Tissue Biomarker Discovery Archives - Biognosys

Trapped ion mobility spectrometry (TIMS) extends conventional LC-MS/MS proteomic workflows with an additional ion mobility dimension. Next to the benefits of signal separation, the implementation of TIMS in Bruker timsTOF instruments has demonstrated that collisional cross section (CCS) values of peptides are highly reproducible and can be used as orthogonal coordinates to retention time and ion m/z values for targeted data extraction in data-independent acquisition (DIA) workflows, or as additional metric for rescoring in spectrum-centric database searches.

Neural networks have been extensively used in the proteomics field and their role on improving identifications is rapidly becoming more relevant. DeepiRT is a neural network designed to predict Indexed Retention Time (iRT) (Escher, 2012) for a given precursor based on its modified sequence.

This poster delves into the ULTRA-DEEP EXPLORATION OF HUMAN TISSUE PROTEOMES, where 20025 protein groups were identified across all 22 tissue samples (19 healthy and 3 cancer). The poster concludes that the qualitative human tissue digital proteome serves as a rich resource that can be mined for various applications such as basal protein expression, different proteoforms, PTMs etc.

 

Mass spectrometry (MS)-based proteomics allows the comprehensive identification and quantification of proteins in various biological specimen such as cell lines, body fluids or tissues. The study of these complex samples for applications like biomarker discovery requires large sample cohorts with low technical variability to overcome inter-individual differences and achieve sufficient statistical power.

Rapid developments in the field of proteomics within recent years have enabled the reproducible and reliable quantification of large sample cohorts. Large scale studies comprising hundreds of samples are primarily processed and analyzed in one centralized facility.

The primary goal of many DIA based experiments is to discover proteins or peptides (candidates) that are differentially expressed in two or more conditions. Improvements in DIA workflow are typically measured based on identification, precision, and accuracy.

The fusion of trapped ion mobility spectrometry (TIMS) with parallel reaction monitoring (PRM), particularly through the prm-PASEF ® technique, is indeed a groundbreaking development in proteomics. This innovative approach leverages the parallel accumulation-serial fragmentation (PASEF) mode to synchronize ion release from TIMS with selective precursor isolation, reducing the noise in the peptide ion spectra without sacrificing sensitivity.

Numerous software tools, including Spectronaut, have been developed to interpret the increasingly complex and voluminous raw data generated from mass-spectrometry-based proteomics data. These resulting datasets are typically extensive and challenging to analyze, necessitating substantial expertise in the field of proteomics.

This poster emphasizes the importance of MHC molecules in immune responses, particularly in cancer research, where comprehending tumor-associated antigens holds great significance. Accurately quantifying HLA class I/II neoantigens is essential for understanding how the immune system detects and reacts to cancerous cells. However, a significant limitation lies in the high input material requirement.

We devised an integrated immunopeptidomics (IMPX) workflow tailored for cell and tissue samples to address this challenge. This innovative approach allows for in-depth profiling of immunopeptides while substantially reducing the input material needed, which is particularly beneficial for PBMC samples.

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