Copy Number Variation Research Articles

Highly demarcated structural alterations in the brain and impaired social incentive learning in Tbx1 heterozygous mice.

Copy number variants (CNVs) are robustly associated with psychiatric disorders and changes in brain structures. However, because CNVs contain many genes, the precise gene-phenotype relationship remains unclear. Although various volumetric alterations in the brains of 22q11.2 CNV carriers have been identified in humans and mouse models, it is unknown how each gene encoded in the 22q11.2 region contributes to structural alterations, associated mental illnesses, and their dimensions. Our previous studies identified Tbx1, a T-box family transcription factor encoded in the 22q11.2 CNV, as a driver gene for social interaction and communication, spatial and working memory, and cognitive flexibility. However, it remains unclear how TBX1 impacts the volumes of various brain regions and their functionally linked behavioral dimensions. In this study, we used volumetric magnetic resonance imaging analysis to comprehensively evaluate brain region volumes and behavioral alterations relevant to affected structures in congenic Tbx1 heterozygous mice. Our data showed that the volumes of the anterior and posterior portions of the amygdaloid complex and its surrounding cortical regions were most robustly reduced in Tbx1 heterozygous mice. In an amygdala-dependent task, Tbx1 heterozygous mice were impaired in their ability to learn the incentive value of a social partner. The volumes of the primary and secondary auditory cortexes were increased, and acoustic, but not non-acoustic, sensorimotor gating was impaired in Tbx1 heterozygous mice. Our findings identify the brain's regional volume alterations and their relevant behavioral dimensions associated with Tbx1 heterozygosity.

A comprehensive map of copy number variations in dromedary camels based on whole genome sequence data

Copy number variants (CNVs) are structural variants within the eukaryotic genome that vary among individuals of a species. These variants have been associated with different phenotypic traits, making them a valuable consideration as markers for designing breeding programmes. In this study, whole genome sequence data of 60 dromedary camel samples originating from the Arabian Peninsula were analyzed to construct a comprehensive dromedary CNV map. Utilizing four CNV callers employing read-depth, split-read and paired-end mapping approaches, a total of 37,519 CNV events (17,847 deletions and 19,672 duplications) were called on the dromedary autosomes. These CNV events were merged into 2,557 regions, categorized as 1,322 losses, 122 gains, and 1,113 “mixed regions” comprising both types. The cumulative size of the CNV regions amounted to 22.5 Mb, covering roughly 1.16% of the dromedary autosomes. Approximately 32% of the defined CNV regions (comprising 60% losses, 18% gains, and 0.27% mixed regions) were found in ≥ 90% of the dromedary samples, classifying them as prevalent regions. Genes with biological functions related to the different adaptive physiologies of dromedary camels, such as fertility, heat stress, musculoskeletal development, and fat metabolism, were overlapping with or in close proximity to ~ 68% of the defined CNV regions, demonstrating their potential role in dromedaries’ physiology. This study presents the first comprehensive CNV map of dromedary camels and builds on the present knowledge in understanding the genetic structure of this species.

Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses

We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs.

CancerSCEM 2.0: an updated data resource of single-cell expression map across various human cancers.

The field of single-cell RNA sequencing (scRNA-seq) has advanced rapidly in the past decade, generating significant amounts of valuable data for researchers to study complex tumor profiles. This data is crucial for gaining innovative insights into cancer biology. CancerSCEM (https://ngdc.cncb.ac.cn/cancerscem) is a public resource that integrates, analyzesand visualizes scRNA-seq data related to cancer, and it provides invaluable support to numerous cancer-related studies. With CancerSCEM 2.0, scRNA-seq data have increased from 208 to 1466 datasets, covering tumor, matching-normaland peripheral blood samples across 127 research projects and 74 cancer types. The new version of this resource enhances transcriptome analysis by adding copy number variation evaluation, transcription factor enrichment, pseudotime trajectory construction, and diverse biological feature scoring. It also introduces a new cancer metabolic map at the single-cell level, providing an intuitive understanding of metabolic regulation across different cancer types. CancerSCEM 2.0 has a more interactive analysis platform, including four modules and 14 analytical functions, allowing researchers to perform cancer scRNA-seq data analyses in various dimensions. These enhancements are expected to expand the usability of CancerSCEM 2.0 to a broader range of cancer research and clinical applications, potentially revolutionizing our understanding of cancer mechanisms and treatments.

