Dataset Information

Pin1 plays a key role in the response to treatment and clinical outcome in triple negative breast cancer.

ABSTRACT:

Background

Triple negative breast cancer (TNBC) is the subset of breast cancer associated with the poorest outcome, and currently lacks targeted treatments. Standard of care (SoC) chemotherapy often consists of DNA damaging chemotherapies?±?taxanes, with a range of responses observed. However, we currently lack biomarkers to predict this response and lack alternate treatment options.

Methods

Pin1 expression was modulated in vitro and proliferation and treatment response was studied. Pin1 expression was analysed in patient samples and correlated with clinical outcome.

Results

In this study, we have shown that the prolyl isomerase, Pin1, which is highly expressed in TNBC, plays a key role in pathogenesis of the disease. Knockdown of Pin1 in TNBC resulted in cell death while the opposite is seen in normal cells. We revealed for the first time that loss of Pin1 leads to increased sensitivity to Taxol but only in the absence of functional BRCA1. Conversely, loss of Pin1 results in decreased sensitivity to DNA-damaging agents independent of BRCA1 status. Analysis of Pin1 gene or IHC-based expression in over 200 TNBC patient samples revealed a novel role for Pin1 as a TNBC-specific biomarker, with high expression associated with improved outcome in the context of SoC chemotherapy. Preliminary data indicated this may be extended to other treatment options (e.g. Cisplatin/Parp Inhibitors) that are gaining traction for the treatment of TNBC.

Conclusions

This study highlights the important role played by Pin1 in TNBC and highlights the context-dependent functions in modulating cell growth and response to treatment.

SUBMITTER: Knowlson C

PROVIDER: S-EPMC7065279 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Pin1 plays a key role in the response to treatment and clinical outcome in triple negative breast cancer.

Knowlson Catherine C Haddock Paula P Bingham Victoria V McQuaid Stephen S Mullan Paul B PB Buckley Niamh E NE

Therapeutic advances in medical oncology 20200309

<h4>Background</h4>Triple negative breast cancer (TNBC) is the subset of breast cancer associated with the poorest outcome, and currently lacks targeted treatments. Standard of care (SoC) chemotherapy often consists of DNA damaging chemotherapies ± taxanes, with a range of responses observed. However, we currently lack biomarkers to predict this response and lack alternate treatment options.<h4>Methods</h4>Pin1 expression was modulated <i>in vitro</i> and proliferation and treatment response was ...[more]

PMID: 32215056

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Project description:BackgroundNeoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30-40% of TNBC patients. Tumor-infiltrating lymphocytes (TILs), Ki67 and phosphohistone H3 (pH3) are a few known biomarkers to predict NAC response. Currently, systematic evaluation of the combined value of these biomarkers in predicting NAC response is lacking. In this study, the predictive value of markers derived from H&E and IHC stained biopsy tissue was comprehensively evaluated using a supervised machine learning (ML)-based approach. Identifying predictive biomarkers could help guide therapeutic decisions by enabling precise stratification of TNBC patients into responders and partial or non-responders.MethodsSerial sections from core needle biopsies (n = 76) were stained with H&E and immunohistochemically for the Ki67 and pH3 markers, followed by whole-slide image (WSI) generation. The serial section stains in H&E stain, Ki67 and pH3 markers formed WSI triplets for each patient. The resulting WSI triplets were co-registered with H&E WSIs serving as the reference. Separate mask region-based CNN (MRCNN) models were trained with annotated H&E, Ki67 and pH3 images for detecting tumor cells, stromal and intratumoral TILs (sTILs and tTILs), Ki67+, and pH3+ cells. Top image patches with a high density of cells of interest were identified as hotspots. Best classifiers for NAC response prediction were identified by training multiple ML models and evaluating their performance by accuracy, area under curve, and confusion matrix analyses.ResultsHighest prediction accuracy was achieved when hotspot regions were identified by tTIL counts and each hotspot was represented by measures of tTILs, sTILs, tumor cells, Ki67+, and pH3+ features. Regardless of the hotspot selection metric, a complementary use of multiple histological features (tTILs, sTILs) and molecular biomarkers (Ki67 and pH3) resulted in top ranked performance at the patient level.ConclusionsOverall, our results emphasize that prediction models for NAC response should be based on biomarkers in combination rather than in isolation. Our study provides compelling evidence to support the use of ML-based models to predict NAC response in patients with TNBC.

Project description:BackgroundThe treatment of Triple-negative breast cancer (TNBC) has always been challenging due to its heterogeneity and the absence of well-defined molecular targets. The present study aims to elucidate the role of protein-coding circRNAs in the etiology and carcinogenesis of TNBC.MethodsCircRNA expression data in TNBC (GEO: GSE113230, GSE101123) were reanalyzed and then circCAPG was selected for further study. To identify the polypeptide-coding function of circCAPG, a series of experiments, such as Mass spectrometry and dual-luciferase reporter assays were conducted. Cell proliferation, apoptosis and metastasis parameters were determined to investigate the cancerous functions CAPG-171aa plays in both TNBC organoids and nude mice. Mechanistically, the relation between CAPG-171aa and STK38 in TNBC was verified by immunoprecipitation analyses and mass spectrometry. The interactions between SLU7 and its binding site on circCAPG were validated by RIP-qPCR experiments.ResultsIn both TNBC clinical samples and cell lines, the expression level of circCAPG was identified to be higher compared with normal ones and positively correlated with the overall survival (n = 132) in a 10-year follow-up study, in which the area under the curve of receiver operating characteristic was 0.8723 with 100% specificity and 80% sensitivity. In addition, we found that circCAPG knockdown (KD) significantly inhibited the growth of TNBC organoids. Intriguingly, circCAPG can be translated into a polypeptide named CAPG-171aa which promotes tumor growh by disrupting the binding of serine/threonine kinase 38 (STK38) to SMAD-specific E3 ubiquitin protein ligase 1 (SMURF1) and thereby preventing MEKK2 ubiquitination and proteasomal degradation. Furthermore, we found that SLU7 Homolog- Splicing Factor (SLU7) can regulate the bio-generation of circCAPG through binding to the flanking Alu sequences of circRNA transcripts.ConclusionscircCAPG significantly enhances the proliferation and metastasis of TNBC cells by encoding a novel polypeptide CAPG-171aa and afterwards activates MEKK2-MEK1/2-ERK1/2 pathway. Additionally, the formation of circCAPG is found to be mediated by SLU7. The present study provides innovative insight into the role of protein-coding circRNAs CAPG-171aa in TNBC, and its capacity to serve as a promising prognostic biomarker and potential therapeutic target in TNBC.

Dataset Information

Pin1 plays a key role in the response to treatment and clinical outcome in triple negative breast cancer.

Background

Methods

Results

Conclusions

Publications

Pin1 plays a key role in the response to treatment and clinical outcome in triple negative breast cancer.

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