Oncology Archives - Biognosys

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Although immunotherapy has improved the treatment of NSCLC, a significant number of patients still fail to respond or develop resistance.

Plasma is the most widely collected biofluid and an invaluable source of biomarkers. The analysis of plasma using discovery mass spectrometry–based proteomics faces challenges as the 22 most abundant proteins constitute more than 99% of the total protein content. This is hindering the detection of lower abundant proteins, potentially disease-relevant biomarkers. To overcome this, we developed and optimized an enrichment workflow, termed P2 Plasma Enrichment System, based on protein corona formation. Protein corona formation leads to a reduction in dynamic range enabling the detection of lower abundant proteins.
We characterized P2 in terms of pre-analytical variation, robustness and quantification. Finally, we applied it to find predictive biomarkers in a multicentric phase II clinical trial (SAKK17/18) in patients with non-small cell lung cancer (NSCLC).

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.

Our collaborator, GreyWolf Therapeutics, has uncovered the effect of aminopeptidase ERAP2 inhibition for generating the de novo antitumor T-cell responses, thereby overcoming the resistance mechanism for current immune-oncology therapy.

Learn more about leveraging our TrueDiscovery® immunopeptidomics CRO services to overcome the challenges in immune-oncology.

Disclaimer: The contact information provided for poster download will also be shared with GreyWolf Therapeutics

 

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.

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