KuLGaP: A Selective Measure for Assessing Therapy Response in Patient-Derived Xenografts

Abstract Quantifying response to drug treatment in mouse models of human cancer is important for treatment development and assignment, and yet remains a challenging task. A preferred measure to quantify this response should take into account as much of the experimental data as possible, i.e. both tumor size over time and the variation among replicates. We propose a theoretically grounded measure, KuLGaP, to compute the difference between the treatment and control arms. KuLGaP is more selective than currently existing measures, reduces the risk of false positive calls and improves translation of the lab results to clinical practice..

Medienart:

Preprint

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

bioRxiv.org - (2022) vom: 17. Nov. Zur Gesamtaufnahme - year:2022

Sprache:

Englisch

Beteiligte Personen:

Ortmann, Janosch [VerfasserIn]
Rampášek, Ladislav [VerfasserIn]
Tai, Elijah [VerfasserIn]
Mer, Arvind Singh [VerfasserIn]
Shi, Ruoshi [VerfasserIn]
Stewart, Erin L [VerfasserIn]
Mascaux, Celine [VerfasserIn]
Fares, Aline [VerfasserIn]
Pham, Nhu-An [VerfasserIn]
Beri, Gangesh [VerfasserIn]
Eeles, Christopher [VerfasserIn]
Tkachuk, Denis [VerfasserIn]
Ho, Chantal [VerfasserIn]
Sakashita, Shingo [VerfasserIn]
Weiss, Jessica [VerfasserIn]
Jiang, Xiaoqian [VerfasserIn]
Liu, Geoffrey [VerfasserIn]
Cescon, David W. [VerfasserIn]
O’Brien, Catherine [VerfasserIn]
Guo, Sheng [VerfasserIn]
Tsao, Ming-Sound [VerfasserIn]
Haibe-Kains, Benjamin [VerfasserIn]
Goldenberg, Anna [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.1101/2020.09.08.287573

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI018719090