Aging represses lung tumorigenesis and alters tumor suppression.

Most cancers are diagnosed in persons over the age of sixty, but little is known about how age impacts tumorigenesis. While aging is accompanied by mutation accumulation - widely understood to contribute to cancer risk - it is also associated with numerous other cellular and molecular changes likely to impact tumorigenesis. Moreover, cancer incidence decreases in the oldest part of the population, suggesting that very old age may reduce carcinogenesis. Here we show that aging represses tumor initiation and growth in genetically engineered mouse models of human lung cancer. Moreover, aging dampens the impact of inactivating many, but not all, tumor suppressor genes with the impact of inactivating PTEN, a negative regulator of the PI3K/AKT pathway, weakened to a disproportionate extent. Single-cell transcriptomic analysis revealed that neoplastic cells from tumors in old mice retain many age-related transcriptomic changes, showing that age has an enduring impact that persists through oncogenic transformation. Furthermore, the consequences of PTEN inactivation were strikingly age-dependent, with PTEN deficiency reducing signatures of aging in cancer cells and the tumor microenvironment. Our findings suggest that the relationship between age and lung cancer incidence may reflect an integration of the competing effects of driver mutation accumulation and tumor suppressive effects of aging.

Enrichment of Rare Variants of Hemophagocytic Lymphohistiocytosis Genes in Systemic Juvenile Idiopathic Arthritis.

OBJECTIVE: To evaluate whether there is an enrichment of rare variants in familial hemophagocytic lymphohistiocytosis (HLH)-associated genes among patients with systemic juvenile idiopathic arthritis (sJIA) with or without macrophage activation syndrome (MAS). METHODS: Targeted sequencing of HLH genes (LYST, PRF1, RAB27A, STX11, STXBP2, UNC13D) was performed in sJIA subjects from an established cohort. Sequence data from control subjects were obtained in silico (dbGaP:phs000280.v8.p2). Rare variant association testing (RVT) was performed with sequence kernel association test (SKAT) package. Significance was defined as p < 0.05 after 100,000 permutations. RESULTS: Sequencing data from 524 sJIA cases were jointly called and harmonized with exome-derived target data from 3000 controls. Quality control operations produced a set of 480 cases and 2924 ancestrally-matched control subjects. RVT of cases and controls revealed a significant association with rare protein-altering variants (minor allele frequency [MAF] < 0.01) of STXBP2 (p = 0.020), and ultra-rare variants (MAF < 0.001) of STXBP2 (p = 0.006) and UNC13D (p = 0.046). A sub-analysis of 32 cases with known MAS and 90 without revealed a significant difference in the distribution of rare UNC13D variants (p = 0.0047) between the groups. Additionally, sJIA patients more often carried ≥ 2 HLH variants than did controls (p = 0.007), driven largely by digenic combinations involving LYST. CONCLUSION: We identified an enrichment of rare HLH variants in sJIA patients compared with controls, driven by STXBP2 and UNC13D. Biallelic variation in HLH genes was associated with sJIA, driven by LYST. Only UNC13D displayed enrichment in patients with MAS. This suggests that HLH variants may contribute to the pathophysiology of sJIA, even without MAS.

High-Throughput Identification, Modeling, and Analysis of Cancer Driver Genes In Vivo.

The vast number of genomic and molecular alterations in cancer pose a substantial challenge to uncovering the mechanisms of tumorigenesis and identifying therapeutic targets. High-throughput functional genomic methods in genetically engineered mouse models allow for rapid and systematic investigation of cancer driver genes. In this review, we discuss the basic concepts and tools for multiplexed investigation of functionally important cancer genes in vivo using autochthonous cancer models. Furthermore, we highlight emerging technical advances in the field, potential opportunities for future investigation, and outline a vision for integrating multiplexed genetic perturbations with detailed molecular analyses to advance our understanding of the genetic and molecular basis of cancer.

Multiplexed screens identify RAS paralogues HRAS and NRAS as suppressors of KRAS-driven lung cancer growth.

Oncogenic KRAS mutations occur in approximately 30% of lung adenocarcinoma. Despite several decades of effort, oncogenic KRAS-driven lung cancer remains difficult to treat, and our understanding of the regulators of RAS signalling is incomplete. Here to uncover the impact of diverse KRAS-interacting proteins on lung cancer growth, we combined multiplexed somatic CRISPR/Cas9-based genome editing in genetically engineered mouse models with tumour barcoding and high-throughput barcode sequencing. Through a series of CRISPR/Cas9 screens in autochthonous lung cancer models, we show that HRAS and NRAS are suppressors of KRASG12D-driven tumour growth in vivo and confirm these effects in oncogenic KRAS-driven human lung cancer cell lines. Mechanistically, RAS paralogues interact with oncogenic KRAS, suppress KRAS-KRAS interactions, and reduce downstream ERK signalling. Furthermore, HRAS and NRAS mutations identified in oncogenic KRAS-driven human tumours partially abolished this effect. By comparing the tumour-suppressive effects of HRAS and NRAS in oncogenic KRAS- and oncogenic BRAF-driven lung cancer models, we confirm that RAS paralogues are specific suppressors of KRAS-driven lung cancer in vivo. Our study outlines a technological avenue to uncover positive and negative regulators of oncogenic KRAS-driven cancer in a multiplexed manner in vivo and highlights the role RAS paralogue imbalance in oncogenic KRAS-driven lung cancer.

A Functional Taxonomy of Tumor Suppression in Oncogenic KRAS-Driven Lung Cancer.

Cancer genotyping has identified a large number of putative tumor suppressor genes. Carcinogenesis is a multistep process, but the importance and specific roles of many of these genes during tumor initiation, growth, and progression remain unknown. Here we use a multiplexed mouse model of oncogenic KRAS-driven lung cancer to quantify the impact of 48 known and putative tumor suppressor genes on diverse aspects of carcinogenesis at an unprecedented scale and resolution. We uncover many previously understudied functional tumor suppressors that constrain cancer in vivo. Inactivation of some genes substantially increased growth, whereas the inactivation of others increases tumor initiation and/or the emergence of exceptionally large tumors. These functional in vivo analyses revealed an unexpectedly complex landscape of tumor suppression that has implications for understanding cancer evolution, interpreting clinical cancer genome sequencing data, and directing approaches to limit tumor initiation and progression. SIGNIFICANCE: Our high-throughput and high-resolution analysis of tumor suppression uncovered novel genetic determinants of oncogenic KRAS-driven lung cancer initiation, overall growth, and exceptional growth. This taxonomy is consistent with changing constraints during the life history of cancer and highlights the value of quantitative in vivo genetic analyses in autochthonous cancer models.This article is highlighted in the In This Issue feature, p. 1601.