A novel proteomics-based approach for detection of ESR1 mutant peptides in hormone receptor positive metastatic breast cancer: An exploratory study from India.

e15175 Background: ESR1 gene mutation is a commonly implicated mechanism of endocrine resistance in metastatic breast cancers (MBCs). Though many mutations occur at gene level, all of them are not translated into proteins. Hence, mass spectrometry (MS)-based proteomic assays provide a comprehensive knowledge about functional impact of mutations on cellular processes and disease mechanisms. Quantitative proteomics has enabled MS-based protein profiling of different types of cancers, and thereby has navigated towards discovery of several biomarkers and potential therapeutic targets. There are limited studies on utilization of this versatile MS platform for detection of mutant protein peptides. Methods: The research was conducted prospectively, on formalin fixed and paraffin embedded (FFPE) samples of hormone receptor (HR) positive & Her2 negative MBCs. The sample preparation phase included- deparaffinization and protein extraction, followed by proteomic sample preparation by reduction, alkylation and trypsin digestion. Trypsin-digested peptides were desalted and reconstituted for liquid chromatography (LC)-MS analysis. The data acquisition was carried out using ThermoFisher Orbitrap Tribrid Fusion MS. During the discovery phase, MS data acquisition was carried out using the data dependent analysis(DDA)-MS approach to ascertain the utility of MS method for detection of mutations at protein level. Further, a 120 min-data independent analysis (DIA)-MS method was optimized for the detection of ESR1 mutant peptides from the samples. The resultant raw data was searched against an in-house generated variant peptide spectral library for ESR1 mutations. The data analysis was carried out using the software Skyline v22.2 for detection of variant peptides corresponding to the mutated ESR1 protein. Results: Out of 55 eligible patients subjected for proteomic studies, one failed sample preparation. The DDA-MS acquisition was done initially on 9 samples and further DIA-MS was done on the remaining 45 samples. Overall frequency of ESR1 mutation was 42.6% (23 out of 54) samples, detected in all 9 samples subjected for DDA acquisition and in 31% (14 out of 45) samples subjected for DIA-MS analysis. Majority had polyclonal mutations. Y537 was the most commonly involved codon. Multiple hotspot mutations were observed in individual patients. Conclusions: The current study is the first of its kind to explore mass spectrometry based approach for detection of ESR1 mutant peptides on FFPE samples. Our results can be further validated by targeted proteomics approach like selective reaction monitoring by use of synthetic peptides. We anticipate similar studies in future that will hopefully pave the way for proteomics based techniques for detection of druggable putative peptide variant targets in archived tissue samples.