NEW YORK (GenomeWeb) – Researchers from the University of Montreal have developed a proteogenomic approach to identify tumor-specific antigens for use in cancer immunotherapies.
Tumor-specific antigens (TSAs) help the immune system respond to cancer, and cancer immunotherapies may target them to boost that response. But according to Montreal's Claude Perreault and his colleagues, approaches for uncovering TSAs have been beset by false-positive findings or meager yield, and have focused on mutated TSAs rather than aberrantly expressed TSAs.
Perreault and his colleagues argued that by opening up their analyses to include noncoding regions, they could boost the number of TSAs identified. As they reported today in Science Translational Medicine, the researchers applied a proteogenomic approach they developed to uncover 40 TSAs, including both mutated TSAs and expressed TSAs, within two mouse cancer cell lines and seven human primary tumors.
"[T]he strategy reported herein could considerably facilitate the identification and prioritization of actionable human TSAs," the researchers added in their paper.
The researchers' proteogenomic approach relies on the construction of a global cancer database for each sample that includes both a canonical cancer proteome and a cancer-specific proteome.
To generate the canonical proteome, the researchers map cancer RNA-sequencing reads to the reference genome and call mutations. With that, they build a personalized exome and use that to translate in silico the expressed protein-coding transcripts to develop a canonical cancer proteome.
Meanwhile, to build the cancer-specific proteome, they generate k-mers from the RNA-seq reads so they can detect peptides generated from any reading frame. They remove any cancer-derived k-mers that are also present in a control, in this case MHC IIhi medullary thymic epithelial cells. They then concatenate both the canonical and cancer-specific proteomes to develop the global cancer database.
The researchers applied this approach to two mouse tumor cell lines, the colorectal carcinoma line CT26 and the T-lymphoblastic lymphoma line EL4. By combining their global cancer database with LC-MS/MS findings, they identified six mutated TSA candidates and 15 aberrantly expressed TSA candidates. After excluding candidates found in the Immune Epitope Database or expressed in a panel of 22 tissues, the researchers were left with six mutated TSAs and 11 aberrantly expressed TSAs. Most of these TSAs were derived from atypical translation events, and many came from noncoding regions, they added.
Aberrantly expressed TSAs, the researchers noted, may be more useful clinically than mutated TSAs, since mutated TSAs are more likely to be specific to a given tumor, while aberrantly expressed TSAs could be shared across numerous tumor types.
To test whether vaccination with these TSAs affected anti-tumor response, the researchers immunized mice with TSAs uncovered in EL4 cells and then challenged those mice with EL4 cells. Three TSAs led to increased and prolonged survival in the mouse model, reaching day 150 survival rates of between 20 percent and 100 percent, depending on the TSA. A later rechallenge of surviving mice found the protection to be long lasting, the researchers reported.
Two factors, the researchers found, influenced the strength of antitumor response after vaccination: TSA expression and how common TSA-responsive T-cells are in the pre-immune repertoire.
The researchers also applied their approach to seven human primary tumor samples, including four B-ALL and three lung cancer samples. They found two mutated TSAs and 20 aberrantly expressed TSAs within these samples, work that took about two weeks.
In addition, they said their approach could help prioritize TSAs for follow up.
"Widely shared, highly abundant TSAs recognized by high-frequency T cells could then be selected for clinical trials," Perreault and his colleagues wrote. "These optimal [aberrantly expressed] TSAs could then potentially be combined in a single vaccine using already available synthesis and delivery platforms."