Comprehensive genome analysis and variant detection at scale using DRAGEN.

Research and medical genomics require comprehensive, scalable methods for the discovery of novel disease targets, evolutionary drivers and genetic markers with clinical significance. This necessitates a framework to identify all types of variants independent of their size or location. Here we present DRAGEN, which uses multigenome mapping with pangenome references, hardware acceleration and machine learning-based variant detection to provide insights into individual genomes, with ~30 min of computation time from raw reads to variant detection. DRAGEN outperforms current state-of-the-art methods in speed and accuracy across all variant types (single-nucleotide variations, insertions or deletions, short tandem repeats, structural variations and copy number variations) and incorporates specialized methods for analysis of medically relevant genes. We demonstrate the performance of DRAGEN across 3,202 whole-genome sequencing datasets by generating fully genotyped multisample variant call format files and demonstrate its scalability, accuracy and innovation to further advance the integration of comprehensive genomics. Overall, DRAGEN marks a major milestone in sequencing data analysis and will provide insights across various diseases, including Mendelian and rare diseases, with a highly comprehensive and scalable platform.

Pangenome graph analysis reveals extensive effector copy-number variation in spinach downy mildew.

Plant pathogens adapt at speeds that challenge contemporary disease management strategies like the deployment of disease resistance genes. The strong evolutionary pressure to adapt, shapes pathogens' genomes, and comparative genomics has been instrumental in characterizing this process. With the aim to capture genomic variation at high resolution and study the processes contributing to adaptation, we here leverage an innovative, multi-genome method to construct and annotate the first pangenome graph of an oomycete plant pathogen. We expand on this approach by analysing the graph and creating synteny based single-copy orthogroups for all genes. We generated telomere-to-telomere genome assemblies of six genetically diverse isolates of the oomycete pathogen Peronospora effusa, the economically most important disease in cultivated spinach worldwide. The pangenome graph demonstrates that P. effusa genomes are highly conserved, both in chromosomal structure and gene content, and revealed the continued activity of transposable elements which are directly responsible for 80% of the observed variation between the isolates. While most genes are generally conserved, virulence related genes are highly variable between the isolates. Most of the variation is found in large gene clusters resulting from extensive copy-number expansion. Pangenome graph-based discovery can thus be effectively used to capture genomic variation at exceptional resolution, thereby providing a framework to study the biology and evolution of plant pathogens.

Genetic analysis of preaxial polydactyly: identification of novel variants and the role of ZRS duplications in a Chinese cohort of 102 cases.

Preaxial polydactyly (PPD) is a congenital limb malformation, previously reported to be caused primarily by variants in the ZRS and upstream preZRS regions. This study investigated genetic variations associated with PPD, focusing on point variants and copy number variations (CNVs) in the ZRS and preZRS regions. Comprehensive genetic analyses were conducted on 102 patients with PPD, including detailed clinical examinations and Sanger sequencing of the ZRS and preZRS regions. Additionally, real-time quantitative PCR (qPCR) was used to detect CNVs in the ZRS region. The evolutionary conservation and population frequencies of identified variants were also evaluated. Six point variants were identified, among which four are likely pathogenic novel variants: 93G > T (g.156584477G > T), 106G > A (g.156584464G > A), 278G > A (g.156584292G > A), and 409A > C (g.156585378A > C). Additionally, qPCR analysis revealed that 66.67% of patients exhibited ZRS duplications. Notably, these duplications were also present in cases with newly identified potential pathogenic point variants. These findings suggest the possible interaction of point variants in ZRS and preZRS through a common pathogenic mechanism, leading jointly to PPD. The findings expand the variant spectrum associated with non-syndromic polydactyly and highlight that, despite different classifications, anterior polydactyly caused by variants in ZRS and nearby regions may share common pathogenic mechanisms. The incorporation of various variant types in genetic screening can effectively enhance the rate of pathogenic variant detection and contribute to the cost-effectiveness of genetic testing for limb developmental defects, thereby promoting healthy births.

