Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage

BACKGROUND: The sensitivity of Optical Coherence Tomography (OCT) images to identify retinal tissue morphology characterized by early neural loss from normal healthy eyes is tested by calculating structural information and fractal dimension. OCT data from 74 healthy eyes and 43 eyes with type 1 diabetes mellitus with mild diabetic retinopathy (MDR) on biomicroscopy was analyzed using a custom-built algorithm (OCTRIMA) to measure locally the intraretinal layer thickness. A power spectrum method was used to calculate the fractal dimension in intraretinal regions of interest identified in the images. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between pathological and normal groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between eyes of pathological patients and normal healthy eyes. RESULTS: Fractal dimension was higher for all the layers (except the GCL + IPL and INL) in MDR eyes compared to normal healthy eyes. When comparing MDR with normal healthy eyes, the highest AUROC values estimated for the fractal dimension were observed for GCL + IPL and INL. The maximum discrimination value for fractal dimension of 0.96 (standard error =0.025) for the GCL + IPL complex was obtained at a FD <= 1.66 (cut off point, asymptotic 95% Confidence Interval: lower-upper bound = 0.905-1.002). Moreover, the highest AUROC values estimated for the thickness measurements were observed for the OPL, GCL + IPL and OS. Particularly, when comparing MDR eyes with control healthy eyes, we found that the fractal dimension of the GCL + IPL complex was significantly better at diagnosing early DR, compared to the standard thickness measurement. CONCLUSIONS: Our results suggest that the GCL + IPL complex, OPL and OS are more susceptible to initial damage when comparing MDR with control healthy eyes. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early neurodegeneration in the retina

Melanoma Models for the Next Generation of Therapies

There is a lack of appropriate melanoma models that can be used to evaluate the efficacy of novel therapeutic modalities. Here, we discuss the current state of the art of melanoma models including genetically engineered mouse, patient-derived xenograft, zebrafish, and ex&nbsp;vivo and in&nbsp;vitro models. We also identify five major challenges that can be addressed using such models, including metastasis and tumor dormancy, drug resistance, the melanoma immune response, and the impact of aging and environmental exposures on melanoma progression and drug resistance. Additionally, we discuss the opportunity for building models for rare subtypes of melanomas, which represent an unmet critical need. Finally, we identify key recommendations for melanoma models that may improve accuracy of preclinical testing and predict efficacy in clinical trials, to help usher in the next generation of melanoma therapies

Integrative and comparative genomics identifies novel melanoma tumor-suppressor genes

A cardinal feature of melanoma is its metastatic propensity. Paucity of insights into the genetic events that drive metastasis has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for melanoma patients. Recent approaches that integrate human genomic and transcriptomic data provide unprecedented opportunities to discover oncogenic drivers in melanoma. However, the radically altered and complex cytogenetic profile of human melanoma makes the identification of such drivers particularly challenging. There is therefore a pressing need for developing biologically meaningful approaches that would facilitate the identification and validation of the driver lesions. We propose to combine comparative oncogenomics with an innovative mouse model to identify new bona fide cancer genes/pathways that drive melanoma progression and metastasis. Spontaneously acquired genetic alterations such as copy-number alterations and specific point mutations in mouse tumours of defined genetic origin will be used to prioritize relevant lesions from the complex human melanoma genomes. Priority will be given to lesions involving modifiers of the p53 tumour suppressor and non-coding RNAs as we are particularly interested in the contribution of these molecules to cancer development. Critically, a somatic cell gene delivery mouse model will be developed for rapid validation of the genetic alterations in an appropriate in vivo context.status: publishe

Beyond microRNA - Novel RNAs derived from small non-coding RNA and their implication in cancer

Over the recent years, Next Generation Sequencing (NGS) technologies targeting the microRNA transcriptome revealed the existence of many different RNA fragments derived from small RNA species other than microRNA. Although initially discarded as RNA turnover artifacts, accumulating evidence suggests that RNA fragments derived from small nucleolar RNA (snoRNA) and transfer RNA (tRNA) are not just random degradation products but rather stable entities, which may have functional activity in the normal and malignant cell. This review summarizes new findings describing the detection and alterations in expression of snoRNA-derived (sdRNA) and tRNA-derived (tRF) RNAs. We focus on the possible interactions of sdRNAs and tRFs with the canonical microRNA pathways in the cell and present current hypotheses on the function of these RNAs. (C) 2013 Elsevier Ireland Ltd. All rights reserved

