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Cureus Dec 2023Diabetic retinopathy (DR) is a leading cause of global visual impairment, necessitating a comprehensive understanding of its vascular and neural components for effective... (Review)
Review
A Systematic Review of the Neuroprotective Effects of Vascular Endothelial Growth Factor (VEGF) in Diabetic Retinopathy and Diabetic Macular Edema: Unraveling the Molecular Mechanisms and Clinical Implications.
Diabetic retinopathy (DR) is a leading cause of global visual impairment, necessitating a comprehensive understanding of its vascular and neural components for effective therapeutic interventions. While vascular pathology is well-established, recent evidence suggests a neurodegenerative role in DR. Vascular endothelial growth factor (VEGF), traditionally implicated in angiogenesis, has emerged as a key player with neuroprotective potential. This systematic review evaluates the literature to shed light on molecular mechanisms and clinical implications in this regard. The review adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, encompassing a thorough search strategy across multiple databases. Three in vitro studies met the inclusion criteria, highlighting the limited research in this evolving field. Findings suggest VEGF's neuroprotective effects on retinal ganglion cells (RGCs) and retinal neurons, unveiling potential therapeutic avenues. However, concerns arise regarding anti-VEGF therapies' impact on RGC survival. The review discusses the need for further research to delineate specific isoforms and signaling pathways responsible for VEGF-mediated neuroprotection. The delicate balance between angiogenesis and neuroprotection poses challenges in therapeutic development, emphasizing the importance of targeted interventions. Despite limitations, this review provides valuable insights into the intricate relationship between VEGF and neuroprotection in DR, paving the way for future investigations and redefining therapeutic strategies.
PubMed: 38288195
DOI: 10.7759/cureus.51351 -
Journal of Human Genetics May 2015Mutations in APP, PSEN1 and PSEN2 as the genetic causes of familial Alzheimer's disease (FAD) have been found in various ethnic populations. A substantial number of FAD... (Meta-Analysis)
Meta-Analysis Review
Mutations in APP, PSEN1 and PSEN2 as the genetic causes of familial Alzheimer's disease (FAD) have been found in various ethnic populations. A substantial number of FAD pedigrees with mutations have been reported in the Japanese population; however, it remains unclear whether the genetic and clinical features of FAD in the Japanese population differ from those in other populations. To address this issue, we conducted a systematic review and meta-analysis of Japanese FAD and frontotemporal dementia with parkinsonism linked to chromosome 17 (FTDP-17) by literature search. Using this analysis, we identified 39 different PSEN1 mutations in 140 patients, 5 APP mutations in 35 patients and 16 MAPT mutations in 84 patients. There was no PSEN2 mutation among Japanese patients. The age at onset in Japanese FAD patients with PSEN1 mutations was significantly younger than that in patients with APP mutations. Kaplan-Meier analysis revealed that patients with MAPT mutations showed a shorter survival than patients with PSEN1 or APP mutations. Patients with mutations in different genes exhibit characteristic clinical presentations, suggesting that mutations in causative genes may modify the clinical presentations. By collecting and cataloging genetic and clinical information on Japanese FAD and FTDP-17, we developed an original database designated as Japanese Familial Alzheimer's Disease Database, which is accessible at http://alzdb.bri.niigata-u.ac.jp/.
Topics: Age of Onset; Alzheimer Disease; Chromosomes, Human, Pair 17; Frontotemporal Dementia; Genetic Predisposition to Disease; Humans; Mutation
PubMed: 25694106
DOI: 10.1038/jhg.2015.15 -
Neuro-oncology Jun 2023Quantitative imaging analysis through radiomics is a powerful technology to non-invasively assess molecular correlates and guide clinical decision-making. There has been...
BACKGROUND
Quantitative imaging analysis through radiomics is a powerful technology to non-invasively assess molecular correlates and guide clinical decision-making. There has been growing interest in image-based phenotyping for meningiomas given the complexities in management.
METHODS
We systematically reviewed meningioma radiomics analyses published in PubMed, Embase, and Web of Science until December 20, 2021. We compiled performance data and assessed publication quality using the radiomics quality score (RQS).
RESULTS
A total of 170 publications were grouped into 5 categories of radiomics applications to meningiomas: Tumor detection and segmentation (21%), classification across neurologic diseases (54%), grading (14%), feature correlation (3%), and prognostication (8%). A majority focused on technical model development (73%) versus clinical applications (27%), with increasing adoption of deep learning. Studies utilized either private institutional (50%) or public (49%) datasets, with only 68% using a validation dataset. For detection and segmentation, radiomic models had a mean accuracy of 93.1 ± 8.1% and a dice coefficient of 88.8 ± 7.9%. Meningioma classification had a mean accuracy of 95.2 ± 4.0%. Tumor grading had a mean area-under-the-curve (AUC) of 0.85 ± 0.08. Correlation with meningioma biological features had a mean AUC of 0.89 ± 0.07. Prognostication of the clinical course had a mean AUC of 0.83 ± 0.08. While clinical studies had a higher mean RQS compared to technical studies, quality was low overall with a mean RQS of 6.7 ± 5.9 (possible range -8 to 36).