Advances in bacterial artificial chromosome (BAC) transgenic mice for gene analysis and disease research.

Transgenic mice, including those created using Bacterial Artificial Chromosomes (BACs), are artificial manipulations that have become critical tools for studying gene function. While conventional transgenic techniques face challenges in achieving precise expression of foreign genes in specific cells and tissues, BAC transgenic mice offer a solution by incorporating large DNA segments that can include entire expression units with tissue-specific enhancers. This review provides a thorough examination of BAC transgenic mouse technology, encompassing both traditional and humanized models. We explore the benefits and drawbacks of BAC transgenesis compared to other techniques such as knock-in and CRISPR/Cas9 technologies. The review emphasizes the applications of BAC transgenic mice in various disciplines, including neuroscience, immunology, drug metabolism, and disease modeling. Additionally, we address crucial aspects of generating and analyzing BAC transgenic mice, such as position effects, copy number variations, and strategies to mitigate these challenges. Despite certain limitations, humanized BAC transgenic mice have proven to be invaluable tools for studying the pathogenesis of human diseases, drug development, and understanding intricate gene regulatory mechanisms. This review discusses current topics on BAC transgenic mice and their evolving significance in biomedical research.

NRXN1 as a Prognostic Biomarker: Linking Copy Number Variation to EMT and Survival in Colon Cancer.

The role of biomarkers in cancer treatment varies significantly depending on the cancer stage. Thus, in clinical practice, tailoring biomarkers to meet the specific needs and challenges of each cancer stage can increase the precision of treatment. Because they reflect underlying genetic alterations that influence cancer progression, copy number variation (CNV) biomarkers can play crucial prognostic roles. In our previous study, we identified potential survival-related genes for colorectal cancer (CRC) by analyzing CNV and gene expression data using a machine-learning approach. To further investigate the biological function of NRXN1, we assessed the use of RNA sequencing, phosphokinase assays, real-time quantitative PCR, and Western blot analysis. We found that NRXN1 copy number deletion was significantly associated with poor overall survival (OS) and recurrence-free survival (RFS), even in patients who received adjuvant chemotherapy. Compared with its expression in normal tissues, NRXN1 expression was lower in tumors, suggesting its potential role as a tumor suppressor. NRXN1 knockdown enhanced CRC cell viability and invasion, and transcriptome analysis indicated that the increased invasion was caused by GSK3β-mediated epithelial-mesenchymal transition. These findings highlight NRXN1 copy number deletion as a novel biomarker for predicting recurrence and survival in patients with resected colon cancer.

Genetic analysis using next-generation sequencing and multiplex ligation probe amplification in Chinese aniridia patients

BackgroundCongenital aniridia is a rare pan-ocular disease characterized by complete irideremia, partial iridocoloboma. The progressive nature of aniridia is frequently accompanied by secondary ocular complications such as glaucoma and aniridia-associated keratopathy, which can lead to severely impaired vision or blindness. The genetic basis of aniridia has been the subject of numerous studies, leading to the development of innovative therapeutic options based on PAX6 nonsense mutations. Specific knowledge of the genetics of aniridia has become increasingly important. To report the clinical features, elucidate the genetic etiology, and reveal the mutational spectrum of congenital aniridia in the Chinese population, sixty patients with congenital aniridia from 51 families were recruited. Candidate genes associated with developmental eye diseases were identified and analyzed using panel-based next-generation sequencing (NGS), and mutations were confirmed through polymerase chain reaction and Sanger sequencing. Multiplex ligation probe amplification (MLPA) of PAX6 and FOXC1 was performed to detect copy number variations in the patients without intragenic mutations.ResultsClinical examination revealed complete iris hypoplasia in 58 patients and partial iris hypoplasia in two patients. Additionally, two patients were diagnosed with Wilms’ tumor-aniridia-genital anomalies-retardation syndrome and nephroblastoma. By combining panel-based NGS and MLPA, 43 intragenic mutations or deletions of PAX6, FOXC1, and BCOR were identified in 59 patients, including 33 point mutations (76.7%) in 43 patients and 10 deletions (23.3%) in 16 patients. The total detection rate was 98.3%. Phenotypic variation was observed between and within families.ConclusionsVariations in PAX6 and its adjacent regions were the predominant causes of aniridia in China. In addition to intragenic point mutations in PAX6, deletion of PAX6 or its adjacent genes is a common cause of congenital aniridia. Furthermore, FOXC1 is an important gene associated with congenital aniridia. The combination of panel-based NGS and MLPA significantly enhanced the detection rate of gene mutations in patients with congenital aniridia.

