ThicknessTool: automated ImageJ retinal layer thickness and profile in digital images

To develop an automated retina layer thickness measurement tool for the ImageJ platform, to quantitate nuclear layers following the retina contour. We developed the ThicknessTool (TT), an automated thickness measurement plugin for the ImageJ platform. To calibrate TT, we created a calibration dataset of mock binary skeletonized mask images with increasing thickness masks and different rotations. Following, we created a training dataset and performed an agreement analysis of thickness measurements between TT and two masked manual observers. Finally, we tested the performance of TT measurements in a validation dataset of retinal detachment images. In the calibration dataset, there were no differences in layer thickness between measured and known thickness masks, with an overall coefficient of variation of 0.00%. Training dataset measurements of immunofluorescence retina nuclear layers disclosed no significant differences between TT and any observer's average outer nuclear layer (ONL) (p = 0.998), inner nuclear layer (INL) (p = 0.807), and ONL/INL ratio (p = 0.944) measurements. Agreement analysis showed that bias between TT vs. observers' mean was lower than between any observers' mean against each other in the ONL (0.77 ± 0.34 µm vs 3.25 ± 0.33 µm) and INL (1.59 ± 0.28 µm vs 2.82 ± 0.36 µm). Validation dataset showed that TT can detect significant and true ONL thinning (p = 0.006), more sensitive than manual measurement capabilities (p = 0.069). ThicknessTool can measure retina nuclear layers thickness in a fast, accurate, and precise manner with multi-platform capabilities. In addition, the TT can be customized to user preferences and is freely available to download

KCNQ potassium channels modulate Wnt activity in gastro-oesophageal adenocarcinomas

Voltage-sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large-scale analysis of 897 patients with gastro-oesophageal adenocarcinomas (GOAs) coupled with in vitro models, we find KCNQ family genes are mutated in ∼30% of patients, and play therapeutically targetable roles in GOA cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation through resultant effects on cadherin junctions. This also highlights novel roles of KCNQ3 in non-excitable tissues. We also discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors and that inhibition of KCNQ activity reduces proliferation of GOA cancer cells. These findings reveal a novel and exploitable role of potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GOAs may exist through KCNQ inhibitors

Issues with the Specificity of Immunological Reagents for NLRP3: Implications for Age-related Macular Degeneration

Contradictory data have been presented regarding the implication of the NACHT, LRR and PYD domains-containing protein 3 (NLRP3) inflammasome in age-related macular degeneration (AMD), the leading cause of vision loss in the Western world. Recognizing that antibody specificity may explain this discrepancy and in line with recent National Institutes of Health (NIH) guidelines requiring authentication of key biological resources, the specificity of anti-NLRP3 antibodies was assessed to elucidate whether non-immune RPE cells express NLRP3. Using validated resources, NLRP3 was not detected in human primary or human established RPE cell lines under multiple inflammasome-priming conditions, including purported NLRP3 stimuli in RPE such as DICER1 deletion and Alu RNA transfection. Furthermore, NLRP3 was below detection limits in ex vivo macular RPE from AMD patients, as well as in human induced pluripotent stem cell (hiPSC)-derived RPE from patients with overactive NLRP3 syndrome (Chronic infantile neurologic cutaneous and articulate, CINCA syndrome). Evidence presented in this study provides new data regarding the interpretation of published results reporting NLRP3 expression and upregulation in RPE and addresses the role that this inflammasome plays in AMD pathogenesis

Computational pathology aids derivation of microRNA biomarker signals from Cytosponge samples.

BACKGROUND: Non-endoscopic cell collection devices combined with biomarkers can detect Barrett's intestinal metaplasia and early oesophageal cancer. However, assays performed on multi-cellular samples lose information about the cell source of the biomarker signal. This cross-sectional study examines whether a bespoke artificial intelligence-based computational pathology tool could ascertain the cellular origin of microRNA biomarkers, to inform interpretation of the disease pathology, and confirm biomarker validity. METHODS: The microRNA expression profiles of 110 targets were assessed with a custom multiplexed panel in a cohort of 117 individuals with reflux that took a Cytosponge test. A computational pathology tool quantified the amount of columnar epithelium present in pathology slides, and results were correlated with microRNA signals. An independent cohort of 139 Cytosponges, each from an individual patient, was used to validate the findings via qPCR. FINDINGS: Seventeen microRNAs are upregulated in BE compared to healthy squamous epithelia, of which 13 remain upregulated in dysplasia. A pathway enrichment analysis confirmed association to neoplastic and cell cycle regulation processes. Ten microRNAs positively correlated with columnar epithelium content, with miRNA-192-5p and -194-5p accurately detecting the presence of gastric cells (AUC 0.97 and 0.95). In contrast, miR-196a-5p is confirmed as a specific BE marker. INTERPRETATION: Computational pathology tools aid accurate cellular attribution of molecular signals. This innovative design with multiplex microRNA coupled with artificial intelligence has led to discovery of a quality control metric suitable for large scale application of the Cytosponge. Similar approaches could aid optimal interpretation of biomarkers for clinical use. FUNDING: Funded by the NIHR Cambridge Biomedical Research Centre, the Medical Research Council, the Rosetrees and Stoneygate Trusts, and CRUK core grants

