Clonal dynamics following p53 loss of heterozygosity in Kras-driven cancers

Abstract

Although it has become increasingly clear that cancers display extensive cellular heterogeneity, the spatial growth dynamics of genetically distinct clones within developing solid tumours remain poorly understood. Here we leverage mosaic analysis with double markers (MADM) to trace subclonal populations retaining or lacking p53 within oncogenic Kras-initiated lung and pancreatic tumours. In both models, p53 constrains progression to advanced adenocarcinomas. Comparison of lineage-related p53 knockout and wild-type clones reveals a minor role of p53 in suppressing cell expansion in lung adenomas. In contrast, p53 loss promotes both the initiation and expansion of low-grade pancreatic intraepithelial neoplasia (PanINs), likely through differential expression of the p53 regulator p19ARF. Strikingly, lineage-related cells are often dispersed in lung adenomas and PanINs, contrasting with more contiguous growth of advanced subclones. Together, these results support cancer type-specific suppressive roles of p53 in early tumour progression and offer insights into clonal growth patterns during tumour development.

Enhancer Reprogramming Promotes Pancreatic Cancer Metastasis

“…However, our data indicates that FOXA1-mediated enhancer reprogramming occurs independently of p53 LOH. Since p53 has been proposed to regulate epigenetic states (Levine and Greenbaum, 2012) and p53 LOH has been shown as an important driver of PDA progression (Muzumdar et al, 2016), it is still possible that tumor cells with p53 LOH become more permissive to epigenetic alterations in certain contexts, such as stromal cues or metabolic challenges. Nonetheless, this requires further investigation to determine whether cooperativity exists between enhancer reprogramming and p53 LOH in PDA progression and metastasis in vivo.…”

Endocrine-exocrine signaling drives obesity-associated pancreatic ductal adenocarcinoma

“…We postulated that obesity might induce DNA damage in the setting of enhanced oxidative stress (Usman and Volpi, 2018) and that tumor progression in KCO mice would depend on additional driver gene mutations beyond oncogenic Kras. Precedent for this hypothesis is provided by acceleration of oncogenic Kras-induced pancreatic tumor development in mice following inactivating mutations in Trp53, Cdkn2a, and Smad4 (Bardeesy et al, 2006a;Bardeesy et al, 2006b;Hingorani et al, 2005;Muzumdar et al, 2016) -the hallmark recurrently mutated tumor suppressor genes (TSGs) in human PDAC (Bailey et al, 2016;The Cancer Genome Atlas Research Network, 2017)). In further support, survival of KCO mice was comparable to what we previously observed (Muzumdar et al, 2016) in KPC mice (Pdx1-Cre;…”

“…Mice were housed in a specific-pathogen free facility, kept at room temperature with standard day-night cycles, and maintained on a mixed background unless otherwise specified. MADM11-GT,p53 WT /MADM11-TG-p53 KO (MADM-p53), were generated as described previously (Muzumdar et al, 2016). Mice were genotyped using tail DNA by the HotShot method.…”

“…Genotyping primers and protocols have been previously reported (Ellett et al, 2009;Lavine et al, 2015;Muzumdar et al, 2016) or are available online (http://www.jax.org).…”

Advances and perspectives in tissue clearing using CLARITY

“…CLARITY-based protocols have been used with little, e.g. lower acrylamide concentrations, or no modifications to clear most other organs such as lever (Lee et al, 2014;Font-Burgada et al, 2015), kidney (Yang et al, 2014;Lee et al, 2014;Unnersjö-Jess et al, 2015), pancreas (Lee et al, 2014;Muzumdar et al, 2016), adrenal gland (Epp et al, 2015), spleen (Epp et al, 2015;Kie↵er et al, 2017), lymphoid tissues (Kie↵er et al, 2017), intestine (Yang et al, 2014;Lee et al, 2014;Epp et al, 2015;Neckel et al, 2016;Kie↵er et al, 2017), testes (Epp et al, 2015;Frétaud et al, 2017), ovaries (Feng et al, 2017), and lung tissue (Yang et al, 2014;Lee et al, 2014;Epp et al, 2015;Saboor et al, 2016). However, given that organs have di↵erent densities and ratios of connective tissue, lipids, and protein the clearing times and the average RI of the tissue-hydrogel vary (table 2).…”