Feature fusion of Raman chemical imaging and digital histopathology using machine learning for prostate cancer detection.

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient's quality of life and prognosis. Towards addressing this issue, we present a learning model for the automatic identification of prostate cancer. While many prostate cancer studies have adopted Raman spectroscopy approaches, none have utilised the combination of Raman Chemical Imaging (RCI) and other imaging modalities. This study uses multimodal images formed from stained Digital Histopathology (DP) and unstained RCI. The approach was developed and tested on a set of 178 clinical samples from 32 patients, containing a range of non-cancerous, Gleason grade 3 (G3) and grade 4 (G4) tissue microarray samples. For each histological sample, there is a pathologist labelled DP-RCI image pair. The hypothesis tested was whether multimodal image models can outperform single modality baseline models in terms of diagnostic accuracy. Binary non-cancer/cancer models and the more challenging G3/G4 differentiation were investigated. Regarding G3/G4 classification, the multimodal approach achieved a sensitivity of 73.8% and specificity of 88.1% while the baseline DP model showed a sensitivity and specificity of 54.1% and 84.7% respectively. The multimodal approach demonstrated a statistically significant 12.7% AUC advantage over the baseline with a value of 85.8% compared to 73.1%, also outperforming models based solely on RCI and mean and median Raman spectra. Feature fusion of DP and RCI does not improve the more trivial task of tumour identification but does deliver an observed advantage in G3/G4 discrimination. Building on these promising findings, future work could include the acquisition of larger datasets for enhanced model generalization.

Improving the uniformity of holographic recording using multilayer photopolymer. Part I. Theoretical analysis.

An experimental and theoretical investigation of the preparation and exposure of multilayer photosensitive materials is presented. It is shown how the recorded change in the refractive index in each layer depends on the dye (photosensitizer) concentrations in each layer. It is also shown how the photosensitive material properties in each layer can be controlled to optimize some recording characteristics for particular applications. To do so, a set of equations, predicting the amplitude of higher harmonics refractive index amplitudes induced in the material layers with depth during exposure, is derived. This results in a technique for varying the dye concentration in each layer of a multilayer, so as to optimize volume diffraction grating performance. In part I of this paper, the 3D nonlocal photopolymerization-driven diffusion (NPDD) model is applied to calculate the resulting combined multilayer absorption and polymerization processes. The NPDD describes the time-varying behaviors taking place during exposure in such photopolymer materials. Simulations are performed for an acrylamide/polyvinyl alcohol-based photopolymer containing erythrosine-B dye. It is predicted that, in general, non-uniform gratings are formed, with the resulting refractive index being distorted both from the ideal sinusoidal cross-sectional spatial distribution and also with depth. This agrees with previous results indicating that increasing the thickness of a single photopolymer layer does not in practice lead to ever-increasing angular selectivity. In part II of this paper, it is confirmed experimentally that a suitably modified multilayer can be used to increase grating angular selectivity, i.e., reduce the width of the off-Bragg replay curve.

Improving the uniformity of holographic recording using multi-layer photopolymer: Part II. Experimental results.

In the first part of this study, a 3D nonlocal photopolymerization driven diffusion model was developed and applied to simulate the absorption and polymerization taking place during holographic exposures of a multi-layer. The Beer-Lambert law was used to choose appropriate dye concentrations for each layer, with the objective of improving the resulting volume grating uniformity and thus diffraction characteristics. The predictions made, using previously estimated physical parameter values, indicated that improvements in the uniformity of the recorded modulation were possible. In this paper the results of experiments carried out to explore the validity of these predictions are presented. Improvements in material response are demonstrated experimentally, with improved grating diffraction (narrower angular selectivity) being observed for appropriately sensitized multi-layers.

Micro- or nanorod and nanosphere structures derived from a series of phenyl-porphyrins.

We examine here a series of meso-phenyl porphyrin micro- and nanostructures. Optical absorption and emission spectroscopy imaging and atomic force microscopy are used to investigate the effect of peripheral groups in nano- and microstructures of 5,10,15,20-tetraphenylporphyrin (H2TPP) compared to three other phenylporphyrins, i.e. 5,10,15-triphenylporphyrin (H2-Tri-PP), 5,10-diphenylporphyrin (H25,10-BPP) and 5,15-diphenylporphyrin (H25,15-BPP) molecules. We show that nanospheres and nanorods are formed, the occurrence and properties of which are influenced by the number and position of the phenyl substituents.

Prognostic value of the 6-gene OncoMasTR test in hormone receptor-positive HER2-negative early-stage breast cancer: Comparative analysis with standard clinicopathological factors.

AIM: The aim of the study was to assess the prognostic performance of a 6-gene molecular score (OncoMasTR Molecular Score [OMm]) and a composite risk score (OncoMasTR Risk Score [OM]) and to conduct a within-patient comparison against four routinely used molecular and clinicopathological risk assessment tools: Oncotype DX Recurrence Score, Ki67, Nottingham Prognostic Index and Clinical Risk Category, based on the modified Adjuvant! Online definition and three risk factors: patient age, tumour size and grade. METHODS: Biospecimens and clinicopathological information for 404 Irish women also previously enrolled in the Trial Assigning Individualized Options for Treatment [Rx] were provided by 11 participating hospitals, as the primary objective of an independent translational study. Gene expression measured via RT-qPCR was used to calculate OMm and OM. The prognostic value for distant recurrence-free survival (DRFS) and invasive disease-free survival (IDFS) was assessed using Cox proportional hazards models and Kaplan-Meier analysis. All statistical tests were two-sided ones. RESULTS: OMm and OM (both with likelihood ratio statistic [LRS] P < 0.001; C indexes = 0.84 and 0.85, respectively) were more prognostic for DRFS and provided significant additional prognostic information to all other assessment tools/factors assessed (all LRS P ≤ 0.002). In addition, the OM correctly classified more patients with distant recurrences (DRs) into the high-risk category than other risk classification tools. Similar results were observed for IDFS. DISCUSSION: Both OncoMasTR scores were significantly prognostic for DRFS and IDFS and provided additional prognostic information to the molecular and clinicopathological risk factors/tools assessed. OM was also the most accurate risk classification tool for identifying DR. A concise 6-gene signature with superior risk stratification was shown to increase prognosis reliability, which may help clinicians optimise treatment decisions.

