Community assessment of methods to deconvolve cellular composition from bulk gene expression.

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Transcriptional profiling links unique human macrophage phenotypes to the growth of intracellular Salmonella enterica serovar Typhi.

Macrophages provide a crucial environment for Salmonella enterica serovar Typhi (S. Typhi) to multiply during typhoid fever, yet our understanding of how human macrophages and S. Typhi interact remains limited. In this study, we delve into the dynamics of S. Typhi replication within human macrophages and the resulting heterogeneous transcriptomic responses of macrophages during infection. Our study reveals key factors that influence macrophage diversity, uncovering distinct immune and metabolic pathways associated with different stages of S. Typhi intracellular replication in macrophages. Of note, we found that macrophages harboring replicating S. Typhi are skewed towards an M1 pro-inflammatory state, whereas macrophages containing non-replicating S. Typhi exhibit neither a distinct M1 pro-inflammatory nor M2 anti-inflammatory state. Additionally, macrophages with replicating S. Typhi were characterized by the increased expression of genes associated with STAT3 phosphorylation and the activation of the STAT3 transcription factor. Our results shed light on transcriptomic pathways involved in the susceptibility of human macrophages to intracellular S. Typhi replication, thereby providing crucial insight into host phenotypes that restrict and support S. Typhi infection.

Genetic associations with a fever after measles-containing vaccines.

Children have elevated fever risk 1 to 2 weeks after the first dose of a measles-containing vaccine (MCV), which is likely affected by genetic, immunologic, and clinical factors. Fever after MCV is associated with febrile seizures, though may also be associated with higher measles antibody titers. This exploratory study investigated genetic and immunologic associations with a fever after MCV. Concurrent with a randomized Phase 3 clinical trial of 12-15-month-olds who received their first measles-mumps-rubella (MMR) vaccine in which parents recorded post-vaccination temperatures daily, we consented a subset to collect additional blood and performed human leukocyte antigens (HLA) typing. Association between fever 5-12 days after MMR ("MMR-associated") and HLA type was assessed using logistic regression. We compared 42-day post-vaccination geometric mean titers (GMT) to measles between children who did and did not have fever using a t-test. We enrolled 86 children and performed HLA typing on 82; 13 (15.1%) had MMR-associated fever. Logistic regressions identified associations between MMR-associated fever and HLA Class I loci A-29:02 (P = .036), B-57:01 (P = .018), C-06:02 (P = .006), C-14:02 (P = .022), and Class II loci DRB1-15 (P = .045). However, Bonferroni's adjustment for multiple comparisons suggests that these associations could have been due to chance. Ninety-eight percent of children had protective antibody titers to measles; however, GMT was higher among those with fever compared with children without fever (P = .006). Fever after the measles vaccine correlated with genetic factors and higher immune response. This study suggests a possible genetic susceptibility to MMR-associated fever.

Workflow optimization of whole genome amplification and targeted panel sequencing for CTC mutation detection.

Genomic characterization of circulating tumor cells (CTCs) may prove useful as a surrogate for conventional tissue biopsies. This is particularly important as studies have shown different mutational profiles between CTCs and ctDNA in some tumor subtypes. However, isolating rare CTCs from whole blood has significant hurdles. Very limited DNA quantities often can't meet NGS requirements without whole genome amplification (WGA). Moreover, white blood cells (WBC) germline contamination may confound CTC somatic mutation analyses. Thus, a good CTC enrichment platform with an efficient WGA and NGS workflow are needed. Here, Vortex label-free CTC enrichment platform was used to capture CTCs. DNA extraction was optimized, WGA evaluated and targeted NGS tested. We used metastatic colorectal cancer (CRC) as the clinical target, HCT116 as the corresponding cell line, GenomePlex® and REPLI-g as the WGA methods, GeneRead DNAseq Human CRC Panel as the 38 gene panel. The workflow was further validated on metastatic CRC patient samples, assaying both tumor and CTCs. WBCs from the same patients were included to eliminate germline contaminations. The described workflow performed well on samples with sufficient DNA, but showed bias for rare cells with limited DNA input. REPLI-g provided an unbiased amplification on fresh rare cells, enabling an accurate variant calling using the targeted NGS. Somatic variants were detected in patient CTCs and not found in age matched healthy donors. This demonstrates the feasibility of a simple workflow for clinically relevant monitoring of tumor genetics in real time and over the course of a patient's therapy using CTCs.

Sample matching by inferred agonal stress in gene expression analyses of the brain.

BACKGROUND: Gene expression patterns in the brain are strongly influenced by the severity and duration of physiological stress at the time of death. This agonal effect, if not well controlled, can lead to spurious findings and diminished statistical power in case-control comparisons. While some recent studies match samples by tissue pH and clinically recorded agonal conditions, we found that these indicators were sometimes at odds with observed stress-related gene expression patterns, and that matching by these criteria still sometimes results in identifying case-control differences that are primarily driven by residual agonal effects. This problem is analogous to the one encountered in genetic association studies, where self-reported race and ethnicity are often imprecise proxies for an individual's actual genetic ancestry. RESULTS: We developed an Agonal Stress Rating (ASR) system that evaluates each sample's degree of stress based on gene expression data, and used ASRs in post hoc sample matching or covariate analysis. While gene expression patterns are generally correlated across different brain regions, we found strong region-region differences in empirical ASRs in many subjects that likely reflect inter-individual variabilities in local structure or function, resulting in region-specific vulnerability to agonal stress. CONCLUSION: Variation of agonal stress across different brain regions differs between individuals, revealing a new level of complexity for gene expression studies of brain tissues. The Agonal Stress Ratings quantitatively assess each sample's extent of regulatory response to agonal stress, and allow a strong control of this important confounder.

Systematic changes in gene expression in postmortem human brains associated with tissue pH and terminal medical conditions.

Studies of gene expression abnormalities in psychiatric or neurological disorders often involve the use of postmortem brain tissue. Compared with single-cell organisms or clonal cell lines, the biological environment and medical history of human subjects cannot be controlled, and are often difficult to document fully. The chance of finding significant and replicable changes depends on the nature and magnitude of the observed variations among the studied subjects. During an analysis of gene expression changes in mood disorders, we observed a remarkable degree of natural variation among 120 samples, which represented three brain regions in 40 subjects. Most of such diversity can be accounted for by two distinct expression patterns, which in turn are strongly correlated with tissue pH. Individuals who suffered prolonged agonal states, such as with respiratory arrest, multi-organ failure or coma, tended to have lower pH in the brain; whereas those who experienced brief deaths, associated with accidents, cardiac events or asphyxia, generally had normal pH. The lower pH samples exhibited a systematic decrease in expression of genes involved in energy metabolism and proteolytic activities, and a consistent increase of genes encoding stress-response proteins and transcription factors. This functional specificity of changed genes suggests that the difference is not merely due to random RNA degradation in low pH samples; rather it reflects a broad and actively coordinated biological response in living cells. These findings shed light on critical molecular mechanisms that are engaged during different forms of terminal stress, and may suggest clinical targets of protection or restoration.