Unravelling the architecture of major histocompatibility complex class II haplotypes in rhesus macaques.

The regions in the genome that encode components of the immune system are often featured by polymorphism, copy number variation, and segmental duplications. There is a need to thoroughly characterize these complex regions to gain insight into the impact of genomic diversity on health and disease. Here we resolve the organization of complete major histocompatibility complex (MHC) class II regions in rhesus macaques by using a long-read sequencing strategy (Oxford Nanopore Technologies) in concert with adaptive sampling. In particular, the expansion and contraction of the primate DRB-region appear to be a dynamic process that involves the rearrangement of different cassettes of paralogous genes. These chromosomal recombination events are propagated by a conserved pseudogene, DRB6, which features the integration of two retroviral elements. In contrast, the DRA locus appears to be protected from rearrangements, which may be owing to the presence of an adjacently located truncated gene segment, DRB9 With our sequencing strategy, the annotation, evolutionary conservation, and potential function of pseudogenes can be reassessed, an aspect that was neglected by most genome studies in primates. Furthermore, our approach facilitates the characterization and refinement of an animal model essential to study human biology and disease.

Locoregional event or dyssynchronous distant metastasis: clinicopathological and molecular analysis of contralateral axillary lymph node metastasis in breast cancer patients.

Contralateral axillary lymph node metastasis (CAM) is a rare clinical condition in patients with breast cancer (BC). CAM can be either a locoregional event or a distant metastasis. Molecular application for clonal evolution in BC has not been reported in CAM cases. We studied six patients with CAM with clinical, pathological and/or molecular evidence of distant metastasis; those patients had poor outcomes. Two cases with molecular analysis of paired primary and CAM established clonal evolution of the CAM with its corresponding primary with additional molecular alteration, increased tumour mutation burden, and copy number variations (CNVs) in the CAMs. Four cases containing alterations from genes potentially modulate chromatin organization, supporting chromatin and subsequent transcriptional signature changes are essential in CAM. Molecular analysis is critical to establish the connection between CAM and its primary counterpart. Distant CAM shows clonal evolution compared with its corresponding primary with additional molecular alterations, increased mutation burden and/or copy number variations. CAM should be evaluated individually and handled in a personalized fashion. Evidence of a true metastatic CAM can be supported by distant metastasis to other organs, specific morphological features and/or clonal evolution.

Single-cell RNA-seq analysis revealed the stemness of a specific cluster of B cells in acute lymphoblastic leukemia progression.

Childhood acute lymphoblastic leukemia (ALL) is a common pediatric cancer. The heterogeneous characterization of B cells in ALL progression poses new challenges to researchers. We used single-cell sequencing to explore the critical role of B cells in regulating the ALL immune microenvironment. We collected the single cell (sc) RNA-seq data of ALL and health sample from the gene expression omnibus (GEO) database, the "Seurat" and "harmony" R package was used for quality control and scRNA-seq analysis, in which the CellMarker2.0 database was used for cell type annotation. Subsequently, the FindAllMarkers function was used to identify the differentially expressed genes (DEGs) among various cell types and the DAVID database was applied for the biological process of DEGs. Then, the "inferCNV" package was used for copy number variation, regulons and cell communication were performed by SCENIC tool and CellChat package. The role of the target gene in regulating ALL progression was assessed using RT-qPCR, Transwell and scratch healing assays. We identified nine mainly cell clusters after scRNA-seq analysis, in which the B cells had higher infiltration proportion in the ALL samples and were sub-clustered into five cell sub-groups. The B cells 1 is closely associated with cell proliferation and stemness (TNFAIP3 and KDM5B), and the significant CNV of amplification occurred on chr6 and chr21 that supported stemness of B cells1. RXRB is a key transcription factor mediated the proliferation of B cells 1, which in turn suppressed hematopoietic stem cells (HSCs) proliferation and promoted cytotoxic NK/T cells activation through diverse cell communication ways. One of the key regulators of B cells is MYC, which promotes the migration and invasive ability of cell line leukemia cell lines. This study reveals the stemness characteristics of B cells and their critical role in ALL progression, a finding that provides new potential directions for the development of targeted therapies against ALL.

