Mass Spectrometry Unit

Multispecific antibodies, including trispecifics tsAbs, offer significant therapeutic potential. However, their production requires the co-expression of multiple different polypeptide chains, which may result in incorrect chain pairing and the production of undesired and non-functional mispaired species. Minimizing these mispairing impurities would simplify following downstream purification steps, reducing production costs and duration. 

In this collaborative study between iBET and Sanofi, quantitative transcriptomics and proteomics analyses were employed to investigate which signalling pathways correlated with low and high mispairing clone signatures.

Gene and protein expression profiles of Chinese hamster ovary (CHO) cells, producing tsAbs, were analyzed during different growth phases. Functional analysis revealed that low mispairing clones exhibited increased endocytosis and target protein degradation, suggesting the elimination of unfolded proteins through ubiquitin-mediated mechanisms. Furthermore, transcriptomic profiling identified a set of genes that may serve as biomarkers, enabling the identification of high mispairing levels earlier in the bioprocess development. (M J Sebastião et al., 2023)

Sorafenib is the first line of treatment against advanced hepatocellular carcinoma, the predominant form of liver cancer. Despite its widespread clinical use, a comprehensive understanding of sorafenib’s mechanisms of action remains elusive. This knowledge gap limits efforts to overcome treatment resistance.

In this study, Cellular Thermal Shift Assay (CETSA) coupled with MS was employed to identify sorafenib’s protein targets within a human hepatoma cell model. 

CETSA relies on the thermal stability changes induced by a ligand when it binds to a target protein. CETSA-MS integrates this approach with multiplexed quantitative MS, enabling a proteome-wide monitoring of thermal stability changes induced by sorafenib. The authors were able to identify Aldehyde Dehydrogenase 2 (ALDH2) as a target for sorafenib, and demonstrate that sorafenib inhibits ALDH2 activity, suggesting a functional role for this interaction. Sorafenib-resistant cells showed lower ALDH2 expression and activity compared to non-resistant cells. (I Ferreira et al., 2024)

This project was funded through iBET’s innovation program – iBETXplore.

Understanding the structure and properties of the SARS-CoV-2 spike protein is essential for developing effective vaccines and diagnostic assays. This was explored in two case studies involving UniMS and other iBET research teams. 

In the first case-study (B Fernandes et al., 2022), iBET researchers developed a scalable bioprocess using the insect cells-baculovirus expression vector system (IC-BEVS) to produce high-quality spike protein. UniMS provided a site-specific glycan analysis of the produced protein, ensuring its functionality and potential effectiveness in vaccine development.

In the second case-study (R Castro et al., 2021), the spike, and its receptor binding domain (RBD) were produced in two human derived cell hosts, evaluating the impact of different bioprocessing approaches on production yields. UniMS provided an in-depth characterization of the Spike and RBD proteins, namely the antigen’s oligomeric state, glycosylation profiles, and thermal stability during storage.

Host cell proteins (HCPs) are process-related impurities produced during the manufacturing of biotherapeutics, such as monoclonal antibodies (mAbs). However, some HCPs can persist after downstream processing, negatively impacting the stability, efficacy, and safety of the final product.

In this collaborative study, iBET and Sanofi researchers investigated the use of a MS-based proteomics tool, the sequential window acquisition of all theoretical fragment-ion spectra (SWATH) strategy, to monitor and quantify HCPs in mAb production. 

The SWATH-MS approach was developed for high-throughput HCP profiling. The design space of HCP clearance of two polishing resins was assessed through a DoE study. Absolute or semi-absolute quantification of all identified HCPs was achieved. It was concluded that the SWATH-MS approach enabled a deeper characterization of a mAb purification platform. (S Carvalho et al., 2024)

Predicting a patient’s outcome with Ovarian Cancer (OvC) and the onset of drug resistance are still major challenges. Chemoresistance is deeply influenced by the complex cellular interactions within the tumor microenvironment (TME), including metabolic crosstalk. Previous work from these authors demonstrated that ex vivo OvC tissue cultures retain TME components for at least four weeks of culture, allowing for drug response assessment.

In this study (R Mendes et al., 2022), researchers from iBET in collaboration with IPO Lisboa and Abbvie, utilized tissue cultures derived from 9 OvC patients and exposed these cultures to carboplatin and paclitaxel, the standard-of-care chemotherapeutics. The resulting metabolic profiles were characterized by Liquid Chromatography-Mass Spectrometry (LC-MS). 

Machine learning analysis revealed metabolic signatures that discriminate tumor tissues with higher vs. lower drug sensitivity. Additionally, potential biomarkers involved in the production of specific building blocks of cells and energy generation processes were also proposed. Overall, this study establishes a platform to explore metabolic features of the complex environment of each patient’s tumor that can underpin the discovery of biomarkers of drug response.