SifiNet: a robust and accurate method to identify feature gene sets and annotate cells.

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multi-omic cellular profiles. It is conveniently available as an open-source R package.

DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree.

Rare-variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNamic Aggregation TEsting (DYNATE). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with a controlled weighted false discovery rate. DYNATE's main advantage lies in its strong ability to identify short genomic regions highly enriched for disease-associated RVs. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared with existing methods. We applied DYNATE to an amyotrophic lateral sclerosis study and identified a new gene, EPG5, harboring possibly pathogenic mutations.

SifiNet: A robust and accurate method to identify feature gene sets and annotate cells.

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multiomic cellular profiles. It is conveniently available as an open-source R package.

Single-cell landscape analysis unravels molecular programming of the human B cell compartment in chronic GVHD.

Alloreactivity can drive autoimmune syndromes. After allogeneic hematopoietic stem cell transplantation (allo-HCT), chronic graft-versus-host disease (cGVHD), a B cell-associated autoimmune-like syndrome, commonly occurs. Because donor-derived B cells continually develop under selective pressure from host alloantigens, aberrant B cell receptor (BCR) activation and IgG production can emerge and contribute to cGVHD pathobiology. To better understand molecular programing of B cells in allo-HCT, we performed scRNA-Seq analysis on high numbers of purified B cells from patients. An unsupervised analysis revealed 10 clusters, distinguishable by signature genes for maturation, activation, and memory. Within the memory B cell compartment, we found striking transcriptional differences in allo-HCT patients compared with healthy or infected individuals, including potentially pathogenic atypical B cells (ABCs) that were expanded in active cGVHD. To identify intrinsic alterations in potentially pathological B cells, we interrogated all clusters for differentially expressed genes (DEGs) in active cGVHD versus patients who never had signs of immune tolerance loss (no cGVHD). Active cGVHD DEGs occurred in both naive and BCR-activated B cell clusters. Remarkably, some DEGs occurred across most clusters, suggesting common molecular programs that may promote B cell plasticity. Our study of human allo-HCT and cGVHD provides understanding of altered B cell memory during chronic alloantigen stimulation.

Immune Phenotype and Postoperative Complications After Elective Surgery.

OBJECTIVES: To characterize and quantify accumulating immunologic alterations, pre and postoperatively in patients undergoing elective surgical procedures. BACKGROUND: Elective surgery is an anticipatable, controlled human injury. Although the human response to injury is generally stereotyped, individual variability exists. This makes surgical outcomes less predictable, even after standardized procedures, and may provoke complications in patients unable to compensate for their injury. One potential source of variation is found in immune cell maturation, with phenotypic changes dependent on an individual's unique, lifelong response to environmental antigens. METHODS: We enrolled 248 patients in a prospective trial facilitating comprehensive biospecimen and clinical data collection in patients scheduled to undergo elective surgery. Peripheral blood was collected preoperatively, and immediately on return to the postanesthesia care unit. Postoperative complications that occurred within 30 days after surgery were captured. RESULTS: As this was an elective surgical cohort, outcomes were generally favorable. With a median follow-up of 6 months, the overall survival at 30 days was 100%. However, 20.5% of the cohort experienced a postoperative complication (infection, readmission, or system dysfunction). We identified substantial heterogeneity of immune senescence and terminal differentiation phenotypes in surgical patients. More importantly, phenotypes indicating increased T-cell maturation and senescence were associated with postoperative complications and were evident preoperatively. CONCLUSIONS: The baseline immune repertoire may define an immune signature of resilience to surgical injury and help predict risk for surgical complications.

Neuroimaging and immunological features of neurocognitive function related to substance use in people with HIV.

