Infographic: Neoantigen Prediction for Personalized Vaccine Design
Infographic: Neoantigen Prediction for Personalized Vaccine Design

Infographic: Neoantigen Prediction for Personalized Vaccine Design

See how a computational pipeline uses next-generation sequencing data to identify genetic alterations that produce cancer-specific antigens.

Jul 15, 2019
Jasreet Hundal, Elaine R. Mardis

ABOVE: MODIFIED FROM
© Therese Winslow

To create an individualized cancer vaccine, researchers must identify cancer-specific peptides called neoantigens, then use a cell-, protein-, or nucleic acid–based platform to deliver those neoantigens to patients to prime the immune system to attack the tumor. Antigen-presenting cells such as dendritic cells (purple) internalize the cancer-specific peptides (bright green) selected for a personalized cancer vaccine and display them on their surface with the help of major histocompatibility complex (MHC) proteins. This triggers T cells (blue) with receptors that bind those neoantigens to differentiate into effector, or killer, T cells (green) that mobilize an immune reaction against cancer cells (orange).


In designing a vaccine that initiates this process, researchers have several options:

1. DENDRITIC CELL VACCINE

Monocytes are extracted from the blood of patients and cultured with synthetic versions of selected cancer neoantigens to form mature dendritic cells carrying those neoantigens. These cells are then reinfused into the patient’s circulation.

2. LONG PEPTIDE VACCINES

Synthetic peptides containing the neoantigen sequences are injected into the body, where they are picked up by antigen presenting cells.




3. DNA & RNA Vaccines

Nucleic acids encoding the neoantigens are introduced into the body, where they are translated into proteins and picked up by antigen presenting cells.



Before building an individualized cancer vaccine, researchers must determine which neoantigens will be included to elicit an immune response against the tumor cells. In collaboration with scientists around the world, our group has developed a computational pipeline for selecting those cancer-specific peptides that are most likely to drive a robust immune response against the tumor.

© Therese Winslow
1

DNA sequencing, alignment, and variant calling

Next-generation sequencing data from tumor and normal DNA are aligned and compared to the human reference genome and then to each other to identify tumor-specific alterations. These variants are then evaluated for their resultant changes to the amino acid sequences of the encoded proteins.

2

Epitope prediction

The selected sequences are evaluated by computer models that predict the binding of the neoantigens to the major histocompatibility complex (MHC) proteins that would present them on the surface of cells.

3

Candidate Neoantigens Filter #1

RNAseq data from tumor RNA are evaluated to ensure the predicted alterations are being made into RNA transcripts, and we can further cull the list for other reasons, such as lack of sequence coverage of that region or gene.

4

Candidate Neoantigens Filter #2

Researchers isolate MHC proteins from patients and evaluate their bound peptides by mass spectrometry to validate that these peptides are being presented by MHC. In aggregate, such data can be used to improve the computer models that predict neoantigens.

Read the full story.