Literature DB >> 26958999

Targeted MS Assay Predicting Tamoxifen Resistance in Estrogen-Receptor-Positive Breast Cancer Tissues and Sera.

Tommaso De Marchi1,2, Erik Kuhn3, Lennard J Dekker4, Christoph Stingl4, Rene B H Braakman1,2, Mark Opdam5, Sabine C Linn5, Fred C G J Sweep6, Paul N Span7, Theo M Luider4, John A Foekens1,3, John W M Martens1, Steven A Carr3, Arzu Umar1,2.   

Abstract

We recently reported on the development of a 4-protein-based classifier (PDCD4, CGN, G3BP2, and OCIAD1) capable of predicting outcome to tamoxifen treatment in recurrent, estrogen-receptor-positive breast cancer based on high-resolution MS data. A precise and high-throughput assay to measure these proteins in a multiplexed, targeted fashion would be favorable to measure large numbers of patient samples to move these findings toward a clinical setting. By coupling immunoprecipitation to multiple reaction monitoring (MRM) MS and stable isotope dilution, we developed a high-precision assay to measure the 4-protein signature in 38 primary breast cancer whole tissue lysates (WTLs). Furthermore, we evaluated the presence and patient stratification capabilities of our signature in an independent set of 24 matched (pre- and post-therapy) sera. We compared the performance of immuno-MRM (iMRM) with direct MRM in the absence of fractionation and shotgun proteomics in combination with label-free quantification (LFQ) on both WTL and laser capture microdissected (LCM) tissues. Measurement of the 4-proteins by iMRM showed not only higher accuracy in measuring proteotypic peptides (Spearman r: 0.74 to 0.93) when compared with MRM (Spearman r: 0.0 to 0.76) but also significantly discriminated patient groups based on treatment outcome (hazard ratio [HR]: 10.96; 95% confidence interval [CI]: 4.33 to 27.76; Log-rank P < 0.001) when compared with LCM (HR: 2.85; 95% CI: 1.24 to 6.54; Log-rank P = 0.013) and WTL (HR: 1.16; 95% CI: 0.57 to 2.33; Log-rank P = 0.680) LFQ-based predictors. Serum sample analysis by iMRM confirmed the detection of the four proteins in these samples. We hereby report that iMRM outperformed regular MRM, confirmed our previous high-resolution MS results in tumor tissues, and has shown that the 4-protein signature is measurable in serum samples.

Entities:  

Keywords:  MRM; SISCAPA; breast cancer; immunoaffinity capture; predictive biomarkers

Mesh:

Substances:

Year:  2016        PMID: 26958999     DOI: 10.1021/acs.jproteome.5b01119

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  6 in total

1.  A Strong Neutrophil Elastase Proteolytic Fingerprint Marks the Carcinoma Tumor Proteome.

Authors:  Michał Kistowski; Janusz Dębski; Jakub Karczmarski; Agnieszka Paziewska; Jacek Olędzki; Michał Mikula; Jerzy Ostrowski; Michał Dadlez
Journal:  Mol Cell Proteomics       Date:  2016-12-07       Impact factor: 5.911

Review 2.  Dissecting the Roles of PDCD4 in Breast Cancer.

Authors:  Qian Cai; Hsin-Sheng Yang; Yi-Chen Li; Jiang Zhu
Journal:  Front Oncol       Date:  2022-06-20       Impact factor: 5.738

3.  A novel lncRNA derived from an ultraconserved region: lnc-uc.147, a potential biomarker in luminal A breast cancer.

Authors:  Erika Pereira Zambalde; Recep Bayraktar; Tayana Schultz Jucoski; Cristina Ivan; Ana Carolina Rodrigues; Carolina Mathias; Erik Knutsen; Rubens Silveira de Lima; Daniela Fiori Gradia; Enilze Maria de Souza Fonseca Ribeiro; Samir Hannash; George Adrian Calin; Jaqueline Carvalhode Oliveira
Journal:  RNA Biol       Date:  2021-08-13       Impact factor: 4.766

Review 4.  A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research.

Authors:  Sara S Faria; Carlos F M Morris; Adriano R Silva; Micaella P Fonseca; Patrice Forget; Mariana S Castro; Wagner Fontes
Journal:  Front Oncol       Date:  2017-02-20       Impact factor: 6.244

5.  Single-cell expression and Mendelian randomization analyses identify blood genes associated with lifespan and chronic diseases.

Authors:  Arnaud Chignon; Valentin Bon-Baret; Marie-Chloé Boulanger; Zhonglin Li; Deborah Argaud; Yohan Bossé; Sébastien Thériault; Benoit J Arsenault; Patrick Mathieu
Journal:  Commun Biol       Date:  2020-05-01

6.  OCIAD1 Controls Electron Transport Chain Complex I Activity to Regulate Energy Metabolism in Human Pluripotent Stem Cells.

Authors:  Deeti K Shetty; Kaustubh P Kalamkar; Maneesha S Inamdar
Journal:  Stem Cell Reports       Date:  2018-06-21       Impact factor: 7.765

  6 in total

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