Integrating Patient-Reported Outcomes Into Prognostication in Gastroesophageal Cancer: Results of a Population-Based Retrospective Cohort Analysis.

BACKGROUND: Patient-reported outcomes measures (PROM) are self-reflections of an individual's physical functioning and emotional well-being. The Edmonton Symptom Assessment Scale (ESAS) is a simple and validated PRO tool of 10 common symptoms and a patient-reported functional status (PRFS) measure. The prognostic value of this tool is unknown in patients with gastroesophageal cancer (GEC). In this study, we examined the association between the ESAS score and overall survival (OS) in patients with GEC, the prognostication difference between ESAS and Eastern Cooperative Oncology Group (ECOG), and assessed the correlation between PRFS and the physician-reported ECOG performance status (PS). METHODS: The study was a retrospective cohort study of 211 patients with GEC with localized (stages I-III) and metastatic disease who completed at least one baseline ESAS prior to treatment. Patients were grouped into 3 cohorts based on ESAS score. OS was assessed using the Kaplan-Meier method, and the concordance index (c-index) was calculated for ESAS and physician-reported ECOG. The agreement between PRFS and physician-ECOG was also assessed. RESULTS: In total, 211 patients were included. The median age was 60.8 years; 90% of patients were ECOG PS 0-1; 38% of patients were stages I-III, while 62% were de novo metastatic patients. Median OS in low, moderate, high symptom burden (SB) patients' cohorts was 19.17 m, 16.39 mm, and 12.68 m, respectively (P < .04). The ability to predict death was similar between physician-ECOG and ESAS (c-index 0.56 and 0.5753, respectively) and PRFS and physician-ECOG (c-index of 0.5615 and 0.5545, respectively). The PS agreement between patients and physicians was 50% with a weighted Kappa of 0.27 (95% CI: 0.17-0.38). CONCLUSION: Patient's SB seems to carry a prognostic significance. ESAS and physician-reported ECOG exhibit comparable prognostic values. Physicians and patients can frequently have divergent opinions on PS. ESAS takes a patient-centered approach and should be encouraged in practice among patients with GEC as an additional tool for prognostication.

Leptomeningeal carcinomatosis and brain metastases in gastroesophageal carcinoma: a real-world analysis of clinical and pathologic characteristics and outcomes.

BACKGROUND: Brain metastasis (BrM) and Leptomeningeal Carcinomatosis (LMC) are uncommon complications in gastroesophageal carcinoma (GEC) patients. These patients have a poor prognosis and are challenging to treat. We described the clinicopathologic features and outcomes in the largest cohort of Central Nervous System (CNS) metastasis in GEC patients. METHODS: single-center retrospective study of GEC treated from 2007 to 2021. Clinicopathologic characteristics and treatment modalities were reviewed. Survival was calculated from the date of CNS diagnosis until date of death/last follow-up using the Kaplan-Meier method. A multivariable Cox proportional hazards regression model was used. RESULTS: Of 3283 GEC patients, 100 (3.04%) were diagnosed with BrM and 20 with LMC (0.61%). Patients with known human epidermal growth factor receptor 2 (HER2) status (N = 48), 60% were HER2 positive (defined as IHC 3 + or IHC 2+/FISH+). Among LMC patients most were signet-ring subtype (85%), and only 15% (2/13) were HER2 positive. Median survival was 0.7; 3.8; and 7.7 months in BrM patients treated with best supportive care, radiation, and surgery, respectively (p < 0.001). In LMC, median survival was 0.7 month in patients who had best supportive care (7/19) and 2.8 months for those who had whole brain radiation therapy (p = 0.015). Multivariate analysis showed worse outcomes in ECOG ≥ 2 (p = 0.002), number of BrM ≥ 4 (p < 0.001) and number of metastatic sites (p = 0.009). CONCLUSION: HER2 expression were enriched in patients with BrM, while it is uncommon in LMC. Patients treated with surgery followed by radiation had an improved OS in BrM and WBRT benefited patients with LMC.

Proteomic and genomic profiling of plasma exosomes from patients with ankylosing spondylitis.

