Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

Digital pathology (DP), or the digitization of pathology images, has transformed oncology research and cancer diagnostics. The application of artificial intelligence (AI) and other forms of machine learning (ML) to these images allows for better interpretation of morphology, improved quantitation of biomarkers, introduction of novel concepts to discovery and diagnostics (such as spatial distribution of cellular elements), and the promise of a new paradigm of cancer biomarkers. The application of AI to tissue analysis can take several conceptual approaches, within the domains of language modelling and image analysis, such as Deep Learning Convolutional Neural Networks, Multiple Instance Learning approaches, or the modelling of risk scores and their application to ML. The use of different approaches solves different problems within pathology workflows, including assistive applications for the detection and grading of tumours, quantification of biomarkers, and the delivery of established and new image-based biomarkers for treatment prediction and prognostic purposes. All these AI formats, applied to digital tissue images, are also beginning to transform our approach to clinical trials. In parallel, the novelty of DP/AI devices and the related computational science pipeline introduces new requirements for manufacturers to build into their design, development, regulatory and post-market processes, which may need to be taken into account when using AI applied to tissues in cancer discovery. Finally, DP/AI represents challenge to the way we accredit new diagnostic tools with clinical applicability, the understanding of which will allow cancer patients to have access to a new generation of complex biomarkers

Fluphenazine reduces proteotoxicity in C. elegans and mammalian models of alpha-1-antitrypsin deficiency

The classical form of α1-antitrypsin deficiency (ATD) is associated with hepatic fibrosis and hepatocellular carcinoma. It is caused by the proteotoxic effect of a mutant secretory protein that aberrantly accumulates in the endoplasmic reticulum of liver cells. Recently we developed a model of this deficiency in C. Elegans and adapted it for high-content drug screening using an automated, image-based array scanning. Screening of the Library of Pharmacologically Active Compounds identified fluphenazine (Flu) among several other compounds as a drug which reduced intracellular accumulation of mutant α1-antitrypsin Z (ATZ). Because it is representative of the phenothiazine drug class that appears to have autophagy enhancer properties in addition to mood stabilizing activity, and can be relatively easily re-purposed, we further investigated its effects on mutant ATZ. The results indicate that Flu reverses the phenotypic effects of ATZ accumulation in the C. elegans model of ATD at doses which increase the number of autophagosomes in vivo . Furthermore, in nanomolar concentrations, Flu enhances the rate of intracellular degradation of ATZ and reduces the cellular ATZ load in mammalian cell line models. In the PiZ mouse model Flu reduces the accumulation of ATZ in the liver and mediates a decrease in hepatic fibrosis. These results show that Flu can reduce the proteotoxicity of ATZ accumulation in vivo and, because it has been used safely in humans, this drug can be moved rapidly into trials for liver disease due to ATD. The results also provide further validation for drug discovery using C. elegans models that can be adapted to high-content drug screening platforms and used together with mammalian cell line and animal models. © 2014 Li et al

Inhibition of Chondrosarcoma Growth by mTOR Inhibitor in an In Vivo Syngeneic Rat Model

BACKGROUND: Chondrosarcomas are the second most frequent primary malignant type of bone tumor. No effective systemic treatment has been identified in advanced or adjuvant phases for chondrosarcoma. The aim of the present study was to determine the antitumor effects of doxorubicin and everolimus, an mTOR inhibitor on chondrosarcoma progression. METHODS AND FINDINGS: Doxorubin and/or everolimus were tested in vivo as single agent or in combination in the rat orthotopic Schwarm chondrosarcoma model, in macroscopic phase, as well as with microscopic residual disease. Response to everolimus and/or doxorubicin was evaluated using chondrosarcoma volume evolution (MRI). Histological response was evaluated with % of tumor necrosis, tumor proliferation index, metabolism quantification analysis between the treated and control groups. Statistical analyses were performed using chi square, Fishers exact test. Doxorubicin single agent has no effect of tumor growth as compared to no treatment; conversely, everolimus single agent significantly inhibited tumor progression in macroscopic tumors with no synergistic additive effect with doxorubicin. Everolimus inhibited chondrosarcoma proliferation as evaluated by Ki67 expression did not induce the apoptosis of tumor cells; everolimus reduced Glut1 and 4EBP1 expression. Importantly when given in rats with microscopic residual diseases, in a pseudo neoadjuvant setting, following R1 resection of the implanted tumor, everolimus significantly delayed or prevented tumor recurrence. CONCLUSIONS: MTOR inhibitor everolimus blocks cell proliferation, Glut1 expression and HIF1a expression, and prevents in vivo chondrosarcoma tumor progression in both macroscopic and in adjuvant phase post R1 resection. Taken together, our preclinical data indicate that mTOR inhibitor may be effective as a single agent in treating chondrosarcoma patients. A clinical trial evaluating mTOr inhibitor as neo-adjuvant and adjuvant therapy in chondrosarcoma patients is being constructed