This study sought to identify neuroimaging and immunological factors associated with substance use and that contribute to neurocognitive impairment (NCI) in people with HIV (PWH). We performed cross-sectional immunological phenotyping, neuroimaging, and neurocognitive testing on virally suppressed PWH in four substance groups: cocaine only users (COC), marijuana only users (MJ), dual users (Dual), and Non-users. Participants completed substance use assessments, multimodal MRI brain scan, neuropsychological testing, and blood and CSF sampling. We employed a two-stage analysis of 305 possible biomarkers of cognitive function associated with substance use. Feature reduction (Kruskal Wallis p-value < 0.05) identified 53 biomarkers associated with substance use (22 MRI and 31 immunological) for model inclusion along with clinical and demographic variables. We employed eXtreme Gradient Boosting (XGBoost) with these markers to predict cognitive function (global T-score). SHapley Additive exPlanations (SHAP) values were calculated to rank features for impact on model output and NCI. Participants were 110 PWH with sustained HIV viral suppression (33 MJ, 12 COC, 22 Dual, and 43 Non-users). The ten highest ranking biomarkers for predicting global T-score were 4 neuroimaging biomarkers including functional connectivity, gray matter volume, and white matter integrity; 5 soluble biomarkers (plasma glycine, alanine, lyso-phosphatidylcholine (lysoPC) aC17.0, hydroxy-sphingomyelin (SM.OH) C14.1, and phosphatidylcholinediacyl (PC aa) C28.1); and 1 clinical variable (nadir CD4 count). The results of our machine learning model suggest that substance use may indirectly contribute to NCI in PWH through both metabolomic and neuropathological mechanisms.

TEAM: A MULTIPLE TESTING ALGORITHM ON THE AGGREGATION TREE FOR FLOW CYTOMETRY ANALYSIS.

In immunology studies, flow cytometry is a commonly used multivariate single-cell assay. One key goal in flow cytometry analysis is to detect the immune cells responsive to certain stimuli. Statistically, this problem can be translated into comparing two protein expression probability density functions (pdfs) before and after the stimulus; the goal is to pinpoint the regions where these two pdfs differ. Further screening of these differential regions can be performed to identify enriched sets of responsive cells. In this paper, we model identifying differential density regions as a multiple testing problem. First, we partition the sample space into small bins. In each bin, we form a hypothesis to test the existence of differential pdfs. Second, we develop a novel multiple testing method, called TEAM (Testing on the Aggregation tree Method), to identify those bins that harbor differential pdfs while controlling the false discovery rate (FDR) under the desired level. TEAM embeds the testing procedure into an aggregation tree to test from fine- to coarse-resolution. The procedure achieves the statistical goal of pinpointing density differences to the smallest possible regions. TEAM is computationally efficient, capable of analyzing large flow cytometry data sets in much shorter time compared with competing methods. We applied TEAM and competing methods on a flow cytometry data set to identify T cells responsive to the cytomegalovirus (CMV)-pp65 antigen stimulation. With additional downstream screening, TEAM successfully identified enriched sets containing monofunctional, bifunctional, and polyfunctional T cells. Competing methods either did not finish in a reasonable time frame or provided less interpretable results. Numerical simulations and theoretical justifications demonstrate that TEAM has asymptotically valid, powerful, and robust performance. Overall, TEAM is a computationally efficient and statistically powerful algorithm that can yield meaningful biological insights in flow cytometry studies.

Clustering Deviation Index (CDI): a robust and accurate internal measure for evaluating scRNA-seq data clustering.

Most single-cell RNA sequencing (scRNA-seq) analyses begin with cell clustering; thus, the clustering accuracy considerably impacts the validity of downstream analyses. In contrast with the abundance of clustering methods, the tools to assess the clustering accuracy are limited. We propose a new Clustering Deviation Index (CDI) that measures the deviation of any clustering label set from the observed single-cell data. We conduct in silico and experimental scRNA-seq studies to show that CDI can select the optimal clustering label set. As a result, CDI also informs the optimal tuning parameters for any given clustering method and the correct number of cluster components.

Evaluating immune response and metabolic related biomarkers pre-allogenic hematopoietic stem cell transplant in acute myeloid leukemia.

