Common Copy Number Variations Research Articles

Trauma plays an important role in acral melanoma: A retrospective study of 303 patients.

Acral melanoma (AM) is the most common subtype of malignant melanoma in China, with a very poor prognosis. Despite the frequent reporting of trauma events in AM cases, the precise etiology of AM remains elusive. A retrospective analysis was conducted on a cohort of 303 AM patients at Nanjing Drum Tower Hospital. The patients were categorized into four distinct groups based on different patterns of disease onset: trauma type (Type 1), pigmented nevus type (Type 2), pigmented nevi with trauma (Type 3), and pigmented nevi with natural ulceration (Type 4). Differences in clinicopathological features, genetic alterations, and tumor immune microenvironment (TIME) were analyzed. Traumatic events accounted for a large proportion of AM cases. Among these categories, Type 1 patients displayed the least favorable pathological traits and an immunosuppressive TIME. Common copy number variations (CNVs) were observed in CCND1, RB1, FGF19, and IL7R, while CNVs in CDK4 and TERT occurred less frequently in patients with a history of trauma (Type 1 and Type 3). Type 2 patients exhibited the most favorable pathological characteristics and genetic profiles, and demonstrated the lowest incidence of CCDN1 and RB1 CNVs but had the highest CDK4 CNVs. In contrast, the pathological behavior of Type 3 and Type 4 patients was in between Type 1 and Type 2. And patients in Type 3 and Type 4 displayed a more favorable overall microenvironment. This study provides a clinical classification of Chinese AM based on diverse clinical onset characteristics and highlights the important role of trauma in AM. These findings may help to guide the diagnosis, treatment, and prognosis of AM patients. Further investigations are imperative to elucidate the underlying mechanisms governing the association between trauma and AM.

Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer

PurposeThe progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) in humans is highly variable. To better understand the relationship between them, we performed a multi-omic characterization of co-occurring DCIS and IBC lesions in a cohort of individuals.MethodsFormalin-fixed paraffin-embedded tissue samples from 50 patients with co-occurring DCIS and IBC lesions were subjected to DNA-seq and whole transcriptome RNA-seq. Paired DCIS and IBC multi-omics profiles were then interrogated for DNA mutations, gene expression profiles and pathway analysis.ResultsMost small variants and copy number variations were shared between co-occurring DCIS and IBC lesions, with IBC exhibiting on average a higher degree of additional mutations. However, 36% of co-occurring lesions shared no common mutations and 49% shared no common copy number variations. The most frequent genomic variants in both DCIS and IBC were PIK3CA, TP53, KMT2C, MAP3K1, GATA3 and SF3B1, with KMT2C being more frequent in DCIS and TP53 and MAP3K1 more frequent in IBC, though the numbers are too small for definitive conclusions. The most frequent copy number variations were seen in MCL1, CKSB1 and ERBB2. ERBB2 changes were not seen in IBC unless present in the corresponding DCIS. Transcriptional profiles were highly distinct between DCIS and IBC, with DCIS exhibiting upregulation of immune-related signatures, while IBC showed significant overexpression in genes and pathways associated with cell division and proliferation. Interestingly, DCIS and IBC exhibited significant differential expression of different components of extracellular matrix (ECM) formation and regulation, with DCIS showing overexpression of ECM-membrane interaction components while IBC showed upregulation of genes associated with fibronectin and invadopodia.ConclusionWhile most co-occurring DCIS and IBC were mutationally similar and suggestive of a common clonal progenitor, transcriptionally the lesions are highly distinct, with IBC expressing key pathways that facilitate invasion and proliferation. These results are suggestive of additional levels of regulation, epigenetic or other, that facilitate the acquisition of invasive properties during tumor evolution.

