Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing.

Human tumours typically harbour a remarkable number of somatic mutations. If presented on major histocompatibility complex class I molecules (MHCI), peptides containing these mutations could potentially be immunogenic as they should be recognized as 'non-self' neo-antigens by the adaptive immune system. Recent work has confirmed that mutant peptides can serve as T-cell epitopes. However, few mutant epitopes have been described because their discovery required the laborious screening of patient tumour-infiltrating lymphocytes for their ability to recognize antigen libraries constructed following tumour exome sequencing. We sought to simplify the discovery of immunogenic mutant peptides by characterizing their general properties. We developed an approach that combines whole-exome and transcriptome sequencing analysis with mass spectrometry to identify neo-epitopes in two widely used murine tumour models. Of the >1,300 amino acid changes identified, ∼13% were predicted to bind MHCI, a small fraction of which were confirmed by mass spectrometry. The peptides were then structurally modelled bound to MHCI. Mutations that were solvent-exposed and therefore accessible to T-cell antigen receptors were predicted to be immunogenic. Vaccination of mice confirmed the approach, with each predicted immunogenic peptide yielding therapeutically active T-cell responses. The predictions also enabled the generation of peptide-MHCI dextramers that could be used to monitor the kinetics and distribution of the anti-tumour T-cell response before and after vaccination. These findings indicate that a suitable prediction algorithm may provide an approach for the pharmacodynamic monitoring of T-cell responses as well as for the development of personalized vaccines in cancer patients.

A hierarchy of self-renewing tumor-initiating cell types in glioblastoma.

The neural stem cell marker CD133 is reported to identify cells within glioblastoma (GBM) that can initiate neurosphere growth and tumor formation; however, instances of CD133(-) cells exhibiting similar properties have also been reported. Here, we show that some PTEN-deficient GBM tumors produce a series of CD133(+) and CD133(-) self-renewing tumor-initiating cell types and provide evidence that these cell types constitute a lineage hierarchy. Our results show that the capacities for self-renewal and tumor initiation in GBM need not be restricted to a uniform population of stemlike cells, but can be shared by a lineage of self-renewing cell types expressing a range of markers of forebrain lineage.