A Spatial Omnibus Test (SPOT) for Spatial Proteomic Data.

MOTIVATION: Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripley's K or Besag's L, to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific. RESULTS: We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus P-value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to ovarian and lung cancer studies. AVAILABILITY AND IMPLEMENTATION: An R package and tutorial are provided at https://github.com/sarahsamorodnitsky/SPOT.

A multi-bin rarefying method for evaluating alpha diversities in TCR sequencing data.

MOTIVATION: T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed. RESULTS: In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conducts rarefying within each bin for alpha diversity calculations, and performs meta-analysis across bins. Extensive simulations using real-world data highlight the inadequacy of the overall rarefying approach in controlling the confounding effect of library size. Our method proves robust in addressing library size confounding, outperforming competing normalization strategies by achieving better-controlled type-I error rates and enhanced statistical power in association tests. AVAILABILITY AND IMPLEMENTATION: The code is available at https://github.com/mli171/MultibinAlpha. The datasets are freely available at https://doi.org/10.21417/B7001Z and https://doi.org/10.21417/AR2019NC.

Preclinical Studies of Gene Replacement Therapy for CDKL5 Deficiency Disorder.

Cyclin dependent kinase-like 5 (CDKL5) Deficiency Disorder (CDD) is a rare neurodevelopmental disorder caused by a mutation in the X-linked CDKL5 gene. CDKL5 is a serine/threonine kinase that is critical for axon outgrowth, dendritic morphogenesis, as well as synapse formation, maturation, and maintenance. This disorder is characterized by early-onset epilepsy, hypotonia, and failure to reach cognitive and motor developmental milestones. Because the disease is monogenic, delivery of the CDKL5 gene to the brain of patients should provide clinical benefit. To this end, we designed a gene therapy vector, adeno-associated virus (AAV)9.Syn.hCDKL5, in which human CDKL5 gene expression is driven by the synapsin promoter. In biodistribution studies conducted in mice, intracerebroventricular (ICV) injection resulted in broader, more optimal biodistribution than did intracisterna magna (ICM) delivery. AAV9.Syn.hCDKL5 treatment increased phosphorylation of EB2, a bona fide CDKL5 substrate, demonstrating biological activity in vivo. Our data provides proof-of-concept that ICV delivery of AAV9.Syn.hCDKL5 to neonatal male Cdkl5 knockout mice reduces pathology and reduces aberrant behavior. Functional improvements were seen at doses of 3e11 to 5e11 vector genomes (vg)/g brain, which resulted in transfection of ≥50% of the neurons. Functional improvements were not seen at lower doses suggesting a requirement for broad distribution for efficacy.

Viral genomic variation and the severity of genital HSV-2 infection as quantified by shedding rate: a viral genome-wide association study.

BACKGROUND: The clinical severity of genital HSV-2 infection varies widely among infected persons with some experiencing frequent genital lesions while others are asymptomatic. The viral genital shedding rate is closely associated with and has been established as a surrogate marker of clinical severity. METHODS: To assess the relationship between viral genetics and shedding, we assembled a set of 145 persons who had the severity of their genital herpes quantified through determination of their HSV genital shedding rate. An HSV-2 sample from each person was sequenced and biallelic variants among these genomes were identified. RESULTS: We found no association between metrics of genome-wide variation in HSV-2 and shedding rate. A viral genome-wide association study (vGWAS) identified the minor alleles of three individual unlinked variants as significantly associated with higher shedding rate (p<8.4x10-5): C44973T (A512T), a non-synonymous variant in UL22 (glycoprotein H); A74534G, a synonymous variant in UL36 (large tegument protein); and T119283C, an intergenic variant. We also found an association between the total number of minor alleles for the significant variants and shedding rate (p=6.6x10-7). CONCLUSIONS: These results add to a growing body of literature for HSV suggesting a connection between viral genetic variation and clinically important phenotypes of infection.

A Spatial Omnibus Test (SPOT) for Spatial Proteomic Data.

Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripley's K or Besag's L, to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific. We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus p-value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to an ovarian cancer study. An R package and tutorial is provided at https://github.com/sarahsamorodnitsky/SPOT.

The prevalence and risk factors of Helicobacter pylori infection and cagA virulence gene carriage in adults in the Navajo Nation.

Background: American Indian and Alaska Native people in the United States experience high rates of stomach cancer. Helicobacter pylori infection is a significant risk factor for stomach cancer, and H. pylori strains that carry the cagA gene are linked to greater gastrointestinal disease severity. Yet, little is known about H. pylori and cagA infections in American Indian and Alaska Native people, particularly at the tribal level. We assessed the prevalence and risk factors of H. pylori infection and cagA gene carriage in tribal members from the Navajo Nation. Materials and Methods: We conducted a cross-sectional study with adults from the Navajo Nation. Stool samples collected from participants were analyzed with droplet digital PCR for H. pylori 16S ribosomal and cagA virulence genes. Self-administered health and food questionnaires were mailed to participants to collect information on sociodemographic, health, lifestyle, and environmental risk factors for H. pylori infection. Logistic regression assessed the association between risk factors and H. pylori infection and cagA gene carriage. Results: Among 99 adults, the median age was 45 (age range: 18 to 79 years), and 73.7% were female. About 56.6% (95% CI: 46.2-66.5) of participants were infected with H. pylori. Of H. pylori-infected participants, 78.6% (95% CI: 65.6-88.4) were cagA-gene positive. No significant associations of relevant risk factors with H. pylori and cagA-gene positive infections were noted. Conclusions: In a community-based study population, a substantial proportion of adult tribal members had H. pylori and cagA-gene positive infections. Given these high proportions, culturally appropriate prevention strategies and interventions addressing H. pylori infections present an avenue for additional research and stomach cancer prevention in the Navajo Nation.

Lung-MAP Next Generation Sequencing Analysis of Advanced Squamous Cell Lung Cancers (SWOG S1400).

INTRODUCTION: Squamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, i.e., by next generation sequencing (NGS), is needed to identify potential targets. Lung-MAP SWOG S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic substudies. METHODS: Tumors underwent NGS using Foundation Medicine's FoundationOne research platform, which sequenced the exons and/or introns of 313 cancer-related genes. Mutually Exclusive Gene Set Analysis (MEGSA) and Selected Events Linked by Evolutionary Conditions across human Tumors (SELECT) were performed to identify mutually exclusive and co-occurring gene alterations. Comparisons were performed with data on 495 lung SqCC downloaded from The Cancer Genome Atlas. Cox proportional hazards models were used to examine associations between genetic variants and survival. RESULTS: NGS data are reported for 1672 patients enrolled on S1400 between 2014 and 2019. MEGSA identified two non-overlapping sets of mutually exclusive alterations with a false discovery rate < 15%: NFE2L2, KEAP1 and PARP4; and CDKN2A and RB1. PARP4, a relatively uncharacterized gene, showed three frequent mutations suggesting functional significance: 3116T>C (I1039T), 3176A>G (Q1059R) and 3509C>T (T1170I). NFE2L2 and KEAP1 alterations when taken together were associated with poorer survival. CONCLUSIONS: As the largest dataset to-date of lung SqCC profiled on a clinical trial, the S1400 NGS dataset establishes a rich resource for biomarker discovery. Mutual exclusivity of PARP4 and NFE2L2 or KEAP1 alterations suggests that PARP4 may have an uncharacterized role in a key pathway known to impact oxidative stress response and treatment resistance.