Abstract 2418: Copy number variation status of DNA in extracellular vesicles as novel biomarkers of high-grade serous ovarian carcinoma

Abstract Objective: Ovarian cancer is a gynecologic malignancy with a dismal prognosis due to the lack of accurate methods for early diagnosis methods and effective therapies. High-grade serous ovarian carcinoma (HGSOC) is the most common subtype and copy number variations (CNVs) are the dominant genomic events in HGSOC. Extracellular vesicles (EVs) circulate in body fluids and carry pathological genomic information positively. In this study, we evaluated the significance of EV-DNA as novel biomarkers for HGSOC patients. Methods: A total of 124 samples from HGSOC patients and cell lines were analyzed. EVs were isolated using the ultracentrifuge method. Comprehensive CNV statuses were analyzed by whole genome sequencing (WGS) and SNP array. In reference to the Ovarian Cancer Moon Shot database, 30 dominant CNVs in HGSOC were selected as dominant targets for analysis by droplet digital PCR (ddPCR). For predicting the response to PARP inhibitors, HGSOC patients who were treated with olaparib were collected, and DNA was extracted from FFPE tissue at the time of surgery. Results: NTA assays and cryo-electron microscopic analyses showed that the EVs were successfully isolated from all samples. Both WGS and SNP arrays detected correlating CNVs in cell-DNA and EV-DNA for cell lines, and in tissue-DNA and EV-DNA in ascites for patients. The CNV status was also accurately measured by ddPCR. Copy numbers of RAD51, BRCA1, AKT2, CCNE1, and MSH6 were significantly higher in malignant tissue than in benign tissue (p<0.0001, p<0.0001, p=0.0012, p=0.002. p=0.0328, respectively), and were detectable in EV-DNA from ascites. Additionally, the amount of DNA in malignant ascites was significantly higher than in benign ascites (p=0.016), and increased DNA in ascites itself suggested the presence of malignancy. Furthermore, EV-DNA more accurately reflected the CNV status of tumor DNA than cell-free DNA in ascites. Regarding the prediction of PARP inhibitor response, the CNV status in EV-DNA from patients who were treated with olaparib, a PARP inhibitor, demonstrated a marked difference between responders and non-responders. The equation calculated based on the combination of six genes (RB1, GABRA6, CTNNB1, MYC, RAD51, BARD1) could predict the response to olaparib (AUC: 1.0). The selected genes were validated in vitro using EV-DNA, and responders could be identified using the prediction equation calculated from CNV status of the selected genes in EV-DNA from ascites. Conclusion: CNV status of EV-DNA was correctly evaluated and can serve as novel diagnostic and prognostic biomarkers for HGSOC. Citation Format: Ryosuke Uekusa, Akira Yokoi, Kosuke Yoshida, Juntaro Matsuazki, Yusuke Yamamoto, Hiroaki Kajiyama. Copy number variation status of DNA in extracellular vesicles as novel biomarkers of high-grade serous ovarian carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2418.

Identification of a rare copy number polymorphic gain at 3q12.2 with candidate genes for familial endometriosis.

Endometriosis is a complex disease that affects 10-15% of women of reproductive age. Familial studies show that relatives of affected patients have a higher risk of developing the disease, implicating a genetic role for this disorder. Little is known about the impact of germline genomic copy number variant (CNV) polymorphisms on the heredity of the disease. In this study, we describe a rare CNV identified in two sisters with familial endometriosis, which contain genes that may increase the susceptibility and progression of this disease. We investigated the presence of CNVs from the endometrium and blood of the sisters with endometriosis and normal endometrium of five women as controls without the disease using array-CGH through the Agilent 2x400K platform. We excluded common CNVs that were present in the database of genomic variation. We identified, in both sisters, a rare CNV gain affecting 113kb at band 3q12.2 involving two candidate genes: ADGRG7 and TFG. The CNV gain was validated by qPCR. ADGRG7 is located at 3q12.2 and encodes a G protein-coupled receptor influencing the NF-kappaβ pathway. TFG participates in chromosomal translocations associated with hematologic tumor and soft tissue sarcomas, and is also involved in the NF-kappa B pathway. The CNV gain in this family provides a new candidate genetic marker for future familial endometriosis studies. Additional longitudinal studies of affected families must confirm any associations between this rare CNV gain and genes involved in the NF-kappaβ pathway in predisposition to endometriosis.

