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Developing AFFIRM assays for detection of potential biomarkers for relapsed breast cancer in plasma

Kadamalakunte Narayana, Sumana LU (2016) KIMM01 20161
Educational programmes, LTH
Department of Immunotechnology
Abstract
Today, breast cancer is the leading cause of cancer related death in women. Early detection of breast cancer relapse presents increased treatment options and better control. Protein biomarkers from plasma are currently measured by state-of-the-art methods like ELISA, which require antibodies with high sensitivity and specificity. Developing such assays is laborious and time consuming. Thus, there is a great need for developing alternative quicker analysis methods for protein detection. Selected Reaction Monitoring (SRM) provides a specific readout where peptides unique to protein of interest are measured selectively. SRM assays are easier and quicker to develop. AFFIRM (AFFInity sRM) is an established platform that combines the sensitivity... (More)
Today, breast cancer is the leading cause of cancer related death in women. Early detection of breast cancer relapse presents increased treatment options and better control. Protein biomarkers from plasma are currently measured by state-of-the-art methods like ELISA, which require antibodies with high sensitivity and specificity. Developing such assays is laborious and time consuming. Thus, there is a great need for developing alternative quicker analysis methods for protein detection. Selected Reaction Monitoring (SRM) provides a specific readout where peptides unique to protein of interest are measured selectively. SRM assays are easier and quicker to develop. AFFIRM (AFFInity sRM) is an established platform that combines the sensitivity of antibody antigen capture and specificity of SRM readout to develop robust assays for detection and quantification of proteins. This project aimed at developing such AFFIRM assays for 30 proteins indicated to be associated with breast cancer relapse. AFFIRM uses antibodies in the form of single chain variable fragments (scFv) immobilized on MagneHis beads to capture the proteins from plasma, followed by protein digestion and SRM assay readout. More specifically in this work, trypsin digestion conditions were optimized. The developed assays were tested in single- and multiplex modes. Assays for 22 out of 30 proteins could successfully measure its target proteins at 50 ng concentration in single-plex mode; 19 out of 30 were successful in multiplex mode, i.e. measuring all 19 target proteins in parallel in the same analysis. (Less)
Popular Abstract
Breast cancer is the leading cancer in women worldwide. Every year, 1.6 million women are diagnosed with it, out of which 58% die due to the cancer. The incidence is rising rapidly in developing countries. Even though there are several treatments, inability to detect the cancer at an early stage limits the possibilities of curing it in time. After a patient has been treated for cancer and has completed his/ her treatment they are happy to have won the biggest battle of their life and survived it. But after a few months or a year, or even several years, they are struck by the news from the doctor that the cancer is back, which is called a relapse. In most breast cancer cases, death is caused from the relapse rather than the initial cancer.... (More)
Breast cancer is the leading cancer in women worldwide. Every year, 1.6 million women are diagnosed with it, out of which 58% die due to the cancer. The incidence is rising rapidly in developing countries. Even though there are several treatments, inability to detect the cancer at an early stage limits the possibilities of curing it in time. After a patient has been treated for cancer and has completed his/ her treatment they are happy to have won the biggest battle of their life and survived it. But after a few months or a year, or even several years, they are struck by the news from the doctor that the cancer is back, which is called a relapse. In most breast cancer cases, death is caused from the relapse rather than the initial cancer. Therefore, it is necessary to develop methods which detect the relapse early and ensure appropriate treatment can be given or relapse can be prevented. The most easily available sample for testing is plasma from the patient’s blood. Presence of cancer can be detected by testing for certain protein biomarkers (target proteins) that would be present in the plasma in case the patient is suffering from the cancer or if the cancer is relapsing.
