An in vivo systematic genetic analysis of tumour progression in Drosophila - RNAi line: 34689
Publication Date
May 10, 2019
Creators
Description
Metastasis is the leading cause of death for cancer patients. Consequently it is imperative that we improve our understanding of the molecular mechanisms that underlie progression of tumour growth towards malignancy. Advances in genome characterisation technologies have been very successful in identifying commonly mutated or misregulated genes in a variety of human cancers. A major challenge however is the translation of these findings to new biological insight due to the difficulty in evaluating whether these candidate genes drive tumour progression. Using the genetic amenability of Drosophila melanogaster we generated tumours with specific genotypes in the living animal and carried out a detailed systematic loss-of-function analysis to identify numerous conserved genes that enhance or suppress epithelial tumour progression. This enabled the discovery of functional cooperative regulators of invasion and the establishment of a network of conserved ‘invasion suppressors’.
RNAi line: 34689 (III)
Source: Bloomington
Name: shn
Full name: schnurri
Also known as: quo, schnurri, l(2)04738, EP2359
Annotation symbol: CG7734
FlyBase ID: FBgn0003396
File naming convention: File names typically contain representations of date (DDMMYY), RNAi Line, Animal Number and, in some cases, window (to accommodate larger samples that require multiple image stacks)
Collection dates:
October 2012 - April 2017
Subjects (LCSH)
Subjects (MeSH)
Subjects
Divisions
University of Nottingham, UK Campus::Faculty of Medicine and Health Sciences::School of Life Sciences
Data type
Image files
Funders
Grant Number
C36430, A12891
Data collection method
Live imaging was performed with either a Leica SP2 inverted confocal microscope equipped with a × 40/1.25 NA oil objective with PL APO correction, a Zeiss LSM880 inverted confocal microscope equipped with a x 40/ 1.30 NA oil Ph3 M27 objective or a Zeiss LSM5 Exciter AxioObserver equipped with an EC Plan-NeoFluar × 40/1.30 oil lens. Z-series were acquired using 1 μm z-sectioning.
Resource languages
English
Publisher
University of Nottingham
Date Issued
May 1, 2019
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Name
34689 (III).zip
Size
94.85 MB
Format
Unknown
Checksum (MD5)
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Name
readme.txt
Size
1.68 KB
Format
Text
Checksum (MD5)
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