Dataset Information

Liu2019 - Logistic Regression models to predict intrinsic resistance to anti-PD1 ICB in Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma.

ABSTRACT: In this comprehensive study, the authors have developed concise models integrating clinical, genomic and transcriptomic features to predict intrinsic resistance to anti-PD1 Immune Checkpoint Blockade (ICB) treatment in individual tumors. It's important to note that their validation was performed in smaller, independent cohorts, constrained by data availability. The authors have developed two Logistic Regression based models for Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma. The main predictive features for the Ipilimumab treated patients are MHC-II HLA, LDH at treatment initiation and the presence of lymph node metastases (LN met), chosen using forward selection methodology. The main predictive features for the Ipilimumab naive patients are tumor heterogeneity, tumor ploidy and tumor purity, chosen using forward selection methodology. Please note that in these models, the output ‘1’ means progressive disease (PD) and ‘0’ means non-PD. The original GitHub repository can be accessed at https://github.com/vanallenlab/schadendorf-pd1

SUBMITTER: Divyang Deep Tiwari

PROVIDER: MODEL2310150001 | BioModels | 2023-11-17

REPOSITORIES: BioModels

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Publications

Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma.

Liu David D Schilling Bastian B Liu Derek D Sucker Antje A Livingstone Elisabeth E Jerby-Arnon Livnat L Zimmer Lisa L Gutzmer Ralf R Satzger Imke I Loquai Carmen C Grabbe Stephan S Vokes Natalie N Margolis Claire A CA Conway Jake J He Meng Xiao MX Elmarakeby Haitham H Dietlein Felix F Miao Diana D Tracy Adam A Gogas Helen H Goldinger Simone M SM Utikal Jochen J Blank Christian U CU Rauschenberg Ricarda R von Bubnoff Dagmar D Krackhardt Angela A Weide Benjamin B Haferkamp Sebastian S Kiecker Felix F Izar Ben B Garraway Levi L Regev Aviv A Flaherty Keith K Paschen Annette A Van Allen Eliezer M EM Schadendorf Dirk D

Nature medicine 20191202 12

Immune-checkpoint blockade (ICB) has demonstrated efficacy in many tumor types, but predictors of responsiveness to anti-PD1 ICB are incompletely characterized. In this study, we analyzed a clinically annotated cohort of patients with melanoma (n = 144) treated with anti-PD1 ICB, with whole-exome and whole-transcriptome sequencing of pre-treatment tumors. We found that tumor mutational burden as a predictor of response was confounded by melanoma subtype, whereas multiple novel genomic and transc ...[more]

PMID: 31792460

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Dataset Information

Liu2019 - Logistic Regression models to predict intrinsic resistance to anti-PD1 ICB in Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma.

Publications

Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma.

Similar Datasets

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