Faculty Bibliography

Squamous cell carcinomas (SCCs) are heterogeneous tumors sustained by tumor-propagating cancer cells (TPCs). SCCs frequently resist chemotherapy through still unknown mechanisms. Here, we combine H2B-GFP-based pulse-chasing with cell-surface markers to distinguish quiescent from proliferative TPCs within SCCs. We find that quiescent TPCs resist DNA damage and exhibit increased tumorigenic potential in response to chemotherapy, whereas proliferative TPCs undergo apoptosis. Quiescence is regulated by TGF-beta/SMAD signaling, which directly regulates cell-cycle gene transcription to control a reversible G1 cell-cycle arrest, independent of p21CIP function. Indeed, genetic or pharmacological TGF-beta inhibition increases the susceptibility of TPCs to chemotherapy because it prevents entry into a quiescent state. These findings provide direct evidence that TPCs can reversibly enter a quiescent, chemoresistant state and thereby underscore the need for combinatorial approaches to improve treatment of chemotherapy-resistant SCCs.

Low-grade astrocytomas (LGAs) carry neomorphic mutations in isocitrate dehydrogenase (IDH) concurrently with P53 and ATRX loss. To model LGA formation, we introduced R132H IDH1, P53 shRNA, and ATRX shRNA into human neural stem cells (NSCs). These oncogenic hits blocked NSC differentiation, increased invasiveness in vivo, and led to a DNA methylation and transcriptional profile resembling IDH1 mutant human LGAs. The differentiation block was caused by transcriptional silencing of the transcription factor SOX2 secondary to disassociation of its promoter from a putative enhancer. This occurred because of reduced binding of the chromatin organizer CTCF to its DNA motifs and disrupted chromatin looping. Our human model of IDH mutant LGA formation implicates impaired NSC differentiation because of repression of SOX2 as an early driver of gliomagenesis.

We report here an update to the draft genome sequence of Kluyvera intestini sp. nov. strain GT-16, generated using MinION long-read sequencing technology. The complete genome sequence of the human-derived strain GT-16 measured 5,768,848 bp. An improved high-quality complete genome sequence provides insights into the mobility potential of resistance genes in this species.

Loss-of-function mutations in TET2 occur frequently in patients with clonal hematopoiesis, myelodysplastic syndrome (MDS), and acute myeloid leukemia (AML) and are associated with a DNA hypermethylation phenotype. To determine the role of TET2 deficiency in leukemia stem cell maintenance, we generated a reversible transgenic RNAi mouse to model restoration of endogenous Tet2 expression. Tet2 restoration reverses aberrant hematopoietic stem and progenitor cell (HSPC) self-renewal in vitro and in vivo. Treatment with vitamin C, a co-factor of Fe2+ and alpha-KG-dependent dioxygenases, mimics TET2 restoration by enhancing 5-hydroxymethylcytosine formation in Tet2-deficient mouse HSPCs and suppresses human leukemic colony formation and leukemia progression of primary human leukemia PDXs. Vitamin C also drives DNA hypomethylation and expression of a TET2-dependent gene signature in human leukemia cell lines. Furthermore, TET-mediated DNA oxidation induced by vitamin C treatment in leukemia cells enhances their sensitivity to PARP inhibition and could provide a safe and effective combination strategy to selectively target TET deficiency in cancer.

Increased intestinal permeability and translocation of gut bacteria trigger various polyaetiological diseases associated with chronic inflammation and underlie a variety of poorly treatable pathologies. Previous studies have established a primary role of the microbiota composition and intestinal permeability in such pathologies. Using a rat model, we examined the effects of exposure to a bacteriophage cocktail on intestinal permeability and relative abundance of taxonomic units in the gut bacterial community. There was an increase in markers of impaired gut permeability, such as the lactulose/mannitol ratio, plasma endotoxin concentrations, and serum levels of inflammation-related cytokines, following the bacteriophage challenge. We observed significant differences in the alpha diversity of faecal bacterial species and found that richness and diversity index values increased following the bacteriophage challenge. There was a reduction in the abundance of Blautia, Catenibacterium, Lactobacillus, and Faecalibacterium species and an increase in Butyrivibrio, Oscillospira and Ruminococcus after bacteriophage administration. These findings provide novel insights into the role of bacteriophages as potentially pathogenic for mammals and their possible implication in the development of diseases associated with increased intestinal permeability.