Postnatal Outcomes of Fetal Variants of Unknown Significance in Prenatal Chromosomal Microarray Analysis: A Single-Center Study.

Chromosomal microarray analysis (CMA) can identify clinically significant microdeletions and microduplications, providing valuable insights into the genetic basis of various disorders. Our study was to evaluate clinical management and prognosis of fetuses with prenatal variants of unknown significance (VOUS) and determine diagnostic approaches for subsequent pregnancies. This study included 2,953 fetuses undergoing CMA at the Prenatal Diagnostic Center of Changzhou Maternal and Child Health Care Hospital from January 2018 to December 2022, identifying 162 cases with VOUS. Parent-of-origin testing determined the origin of copy number variations. Prenatal genetic counseling was provided, and outcomes were followed for 3-36 months post-birth. All 162 VOUS cases received prenatal genetic counseling. Among these, 123 continued the pregnancy; 22 chose termination, and 17 were lost to follow-up. Of the continuations, 116 delivered at term and 7 preterm. Post-birth follow-up showed 5/123 live-born fetuses developed relevant clinical phenotypes. Parent-of-origin testing in 21 cases identified 18 hereditary and 3 de novo variants. Additionally, five subsequent pregnancies were monitored, with two undergoing amniocentesis and three receiving low-risk noninvasive prenatal testing, all with positive outcomes. VOUS, occurring in approximately 5% of cases, require comprehensive prenatal genetic counseling and show generally favorable outcomes. Despite low association with adverse clinical phenotypes, the importance of postnatal follow-up and regular report updates is emphasized to detect potential clinical associations early.

Application of Genetic Origin Analysis of Copy Number Variations in Non-Invasive Prenatal Testing.

This study aimed to assess the application of origin analysis of copy number variations (CNVs) in non-invasive prenatal testing (NIPT) and provide a basis for expanding the clinical application of NIPT. We enrolled 35,317 patients who underwent NIPT between January 2019 and March 2023. Genome sequencing of copy number variation (CNV-Seq) analysis was performed using the CNV calling pipeline to identify subchromosomal abnormalities in maternal plasma. Genetic origin was determined by comparing the chimaerism ratio of CNV and the concentration of cell-free foetal DNA (cffDNA). All pregnant women with a high risk of CNV, as indicated by the NIPT, were informed of their genetic origins. Amniocentesis was recommended for detecting the CNVs in foetal chromosomes, and pregnancy outcomes were tracked. A total of 109 pregnancies showed clinically significant positive results for CNV after NIPT, including 65 cases of maternal/foetal (M/F)-CNVs and 44 cases of F-CNVs. The occurrence of M/F-CNVs was independent of age, screening (serological or ultrasound) indications for abnormalities, and mode of pregnancy. The incidence of pathogenic/likely pathogenic (P/LP)-F-CNVs was high in cases where serological screening indicated intermediate, high-risk, or abnormal US findings (p<0.05). In the M/F-CNV group, most of the P/LP-CNVs were small fragments with low penetrance; 55 (84.62%) were less than 5Mb in size, and nine (13.85%) were between 5 and 10Mb. In the F-CNV group, foetal P/LP-CNV was detected in 36 of 42 cases undergoing prenatal diagnosis, and no significant bias was noted in the size distribution of P/LP-F-CNV fragments. The prenatal diagnostic rate and positive predictive value in the F-CNV group were 95.45% and 85.71%, respectively, which were significantly different from those in the M/F group (26.15% and 52.95%), respectively (p<0.05). Genetic origin analysis of CNV can effectively improve adherence to prenatal diagnosis in pregnant women and the accuracy of prenatal diagnosis.

