Single-nucleotide variation and gene expression of disease samples represent important resources for biomarker discovery. Many databases have been built to host and make available such data to the community, but these databases are frequently limited in scope and/or content. BioMuta, a database of cancer-associated single-nucleotide variations, and BioXpress, a database of cancer-associated differentially expressed genes and microRNAs, differ from other disease-associated variation and expression databases primarily through the aggregation of data across many studies into a single source with a unified representation and annotation of functional attributes. Early versions of these resources were initiated by pilot funding for specific research applications, but newly awarded funds have enabled hardening of these databases to production-level quality and will allow for sustained development of these resources for the next few years. Because both resources were developed using a similar methodology of integration, curation, unification, and annotation, we present BioMuta and BioXpress as allied databases that will facilitate a more comprehensive view of gene associations in cancer. BioMuta and BioXpress are hosted on the High-performance Integrated Virtual Environment (HIVE) server at the George Washington University at https://hive.biochemistry.gwu.edu/biomuta and https://hive.biochemistry.gwu.edu/bioxpress, respectively.
The Wee1 kinase inhibitor adavosertib abrogates cell cycle arrest, leading to cell death. Prior testing of twice-daily adavosertib in patients with advanced solid tumors determined the recommended phase 2 dose (RPh2D). Here, we report results for once-daily adavosertib.Patients and Methods: A 3 + 3 dose escalation design was used, with adavosertib given once daily on days 1-5 and 8-12 in 21-day cycles. Molecular biomarkers of Wee1 activity, including tyrosine 15-phosphorylated Cdk1/2 [pY15-Cdk]), were assessed in paired tumor biopsies.Whole-exome sequencing and RNA sequencing of remaining tumor tissue identified potential predictive biomarkers.Results: Among the 42 patients enrolled, the most common toxicities were gastrointestinal and hematological; dose-limiting toxicities were grade 4 hematological toxicity and grade 3 fatigue.The once-daily RPh2D was 300 mg. Six patients (14%) had confirmed partial responses (PR): 4 ovarian, 2 endometrial. Adavosertib plasma exposures were similar to those from twice-daily dosing. On cycle 1 day 8 (pre-dose), tumor pY15-Cdk levels were higher than baseline in 4 of 8 patients, suggesting target rebound during the day 5-8 dosing break. One patient who progressed rapidly had a tumor WEE1 mutation and potentially compensatory PKMYT1 overexpression.Baseline CCNE1 overexpression occurred in both of 2 responding patients, only 1 of whom had CCNE1 amplification, and in 0 of 3 non-responding patients. Conclusions:We determined the once-daily adavosertib RPh2D and observed activity in patients with ovarian or endometrial carcinoma, including 2 with baseline CCNE1 mRNA overexpression. Future studies will determine whether CCNE1 overexpression is a predictive biomarker for adavosertib.
Human endogenous retroviruses (HERVs) have been investigated for potential links with human cancer. However, the distribution of somatic nucleotide variations in HERV elements has not been explored in detail. This study aims to identify HERV elements with an over-representation of somatic mutations (hot spots) in cancer patients. Four HERV elements with mutation hotspots were identified that overlap with exons of four human protein coding genes. These hotspots were identified based on the significant over-representation (p<8.62e-4) of non-synonymous single-nucleotide variations (nsSNVs). These genes are TNN (HERV-9/LTR12), OR4K15 (HERV-IP10F/LTR10F), ZNF99 (HERV-W/HERV17/LTR17), and KIR2DL1 (MST/MaLR). In an effort to identify mutations that effect survival, all nsSNVs were further evaluated and it was found that kidney cancer patients with mutation C2270G in ZNF99 have a significantly lower survival rate (hazard ratio = 2.6) compared to those without it. Among HERV elements in the human non-protein coding regions, we found 788 HERVs with significantly elevated numbers of somatic single-nucleotide variations (SNVs) (p<1.60e-5). From this category the top three HERV elements with significantly over-represented SNVs are HERV-H/LTR7, HERV-9/LTR12 and HERV-L/MLT2. Majority of the SNVs in these 788 HERV elements are located in three DNA functional groups: long non-coding RNAs (lncRNAs) (60%), introns (22.2%) and transcriptional factor binding sites (TFBS) (14.8%). This study provides a list of mutational hotspots in HERVs, which could potentially be used as biomarkers and therapeutic targets.
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