The UGT1A9*22 genotype identifies a high-risk group for irinotecan toxicity among gastric cancer patients.

Several studies have shown associations between irinotecan toxicity and UGT1A genetic variations in colorectal and lung cancer, but only limited data are available for gastric cancer patients. We evaluated the frequencies of UGT1A polymorphisms and their relationship with clinicopathologic parameters in 382 Korean gastric cancer patients. Polymorphisms of UGT1A1*6, UGT1A1*27, UGT1A1*28, UGT1A1*60, UGT1A7*2, UGT1A7*3, and UGT1A9*22 were genotyped by direct sequencing. In 98 patients treated with irinotecan-containing regimens, toxicity and response were compared according to the genotype. The UGT1A1*6 and UGT1A9*22 genotypes showed a higher prevalence in Korean gastric cancer patients, while the prevalence of the UG1A1*28 polymorphism was lower than in normal Koreans, as has been found in other studies of Asian populations. The incidence of severe diarrhea after irinotecan-containing treatment was more common in patients with the UGT1A1*6, UGT1A7*3, and UGT1A9*22 polymorphisms than in controls. The presence of the UGT1A1*6 allele also showed a significant association with grade III-IV neutropenia. Upon haplotype and diplotype analyses, almost every patient bearing the UGT1A1*6 or UGT1A7*3 variant also had the UGT1A9*22 polymorphism, and all severe manifestations of UGT1A polymorphism-associated toxicity were related to the UGT1A9*22 polymorphism. By genotyping UGT1A9*22 polymorphisms, we could identify high-risk gastric cancer patients receiving irinotecan-containing chemotherapy, who would experience severe toxicity. When treating high-risk patients with the UGT1A9*22 polymorphism, clinicians should closely monitor them for signs of severe toxicity such as intense diarrhea or neutropenia.

Cervical small cell neuroendocrine tumor mutation profiles via whole exome sequencing.

Cervical small cell neuroendocrine tumors (CSCNETs) are rare, aggressive neuroendocrine tumors (NETs). Reliable diagnostic and prognostic CSCNET markers are lacking, making diagnosis and prognosis prediction difficult, and treatment strategies limited. Here we provide mutation profiles for five tumor-normal paired CSCNETs using whole exome sequencing (WES). We expanded our assessment of frequently mutated genes to include publicly available data from 55 small intestine neuroendocrine tumors, 10 pancreatic neuroendocrine tumors, 42 small cell lung cancers, six NET cell lines, and 188 cervical cancers, along with our five CSCNETs. We identified 1,968 somatic mutations, including 1,710 missense, 106 nonsense, 144 splice site, 4 lncRNA, 3 nonstop, and 1 start codon mutation. We assigned functions to the 114 most frequently mutated genes based on gene ontology. ATRX, ERBB4, and genes in the Akt/mTOR pathway were most frequently mutated. Positive cytoplasmic ERBB4 immunohistochemical staining was detected in all CSCNET tumors tested, but not in adjacent normal tissues. To our knowledge, this study is the first to utilize WES in matched CSCNET and normal tissues to identify somatic mutations. Further studies will improve our understanding of how ATRX and ERBB4 mutations and AKT/mTOR signaling promote CSCNET tumorigenesis, and may be leveraged in novel anti-cancer treatment strategies.

Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditions.

BACKGROUND: Human diseases frequently cause complications such as obesity-induced diabetes and share numbers of pathological conditions, such as inflammation, by dysfunctions of common functional modules, such as protein-protein interactions (PPIs). METHODS: Our developed pipeline, ICod (Interaction analysis for disease Comorbidity), grades similarities between pairs of disease-related PPIs including comorbid diseases and pathological conditions. ICod displayed a disease similarity network consisting of nodes of disease PPIs and edges of similarity value. As a proof of concept, eight complex diseases and pathological conditions, such as type 2 diabetes, obesity, inflammation, and cancers, were examined to discover whether PPIs shared between diseases were associated with comorbidities. RESULTS: By comparing Medicare reports of disease co-occurrences from 31 million patients, the disease similarity network shows that PPIs of pathological conditions, including insulin resistance, and inflammation, overlap significantly with PPIs of various comorbid diseases, including diabetes, obesity, and cancers (p < 0.05). Interestingly, maintaining connectivity between essential genes was more drastically perturbed by removing a node of a disease-related gene rather than a pathological condition-related gene, such as one related to inflammations. CONCLUSION: Thus, PPIs of pathological symptoms are underlying functional modules across diseases accompanying comorbidity phenomena, whereas they contribute only marginally to maintaining interactions between essential genes.

Genetic and metabolic characterization of insomnia.

Insomnia is reported to chronically affect 10∼15% of the adult population. However, very little is known about the genetics and metabolism of insomnia. Here we surveyed 10,038 Korean subjects whose genotypes have been previously profiled on a genome-wide scale. About 16.5% reported insomnia and displayed distinct metabolic changes reflecting an increase in insulin secretion, a higher risk of diabetes, and disrupted calcium signaling. Insomnia-associated genotypic differences were highly concentrated within genes involved in neural function. The most significant SNPs resided in ROR1 and PLCB1, genes known to be involved in bipolar disorder and schizophrenia, respectively. Putative enhancers, as indicated by the histone mark H3K4me1, were discovered within both genes near the significant SNPs. In neuronal cells, the enhancers were bound by PAX6, a neural transcription factor that is essential for central nervous system development. Open chromatin signatures were found on the enhancers in human pancreas, a tissue where PAX6 is known to play a role in insulin secretion. In PLCB1, CTCF was found to bind downstream of the enhancer and interact with PAX6, suggesting that it can probably inhibit gene activation by PAX6. PLCB4, a circadian gene that is closely located downstream of PLCB1, was identified as a candidate target gene. Hence, dysregulation of ROR1, PLCB1, or PLCB4 by PAX6 and CTCF may be one mechanism that links neural and pancreatic dysfunction not only in insomnia but also in the relevant psychiatric disorders that are accompanied with circadian rhythm disruption and metabolic syndrome.