Dissecting 16p11.2 hemi-deletion to study sex-specific striatal phenotypes of neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) are polygenic in nature and copy number variants (CNVs) are ideal candidates to study the nature of this polygenic risk. The disruption of striatal circuits is considered a central mechanism in NDDs. The 16p11.2 hemi-deletion (16p11.2 del/+) is one of the most common CNVs associated with NDD, and 16p11.2 del/+ mice show sex-specific striatum-related behavioral phenotypes. However, the critical genes among the 27 genes in the 16p11.2 region that underlie these phenotypes remain unknown. Previously, we applied a novel strategy to identify candidate genes associated with the sex-specific phenotypes of 16p11.2 del/+ mice and highlighted three genes within the deleted region: thousand and one amino acid protein kinase 2 (Taok2), seizure-related 6 homolog-like 2 (Sez6l2), and major vault protein (Mvp). Using CRISPR/Cas9, we generated mice carrying null mutations inTaok2, Sez6l2, and Mvp (3 gene hemi-deletion (3g del/+)). Hemi-deletion of these 3 genes recapitulates sex-specific behavioral alterations in striatum-dependent behavioral tasks observed in 16p11.2 del/+ mice, specifically male-specific hyperactivity and impaired motivation for reward seeking. Moreover, RNAseq analysis revealed that 3g del/+ mice exhibit gene expression changes in the striatum similar to 16p11.2 del/+ mice exclusively in males. Subsequent analysis identified translation dysregulation and/or extracellular signal-regulated kinase signaling as plausible molecular mechanisms underlying male-specific, striatum-dependent behavioral alterations. Interestingly, ribosomal profiling supported the notion of translation dysregulation in both 3g del/+ and 16p11.2 del/+ male mice. However, mice carrying a 4-gene deletion (with an additional deletion of Mapk3) exhibited fewer phenotypic similarities with 16p11.2 del/+ mice. Together, the mutation of 3 genes within the 16p11.2 region phenocopies striatal sex-specific phenotypes of 16p11.2 del/+ mice. These results support the importance of a polygenic approach to study NDDs and underscore that the effects of the large genetic deletions result from complex interactions between multiple candidate genes.

Analysis of the Genetic Characteristics and Metastatic Pathways of G1 and G2 Colorectal Neuroendocrine Neoplasms.

G1 and G2 colorectal neuroendocrine neoplasms (NENs) are a group of rare and indolent diseases. We aimed to delineate their genetic characteristics and explore their metastatic mechanisms. We used next-generation sequencing technology for targeted sequencing for 54 patients with G1 and G2 colorectal NENs. We delineated their genetic features and compared the genetic characteristics between metastatic NENs and nonmetastatic NENs. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was utilized to explore their abnormal pathways and study their potential metastatic mechanisms. We collected 23 metastatic NENs and 31 nonmetastatic NENs. In the whole cohort, the common mutated genes were NCOR2, BRD4, MDC1, ARID1A, AXIN2, etc. The common copy number variations (CNVs) included amplification of HIST1H3D, amplification of HIST1H3E, and loss of PTEN. The KEGG enrichment analysis revealed that PI3K-Akt, MAPK, and Rap1 were the major abnormal pathways. There were significantly different genetic features between metastatic NENs and nonmetastatic NENs. The metastatic NENs shared only 47 (22.5%) mutated genes and 6 (13.3%) CNVs with nonmetastatic NENs. NCOR2, BRD4, CDKN1B, CYP3A5, and EIF1AX were the commonly mutated genes in metastatic NENs, while NCOR2, MDC1, AXIN2, PIK3C2G, and PTPRT were the commonly mutated genes in nonmetastatic NENs. Metastatic NENs presented a significantly higher proportion of abnormal pathways of cell senescence (56.5% vs 25.8%, P = .022) and lysine degradation (43.5% vs 16.1%, P = .027) than nonmetastatic NENs. G1 and G2 colorectal NENs are a group of heterogeneous diseases that might obtain an increased invasive ability through aberrant cell senescence and lysine degradation pathways.

CNVs Numbers Scoring System Was a Good Prognostic Risk Stratification for NDMM with Whole Genomic Mapping Array