Identifying differential exon splicing using linear models and correlation coefficients

Background: With the availability of the Affymetrix exon arrays a number of tools have been developed to enable the analysis. These however can be expensive or have several pre-installation requirements. This led us to develop an analysis workflow for analysing differential splicing using freely available software packages that are already being widely used for gene expression analysis. The workflow uses the packages in the standard installation of R and Bioconductor (BiocLite) to identify differential splicing. We use the splice index method with the LIMMA framework. The main drawback with this approach is that it relies on accurate estimates of gene expression from the probe-level data. Methods such as RMA and PLIER may misestimate when a large proportion of exons are spliced. We therefore present the novel concept of a gene correlation coefficient calculated using only the probeset expression pattern within a gene. We show that genes with lower correlation coefficients are likely to be differentially spliced.Results: The LIMMA approach was used to identify several tissue-specific transcripts and splicing events that are supported by previous experimental studies. Filtering the data is necessary, particularly removing exons and genes that are not expressed in all samples and cross-hybridising probesets, in order to reduce the false positive rate. The LIMMA approach ranked genes containing single or few differentially spliced exons much higher than genes containing several differentially spliced exons. On the other hand we found the gene correlation coefficient approach better for identifying genes with a large number of differentially spliced exons.Conclusion: We show that LIMMA can be used to identify differential exon splicing from Affymetrix exon array data. Though further work would be necessary to develop the use of correlation coefficients into a complete analysis approach, the preliminary results demonstrate their usefulness for identifying differentially spliced genes. The two approaches work complementary as they can potentially identify different subsets of genes (single/few spliced exons vs. large transcript structure differences)

Individualizing therapy – in search of approaches to maximize the benefit of drug treatment (II)

Adjusting drug therapy to the individual, a common approach in clinical practice, has evolved from 1) dose adjustments based on clinical effects to 2) dose adjustments made in response to drug levels and, more recently, to 3) dose adjustments based on deoxyribonucleic acid (DNA) sequencing of drug-metabolizing enzyme genes, suggesting a slow drug metabolism phenotype. This development dates back to the middle of the 20(th )century, when several different drugs were administered on the basis of individual plasma concentration measurements. Genetic control of drug metabolism was well established by the 1960s, and pharmakokinetic-based individualized therapy was in use by 1973

Durable Responses and Low Toxicity After Fast Off-Rate CD19 Chimeric Antigen Receptor-T Therapy in Adults With Relapsed or Refractory B-Cell Acute Lymphoblastic Leukemia

PURPOSE Prognosis for adult B-cell acute lymphoblastic leukemia (B-ALL) is poor, and there are currently no licensed CD19 chimeric antigen receptor (CAR) therapeutics. We developed a novel second-generation CD19-CAR (CAT19-41BB-Z) with a fast off rate, designed for more physiologic T-cell activation to reduce toxicity and improve engraftment. We describe the multicenter phase I ALLCAR19 (NCT02935257) study of autologous CAT19-41BB-Z CAR T cells (AUTO1) in relapsed or refractory (r/r) adult B-ALL. METHODS Patients age ≥ 16 years with r/r B-ALL were eligible. Primary outcomes were toxicity and manufacturing feasibility. Secondary outcomes were depth of response at 1 and 3 months, persistence of CAR-T, incidence and duration of hypogammaglobulinemia and B-cell aplasia, and event-free survival and overall survival at 1 and 2 years. RESULTS Twenty-five patients were leukapheresed, 24 products were manufactured, and 20 patients were infused with AUTO1. The median age was 41.5 years; 25% had prior blinatumomab, 50% prior inotuzumab ozogamicin, and 65% prior allogeneic stem-cell transplantation. At the time of preconditioning, 45% had ≥ 50% bone marrow blasts. No patients experienced ≥ grade 3 cytokine release syndrome; 3 of 20 (15%) experienced grade 3 neurotoxicity that resolved to ≤ grade 1 within 72 hours with steroids. Seventeen of 20 (85%) achieved minimal residual disease–negative complete response at month 1, and 3 of 17 underwent allogeneic stem-cell transplantation while in remission. The event-free survival at 6 and 12 months was 68.3% (42.4-84.4) and 48.3% (23.1%-69.7%), respectively. High-level expansion (Cmax 127,152 copies/µg genomic DNA) and durable CAR-T persistence were observed with B-cell aplasia ongoing in 15 of 20 patients at last follow-up. CONCLUSION AUTO1 demonstrates a tolerable safety profile, high remission rates, and excellent persistence in r/r adult B-ALL. Preliminary data support further development of AUTO1 as a stand-alone treatment for r/r adult B-ALL

