Dataset Information

Loss of RasGAP Tumor Suppressors Underlies the Aggressive Nature of Luminal B Breast Cancers.

ABSTRACT: Luminal breast cancers are typically estrogen receptor-positive and generally have the best prognosis. However, a subset of luminal tumors, namely luminal B cancers, frequently metastasize and recur. Unfortunately, the causal events that drive their progression are unknown, and therefore it is difficult to identify individuals who are likely to relapse and should receive escalated treatment. Here, we identify a bifunctional RasGAP tumor suppressor whose expression is lost in almost 50% of luminal B tumors. Moreover, we show that two RasGAP genes are concomitantly suppressed in the most aggressive luminal malignancies. Importantly, these genes cooperatively regulate two major oncogenic pathways, RAS and NF-κB, through distinct domains, and when inactivated drive the metastasis of luminal tumors in vivo Finally, although the cooperative effects on RAS drive invasion, NF-κB activation triggers epithelial-to-mesenchymal transition and is required for metastasis. Collectively, these studies reveal important mechanistic insight into the pathogenesis of luminal B tumors and provide functionally relevant prognostic biomarkers that may guide treatment decisions.

Significance

The lack of insight into mechanisms that underlie the aggressive behavior of luminal B breast cancers impairs treatment decisions and therapeutic advances. Here, we show that two RasGAP tumor suppressors are concomitantly suppressed in aggressive luminal B tumors and demonstrate that they drive metastasis by activating RAS and NF-κB. Cancer Discov; 7(2); 202-17. ©2016 AACR.See related commentary by Sears and Gray, p. 131This article is highlighted in the In This Issue feature, p. 115.

SUBMITTER: Olsen SN

PROVIDER: S-EPMC6461361 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Loss of RasGAP Tumor Suppressors Underlies the Aggressive Nature of Luminal B Breast Cancers.

Olsen Sarah Naomi SN Wronski Ania A Castaño Zafira Z Dake Benjamin B Malone Clare C De Raedt Thomas T Enos Miriam M DeRose Yoko S YS Zhou Wenhui W Guerra Stephanie S Loda Massimo M Welm Alana A Partridge Ann H AH McAllister Sandra S SS Kuperwasser Charlotte C Cichowski Karen K

Cancer discovery 20161214 2

Luminal breast cancers are typically estrogen receptor-positive and generally have the best prognosis. However, a subset of luminal tumors, namely luminal B cancers, frequently metastasize and recur. Unfortunately, the causal events that drive their progression are unknown, and therefore it is difficult to identify individuals who are likely to relapse and should receive escalated treatment. Here, we identify a bifunctional RasGAP tumor suppressor whose expression is lost in almost 50% of lumina ...[more]

PMID: 27974415

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Project description:Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString®) and CDx (Foundation One®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

Project description:PurposeThis study aimed to evaluate a radiomics model using Photoacoustic/ultrasound (PA/US) imaging at intra and peri-tumoral area to differentiate Luminal and non-Luminal breast cancer (BC) and to determine the optimal peritumoral area for accurate classification.Materials and methodsFrom February 2022 to April 2024, this study continuously collected 322 patients at Shenzhen People's Hospital, using standardized conditions for PA/US imaging of BC. Regions of interest were delineated using ITK-SNAP, with peritumoral regions of 2 mm, 4 mm, and 6 mm automatically expanded using code from the Pyradiomic package. Feature extraction was subsequently performed using Pyradiomics. The study employed Z-score normalization, Spearman correlation for feature correlation, and LASSO regression for feature selection, validated through 10-fold cross-validation. The radiomics model integrated intra and peri-tumoral area, evaluated by receiver operating characteristic curve(ROC), Calibration and Decision Curve Analysis(DCA).ResultsWe extracted and selected features from intratumoral and peritumoral PA/US images regions at 2 mm, 4 mm, and 6 mm. The comprehensive radiomics model, integrating these regions, demonstrated enhanced diagnostic performance, especially the 4 mm model which showed the highest area under the curve(AUC):0.898(0.78-1.00) and comparably high accuracy (0.900) and sensitivity (0.937). This model outperformed the standalone clinical model and combined clinical-radiomics model in distinguishing between Luminal and non-Luminal BC, as evidenced in the test set results.ConclusionThis study developed a radiomics model integrating intratumoral and peritumoral at 4 mm region PA/US model, enhancing the differentiation of Luminal from non-Luminal BC. It demonstrated the diagnostic utility of peritumoral characteristics, reducing the need for invasive biopsies and aiding chemotherapy planning, while emphasizing the importance of optimizing tumor surrounding size for improved model accuracy.

Dataset Information

Loss of RasGAP Tumor Suppressors Underlies the Aggressive Nature of Luminal B Breast Cancers.

Significance

Publications

Loss of RasGAP Tumor Suppressors Underlies the Aggressive Nature of Luminal B Breast Cancers.

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