CONCLUSIONS
There has been global growth in meningioma radiomics, driven by data accessibility and novel computational methodology. Translatability toward complex tasks such as prognostication requires studies that improve quality, develop comprehensive patient datasets, and engage in prospective trials.
Topics: Humans; Meningioma; Prospective Studies; Neoplasm Grading; Meningeal Neoplasms
PubMed: 36723606
DOI: 10.1093/neuonc/noad028 -
Cancers Sep 2023Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment.... (Review)
Review
Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment. Computational pathology (CPATH) can identify clinical outcome predictors, offering an objective approach to improve prognosis. However, a systematic review of CPATH in BC literature is lacking. Therefore, we present a comprehensive overview of studies that used CPATH in BC, analyzing 33 out of 2285 identified studies. Most studies analyzed regions of interest to distinguish normal versus tumor tissue and identify tumor grade/stage and tissue types (e.g., urothelium, stroma, and muscle). The cell's nuclear area, shape irregularity, and roundness were the most promising markers to predict recurrence and survival based on selected regions of interest, with >80% accuracy. CPATH identified molecular subtypes by detecting features, e.g., papillary structures, hyperchromatic, and pleomorphic nuclei. Combining clinicopathological and image-derived features improved recurrence and survival prediction. However, due to the lack of outcome interpretability and independent test datasets, robustness and clinical applicability could not be ensured. The current literature demonstrates that CPATH holds the potential to improve BC diagnosis and prediction of prognosis. However, more robust, interpretable, accurate models and larger datasets-representative of clinical scenarios-are needed to address artificial intelligence's reliability, robustness, and black box challenge.
PubMed: 37760487
DOI: 10.3390/cancers15184518 -
Insights Into Imaging Dec 2023Calcifications on mammography can be indicative of breast cancer, but the prognostic value of their appearance remains unclear. This systematic review and meta-analysis... (Review)
Review
BACKGROUND
Calcifications on mammography can be indicative of breast cancer, but the prognostic value of their appearance remains unclear. This systematic review and meta-analysis aimed to evaluate the association between mammographic calcification morphology descriptors (CMDs) and clinicopathological factors.
METHODS
A comprehensive literature search in Medline via Ovid, Embase.com, and Web of Science was conducted for articles published between 2000 and January 2022 that assessed the relationship between CMDs and clinicopathological factors, excluding case reports and review articles. The risk of bias and overall quality of evidence were evaluated using the QUIPS tool and GRADE. A random-effects model was used to synthesize the extracted data. This systematic review is reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA).
RESULTS
Among the 4715 articles reviewed, 29 met the inclusion criteria, reporting on 17 different clinicopathological factors in relation to CMDs. Heterogeneity between studies was present and the overall risk of bias was high, primarily due to small, inadequately described study populations. Meta-analysis demonstrated significant associations between fine linear calcifications and high-grade DCIS [pooled odds ratio (pOR), 4.92; 95% confidence interval (CI), 2.64-9.17], (comedo)necrosis (pOR, 3.46; 95% CI, 1.29-9.30), (micro)invasion (pOR, 1.53; 95% CI, 1.03-2.27), and a negative association with estrogen receptor positivity (pOR, 0.33; 95% CI, 0.12-0.89).
CONCLUSIONS
CMDs detected on mammography have prognostic value, but there is a high level of bias and variability between current studies. In order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.
CRITICAL RELEVANCE STATEMENT
Mammographic calcification morphology descriptors (CMDs) have prognostic value, but in order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.
SYSTEMATIC REVIEW REGISTRATION
CRD42022341599 KEY POINTS: • Mammographic calcifications can be indicative of breast cancer. • The prognostic value of mammographic calcifications is still unclear. • Specific mammographic calcification morphologies are related to lesion aggressiveness. • Variability between studies necessitates standardization in calcification evaluation to achieve clinical utility.