Verteporfin-induced formation of protein cross-linked oligomers and high molecular weight complexes is mediated by light and leads to cell toxicity

Verteporfin (VP) was first used in Photodynamic therapy, where a non-thermal laser light (689 nm) in the presence of oxygen activates the drug to produce highly reactive oxygen radicals, resulting in local cell and tissue damage. However, it has also been shown that Verteporfin can have non-photoactivated effects such as interference with the YAP-TEAD complex of the HIPPO pathway, resulting in growth inhibition of several neoplasias. More recently, it was proposed that, another non-light mediated effect of VP is the formation of cross-linked oligomers and high molecular weight protein complexes (HMWC) that are hypothesized to interfere with autophagy and cell growth. Here, in a series of experiments, using human uveal melanoma cells (MEL 270), human embryonic kidney cells (HEK) and breast cancer cells (MCF7) we showed that Verteporfin-induced HMWC require the presence of light. Furthermore, we showed that the mechanism of this cross-linking, which involves both singlet oxygen and radical generation, can occur very efficiently even after lysis of the cells, if the lysate is not protected from ambient light. This work offers a better understanding regarding VP’s mechanisms of action and suggests caution when one studies the non-light mediated actions of this drug

KCNQ potassium channels modulate Wnt activity in gastro-oesophageal adenocarcinomas.

Voltage-sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large-scale analysis of 897 patients with gastro-oesophageal adenocarcinomas (GOAs) coupled with in vitro models, we find KCNQ family genes are mutated in ∼30% of patients, and play therapeutically targetable roles in GOA cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation through resultant effects on cadherin junctions. This also highlights novel roles of KCNQ3 in non-excitable tissues. We also discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors and that inhibition of KCNQ activity reduces proliferation of GOA cancer cells. These findings reveal a novel and exploitable role of potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GOAs may exist through KCNQ inhibitors

Genomic copy number predicts esophageal cancer years before transformation

Summary Recent studies show that aneuploidies and driver gene mutations precede cancer diagnosis by many years1–4. We assess whether these genomic signals can be used for early detection and pre-emptive cancer treatment using the neoplastic precursor lesion Barrett’s esophagus, as an exemplar5. Shallow whole genome sequencing of 777 biopsies, sampled from 88 patients in Barrett’s surveillance over a period of up to 15 years shows that genomic signals can distinguish progressive from stable disease even ten years prior to histopathological transformation. These findings are validated on two independent cohorts of 76 and 248 patients. These methods are low cost and applicable to standard clinical biopsy samples. Compared with current management guidelines based on histopathology and clinical presentation, genomic classification enables earlier treatment for high risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer.The laboratory of R.C.F. is funded by a Core Programme Grant from the Medical Research Council (RG84369). This work was also funded by a United European Gastroenterology Research Prize (RG76026)

Genomic copy number predicts esophageal cancer years before transformation

Summary Recent studies show that aneuploidies and driver gene mutations precede cancer diagnosis by many years1–4. We assess whether these genomic signals can be used for early detection and pre-emptive cancer treatment using the neoplastic precursor lesion Barrett’s esophagus, as an exemplar5. Shallow whole genome sequencing of 777 biopsies, sampled from 88 patients in Barrett’s surveillance over a period of up to 15 years shows that genomic signals can distinguish progressive from stable disease even ten years prior to histopathological transformation. These findings are validated on two independent cohorts of 76 and 248 patients. These methods are low cost and applicable to standard clinical biopsy samples. Compared with current management guidelines based on histopathology and clinical presentation, genomic classification enables earlier treatment for high risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer.The laboratory of R.C.F. is funded by a Core Programme Grant from the Medical Research Council (RG84369). This work was also funded by a United European Gastroenterology Research Prize (RG76026)