Multiple myeloma (MM) is a genetically heterogeneous disease characterized by plasma cell clonal proliferation. Due to the potential complex cytogenetic abnormalities, the clinical progresses are heterogeneous. Thus, genome-wide identification of cytogenetic abnormalities is necessary given the limitations of traditional cytogenetic detecting methods. In this study, we utilized whole genomic mapping methods Cytoscan 750K array to analyze the genomic copy number variations (CNVs) of 611 Newly Diagnosed MM (NDMM) from The First Affiliated Hospital of Soochow University. The results showed that 95.3% of NDMM patients harbored the chromosome alterations including structural or numerical abnormalities, and most of them (67.3%) were accompanied both, including 23.7% with only structural abnormalities and 4.3% with only numerical abnormalities. The average number of CNV per patient was 9. In addition, we have identified 34 common CNV events with a frequency of ≥5%, 5 of which were high frequency (≥20%), including dup(1)(q21q44) (50.2%), del(14)(q22q32) (24.9%), del(1)(p31p12) (21.9%), del(13)(q12q22) (21.9%) and dup(19)(p13p12) (20.6%). Additionally, 6 CNVs with median frequency (≥15% and <20%) included dup(6)(p25p12) (16.9%), dup(9)(q21q34) (18.2%), del(16)(q12q24) (18.7%), del(8)(p23p12) (17.5%), dup(11)(q13q25) (15.7%) and del(22)(q11q12) (15.4%). And the other 23 CNVs were low frequency (<15%), including del(6)(q24q27) (14.6%), del(X)(p22q25) (14.1%), dup(X)(q28) (13.7%), dup(8) (q11q24) (12.6%), del(17)(p13p12) (11%) and so on. Most CNVs were closely related with clinical risk factors of MM such as LDH. Prognostic analysis based on the VRD treatment (n=353, the median follow-up was 22 months) showed that patients with only numerical abnormalities had a better progress free survival (PFS) outcome than that with structural abnormalities only or with both, although they seemed to have the similar overall survival (OS) rate. Furthermore, univariate analysis showed that 6 CNVs were correlated with poor PFS including 1q+, 4q-, 6q-, 12p-, 16q-, 17p-, and 5 CNVs were correlated with poor OS including 1p-, 4q-, 7p-, 12p-, 17p-. For the effect of counts of CNV events on MM prognosis, the receiver operating characteristic (ROC) curve analysis was performed to calculate the best cutoff, with a result of 23 CNV events. Therefore, MM patients were divided into 4 subgroups according to the counts of CNV they harbored, including high complexity group (CNVs≥23, n=32) which excluded patients with chromothripsis (more than 10 CNVs on the same chromosome) , median complexity group (10≤CNVs<23, n=168), low complexity group (1≤CNVs<10, n=324), and no CNVs group (n=73). The patients in high complexity group had the worst prognosis of PFS and OS (media PFS 18 months, media OS 29 months, P<0.001). As expected, some common high risk clinical factors such as 1q+, 17p-, DS III, ISS III, serum Ca++,β2-MG and plasma cells in BM were gradually increased among the group from low to high complexity, but decreased in the rate of complete remission (CR), which suggested that the risk classification system was reliable. Importantly, univariate and multivariate COX regression analysis showed that CNV≥23 was an independent prognostic risk factor affecting both PFS and OS in NDMM patients. Over all, we utilized a large MM cohort to identify recurrent and potential driver CNV events, and their correlation with prognosis. In addition, the count of CNVs in NDMM patient was creatively considered to be the basis for prognostic risk stratification.

Prenatal genetic diagnosis associated with fetal ventricular septal defect: an assessment based on chromosomal microarray analysis and exome sequencing

Objective: In the study, we investigated the genetic etiology of the ventricular septal defect (VSD) and comprehensively evaluated the diagnosis rate of prenatal chromosomal microarray analysis (CMA) and exome sequencing (ES) for VSD to provide evidence for genetic counseling.Methods: We carried out chromosomal microarray analysis (CMA) on 468 fetuses with VSD and exome sequencing (ES) on 51 fetuses.Results: In our cohort, 68 (14.5%) VSD fetuses received a genetic diagnosis, including 61 (13.03%, 61/468) cases with chromosomal abnormalities and seven (13.7%, 7/51) cases with gene sequence variants. The detection rate of total pathogenic and likely pathogenic gene variations in the non-isolated VSD group (61/335, 18.2%, 55 by QF-PCR/karyotype/CMA + 6 by ES) was significantly higher than that in the isolated VSD group (7/133, 5.3%, 6 by QF-PCR/karyotype/CMA + 1 by ES, p = 0.000). The most common copy number variation (CNV) was 22q11.2 microdeletion syndrome. Additionally, we found six previously unreported variants, which expanded the variation spectrum of VSD-related genes.Conclusion: In this study, CNVs and sequence variants were found in 13.03% and 13.7% of cases, respectively. ES can be recommended for fetuses with VSD without chromosome abnormalities and pathogenic CNVs, especially those that are combined with other ultrasound abnormalities.

