A novel treatment strategy utilizing panobinostat for high-risk and treatment-refractory hepatoblastoma.

BACKGROUND & AIMS: Patients with metastatic, treatment-refractory, and relapsed hepatoblastoma (HB) have survival rates of less than 50% due to limited treatment options. To develop new therapeutic strategies for these patients, our laboratory has developed a preclinical testing pipeline. Given that histone deacetylase (HDAC) inhibition has been proposed for HB, we hypothesized that we could find an effective combination treatment strategy utilizing HDAC inhibition. METHODS: RNA sequencing, microarray, NanoString, and immunohistochemistry data of patient HB samples were analyzed for HDAC class expression. Patient-derived spheroids (PDSp) were used to screen combination chemotherapy with an HDAC inhibitor, panobinostat. Patient-derived xenograft (PDX) mouse models were developed and treated with the combination therapy that showed the highest efficacy in the PDSp drug screen. RESULTS: HDAC RNA and protein expression were elevated in HB tumors compared to normal livers. Panobinostat (IC50 of 0.013-0.059 µM) showed strong in vitro effects and was associated with lower cell viability than other HDAC inhibitors. PDSp demonstrated the highest level of cell death with combination treatment of vincristine/irinotecan/panobinostat (VIP). All four models responded to VIP therapy with a decrease in tumor size compared to placebo. After 6 weeks of treatment, two models demonstrated necrotic cell death, with lower Ki67 expression, decreased serum alpha fetoprotein and reduced tumor burden compared to paired VI- and placebo-treated groups. CONCLUSIONS: Utilizing a preclinical HB pipeline, we demonstrate that panobinostat in combination with VI chemotherapy can induce an effective tumor response in models developed from patients with high-risk, relapsed, and treatment-refractory HB. IMPACT AND IMPLICATIONS: Patients with treatment-refractory hepatoblastoma have limited treatment options with survival rates of less than 50%. Our manuscript demonstrates that combination therapy with vincristine, irinotecan, and panobinostat reduces the size of high-risk, relapsed, and treatment-refractory tumors. With this work we provide preclinical evidence to support utilizing this combination therapy as an arm in future clinical trials.

Acute Intermittent Porphyria: Predicted Pathogenicity of HMBS Variants Indicates Extremely Low Penetrance of the Autosomal Dominant Disease.

Acute intermittent porphyria results from hydroxymethylbilane synthase (HMBS) mutations that markedly decrease HMBS enzymatic activity. This dominant disease is diagnosed when heterozygotes have life-threatening acute attacks, while most heterozygotes remain asymptomatic and undiagnosed. Although >400 HMBS mutations have been reported, the prevalence of pathogenic HMBS mutations in genomic/exomic databases, and the actual disease penetrance are unknown. Thus, we interrogated genomic/exomic databases, identified non-synonymous variants (NSVs) and consensus splice-site variants (CSSVs) in various demographic/racial groups, and determined the NSV's pathogenicity by prediction algorithms and in vitro expression assays. Caucasians had the most: 58 NSVs and two CSSVs among ∼92,000 alleles, a 0.00575 combined allele frequency. In silico algorithms predicted 14 out of 58 NSVs as "likely-pathogenic." In vitro expression identified 10 out of 58 NSVs as likely-pathogenic (seven predicted in silico), which together with two CSSVs had a combined allele frequency of 0.00056. Notably, six presumably pathogenic mutations/NSVs in the Human Gene Mutation Database were benign. Compared with the recent prevalence estimate of symptomatic European heterozygotes (∼0.000005), the prevalence of likely-pathogenic HMBS mutations among Caucasians was >100 times more frequent. Thus, the estimated penetrance of acute attacks was ∼1% of heterozygotes with likely-pathogenic mutations, highlighting the importance of predisposing/protective genes and environmental modifiers that precipitate/prevent the attacks.

Optimization, purification and characterization of pectinases from pectinolytic strain, Aspergillus foetidus MTCC 10559.

A strain (MPUAT-2), isolated from coconut hull and identified as Aspergillus foetidus MTCC 10559, was used for pectinase production. Optimum pectinase production was obtained at pH 8.0 and temperature 35 degrees C under static conditions in submerged fermentation after 5 days of incubation. Orange peel, a byproduct of fruit industry, was used as a sole carbon source (3% w/v) to produce high pectinase, thus making the process cost effective. The culture filtrate was analyzed for pectin methyl esterase (PME) and endopolygalacturonase (endo-PG) enzymes. The enzymes, PME and endo-PG were purified using ammonium sulphate precipitation and molecular exclusion chromatography (Sephadex G-75) with corresponding recovery of 39.3 and 44.3%. The partially purified enzymes were also characterized for their kinetic properties.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials.

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species. To address this issue, we are developing MIRACCL (molecular and imaging response analysis of co-clinical trials), a web-based analytical tool. For prototyping, we simulated data for a co-clinical trial in "triple-negative" breast cancer (TNBC) by pairing pre- (T0) and on-treatment (T1) magnetic resonance imaging (MRI) from the I-SPY2 trial, as well as PDX-based T0 and T1 MRI. Baseline (T0) and on-treatment (T1) RNA expression data were also simulated for TNBC and PDX. Image features derived from both datasets were cross-referenced to omic data to evaluate MIRACCL functionality for correlating and displaying MRI-based changes in tumor size, vascularity, and cellularity with changes in mRNA expression as a function of treatment.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach.

