A high-throughput screen of real-time ATP levels in individual cells reveals mechanisms of energy failure.

Insufficient or dysregulated energy metabolism may underlie diverse inherited and degenerative diseases, cancer, and even aging itself. ATP is the central energy carrier in cells, but critical pathways for regulating ATP levels are not systematically understood. We combined a pooled clustered regularly interspaced short palindromic repeats interference (CRISPRi) library enriched for mitochondrial genes, a fluorescent biosensor, and fluorescence-activated cell sorting (FACS) in a high-throughput genetic screen to assay ATP concentrations in live human cells. We identified genes not known to be involved in energy metabolism. Most mitochondrial ribosomal proteins are essential in maintaining ATP levels under respiratory conditions, and impaired respiration predicts poor growth. We also identified genes for which coenzyme Q10 (CoQ10) supplementation rescued ATP deficits caused by knockdown. These included CoQ10 biosynthetic genes associated with human disease and a subset of genes not linked to CoQ10 biosynthesis, indicating that increasing CoQ10 can preserve ATP in specific genetic contexts. This screening paradigm reveals mechanisms of metabolic control and genetic defects responsive to energy-based therapies.

Prescribing diabetes nutrition therapy: a qualitative study of dietitians' experiences of carbohydrate restriction in Canada.

Background: Diabetes care has traditionally not included nutrition therapy using carbohydrate restriction, nor has carbohydrate restriction been taught to registered dietitians (RDs) to support patients living with diabetes choosing this dietary approach. We aimed to describe the experiences and views of RDs caring for patients using therapeutic carbohydrate-restricted diets (TCR), particularly metabolic conditions such as type 2 diabetes or prediabetes. Subjects/Methods: A qualitative study design using free-text responses from an online needs assessment survey was employed. RDs who practised in Canada were invited (n=6640) and 274 completed the survey, with 45 respondents who regularly prescribed TCR to their patients providing open-text responses (2987 words), which were analysed using inductive thematic analysis. Results: We identified four themes characterising Canadian RDs' experiences around prescribing TCR: interpersonal context, personal experience/knowledge, regulatory environment and patient-centredness. While these themes often interacted, each impacted TCR prescription uniquely, with patient-centred care at the core of reported experiences of prescribing. Conclusions: There exists a variety of experiences and perspectives related to prescribing of TCR among Canadian RDs caring for patients with diabetes, and all focus on the patient's needs, benefits and preferences. Prescribing TCR was often informed by the scientific literature yet also by RDs' experiential knowledge. Responses highlighted a desire for evidence-based educational materials and greater discussion within the diabetes nutrition community on this topic.

What Is a School Farm? Results of a Scoping Review.

As school farms become more prominent programs to teach food education, research is needed to support school farms' implementation and sustainability. This scoping review included 94 articles on school farms from three bibliometric databases covering broad international literature. Vocational agricultural training, animal husbandry, and crop production were common characteristics of school farms across 103 years of publications. Themes of sustainability, healthy eating, and food systems were more prominent in recent literature. Peer-reviewed studies (1985-2019) provided some empirical research showing school farms' impact on students. This review discusses school farms' structures and objectives as promising food education and production programming.

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes.

Introduction: Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes. Methods: In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival. Results: We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line. Conclusion: We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel.

Development and characterization of new patient-derived xenograft (PDX) models of osteosarcoma with distinct metastatic capacities.

Models to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology, especially for highly aggressive cancers with a propensity for metastatic spread. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, a large panel of models is needed to fully elucidate key aspects of disease biology and to recapitulate clinically-relevant phenotypes. We describe the development and characterization of osteosarcoma patient-derived xenografts (PDXs) and a panel of PDX-derived cell lines. Matched patient samples, PDXs, and PDX-derived cell lines were comprehensively evaluated using whole genome sequencing and RNA sequencing. PDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication (WGD) in a subset of cell lines. These cell line models were heterogeneous in their metastatic capacity and their tissue tropism as observed in both intravenous and orthotopic models. As proof-of-concept study, we used one of these models to test the preclinical effectiveness of a CDK inhibitor on the growth of metastatic tumors in an orthotopic amputation model. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden in this model.

A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires.

Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.

Tumor-Infiltrating B- and T-Cell Repertoire in Pancreatic Cancer Associated With Host and Tumor Features.

