Mining the plasma immunopeptidome for cancer peptides as biomarkers and beyond

Hickman, Heather D.; Yewdell, Jonathan W.

doi:10.1073/pnas.1013851107

Cited by 13 publications

(11 citation statements)

References 20 publications

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“…We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field. The immunopeptidome is referred to as the collection of peptides associated with and presented by major histocompatibility complex (MHC) molecules (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11). MHC-associated peptides are recognized by T lymphocytes that are in turn activated to eliminate abnormal cells such as pathogen-infected and cancer cells.…”

mentioning

confidence: 99%

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry*

Caron

Kowalewski

Koh

et al. 2015

Molecular & Cellular Proteomics

194

118

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The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field. Molecular & Cellular

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mentioning

confidence: 99%

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry*

Caron

Kowalewski

Koh

et al. 2015

Molecular & Cellular Proteomics

194

118

View full text Add to dashboard Cite

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“…Using the RF algorithm, trained with the entire database, effectively the dignity (benign or malignant) of samples could be determined on protein level as well as by typing based on solely the top 20 benign and malignant associated antigens. The extensive peptide diversity in various tissues and the high sensitivity of mass spectrometry highlight the potential use of immunopeptidomic for antigen classification and biomarker diagnostics for cancer testing and further diseases 50,51 .…”

Section: Discussionmentioning

confidence: 99%

An innovative approach for HLA typing, molecular tumor testing and the validation of tumor exclusive antigens

Ghosh

Bichmann

Scheid

et al. 2020

Preprint

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The immunopeptidome, representing the point of contact between somatic and T cells, is key for adaptive immunity. Each presented peptide holds an abundance of information not yet well understood. Up to now, the scientific focus has been the definition of pathogenic or tumor derived epitopes and the deconvolution of HLA peptide motifs of the entire immunopeptidome. Here we go one step further and assess the properties of individual peptides to identify defined HLA allotype-specific and frequently presented peptides. Such allotypic peptides represent a versatile tool to determine HLA allotypes or serve as internal standard for characterization of cancer antigens and differentially processed antigens. Finally, individual tissue-and dignity-specific antigens were defined, and the latter were successfully implemented for molecular tumor testing.Using mass spectrometry based immunopeptidomics a database was generated consisting of ~900 HLA-typed samples. The identified allotypic peptides enabled a HLA class I allotype determination, which was 95% correct in our in-house dataset and 98% in an external dataset.These abundant peptides were implemented as internal standard for a semi-quantitative investigation of established tumor antigens and antigens processed differentially in malignant and benign tissue. Defined dignity-specific antigens allowed a 87% correct tumor detection across numerous tumor types.In summary, we describe a machine learning approach for mining immunopeptidomic data in order to develop a classification method, allowing to differentiate HLA class I-allotypes of a sample or distinguish between healthy and malignant state of tissues. Furthermore, based on this method, we developed a procedure for the validation of tumor exclusive antigens. Our results support classification of immunopeptidomic data sets using machine learning and highlight their potential utility for biomarker development.

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“…Due to the highly complex nature of peptide/HLA pools, current methods for mining the immunopeptidome for HLA associated biomarkers are time consuming. This process requires the affinity purification of soluble HLA from plasma, separation of HLA associated peptides by reverse phase high pressure liquid chromatography (RP-HPLC) and peptide sequencing by tandem mass spectrometry (MS/MS) 6,7 . Although this process is a viable option for the discovery of novel therapeutic targets, it is a cumbersome process as a companion diagnostic tool for HLA associated targets already in the therapeutic vaccine or biopharmaceutical pipeline [8][9][10] .…”

Section: Introductionmentioning

confidence: 99%

Detection of Human Leukocyte Antigen Biomarkers in Breast Cancer Utilizing Label-free Biosensor Technology

Weidanz

Doll

Mohanasundaram

et al. 2015

JoVE

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According to the American Cancer Society, more than 200,000 women will be diagnosed with invasive breast cancer each year and approximately 40,000 will die from the disease. The human leukocyte antigen (HLA) class I samples peptides derived from proteasomal degradation of cellular proteins and presents these fragments on the cell surface for interrogation by circulating cytotoxic T lymphocytes (CTL). Generation of T-cell receptor mimic (TCRm) monoclonal antibodies (mAbs) which recognize breast cancer specific peptide/HLA-A*02:01 complexes such as those derived from macrophage migration inhibitory factor ) and NY-ESO-1 157-165 enable detection and destruction of breast cancer cells in the absence of an effective anti-tumor CTL response. Intact class I HLA/peptide complexes are shed by breast cancer cells and represent potentially relevant cancer biomarkers. In this work, a breakthrough biomarker screening system for cancer diagnostics incorporating T-cell receptor mimic monoclonal antibodies combined with a novel, label-free biosensor utilizing guided-mode resonance (GMR) sensor technology is presented. Detection of shed MIF/HLA-A*02:01 complexes in MDA-MB-231 cell supernatants, spiked human serum, and patient plasma is demonstrated. The impact of this work could revolutionize personalized medicine through development of companion disease diagnostics for targeted immunotherapies.

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Mining the plasma immunopeptidome for cancer peptides as biomarkers and beyond

Cited by 13 publications

References 20 publications

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry*

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry*

An innovative approach for HLA typing, molecular tumor testing and the validation of tumor exclusive antigens

Detection of Human Leukocyte Antigen Biomarkers in Breast Cancer Utilizing Label-free Biosensor Technology

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