Optical genome mapping of structural variants in Parkinson’s disease-related induced pluripotent stem cells

BackgroundCertain structural variants (SVs) including large-scale genetic copy number variants, as well as copy number-neutral inversions and translocations may not all be resolved by chromosome karyotype studies. The identification of genetic risk factors for Parkinson’s disease (PD) has been primarily focused on the gene-disruptive single nucleotide variants. In contrast, larger SVs, which may significantly influence human phenotypes, have been largely underexplored. Optical genomic mapping (OGM) represents a novel approach that offers greater sensitivity and resolution for detecting SVs. In this study, we used induced pluripotent stem cell (iPSC) lines of patients with PD-linked SNCA and PRKN variants as a proof of concept to (i) show the detection of pathogenic SVs in PD with OGM and (ii) provide a comprehensive screening of genetic abnormalities in iPSCs.ResultsOGM detected SNCA gene triplication and duplication in patient-derived iPSC lines, which were not identified by long-read sequencing. Additionally, various exon deletions were confirmed by OGM in the PRKN gene of iPSCs, of which exon 3–5 and exon 2 deletions were unable to phase with conventional multiplex-ligation-dependent probe amplification. In terms of chromosomal abnormalities in iPSCs, no gene fusions, no aneuploidy but two balanced inter-chromosomal translocations were detected in one line that were absent in the parental fibroblasts and not identified by routine single nucleotide variant karyotyping.ConclusionsIn summary, OGM can detect pathogenic SVs in PD-linked genes as well as reveal genomic abnormalities for iPSCs that were not identified by other techniques, which is supportive for OGM’s future use in gene discovery and iPSC line screening.

Identification and Copy Number Variant Analysis of Enhancer Regions of Genes Causing Spinocerebellar Ataxia.

Currently, routine diagnostics for spinocerebellar ataxia (SCA) look for polyQ repeat expansions and conventional variations affecting the proteins encoded by known SCA genes. However, ~40% of the patients still remain without a genetic diagnosis after routine tests. Increasing evidence suggests that variations in the enhancer regions of genes involved in neurodegenerative disorders can also cause disease. Since the enhancers of SCA genes are not yet known, it remains to be determined whether variations in these regions are a cause of SCA. In this pilot project, we aimed to identify the enhancers of the SCA genes ATXN1, ATXN3, TBP and ITPR1 in the human cerebellum using 4C-seq, publicly available datasets, reciprocal 4C-seq, and luciferase assays. We then screened these enhancers for copy number variants (CNVs) in a cohort of genetically undiagnosed SCA patients. We identified two active enhancers for each of the four SCA genes. CNV analysis did not reveal any CNVs in the enhancers of the four SCA genes in the genetically undiagnosed SCA patients. However, in one patient, we noted a CNV deletion with an unknown clinical significance near one of the ITPR1 enhancers. These results not only reveal elements involved in SCA gene regulation but can also lead to the discovery of novel SCA-causing genetic variants. As enhancer variations are being increasingly recognized as a cause of brain disorders, screening the enhancers of ATXN1, ATXN3, TBP and ITPR1 for variations other than CNVs and identifying and screening enhancers of other SCA genes might elucidate the genetic cause in undiagnosed patients.

ScTML: a pan-cancer single-cell landscape of multiple mutation types.