Although hematopoietic stem cell transplantation (HCT) is the only curative treatment for acute myeloid leukemia (AML), it is associated with significant treatment related morbidity and mortality. There is great need for predictive biomarkers associated with overall survival (OS) and clinical outcomes. We hypothesized that circulating metabolic, inflammatory, and immune molecules have potential as predictive biomarkers for AML patients who receive HCT treatment. This retrospective study was designed with an exploratory approach to comprehensively characterize immune, inflammatory, and metabolomic biomarkers. We identified patients with AML who underwent HCT and had existing baseline plasma samples. Using those samples (n = 34), we studied 65 blood based metabolomic and 61 immune/inflammatory related biomarkers, comparing patients with either long-term OS (≥ 3 years) or short-term OS (OS ≤ 1 years). We also compared the immune/inflammatory response and metabolomic biomarkers in younger vs. older AML patients (≤30 years vs. ≥ 55 years old). In addition, the biomarker profiles were analyzed for their association with clinical outcomes, namely OS, chronic graft versus host disease (cGVHD), acute graft versus host disease (aGVHD), infection and relapse. Several baseline biomarkers were elevated in older versus younger patients, and baseline levels were lower for three markers (IL13, SAA, CRP) in patients with OS ≥ 3 years. We also identified immune/inflammatory response markers associated with aGVHD (IL-9, Eotaxin-3), cGVHD (Flt-1), infection (D-dimer), or relapse (IL-17D, bFGF, Eotaxin-3). Evaluation of metabolic markers demonstrated higher baseline levels of medium- and long-chain acylcarnitines (AC) in older patients, association with aGVHD (lactate, long-chain AC), and cGVHD (medium-chain AC). These differentially expressed profiles merit further evaluation as predictive biomarkers.

APOBEC Mutagenesis Inhibits Breast Cancer Growth through Induction of T cell-Mediated Antitumor Immune Responses.

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are enriched in the HER2 subtype of breast cancer and are associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induced antitumor adaptive immune responses and CD4+ T cell-mediated, antigen-specific tumor growth inhibition. Although polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected, suggesting that APOBEC-mediated genetic heterogeneity limits antitumor adaptive immune responses. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to anti-CTLA-4 checkpoint inhibition and led to a complete response to combination anti-CTLA-4 and anti-HER2 therapy. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures and clonality as biomarkers predicting immunotherapy response in HER2-positive (HER2+) breast cancers.

Hypercapnia in Advanced Chronic Obstructive Pulmonary Disease: A Secondary Analysis of the National Emphysema Treatment Trial.

RATIONALE: Hypercapnia develops in one third of patients with advanced chronic obstructive pulmonary disease (COPD) and is associated with increased morbidity and mortality. Multiple factors in COPD are thought to contribute to the development of hypercapnia including increased carbon dioxide (CO2) production, increased dead space ventilation, and the complex interactions of deranged respiratory system mechanics, inspiratory muscle overload and the ventilatory control center in the brainstem. However, these factors have not previously been systematically analyzed in a large, well-characterized population of severe COPD patients. METHODS: This is a secondary analysis of the clinical, physiologic and imaging data from the National Emphysema Treatment Trial (NETT). All patients with complete baseline data for the key predictor variables were included. An inclusive list of 32 potential predictor variables were selected a priori based on consensus of the investigators and literature review. Stepwise variable selection yielded 10 statistically significant associations in multivariate regression. RESULTS: A total of 1419 patients with severe COPD were included in the analysis; mean age 66.4 years (standard deviation 6.3), 38% females, and 422 (29.7%) had baseline hypercapnia. Key variables associated with hypercapnia were low resting partial pressure of oxygen in blood, low minute ventilation (Ve), high volume of exhaled carbon dioxide, low forced expiratory volume in 1 second, high residual volume, lower % emphysema on chest computed tomography, use of oxygen, low ventilatory reserve (high Ve/maximal voluntary ventilation), and not being at high altitude. Low diffusing capacity for carbon monoxide showed a positive association with hypercapnia in univariate analysis but a negative correlation in multivariate analysis. Measures of dyspnea and quality of life did not associate with degree of hypercapnia in multivariable analysis. CONCLUSION: Hypercapnia in a well-characterized cohort with severe COPD and emphysema is chiefly related to poor lung mechanics, high CO2 production, and a reduced ventilatory capability. Hypercapnia is less impacted by gas exchange abnormalities or the presence of emphysema.

Microtransplantation in older patients with AML: A pilot study of safety, efficacy and immunologic effects.