PubMed: 38051355
DOI: 10.1186/s13244-023-01529-z -
World Journal of Gastroenterology Aug 2016Epithelial-to-mesenchymal transition (EMT) is defined as the transformation of an epithelial cell into a spindle cell with the loss of membrane E-cadherin expression and... (Review)
Review
Epithelial-to-mesenchymal transition (EMT) is defined as the transformation of an epithelial cell into a spindle cell with the loss of membrane E-cadherin expression and the gain of mesenchymal markers positivity. In the field of colorectal cancer (CRC), first data about EMT was published in 1995 and more than 400 papers had been written up to March 2016. Most of them are focused on the molecular pathways and experimentally-proved chemoresistance. In the present article, an update in the field of EMT in CRC based on the review of the literature and personal experience of the authors is presented. The information about the molecular and immunohistochemical (IHC) particularities of these processes and their possible role in the prognosis of CRC were also up-dated. This article focuses on the IHC quantification of the EMT, the immunoprofile of tumor buds and on the relation between EMT, angiogenesis, and stem cells activation. The EMT-induced chemoresistance vs chemotherapy- or radiotherapy-induced EMT and cellular senescence was also synthesized for both conventional and targeted therapy. As a future perspective, the EMT-angiogenesis-stemness link could be used as a possible valuable parameter for clinical follow-up and targeted therapeutic oncologic management of patients with CRC. Association of dexamethasone and angiotensin converting enzyme inhibitors combined with conventional chemotherapies could have clinical benefits in patients with CRC. The main conclusion is that, although many studies have been published, the EMT features are still incompletely elucidated and newly discovered EMT markers provide confusing data in understanding this complicated process, which might have significant clinical impact.
Topics: Colorectal Neoplasms; Epithelial-Mesenchymal Transition; Humans; Immunohistochemistry; Neoplasm Metastasis; Neovascularization, Physiologic
PubMed: 27570416
DOI: 10.3748/wjg.v22.i30.6764 -
Molecular Oncology Nov 2021Gastric cancer (GC) pathogenesis is complex and heterogeneous, reflecting morphological, molecular and genetic diversity. Diffuse gastric cancer (DGC) and intestinal... (Review)
Review
Gastric cancer (GC) pathogenesis is complex and heterogeneous, reflecting morphological, molecular and genetic diversity. Diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC) are the major histological types. GC may be sporadic or hereditary; sporadic GC is related to environmental and genetic low-risk factors and hereditary GC is caused by inherited high-risk mutations, so far identified only for the diffuse histotype. DGC phenotypic heterogeneity challenges the current understanding of molecular mechanisms underlying carcinogenesis. The definition of a DGC-specific mutational profile remains controversial, possibly reflecting the heterogeneity of DGC-related histological subtypes [signet-ring cell carcinoma (SRCC) and poorly cohesive carcinoma not otherwise specified (PCC-NOS)]. Indeed, DGC and DGC-related subtypes may present specific mutational profiles underlying the particularly aggressive behaviour and dismal prognosis of DGC vs IGC and PCC-NOS vs SRCC. In this systematic review, we revised the histological presentations, molecular classifications and approved therapies for gastric cancer, with a focus on DGC. We then analysed results from the most relevant studies, reporting mutational analysis data specifying mutational frequencies, and their relationship with DGC and IGC histological types, and with specific DGC subtypes (SRCC and PCC-NOS). We aimed at identifying histology-associated mutational profiles with an emphasis in DGC and its subtypes (DGC vs IGC; sporadic vs hereditary DGC; and SRCC vs PCC-NOS). We further used these mutational profiles to identify the most commonly affected molecular pathways and biological functions, and explored the clinical trials directed specifically to patients with DGC. This systematic analysis is expected to expose a DGC-specific molecular profile and shed light into potential targets for therapeutic intervention, which are currently missing.
Topics: Adenocarcinoma; Carcinoma, Signet Ring Cell; Germ-Line Mutation; Humans; Stomach Neoplasms
PubMed: 33724653
DOI: 10.1002/1878-0261.12948 -
Biomedicine & Pharmacotherapy =... Sep 2022In multicellular organisms, nutrient uptake and its metabolism are subject to stringent regulation to maintain cellular integrity and prevent aberrant cell... (Review)
Review
In multicellular organisms, nutrient uptake and its metabolism are subject to stringent regulation to maintain cellular integrity and prevent aberrant cell proliferation. However, the altered signaling pathways and gene expression disorders in hepatocellular carcinoma (HCC) induce the transformation of metabolic patterns. The reprogrammed metabolic pattern not only conferred HCC cells viability in nutrient-deficient environments, but also contributed to the formation of a unique immune surveillance barrier. Furthermore, in this metabolic pattern, the accumulation of a large number of oxidation products in cells also activates tumor-related signaling pathways. Therefore, the exploration of underlying molecular mechanisms of the metabolic switch will help to improve therapeutic strategies for HCC. We systematically reviewed the landmark events and current research breakthroughs in the study of glucometabolic reprogramming in HCC. Focusing on the central carbon metabolism, the internal energy conversion in HCC and its cancerous mechanisms were fully explained. Furthermore, we also discussed the HCC-specific acellular regulation, metabolic switch of cancer stem cells, oxidative stress adaptation and the formation of immunosuppressive microenvironment, hoping to provide insights for future basic and clinical research.
