Association of Variants in PLD1, 3p24.1, and 10q11.21 Regions With Hirschsprung's Disease in Han Chinese Population

Construction of an lncRNA model for prognostic prediction of bladder cancer

OBJECTIVE

We aimed to investigate the role and potential mechanisms of long non-coding RNAs (lncRNAs) in bladder cancer (BC), as well as determine their prognostic value.

METHODS

LncRNA expression data and clinical data from BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to carry out principal component analysis (PCA), differential analysis, and prognostic analysis. Lasso regression and multivariate Cox regression analyses were performed to identify potential prognostic genes. The expression of five identified genes and their correlation with prognosis were verified using TCGA and GSE13507 datasets. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm the expression of these five genes in cell lines (two human BC cell lines and one human bladder epithelial cell line) and tissues (84 pairs of BC tissues and the corresponding paracancerous tissues). Risk scores that had been generated from the five genes and their prognostic ability were assessed by receiver operating characteristic (ROC) and Kaplan-Meier (KM) curves. Co-expressed genes were screened by WGCNA and analyzed by GO and KEGG, while functional enrichment and immune infiltration analyses were performed using STRING ( https://cn.string-db.org/ ) and TIMER2.0 ( http://timer.cistrome.org/ ) online tools, respectively.

RESULTS

CYP4F8, FAR2P1, LINC01518, LINC01764, and DTNA were identified as potential prognostic genes. We found that these five genes were differentially expressed in BC tissue, as well as in BC cell lines, and were significantly correlated with the prognosis of BC patients. KM analysis considering risk scores as independent parameters revealed differences in overall survival (OS) by subgroups. The ROC curve revealed that a combined model consisting of all five genes had good predictive ability at 1, 3, and 5 years. GO and KEGG analyses of 567 co-expressed genes revealed that these genes were significantly associated with muscle function.

CONCLUSION

LncRNAs can be good predictors of BC development and prognosis, and may act as potential tumor markers and therapeutic targets that may be beneficial in helping clinicians decide the most effective treatment strategies.

The Emerging Genetic Landscape of Hirschsprung Disease and Its Potential Clinical Applications

Hirschsprung disease (HSCR) is the leading cause of neonatal functional intestinal obstruction. It is a rare congenital disease with an incidence of one in 3,500-5,000 live births. HSCR is characterized by the absence of enteric ganglia in the distal colon, plausibly due to genetic defects perturbing the normal migration, proliferation, differentiation, and/or survival of the enteric neural crest cells as well as impaired interaction with the enteric progenitor cell niche. Early linkage analyses in Mendelian and syndromic forms of HSCR uncovered variants with large effects in major HSCR genes including RET, EDNRB, and their interacting partners in the same biological pathways. With the advances in genome-wide genotyping and next-generation sequencing technologies, there has been a remarkable progress in understanding of the genetic basis of HSCR in the past few years, with common and rare variants with small to moderate effects being uncovered. The discovery of new HSCR genes such as neuregulin and BACE2 as well as the deeper understanding of the roles and mechanisms of known HSCR genes provided solid evidence that many HSCR cases are in the form of complex polygenic/oligogenic disorder where rare variants act in the sensitized background of HSCR-associated common variants. This review summarizes the roadmap of genetic discoveries of HSCR from the earlier family-based linkage analyses to the recent population-based genome-wide analyses coupled with functional genomics, and how these discoveries facilitated our understanding of the genetic architecture of this complex disease and provide the foundation of clinical translation for precision and stratified medicine.