Despite new developments in molecular techniques and better knowledge on lung cancer tumor biology, many genetic alterations associated with the development and progression of lung carcinogenesis still remain unclear. Although the development of targeted agents has improved response rates and survival, lung cancer has a very high mortality rate, even for early stages. Thus, there is a greater need for other mechanisms or technologies that may help us diagnose, predict, and treat patients with lung cancer in a more effective way. One of these technologies has been the use of genomics. Some of the available genomic technologies include single-nucleotide polymorphism analysis, high-throughput capillary sequencing, serial analysis of gene expression, and gene expression arrays. DNA microarray analysis is capable of discovering changes in DNA expression within the neoplastic tumor. Thus, gene expression array could help us to decipher the complexity and interaction of different oncogenic pathways and, hence, could contribute to the selection of better targeted agents on an individual basis rather than a general and nonspecific approach as it has been done for many decades. Several studies initiated a few years ago have started to produce fruitful results. Herein, we review the role of gene expression profiling in lung cancer as a diagnostic tool, predictive and prognostic biomarker, and its potential use for a "personalized" medicine in the years to come.
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http://dx.doi.org/10.3816/CLC.2009.n.023 | DOI Listing |
Curr Pharm Biotechnol
January 2025
Department of Intensive Care Unit, Affiliated Hospital of Guangdong Medical University, 524000 Zhanjiang, China.
Objectives: This study aimed to comprehensively investigate the molecular landscape of gastric cancer (GC) by integrating various bioinformatics tools and experimental validations.
Methodology: GSE79973 dataset, limma package, STRING, UALCAN, GEPIA, OncoDB, cBioPortal, DAVID, TISIDB, Gene Set Cancer Analysis (GSCA), tissue samples, RT-qPCR, and cell proliferation assay were employed in this study.
Results: Analysis of the GSE79973 dataset identified 300 differentially expressed genes (DEGs), from which COL1A1, COL1A2, CHN1, and FN1 emerged as pivotal hub genes using protein-protein interaction network analysis.
CNS Neurol Disord Drug Targets
January 2025
Department of Biotechnology, National Institute of Technology, Raipur, 492001, India.
Parkinson's disease (PD) is a neurodegenerative disorder that results from the progressive loss of neurons in the brain followed by symptoms such as slowness and rigidity in movement, sleep disorders, dementia and many more. The different mechanisms due to which the neuronal degeneration occurs have been discussed, such as mutation in PD related genes, formation of Lewy bodies, oxidation of dopamine. This review discusses current surgical treatment and gene therapies with novel developments proposed for PD.
View Article and Find Full Text PDFJ Pathol
January 2025
Laboratory of Pathology, Center for Cancer Research, NCI, Bethesda, MD, USA.
Rhabdomyosarcoma (RMS) is a family of phenotypically myogenic paediatric cancers consisting of two major subtypes: fusion-positive (FP) RMS, most commonly involving the PAX3::FOXO1 fusion gene, formed by the fusion of paired box 3 (PAX3) and forkhead box O1 (FOXO1) genes, and fusion-negative (FN) RMS, lacking these gene fusions. In humans, DNA methylation patterns distinguish these two subtypes as well as mutation-associated subsets within these subtypes. To investigate the biological factors responsible for these methylation differences, we profiled DNA methylation in RMS tumours derived from genetically engineered mouse models (GEMMs) in which various driver mutations were introduced into different myogenic lineages.
View Article and Find Full Text PDFSmall
January 2025
Department of Surgical Oncology and General Surgery Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education The First Affiliated Hospital of China Medical University, Shenyang, 110001, China.
Current in vitro models for gastric cancer research, such as 2D cell cultures and organoid systems, often fail to replicate the complex extracellular matrix (ECM) found in vivo. For the first time, this study utilizes a gelatin methacryloyl (GelMA) hydrogel, a biomimetic ECM-like material, in 3D bioprinting to construct a physiologically relevant gastric cancer model. GelMA's tunable mechanical properties allow for the precise manipulation of cellular behavior within physiological ranges.
View Article and Find Full Text PDFCancer Med
January 2025
Department of Pharmacology, College of Pharmacy, Jinan University, Guangzhou, China.
Background: Distinctive heterogeneity characterizes diffuse large B-cell lymphoma (DLBCL), one of the most frequent types of non-Hodgkin's lymphoma. Mitochondria have been demonstrated to be closely involved in tumorigenesis and progression, particularly in DLBCL.
Objective: The purposes of this study were to identify the prognostic mitochondria-related genes (MRGs) in DLBCL, and to develop a risk model based on MRGs and machine learning algorithms.
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