Advancing Antigen Discovery With Microfluidics Automation for Sparse Samples

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Our group at the Ludwig Institute for Cancer Research in Lausanne, Switzerland, has published an innovative method in Cell Reports Methods for tumor antigen discovery. Our automated and cost-effective workflow in immunopeptidomics, utilizing microfluidics technology, overcomes limitations in sample preparation, particularly the immunoaffinity purification (IP) of human leukocyte antigen (HLA)-restricted peptides. This novel method enables sensitive detection of multiple immunogenic tumor-associated antigens from small clinical tumor biopsies, making it a powerful tool for antigen discovery in sparse samples.

Mass spectrometry (MS)-based immunopeptidomics is a valuable method for identifying peptides presented by HLA molecules on cell surfaces, which are essential for T cell-mediated immune responses. The unique immunopeptidomes of cancer cells offer potential targets for immunotherapies like cancer vaccines and adoptive cell transfer therapies. MS is crucial for comprehensive peptide analysis, but current sample preparation methods for immunopeptidomics are laborious and hinder large-scale clinical applications. Existing alternatives, such as robotic platforms, are costly, posing financial burdens for many laboratories. The study aimed to develop an automated, cost-effective and efficient microfluidics-based workflow for sensitive immunopeptidomics to overcome these challenges.

We developed an automated and cost-effective workflow for immunopeptidomics by utilizing microfluidics technology to overcome the limitations of existing sample preparation methods, especially for the IP of HLA-restricted peptides. We engineered a microfluidic platform with a meta-array of micropillars to enhance immunoaffinity interactions. The platform incorporated a programmable fluidic control system for the IP procedure and integrated C18 cartridges for sample clean-up. This workflow streamlines the sample preparation process and reduces material consumption, leading to enhanced target purification. We demonstrated the performance of our approach by analyzing low-input samples and tumor biopsies, leveraging data-independent acquisition computational methods for sensitive detection of tumor antigens using MS. The novel microfluidics-based workflow showed competitive performance over the traditional one, offering an automated, cost-effective and efficient solution for immunopeptidomics analysis.

The key findings of the paper were:

The newly created microfluidics-based workflow presents an automated and user-friendly system for immunopeptidomics. This is achieved by reducing the sample volume and integrating purification steps, resulting in enhanced assay efficiency. Additionally, with continuing developments allowing for scalability, larger-scale studies and potential clinical applications can be pursued in the future. Furthermore, in comparison to costly robotic liquid handling platforms, the microfluidics approach offers a cost-effective alternative, making immunopeptidomics analysis accessible to a broader spectrum of research laboratories.

The combination of microfluidics technology and data-independent acquisition computational approaches enables sensitive and reliable identification of tumor antigens. This can significantly contribute to the discovery of cancer-specific peptide antigens, which are crucial for developing targeted T cell-mediated cancer therapies, including TCR-T therapy and cancer vaccines. The ability to detect these antigens accurately and characterize them can potentially lead to the development of more effective personalized cancer treatments.

Microfluidics devices' ability to handle sub-milliliter sample volumes makes them suitable for analyzing limited clinical samples such as liquid biopsies or small tumor biopsies. This capability opens up opportunities for studying immunopeptidomes in situations where sample availability is limited. It can provide valuable insights into cancer-specific peptide antigens and immunogenic tumor-associated antigens, potentially leading to a better understanding of immune responses in cancer and the development of targeted therapies.

The impact of this study lies in its advancements in the field of immunopeptidomics. By introducing an inexpensive, automated and easy-to-operate workflow using microfluidics technology, the study addresses bottlenecks in sample preparation and enhances target purification. This has significant implications for cancer research and personalized cancer therapies. The study enables more efficient and cost-effective analysis of tumor antigens, leading to the discovery of cancer-specific peptide antigens and immunogenic tumor-associated antigens. This knowledge can potentially revolutionize the development of targeted T cell-mediated cancer therapies, such as TCR-T therapy and cancer vaccines. Moreover, the ability to handle scarce clinical samples expands the possibilities for studying immunopeptidomes and improving our understanding of immune responses in cancer.

While the study on the automated microfluidics workflow for immunopeptidomics brings significant advancements, it also has certain limitations that should be acknowledged. The evaluation of the workflow's performance was mainly conducted using low-input samples and tumor biopsies. It is crucial to assess its applicability and performance across a broader range of sample types, including different cancer types and various biological fluids. Validation studies on a larger scale and diverse patient cohorts are necessary to establish the reliability and reproducibility of the approach. Another limitation is that the study does not address the potential challenges associated with analysis of peptides restricted by other HLA classes, such as Class II HLAs. Factors such as scalability, cost-effectiveness and integration with existing clinical workflows need to be considered for successful translation into large-scale clinical applications.

In the future, efforts should be directed towards scaling up the assay throughput by incorporating multiple microfluidics modules in a relatively cost-effective and small footprint. An intuitive system control interface and packaged chip devices should be implemented to allow inexperienced users to handle the platform effortlessly.

To validate the clinical utility of the workflow, large-scale validation studies involving a substantial number of patient samples should be conducted. This will enable the assessment of its diagnostic and prognostic capabilities and provide evidence for its effectiveness in personalized cancer treatment.

Reference: Li X, Pak HS, Huber F, et al. A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics. Cell Rep Methods. 2023;3(6):100479. doi:10.1016/j.crmeth.2023.100479

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