Application of Artificial Intelligence/Machine Vision & Learning for the Development of a Live Single-cell Phenotypic Biomarker Test to Predict Prostate Cancer Tumor Aggressiveness

To assess the usefulness and applications of machine vision (MV) and machine learning (ML) techniques that have been used to develop a single cell-based phenotypic (live and fixed biomarkers) platform that correlates with tumor biological aggressiveness and risk stratification, 100 fresh prostate samples were acquired, and areas of prostate cancer were determined by post-surgery pathology reports logged by an independent pathologist. The prostate samples were dissociated into single-cell suspensions in the presence of an extracellular matrix formulation. These samples were analyzed via live-cell microscopy. Dynamic and fixed phenotypic biomarkers per cell were quantified using objective MV software and ML algorithms. The predictive nature of the ML algorithms was developed in two stages. First, random forest (RF) algorithms were developed using 70% of the samples. The developed algorithms were then tested for their predictive performance using the blinded test dataset that contained 30% of the samples in the second stage. Based on the ROC (receiver operating characteristic) curve analysis, thresholds were set to maximize both sensitivity and specificity. We determined the sensitivity and specificity of the assay by comparing the algorithm-generated predictions with adverse pathologic features in the radical prostatectomy (RP) specimens. Using MV and ML algorithms, the biomarkers predictive of adverse pathology at RP were ranked and a prostate cancer patient risk stratification test was developed that distinguishes patients based on surgical adverse pathology features. The ability to identify and track large numbers of individual cells over the length of the microscopy experimental monitoring cycles, in an automated way, created a large biomarker dataset of primary biomarkers. This biomarker dataset was then interrogated with ML algorithms used to correlate with post-surgical adverse pathology findings. Algorithms were generated that predicted adverse pathology with >0.85 sensitivity and specificity and an AUC (area under the curve) of >0.85. Phenotypic biomarkers provide cellular and molecular details that are informative for predicting post-surgical adverse pathologies when considering tumor biopsy samples. Artificial intelligence ML-based approaches for cancer risk stratification are emerging as important and powerful tools to compliment current measures of risk stratification. These techniques have capabilities to address tumor heterogeneity and the molecular complexity of prostate cancer. Specifically, the phenotypic test is a novel example of leveraging biomarkers and advances in MV and ML for developing a powerful prognostic and risk-stratification tool for prostate cancer patients.     

Quirks of dye nomenclature. 1. Evans blue

The history, origin, identity, chemistry and use of Evans blue dye are described along with the first application to staining by Herbert McLean Evans in 1914. In the 1930s, the dye was marketed under the name, Evans blue dye, which was profoundly more acceptable than the ponderous chemical name.     

Acceptor specificity of the human leukocyte alpha3 fucosyltransferase: role of FucT-VII in the generation of selectin ligands

The alpha3 fucosyltransferase, FucT-VII, is one of the key glycosyltransferases involved in the biosynthesis of the sialyl Lewis X (sLex) antigen on human leukocytes. The sialyl Lewis X antigen (NeuAcalpha(2-3)Galbeta(1-4)[Fucalpha(1-3)]GlcNAc-R) is an essential component of the recruitment of leukocytes to sites of inflammation, mediating the primary interaction between circulating leukocytes and activated endothelium. In order to characterize the enzymatic properties of the leukocyte alpha3 fucosyltransferase FucT-VII, the enzyme has been expressed in Trichoplusia ni insect cells. The enzyme is capable of synthesizing both sLexand sialyl-dimeric-Lexstructures in vitro , from 3'-sialyl-lacNAc and VIM-2 structures, respectively, with only low levels of fucose transfer observed to neutral or 3'-sulfated acceptors. Studies using fucosylated NeuAcalpha(2-3)-(Galbeta(1- 4)GlcNAc)3-Me acceptors demonstrate that FucT-VII is able to synthesize both di-fucosylated and tri-fucosylated structures from mono- fucosylated precursors, but preferentially fucosylates the distal GlcNAc within a polylactosamine chain. Furthermore, the rate of fucosylation of the internal GlcNAc residues is reduced once fucose has been added to the distal GlcNAc. These results indicate that FucT-VII is capable of generating complex selectin ligands, in vitro , however the order of fucose addition to the lactosamine chain affects the rate of selectin ligand synthesis.      

Gene selection in arthritis classification with large-scale microarray expression profiles

The use of large-scale microarray expression profiling to identify predictors of disease class has become of major interest. Beyond their impact in the clinical setting (i.e. improving diagnosis and treatment), these markers are also likely to provide clues on the molecular mechanisms underlining the diseases. In this paper we describe a new method for the identification of multiple gene predictors of disease class. The method is applied to the classification of two forms of arthritis that have a similar clinical endpoint but different underlying molecular mechanisms: rheumatoid arthritis (RA) and osteoarthritis (OA). We aim at both the classification of samples and the location of genes characterizing the different classes. We achieve both goals simultaneously by combining a binary probit model for classification with Bayesian variable selection methods to identify important genes.We find very small sets of genes that lead to good classification results. Some of the selected genes are clearly correlated with known aspects of the biology of arthritis and, in some cases, reflect already known differences between RA and OA.     

Grb7 SH2 domain structure and interactions with a cyclic peptide inhibitor of cancer cell migration and proliferation

Background

Human growth factor receptor bound protein 7 (Grb7) is an adapter protein that mediates the coupling of tyrosine kinases with their downstream signaling pathways. Grb7 is frequently overexpressed in invasive and metastatic human cancers and is implicated in cancer progression via its interaction with the ErbB2 receptor and focal adhesion kinase (FAK) that play critical roles in cell proliferation and migration. It is thus a prime target for the development of novel anti-cancer therapies. Recently, an inhibitory peptide (G7-18NATE) has been developed which binds specifically to the Grb7 SH2 domain and is able to attenuate cancer cell proliferation and migration in various cancer cell lines.

