The University of Southampton
University of Southampton Institutional Repository

Resistance patterns in drug-adapted cancer cell lines reflect the complex evolution in clinical tumours

Resistance patterns in drug-adapted cancer cell lines reflect the complex evolution in clinical tumours
Resistance patterns in drug-adapted cancer cell lines reflect the complex evolution in clinical tumours
Background: here, we introduce a novel set of triple-negative breast cancer (TNBC) cell lines consisting of MDA-MB-468, HCC38, and HCC1806 and their sublines adapted to cisplatin, doxorubicin, eribulin, paclitaxel, gemcitabine, or 5-fluorouracil.

Methods: the cell lines were characterized by whole exome sequencing and the determination of drug-response profiles. Moreover, genes harbouring resistance-associated mutations were investigated using TCGA data for potential clinical relevance.

Result: sequencing combined with TCGA-derived patient data resulted in the identification of 682 biomarker candidates in the pan-cancer analysis. Thirty-five genes were considered the most promising candidates because they harboured resistance-associated variants in at least two resistant sublines, and their expression correlated with TNBC patient survival. Exome sequencing and response profiles to cytotoxic drugs and DNA damage response inhibitors identified revealed remarkably little overlap between the resistant sublines, suggesting that each resistance formation process follows a unique route. All of the drug-resistant TNBC sublines remained sensitive or even displayed collateral sensitivity to a range of tested compounds. Cross-resistance levels were lowest for the CHK2 inhibitor CCT241533, the PLK1 inhibitor SBE13, and the RAD51 recombinase inhibitor B02, suggesting that CHK2, PLK1, and RAD51 are potential drug targets for therapy-refractory TNBC.

Conclusions: we present novel preclinical models of acquired drug resistance in TNBC and many novel candidate biomarkers for further investigation. The finding that each cancer cell line adaptation process follows an unpredictable route reflects recent findings on cancer cell evolution in patients, supporting the relevance of drug-adapted cancer cell lines as preclinical models of acquired resistance
bioRxiv
Grimsley, Helen E.
bb750c7f-b170-43e3-9e96-cba6f531bb57
Antczak, Magdalena
eaec9fc2-f3f0-4367-ace2-da115daffa51
Reddin, Ian G.
b5f50ec1-83fb-4f15-a41f-f9c544d7ccc0
McLaughlin, Katie-May
d70f3b6c-6aab-4193-bf36-f58745c16a72
Nist, Andrea
07be8aac-5f20-4aa5-8560-4da8f623ac22
Mernberger, Marco
f7191570-ad1a-4c2b-b209-e24c113df7b3
Stiewe, Thorsten
48f8bc49-860a-43c5-9ff7-5d65de011f40
Fenton, Tim R.
087260ba-f6a1-405a-85df-099d05810a84
Speidel, Daniel
91226072-99ae-4580-8955-05b5d5dd65b9
Harper-Wynne, Catherine
c58e2b5e-f9d6-40bb-bf0c-ba193bf13db8
Cox, Karina
0f8bb6f0-6462-443f-abc0-e330e04408c3
Cinatl, Jindrich
473634ec-c6c2-44b9-b708-7229dd780790
Wass, Mark N.
58e102d5-8520-4372-a826-d3aa6f14d1f1
Garrett, Michelle D.
3ee60142-b09e-487f-a2fd-5df8e5797887
Michaelis, Martin
be3faca6-397a-40e1-be6e-3a8c89eeb341
Grimsley, Helen E.
bb750c7f-b170-43e3-9e96-cba6f531bb57
Antczak, Magdalena
eaec9fc2-f3f0-4367-ace2-da115daffa51
Reddin, Ian G.
b5f50ec1-83fb-4f15-a41f-f9c544d7ccc0
McLaughlin, Katie-May
d70f3b6c-6aab-4193-bf36-f58745c16a72
Nist, Andrea
07be8aac-5f20-4aa5-8560-4da8f623ac22
Mernberger, Marco
f7191570-ad1a-4c2b-b209-e24c113df7b3
Stiewe, Thorsten
48f8bc49-860a-43c5-9ff7-5d65de011f40
Fenton, Tim R.
087260ba-f6a1-405a-85df-099d05810a84
Speidel, Daniel
91226072-99ae-4580-8955-05b5d5dd65b9
Harper-Wynne, Catherine
c58e2b5e-f9d6-40bb-bf0c-ba193bf13db8
Cox, Karina
0f8bb6f0-6462-443f-abc0-e330e04408c3
Cinatl, Jindrich
473634ec-c6c2-44b9-b708-7229dd780790
Wass, Mark N.
58e102d5-8520-4372-a826-d3aa6f14d1f1
Garrett, Michelle D.
3ee60142-b09e-487f-a2fd-5df8e5797887
Michaelis, Martin
be3faca6-397a-40e1-be6e-3a8c89eeb341

Grimsley, Helen E., Antczak, Magdalena, Reddin, Ian G., McLaughlin, Katie-May, Nist, Andrea, Mernberger, Marco, Stiewe, Thorsten, Fenton, Tim R., Speidel, Daniel, Harper-Wynne, Catherine, Cox, Karina, Cinatl, Jindrich, Wass, Mark N., Garrett, Michelle D. and Michaelis, Martin (2024) Resistance patterns in drug-adapted cancer cell lines reflect the complex evolution in clinical tumours. (doi:10.1101/2024.01.20.576412).

Record type: Other

Abstract

Background: here, we introduce a novel set of triple-negative breast cancer (TNBC) cell lines consisting of MDA-MB-468, HCC38, and HCC1806 and their sublines adapted to cisplatin, doxorubicin, eribulin, paclitaxel, gemcitabine, or 5-fluorouracil.

Methods: the cell lines were characterized by whole exome sequencing and the determination of drug-response profiles. Moreover, genes harbouring resistance-associated mutations were investigated using TCGA data for potential clinical relevance.

Result: sequencing combined with TCGA-derived patient data resulted in the identification of 682 biomarker candidates in the pan-cancer analysis. Thirty-five genes were considered the most promising candidates because they harboured resistance-associated variants in at least two resistant sublines, and their expression correlated with TNBC patient survival. Exome sequencing and response profiles to cytotoxic drugs and DNA damage response inhibitors identified revealed remarkably little overlap between the resistant sublines, suggesting that each resistance formation process follows a unique route. All of the drug-resistant TNBC sublines remained sensitive or even displayed collateral sensitivity to a range of tested compounds. Cross-resistance levels were lowest for the CHK2 inhibitor CCT241533, the PLK1 inhibitor SBE13, and the RAD51 recombinase inhibitor B02, suggesting that CHK2, PLK1, and RAD51 are potential drug targets for therapy-refractory TNBC.

Conclusions: we present novel preclinical models of acquired drug resistance in TNBC and many novel candidate biomarkers for further investigation. The finding that each cancer cell line adaptation process follows an unpredictable route reflects recent findings on cancer cell evolution in patients, supporting the relevance of drug-adapted cancer cell lines as preclinical models of acquired resistance

Text
2024.01.20.576412v2.full - Author's Original
Download (1MB)

More information

Published date: 4 September 2024

Identifiers

Local EPrints ID: 494079
URI: http://eprints.soton.ac.uk/id/eprint/494079
PURE UUID: 93a3a7af-7c5a-43dc-b54a-06f74c3f07d0
ORCID for Ian G. Reddin: ORCID iD orcid.org/0000-0001-5478-7855
ORCID for Tim R. Fenton: ORCID iD orcid.org/0000-0002-4737-8233

Catalogue record

Date deposited: 23 Sep 2024 16:39
Last modified: 24 Sep 2024 02:01

Export record

Altmetrics

Contributors

Author: Helen E. Grimsley
Author: Magdalena Antczak
Author: Ian G. Reddin ORCID iD
Author: Katie-May McLaughlin
Author: Andrea Nist
Author: Marco Mernberger
Author: Thorsten Stiewe
Author: Tim R. Fenton ORCID iD
Author: Daniel Speidel
Author: Catherine Harper-Wynne
Author: Karina Cox
Author: Jindrich Cinatl
Author: Mark N. Wass
Author: Michelle D. Garrett
Author: Martin Michaelis

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×