Single allele loss-of-function mutations select and sculpt conditional cooperative networks in breast cancer

Abstract

The most common events in breast cancer (BC) involve chromosome arm losses and gains. Here we describe identification of 1089 gene-centric common insertion sites (gCIS) from transposon-based screens in 8 mouse models of BC. Some gCIS are driver-specific, others driver non-specific, and still others associated with tumor histology. Processes affected by driver-specific and histology-specific mutations include well-known cancer pathways. Driver non-specific gCIS target the Mediator complex, Ca++ signaling, Cyclin D turnover, RNA-metabolism among other processes. Most gCIS show single allele disruption and many map to genomic regions showing high-frequency hemizygous loss in human BC. Two gCIS, Nf1 and Trps1, show synthetic haploinsufficient tumor suppressor activity. Many gCIS act on the same pathway responsible for tumor initiation, thereby selecting and sculpting just enough and just right signaling. These data highlight ~1000 genes with predicted conditional haploinsufficient tumor suppressor function and the potential to promote chromosome arm loss in BC.

In vivo CRISPR screens reveal SCAF1 and USP15 as novel drivers of pancreatic cancer

“…The copyright holder for this preprint this version posted March 13, 2022. ; https://doi.org/10.1101/2022.03.13.484174 doi: bioRxiv preprint functions as a haploinsufficient tumor suppressor in pancreas cancer. The growing list of haploinsufficient cancer driver genes identified in genetic screens 11,[51][52][53][54][55][56] raises the provocative question whether the lack of comprehensive screening within innate tumor microenvironment obstructed our capabilities of identifying many of these haploinsufficient cancer driver genes. This is in line with recent findings from Martin et al, showing that the adaptive immune system is a major driver of selection for tumor suppressor gene inactivation 57 .…”

“…Importantly, our data indicates that USP15 10 functions as a haploinsufficient tumor suppressor in pancreas cancer. The growing list of haploinsufficient cancer driver genes identified in genetic screens 11,[51][52][53][54][55][56] raises the provocative question whether the lack of comprehensive screening within innate tumor microenvironment obstructed our capabilities of identifying many of these haploinsufficient cancer driver genes. This is in line with recent findings from Martin et al,…”

In vivo CRISPR screens reveal SCAF1 and USP15 as novel drivers of pancreatic cancer

“…Importantly, our data indicates that USP15 functions in a haploinsufficient manner, which is seen in a clinically relevant portion of ~25% of PDAC patients. The growing list of haploinsufficient cancer driver genes identified in genetic in vivo screens 11,[50][51][52][53][54][55] raises the provocative question whether the lack of comprehensive screening within innate tumor microenvironment obstructed our capabilities of identifying many of these haploinsufficient cancer driver genes. This is in line with recent findings from Martin et al, showing that the adaptive immune system is a major driver of selection for tumor suppressor gene inactivation 56 .…”

In vivofunctional genomics identifies essentiality of potassium homeostasis in medulloblastoma

“…Finally, purified PCR products were sent for 454 parallel sequencing at the Ontario Institute for Cancer Research. Genomic DNA libraries from LP tumours were prepared as sequenced as previously described (Schachter et al, 2021). Three libraries were prepared to identify different types of LP insertion events.…”

“…We removed insertions mapping to non-standard or donor chromosomes, those with single read support, or those detected in Ptch1 +/- control mice. A dynamic filter was used to categorize insertions as clonal or subclonal, as previously described (Brett et al, 2011; Schachter et al, 2021). For each library, three thresholds were calculated using the insertion data: (i) >95th percentile of reads under the negative binomial distribution fit to the number of sites with 1–3 reads, (ii) 1% of the read count of the most abundant insertion site, (iii) 0.1% of the total read number.…”