Dataset Information

Profiling of retinaldehyde dehydrogenases in cancer cells

ABSTRACT: Retinaldehyde dehydrogenases convert retinal into all-trans retinoic acid (ATRA), thereby regulating cell differentiation and cancer stem cell proliferation. Chemical tools and methods are valuable commodities to study aldehyde dehydrogenase (ALDH) activity in human cells. Here, we describe the design, synthesis and application of LEI-945, a first-in-class activity-based probe modeled on retinal that reports on individual ALDHs in cancer cells. Comparative chemical proteomics with LEI-945 explained the ability of various breast cancer cell lines to produce ATRA via retinaldehyde dehydrogenases isozymes, whereas the ALDEFLUORTM assay could not. Competitive chemical proteomics using LEI-945 revealed that the ALDH inhibitor NCT-505 inhibited both ALDH1A1 and ALDH1A3 in MDA-MB-468 breast cancer cells inducing a cell cycle arrest in the G1 phase as well as cell death through necrosis. Our results show that LEI-945 holds promise to guide the discovery of ALDH-based therapeutics

INSTRUMENT(S): Synapt MS

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Cell Culture

DISEASE(S): Breast Cancer

SUBMITTER: Bogdan Florea

LAB HEAD: Mario van der Stelt, PhD

PROVIDER: PXD015495 | Pride | 2019-12-18

REPOSITORIES: Pride

ACCESS DATA

Publications

Development of a Retinal-Based Probe for the Profiling of Retinaldehyde Dehydrogenases in Cancer Cells.

Koenders Sebastiaan T A STA Wijaya Lukas S LS Erkelens Martje N MN Bakker Alexander T AT van der Noord Vera E VE van Rooden Eva J EJ Burggraaff Lindsey L Putter Pasquale C PC Botter Else E Wals Kim K van den Elst Hans H den Dulk Hans H Florea Bogdan I BI van de Water Bob B van Westen Gerard J P GJP Mebius Reina E RE Overkleeft Herman S HS Le Dévédec Sylvia E SE van der Stelt Mario M

ACS central science 20191212 12

Retinaldehyde dehydrogenases belong to a superfamily of enzymes that regulate cell differentiation and are responsible for detoxification of anticancer drugs. Chemical tools and methods are of great utility to visualize and quantify aldehyde dehydrogenase (ALDH) activity in health and disease. Here, we present the discovery of a first-in-class chemical probe based on retinal, the endogenous substrate of retinal ALDHs. We unveil the utility of this probe in quantitating ALDH isozyme activity in a ...[more]

PMID: 31893226

Similar Datasets

Project description:Recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) has a poor prognosis with less than 1-year median survival. Platinum-based chemotherapy (cisplatin or carboplatin) remains the first-line treatment for HNSCC. The cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self-renewing CSC population that is also capable of differentiating into non-self renewing cell populations that constitute the bulk of the tumor. A small population of CSCs exists within HNSCC that are relatively resistant to chemotherapy and clinically predicted to mediate tumor recurrence. These CSCs are identified by high cell-surface expression of CD44 and high intracellular activity of aldehyde dehydrogenase (ALDH) and termed ALDHhighCD44high. We investigated the molecular pathways active in ALDHhighCD44high cells, which remain poorly studied. Additionally, we performed a molecular examination of cisplatin-resistant ALDHhighCD44high cells, which has not been reported. Two HNSCC cell lines, UM-SCC-1 and UM-SCC-22b, were utilized in this study. For microarray analysis, UM-SCC-22b cells were treated for 5 days in vitro with 2uM cisplatin and analyzed by flow cytometry, sorted and submitted for microarray analysis of ALDHhighCD44high and ALDHlowCD44low cells from untreated and cisplatin treated cells. Four separate flow cytometry experiments were performed using Affymetrix Human Gene ST 2.1 microarrays. Microarray data was analyzed using R/Bioconductor. Files were preprocessed by Robust Multiarray Average (RMA) with background substraction, quantile normalization, and median polish (oligo package). Data was fitted with robust probe level linear models to all the probesets (oligo package). Experiment and processing batch differences were accounted for using 'ComBat' within the SVA package. Differentially expressed genes were identified using univariate comparisons after fitting data to a linear model (limma package). Initial statistics were determined using an empirical Bayesian model. Multiple testing comparisons were adjusted using Benjamini and Hochberg (aka FDR). Probes with an adjusted p-value <0.05 were considered statistically significant. Unsupervised hierarchical clustering with complete linkage and Euclidean distance was performed on only statistically significant probes. In four separate experiments, the head and neck squamous cell carcinoma cell line UM-SCC-22b were cultured for 5 days with or without 2uM (micromolar) cisplatin in 6-well plates. Media was replaced every other day. Control and cisplatin treated cells were trypsinized, procesed, and stained for CD44 cell-surface expression and intracellular aldehyde dehydrogenase (ALDH) activity to identify cancer stem cells (ALDH+CD44+). CSCs and non-CSCs (ALDH-CD44-) were collected by flow cytometry from both groups. Total RNA was collected from each fraction (ALDH+CD44+, ALDH-CD44-), treatment (control, cisplatin), and experiment (#1-4). A total of 16 samples were analyzed. One set of 4 (experiment #4) were analyzed on a Human Gene ST 2.1 strip and the rest on a Human Gene ST 2.1 plate. Differential gene expression was determined with R/Bioconductor with Robust Multiarray Average (RMA) and fitting the data to linear models (limma). Experimental and processing batch effects were accounted for using ComBat. Four sets of univariate comparisons were made: 1) Cisplatin ALDH+CD44+ vs Control ALDH+CD44+; 2) Control ALDH+CD44+ vs Control ALDH-CD44-; 3) Cisplatin ALDH+CD44+ vs Cisplatin ALDH-CD44-; 4) Cisplatin ALDH-CD44- vs Control ALDH-CD44-. Multiple testing comparisons were adjusted using Benjamini and Hochberg (aka FDR). Probes with an adjusted p-value <0.05 were considered statistically significant.

Dataset Information

Profiling of retinaldehyde dehydrogenases in cancer cells

Publications

Development of a Retinal-Based Probe for the Profiling of Retinaldehyde Dehydrogenases in Cancer Cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure