Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in non-responding tumors in three immunotherapy-treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature, and HLA status provided an improved predictor of response to immunotherapy that was independently validated.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 2 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001005796	The dataset for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer includes 106 bam files from whole exome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include matched tumor/normal samples from non-small cell lung cancer patients treated with immunotherapy.	Illumina HiSeq 2500	106

Publications	Citations
Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer. Anagnostou V, Niknafs N, Marrone K, Bruhm DC, White JR, Naidoo J, Hummelink K, Monkhorst K, Lalezari F, Lanis M, Rosner S, Reuss JE, Smith KN, Adleff V, Rodgers K, Belcaid Z, Rhymee L, Levy B, Feliciano J, Hann CL, Ettinger DS, Georgiades C, Verde F, Illei P, Li QK, Baras AS, Gabrielson E, Brock MV, Karchin R, Pardoll DM, Baylin SB, Brahmer JR, Scharpf RB, Forde PM, Velculescu VE. Nat Cancer 1: 2020 99-111	101
Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer. Ravi A, Hellmann MD, Arniella MB, Holton M, Freeman SS, Naranbhai V, Stewart C, Leshchiner I, Kim J, Akiyama Y, Griffin AT, Vokes NI, Sakhi M, Kamesan V, Rizvi H, Ricciuti B, Forde PM, Anagnostou V, Riess JW, Gibbons DL, Pennell NA, Velcheti V, Digumarthy SR, Mino-Kenudson M, Califano A, Heymach JV, Herbst RS, Brahmer JR, Schalper KA, Velculescu VE, Henick BS, Rizvi N, Jänne PA, Awad MM, Chow A, Greenbaum BD, Luksza M, Shaw AT, Wolchok J, Hacohen N, Getz G, Gainor JF. Nat Genet 55: 2023 807-819	41

Publications

Citations

Multimodal genomic features predict outcome of immune checkpoint blockade in non-small-cell lung cancer.
Anagnostou V, Niknafs N, Marrone K, Bruhm DC, White JR, Naidoo J, Hummelink K, Monkhorst K, Lalezari F, Lanis M, Rosner S, Reuss JE, Smith KN, Adleff V, Rodgers K, Belcaid Z, Rhymee L, Levy B, Feliciano J, Hann CL, Ettinger DS, Georgiades C, Verde F, Illei P, Li QK, Baras AS, Gabrielson E, Brock MV, Karchin R, Pardoll DM, Baylin SB, Brahmer JR, Scharpf RB, Forde PM, Velculescu VE. Nat Cancer 1: 2020 99-111

101

Genomic and transcriptomic analysis of checkpoint blockade response in advanced non-small cell lung cancer.
Ravi A, Hellmann MD, Arniella MB, Holton M, Freeman SS, Naranbhai V, Stewart C, Leshchiner I, Kim J, Akiyama Y, Griffin AT, Vokes NI, Sakhi M, Kamesan V, Rizvi H, Ricciuti B, Forde PM, Anagnostou V, Riess JW, Gibbons DL, Pennell NA, Velcheti V, Digumarthy SR, Mino-Kenudson M, Califano A, Heymach JV, Herbst RS, Brahmer JR, Schalper KA, Velculescu VE, Henick BS, Rizvi N, Jänne PA, Awad MM, Chow A, Greenbaum BD, Luksza M, Shaw AT, Wolchok J, Hacohen N, Getz G, Gainor JF. Nat Genet 55: 2023 807-819