Copy number variants landscape of multiple cancers and clinical applications based on NGS gene panel

Background The rapid adoption of next-generation sequencing in clinical oncology has enabled detection of molecular biomarkers which are shared between multiple tumour types. Intra-tumour heterogeneity is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the tumour-related copy number variants (CNVs), as key regulators of cancer origination, development, and progression, across various types of cancers are poorly understood. Methods We performed pan-cancer CNV analysis of cancer-related genes in 15 types of cancers including 1438 cancerous patients by next-generation sequencing using a commercially available pan-cancer panel (Onco PanScan™). Downstream bioinformatics analysis was performed in order to detect CNVs, cluster analysis of the found CNVs, and comparison of the frequency of gained CNVs between different types of cancers. LASSO analysis was used for identification of the most important CNVs. Results We also identified 523 CNVs among which 16 CNVs were common while 22 CNVs were caner-specific CNVs. Meanwhile, FAM58A was most commonly found in all studied cancers in this study and significant differences were found in FAM58A between female and male patients (p = .001). Common CNVs, such as FOXA1, NFKBIA, HEY1, MECOM, CHD7, AGO2, were mutated in 6.79%, 8.45%, 7.51%, 6.43%, 7.59%, 8.16% of tumours, while most of these mutations have proven roles in positive regulation of transcription from RNA polymerase II promoter. 11 features including sex, DIS3, EPHB1, ERBB2, FLT1, HCK, KEAP1, MYD88, PARP3, TBX3, and TOP2A were found as the key features for classification of cancers using CNVs. Conclusion The 16 common CNVs between cancers can be used to identify the target of pan-cancer drug design and targeted therapies. Additionally, 22 caner-specific CNVs can be used as unique diagnostic markers for each cancer type.

Copy number variations and their effect on the plasma proteome.

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation.

The search for biomarkers to predict radiosensitivity is important not only to individualize radiotherapy of cancer patients but also to forecast radiation exposure risks. The aim of this study was to devise a machine-learning method to stratify radiosensitivity and to investigate its association with genome-wide copy number variations (CNVs) as markers of sensitivity to ionizing radiation. We used the Affymetrix CytoScan HD microarrays to survey common CNVs in 129 fibroblast cell strains. Radiosensitivity was measured by the surviving fraction at 2 Gy (SF2). We applied a dynamic programming (DP) algorithm to create a piecewise (segmented) multivariate linear regression model predicting SF2 and to identify SF2 segment-related distinctive CNVs. SF2 ranged between 0.1384 and 0.4860 (mean=0.3273 The DP algorithm provided optimal segmentation by defining batches of radio-sensitive (RS), normally-sensitive (NS), and radio-resistant (RR) responders. The weighted mean relative errors (MRE) decreased with increasing the segments' number. The borders of the utmost segments have stabilized after partitioning SF2 into 5 subranges. The 5-segment model associated C-3SFBP marker with the most-RS and C-7IUVU marker with the most-RR cell strains. Both markers were mapped to gene regions (MCC and SLC1A6, respectively). In addition, C-3SFBP marker is also located in enhancer and multiple binding motifs. Moreover, for most CNVs significantly correlated with SF2, the radiosensitivity increased with the copy-number decrease.In conclusion, the DP-based piecewise multivariate linear regression method helps narrow the set of CNV markers from the whole radiosensitivity range to the smaller intervals of interest. Notably, SF2 partitioning not only improves the SF2 estimation but also provides distinctive markers. Ultimately, segment-related markers can be used, potentially with tissues' specific factors or other clinical data, to identify radiotherapy patients who are most RS and require reduced doses to avoid complications and the most RR eligible for dose escalation to improve outcomes.

The prognostic, immunological and single-cell features of m6A molecules in cervical cancer.