Investigating mutations, including single nucleotide variations (SNVs), gene fusions, alternative splicing and copy number variations (CNVs), is fundamental to cancer study. Recent computational methods and biological research have demonstrated the reliability and biological significance of detecting mutations from single-cell transcriptomic data. However, there is a lack of a single-cell-level database containing comprehensive mutation information in all types of cancer. Establishing a single-cell mutation landscape from the huge emerging single-cell transcriptomic data can provide a critical resource for elucidating the mechanisms of tumorigenesis and evolution. Here, we developed scTML (http://sctml.xglab.tech/), the first database offering a pan-cancer single-cell landscape of multiple mutation types. It includes SNVs, insertions/deletions, gene fusions, alternative splicing and CNVs, along with gene expression, cell states and other phenotype information. The data are from 74 datasets with 2 582 633 cells, including 35 full-length (Smart-seq2) transcriptomic single-cell datasets (all publicly available data with raw sequencing files), 23 datasets from 10X technology and 16 spatial transcriptomic datasets. scTML enables users to interactively explore multiple mutation landscapes across tumors or cell types, analyze single-cell-level mutation-phenotype associations and detect cell subclusters of interest. scTML is an important resource that will significantly advance deciphering intra-tumor and inter-tumor heterogeneity, and how mutations shape cell phenotypes.

Integrative analysis of single-cell and bulk multi-omics data to reveal subtype-specific characteristics and therapeutic strategies in clear cell renal cell carcinoma patients.

Background: Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of malignant renal cell carcinoma and is well known as a common genitourinary cancer. Stratifying tumors based on heterogeneity is essential for better treatment options. Methods: In this study, consensus clusters were constructed based on gene expression, DNA methylation, and gene mutation data, which were combined with multiple clustering algorithms. After identifying two heterogeneous subtypes, we analyzed the molecular characteristics, immunotherapy response, and drug sensitivity differences of each subtype. And we further integrated bulk data and single-cell RNA sequencing (scRNA-Seq) data to infer the immune cell composition and malignant tumor cell proportion of subtype-related cell subpopulations. Results: Among the two identified consensus subtypes (CS1 and CS2), CS1 was enriched in more inflammation-related and oncogenic pathways than CS2. Simultaneously, CS1 showed a worse prognosis and we found more copy number variations and BAP1 mutations in CS1. Although CS1 had a high immune infiltration score, it exhibited high expression of suppressive immune features. Based on the prediction of immunotherapy and drug sensitivity, we inferred that CS1 may respond poorly to immunotherapy and be less sensitive to targeted drugs. The analysis of bulk data integrated with single-cell data further reflected the high expression of inhibitory immune features in CS1 and the high proportion of malignant tumor cells. And CS2 contained a large number of plasmacytoid B cells, presenting an activated immune microenvironment. Finally, the robustness of our subtypes was successfully validated in four external datasets. Conclusion: In summary, we conducted a comprehensive analysis of multi-omics data with 10 clustering algorithms to reveal the molecular characteristics of KIRC patients and validated the relevant conclusions by single-cell analysis and external data. Our findings discovered new KIRC subtypes and may further guide personalized and precision treatments.

Pharmacoproteogenomic approach identifies on-target kinase inhibitors for cancer drug repositioning.

Drug repositioning of approved drugs offers advantages over de novo drug development for a rare type of cancer. To efficiently identify on-target drugs from clinically successful kinase inhibitors in cancer drug repositioning, drug screening and molecular profiling of cell lines are essential to exclude off-targets. We developed a pharmacoproteogenomic approach to identify on-target kinase inhibitors, combining molecular profiling of genomic features and kinase activity, and drug screening of patient-derived cell lines. This study examined eight patient-derived giant cell tumor of the bone (GCTB) cell lines, all of which harbored a signature mutation of H3-3A but otherwise without recurrent copy number variants and mutations. Kinase activity profiles of 100 tyrosine kinases with a three-dimensional substrate peptide array revealed that nine kinases were highly activated. Pharmacological screening of 60 clinically used kinase inhibitors found that nine drugs directed at 29 kinases strongly suppressed cell viability. We regarded ABL1, EGFR, and LCK as on-target kinases; among the two corresponding on-target kinase inhibitors, osimertinib and ponatinib emerged as on-target drugs whose target kinases were significantly activated. The remaining 26 kinases and seven kinase inhibitors were excluded as off-targets. Our pharmacoproteomic approach enabled the identification of on-target kinase inhibitors that are useful for drug repositioning.