Background: Infiltrating B and T cells have been observed in several tumor tissues, including pancreatic ductal adenocarcinoma (PDAC). The majority known PDAC risk factors point to a chronic inflammatory process leading to different forms of immunological infiltration. Understanding pancreatic tumor infiltration may lead to improved knowledge of this devastating disease. Methods: We extracted the immunoglobulins (IGs) and T cell receptors (TCRs) from RNA-sequencing of 144 PDAC from TCGA and 180 pancreatic normal tissue from GTEx. We used Shannon entropy to find differences in IG/TCR diversity. We performed a clonotype analysis considering the IG clone definition (same V and J segments, same CDR3 length, and 90% nucleotide identity between CDR3s) to study differences among the tumor samples. Finally, we performed an association analysis to find host and tumor factors associated with the IG/TCR. Results: PDAC presented a richer and more diverse IG and TCR infiltration than normal pancreatic tissue. A higher IG infiltration was present in heavy smokers and females and it was associated with better overall survival. In addition, specific IG clonotypes classified samples with better prognosis explaining 24% of the prognosis phenotypic variance. On the other hand, a larger TCR infiltration was present in patients with previous history of diabetes and was associated with lower nonantigen load. Conclusions: Our findings support PDAC subtyping according to its immune repertoire landscape with a potential impact on the understanding of the inflammatory basis of PDAC risk factors as well as the design of treatment options and prognosis monitoring.

Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19.

The novel SARS-CoV-2 virus emerged in December 2019 and has few effective treatments. We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available data. We utilized three independent published studies to acquire or generate lists of differentially expressed genes between control and SARS-CoV-2-infected samples. Using a rank-based pattern matching strategy based on the Kolmogorov-Smirnov Statistic, the signatures were queried against drug profiles from Connectivity Map (CMap). We validated sixteen of our top predicted hits in live SARS-CoV-2 antiviral assays in either Calu-3 or 293T-ACE2 cells. Validation experiments in human cell lines showed that 11 of the 16 compounds tested to date (including clofazimine, haloperidol and others) had measurable antiviral activity against SARS-CoV-2. These initial results are encouraging as we continue to work towards a further analysis of these predicted drugs as potential therapeutics for the treatment of COVID-19.

Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19.

The novel SARS-CoV-2 virus emerged in December 2019 and has few effective treatments. We applied a computational drug repositioning pipeline to SARS-CoV-2 differential gene expression signatures derived from publicly available data. We utilized three independent published studies to acquire or generate lists of differentially expressed genes between control and SARS-CoV-2-infected samples. Using a rank-based pattern matching strategy based on the Kolmogorov-Smirnov Statistic, the signatures were queried against drug profiles from Connectivity Map (CMap). We validated 16 of our top predicted hits in live SARS-CoV-2 antiviral assays in either Calu-3 or 293T-ACE2 cells. Validation experiments in human cell lines showed that 11 of the 16 compounds tested to date (including clofazimine, haloperidol and others) had measurable antiviral activity against SARS-CoV-2. These initial results are encouraging as we continue to work towards a further analysis of these predicted drugs as potential therapeutics for the treatment of COVID-19.

Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis.

Multiple myeloma (MM) cell lines are routinely used to model the disease. However, a long-standing question is how well these cell lines truly represent tumor cells in patients. Here, we employ a recently described method of transcriptional correlation profiling to compare similarity of 66 MM cell lines to 779 newly diagnosed MM patient tumors. We found that individual MM lines differ significantly with respect to patient tumor representation, with median R ranging from 0.35 to 0.54. ANBL-6 was the "best" line, markedly exceeding all others (p < 2.2e-16). Notably, some widely used cell lines (RPMI-8226, U-266) scored poorly in our patient similarity ranking (48 and 52 of 66, respectively). Lines cultured with interleukin-6 showed significantly improved correlations with patient tumor (p = 9.5e-4). When common MM genomic features were matched between cell lines and patients, only t(4;14) and t(14;16) led to increased transcriptional correlation. To demonstrate the utility of our top-ranked line for preclinical studies, we showed that intravenously implanted ANBL-6 proliferates in hematopoietic organs in immunocompromised mice. Overall, our large-scale quantitative correlation analysis, utilizing emerging datasets, provides a resource informing the MM community of cell lines that may be most reliable for modeling patient disease while also elucidating biological differences between cell lines and tumors.

