We hypothesize that selection during dog domestication targeted CNVs associated with hypersociability.
ObjectivesJuvenile idiopathic arthritis (JIA) is a heterogeneous group of conditions unified by the presence of chronic childhood arthritis without an identifiable cause. Systemic JIA (sJIA) is a rare form of JIA characterised by systemic inflammation. sJIA is distinguished from other forms of JIA by unique clinical features and treatment responses that are similar to autoinflammatory diseases. However, approximately half of children with sJIA develop destructive, long-standing arthritis that appears similar to other forms of JIA. Using genomic approaches, we sought to gain novel insights into the pathophysiology of sJIA and its relationship with other forms of JIA.MethodsWe performed a genome-wide association study of 770 children with sJIA collected in nine countries by the International Childhood Arthritis Genetics Consortium. Single nucleotide polymorphisms were tested for association with sJIA. Weighted genetic risk scores were used to compare the genetic architecture of sJIA with other JIA subtypes.ResultsThe major histocompatibility complex locus and a locus on chromosome 1 each showed association with sJIA exceeding the threshold for genome-wide significance, while 23 other novel loci were suggestive of association with sJIA. Using a combination of genetic and statistical approaches, we found no evidence of shared genetic architecture between sJIA and other common JIA subtypes.ConclusionsThe lack of shared genetic risk factors between sJIA and other JIA subtypes supports the hypothesis that sJIA is a unique disease process and argues for a different classification framework. Research to improve sJIA therapy should target its unique genetics and specific pathophysiological pathways.
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
In our study, IL1RN was the only candidate locus associated with systemic JIA. The implicated SNPs are among the strongest known determinants of IL1RN and interleukin-1 receptor antagonist levels, linking low expression with increased systemic JIA risk. Homozygous high expression alleles predicted nonresponsiveness to anakinra therapy, making them ideal candidate biomarkers to guide systemic JIA treatment. This study is an important first step toward the personalized treatment of systemic JIA.
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 positive and negative regulators of RAS signaling is incomplete. To uncover the functional impact of diverse KRAS-interacting proteins on lung cancer growth in vivo, we used multiplexed somatic CRISPR/Cas9-based genome editing in genetically engineered mouse models with tumor barcoding and high-throughput barcode sequencing. Through a series of CRISPR/Cas9 screens in autochthonous lung tumors, we identified HRAS and NRAS as key suppressors of KRAS G12D -driven tumor growth in vivo and confirmed these effects in oncogenic KRAS-driven human lung cancer cell lines. Mechanistically, RAS paralogs interact with oncogenic KRAS, suppress KRAS-KRAS interactions, and reduce downstream ERK signaling. HRAS mutations identified in KRAS-driven human tumors partially abolished this effect. Comparison of the tumorsuppressive effects of HRAS and NRAS in KRAS-and BRAF-driven lung cancer models confirmed that RAS paralogs are specific suppressors of oncogenic 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 of RAS paralog imbalance in oncogenic KRAS-driven lung cancer.
Lung cancer is a lethal and genomically-complex disease. Structural genomics has largely advanced our knowledge of genomic alterations, yet the function of a majority of altered genes remains less clear. Previous in silico and in vitro functional genomics data often lead to contradictory conclusions on gene functions. Genetically-engineered mouse models are reliable approaches for in vivo functional analyses, but development of these models are lagging behind due to the throughput limit. To overcome this throughput limit, we developed tumor barcoding and ultradeep barcode sequencing (Tuba-seq) that precisely quantifies the growth metrics of hundreds of tumor genotypes, which is a huge leap forward. Through this approach, we have begun a journey to create a quantitative functional taxonomy of tumor suppression in oncogenic KRAS-driven lung cancer. For example, STAG2 and CDKN2C emerged as novel functional tumor suppressor genes in the lung, when they were often overlooked by computational analyses due to relatively low mutation prevalence. Interestingly, STK11 and PTEN, both playing an important role in tumor growth, exhibit distinct roles in tumor initiation. These findings suggest that structural genomics is not sufficient to predict cancer driver genes, and calls for closer investigation of tumor suppressor functions in specific tumorigenesis stages. Furthermore, the quantitative nature of our data has enabled systematic characterization of interactions between tumor suppressor genes. For instance, RNF43 exhibits different tumor suppression modes in the presence or absence of STK11 or TRP53, while TRP53 can play opposite roles in PTEN- and RB1-deficient tumors. In addition, Foggetti et al. (2021) reported that tumor suppressors can play opposite roles in the contexts of different oncogenes. Collectively, these findings suggest that cooccurring mutations shift the functional landscape of tumor suppressors even in the same pathological subtype of cancer. Given the genomic diversity of lung cancer patients, driver genes may change case by case. We are now investigating the molecular mechanisms underlying these tumor suppressors and their genetic interactions. Our findings underscore the necessity of determining the consequences of enormous combinations of genomic alterations in their natural environment, which is challenging but critical for understanding cancer evolution, interpreting clinical cancer genome sequencing data, and directing approaches to limit tumor initiation and progression. Citation Format: Hongchen Cai, Su Kit Chew, Chuan Li, Christopher W. Murray, Laura Andrejka, Jess D. Hebert, Min K. Tsai, Rui Tang, Nicholas W. Hughes, Emily G. Shuldiner, Emily L. Ashkin, Shi Ya C. Lee, Maryam Yousefi, Dmitri A. Petrov, Charles Swanton, Monte W. Winslow. A journey to deconvolute the multifaceted functions and context-dependency of cancer driver genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 827.
Oncogenic KRAS mutations occur in approximately 30% of human lung adenocarcinoma. Despite tremendous effort over the past several decades, oncogenic KRAS-driven lung cancer remains difficult to treat, and our understanding of the positive and negative regulators of RAS signaling is incomplete. To uncover and corroborate the functional impact of diverse KRAS-interacting proteins on lung cancer growth in vivo, we integrate somatic CRISPR/Cas9-based genome editing in genetically engineered mouse models with tumor barcoding and high-throughput barcode sequencing (Tuba-seq). Through a series of in vivo CRISPR/Cas9 screens, we identified HRAS and NRAS as key suppressors of KRASG12D-driven lung tumor growth in vivo and confirmed these effects in oncogenic KRAS-driven human lung cancer cell lines. Mechanistically, we find that these RAS paralogs interact with oncogenic KRASG12D, suppress KRASG12D-KRASG12D interaction, and reduce downstream ERK signaling. Patient-derived mutations HRAST50M and HRASR123C partially abolished this effect. Comparison of the tumor-suppressive effects of HRAS and NRAS in KRASG12D- and BRAFV600E-driven lung cancer models confirmed that these RAS paralogs are specific suppressors of oncogenic KRAS-driven lung cancer in vivo. Our study outlines a technological avenue to specifically uncover positive and negative regulators of oncogenic KRAS-driven cancer in a multiplexed manner and highlights the role of RAS paralog imbalance in oncogenic KRAS-driven cancers.
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