Dataset Information

Targeting MYCN in Pediatric and Adult Cancers.

ABSTRACT: The deregulation of the MYC family of oncogenes, including c-MYC, MYCN and MYCL occurs in many types of cancers, and is frequently associated with a poor prognosis. The majority of functional studies have focused on c-MYC due to its broad expression profile in human cancers. The existence of highly conserved functional domains between MYCN and c-MYC suggests that MYCN participates in similar activities. MYC encodes a basic helix-loop-helix-leucine zipper (bHLH-LZ) transcription factor (TF) whose central oncogenic role in many human cancers makes it a highly desirable therapeutic target. Historically, as a TF, MYC has been regarded as "undruggable". Thus, recent efforts focus on investigating methods to indirectly target MYC to achieve anti-tumor effects. This review will primarily summarize the recent progress in understanding the function of MYCN. It will explore efforts at targeting MYCN, including strategies aimed at suppression of MYCN transcription, destabilization of MYCN protein, inhibition of MYCN transcriptional activity, repression of MYCN targets and utilization of MYCN overexpression dependent synthetic lethality.

SUBMITTER: Liu Z

PROVIDER: S-EPMC7898977 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Targeting MYCN in Pediatric and Adult Cancers.

Liu Zhihui Z Chen Samuel S SS Clarke Saki S Veschi Veronica V Thiele Carol J CJ

Frontiers in oncology 20210208

The deregulation of the MYC family of oncogenes, including c-MYC, MYCN and MYCL occurs in many types of cancers, and is frequently associated with a poor prognosis. The majority of functional studies have focused on c-MYC due to its broad expression profile in human cancers. The existence of highly conserved functional domains between MYCN and c-MYC suggests that MYCN participates in similar activities. MYC encodes a basic helix-loop ...[more]

PMID: 33628735

Similar Datasets

Project description:The genomics data-driven identification of gene signatures and pathways has been routinely explored for predicting cancer survival and making decisions related to targeted treatments. A large number of packages and tools have been developed to correlate gene expression/mutations to the clinical outcome but lack the ability to perform such analysis based on pathways, gene sets, and gene ratios. Furthermore, in this single-cell omics era, the cluster markers from cancer single-cell transcriptomics studies remain an underutilized prognostic option. Additionally, no bioinformatics online tool evaluates the associations between the enrichment of canonical cell types and survival across cancers. Here we have developed Survival Genie, a web tool to perform survival analysis on single-cell RNA-seq (scRNA-seq) data and a variety of other molecular inputs such as gene sets, genes ratio, tumor-infiltrating immune cells proportion, gene expression profile scores, and tumor mutation burden. For a comprehensive analysis, Survival Genie contains 53 datasets of 27 distinct malignancies from 11 different cancer programs related to adult and pediatric cancers. Users can upload scRNA-seq data or gene sets and select a gene expression partitioning method (i.e., mean, median, quartile, cutp) to determine the effect of expression levels on survival outcomes. The tool provides comprehensive results including box plots of low and high-risk groups, Kaplan-Meier plots with univariate Cox proportional hazards model, and correlation of immune cell enrichment and molecular profile. The analytical options and comprehensive collection of cancer datasets make Survival Genie a unique resource to correlate gene sets, pathways, cellular enrichment, and single-cell signatures to clinical outcomes to assist in developing next-generation prognostic and therapeutic biomarkers. Survival Genie is open-source and available online at https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/ .

Dataset Information

Targeting MYCN in Pediatric and Adult Cancers.

Publications

Targeting <i>MYCN</i> in Pediatric and Adult Cancers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets