Keith T.

AU - Sullivan, Ryan J.

AU - Boland, Genevieve M.

AU - Meyerson, Matthew

AU - Getz, Gad

AU - Hacohen, Nir

PY - 2022/2/15

Y1 - 2022/2/15

N2 - Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.

AB - Immune checkpoint blockade (CPB) improves melanoma outcomes, but many patients still do not respond. Tumor mutational burden (TMB) and tumor-infiltrating T cells are associated with response, and integrative models improve survival prediction. However, integrating immune/tumor-intrinsic features using data from a single assay (DNA/RNA) remains underexplored. Here, we analyze whole-exome and bulk RNA sequencing of tumors from new and published cohorts of 189 and 178 patients with melanoma receiving CPB, respectively. Using DNA, we calculate T cell and B cell burdens (TCB/BCB) from rearranged TCR/Ig sequences and find that patients with TMBhigh and TCBhigh or BCBhigh have improved outcomes compared to other patients. By combining pairs of immune- and tumor-expressed genes, we identify three gene pairs associated with response and survival, which validate in independent cohorts. The top model includes lymphocyte-expressed MAP4K1 and tumor-expressed TBX3. Overall, RNA or DNA-based models combining immune and tumor measures improve predictions of melanoma CPB outcomes.

KW - T cell receptor

KW - TMB

KW - cancer genomics

KW - cancer immunotherapy

KW - immune checkpoint blockade

KW - integrative model

KW - melanoma

KW - melanoma subtype

KW - tumor mutational burden

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U2 - 10.1016/j.xcrm.2021.100500

DO - 10.1016/j.xcrm.2021.100500

M3 - Article

C2 - 35243413

AN - SCOPUS:85124612851

SN - 2666-3791

VL - 3

JO - Cell Reports Medicine

JF - Cell Reports Medicine

IS - 2

M1 - 100500

ER -

Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

Abstract

Keywords

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