Assessment of monocytic HLA-DR expression in ICU patients: analytical issues for multicentric flow cytometry studies

International audienc

PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity

P16-37. HIV controllers with weak CD8+ T cell responses maintain a tight control of infection despite carrying infectious viruses

International audienc

Tumor-infiltrating lymphocytes in patients receiving trastuzumab/pertuzumab-based chemotherapy : a TRYPHAENA Substudy

Background: There is an urgent requirement to identify biomarkers to tailor treatment in human epidermal growth factor receptor 2 (HER2)-amplified early breast cancer treated with trastuzumab/pertuzumab-based chemotherapy. Methods: Among the 225 patients randomly assigned to trastuzumab/pertuzumab concurrently or sequentially with an anthracycline-containing regimen or concurrently with an anthracycline-free regimen in the Tryphaena trial, we determined the percentage of tumor-infiltrating lymphocytes (TILs) at baseline in 213 patients, of which 126 demonstrated a pathological complete response (pCR; ypT0/is ypN0), with 28 demonstrating event-free survival (EFS) events. We investigated associations between baseline TIL percentage and either pCR or EFS after adjusting for clinicopathological characteristics using logistic and Cox regression models, respectively. To understand TIL biology, we evaluated associations between baseline TILs and baseline tumor gene expression data (800 gene set by NanoString) in a subset of 173 patients. All statistical tests were two-sided. Results: Among the patients with measurable TILs at baseline, the median level was 14.1% (interquartile range = 7.1%-32.4%). After adjusting for clinicopathological characteristics, baseline percentage TIL was not associated with pCR (adjusted odds ratio [aOR] for every 10-percentage unit increase in TILs = 1.12, 95% confidence interval [CI] = 0.95 to 1.31, P = .17). At a median follow-up of 4.7 years, for every increase in baseline TILs of 10%, there was a 25% reduction in the hazard for an EFS event (aOR = 0.75, 95% CI = 0.56 to 1.00, P = .05) after adjusting for baseline clinicopathological characteristics and pCR. Additionally, genes associated with epithelial-mesenchymal transition, angiogenesis, and T-cell inhibition such as SNAIL1, ZEB1, NOTCH3, and B7-H3 were statistically significantly inversely correlated with percentage TIL. Conclusions: Baseline TIL percentage provides independent prognostic information in patients treated with trastuzumab/pertuzumab-based neoadjuvant chemotherapy. However, further validation is required

Biasogram: visualization of confounding technical bias in gene expression data.

Gene expression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factors such as RNA quality and array hybridization conditions. If such technical bias is correlated with the clinical variable of interest, the likelihood of identifying false positive genes is increased. Here we describe a method to visualize an expression matrix as a projection of all genes onto a plane defined by a clinical variable and a technical nuisance variable. The resulting plot indicates the extent to which each gene is correlated with the clinical variable or the technical variable. We demonstrate this method by applying it to three clinical trial microarray data sets, one of which identified genes that may have been driven by a confounding technical variable. This approach can be used as a quality control step to identify data sets that are likely to yield false positive results