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A Text-Based Computational Framework for Patient-Specific Modeling for Classification of Cancers

37 Pages Posted: 18 Nov 2021 Publication Status: Published

See all articles by Hiroaki Imoto

Hiroaki Imoto

Osaka University - Institute for Protein Research

Sawa Yamashiro

Osaka University - Institute for Protein Research

Mariko Okada-Hatakeyama

Osaka University - Institute for Protein Research; RIKEN Center for Integrative Medical Sciences

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Abstract

Patient heterogeneity precludes cancer treatment and drug development; hence, development of methods for finding prognostic markers for individual treatment are urgently required. Here, we present Pasmopy (Patient-Specific Modeling in Python), a computational framework for stratification of patients using in silico signaling dynamics. Pasmopy converts texts and sentences on gene regulation into an executable mathematical model. Using this framework, we built a model of the ErbB receptor signaling network, trained in cultured cell lines, and performed in silico simulation of 377 breast cancer patients using The Cancer Genome Atlas (TCGA) transcriptome datasets. The temporal dynamics of Akt, Extracellular Signal-Regulated Kinase (ERK), and c-Myc in each patient were able to accurately predict the difference in prognosis and sensitivity to kinase inhibitors in triple-negative breast cancer (TNBC). Our model applies to any type of signaling network and facilitates the network-based use of prognostic markers and prediction of drug response.

Keywords: Mathematical modeling, signaling network, Cancer classification, Clinical data analysis

Suggested Citation

Imoto, Hiroaki and Yamashiro, Sawa and Okada-Hatakeyama, Mariko, A Text-Based Computational Framework for Patient-Specific Modeling for Classification of Cancers. Available at SSRN: https://ssrn.com/abstract=3965951 or http://dx.doi.org/10.2139/ssrn.3965951
This version of the paper has not been formally peer reviewed.

Hiroaki Imoto

Osaka University - Institute for Protein Research

3-2 Yamadaoka
Suita
Osaka Prefecture, 565-0871
Japan

Sawa Yamashiro

Osaka University - Institute for Protein Research

3-2 Yamadaoka
Suita
Osaka Prefecture, 565-0871
Japan

Mariko Okada-Hatakeyama (Contact Author)

Osaka University - Institute for Protein Research ( email )

3-2 Yamadaoka
Suita
Osaka Prefecture, 565-0871
Japan

RIKEN Center for Integrative Medical Sciences ( email )

1-7-22, Suehiro-cho
Tsurumi-ku
Yokohama, Kanagawa
Japan

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