Results

As a first step towards understanding how Grb7 may be inhibited by G7-18NATE, we solved the crystal structure of the Grb7 SH2 domain to 2.1 Å resolution. We describe the details of the peptide binding site underlying target specificity, as well as the dimer interface of Grb 7 SH2. Dimer formation of Grb7 was determined to be in the μM range using analytical ultracentrifugation for both full-length Grb7 and the SH2 domain alone, suggesting the SH2 domain forms the basis of a physiological dimer. ITC measurements of the interaction of the G7-18NATE peptide with the Grb7 SH2 domain revealed that it binds with a binding affinity of K_d = ~35.7 μM and NMR spectroscopy titration experiments revealed that peptide binding causes perturbations to both the ligand binding surface of the Grb7 SH2 domain as well as to the dimer interface, suggesting that dimerisation of Grb7 is impacted on by peptide binding.

Conclusion

Together the data allow us to propose a model of the Grb7 SH2 domain/G7-18NATE interaction and to rationalize the basis for the observed binding specificity and affinity. We propose that the current study will assist with the development of second generation Grb7 SH2 domain inhibitors, potentially leading to novel inhibitors of cancer cell migration and invasion.     

Lidocaine block of cardiac sodium channels

Lidocaine block of cardiac sodium channels was studied in voltage-clamped rabbit purkinje fibers at drug concentrations ranging from 1 mM down to effective antiarrhythmic doses (5-20 μM). Dose-response curves indicated that lidocaine blocks the channel by binding one-to-one, with a voltage-dependent K(d). The half-blocking concentration varied from more than 300 μM, at a negative holding potential where inactivation was completely removed, to approximately 10 μM, at a depolarized holding potential where inactivation was nearly complete. Lidocaine block showed prominent use dependence with trains of depolarizing pulses from a negative holding potential. During the interval between pulses, repriming of I (Na) displayed two exponential components, a normally recovering component (τless than 0.2 s), and a lidocaine-induced, slowly recovering fraction (τ approximately 1-2 s at pH 7.0). Raising the lidocaine concentration magnified the slowly recovering fraction without changing its time course; after a long depolarization, this fraction was one-half at approximately 10 μM lidocaine, just as expected if it corresponded to drug-bound, inactivated channels. At less than or equal to 20 μM lidocaine, the slowly recovering fraction grew exponentially to a steady level as the preceding depolarization was prolonged; the time course was the same for strong or weak depolarizations, that is, with or without significant activation of I(Na). This argues that use dependence at therapeutic levels reflects block of inactivated channels, rather than block of open channels. Overall, these results provide direct evidence for the “modulated-receptor hypothesis” of Hille (1977) and Hondeghem and Katzung (1977). Unlike tetrodotoxin, lidocaine shows similar interactions with Na channels of heart, nerve, and skeletal muscle.     

ERRATUM: New Body Mass Estimates for Omomys carteri,a Middle Eocene Primate From North America. Am J Phys Anthropol 109:41–52.

Payseur BA, Covert HA, Vinyard CJ, Dagosto M. 1999. New Body Mass Estimates for Omomys carteri, a Middle Eocene Primate From North America. Am J Phys Anthropol 109:41–52. This article included an incomplete Table 2. The final two columns, showing “Intercept” and “SEE” data were omitted. The complete Table 2, with these two columns included, is provided below.     

High definition bronchoscopy: a randomized exploratory study of diagnostic value compared to standard white light bronchoscopy and autofluorescence bronchoscopy

Background

Videobronchoscopy is an essential diagnostic procedure for evaluation of the central airways and pivotal for the diagnosis and staging of lung cancer. Technological improvements have resulted in high definition (HD) images with advanced real time image enhancement techniques (i-scan).

Objectives

In this study we aimed to explore the sensitivity of HD+ i-scan bronchoscopy for detection of epithelial changes like vascular abnormalities and suspicious preinvasive lesions, and tumors.

Methods

In patients scheduled for a therapeutic or diagnostic procedure under general anesthesia videos of the bronchial tree were made using 5 videobronchoscopy modes in random order: normal white light videobronchoscopy (WLB), HD-bronchoscopy (HD), HD bronchoscopy with surface enhancement technique (i-scan1), HD with surface- and tone enhancement technique (i-scan2) and dual mode autofluorescence videobronchoscopy (AFB). The videos were scored in random order by two independent and blinded expert bronchoscopists.

Results

In 29 patients all videos were available for analysis. Vascular abnormalities were scored most frequently in HD + i-scan2 bronchoscopy (1.33 ± 0.29 abnormal or suspicious sites per patient) as compared to 0.12 ± 0.05 site for AFB (P = 0.003). Sites suspicious for preinvasive lesions were most frequently reported using AFB (0.74 ± 0.12 sites per patient) as compared to 0.17 ± 0.06 for both WLB and HD bronchoscopy (P = 0.003). Tumors were detected equally by all modalities. The preferred modality was HD bronchoscopy with i-scan (tone- plus surface and surface enhancement in respectively 38% and 35% of cases P = 0.006).

Conclusions

This study shows that high definition bronchoscopy with image enhancement technique may result in better detection of subtle vascular abnormalities in the airways. Since these abnormalities may be related to preneoplastic lesions and tumors this is of clinical relevance. Further investigations using this technique relating imaging to histology are warranted.