Cervical cancer (CC) is a growing health concern, emphasizing the need for reliable biomarkers in treatment selection and prognosis assessment. We analyzed gene expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA) for CC. Using Consensus Cluster Plus, we applied machine learning to cluster the CC cohort. Differential analysis was performed using the edge R package, while weighted correlation network analysis (WGCNA) was conducted using the WGCNA package. Single-sample gene set enrichment analysis (ssGSEA) evaluated immune cell abundance and computed the m6Ascore. Western blot and Q-PCR validated the m6A score in CC. Common copy number variation alterations were observed in the 23 m6A-related genes in CC, and their mutation frequency was summarized in a waterfall chart. Patients were grouped into two clusters, m6AclusterA and m6AclusterB. Improved clinical outcomes were observed in m6AclusterA, while m6AclusterB exhibited higher infiltration of 14 immune cell types. WGCNA analysis generated seven integrated modules, enriched in several biological processes. Prognostic differential genes were used to generate two gene clusters (gene Cluster I and gene Cluster II). Using ssGSEA, the m6Ascore was calculated for each patient. Lower m6Ascore correlated with better clinical outcomes, lower gene mutation frequency, and wild-type status. We investigated the sensitivity of high and low m6Ascore to immunotherapy, visualized through violin and UMAP diagrams showcasing crosstalk among single-cell clusters. The key gene PFKFB4 showed higher expression in CC cell lines and tumor tissues compared to normal cells and tissue. Our study elucidates the role of m6A molecules in predicting prognosis, biological features, and appropriate treatment for CC patients.

A Retrospective Genomic Landscape of 661 Young Adult Glioblastomas Diagnosed Using 2016 WHO Guidelines for Central Nervous System Tumors.

The authors present a cohort of 661 young adult glioblastomas diagnosed using 2016 WHO World Health Organization Classification of Tumors of the Central Nervous System, utilizing comprehensive genomic profiling (CGP) to explore their genomic landscape and assess their relationship to currently defined disease entities. This analysis explored variants with evidence of pathogenic function, common copy number variants (CNVs), and several novel fusion events not described in literature. Tumor mutational burden (TMB) mutational signatures, anatomic location, and tumor recurrence are further explored. Using data collected from CGP, unsupervised machine-learning techniques were leveraged to identify 10 genomic classes in previously assigned young adult glioblastomas. The authors relate these molecular classes to current World Health Organization guidelines and reference current literature to give therapeutic and prognostic descriptions where possible.

Low-coverage whole-genome sequencing for the effective diagnosis of early endometrial cancer: A pilot study

BackgroundEndometrial carcinoma (EC) is a disease that predominantly affects peri- and post-menopausal women and its incidence has continued to rise over recent years. Since the gold standard for EC diagnosis—hysteroscopic biopsy—is invasive, expensive, and unsuitable for wide use, there is an urgent need for a non-invasive method that exhibits both high sensitivity and high specificity. We therefore investigated the efficacy of UterCAD (the uterine exfoliated cell chromosomal aneuploidy detector) using tampon-collected specimens for the early detection of EC. MethodsWe prospectively recruited 51 patients with a history of abnormal bleeding and who planned to undergo hysteroscopic examination or hysterectomy between March 2020 and January 2021. Before executing an invasive procedure, a tampon was inserted into the patient's vagina for 6 h to collect exfoliated cells from the uterine cavity. Total DNA was extracted and low-coverage whole-genome sequencing was performed on an Illumina HiSeq X10, and we analyzed the differences in chromosomal status between women with EC and those bearing benign lesions using UterCAD. ResultsThirty EC patients—including 26 with endometrioid carcinoma (EEC) and four with uterine serous carcinoma (USC), as well as 14 benign cases—were enrolled in our final analysis. Copy-number variations (CNVs) were detected in tampon specimens collected from 26 EC patients (83.3%), including 21 with EEC (80.7%) and four with USC (100%). In the benign group, only one woman with focal atypical hyperplasia presented with a 10q chromosomal gain (P < 0.001). In the EC group, the most common CNVs were copy gains of 8q (N = 14), 2q (N = 4), and 10q (N = 3); and copy losses of 2q (N = 3) and 17p (N = 2). When we stratified by FIGO stage, the CNV rates in stages IA, IB, and II/III were 83.3% (15/18), 85.7% (6/7), and 80.0% (4/5), respectively. At the optimal cutoff (|Z| ≥ 2.3), UterCAD discriminated 83.3% of EC cases from benign cases, with a specificity of 92.9%. ConclusionsWe initially reported that UterCAD could serve as a non-invasive method for the early detection of EC, especially in the rare and aggressive USC subtype. The use of UterCAD might thus avoid unnecessary invasive procedures and thereby reduce the treatment burden on patients.