Older AML patients have low remission rates and poor survival outcomes with standard chemotherapy. Microtransplantation (MST) refers to infusion of allogeneic hematopoietic stem cells without substantial engraftment. MST has been shown to improve clinical outcomes compared with chemotherapy alone. This is the first trial reporting on broad correlative studies to define immunologic mechanisms of action of MST in older AML patients. Older patients with newly diagnosed AML were eligible for enrollment, receiving induction chemotherapy with cytarabine (100 mg/m2) on days 1-7 and idarubicin (12 mg/m2) on days 1-3 (7 + 3). MST was administered 24 hours later. Patients with complete response (CR) were eligible for consolidation with high dose cytarabine (HiDAC) and a second cycle of MST. Responses were evaluated according to standard criteria per NCCN. Immune correlative studies were performed. Sixteen patients were enrolled and received 7 + 3 and MST (median age 73 years). Nine (56%) had high-risk and seven (44%) had standard-risk cytogenetics. Ten episodes of CRS were observed. No cases of GVHD or treatment-related mortality were reported. Event-free survival (EFS) was 50% at 6 months and 19% at 1 year. Overall survival (OS) was 63% at 6 months and 44% at 1 year. Donor microchimerism was not detected. Longitudinal changes were noted in NGS, TCR sequencing, and cytokine assays. Addition of MST to induction and consolidation chemotherapy was well tolerated in older AML patients. Inferior survival outcomes in our study may be attributed to a higher proportion of very elderly patients with high-risk features. Potential immunologic mechanisms of activity of MST include attenuation of inflammatory cytokines and emergence of tumor-specific T cell clones.

Genetic variants in the calcium signaling pathway genes are associated with cutaneous melanoma-specific survival.

Remodeling or deregulation of the calcium signaling pathway is a relevant hallmark of cancer including cutaneous melanoma (CM). In this study, using data from a published genome-wide association study (GWAS) from The University of Texas M.D. Anderson Cancer Center, we assessed the role of 41,377 common single-nucleotide polymorphisms (SNPs) of 167 calcium signaling pathway genes in CM survival. We used another GWAS from Harvard University as the validation dataset. In the single-locus analysis, 1830 SNPs were found to be significantly associated with CM-specific survival (CMSS; P ≤ 0.050 and false-positive report probability ≤ 0.2), of which 9 SNPs were validated in the Harvard study (P ≤ 0.050). Among these, three independent SNPs (i.e. PDE1A rs6750552 T>C, ITPR1 rs6785564 A>G and RYR3 rs2596191 C>A) had a predictive role in CMSS, with a meta-analysis-derived hazards ratio of 1.52 (95% confidence interval = 1.19-1.94, P = 7.21 × 10-4), 0.49 (0.33-0.73, 3.94 × 10-4) and 0.67 (0.53-0.86, 0.0017), respectively. Patients with an increasing number of protective genotypes had remarkably improved CMSS. Additional expression quantitative trait loci analysis showed that these genotypes were also significantly associated with mRNA expression levels of the genes. Taken together, these results may help us to identify prospective biomarkers in the calcium signaling pathway for CM prognosis.

Prevalence and Cost Analysis of Chronic Pain After Hernia Repair: A Potential Alternative Approach With Neurostimulation.