Loss of α-Synuclein Does Not Affect Mitochondrial Bioenergetics in Rodent Neurons.

Increased α-synuclein (αsyn) and mitochondrial dysfunction play central roles in the pathogenesis of Parkinson's disease (PD), and lowering αsyn is under intensive investigation as a therapeutic strategy for PD. Increased αsyn levels disrupt mitochondria and impair respiration, while reduced αsyn protects against mitochondrial toxins, suggesting that interactions between αsyn and mitochondria influences the pathologic and physiologic functions of αsyn. However, we do not know if αsyn affects normal mitochondrial function or if lowering αsyn levels impacts bioenergetic function, especially at the nerve terminal where αsyn is enriched. To determine if αsyn is required for normal mitochondrial function in neurons, we comprehensively evaluated how lowering αsyn affects mitochondrial function. We found that αsyn knockout (KO) does not affect the respiration of cultured hippocampal neurons or cortical and dopaminergic synaptosomes, and that neither loss of αsyn nor all three (α, ß and γ) syn isoforms decreased mitochondria-derived ATP levels at the synapse. Similarly, neither αsyn KO nor knockdown altered the capacity of synaptic mitochondria to meet the energy requirements of synaptic vesicle cycling or influenced the localization of mitochondria to dopamine (DA) synapses in vivo. Finally, αsyn KO did not affect overall energy metabolism in mice assessed with a Comprehensive Lab Animal Monitoring System. These studies suggest either that αsyn has little or no significant physiological effect on mitochondrial bioenergetic function, or that any such functions are fully compensated for when lost. These results implicate that αsyn levels can be reduced in neurons without impairing (or improving) mitochondrial bioenergetics or distribution.

Somatic and Germline TP53 Alterations in Second Malignant Neoplasms from Pediatric Cancer Survivors.

Purpose: Second malignant neoplasms (SMNs) are severe late complications that occur in pediatric cancer survivors exposed to radiotherapy and other genotoxic treatments. To characterize the mutational landscape of treatment-induced sarcomas and to identify candidate SMN-predisposing variants, we analyzed germline and SMN samples from pediatric cancer survivors.Experimental Design: We performed whole-exome sequencing (WES) and RNA sequencing on radiation-induced sarcomas arising from two pediatric cancer survivors. To assess the frequency of germline TP53 variants in SMNs, Sanger sequencing was performed to analyze germline TP53 in 37 pediatric cancer survivors from the Childhood Cancer Survivor Study (CCSS) without any history of a familial cancer predisposition syndrome but known to have developed SMNs.Results: WES revealed TP53 mutations involving p53's DNA-binding domain in both index cases, one of which was also present in the germline. The germline and somatic TP53-mutant variants were enriched in the transcriptomes for both sarcomas. Analysis of TP53-coding exons in germline specimens from the CCSS survivor cohort identified a G215C variant encoding an R72P amino acid substitution in 6 patients and a synonymous SNP A639G in 4 others, resulting in 10 of 37 evaluable patients (27%) harboring a germline TP53 variant.Conclusions: Currently, germline TP53 is not routinely assessed in patients with pediatric cancer. These data support the concept that identifying germline TP53 variants at the time a primary cancer is diagnosed may identify patients at high risk for SMN development, who could benefit from modified therapeutic strategies and/or intensive posttreatment monitoring. Clin Cancer Res; 23(7); 1852-61. ©2016 AACR.

Mutational Analysis of Ionizing Radiation Induced Neoplasms.

Ionizing radiation (IR) is a mutagen that promotes tumorigenesis in multiple exposure contexts. One severe consequence of IR is the development of second malignant neoplasms (SMNs), a radiotherapy-associated complication in survivors of cancers, particularly pediatric cancers. SMN genomes are poorly characterized, and the influence of genetic background on genotoxin-induced mutations has not been examined. Using our mouse models of SMNs, we performed whole exome sequencing of neoplasms induced by fractionated IR in wild-type and Nf1 mutant mice. Using non-negative matrix factorization, we identified mutational signatures that did not segregate by genetic background or histology. Copy-number analysis revealed recurrent chromosomal alterations and differences in copy number that were background dependent. Pathway analysis identified enrichment of non-synonymous variants in genes responsible for cell assembly and organization, cell morphology, and cell function and maintenance. In this model system, ionizing radiation and Nf1 heterozygosity each exerted distinct influences on the mutational landscape.