Bim Nuclear Translocation and Inactivation by Viral Interferon Regulatory Factor

Viral replication efficiency is in large part governed by the ability of viruses to counteract pro-apoptotic signals induced by infection of the host cell. Human herpesvirus 8 (HHV-8) uses several strategies to block the host's innate antiviral defenses via interference with interferon and apoptotic signaling. Contributors include the four viral interferon regulatory factors (vIRFs 1–4), which function in dominant negative fashion to block cellular IRF activities in addition to targeting IRF signaling-induced proteins such as p53 and inhibiting other inducers of apoptosis such as TGFβ receptor-activated Smad transcription factors. Here we identify direct targeting by vIRF-1 of BH3-only pro-apoptotic Bcl-2 family member Bim, a key negative regulator of HHV-8 replication, to effect its inactivation via nuclear translocation. vIRF-1-mediated relocalization of Bim was identified in transfected cells, by both immunofluorescence assay and western analysis of fractionated cell extracts. Also, co-localization of vIRF-1 and Bim was detected in nuclei of lytically infected endothelial cells. In vitro co-precipitation assays using purified vIRF-1 and Bim revealed direct interaction between the proteins, and Bim-binding residues of vIRF-1 were mapped by deletion and point mutagenesis. Generation and experimental utilization of Bim-refractory vIRF-1 variants revealed the importance of vIRF-1:Bim interaction, specifically, in pro-replication and anti-apoptotic activity of vIRF-1. Furthermore, blocking of the interaction with cell-permeable peptide corresponding to the Bim-binding region of vIRF-1 confirmed the relevance of vIRF-1:Bim association to vIRF-1 pro-replication activity. To our knowledge, this is the first report of an IRF protein that interacts with a Bcl-2 family member and of nuclear sequestration of Bim or any other member of the family as a means of inactivation. The data presented reveal a novel mechanism utilized by a virus to control replication-induced apoptosis and suggest that inhibitory targeting of vIRF-1:Bim interaction may provide an effective antiviral strategy

Insulin utilizes the PI 3-kinase pathway to inhibit SP-A gene expression in lung epithelial cells

BACKGROUND: It has been proposed that high insulin levels may cause delayed lung development in the fetuses of diabetic mothers. A key event in lung development is the production of adequate amounts of pulmonary surfactant. Insulin inhibits the expression of surfactant protein A (SP-A), the major surfactant-associated protein, in lung epithelial cells. In the present study, we investigated the signal transduction pathways involved in insulin inhibition of SP-A gene expression. METHODS: H441 cells, a human lung adenocarcinoma cell line, or human fetal lung explants were incubated with or without insulin. Transcription run-on assays were used to determine SP-A gene transcription rates. Northern blot analysis was used to examine the effect of various signal transduction inhibitors on SP-A gene expression. Immunoblot analysis was used to evaluate the levels and phosphorylation states of signal transduction protein kinases. RESULTS: Insulin decreased SP-A gene transcription in human lung epithelial cells within 1 hour. Insulin did not affect p44/42 mitogen-activated protein kinase (MAPK) phosphorylation and the insulin inhibition of SP-A mRNA levels was not affected by PD98059, an inhibitor of the p44/42 MAPK pathway. In contrast, insulin increased p70 S6 kinase Thr389 phosphorylation within 15 minutes. Wortmannin or LY294002, both inhibitors of phosphatidylinositol 3-kinase (PI 3-kinase), or rapamycin, an inhibitor of the activation of p70 S6 kinase, a downstream effector in the PI 3-kinase pathway, abolished or attenuated the insulin-induced inhibition of SP-A mRNA levels. CONCLUSION: Insulin inhibition of SP-A gene expression in lung epithelial cells probably occurs via the rapamycin-sensitive PI 3-kinase signaling pathway