Antibodies are proteins that possess the property to bind specifically to targets. Since they are highly sensitive and bind only to their targets, they are used to detect presence of proteins. ELISA is a standard methods used to confirm presence of biomarkers. ELISA used 2 antibodies- primary to bind the target specifically and secondary antibody which a fluorescent tag to measure the amount of bound target protein. Such antibody- based methods are sensitive but are available only for a few proteins and developing them is very demanding and expensive. We have therefore developed assays for another technology. Mass spectrometry is a technology that identifies proteins based on their mass to charge ratio. Digesting a protein with an enzyme like Trypsin results in fragments of the protein called peptides. The type of Mass spectrometry that was used in this study is called Selected Reaction Monitoring (SRM), where we specify to the instrument the peptides that are unique to the target protein and it would detect only these peptides. It is a much easier and faster technique as SRM looks for the specific peptides rather than scanning all the peptides and then identifying the target. AFFIRM is a platform that combines antibody and mass spectrometry technologies to detect and quantify proteins. We produced antibodies that would bind specifically to the target proteins and the antibodies were bound to magnetic beads. When the beads carrying the antibodies were exposed to the plasma spiked with the artificial target proteins, the targets bind to the antibody. This is followed by digestion by an enzyme like Trypsin to cut the protein into several peptides. The sample is then analyzed using the SRM. Development of SRM assays for each of the 30 target proteins was attempted and 19 of them were successfully developed. SRM assays help to pin point if a protein is present in the sample or not, and does it even when the protein content is quite low (sensitive). This way we can identify at a much faster rate that the person is suffering from breast cancer relapse. The developed assays showed promising results in lab tests; it would next be confirmed using labelled heavy peptides. We aim to apply the developed assays to clinical samples from breast cancer patients collected at primary diagnosis and at later recurrence. If successful, it has potential to speed-up the diagnosis process for breast cancer relapse. (Less)
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author
Kadamalakunte Narayana, Sumana LU
supervisor
organization
course
KIMM01 20161
year
type
H2 - Master's Degree (Two Years)
subject
keywords
breast cancer, biomarkers, relapse, antibodies, mass spectrometry, trypsin, protease inhibitors, immunotechnology
language
English
additional info
This Master thesis project was carried out at the Institution of Immunotechnology, Faculty of Engineering, Lund University, Sweden. The project lasted for a duration of 20 weeks starting January 2016 till June 2016. The objective was to develop an assay for detection of breast cancer biomarker proteins in plasma and contribute to society by delivering a technology that may aid in detecting breast cancer relapse at an earlier stage.
The project has helped me learn new concepts and technologies and aided my growth as an early researcher. I hereby express my heartfelt gratitude for being given the opportunity to work on this project. I would like to thank my supervisor, Dr. Sofia Waldemarson for guiding me through the course, Oladapo Olaleyo (co-worker) and everybody at the Institution of Immunotechnology, Lund University who made it possible to perform this work. I would also like to thank Fredrik Levander, for reviewing my work and giving his insights to it.
id
8881042
date added to LUP
2016-06-22 13:21:55
date last changed
2016-06-22 13:21:55
@misc{8881042,
  abstract     = {Today, breast cancer is the leading cause of cancer related death in women. Early detection of breast cancer relapse presents increased treatment options and better control. Protein biomarkers from plasma are currently measured by state-of-the-art methods like ELISA, which require antibodies with high sensitivity and specificity. Developing such assays is laborious and time consuming. Thus, there is a great need for developing alternative quicker analysis methods for protein detection. Selected Reaction Monitoring (SRM) provides a specific readout where peptides unique to protein of interest are measured selectively. SRM assays are easier and quicker to develop. AFFIRM (AFFInity sRM) is an established platform that combines the sensitivity of antibody antigen capture and specificity of SRM readout to develop robust assays for detection and quantification of proteins. This project aimed at developing such AFFIRM assays for 30 proteins indicated to be associated with breast cancer relapse. AFFIRM uses antibodies in the form of single chain variable fragments (scFv) immobilized on MagneHis beads to capture the proteins from plasma, followed by protein digestion and SRM assay readout. More specifically in this work, trypsin digestion conditions were optimized. The developed assays were tested in single- and multiplex modes. Assays for 22 out of 30 proteins could successfully measure its target proteins at 50 ng concentration in single-plex mode; 19 out of 30 were successful in multiplex mode, i.e. measuring all 19 target proteins in parallel in the same analysis.},
  author       = {Kadamalakunte Narayana, Sumana},
  keyword      = {breast cancer,biomarkers,relapse,antibodies,mass spectrometry,trypsin,protease inhibitors,immunotechnology},
  language     = {eng},
  note         = {Student Paper},
  title        = {Developing AFFIRM assays for detection of potential biomarkers for relapsed breast cancer in plasma},
  year         = {2016},
}