OBJECTIVES: Chronic pain (CP) affects a significant number of patients following hernia repair, ranging from 11 to 54% in the literature. The aim of this study was to assess the prevalence, overall costs, and health care utilization associated with CP after hernia repair. MATERIALS AND METHODS: A retrospective longitudinal study was performed using the Truven MarketScan® data base to identify patients who develop chronic neuropathic posthernia repair pain from 2001 to 2012. Patients were grouped into CP and No Chronic Pain (No CP) cohorts. Patients were excluded if they 1) were under 18 years of age; 2) had a previous pain diagnosis; 3) had CP diagnosed <90 days after the index hernia repair; 4) had less than one year of follow-up; or 5) had less than one-year baseline record before hernia repair. Patients were grouped into the CP cohort if their CP diagnosis was made within the two years following index hernia repair. Total, outpatient, and pain prescription costs were collected in the period of five years prehernia to nine years posthernia repair. A longitudinal multivariate analysis was used to model the effects of chronic neuropathic posthernia repair pain on total inpatient/outpatient and pain prescription costs. RESULTS: We identified 76,173 patients who underwent hernia repair and met inclusion criteria (CP: n = 14,919, No CP: n = 61,254). There was a trend for increased total inpatient/outpatient and pain prescription costs one-year posthernia repair, when compared to baseline costs for both cohorts. In both cohorts, total inpatient/outpatient costs remained elevated from baseline through nine years posthernia repair, with the CP cohort experiencing significantly higher cumulative median costs (CP: $51,334, No CP: $37,388). The CP diagnosis year was associated with a 1.75-fold increase (p < 0.001) in total inpatient/outpatient costs and a 2.26-fold increase (p < 0.001) in pain prescription costs versus all other years. In the longitudinal analysis, the CP cohort had a 1.14-fold increase (p < 0.001) in total inpatient/outpatient costs and 2.00-fold increase (p < 0.001) in pain prescription costs. CONCLUSIONS: Our study demonstrates the prevalence of CP after hernia surgery to be nearly 20%, with significantly increased costs and healthcare resource utilization. While current treatment paradigms are effective for many, there remains a large number of patients that could benefit from an overall approach that includes nonopioid treatments, such as potentially incorporating neurostimulation, for CP that presents posthernia repair.

Independent Associations With 30- and 90-Day Unplanned Readmissions After Elective Lumbar Spine Surgery: A National Trend Analysis of 144 123 Patients.

BACKGROUND: Unplanned hospital readmissions contribute significantly to soaring national healthcare expenditures. To alleviate this burden, Centers for Medicare and Medicaid Services implemented initiatives to penalize hospitals for unplanned 30-d hospital readmissions. There is a paucity of data identifying patient risk factors independently associated with 30- and 90-d readmissions. OBJECTIVE: To investigate similarities in patient risk factors associated with 30- and 90-d unplanned readmissions following elective lumbar spine surgery. METHODS: The National Readmission Database (NRD) was queried to identify patients undergoing elective lumbar spine surgery between 2013 and 2014. Patients were grouped by no readmission (Non-R), unplanned readmission within 30 days (30-R), and unplanned readmission within 31 to 90 days (90-R). Multivariate analysis determined factors associated with 30- and 90-d readmissions. RESULTS: We identified 144 123 patients with 10 592 (7.3%) patients experiencing an unplanned readmission (30-R: n = 7228 [5.0%]; 90-R: n = 3364 [2.3%]; Non-R: n = 133 531). The most common inpatient complication observed in those patients readmitted was dural tear (30-R: 7.7%, 90-R: 4.6%, Non-R: 4.3%). The most prevalent 30- and 90-d complication seen among the readmitted cohort was infection (30-R: 18.5%, 90-R: 7.4%). In multivariate regression analysis, age, insurance status, chronic obstructive pulmonary disorder (COPD), depression, hypertension, diabetes, deficiency anemia, and obesity were independently associated with 30-d readmission; however, age and obesity were not independently associated with 90-d readmission. CONCLUSION: Our study demonstrated national unplanned readmission rates after elective spinal surgery to be 7.3%. With age, insurance status, COPD, depression, hypertension, diabetes, deficiency anemia, obesity, and depression all independently associated with unplanned hospital readmission. Future solutions that focus on reducing preventable readmissions may improve patient outcomes and reduce healthcare costs.

Sex Differences in Genetic Associations With Longevity.

