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Objective Determine whether variation in the HLA region is associated with the development of post-traumatic sepsis and septic shock. Background Sepsis-related deaths remain a major source of mortality after traumatic injury. Genetic characteristics may contribute to susceptibility to adverse outcomes including sepsis and septic shock. Recent advances in next-generation sequencing technology now allow comprehensive genotyping of the HLA region. Methods White adult trauma patients requiring more than 2 days of mechanical ventilation underwent HLA genotyping, and were followed for the development of sepsis and septic shock. Odds ratios (OR) for the associations between our outcomes and HLA variants were estimated, a correction for multiple comparisons was applied, and significant variants were included in regression models adjusting for potential confounders. Results A total of 1184 patients were included. Patients were severely injured (median injury severity score 33); 33% developed sepsis, 6% septic shock, and in-hospital mortality was 14%. An amino acid variant (156Q) within the HLA-A peptide-binding groove was associated with greater odds of sepsis [OR 1.50, (1.18-1.89)]. HLA-A02:01 was associated with lower odds of septic shock [OR 0.52, (0.32-0.82)]. These associations remained significant after adjusting for potential confounders. Conclusions This is the first study to apply next-generation sequencing techniques to evaluate associations between immunogenetic factors and post-traumatic sepsis and septic shock. Associations with class I HLA variants are novel as they implicate adaptive immunity in post-traumatic sepsis. These findings are a step towards developing a panel of genetic markers assessing risk of infection-related complications as we move towards more personalized medicine.

The highly polymorphic human leukocyte antigen (HLA) class I molecules present peptide antigens to CD8+ T cells, inducing immunity against infections and cancers. Quality control mediated by peptide loading complex (PLC) components is expected to ensure the cell surface expression of stable peptide-HLA class I complexes. This is exemplified by HLA-B*08:01 in primary human lymphocytes, with both expression level and half-life at the high end of the measured HLA-B expression and stability hierarchies. Conversely, low expression on lymphocytes is measured for three HLA-B allotypes that bind peptides with proline at position 2, which are disfavored by the transporter associated with antigen processing. Surprisingly, these lymphocyte-specific expression and stability differences become reversed or altered in monocytes, which display larger intracellular pools of HLA class I than lymphocytes. Together, the findings indicate that allele and cell-dependent variations in antigen acquisition pathways influence HLA-B surface expression levels, half-lives and receptivity to exogenous antigens., eLife digest Most cells in the body make proteins called human leukocyte antigen class I (or HLA-I). These proteins sit on the cell surface, where they help the immune system distinguish between healthy and diseased cells. A groove in each HLA-I protein holds a fragment of a protein chain, called a peptide, from inside the cell. In healthy cells, all the peptides come from normal proteins. Yet in diseased or infected cells, the peptides may come from abnormal or foreign proteins – those encoded by viruses, for example. When the immune system sees these abnormal peptides, it responds by killing the cell. Across the human population, there are thousands of types of HLA-I, each able to carry a different set of peptides. Any individual person can only make a maximum of six types of the HLA-I, meaning we each show a different combination of peptides to our immune cells. This difference will change the way different people respond to the same disease. Before a peptide can be assembled into HLA-I, it must be moved to the correct part of the cell by a transporter known as TAP. This transport favors peptides with certain characteristics, but these characteristics do not always match the preferences of the individual's HLA-I proteins. For example, TAP is less likely to transport peptides where the second building block in the chain is a proline, but these peptides will still fit into the binding grooves of some HLA-I variants. Here, Yarzabek, Zaitouna, Olson et al. obtained blood from healthy human donors to answer questions about what happens when TAP and HLA-I have different preferences. Specifically, how many HLA-I molecules reach the surface, how long do they last, and which peptides do they carry? This analysis revealed that, when there was a mismatch between HLA-I and TAP, the amount of some HLA-I types on the surface of white blood cells called lymphocytes dropped. These HLA-I types were also able to pick up new peptides from their environment, indicating that some HLA-I were at the surface of the cell without a peptide. The role of these empty HLA-I remains to be fully defined. The reverse was true for other white blood cells called monocytes; HLA-I variants that were mismatched with TAP became more abundant on the cell surface. Monocytes also had more HLA-I molecules inside and did not pick up peptides from the environment. This suggests that monocytes may load peptides via new pathways, filling grooves left empty in lymphocytes, although other mechanisms might also explain the differences between the two types of white blood cells. Taken together, the findings reveal that HLA-I on the surface of cells depends on both the type of HLA-I and the type of immune cell. HLA-I proteins play a key role in the immune system’s ability to recognize and kill diseased cells. A better knowledge of how HLA-I variants differ could help us to understand why people respond differently to the same disease. A better grasp of HLA-I could in the future lead to improved drug and vaccine design.

The accurate and complete selection of candidate genomic regions from a DNA sample before sequencing is critical in molecular diagnostics. Several recently developed technologies await substantial improvements in performance, cost, and multiplex sample processing. Here we present the utility of long padlock probes (LPPs) for targeted exon capture followed by array-based sequencing. We found that on average 92% of 5,471 exons from 524 nuclear-encoded mitochondrial genes were successfully amplified from genomic DNA from 63 individuals. Only 144 exons did not amplify in any sample due to high GC content. One LPP was sufficient to capture sequences from

Introduction Triple-negative breast cancer (TNBC) is aggressive and lacks targeted therapies. Phosphatidylinositide 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) pathways are frequently activated in TNBC patient tumors at the genome, gene expression and protein levels, and mTOR inhibitors have been shown to inhibit growth in TNBC cell lines. We describe a panel of patient-derived xenografts representing multiple TNBC subtypes and use them to test preclinical drug efficacy of two mTOR inhibitors, sirolimus (rapamycin) and temsirolimus (CCI-779). Methods We generated a panel of seven patient-derived orthotopic xenografts from six primary TNBC tumors and one metastasis. Patient tumors and corresponding xenografts were compared by histology, immunohistochemistry, array comparative genomic hybridization (aCGH) and phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA) sequencing; TNBC subtypes were determined. Using a previously published logistic regression approach, we generated a rapamycin response signature from Connectivity Map gene expression data and used it to predict rapamycin sensitivity in 1,401 human breast cancers of different intrinsic subtypes, prompting in vivo testing of mTOR inhibitors and doxorubicin in our TNBC xenografts. Results Patient-derived xenografts recapitulated histology, biomarker expression and global genomic features of patient tumors. Two primary tumors had PIK3CA coding mutations, and five of six primary tumors showed flanking intron single nucleotide polymorphisms (SNPs) with conservation of sequence variations between primary tumors and xenografts, even on subsequent xenograft passages. Gene expression profiling showed that our models represent at least four of six TNBC subtypes. The rapamycin response signature predicted sensitivity for 94% of basal-like breast cancers in a large dataset. Drug testing of mTOR inhibitors in our xenografts showed 77 to 99% growth inhibition, significantly more than doxorubicin; protein phosphorylation studies indicated constitutive activation of the mTOR pathway that decreased with treatment. However, no tumor was completely eradicated. Conclusions A panel of patient-derived xenograft models covering a spectrum of TNBC subtypes was generated that histologically and genomically matched original patient tumors. Consistent with in silico predictions, mTOR inhibitor testing in our TNBC xenografts showed significant tumor growth inhibition in all, suggesting that mTOR inhibitors can be effective in TNBC, but will require use with additional therapies, warranting investigation of optimal drug combinations.