Genetic Spectrum of Congenital Anomalies of the Kidney and Urinary Tract in Chinese Newborn Genome Project

Congenital anomalies of the kidney and urinary tract (CAKUT) corresponds to a spectrum of defects. Several large-cohort studies have used high-throughput sequencing to investigate the genetic risk of CAKUT during antenatal, childhood, and adulthood period. However, our knowledge of newborns with CAKUT is limited. This multicenter retrospective cohort study explored the genetic spectrum of CAKUT in a Chinese neonatal cohort. Clinical data and whole exome sequencing (WES) data of 330 newborns clinically diagnosed with CAKUT were collected. WES data were analyzed for putative deleterious single nucleotide variants (SNVs) and potential disease-associated copy number variants (CNVs). In this study, pathogenic variants were identified in 61 newborns (18.5%, 61/330), including 35 patients (57.4%) with SNVs, 25 patients (41%) with CNVs, and 1 patient with both an SNV and a CNV. Genetic diagnosis rates were significantly higher in patients with extrarenal manifestations (P＜0.001), especially in those with cardiovascular malformations (P＜0.05). SNVs in genes related to syndromic disorders (CAKUT with extrarenal manifestations) were common, affecting 20 patients (57.1%, 20/35). KMT2D was the most common gene (5 patients) and 17q12 deletion was the most common CNV (4 patients). Patient 110 was detected with both a CNV (17q12 deletion) and an SNV (a homozygous variant of SLC25A13). Among the newborns with positive genetic results, 22 (36.1%, 22/61) patients may benefit from a molecular diagnosis and change in clinical management (including early multidisciplinary treatment, disease-specific follow-up, and familial genetic counseling). This study shows the heterogeneous genetic etiologies in a Chinese CAKUT neonatal cohort by using WES. Patients with CAKUT who have extrarenal manifestations are more likely to harbor genetic diagnoses. Kabuki syndrome and 17q12 deletion syndrome were the most common genetic findings. Approximately 36.1% of the patients may benefit from molecular diagnoses and a change in clinical management.

A CRISPR-engineered isogenic model of the 22q11.2 A-B syndromic deletion

22q11.2 deletion syndrome, associated with congenital and neuropsychiatric anomalies, is the most common copy number variant (CNV)-associated syndrome. Patient-derived, induced pluripotent stem cell (iPS) models have provided insight into this condition. However, patient-derived iPS cells may harbor underlying genetic heterogeneity that can confound analysis. Furthermore, almost all available models reflect the commonly-found ~ 3 Mb “A-D” deletion at this locus. The ~ 1.5 Mb “A-B” deletion, a variant of the 22q11.2 deletion which may lead to different syndromic features, and is much more frequently inherited than the A-D deletion, remains under-studied due to lack of relevant models. Here we leveraged a CRISPR-based strategy to engineer isogenic iPS models of the 22q11.2 “A-B” deletion. Differentiation to excitatory neurons with subsequent characterization by transcriptomics and cell surface proteomics identified deletion-associated alterations in proliferation and adhesion. To illustrate in vivo applications of this model, we further implanted neuronal progenitor cells into the cortex of neonatal mice and found potential alterations in neuronal maturation. The isogenic models generated here will provide a unique resource to study this less-common variant of the 22q11.2 microdeletion syndrome.

Prenatal diagnosis in the fetal hyperechogenic kidneys: assessment using chromosomal microarray analysis and exome sequencing

Fetal hyperechogenic kidneys (HEK) is etiologically a heterogeneous disorder. The aim of this study was to identify the genetic causes of HEK using prenatal chromosomal microarray analysis (CMA) and exome sequencing (ES). From June 2014 to September 2022, we identified 92 HEK fetuses detected by ultrasound. We reviewed and documented other ultrasound anomalies, microscopic and submicroscopic chromosomal abnormalities, and single gene disorders. We also analyzed the diagnostic yield of CMA and ES and the clinical impact the diagnosis had on pregnancy management. In our cohort, CMA detected 27 pathogenic copy number variations (CNVs) in 25 (25/92, 27.2%) fetuses, with the most common CNV being 17q12 microdeletion syndrome. Among the 26 fetuses who underwent further ES testing, we identified 7 pathogenic/likely pathogenic variants and 8 variants of uncertain significance in 9 genes in 12 fetuses. Four novel variants were first reported herein, expanding the mutational spectra for HEK-related genes. Following counseling, 52 families chose to continue the pregnancy, and in 23 of them, postnatal ultrasound showed no detectable renal abnormalities. Of these 23 cases, 15 had isolated HEK on prenatal ultrasound. Taken together, our study showed a high rate of detectable genetic etiologies in cases with fetal HEK at the levels of chromosomal (aneuploidy), sub-chromosomal (microdeletions/microduplications), and single gene (point mutations). Therefore, we speculate that combined CMA and ES testing for fetal HEK is feasible and has good clinical utility. When no genetic abnormalities are identified, the findings can be transient, especially in the isolated HEK group.