IMPORTANCE: Sex differences in genetic associations with human longevity remain largely unknown; investigations on this topic are important for individualized health care. OBJECTIVE: To explore sex differences in genetic associations with longevity. DESIGN SETTING AND PARTICIPANTS: This population-based case-control study used sex-specific genome-wide association study and polygenic risk score (PRS) analyses to examine sex differences in genetic associations with longevity. Five hundred sixty-four male and 1614 female participants older than 100 years were compared with a control group of 773 male and 1526 female individuals aged 40 to 64 years. All were Chinese Longitudinal Healthy Longevity Study participants with Han ethnicity who were recruited in 1998 and 2008 to 2014. MAIN OUTCOMES AND MEASURES: Sex-specific loci and pathways associated with longevity and PRS measures of joint effects of sex-specific loci. RESULTS: Eleven male-specific and 11 female-specific longevity loci (P < 10-5) and 35 male-specific and 25 female-specific longevity loci (10-5 ≤ P < 10-4) were identified. Each of these loci's associations with longevity were replicated in north and south regions of China in one sex but were not significant in the other sex (P = .13-.97), and loci-sex interaction effects were significant (P < .05). The associations of loci rs60210535 of the LINC00871 gene with longevity were replicated in Chinese women (P = 9.0 × 10-5) and US women (P = 4.6 × 10-5) but not significant in Chinese and US men. The associations of the loci rs2622624 of the ABCG2 gene were replicated in Chinese women (P = 6.8 × 10-5) and European women (P = .003) but not significant in both Chinese and European men. Eleven male-specific pathways (inflammation and immunity genes) and 34 female-specific pathways (tryptophan metabolism and PGC-1α induced) were significantly associated with longevity (P < .005; false discovery rate < 0.05). The PRS analyses demonstrated that sex-specific associations with longevity of the 4 exclusive groups of 11 male-specific and 11 female-specific loci (P < 10-5) and 35 male-specific and 25 female-specific loci (10-5 ≤P < 10-4) were jointly replicated across north and south discovery and target samples. Analyses using the combined data set of north and south showed that these 4 groups of sex-specific loci were jointly and significantly associated with longevity in one sex (P = 2.9 × 10-70 to 1.3 × 10-39) but not jointly significant in the other sex (P = .11 to .70), while interaction effects between PRS and sex were significant (P = 4.8 × 10-50 to 1.2 × 10-16). CONCLUSION AND RELEVANCE: The sex differences in genetic associations with longevity are remarkable, but have been overlooked by previously published genome-wide association studies on longevity. This study contributes to filling this research gap and provides a scientific basis for further investigating effects of sex-specific genetic variants and their interactions with environment on healthy aging, which may substantially contribute to more effective and targeted individualized health care for male and female elderly individuals.

Genetic variant of IRAK2 in the toll-like receptor signaling pathway and survival of non-small cell lung cancer.

The toll-like receptor (TLR) signaling pathway plays an important role in the innate immune responses and antigen-specific acquired immunity. Aberrant activation of the TLR pathway has a significant impact on carcinogenesis or tumor progression. Therefore, we hypothesize that genetic variants in the TLR signaling pathway genes are associated with overall survival (OS) of patients with non-small cell lung cancer (NSCLC). To test this hypothesis, we first performed Cox proportional hazards regression analysis to evaluate associations between genetic variants of 165 TLR signaling pathway genes and NSCLC OS using the genome-wide association study (GWAS) dataset from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). The results were further validated by the Harvard Lung Cancer Susceptibility GWAS dataset. Specifically, we identified IRAK2 rs779901 C > T as a predictor of NSCLC OS, with a variant-allele (T) attributed hazards ratio (HR) of 0.78 [95% confidence interval (CI) = 0.67-0.91, P = 0.001] in the PLCO dataset, 0.84 (0.72-0.98, 0.031) in the Harvard dataset, and 0.81 (0.73-0.90, 1.08x10-4 ) in the meta-analysis of these two GWAS datasets. In addition, the T allele was significantly associated with an increased mRNA expression level of IRAK2. Our findings suggest that IRAK2 rs779901 C > T may be a promising prognostic biomarker for NSCLC OS.

bcSeq: an R package for fast sequence mapping in high-throughput shRNA and CRISPR screens.

Summary: CRISPR-Cas9 and shRNA high-throughput sequencing screens have abundant applications for basic and translational research. Methods and tools for the analysis of these screens must properly account for sequencing error, resolve ambiguous mappings among similar sequences in the barcode library in a statistically principled manner, and be computationally efficient. Herein we present bcSeq, an open source R package that implements a fast and parallelized algorithm for mapping high-throughput sequencing reads to a barcode library while tolerating sequencing error. The algorithm uses a Trie data structure for speed and resolves ambiguous mappings by using a statistical sequencing error model based on Phred scores for each read. Availability and implementation: The package source code and an accompanying tutorial are available at http://bioconductor.org/packages/bcSeq/. Supplementary information: Supplementary data are available at Bioinformatics online.