MedGenome’s OncoPeptTUME identifies Immunogenic Features of Prognosis in Human Cancers

By Dr. Malini Manoharan – Bioinformatics Scientist-II, MedGenome Labs

Cancer immunologists scooped the 2018 medicine noble prize for pioneering treatments that unleash the body’s own immune system to attack cancer cells. It represents a completely new principle which unlike the previous strategies that target the cancer cells, rather targets the brakes — the checkpoints — of the host immune system.

Immunotherapy based on check point inhibitors has shown astounding clinical success with countess patients with varied tumor types showing a pronounced clinical response, however, many more patients show a decreased or no clinical benefit. Understanding the complexity and diversity of the tumor microenvironment in the context of its immune composition can largely improve patient stratification. To this end, MedGenome has developed

Figure 1. Role of checkpoint inhibitors in immunotherapy.

OncoPeptTUME, a genomic solution that utilizes its highly cell-type specific proprietary minimal gene expression signature to characterize the composition of currently 8 different immune cells. The expression of genes for a given signature is transformed to produce a cell-type specific immune score that is used to quantitate the relative proportion of cell types present in the tumor microenvironment (Figure 2).

Figure 2: Creation and validation of minimal gene expression signature profile (MGESP) for eight different immune cells. Workflow of the OncopeptTUME platform.

Pan cancer analysis of the TCGA data using OncoPeptTUME revealed immunogenic features that impact prognosis in human cancers. Our analysis revealed that CD8+ T cells expressing higher levels of anergic and exhaustion markers, which are hallmarks of dysfunctional T-cells were enriched in the deceased group compared to the alive group. The analysis published recently (Manoharan et al., 2018) reveals critical determinants of long-term survival pointing to an integrated approach that can be designed for selecting patients who will benefit from cancer immunotherapy treatment.

Manoharan Malini, Mandloi Nitin, Priyadarshini Sushri, Patil Ashwini, Gupta Rohit, Iyer Laxman, Gupta Ravi, Chaudhuri Amitabha (2018). A Computational Approach 1dentifies 1mmunogenic Features of Prognosis in Human Cancers. Front. Immunol., 9.

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