Yichuan Liu, Hui-Qi Qu, Xiao Chang, Frank D Mentch, Haijun Qiu, Kenny Nguyen, Kayleigh Ostberg, Tiancheng Wang, Joseph Glessner, Hakon Hakonarson
<p>Childhood solid tumors represent a significant public health challenge worldwide, with approximately 15,000 new cases annually in the United States and an estimated 300,000 globally. Down syndrome (DS), a genetic disorder characterized by an extra full or partial copy of chromosome 21, results in distinctive developmental and physical features. Notably, individuals with DS exhibit a remarkable resilience against solid tumors compared to the general population, with an overall standardized incidence ratio (SIR) of 0.45, despite their increased susceptibility to hematologic malignancies [<span>1</span>]. This paradoxical observation has spurred extensive research aimed at uncovering the biological underpinnings of this natural resistance to solid cancers. Current theories suggest that the overexpression of specific genes on chromosome 21 may confer protective benefits (e.g. <i>RCAN1</i> contributes to antiangiogenic effects), and alterations in immune system function may enhance apoptosis and DNA repair pathways in individuals with trisomy 21 DS [<span>2</span>]. The well-established epigenetic effects of trisomy 21, which influence the entire genome, are another potential contributor to the reduced risk of solid tumors [<span>3</span>]. Nonetheless, these hypotheses face significant challenges, such as the potential oversimplification of complex genetic interactions and the lack of comprehensive genome-wide analyses. This study seeks to critically evaluate the correlations between genomic variants and cancer clinical phenotypes in patients with DS, and proposes directions for future research into the genetic and molecular mechanisms that confer cancer resistance in DS, potentially transforming our understanding and treatment of pediatric cancers.</p><p>We conducted an innovative unbiased data-driven analysis in 2,452 whole-genome sequencing (WGS) samples with both DS individuals (<i>n</i> = 635) and pediatric oncology cases (<i>n</i> = 280) within the Gabriella Miller Kids First program project (https://kidsfirstdrc.org/) housed at the Children's Hospital of Philadelphia (Supplementary Figure S1). Additionally, 284 RNA sequencing samples from human peripheral blood mononuclear cells (PBMCs), a subset of WGS samples, were also analyzed, offering unprecedented insights into the complex interplay of genetic and immunological factors influencing cancer resistance.</p><p>The importance of each variant was calculated using deep learning algorithms, and their corresponding weights to DS cancer were generated based on linear algebra models as described in the Supplementary Materials and Methods. There were 2,523 unique cancer protective variants identified based on deep learning algorithms combined with linear algebra models in exonic, intronic, non-coding RNA and 5’untranslated region (5’UTR) regions. The prevalence for cancer protective variants in the DS cancer group (89.2%) is significantly higher compared to non-DS cancer individuals (58.1%) (<i>P
{"title":"Deciphering protective genomic factors of tumor development in pediatric Down syndrome via deep learning approach to whole genome and RNA sequencing","authors":"Yichuan Liu, Hui-Qi Qu, Xiao Chang, Frank D Mentch, Haijun Qiu, Kenny Nguyen, Kayleigh Ostberg, Tiancheng Wang, Joseph Glessner, Hakon Hakonarson","doi":"10.1002/cac2.12612","DOIUrl":"10.1002/cac2.12612","url":null,"abstract":"<p>Childhood solid tumors represent a significant public health challenge worldwide, with approximately 15,000 new cases annually in the United States and an estimated 300,000 globally. Down syndrome (DS), a genetic disorder characterized by an extra full or partial copy of chromosome 21, results in distinctive developmental and physical features. Notably, individuals with DS exhibit a remarkable resilience against solid tumors compared to the general population, with an overall standardized incidence ratio (SIR) of 0.45, despite their increased susceptibility to hematologic malignancies [<span>1</span>]. This paradoxical observation has spurred extensive research aimed at uncovering the biological underpinnings of this natural resistance to solid cancers. Current theories suggest that the overexpression of specific genes on chromosome 21 may confer protective benefits (e.g. <i>RCAN1</i> contributes to antiangiogenic effects), and alterations in immune system function may enhance apoptosis and DNA repair pathways in individuals with trisomy 21 DS [<span>2</span>]. The well-established epigenetic effects of trisomy 21, which influence the entire genome, are another potential contributor to the reduced risk of solid tumors [<span>3</span>]. Nonetheless, these hypotheses face significant challenges, such as the potential oversimplification of complex genetic interactions and the lack of comprehensive genome-wide analyses. This study seeks to critically evaluate the correlations between genomic variants and cancer clinical phenotypes in patients with DS, and proposes directions for future research into the genetic and molecular mechanisms that confer cancer resistance in DS, potentially transforming our understanding and treatment of pediatric cancers.</p><p>We conducted an innovative unbiased data-driven analysis in 2,452 whole-genome sequencing (WGS) samples with both DS individuals (<i>n</i> = 635) and pediatric oncology cases (<i>n</i> = 280) within the Gabriella Miller Kids First program project (https://kidsfirstdrc.org/) housed at the Children's Hospital of Philadelphia (Supplementary Figure S1). Additionally, 284 RNA sequencing samples from human peripheral blood mononuclear cells (PBMCs), a subset of WGS samples, were also analyzed, offering unprecedented insights into the complex interplay of genetic and immunological factors influencing cancer resistance.</p><p>The importance of each variant was calculated using deep learning algorithms, and their corresponding weights to DS cancer were generated based on linear algebra models as described in the Supplementary Materials and Methods. There were 2,523 unique cancer protective variants identified based on deep learning algorithms combined with linear algebra models in exonic, intronic, non-coding RNA and 5’untranslated region (5’UTR) regions. The prevalence for cancer protective variants in the DS cancer group (89.2%) is significantly higher compared to non-DS cancer individuals (58.1%) (<i>P","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 11","pages":"1374-1378"},"PeriodicalIF":20.1,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cac2.12612","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}