INTRODUCTION: Recent advances in understanding the biology of ankylosing spondylitis (AS) using innovative genomic and proteomic approaches offer the opportunity to address current challenges in AS diagnosis and management. Altered expression of genes, microRNAs (miRNAs) or proteins may contribute to immune dysregulation and may play a significant role in the onset and persistence of inflammation in AS. The ability of exosomes to transport miRNAs across cells and alter the phenotype of recipient cells has implicated exosomes in perpetuating inflammation in AS. This study reports the first proteomic and miRNA profiling of plasma-derived exosomes in AS using comprehensive computational biology analysis. METHODS: Plasma samples from patients with AS and healthy controls (HC) were isolated via ultracentrifugation and subjected to extracellular vesicle flow cytometry analysis to characterise exosome surface markers by a multiplex immunocapture assay. Cytokine profiling of plasma-derived exosomes and cell culture supernatants was performed. Next-generation sequencing was used to identify miRNA populations in exosomes enriched from plasma fractions. CD4+ T cells were sorted, and the frequency and proliferation of CD4+ T-cell subsets were analysed after treatment with AS-exosomes using flow cytometry. RESULTS: The expression of exosome marker proteins CD63 and CD81 was elevated in the patients with AS compared with HC (q<0.05). Cytokine profiling in plasma-derived AS-exosomes demonstrated downregulation of interleukin (IL)-8 and IL-10 (q<0.05). AS-exosomes cocultured with HC CD4+ T cells induced significant upregulation of IFNα2 and IL-33 (q<0.05). Exosomes from patients with AS inhibited the proliferation of regulatory T cells (Treg), suggesting a mechanism for chronically activated T cells in this disease. Culture of CD4+ T cells from healthy individuals in the presence of AS-exosomes reduced the proliferation of FOXP3+ Treg cells and decreased the frequency of FOXP3+IRF4+ Treg cells. miRNA sequencing identified 24 differentially expressed miRNAs found in circulating exosomes of patients with AS compared with HC; 22 of which were upregulated and 2 were downregulated. CONCLUSIONS: Individuals with AS have different immunological and genetic profiles, as determined by evaluating the exosomes of these patients. The inhibitory effect of exosomes on Treg in AS suggests a mechanism contributing to chronically activated T cells in this disease.

Genetic association and transcriptome integration identify contributing genes and tissues at cystic fibrosis modifier loci.

Cystic Fibrosis (CF) exhibits morbidity in several organs, including progressive lung disease in all patients and intestinal obstruction at birth (meconium ileus) in ~15%. Individuals with the same causal CFTR mutations show variable disease presentation which is partly attributed to modifier genes. With >6,500 participants from the International CF Gene Modifier Consortium, genome-wide association investigation identified a new modifier locus for meconium ileus encompassing ATP12A on chromosome 13 (min p = 3.83x10(-10)); replicated loci encompassing SLC6A14 on chromosome X and SLC26A9 on chromosome 1, (min p<2.2x10(-16), 2.81x10(-11), respectively); and replicated a suggestive locus on chromosome 7 near PRSS1 (min p = 2.55x10(-7)). PRSS1 is exclusively expressed in the exocrine pancreas and was previously associated with non-CF pancreatitis with functional characterization demonstrating impact on PRSS1 gene expression. We thus asked whether the other meconium ileus modifier loci impact gene expression and in which organ. We developed and applied a colocalization framework called the Simple Sum (SS) that integrates regulatory and genetic association information, and also contrasts colocalization evidence across tissues or genes. The associated modifier loci colocalized with expression quantitative trait loci (eQTLs) for ATP12A (p = 3.35x10(-8)), SLC6A14 (p = 1.12x10(-10)) and SLC26A9 (p = 4.48x10(-5)) in the pancreas, even though meconium ileus manifests in the intestine. The meconium ileus susceptibility locus on chromosome X appeared shifted in location from a previously identified locus for CF lung disease severity. Using the SS we integrated the lung disease association locus with eQTLs from nasal epithelia of 63 CF participants and demonstrated evidence of colocalization with airway-specific regulation of SLC6A14 (p = 2.3x10(-4)). Cystic Fibrosis is realizing the promise of personalized medicine, and identification of the contributing organ and understanding of tissue specificity for a gene modifier is essential for the next phase of personalizing therapeutic strategies.

VikNGS: a C++ variant integration kit for next generation sequencing association analysis.

SUMMARY: Integration of next generation sequencing data (NGS) across different research studies can improve the power of genetic association testing by increasing sample size and can obviate the need for sequencing controls. If differential genotype uncertainty across studies is not accounted for, combining datasets can produce spurious association results. We developed the Variant Integration Kit for NGS (VikNGS), a fast cross-platform software package, to enable aggregation of several datasets for rare and common variant genetic association analysis of quantitative and binary traits with covariate adjustment. VikNGS also includes a graphical user interface, power simulation functionality and data visualization tools. AVAILABILITY AND IMPLEMENTATION: The VikNGS package can be downloaded at http://www.tcag.ca/tools/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic association analysis with pedigrees: Direct inference using the composite likelihood ratio.

The likelihood function represents statistical evidence given data and a model. The evidential paradigm (EP), an alternative to Bayesian and Frequentist paradigms, provides considerable theory demonstrating evidence strength for different parameter values via the ratio of likelihoods at different parameter values; thus, enabling inference directly from the likelihood function. The likelihood function, however, can be difficult to compute; for example, in genetic association studies with a binary outcome in large pedigrees. Composite likelihood (CL) is an alternative when the real likelihood is intractable. We show CLs have the two large sample properties of the EP for reliable evidence interpretation: (1) CL supports the true value over a false value by an arbitrarily large factor; and (2) the probability of favouring a false value over the true value is small and bounded. Using simulation, and in a genetic association analysis of reading disability (RD) in large rolandic epilepsy pedigrees, we show that the CL approach yields valid statistical inference and identifies RD associated variants. When compared to analyses using generalized estimating equations, results show a similar prioritization of SNPs, although the CL approach provides additional complementary information, and more intuitive solutions to the multiple hypothesis testing problem.

Statistical Reasoning: Choosing and Checking the Ingredients, Inferences Based on a Measure of Statistical Evidence with Some Applications.

The features of a logically sound approach to a theory of statistical reasoning are discussed. A particular approach that satisfies these criteria is reviewed. This is seen to involve selection of a model, model checking, elicitation of a prior, checking the prior for bias, checking for prior-data conflict and estimation and hypothesis assessment inferences based on a measure of evidence. A long-standing anomalous example is resolved by this approach to inference and an application is made to a practical problem of considerable importance, which, among other novel aspects of the analysis, involves the development of a relevant elicitation algorithm.

Clinical Validation of Human Papilloma Virus Circulating Tumor DNA for Early Detection of Residual Disease After Chemoradiation in Cervical Cancer.

PURPOSE: Most cervical cancers are caused by human papilloma virus (HPV), and HPV circulating tumor DNA (ctDNA) may identify patients at highest risk of relapse. Our pilot study using digital polymerase chain reaction (dPCR) showed that detectable HPV ctDNA at the end of chemoradiation (CRT) is associated with inferior progression-free survival (PFS) and that a next-generation sequencing approach (HPV-seq) may outperform dPCR. We aimed to prospectively validate HPV ctDNA as a tool for early detection of residual disease. METHODS: This prospective, multicenter validation study accrued patients with stage IB-IVA cervical cancer treated with CRT between 2017 and 2022. Participants underwent phlebotomy at baseline, end of CRT, 4-6 weeks post-CRT, and 3 months post-CRT for HPV ctDNA levels. Plasma HPV genotype-specific DNA levels were quantified using both dPCR and HPV-seq. The primary end point was 2-year PFS. RESULTS: With a median follow-up of 2.2 (range, 0.5-5.5) years, there were 24 PFS events among the 70 patients with HPV+ cervical cancer. Patients with detectable HPV ctDNA on dPCR at the end of CRT, 4-6 weeks post-CRT, and 3 months post-CRT had significantly worse 2-year PFS compared with those with undetectable HPV ctDNA (77% v 51%, P = .03; 82% v 15%, P < .001; and 82% v 24%, P < .001, respectively); the median lead time to recurrence was 5.9 months. HPV-seq showed similar results as dPCR. On multivariable analyses, detectable HPV ctDNA on dPCR and HPV-seq remained independently associated with inferior PFS. CONCLUSION: Persistent HPV ctDNA after CRT is independently associated with inferior PFS. HPV ctDNA testing can identify, as early as at the end of CRT, patients at high risk of recurrence for future treatment intensification trials.

Using parametric multipoint lods and mods for linkage analysis requires a shift in statistical thinking.

Multipoint (MP) linkage analysis represents a valuable tool for whole-genome studies but suffers from the disadvantage that its probability distribution is unknown and varies as a function of marker information and density, genetic model, number and structure of pedigrees, and the affection status distribution [Xing and Elston: Genet Epidemiol 2006;30:447-458; Hodge et al.: Genet Epidemiol 2008;32:800-815]. This implies that the MP significance criterion can differ for each marker and each dataset, and this fact makes planning and evaluation of MP linkage studies difficult. One way to circumvent this difficulty is to use simulations or permutation testing. Another approach is to use an alternative statistical paradigm to assess the statistical evidence for linkage, one that does not require computation of a p value. Here we show how to use the evidential statistical paradigm for planning, conducting, and interpreting MP linkage studies when the disease model is known (lod analysis) or unknown (mod analysis). As a key feature, the evidential paradigm decouples uncertainty (i.e. error probabilities) from statistical evidence. In the planning stage, the user calculates error probabilities, as functions of one's design choices (sample size, choice of alternative hypothesis, choice of likelihood ratio (LR) criterion k) in order to ensure a reliable study design. In the data analysis stage one no longer pays attention to those error probabilities. In this stage, one calculates the LR for two simple hypotheses (i.e. trait locus is unlinked vs. trait locus is located at a particular position) as a function of the parameter of interest (position). The LR directly measures the strength of evidence for linkage in a given data set and remains completely divorced from the error probabilities calculated in the planning stage. An important consequence of this procedure is that one can use the same criterion k for all analyses. This contrasts with the situation described above, in which the value one uses to conclude significance may differ for each marker and each dataset in order to accommodate a fixed test size, α. In this study we accomplish two goals that lead to a general algorithm for conducting evidential MP linkage studies. (1) We provide two theoretical results that translate into guidelines for investigators conducting evidential MP linkage: (a) Comparing mods to lods, error rates (including probabilities of weak evidence) are generally higher for mods when the null hypothesis is true, but lower for mods in the presence of true linkage. Royall [J Am Stat Assoc 2000;95:760-780] has shown that errors based on lods are bounded and generally small. Therefore when the true disease model is unknown and one chooses to use mods, one needs to control misleading evidence rates only under the null hypothesis; (b) for any given pair of contiguous marker loci, error rates under the null are greatest at the midpoint between the markers spaced furthest apart, which provides an obvious simple alternative hypothesis to specify for planning MP linkage studies. (2) We demonstrate through extensive simulation that this evidential approach can yield low error rates under the null and alternative hypotheses for both lods and mods, despite the fact that mod scores are not true LRs. Using these results we provide a coherent approach to implement a MP linkage study using the evidential paradigm.

Evidence of shared genetic risk factors for migraine and rolandic epilepsy.

PURPOSE: Evidence for a specific association between migraine and rolandic epilepsy (RE) has been conflicting. Children with migraine frequently have electroencephalographic (EEG) abnormalities, including rolandic discharges, and approximately 50% of siblings of patients with RE exhibit rolandic discharges. We assessed migraine risk in RE probands and their siblings. METHODS: We used cohort and reconstructed cohort designs to respectively assess the relative risk of migraine in 72 children with RE and their 88 siblings using International Classification of Headache Disorders (ICHD-2) criteria. Incidences were compared in 150 age and geographically matched nonepilepsy probands and their 188 siblings. We used a Cox proportional hazards model, using age as the time base, adjusting hazard ratios (HRs) for sex in the proband analysis, and for sex and proband migraine status in the sibling analysis. RESULTS: Prevalence of migraine in RE probands was 15% versus 7% in nonepilepsy probands, and in siblings of RE probands prevalence was 14% versus 4% in nonepilepsy siblings. The sex-adjusted HR of migraine for an RE proband was 2.46 [95% confidence interval (CI) 1.06-5.70]. The adjusted HR of having > or =1 sibling with migraine in an RE family was 3.35 (95% CI 1.20-9.33), whereas the HR of any one sibling of a RE proband was 2.86 (95% CI 1.10-7.43). DISCUSSION: Migraine is strongly comorbid in RE and independently clusters in their siblings. These results suggest shared susceptibility to migraine and RE that is not directly mediated by epileptic seizures. Susceptibility gene variants for RE may be tested as risk factors for migraine.

Improving imputation in disease-relevant regions: lessons from cystic fibrosis.

Does genotype imputation with public reference panels identify variants contributing to disease? Genotype imputation using the 1000 Genomes Project (1KG; 2504 individuals) displayed poor coverage at the causal cystic fibrosis (CF) transmembrane conductance regulator (CFTR) locus for the International CF Gene Modifier Consortium. Imputation with the larger Haplotype Reference Consortium (HRC; 32,470 individuals) displayed improved coverage but low sensitivity of variants clinically relevant for CF. A hybrid reference that combined whole genome sequencing (WGS) from 101 CF individuals with the 1KG imputed a greater number of single-nucleotide variants (SNVs) that would be analyzed in a genetic association study (r2 ≥ 0.3 and MAF ≥ 0.5%) than imputation with the HRC, while the HRC excelled in the lower frequency spectrum. Using the 1KG or HRC as reference panels missed the most common CF-causing variants or displayed low imputation accuracy. Designs that incorporate population-specific WGS can improve imputation accuracy at disease-specific loci, while imputation using public data sets can omit disease-relevant genotypes.

Goodness of fit for the logistic regression model using relative belief.

A logistic regression model is a specialized model for product-binomial data. When a proper, noninformative prior is placed on the unrestricted model for the product-binomial model, the hypothesis H 0 of a logistic regression model holding can then be assessed by comparing the concentration of the posterior distribution about H 0 with the concentration of the prior about H 0. This comparison is effected via a relative belief ratio, a measure of the evidence that H 0 is true, together with a measure of the strength of the evidence that H 0 is either true or false. This gives an effective goodness of fit test for logistic regression.

The genetics of reading disability in an often excluded sample: novel loci suggested for reading disability in Rolandic epilepsy.

BACKGROUND: Reading disability (RD) is a common neurodevelopmental disorder with genetic basis established in families segregating "pure" dyslexia. RD commonly occurs in neurodevelopmental disorders including Rolandic Epilepsy (RE), a complex genetic disorder. We performed genomewide linkage analysis of RD in RE families, testing the hypotheses that RD in RE families is genetically heterogenenous to pure dyslexia, and shares genetic influences with other sub-phenotypes of RE. METHODS: We initially performed genome-wide linkage analysis using 1000 STR markers in 38 US families ascertained through a RE proband; most of these families were multiplex for RD. We analyzed the data by two-point and multipoint parametric LOD score methods. We then confirmed the linkage evidence in a second US dataset of 20 RE families. We also resequenced the SEMA3C gene at the 7q21 linkage locus in members of one multiplex RE/RD pedigree and the DISC1 gene in affected pedigrees at the 1q42 locus. RESULTS: In the discovery dataset there was suggestive evidence of linkage for RD to chromosome 7q21 (two-point LOD score 3.05, multipoint LOD 3.08) and at 1q42 (two-point LOD 2.87, multipoint LOD 3.03). Much of the linkage evidence at 7q21 derived from families of French-Canadian origin, whereas the linkage evidence at 1q42 was well distributed across all the families. There was little evidence for linkage at known dyslexia loci. Combining the discovery and confirmation datasets increased the evidence at 1q42 (two-point LOD = 3.49, multipoint HLOD = 4.70), but decreased evidence at 7q21 (two-point LOD = 2.28, multipoint HLOD  = 1.81), possibly because the replication sample did not have French Canadian representation. DISCUSSION: Reading disability in rolandic epilepsy has a genetic basis and may be influenced by loci at 1q42 and, in some populations, at 7q21; there is little evidence of a role for known DYX loci discovered in "pure" dyslexia pedigrees. 1q42 and 7q21 are candidate novel dyslexia loci.

Centrotemporal sharp wave EEG trait in rolandic epilepsy maps to Elongator Protein Complex 4 (ELP4).

Rolandic epilepsy (RE) is the most common human epilepsy, affecting children between 3 and 12 years of age, boys more often than girls (3:2). Focal sharp waves in the centrotemporal area define the electroencephalographic (EEG) trait for the syndrome, are a feature of several related childhood epilepsies and are frequently observed in common developmental disorders (eg, speech dyspraxia, attention deficit hyperactivity disorder and developmental coordination disorder). Here we report the first genome-wide linkage scan in RE for the EEG trait, centrotemporal sharp waves (CTS), with genome-wide linkage of CTS to 11p13 (HLOD 4.30). Pure likelihood statistical analysis refined our linkage peak by fine mapping CTS to variants in Elongator Protein Complex 4 (ELP4) in two independent data sets; the strongest evidence was with rs986527 in intron 9 of ELP4, providing a likelihood ratio of 629:1 (P=0.0002) in favor of an association. Resequencing of ELP4 coding, flanking and promoter regions revealed no significant exonic polymorphisms. This is the first report of a gene implicated in a common focal epilepsy and the first human disease association of ELP4. ELP4 is a component of the Elongator complex, involved in transcription and tRNA modification. Elongator depletion results in the brain-specific downregulation of genes implicated in cell motility and migration. We hypothesize that a non-coding mutation in ELP4 impairs brain-specific Elongator-mediated interaction of genes implicated in brain development, resulting in susceptibility to seizures and neurodevelopmental disorders.