> Immune repertoire deep sequencing allows comprehensive characterization of antigen receptor–encoding genes in a lymphocyte population. [...] In this study, we

> Immune repertoire deep sequencing allows comprehensive characterization of antigen receptor–encoding genes in a lymphocyte population. [...] In this study, we developed statistical classifiers of T-cell receptor (TCR) repertoires that distinguish tumor tissue from patient-matched healthy tissue of the same organ. It might be worth noting for those not familiar with the ins and outs of the immune system that (and i'm remembering this from an undergraduate degree almost twenty years ago, so E&OE): * Lymphocytes are the white blood cells whose job is to recognise foreign molecular patterns that indicate invading pathogens, tumours, etc. B-lymphocytes recognise patterns in the shape of molecules, and T-lymphocytes (studied here) recognise patterns in the sequence of proteins. * Each lymphocyte recognises a different pattern. Initially, at least - when a lymphocyte recognises something which is then classified as a threat, it multiplies itself so it can hunt it down and help destroy it. * T-lymphocytes recognise things using a protein complex called the T-cell receptor (TCR) which sits on the surface of the cell, and checks out fragments of protein presented to it by other cells. * So if they all use the same receptor, how do they recognise different patterns? Lymphocytes have this amazing mechanism where, during their initial production, they cut up and randomise key sections of the DNA for the genes encoding their receptors [1]. This is absolutely wild. * TCRs work by having a peptide-binding cleft with a specific shape and surface properties, so that only selected fragments of protein will fit it, and it's the biophysical properties of the protein sequence making up the cleft that determines that specificity. For example, if you've got some positively-charged residues at one end of the cleft, then the cleft will only bind fragments with negatively-charged residues at that end. By randomising the sequence, you randomise the specificity. So, if you look at the TCR genes a population of T-lymphocytes which is actively involved in fighting some threat, you will find that they are mostly ones which encode recognition of patterns characteristic of that threat. What this study does is come up with a way of fingerprinting a set of TCR genes so that you can decide what kind of threat they are fighting. To my naive mind, the two key ideas are (1) using some fancy machine learning model and (2) representing the TCR genes as features using biophysical properties of the proteins they encode, rather than their sequence, because ultimately it's that that determines specificity. The author is around, so hopefully he will correct me where i've gone wrong. [1] https://en.wikipedia.org/wiki/T-cell_receptor#Generation_of_the_TCR_diversity https://en.wikipedia.org/wiki/T-cell_receptor#Generation_of_...