Whole blood transcriptomics identifies subclasses of pediatric septic shock.

BACKGROUND: Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. METHODS: The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. RESULTS: Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires. CONCLUSIONS: Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock.

Background: Sepsis is a highly heterogeneous syndrome, that has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. Methods: The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA-sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. Results: Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells, and less diverse T-Cell receptor repertoires. Conclusions: Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration: This is a secondary analysis of data generated as part of the observational CAF PINT ancillary of the HALF PINT study (NCT01565941). Registered 29 March 2012.

Rigorous benchmarking of T-cell receptor repertoire profiling methods for cancer RNA sequencing.

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research.

T cell receptor (TCR) studies have grown substantially with the advancement in the sequencing techniques of T cell receptor repertoire sequencing (TCR-Seq). The analysis of the TCR-Seq data requires computational skills to run the computational analysis of TCR repertoire tools. However biomedical researchers with limited computational backgrounds face numerous obstacles to properly and efficiently utilizing bioinformatics tools for analyzing TCR-Seq data. Here we report pyTCR, a computational notebook-based solution for comprehensive and scalable TCR-Seq data analysis. Computational notebooks, which combine code, calculations, and visualization, are able to provide users with a high level of flexibility and transparency for the analysis. Additionally, computational notebooks are demonstrated to be user-friendly and suitable for researchers with limited computational skills. Our tool has a rich set of functionalities including various TCR metrics, statistical analysis, and customizable visualizations. The application of pyTCR on large and diverse TCR-Seq datasets will enable the effective analysis of large-scale TCR-Seq data with flexibility, and eventually facilitate new discoveries.

Differences in Predicted Warfarin Dosing Requirements Between Hmong and East Asians Using Genotype-Based Dosing Algorithms.

INTRODUCTION: Warfarin's narrow therapeutic index and high variability in dosage requirements make dosage selection critical. Genetic factors are known to impact warfarin dosage selection. The Hmong are a unique Asian subpopulation numbering over 278,000 in the United States whose participation in genetics-based research is virtually nonexistent. The translational significance of early reports of warfarin pharmacogene differences in Hmong has not been evaluated. OBJECTIVES: (i) To validate previously identified allele frequency differences relevant to warfarin dosing in Hmong versus East Asians and (ii) to compare predicted warfarin sensitivity and maintenance doses between a Hmong population and an East Asian cohort. METHOD: DNA collected from two independent cohorts (n=236 and n=198) of Hmong adults were genotyped for CYP2C9 (*2, *3), VKORC1 (G-1639A), and CYP4F2 (*3). Allele frequencies between the combined Hmong cohort (n=433) and East Asians (n=1165) from the 2009 International Warfarin Pharmacogenetics Consortium (IWPC) study were compared using a χ2 test. Percentages of Hmong and East Asian participants predicted to be very sensitive to warfarin were compared using a χ2 test, and the predicted mean warfarin maintenance dose was compared with a t test. RESULTS: The allele frequencies of CYP2C9*3 in the combined Hmong cohort and CYP4F2*3 in the VIP-Hmong cohort are significantly different from those in East Asians (18.9% vs 3.0%, p<0.001 and 9.8% vs 22.1%, p<0.001, respectively). Comparing the combined Hmong cohort to the East Asian cohort, the percentage of participants predicted to be very sensitive to warfarin was significantly higher (28% vs 5%, p<0.01) and the mean predicted warfarin maintenance dose was significantly lower (19.8 vs 21.3 mg/week, p<0.001), respectively. CONCLUSION: The unique allele frequencies related to warfarin when combined with nongenetic factors observed in the Hmong translate into clinically relevant differences in predicted maintenance dose requirements for Hmong versus East Asians.

Potential Clinical Relevance of Differences in Allele Frequencies Found within Very Important Pharmacogenes between Hmong and East Asian Populations.