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential.

Immunologically "cold" triple negative breast cancers engraft at a higher rate in patient derived xenografts.

TNBC is a heterogeneous subtype of breast cancer, and only a subset of TNBC can be established as PDXs. Here, we show that there is an engraftment bias toward TNBC with low levels of immune cell infiltration. Additionally, TNBC that failed to engraft show gene expression consistent with a cancer-promoting immunological state, leading us to hypothesize that the immunological state of the tumor and possibly the state of the immune system of the host may be essential for engraftment.

VEGF-C mediates tumor growth and metastasis through promoting EMT-epithelial breast cancer cell crosstalk.

It is well established that a subset of cells within primary breast cancers can undergo an epithelial-to-mesenchymal transition (EMT), although the role of EMT in metastasis remains controversial. We previously demonstrated that breast cancer cells that had undergone an oncogenic EMT could increase metastasis of neighboring cancer cells via non-canonical paracrine-mediated activation of GLI activity that is dependent on SIX1 expression in the EMT cancer cells. However, the mechanism by which these SIX1-expressing EMT cells activate GLI signaling remained unclear. In this study, we demonstrate a novel mechanism for activation of GLI-mediated signaling in epithelial breast tumor cells via EMT cell-induced production and secretion of VEGF-C. We show that VEGF-C, secreted by breast cancer cells that have undergone an EMT, promotes paracrine-mediated increases in proliferation, migration, and invasion of epithelial breast cancer cells, via non-canonical activation of GLI-signaling. We further show that the aggressive phenotypes, including metastasis, imparted by EMT cells on adjacent epithelial cancer cells can be disrupted by either inhibiting VEGF-C in EMT cells or by knocking down NRP2, a receptor which interacts with VEGF-C, in neighboring epithelial cancer cells. Interrogation of TCGA and GEO public datasets supports the relevance of this pathway in human breast cancer, demonstrating that VEGF-C strongly correlates with activation of Hedgehog signaling and EMT in the human disease. Our study suggests that the VEGF-C/NRP2/GLI axis is a novel and conserved paracrine means by which EMT cells enhance metastasis, and provides potential targets for therapeutic intervention in this heterogeneous disease.

Molecular Diversity and Gene Evolution of the Venom Arsenal of Terebridae Predatory Marine Snails.

Venom peptides from predatory organisms are a resource for investigating evolutionary processes such as adaptive radiation or diversification, and exemplify promising targets for biomedical drug development. Terebridae are an understudied lineage of conoidean snails, which also includes cone snails and turrids. Characterization of cone snail venom peptides, conotoxins, has revealed a cocktail of bioactive compounds used to investigate physiological cellular function, predator-prey interactions, and to develop novel therapeutics. However, venom diversity of other conoidean snails remains poorly understood. The present research applies a venomics approach to characterize novel terebrid venom peptides, teretoxins, from the venom gland transcriptomes of Triplostephanus anilis and Terebra subulata. Next-generation sequencing and de novo assembly identified 139 putative teretoxins that were analyzed for the presence of canonical peptide features as identified in conotoxins. To meet the challenges of de novo assembly, multiple approaches for cross validation of findings were performed to achieve reliable assemblies of venom duct transcriptomes and to obtain a robust portrait of Terebridae venom. Phylogenetic methodology was used to identify 14 teretoxin gene superfamilies for the first time, 13 of which are unique to the Terebridae. Additionally, basic local algorithm search tool homology-based searches to venom-related genes and posttranslational modification enzymes identified a convergence of certain venom proteins, such as actinoporin, commonly found in venoms. This research provides novel insights into venom evolution and recruitment in Conoidean predatory marine snails and identifies a plethora of terebrid venom peptides that can be used to investigate fundamental questions pertaining to gene evolution.

The khmer software package: enabling efficient nucleotide sequence analysis.

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at  https://github.com/dib-lab/khmer/.

Effect of salt on survival and P-solubilization potential of phosphate solubilizing microorganisms from salt affected soils.

A total of 23 phosphate solubilizing bacteria (PSB) and 35 phosphate solubilizing fungi (PSF) were isolated from 19 samples of salt affected soils. The ability of 12 selected PSB and PSF to grow and solubilize tricalcium phosphate in the presence of different concentrations of NaCl was examined. Among 12 PSB, Aerococcus sp. strain PSBCRG1-1 recorded the highest (12.15) log viable cell count at 0.4 M NaCl concentration after 7 days after incubation (DAI) and the lowest log cell count (1.39) was recorded by Pseudomonas aeruginosa strain PSBI3-1 at 2.0 M NaCl concentration after 24 h of incubation. Highest mycelial dry weight irrespective of NaCl concentrations was recorded by the Aspergillus terreus strain PSFCRG2-1 (0.567 g). The percent P i release, in general, was found to increase with increase in NaCl concentration up to 0.8 M for bacterial solubilization and declined thereafter. At 15 DAI, strain Aerococcus sp. strain PSBCRG1-1 irrespective of NaCl concentrations showed the maximum P-solubilization (12.12%) which was significantly superior over all other isolates. The amount of P i released in general among PSF was found to decrease with increase in NaCl concentration at all the incubation periods. Aspergillus sp. strain PSFNRH-2 (20.81%) recorded the maximum P i release irrespective of the NaCl concentrations and was significantly superior over all other PSF at 7 DAI.