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}
Xue Xiao, Wei Wang, Peng Bai, Ying Chen, Zhengwen Qin, Tong Cheng, Xing Li, John P. Pineda, Panying Shi, Xiaonan Wang, Jianhong Wang, Lian Xu, Xuemei Gao, Huixian Zheng, Lulu Yang, Wenyi Lin, Wenbin Huang, Rulong Shen, Changjun Yue, Huixiong Xu, Felipe Batalini, Yang Liu, Ning Zhou, Yaoyao Zhang, Hanmin Liu
<p>Cervical cancer remains a significant global public health issue due to its high incidence and mortality. Current clinical guidelines recommend screening for high-risk human papillomavirus (hrHPV)-DNA alongside a Thinprep cytologic test (TCT) before further medical evaluation [<span>1</span>]. The hrHPV-DNA test detects 14 high-risk HPV genotypes including the predominant hrHPV16/18, which can cause cervical abnormalities that may progress to cancer if untreated. TCT is paired with the hrHPV-DNA test to pathologically classify cervical specimens into categories based on increasing malignancy risks. Despite the high sensitivities, both tests have high false positive rates which lead to unnecessary colposcopy while HPV is cleared naturally in most women without progressing into lesions. To reduce overdiagnosis and overtreatment, several DNA methylation detections [<span>2, 3</span>] have been developed for triaging the malignancy risk of hrHPV-positive cervical lesions, but have yet to become clinically available. Here, we proposed an epigenetic biomarker panel based on imprinting alterations as a high-performance triage method to improve cervical cancer risk assessment accuracy in hrHPV-positive women.</p><p>Loss of imprinting (LOI), an early molecular event in carcinogenesis, is an epigenetic phenomenon when a normally silenced allele of the imprinted gene is activated and expressed [<span>4</span>]. Using the quantitative chromogenic imprinted gene in-situ hybridization (QCIGISH) to visualize and quantify imprinted genes’ transcription sites in the nuclei, early epigenetic changes through LOI have been shown as effective biomarkers for detecting multiple malignancies [<span>5</span>]. In the present study, we first screened imprinted gene candidates using resected cervical tissue samples and subsequently developed a cancer risk stratification method based on cytological specimens diagnosed by colposcopy and biopsy (Supplementary Figure S1). The diagnostic model was blindly validated in prospectively collected cytological samples by comparing the QCIGISH results with colposcopy biopsy pathology. Full study protocols are detailed in the Supplementary file.</p><p>To identify the most efficient biomarker panel for differentiating malignancy in cervical lesions, we evaluated four candidate imprinted genes based on prior research evidence and targeted literature review of female cancers: guanine nucleotide-binding protein, alpha-stimulating complex locus (<i>GNAS</i>) related to thyroid cancer, osteosarcoma, and skin cancer [<span>6</span>], small nuclear ribonucleoprotein polypeptide N (<i>SNRPN</i>) associated with seminoma, yolk sac tumor, and acute myeloid leukemia [<span>7</span>], histocompatibility minor 13 (<i>HM13</i>) linked to breast cancer [<span>8</span>], and small nuclear ribonucleoprotein 13 (<i>SNU13</i>) involved with lung cancer [<span>9</span>]. QCIGISH was applied to 79 formalin-fixed paraffin-embedded samples comprised of 30 b
{"title":"Genomic imprinting biomarkers for cervical cancer risk stratification","authors":"Xue Xiao, Wei Wang, Peng Bai, Ying Chen, Zhengwen Qin, Tong Cheng, Xing Li, John P. Pineda, Panying Shi, Xiaonan Wang, Jianhong Wang, Lian Xu, Xuemei Gao, Huixian Zheng, Lulu Yang, Wenyi Lin, Wenbin Huang, Rulong Shen, Changjun Yue, Huixiong Xu, Felipe Batalini, Yang Liu, Ning Zhou, Yaoyao Zhang, Hanmin Liu","doi":"10.1002/cac2.12617","DOIUrl":"10.1002/cac2.12617","url":null,"abstract":"<p>Cervical cancer remains a significant global public health issue due to its high incidence and mortality. Current clinical guidelines recommend screening for high-risk human papillomavirus (hrHPV)-DNA alongside a Thinprep cytologic test (TCT) before further medical evaluation [<span>1</span>]. The hrHPV-DNA test detects 14 high-risk HPV genotypes including the predominant hrHPV16/18, which can cause cervical abnormalities that may progress to cancer if untreated. TCT is paired with the hrHPV-DNA test to pathologically classify cervical specimens into categories based on increasing malignancy risks. Despite the high sensitivities, both tests have high false positive rates which lead to unnecessary colposcopy while HPV is cleared naturally in most women without progressing into lesions. To reduce overdiagnosis and overtreatment, several DNA methylation detections [<span>2, 3</span>] have been developed for triaging the malignancy risk of hrHPV-positive cervical lesions, but have yet to become clinically available. Here, we proposed an epigenetic biomarker panel based on imprinting alterations as a high-performance triage method to improve cervical cancer risk assessment accuracy in hrHPV-positive women.</p><p>Loss of imprinting (LOI), an early molecular event in carcinogenesis, is an epigenetic phenomenon when a normally silenced allele of the imprinted gene is activated and expressed [<span>4</span>]. Using the quantitative chromogenic imprinted gene in-situ hybridization (QCIGISH) to visualize and quantify imprinted genes’ transcription sites in the nuclei, early epigenetic changes through LOI have been shown as effective biomarkers for detecting multiple malignancies [<span>5</span>]. In the present study, we first screened imprinted gene candidates using resected cervical tissue samples and subsequently developed a cancer risk stratification method based on cytological specimens diagnosed by colposcopy and biopsy (Supplementary Figure S1). The diagnostic model was blindly validated in prospectively collected cytological samples by comparing the QCIGISH results with colposcopy biopsy pathology. Full study protocols are detailed in the Supplementary file.</p><p>To identify the most efficient biomarker panel for differentiating malignancy in cervical lesions, we evaluated four candidate imprinted genes based on prior research evidence and targeted literature review of female cancers: guanine nucleotide-binding protein, alpha-stimulating complex locus (<i>GNAS</i>) related to thyroid cancer, osteosarcoma, and skin cancer [<span>6</span>], small nuclear ribonucleoprotein polypeptide N (<i>SNRPN</i>) associated with seminoma, yolk sac tumor, and acute myeloid leukemia [<span>7</span>], histocompatibility minor 13 (<i>HM13</i>) linked to breast cancer [<span>8</span>], and small nuclear ribonucleoprotein 13 (<i>SNU13</i>) involved with lung cancer [<span>9</span>]. QCIGISH was applied to 79 formalin-fixed paraffin-embedded samples comprised of 30 b","PeriodicalId":9495,"journal":{"name":"Cancer Communications","volume":"44 12","pages":"1385-1390"},"PeriodicalIF":20.1,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11666962/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399494","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}