OBJECTIVES: Implementing pharmacogenetics for very important pharmacogenes (VIPs) holds the promise of improving clinical outcomes through optimal medication selection and dosing. However, significant differences in the frequency of actionable variants in VIPs may exist within subpopulations of a given ancestral group. Furthermore, these differences can potentially impact drug selection and dosing. The purpose of this study was to ascertain allele frequencies for VIPs and to predict medication requirements using Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines in Hmong and compare with published data for East Asians. METHODS: Using a community-based participatory action research approach, DNA collected from 194 Hmong adults living in the United States was analyzed for 22 genetic variants within eight VIPs (CYP2C9, CYP2C19, CYP4F2, DPYD, G6PD, SLCO1B1, TPMT, VKORC1). Allele frequencies for VIPs and predicted medication requirements using CPIC guidelines were compared between Hmong participants and East Asians. RESULTS: Significant differences in allele frequencies between the Hmong and East Asians were found for 23% (5/22) of the CPIC-actionable variants tested. Allele frequencies for VIPs in Hmong versus East Asians were 16.6% versus 3.4% in CYP2C9*3A, 42.2% versus 29.0% for CYP2C19*2, 0.3% versus 8.3% in CYP2C19*3, 6.5% versus 22.1% in CYP4F2*3, and 3.6% versus 0.1% in SLCO1B1*5, respectively. These differences significantly influenced predicted medication usage recommendations in warfarin, simvastatin, and phenytoin between Hmong and East Asians. CONCLUSIONS: Important differences in allele frequencies for key genetic variants influencing selection of medications and dosages were found between the Hmong and East Asians. The magnitude and nature of these differences can be expected to result in different medication recommendations for the Hmong relative to East Asians.

HLA-B*58: 01 carrier status of Hmong in Minnesota: first in Hmong genotyping for prevalence of this biomarker of risk for severe cutaneous adverse reactions caused by allopurinol.

Allopurinol, a common medication to treat gout, is associated with severe cutaneous adverse reactions, and the occurrence is highly predicted by an individual's HLA-B*58:01 carrier status. Guidelines endorse preemptive testing in select Asian populations before initiating allopurinol. The Hmong, an Asian subpopulation originally from China who now live dispersed around the world, have a 2.5-fold higher risk of gout when compared to non-Hmong in Minnesota. Given the concern for severe cutaneous adverse reactions when prescribing allopurinol, we quantified the carrier status of HLA-B*58:01 in Hmong from two independent cohorts in Minnesota. Using a community-based participatory research approach, HLA-B*58:01 carrier status was determined in 49 US-born Hmong without a history of gout or allopurinol use. Further, 47 Hmong patients undergoing clinical evaluation to receive gout pharmacotherapy were also tested. The frequency of HLA-B*58:01 positive carrier status in these two cohorts were compared to published data from a Han Chinese (n = 2910) and a Korean cohort (n = 485) using a Fisher's exact test with a Bonferroni-corrected P-value <0.025 for significance. With one uninterpretable result, we identified two out of 95 people (2.1%) who carried HLA-B*58:01. This 2.1% incidence in these Hmong adults is notably lower than Han Chinese (19.6%, P < 0.0001) and Korean (12.2%, P = 0.0016) populations. Though commonly understood to be of Chinese descent, the lower prevalence within the Hmong underscores the risk of generalizing genotypic findings from Chinese to Asian subpopulations. We suggest no change to the current guidelines recommending which populations should be tested for HLA-B*58:01 before allopurinol use until further validation.

Characterization of tumor-targeting Ag2S quantum dots for cancer imaging and therapy in vivo.

Nanomedicine platforms that have the potential to simultaneously provide the function of molecular imaging and therapeutic treatment in one system are beneficial to address the challenges of cancer heterogeneity and adaptive resistance. In this study, Cyclic RGD peptide (cRGD), a less-expensive active tumor targeting tri-peptide, and doxorubicin (DOX), a widely used chemotherapeutic drug, were covalently attached to Ag2S quantum dots (QDs) to form the nano-conjugates Ag2S-DOX-cRGD. The optical characterization of Ag2S-DOX-cRGD manifested the maintenance of QDs fluorescence, which suggested the potential of Ag2S for monitoring intracellular and systemic drug distribution. The low biotoxicity of Ag2S QDs indicated that they are promisingly safe nanoparticles for bio-applications. Furthermore, the selective imaging and favorable tumor inhibition of the nanoconjugates were demonstrated at both cell and animal levels. These results indicated a promising future for the utilization of Ag2S QDs as a kind of multi-functional nano platform to achieve imaging-visible nano-therapeutics.