Dataset Information

Patterson2022 - Tumour mutation data driven Random Forest model to predict immune checkpoint inhibitor therapy benefit in metastatic melanoma

ABSTRACT: A Random Forest model is developed to incorporate tumor mutation data within the context of the biological process known as leukocyte proliferation regulation. This model aims to predict a patient's response to anti-PD1 treatment. The authors conducted experiments using four different types of classifiers: Random Forest, Gradient Boosting, Feed Forward Neural Network, and Long Short-Term Memory (LSTM) recurrent neural network. Among these classifiers, the Random Forest algorithm yielded the best predictive performance when modeling gene mutation data associated with the 'leukocyte proliferation regulation' biological process. Hence, this curated version of the model focuses on the Random Forest model trained specifically on the 'Leukocyte Proliferation Regulation' process. In this model, a value of '0' is assigned to NonResponders, while a value of '1' is assigned to Responders. Please note that to obtain predictions, users should provide mutation data containing only the genes corresponding to the 'GO_REGULATION_OF_LEUKOCYTE_PROLIFERATION' process keyword, as specified in the 'GO_test_genes_dict_intersection' dictionary.

SUBMITTER: Divyang Deep Tiwari

PROVIDER: BIOMD0000001073 | BioModels | 2023-07-03

REPOSITORIES: BioModels

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Dataset's files

Source:

			Action	DRS
	BIOMD0000001073?filename=05_pickled_data.zip	Other
	BIOMD0000001073?filename=MelanomaICI_annotation.csv	Csv
	BIOMD0000001073?filename=Reproduced%20Figures.pdf	Pdf
	BIOMD0000001073?filename=Reproduced%20Metrics.pdf	Pdf
	BIOMD0000001073?filename=docker_predict.zip	Other

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Publications

Mutated processes predict immune checkpoint inhibitor therapy benefit in metastatic melanoma.

Patterson Andrew A Auslander Noam N

Nature communications 20220919 1

Immune Checkpoint Inhibitor (ICI) therapy has revolutionized treatment for advanced melanoma; however, only a subset of patients benefit from this treatment. Despite considerable efforts, the Tumor Mutation Burden (TMB) is the only FDA-approved biomarker in melanoma. However, the mechanisms underlying TMB association with prolonged ICI survival are not entirely understood and may depend on numerous confounding factors. To identify more interpretable ICI response biomarkers based on tumor mutatio ...[more]

PMID: 36123351

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