Inhibition of heat shock 90 (Hsp90) molecular chaperones allows targeting of multiple proteins involved in tumorigenesis. We investigated the safety, recommended phase 2 dose (RP2D), and pharmacokinetic and pharmacodynamic profile of onalespib (AT13387), a potent synthetic Hsp90 inhibitor, administered on days 1, 2, 8, 9, 15, and 16 of 28 day cycles (QDx2/week) in a phase I trial. This study followed an accelerated titration design with a starting dose of 20 mg/m(2)/dose and a standard 3 + 3 dose escalation design for dose level 4 (120 mg/m(2)/dose) and above. Additional patients were enrolled at the RP2D with mandatory paired tumor biopsies to assess modulation of 210 client proteins using reverse phase protein array analysis. Thirty-one patients were treated; RP2D was established at 160 mg/m(2)/dose on the QDx2/week schedule. Common toxicities were gastrointestinal, hepatic, and hematologic. Pharmacokinetic profile was linear and plasma levels increased proportionally with dose (T½ ~8 h). No responses were observed; eight patients had stable disease for > 2 cycles with one patient remaining on study for 6 cycles. Target engagement was demonstrated by transcriptional upregulation of Hsp70 and Hsp27 in PBMCs. Statistically significant modulation of client proteins was not achieved in the 9 paired tumor biopsies evaluated; however, hierarchical clustering revealed two subgroups of patients with differential patterns of protein expression. Further combination studies are needed in order to target prospective driver oncoproteins.

Oral squamous cell carcinoma (OSCC) is the most common malignant tumor of the oral cavity, and long non-coding (lnc)RNA of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) was recently reported to play a crucial role in OSCC development and progression. However, potential effects of genetic variants of MALAT1 on the development of OSCC are still unclear. Herein, we performed a case-control study in 1350 patients with OSCC and 1199 healthy controls to evaluate the association between functional single-nucleotide polymorphisms (SNPs) of MALAT1 and OSCC susceptibility, as well as its clinicopathologic characteristics. A TaqMan allelic discrimination assay was used to genotype four tagging SNPs, viz., rs3200401 C>T, rs619586 A>G, rs1194338 C>A, and rs7927113 G>A, and results showed that the MALAT1 rs3200401 T allele had a lower risk of OSCC (adjusted odds ratio (AOR): 0.779, 95% confidence interval (CI): 0.632~0.960, p=0.019) and a higher risk of developing moderately (grade II)/poorly (grade III) differentiated OSCC (AOR: 1.508-fold, 95% CI: 1.049~2.169, p=0.027) under a dominant model. According to environmental carcinogen exposure, patients with a betel quid-chewing habit who carried the T allele of rs3200401 more easily developed high-grade (II/III) OSCC (AOR: 1.588, 95% CI: 1.055~2.390, p=0.027), and patients with the same genotype but who did not chew betel quid had a lower risk of developing lymph node metastasis (AOR: 0.437, 95% CI: 0.255~0.749, p=0.003). In addition to rs3200401, the rs619586 AG/GG genotype was associated with increased risks of developing advanced stages (III+IV) and larger tumor sizes (>T2) compared to the AA genotype, especially in the subgroup of betel quid chewers. Furthermore, analyses of clinical datasets revealed that the MALAT1 expression level was upregulated in OSCC compared to normal tissues, especially in the betel quid-chewing population. These results indicated involvement of MALAT1 SNPs rs3200401 and rs619586 in the development of OSCC and support the interaction between MALAT1 gene polymorphisms and the environmental carcinogen as a predisposing factor for OSCC progression.

Psychiatric disorders are associated with accelerated aging and enhanced risk for neurodegenerative disorders. Brain aging is associated with molecular, cellular and structural changes that are robust on the group-level, yet show substantial inter-individual variability. Here we assessed deviations in gene expression from normal age-dependent trajectories, and tested their validity as predictors of risk for major mental illnesses and neurodegenerative disorders. We performed large-scale gene expression and genotype analyses in postmortem samples of two frontal cortical brain regions from 214 control subjects aged 20–90 years. Individual estimates of “molecular age” were derived from age-dependent genes, identified by robust regression analysis. Deviation from chronological age was defined as “delta age”. Genetic variants associated with deviations from normal gene expression patterns were identified by expression quantitative trait loci (cis-eQTL) of age-dependent genes or genome-wide association study (GWAS) on delta age, combined into distinct polygenic risk scores (PRS cis-eQTL and PRS GWAS ), and tested for predicting brain disorders or pathology in independent postmortem expression datasets and clinical cohorts. In these validation datasets, molecular ages, defined by 68 and 76 age-related genes for two brain regions respectively, were positively correlated with chronological ages (r=0.88/0.91), elevated in bipolar disorder (BP) and schizophrenia (SCZ), and unchanged in major depressive disorder (MDD). Exploratory analyses in independent clinical datasets show that PRSs were associated with SCZ and MDD diagnostics, and with cognition in SCZ and pathology in Alzheimer’s disease (AD). These results suggest that older molecular brain aging is a common feature of severe mental illnesses and neurodegeneration.

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly (r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman’s coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.