Transcriptional background effects on a tumor driver gene in a transgenic medaka melanoma model
Abdulsahib, S.; Boswell, W.; Boswell, M.; Savage, M.; Schartl, M.; Lu, Y.
Show abstract
The Xiphophorus melanoma receptor kinase gene, xmrk, is a bona fide oncogene driving melanocyte tumorigenesis of Xiphophorus fish. When ectopically expressed in medaka, it not only induces development of several pigment cell tumor types in different strains of medaka, but also induces different tumor types within the same animal, suggesting its oncogenic activity has a transcriptomic background effect. Although the central pathways that xmrk utilizes to lead to melanomagenesis are well documented, genes and genetic pathways that modulate the oncogenic effect, and alter the course of disease have not been studied so far. To understand how the genetic networks between different histocytes of xmrk-driven tumors are composed, we isolated two types of tumors, melanoma and xanthoerythrophoroma, from the same xmrk transgenic medaka individuals, established the transcriptional profiles of both xmrk-driven tumors, and compared (1) genes that are co-expressed with xmrk in both tumor types, and (2) differentially expressed genes and their associated molecular functions, between the two tumor types. Transcriptomic comparisons between the two tumor types show melanoma and xanthoerythrophoroma are characterized by transcriptional features representing varied functions, indicating distinct molecular interactions between the driving oncogene and the cell type-specific transcriptomes. Melanoma tumors exhibited gene signatures that are relevant to proliferation and invasion while xanthoerythrophoroma tumors are characterized by expression profiles related metabolism and DNA repair. We conclude the transcriptomic backgrounds, exemplified by cell-type specific genes that are downstream of xmrk effected signaling pathways, contribute the potential to change the course of tumor development and may affect overall tumor outcomes.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Molecular pathways associated with Kallikrein 6 overexpression in colorectal cancer 93%
- A Comparative Genome-wide Transcriptome Analysis of Glucocorticoid Responder and Non-Responder Primary Human Trabecular Meshwork Cells 92%
- Structural variability, expression profile and pharmacogenetics properties of TMPRSS2 gene as a potential target for COVID-19 therapy 92%
Similar papers in this journal
- Metastasis is altered through multiple processes regulated by the E2F1 transcription factor 93%
- Exploration of phosphoproteomic association during epimorphic regeneration 93%
- Transcriptomic analysis of melanoma cells reveals an association of α-synuclein with regulation of the inflammatory response. 92%
Similar papers in this journal
- The clinical, genomic, and transcriptomic landscape of BRAF mutant cancers 94%
- COL7A1 expression improves prognosis prediction for patients with clear cell renal cell carcinoma atop of stage 93%
- Capacity for compensatory cyclin D2 response confers trametinib resistance in canine mucosal melanoma 93%
Similar papers in this journal
- Computing Skin Cutaneous Melanoma Outcome from the HLA-alleles and Clinical Characteristics 92%
- Hypoxia induced sex-difference in zebrafish brain proteome profile reveals the crucial role of H3K9me3 in recovery from acute hypoxia 92%
- Transcriptomic and epigenomic dynamics of honey bees in response to lethal IAPV viral infection 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.