High Cysteinyl Leukotriene Receptor 1 Expression Correlates with Poor Survival of Uveal Melanoma Patients and Cognate Antagonist Drugs Modulate the Growth, Cancer Secretome, and Metabolism of Uveal Melanoma Cells.

Metastatic uveal melanoma (UM) is a rare, but often lethal, form of ocular cancer arising from melanocytes within the uveal tract. UM has a high propensity to spread hematogenously to the liver, with up to 50% of patients developing liver metastases. Unfortunately, once liver metastasis occurs, patient prognosis is extremely poor with as few as 8% of patients surviving beyond two years. There are no standard-of-care therapies available for the treatment of metastatic UM, hence it is a clinical area of urgent unmet need. Here, the clinical relevance and therapeutic potential of cysteinyl leukotriene receptors (CysLT1 and CysLT2) in UM was evaluated. High expression of CYSLTR1 or CYSLTR2 transcripts is significantly associated with poor disease-free survival and poor overall survival in UM patients. Digital pathology analysis identified that high expression of CysLT1 in primary UM is associated with reduced disease-specific survival (p = 0.012; HR 2.76; 95% CI 1.21-6.3) and overall survival (p = 0.011; HR 1.46; 95% CI 0.67-3.17). High CysLT1 expression shows a statistically significant (p = 0.041) correlation with ciliary body involvement, a poor prognostic indicator in UM. Small molecule drugs targeting CysLT1 were vastly superior at exerting anti-cancer phenotypes in UM cell lines and zebrafish xenografts than drugs targeting CysLT2. Quininib, a selective CysLT1 antagonist, significantly inhibits survival (p < 0.0001), long-term proliferation (p < 0.0001), and oxidative phosphorylation (p < 0.001), but not glycolysis, in primary and metastatic UM cell lines. Quininib exerts opposing effects on the secretion of inflammatory markers in primary versus metastatic UM cell lines. Quininib significantly downregulated IL-2 and IL-6 in Mel285 cells (p < 0.05) but significantly upregulated IL-10, IL-1ß, IL-2 (p < 0.0001), IL-13, IL-8 (p < 0.001), IL-12p70 and IL-6 (p < 0.05) in OMM2.5 cells. Finally, quininib significantly inhibits tumour growth in orthotopic zebrafish xenograft models of UM. These preclinical data suggest that antagonism of CysLT1, but not CysLT2, may be of therapeutic interest in the treatment of UM.

Single-Molecule Nonresonant Wide-Field Surface-Enhanced Raman Scattering from Ferroelectrically Defined Au Nanoparticle Microarrays.

Single-molecule detection by surface-enhanced Raman scattering (SERS) is a powerful spectroscopic technique that is of interest for the sensor development field. An important aspect of optimizing the materials used in SERS-based sensors is the ability to have a high density of "hot spots" that enhance the SERS sensitivity to the single-molecule level. Photodeposition of gold (Au) nanoparticles through electric-field-directed self-assembly on a periodically proton-exchanged lithium niobate (PPELN) substrate provides conditions to form well-ordered microscale features consisting of closely packed Au nanoparticles. The resulting Au nanoparticle microstructure arrays (microarrays) are plasmon-active and support nonresonant single-molecule SERS at ultralow concentrations (<10-9-10-13 M) with excitation power densities <1 × 10-3 W cm-2 using wide-field imaging. The microarrays offer excellent SERS reproducibility, with an intensity variation of <7.5% across the substrate. As most biomarkers and molecules do not support resonance enhancement, this work demonstrates that PPELN is a suitable template for high-sensitivity, nonresonant sensing applications.

Photoinduced Enhanced Raman from Lithium Niobate on Insulator Template.

Photoinduced enhanced Raman spectroscopy from a lithium niobate on insulator (LNOI)-silver nanoparticle template is demonstrated both by irradiating the template with 254 nm ultraviolet (UV) light before adding an analyte and before placing the substrate in the Raman system (substrate irradiation) and by irradiating the sample in the Raman system after adding the molecule (sample irradiation). The photoinduced enhancement enables up to an ∼sevenfold increase of the surface-enhanced Raman scattering signal strength of an analyte following substrate irradiation, whereas an ∼threefold enhancement above the surface-enhanced signal is obtained for sample irradiation. The photoinduced enhancement relaxes over the course of ∼10 h for a substrate irradiation duration of 150 min before returning to initial signal levels. The increase in Raman scattering intensity following UV irradiation is attributed to photoinduced charge transfer from the LNOI template to the analyte. New Raman bands are observed following UV irradiation, the appearance of which is suggestive of a photocatalytic reaction and highlight the potential of LNOI as a photoactive surface-enhanced Raman spectroscopy substrate.