Cohort profile: SUPER-Finland – the Finnish study for hereditary mechanisms of psychotic disorders

PurposeSUPER-Finland is a large Finnish collection of psychosis cases. This cohort also represents the Finnish contribution to the Stanley Global Neuropsychiatric Genetics Initiative, which seeks to diversify genetic sample collection...

Chromosome 11q13 amplification correlates with poor response and prognosis to PD-1 blockade in unresectable hepatocellular carcinoma.

Little is known about molecular biomarkers that predict the response and prognosis in unresectable hepatocellular carcinoma (HCC) treated with programmed death (PD)-1 inhibitors. A total of 62 HCC patients who underwent next-generation sequencing were retrospectively included in our department for this study. Patients with unresectable disease were subjected to systemic therapy. PD-1 inhibitors intervention (PD-1Ab) group and nonPD-1Ab group included 20 and 13 patients, respectively. Primary resistance was defined as initial on-treatment progression or progression with an initial stable disease of less than 6 months. Chromosome 11q13 amplification (Amp11q13) was the most common copy number variation in our cohort. Fifteen (24.2%) patients harbored Amp11q13 in our dataset. Patients with Amp11q13 showed higher level of Des-γ-carboxy-prothrombin (DCP), tumor number and were more prone to be combined with portal vein tumor thrombosis (PVTT). In the PD-1Ab group, the proportion of progressive disease (PD) in patients with Amp11q13 was significantly higher than that in patients with nonAmp11q13 (100% vs 33.3%, P=0.03). In the nonPD-1Ab group, the proportion of PD in patients with Amp11q13 and nonAmp11q13 had no significant difference (0% vs 11.1%, P>0.99). In the PD-1Ab group, the median progression-free survival (PFS) was 1.5 months in Amp11q13 patients vs 16.2 months in non-Amp11q13 patients (HR, 0.05; 95% CI 0.01-0.45; P = 0.0003). No significant difference was observed in the nonPD-1Ab group. Notably, we found that hyperprogressive disease (HPD) might be associated with Amp11q13. The increased density of Foxp3+ Treg cells in HCC patients with Amp11q13 might be one of potential mechanisms. HCC patients with Amp11q13 are less likely to benefit from PD-1 blockade therapies. These findings may help guide the use of immunotherapy for HCC in routine clinical practice.

Eight Aging-Related Genes Prognostic Signature for Cervical Cancer.

This study searched for aging-related genes (ARGs) to predict the prognosis of patients with cervical cancer (CC). All data were obtained from Molecular Signatures Database, Cancer Genome Atlas, Gene Expression Integration, and Genotype Organization Expression. The R software was used to screen out the differentially expressed ARGs (DE-ARGs) between CC and normal tissues. A protein-protein interaction network was established by the DE-ARGs. The univariate and multivariate Cox regression analyses were conducted on the first extracted Molecular Complex Detection component, and a prognostic model was constructed. The prognostic model was further validated in the testing set and GSE44001 dataset. Prognosis was analyzed by Kaplan-Meier curves, and accuracy of the prognostic model was assessed by receiver operating characteristic area under the curve analysis. An independent prognostic analysis of risk score and some clinicopathological factors of CC was also performed. The copy-number variant (CNV) and single-nucleotide variant (SNV) of prognostic ARGs were analyzed by the BioPortal database. A clinical practical nomogram was established to predict individual survival probability. Finally, we carried out cell experiment to further verify the prognostic model. An eight-ARG prognostic signature for CC was constructed. High-risk CC patients had significantly shorter overall survival than low-risk patients. The receiver operating characteristic (ROC) curve validated the good performance of the signature in survival prediction. The Figo_stage and risk score served as independent prognostic factors. The eight ARGs mainly enriched in growth factor regulation and cell cycle pathway, and the deep deletion of FN1 was the most common CNV. An eight-ARG prognostic signature for CC was successfully constructed.