Beyond microRNA – Novel RNAs derived from small non-coding RNA and their implication in cancer

AbstractOver the recent years, Next Generation Sequencing (NGS) technologies targeting the microRNA transcriptome revealed the existence of many different RNA fragments derived from small RNA species other than microRNA. Although initially discarded as RNA turnover artifacts, accumulating evidence suggests that RNA fragments derived from small nucleolar RNA (snoRNA) and transfer RNA (tRNA) are not just random degradation products but rather stable entities, which may have functional activity in the normal and malignant cell.This review summarizes new findings describing the detection and alterations in expression of snoRNA-derived (sdRNA) and tRNA-derived (tRF) RNAs. We focus on the possible interactions of sdRNAs and tRFs with the canonical microRNA pathways in the cell and present current hypotheses on the function of these RNAs

A comprehensive repertoire of tRNA-derived fragments in prostate cancer

Prostate cancer (PCa) is the most common cancer among men in developed countries. Although its genetic background is thoroughly investigated, rather little is known about the role of small non-coding RNAs (sncRNA) in this disease. tRNA-derived fragments (tRFs) represent a new class of sncRNAs, which are present in a broad range of species and have been reported to play a role in several cellular processes. Here, we analyzed the expression of tRFs in fresh frozen patient samples derived from normal adjacent prostate and different stages of PCa by RNA-sequencing. We identified 598 unique tRFs, many of which are deregulated in cancer samples when compared to normal adjacent tissue. Most of the identified tRFs are derived from the 5’- and 3’-ends of mature cytosolic tRNAs, but we also found tRFs produced from other parts of tRNAs, including pre-tRNA trailers and leaders, as well as tRFs from mitochondrial tRNAs. The 5’-derived tRFs comprise the most abundant class of tRFs in general and represent the major class among upregulated tRFs. The 3’-derived tRFs types are dominant among downregulated tRFs in PCa. We validated the expression of three tRFs using qPCR. The ratio of tRFs derived from tRNALysCTT and tRNAPheGAA emerged as a good indicator of progression-free survival and a candidate prognostic marker. This study provides a systematic catalogue of tRFs and their dysregulation in PCa and can serve as the basis for further research on the biomarker potential and functional roles of tRFs in this disease.This article has supplementary files, which can be found here:http://dx.doi.org/10.18632/oncotarget.829

Evaluation of optical features of the macula in multiple sclerosis

Purpose Differences in optical and irregularity measures of abnormal retinal tissue may provide additional information of impairment of the retinal nerve fiber layer (RNFL) and ganglion cell/inner plexiform layer complex (GCL+IPL) in multiple sclerosis (MS). The purpose of our study was to estimate these retinal changes in MS. Methods Twenty‐seven patients with MS were examined using Stratus OCT. The raw macular OCT data was exported and processed using OCTRIMA software and the fractal dimension (FD) and layer index (LI) values of seven intraretinal layers were obtained. The enrolled eyes were divided into two groups, based on ON in the history (ON+ group, n=13 and ON‐ group, n=14). Data of 73 healthy subjects (N) were used as controls. ANOVA with Newman‐Keuls post‐hoc analysis was used for the comparison of FD and LI values. The level of significance was set at p<0.001. Results A significant decrease was observed in LI in the entire macula and the perifoveal region in RNFL (12.4±1.4, 10.8±0.8, 9.3 ±1.4 and 14.0±1.7, 12.0±0.9, 10.0±1.7 for the N, ON‐ and ON+ groups, respectively). The RNFL in the ON‐ group was significantly different from both the N and ON+ groups (p<0.001 for all comparisons). No significant changes were found in the other layers. A significant increase was observed between the ON‐ and ON+ groups in FD in the entire macula and the perifoveal region in the RNFL layer (1.8±0.04, 1.8±0.07 p<0.001 and 1.6±0.06, 1.6±0.1 p<0.001, respectively) but no significant changes were found in the other layers. Conclusion In MS, the optical features of the ganglion cells and the RNFL also change besides the pathological remodeling of macular tissue. This result may help to improve the diagnostic efficacy of OCT in MS. Commercial interes