Topics: Carbon; Carcinoma, Hepatocellular; Cell Line, Tumor; Cell Proliferation; Gene Expression Regulation, Neoplastic; Glycolysis; Humans; Liver Neoplasms; Tumor Microenvironment
PubMed: 36076503
DOI: 10.1016/j.biopha.2022.113485 -
PloS One 2014Though rare in occurrence, patients with rare bleeding disorders (RBDs) are highly heterogeneous and may manifest with severe bleeding diathesis. Due to the high rate of... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Though rare in occurrence, patients with rare bleeding disorders (RBDs) are highly heterogeneous and may manifest with severe bleeding diathesis. Due to the high rate of consanguinity in many caste groups, these autosomal recessive bleeding disorders which are of rare occurrence in populations across the world, may not be as rare in India.
OBJECTIVES
To comprehensively analyze the frequency and nature of mutations in Indian patients with RBDs.
METHODS
Pubmed search was used (www.pubmed.com) to explore the published literature from India on RBDs using the key words "rare bleeding disorders", "mutations", "India", "fibrinogen", "afibrinogenemia", "factor II deficiency", "prothrombin" "factor VII deficiency", "factor V deficiency", "factor X deficiency", "factor XI deficiency", "combined factor V and VIII deficiency", "factor XIII deficiency", "Bernard Soulier syndrome" and "Glanzmanns thrombasthenia" in different combinations. A total of 60 relevant articles could be retrieved. The distribution of mutations from India was compared with that of the world literature by referring to the Human Gene Mutation Database (HGMD) (www.hgmd.org).
RESULTS
Taken together, 181 mutations in 270 patients with different RBDs have been reported from India. Though the types of mutations reported from India and their percentage distribution with respect to the world data are largely similar, yet much higher percentage of small deletions, duplication mutations, insertions, indels were observed in this analysis. Besides the identification of novel mutations and polymorphisms, several common mutations have also been reported, which will allow to develop a strategy for mutation screening in Indian patients with RBDs.
CONCLUSION
There is a need for a consortium of Institutions working on the molecular pathology of RBDs in India. This will facilitate a quicker and cheaper diagnosis of RBDs besides its utility in first trimester prenatal diagnosis of the affected families.
Topics: Blood Coagulation Disorders; Blood Coagulation Factors; Databases, Genetic; Fibrinogen; Humans; India; Mutation; Pathology, Molecular; Rare Diseases
PubMed: 25275492
DOI: 10.1371/journal.pone.0108683 -
European Journal of Cancer (Oxford,... Jan 2022Over the past decade, the development of molecular high-throughput methods (omics) increased rapidly and provided new insights for cancer research. In parallel, deep...
BACKGROUND
Over the past decade, the development of molecular high-throughput methods (omics) increased rapidly and provided new insights for cancer research. In parallel, deep learning approaches revealed the enormous potential for medical image analysis, especially in digital pathology. Combining image and omics data with deep learning tools may enable the discovery of new cancer biomarkers and a more precise prediction of patient prognosis. This systematic review addresses different multimodal fusion methods of convolutional neural network-based image analyses with omics data, focussing on the impact of data combination on the classification performance.
METHODS
PubMed was screened for peer-reviewed articles published in English between January 2015 and June 2021 by two independent researchers. Search terms related to deep learning, digital pathology, omics, and multimodal fusion were combined.
RESULTS
We identified a total of 11 studies meeting the inclusion criteria, namely studies that used convolutional neural networks for haematoxylin and eosin image analysis of patients with cancer in combination with integrated omics data. Publications were categorised according to their endpoints: 7 studies focused on survival analysis and 4 studies on prediction of cancer subtypes, malignancy or microsatellite instability with spatial analysis.
CONCLUSIONS
Image-based classifiers already show high performances in prognostic and predictive cancer diagnostics. The integration of omics data led to improved performance in all studies described here. However, these are very early studies that still require external validation to demonstrate their generalisability and robustness. Further and more comprehensive studies with larger sample sizes are needed to evaluate performance and determine clinical benefits.
Topics: Deep Learning; Genomics; Humans; Image Processing, Computer-Assisted; Neoplasms
PubMed: 34810047
DOI: 10.1016/j.ejca.2021.10.007