Kinase Activity Mapping from Proteome Phosphorylation Data in a Breast Cancer Cohort
(2025) KIMM01 20251Department of Immunotechnology
- Abstract
- Phosphorylation is one of the main post-translational modifications (PTMs) regulating protein function, where kinases reversibly add phosphate groups to specific amino acid residues (phosphosites). Kinase activity is altered in breast cancer (BC), resulting in loss of regulation of several cellular processes. Phosphoproteomics emerges as a powerful approach for profiling samples at phosphosite level, with the potential to identify kinase-driven BC subtypes and guide subsequent treatments. The aim of the present master’s thesis was to conduct a functional analysis of data-independent acquisition (DIA) mass spectrometry phosphoproteomic data from a BC cohort. The data filtering strategy was intended to prioritise low-abundance phosphosites.... (More)
- Phosphorylation is one of the main post-translational modifications (PTMs) regulating protein function, where kinases reversibly add phosphate groups to specific amino acid residues (phosphosites). Kinase activity is altered in breast cancer (BC), resulting in loss of regulation of several cellular processes. Phosphoproteomics emerges as a powerful approach for profiling samples at phosphosite level, with the potential to identify kinase-driven BC subtypes and guide subsequent treatments. The aim of the present master’s thesis was to conduct a functional analysis of data-independent acquisition (DIA) mass spectrometry phosphoproteomic data from a BC cohort. The data filtering strategy was intended to prioritise low-abundance phosphosites. A total of 50 phosphosites were found to be significantly different between the clinical groups, and enabled partial separation of lobular and ductal BC samples in a two-component probabilistic principal component analysis (PPCA). Phosphosite-to-kinase inference was conducted using PTM-Signature Enrichment Analysis (PTM-SEA) and the Integrative iNferred Kinase Activity (INKA) tool. PTM-SEA inferred 17 kinases that showed differential activity. INKA was successfully adapted to the DIA neuronal network (DIA-NN) workflow and inferred 5 kinases that were found significantly different. No group-specific kinase activity was detected when using either PTM-SEA or INKA, and samples did not cluster into their clinical groups in PPCAs based on the significantly different kinase activities inferred from the tools. Nevertheless, PTM-SEA results allowed for unsupervised clustering of sample groups in correspondance with clinical parameters and offered both positive and negative enrichment scores, providing a more comprehensive analysis than INKA. (Less)
- Popular Abstract
- Cells are the building blocks of the human body. Within cells, different activities like energy production or cell growth take place. These activities are mainly controlled by proteins called enzymes.
But not everything inside a cell is required to occur at once or all the time. Cells have different ways of turning certain processes “on” or “off” when needed. One of these ways is by making small chemical changes to proteins, basically, adding or removing certain groups. This is the case of phosphorylation, where a small chemical group called “phosphate” is added to a protein, thus switching “on” or “off” a process. Phosphorylation occurs thanks to special enzymes called protein kinases in specific places of the protein called phosphosite.... (More) - Cells are the building blocks of the human body. Within cells, different activities like energy production or cell growth take place. These activities are mainly controlled by proteins called enzymes.
But not everything inside a cell is required to occur at once or all the time. Cells have different ways of turning certain processes “on” or “off” when needed. One of these ways is by making small chemical changes to proteins, basically, adding or removing certain groups. This is the case of phosphorylation, where a small chemical group called “phosphate” is added to a protein, thus switching “on” or “off” a process. Phosphorylation occurs thanks to special enzymes called protein kinases in specific places of the protein called phosphosite. Protein kinases are very important because they help control many processes in the cell and, If they do not work properly, they can lead to diseases like cancer. In breast cancer, for instance, protein kinases are dysregulated. However, traditional breast cancer classifications often focus on only a few known proteins, leaving out most of the complex inner workings of the cell.
In this project, we studied phosphosites (the places where phosphate groups are added to proteins) in breast cancer tumours from patients. When identifying and analysing all the phosphosites using computer-based tools, we tried to predict which protein kinases might be responsible for the detected phosphosites in different types of breast cancer. This information could help in better understanding the disease and possibly lead to improved diagnosis or treatment in the future.
A total of 50 phosphosites showed differential phosphorylation when comparing subgroups of tumours, and some of them helped in partially differentiating two breast cancer types. Two computer-based tools were used to try to predict the activity of the protein kinases based on the phosphosite abundances of each sample. The first tool, named PTM-SEA, found 17 protein kinases with different activity between subgroups of tumours. The other tool, the INKA tool, only found 5 protein kinases that differed across subgroups of tumours. These findings suggest that kinase mapping tools can reveal tumour-associated protein kinase activities beyond individual phosphosite abundances. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9201372
- author
- Castilla Maldonado, Ignacio LU
- supervisor
- organization
- course
- KIMM01 20251
- year
- 2025
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Breast cancer, Phosphoproteomics, Phosphosites, Phosphosite-to-kinase inference, PTM-SEA, INKA, Pharmaceutical technology
- language
- English
- id
- 9201372
- date added to LUP
- 2025-06-18 15:40:51
- date last changed
- 2025-06-18 15:40:51
@misc{9201372,
abstract = {{Phosphorylation is one of the main post-translational modifications (PTMs) regulating protein function, where kinases reversibly add phosphate groups to specific amino acid residues (phosphosites). Kinase activity is altered in breast cancer (BC), resulting in loss of regulation of several cellular processes. Phosphoproteomics emerges as a powerful approach for profiling samples at phosphosite level, with the potential to identify kinase-driven BC subtypes and guide subsequent treatments. The aim of the present master’s thesis was to conduct a functional analysis of data-independent acquisition (DIA) mass spectrometry phosphoproteomic data from a BC cohort. The data filtering strategy was intended to prioritise low-abundance phosphosites. A total of 50 phosphosites were found to be significantly different between the clinical groups, and enabled partial separation of lobular and ductal BC samples in a two-component probabilistic principal component analysis (PPCA). Phosphosite-to-kinase inference was conducted using PTM-Signature Enrichment Analysis (PTM-SEA) and the Integrative iNferred Kinase Activity (INKA) tool. PTM-SEA inferred 17 kinases that showed differential activity. INKA was successfully adapted to the DIA neuronal network (DIA-NN) workflow and inferred 5 kinases that were found significantly different. No group-specific kinase activity was detected when using either PTM-SEA or INKA, and samples did not cluster into their clinical groups in PPCAs based on the significantly different kinase activities inferred from the tools. Nevertheless, PTM-SEA results allowed for unsupervised clustering of sample groups in correspondance with clinical parameters and offered both positive and negative enrichment scores, providing a more comprehensive analysis than INKA.}},
author = {{Castilla Maldonado, Ignacio}},
language = {{eng}},
note = {{Student Paper}},
title = {{Kinase Activity Mapping from Proteome Phosphorylation Data in a Breast Cancer Cohort}},
year = {{2025}},
}