Biology subjects

Zheng, S.

Publications and source records attributed to Zheng, S..

220 records · Page 13Linked to original sources

bioRxiv2017

TumorFusions: an integrative resource for reporting cancer-associated transcript fusions in 33 tumor types

Fusion genes, particularly those involving kinases, have been demonstrated as drivers and are frequent therapeutic targets in cancer1. Here, we describe our results on detecting transcript fusions across 33 cancer types from The Cancer Genome Atlas (TCGA), totaling 9,966 cancer samples and 648 normal samples2. Preprocessing, including read alignment to both genome and transcriptome, and fusion detection were carried out using a uniform pipeline3. To validate the resultant fusions, we also called somatic structural variations for 561 cancers from whole genome sequencing data. A summary of the data used in this study is provided in Table S1. Our results can be accessed per our portal at http://www.tumorfusions.org.

cancer biology↗

bioRxiv2017

Platform for rapid nanobody discovery in vitro

Camelid single-domain antibody fragments (\"nanobodies\") provide the remarkable specificity of antibodies within a single immunoglobulin VHH domain. This unique feature enables applications ranging from their use as biochemical tools to therapeutic agents. Virtually all nanobodies reported to date have been obtained by animal immunization, a bottleneck restricting many applications of this technology. To solve this problem, we developed a fully in vitro platform for nanobody discovery based on yeast surface display of a synthetic nanobody scaffold. This platform provides a facile and cost-effective method for rapidly isolating nanobodies targeting a diverse range of antigens. We provide a blueprint for identifying nanobodies starting from both purified and non-purified antigens, and in addition, we demonstrate application of the platform to discover rare conformationally-selective nanobodies to a lipid flippase and a G protein-coupled receptor. To facilitate broad deployment of this platform, we have made the library and all associated protocols publicly available.

biochemistry↗

bioRxiv2017

Correcting For Cell-Type Heterogeneity In Epigenome-Wide Association Studies: Premature Analyses And Conclusions

Recently, a study by Rahmani et al [1] claimed that a reference-free cell-type deconvolution method, called ReFACTor, leads to improved power and improved estimates of cell-type composition compared to competing reference-free and reference-based methods in the context of Epigenome-Wide Association Studies (EWAS). However, we identified many critical flaws (both conceptual and statistical in nature), which seriously question the validity of their claims. We outlined constructive criticism in a recent correspondence letter, Zheng et al [2]. The purpose of this letter is two-fold. First, to present additional analyses, which demonstrate that our original criticism is statistically sound. Second, to highlight additional serious concerns, which Rahmani et al have not yet addressed. In summary, we find that ReFACTor has not been demonstrated to outperform state-of-the-art reference-free methods such as SVA or RefFreeEWAS, nor state-of-the-art reference-based methods. Thus, the claim by Rahmani et al (a claim reiterated in their recent response letter [3]) that ReFACT or represents an advance over the state-of-the-art is not supported by an objective and rigorous statistical analysis of the data.

bioinformatics↗

bioRxiv2016

Extrachromosal DNA elements can drive disease evolution in glioblastoma

To understand how genomic heterogeneity of glioblastoma (GBM) contributes to the poor response to therapy, which is characteristic of this disease, we performed DNA and RNA sequencing on GBM tumor samples and the neurospheres and orthotopic xenograft models derived from them. We used the resulting data set to show that somatic driver alterations including single nucleotide variants, focal DNA alterations, and oncogene amplification in extrachromosomal DNA (ecDNA) elements were in majority propagated from tumor to model systems. In several instances, ecDNAs and chromosomal alterations demonstrated divergent inheritance patterns and clonal selection dynamics during cell culture and xenografting. Longitudinal patient tumor profiling showed that oncogenic ecDNAs are frequently retained after disease recurrence. Our analysis shows that extrachromosomal elements increase the genomic heterogeneity during tumor evolution of glioblastoma, independent of chromosomal DNA alterations.

cancer biology↗