Background: There are no predictive biomarkers of ipilimumab (IPI) toxicity. Of metastatic melanoma (MM) patients (pts) receiving IPI (3mg/kg), 35% require systemic therapies to treat immune-related adverse events (irAEs) and 20% must terminate treatment (Horvat et al., JCO 2015). Here we tested the hypothesis that a pre-existing autoantibody (autoAb) profile is predictive of IPI irAEs. Methods: We measured autoAb levels in pre- and post-treatment sera from mm pts who received IPI (3mg/kg) monotherapy on a proteome microarray containing ~20,000 unique full-length human proteins (HuProt array, CDI Laboratories). Clinical data were prospectively collected with protocol-driven follow-up. IrAEs were categorized by CTCAE guidelines as none (grade 0), mild (grade 1-2), or severe (grade 3-4). AutoAb levels were standardized using median quantile normalization and considered positive hits if > 2-SD above the peak array signal and differed by >=2 fold with p < 0.05 between toxicity groups (Non-parametric Analysis/Wilcox test). Results: Seventy-eight sera from 37 mm pts were analyzed. Antibodies against CTLA-4 were significantly elevated post IPI treatment (p < 0.0001), validating the assay. The pre-treatment levels of 190 IgG autoAbs were significantly diferent in pts who experienced irAEs (n = 28) compared to those with no irAEs (n = 9). Comparison of severe irAE (n = 9) and no irAE (n = 9) groups revealed 129 IgG autoAbs that significantly differed in pre-treatment sera. Localization and pathway analysis (UniProt, KEGG, Reactome) showed 81/190 (43%) of the autoAbs targeted nuclear and mitochondrial antigens and were enriched in metabolic pathways (p = 0.015). AutoAbs associated with irAEs did not correlate with treatment response. Conclusions: AutoAbs to antigens enriched in metabolic pathways prior to treatment may predict IPI-induced toxicity in MM. The subcellular localization of targeted antigens could explain the autoimmune toxicities associated with IPI. Studies in larger cohorts and in pts receiving other checkpoint inhibitors and/or combination therapies are essential to determine the validity of the data. If validated, our results would support the discovery of the first toxicity predictor in cancer immunotherapy

BACKGROUND: Long non-coding RNAs (lncRNAs) have emerged as a class of factors that are important for regulating development and cancer. Computational prediction of lncRNAs from ultra-deep RNA sequencing has been successful in identifying candidate lncRNAs. However, the complexity of handling and integrating different types of genomics data poses significant challenges to experimental laboratories that lack extensive genomics expertise. RESULT: To address this issue, we have developed lncRNA-screen, a comprehensive pipeline for computationally screening putative lncRNA transcripts over large multimodal datasets. The main objective of this work is to facilitate the computational discovery of lncRNA candidates to be further examined by functional experiments. lncRNA-screen provides a fully automated easy-to-run pipeline which performs data download, RNA-seq alignment, assembly, quality assessment, transcript filtration, novel lncRNA identification, coding potential estimation, expression level quantification, histone mark enrichment profile integration, differential expression analysis, annotation with other type of segmented data (CNVs, SNPs, Hi-C, etc.) and visualization. Importantly, lncRNA-screen generates an interactive report summarizing all interesting lncRNA features including genome browser snapshots and lncRNA-mRNA interactions based on Hi-C data. CONCLUSION: lncRNA-screen provides a comprehensive solution for lncRNA discovery and an intuitive interactive report for identifying promising lncRNA candidates. lncRNA-screen is available as open-source software on GitHub.