Dongyu Jia

Background: Cancer is the 2nd leading cause of human death, and thus an extensive and fast-evolving research field aimed at understanding and curing this disease has developed. Basic science researchers frequently utilize various model organisms to decipher the secrets of cancer, including Drosophila melanogaster . Methods: In this bibliometric analysis study, we extracted and filtered publication data related to Drosophila cancer research from Clarivate’s Web of Science Core Collection from 1990 to 2024, then utilized HistCite and CiteSpace to analyze the collected 2594 published articles. Results: We observed a general trend of increasing growth in the number of publications in the Drosophila cancer research field over the last 35 years. These studies were published by 8867 individual authors from 1678 institutions across 492 journals. We further analyzed the landscape and evolution of their gene, genetics, and cancer modeling research domains, identifying key historically important articles and cancer research domains. We also revealed that the United States, Harvard University, and Perrimon N were the leading contributors in scientific collaboration among countries, institutions, and authors, respectively. Keyword burst analyses further revealed both historical and emerging trends within the Drosophila cancer research field, which are closely related to genes, genetics, and phenotypic traits of tumor studies. Conclusions: In this study, we analyzed the structural and temporal dimensions of Drosophila as a cancer model, offering a comprehensive retrospective of its role, outlining current cancer research areas, and highlighting emerging trends. By examining its historical significance, showing the latest research areas in genes, genetics, and tumor biology, and projecting future research directions, we aimed to shed light on the evolving landscape of the Drosophila model in cancer research.

Many cancers are initiated by the activation of oncogenes, which cause cancer phenotypes through a variety of disruptive mechanisms. FYN is a human proto-oncogene implicated in many cancers, especially those of the central nervous system and ovary. FYN encodes a non-receptor tyrosine kinase from the Src tyrosine kinase family, and has been shown to promote proliferation and metastasis. Our previous publication demonstrated that introduction of human FYN in the Drosophila eye resulted in a deleterious effect on eye structure, suggesting potential conserved functions across species. This study utilized the Gal4-UAS system to express a wildtype version of human FYN and a constitutively active form of its Drosophila ortholog, Src64B, in the eye and ovary of Drosophila melanogaster, to further explore their conserved functions. Our findings suggested that overexpression of FYN and Src64B in Drosophila eye tissue exhibited conserved developmental defects and a rough eye phenotype. FYN overexpression in the Drosophila ovary demonstrated accumulation of anterior egg chamber squamous cells without associated proliferative activity. These accumulated squamous cells exhibited altered expressions of apical, basolateral, and Par-complex polarity factors. Constitutive expression of Src64B showed similar phenotypes. These results indicate that the conserved oncogenic potential of FYN may be linked to changes in cell polarity signaling, which is considered a hallmark of cancer.

Understanding the signaling pathways in which genes participate is essential for discovering the etiology of diseases in humans. The model organism, Drosophila melanogaster, has been crucial in understanding the signaling pathways in humans, given the evolutionary conservation of a significant number of genes between the two species. Genetic screens using Drosophila are a useful way of testing large number of genes to study their function and roles within signaling pathways. We conducted a large-scale genetic screen to identify which human genes cause an alteration in the morphology of the Drosophila eye. The GMR-Gal4 was employed to activate a single UAS-human gene in the eye tissue. In total, we screened 802 UAS-human gene stocks, corresponding to 787 human protein-coding genes, for the ability to influence eye development. We found that overexpression of 64 human genes were capable of disrupting eye development, as determined by phenotypic changes in eye texture, size, shape, bristle morphology, and ommatidia organization. Subsequent analysis revealed that the fly genome encodes proteins that are homologous to a majority of the 64 human genes, raising the possibility that overexpression of these transgenes altered eye development by altering the activity of evolutionarily conserved developmental signaling pathways. Consistent with this hypothesis, a secondary screen demonstrated that overexpression of fly homologs produced phenotypes that mimicked those produced by overexpression of the human gene. Our screening has identified 64 human genes capable of inducing phenotypes in the fly, offering a foundation for ongoing research aimed at understanding functionally conserved pathways across species.

