How Mass Spectrometry is Advancing our Understanding of Cancer

By Rebecca Ingle, Ph.DOct 20 2021

Mass spectrometry has long been a workhorse technique for chemical identification. Recent advances in the technology and hardware for mass spectrometry have seen it widely employed now as a tool for proteomics, the large-scale study of proteins.¹

Image Credit: Giovanni Cancemi/Shutterstock.com

Proteins are a common target in cancer therapies, as they are the biomolecules responsible for carrying out most biological processes. This means they are responsible for determining disease progression and outcome and can be targeted for either diagnosis or treatment. The ability to perform high throughput measurements with mass spectrometry has made it a popular tool in clinical proteomics and, in some cases, mass spectrometry is replacing antibody testing as the diagnosis of choice for different types of cancers.¹

Recent work carried out by a team of scientists lead by Trey Ideker at the University of California San Diego (UCSD) and Nevan Krogan at the University of California San Francisco (UCSF) has been exploiting recent advancements in mass spectrometry proteomics to make it possible to create structured maps of the protein assemblies in cancer cells.^2,3,4

The team has been using this to understand which genetic mutations may play a role in cancer formation and how all of the different proteins associated with breast cancers may be linked.

Genetic Sequencing

What made the expansive profiling of over 40 different proteins possible in the team’s work was the rapid sequencing times now achievable with mass spectrometry.

With advancements in electron multipliers allowing for more sensitive detection and enhanced signal to noise, as well as improved data analysis routines and sample preparation methods, it is now possible to perform network analysis on cancers that require this number of different genetic profiles.

While the team focused on breast cancers and how genetic mutations were propagated and linked to healthy and diseased cell formation, many of the types of mutations identified can be translated to other cancer types, such as head and neck squamous cell carcinomas.

The team hopes that providing full hierarchical maps of the mutational landscape relating to different cancers will make it possible to identify new targets for treatment and also for the development of new therapeutic strategies that may be able to target different areas of progression.

Biological Sampling Challenges

One of the challenges with performing any kind of analysis method on biological samples is that tissue or blood samples from patients are typically in complex environments.

Samples must be stored properly to avoid degradation but for many types of sampling, it is often not clear how quickly degradation to the proteome sets in after issue removal.¹

Microscopy is a common technique for the diagnosis of cell abnormalities but requires invasive biopsies, whereas techniques such as mass spectrometry could potentially be used with smaller sample amounts as well as different sample types, including blood.

Sample volumes are also an issue – less sensitive techniques often require larger amounts of starting samples from the patient which can introduce other issues.

Typically, proteins from patient samples are digested using a variety of preparative treatments before being introduced to the mass spectrometer for analysis. Advances in the front-end technologies for sample preparation, such as the wider availability of soft ionization techniques, have been an important step for the viability of proteomic with mass spectrometry.

Complex Systems

Mass spectrometers typically consist of three main stages. The front-end, where the sample is ionized, the ion optics, where electric fields are used to accelerate and deflect ions according to their mass to charge ratio, and the detection region, where the signals from those ions are finally recorded.

Proteins are relatively heavy and delicate biomolecules, so low-energy ionization methods are needed to form their charged ion counterparts without fragmenting the systems. The charge separation region contributes to the mass resolution of the instrument, which is crucial for protein identification as mass spectrometry relies on accurate mass detection and small differences in this to distinguish protein species and perform genetic profiling.

The detection region normally consists of some type of charge particle detector, which registers a signal when a charge species hits it. Electron multipliers are a commonly used technology, and their ability to enhance and amplify the initial electron signal from a detection event can help contribute to the sensitivity of mass spectrometry down a sub-femtomolar concentration.⁵

The Future of Mass Spectrometry in Studying Cancer

As methods for high-throughput monitoring continue to become standardized, mass spectrometry will continue to be a tool of increasing importance in developing our understanding of cancer.

Rapid genetic profiling and protein mapping is key to understand the biochemical basis of diseases and identify areas to target with new treatments.

References and Further Reading

1. A Macklin, A., Khan, S., & Kislinger, T. (2020). Recent advances in mass spectrometry based clinical proteomics: Applications to cancer research. Clinical Proteomics, 17(1), 1–25. https://doi.org/10.1186/s12014-020-09283-w

2. Kim, M., Park, J., Bouhaddou, M., Kim, K., Rojc, A., Modak, M., Soucheray, M., McGregor, M. J., O’Leary, P., Wolf, D., Stevenson, E., Foo, T. K., Mitchell, D., Herrington, K. A., Muñoz, D. P., Tutuncuoglu, B., Chen, K.-H., Zheng, F., Kreisberg, J. F., … Krogan, N. J. (2021). A protein interaction landscape of breast cancer. Science (New York, N.Y.), 374(6563), eabf3066. https://doi.org/10.1126/science.abf3066

3. Swaney, D. L., Ramms, D. J., Wang, Z., Park, J., Goto, Y., Soucheray, M., Bhola, N., Kim, K., Zheng, F., Zeng, Y., McGregor, M., Herrington, K. A., O’Keefe, R., Jin, N., VanLandingham, N. K., Foussard, H., Von Dollen, J., Bouhaddou, M., Jimenez-Morales, D., … Krogan, N. J. (2021). A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity. Science, 374(6563). https://doi.org/10.1126/science.abf2911

4. Zheng, F., Kelly, M. R., Ramms, D. J., Heintschel, M. L., Tao, K., Tutuncuoglu, B., Lee, J. J., Ono, K., Foussard, H., Chen, M., Herrington, K. A., Silva, E., Liu, S. N., Chen, J., Churas, C., Wilson, N., Kratz, A., Pillich, R. T., Patel, D. N., … Ideker, T. (2021). Interpretation of cancer mutations using a multiscale map of protein systems. Science, 374(6563). https://doi.org/10.1126/science.abf3067

5. Cunsolo, V., & Foti, S. (2019). Mass spectrometry in proteomics. Mass Spectrometry: An Applied Approach, 261–272. https://doi.org/10.1002/9781119377368.ch8

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