Multi-omics prediction in melanoma immunotherapy: A new brick in the wall

Caroline Robert; Daniel Gautheret

doi:10.1016/j.ccell.2021.12.008

Multi-omics prediction in melanoma immunotherapy: A new brick in the wall

Caroline Robert, Daniel Gautheret

Research output: Contribution to journal › Comment/debate

6 Citations (Scopus)

Abstract

In this issue of Cancer Cell, Newell et al. introduce whole-genome and methylome data to melanoma immunotherapy response analysis. Genome breaks are more frequent in resistant tumors, but the best response classifiers remain mutation burden and interferon-ɣ signature. Clinical translation will need aggregation of many such datasets.

Original language	English
Pages (from-to)	14-16
Number of pages	3
Journal	Cancer Cell
Volume	40
Issue number	1
DOIs	https://doi.org/10.1016/j.ccell.2021.12.008
Publication status	Published - 10 Jan 2022

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title = "Multi-omics prediction in melanoma immunotherapy: A new brick in the wall",

abstract = "In this issue of Cancer Cell, Newell et al. introduce whole-genome and methylome data to melanoma immunotherapy response analysis. Genome breaks are more frequent in resistant tumors, but the best response classifiers remain mutation burden and interferon-ɣ signature. Clinical translation will need aggregation of many such datasets.",

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AU - Gautheret, Daniel

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AB - In this issue of Cancer Cell, Newell et al. introduce whole-genome and methylome data to melanoma immunotherapy response analysis. Genome breaks are more frequent in resistant tumors, but the best response classifiers remain mutation burden and interferon-ɣ signature. Clinical translation will need aggregation of many such datasets.

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Multi-omics prediction in melanoma immunotherapy: A new brick in the wall

Abstract

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