Many highly conserved pathways control the development and determine cell fate in organisms. One of these pathways is the Notch signaling pathway that allows for local cell–cell communication. Researchers have found that the timing for when Notch signaling activates the target gene is important for maintaining normal gene expression. Any alterations in the downstream gene expression could cause issues with development or certain diseases. The Drosophila oogenesis is a widely used model in developmental biology for analyzing the Notch pathway. However, determining the stage of oogenesis is difficult and varies depending on individual analyzing it. Here, we provide a MATLAB tool to automatically identify the stage of a Drosophila egg chamber and reveal the Notch expression pattern. Key words Drosophila Notch signaling Notch expression Egg chamber stage MATLAB

As a result of the culmination of data, and the fast-paced advancement of new research, all the biological information collected can make it difficult to sort data. This is oftentimes experienced when learning about the human genome. Fortunately, with the advancement of technology, the field of bioinformatics has emerged which has allowed for the creation of a variety of biological databases. These biological databases provide a condensed reservoir of organized information that is easy to use and topic-specific. Here, we provide a list of 39 biological databases that help break down the fundamental details of a gene. This chapter uses the NOTCH1 gene as an example to demonstrate how biological databases can be used to extract gene information. Five sections were created to highlight the major areas needed to build a comprehensive foundation of NOTCH1. The first section lists databases containing basic gene and protein product information. The next section consists of protein interactions and signaling pathway databases which are essential in understanding the biological processes a gene product is involved in. Gene expression and disease databases are the next two sections which are connected since disease results from the aberrant expression of a gene product. The last database section examines model organisms which serve a key role in the study of human genetic diseases. Using these databases, we can elucidate NOTCH1’s gene/protein structure, expression, and vital physiological function through the Notch signaling pathway. Key words Notch signaling Bioinformatics tools

Living organisms require complex signaling interactions and proper regulation of these interactions to influence biological processes. Of these complex networks, one of the most distinguished is the Notch pathway. Dysregulation of this pathway often results in defects during organismal development and can be a causative mechanism for initiation and progression of cancer. Despite previous research entailing the importance of this signaling pathway and the organismal processes that it is involved in, less is known concerning the major Notch downstream targets, especially the onset and sequence in which they are modulated during normal development. As timing of regulation may be linked to many biological processes, we investigated and established a model of temporal patterning of major Notch downstream targets including broad, cut, and hindsight during Drosophila melanogaster egg chamber development. We confirmed the sequential order of Broad upregulation, Hindsight upregulation, and Cut downregulation. In addition, we showed that Notch signaling could be activated at stage 4, one stage earlier than the stage 5, a previously long-held belief. However, our further mitotic marker analysis re-stated that mitotic cycle continues until stage 5. Through our study, we once again validated the effectiveness and reliability of our MATLAB toolbox designed to systematically identify egg chamber stages based on area size, ratio, and additional morphological characteristics.

COVID-19 epidemic doubling time by Chinese province was increasing from January 20 through February 9, 2020. The harmonic mean of the arithmetic mean doubling time estimates ranged from 1.4 (Hunan, 95% CI, 1.2-2.0) to 3.1 (Xinjiang, 95% CI, 2.1-4.8), with an estimate of 2.5 days (95% CI, 2.4-2.6) for Hubei.

Notch signaling is a highly conserved regulatory pathway involved in many cellular processes. Dysregulation of this signaling pathway often leads to interference with proper development and may even result in initiation or progression of cancers in certain cases. Because this pathway serves complex and versatile functions, it can be studied extensively through many different approaches. Of these, bioinformatics provides an undeniably cost-efficient, approachable, and user-friendly method of study. Bioinformatics is a useful way to extract smaller pieces of information from large-scale datasets. Through the implementation of various bioinformatics approaches, researchers can quickly, reliably, and efficiently interpret these large datasets, yielding insightful applications and scientific discoveries. Here, a protocol is presented for integration of bioinformatics approaches to investigate the role of Notch signaling in ovarian cancer. Furthermore, bioinformatics findings are validated through experimentation.