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Preclinical evaluation of Insulin-like growth factor receptor 1 (IGF1R) and Insulin Receptor (IR) as a therapeutic targets in triple negative breast cancer.

ABSTRACT: Triple Negative Breast Cancer (TNBC), a subtype of breast cancer, has fewer successful therapeutic therapies than other types of breast cancer. Insulin-like growth factor receptor 1 (IGF1R) and the Insulin receptor (IR) are associated with poor outcomes in TNBC. Targeting IGF1R has failed clinically. We aimed to test if inhibiting both IR/IGF1R was a rationale therapeutic approach to treat TNBC. We showed that despite IGF1R and IR being expressed in TNBC, their expression is not associated with a negative survival outcome. Furthermore, targeting both IR/IGF1R with inhibitors in multiple TNBC cell lines did not inhibit cell growth. Linsitinib, a small molecule inhibitor of both IGF1R and IR, did not block tumour formation and had no effect on tumour growth in vivo. Cumulatively these data suggest that while IGF1R and IR are expressed in TNBC, they are not good therapeutic targets. A potential reason for the limited anti-cancer impact when IR/IGF1R was targeted may be because multiple signalling pathways are altered in TNBC. Therefore, targeting individual signalling pathways may not be sufficient to inhibit cancer growth.

SUBMITTER: Roche S

PROVIDER: S-EPMC10016661 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Preclinical evaluation of Insulin-like growth factor receptor 1 (IGF1R) and Insulin Receptor (IR) as a therapeutic targets in triple negative breast cancer.

Roche Sandra S Gaule Patricia P Winrow Deirdre D Mukherjee Nupur N O'Neill Fiona F Conlon Neil T NT Meiller Justine J Collins Denis M DM Canonici Alexandra A Fawsi Mohammed Ibrahim MI Estepa-Fernández Alejandra A Madden Stephen F SF Crown John J O'Donovan Norma N Eustace Alex J AJ

PloS one 20230315 3

Triple Negative Breast Cancer (TNBC), a subtype of breast cancer, has fewer successful therapeutic therapies than other types of breast cancer. Insulin-like growth factor receptor 1 (IGF1R) and the Insulin receptor (IR) are associated with poor outcomes in TNBC. Targeting IGF1R has failed clinically. We aimed to test if inhibiting both IR/IGF1R was a rationale therapeutic approach to treat TNBC. We showed that despite IGF1R and IR being expressed in TNBC, their expression is not associated with ...[more]

PMID: 36920947

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Project description:PurposeTriple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC.MethodsThe TNBC patients' data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC.ResultsWe obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database.ConclusionThe prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.

Dataset Information

Preclinical evaluation of Insulin-like growth factor receptor 1 (IGF1R) and Insulin Receptor (IR) as a therapeutic targets in triple negative breast cancer.

Publications

Preclinical evaluation of Insulin-like growth factor receptor 1 (IGF1R) and Insulin Receptor (IR) as a therapeutic targets in triple negative breast cancer.

Similar Datasets

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