Dataset Information

Heterogeneity of the cancer cell line metabolic landscape.

ABSTRACT: The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 different species using mass spectrometry (MS). We correlate known cancer-associated mutations and gene expression programs with metabolic signatures, generating novel associations of known metabolic pathways with known cancer drivers. We show that metabolic activity correlates with drug sensitivity and use metabolic activity to predict drug response and synergy. Finally, we study the metabolic heterogeneity of cancer mutations across tissues, and find that genes exhibit a range of context specific, and more general metabolic control.

SUBMITTER: Shorthouse D

PROVIDER: S-EPMC9627668 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Heterogeneity of the cancer cell line metabolic landscape.

Shorthouse David D Bradley Jenna J Critchlow Susan E SE Bendtsen Claus C Hall Benjamin A BA

Molecular systems biology 20221101 11

The unravelling of the complexity of cellular metabolism is in its infancy. Cancer-associated genetic alterations may result in changes to cellular metabolism that aid in understanding phenotypic changes, reveal detectable metabolic signatures, or elucidate vulnerabilities to particular drugs. To understand cancer-associated metabolic transformation, we performed untargeted metabolite analysis of 173 different cancer cell lines from 11 different tissues under constant conditions for 1,099 differ ...[more]

PMID: 36321551

Similar Datasets

Project description:BackgroundCancer metabolism is emerging as an important focus area in cancer research. However, the in vitro cell culture conditions under which much cellular metabolism research is performed differ drastically from in vivo tumor conditions, which are characterized by variations in the levels of oxygen, nutrients like glucose, and other molecules like chemotherapeutics. Moreover, it is important to know how the diverse cell types in a tumor, including cancer stem cells that are believed to be a major cause of cancer recurrence, respond to these variations. Here, in vitro environmental perturbations designed to mimic different aspects of the in vivo environment were used to characterize how an ovarian cancer cell line and its derived, isogenic cancer stem cells metabolically respond to environmental cues.ResultsMass spectrometry was used to profile metabolite levels in response to in vitro environmental perturbations. Docetaxel, the chemotherapeutic used for this experiment, caused significant metabolic changes in amino acid and carbohydrate metabolism in ovarian cancer cells, but had virtually no metabolic effect on isogenic ovarian cancer stem cells. Glucose deprivation, hypoxia, and the combination thereof altered ovarian cancer cell and cancer stem cell metabolism to varying extents for the two cell types. Hypoxia had a much larger effect on ovarian cancer cell metabolism, while glucose deprivation had a greater effect on ovarian cancer stem cell metabolism. Core metabolites and pathways affected by these perturbations were identified, along with pathways that were unique to cell types or perturbations.ConclusionsThe metabolic responses of an ovarian cancer cell line and its derived isogenic cancer stem cells differ greatly under most conditions, suggesting that these two cell types may behave quite differently in an in vivo tumor microenvironment. While cancer metabolism and cancer stem cells are each promising potential therapeutic targets, such varied behaviors in vivo would need to be considered in the design and early testing of such treatments.

Dataset Information

Heterogeneity of the cancer cell line metabolic landscape.

Publications

Heterogeneity of the cancer cell line metabolic landscape.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets