Discovery of Cancer-Specific and Independent Prognostic Gene Subsets of the Slit-Robo Family Using TCGA-PANCAN Datasets.

The Slit-Robo family of axon guidance molecules works in concert, playing important roles in organ development and cancer. Expressions of individual Slit-Robo genes have been used in calculating univariable hazard ratios (HRuni) for predicting cancer prognosis in the literature. However, Slit-Robo members do not act independently; hence, hazard ratios from multivariable Cox regression (HRmulti) on the whole gene set can further lead to identification of cancer-specific, novel, and independent prognostic gene pairs or modules. Herein, we obtained mRNA expressions of the Slit-Robo family consisting of four Robos (ROBO1/2/3/4) and three Slits (SLIT1/2/3), along with four types of survival outcome across cancers found in the Cancer Genome Atlas (TCGA). We used cluster heat maps to visualize closely associated pairs/modules of prognostic genes across 33 different cancers. We found a smaller number of significant genes in HRmulti than in HRuni, suggesting that the former analysis was less redundant. High ROBO4 expression emerged as relatively protective within the family, in both types of HR analyses. Multivariable Cox regression, on the other hand, revealed significantly more HR signatures containing Slit-Robo pairs acting in opposing directions than those containing Slit-Slit or Robo-Robo pairs for disease-specific survival. Furthermore, we discovered, through the online app SmulTCan's lasso regression, Slit-Robo gene subsets that significantly differentiated between high- versus low-risk prognosis patient groups, particularly for renal cancers and low-grade glioma. The statistical pipeline reported herein can help test independent and significant pairs/modules within a codependent gene family for cancer prognostication, and thus should also prove useful in personalized/precision medicine research.

SmulTCan: A Shiny application for multivariable survival analysis of TCGA data with gene sets.

BACKGROUND: Survival analysis is widely used in cancer research, and although several methods exist in R, there is the need for a more interactive, flexible, yet comprehensive online tool to analyze gene sets using Cox proportional hazards (CPH) models. The web-based Shiny application (app) SmulTCan extends existing tools to multivariable CPH models of gene sets-as exemplified using the netrins and their receptors (netrins-receptors). It can be used to identify survival gene signatures (GSs) and select the best subsets of input gene, microRNA, methylation level, and copy number variation sets from the Cancer Genome Atlas (TCGA). OBJECTIVES: To create a tool for CPH model building and best subset selection, using survival data from TCGA with input gene expression files from UCSC Xena. Furthermore, we aim to analyze the input TSV file of netrins-receptors in SmulTCan and discuss our findings. METHODS: SmulTCan uses Shiny's reactivity with built-in R functions from packages for CPH model analysis and best subset selection including "survminer", "riskRegression", "rms", "glmnet", and "BeSS". RESULTS: Results from the SmulTCan app with the netrins-receptors gene set indicated unique hazard ratio GSs in certain renal and neural cancers, while the best subsets for this gene set, obtained via the app, could differentiate between prognostic outcomes in these cancers. AVAILABILITY: SmulTCan is available at http://konulabapps.bilkent.edu.tr:3838/SmulTCan/. The input file for netrins-receptors is available in the online version of this paper. TCGA dataset folders containing survival files are available through https://github.com/aozh7/SmulTCan/. SUPPLEMENTARY INFORMATION: The supplementary information (SI) accompanies the online version of this article.

Human CRY1 variants associate with attention deficit/hyperactivity disorder.

Attention deficit/hyperactivity disorder (ADHD) is a common and heritable phenotype frequently accompanied by insomnia, anxiety, and depression. Here, using a reverse phenotyping approach, we report heterozygous coding variations in the core circadian clock gene cryptochrome 1 in 15 unrelated multigenerational families with combined ADHD and insomnia. The variants led to functional alterations in the circadian molecular rhythms, providing a mechanistic link to the behavioral symptoms. One variant, CRY1Δ11 c.1657+3A>C, is present in approximately 1% of Europeans, therefore standing out as a diagnostic and therapeutic marker. We showed by exome sequencing in an independent cohort of patients with combined ADHD and insomnia that 8 of 62 patients and 0 of 369 controls carried CRY1Δ11. Also, we identified a variant, CRY1Δ6 c.825+1G>A, that shows reduced affinity for BMAL1/CLOCK and causes an arrhythmic phenotype. Genotype-phenotype correlation analysis revealed that this variant segregated with ADHD and delayed sleep phase disorder (DSPD) in the affected family. Finally, we found in a phenome-wide association study involving 9438 unrelated adult Europeans that CRY1Δ11 was associated with major depressive disorder, insomnia, and anxiety. These results defined a distinctive group of circadian psychiatric phenotypes that we propose to designate as "circiatric" disorders.