1028 results for "中国疾控中心2024年12月传染病死亡病例统计数据"

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• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - WXS

  B-PLL is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003275

• Indonesian Genome Diversity Project

  Indonesia, the world’s fourth largest country by population, comprises an archipelago of about 900 permanently inhabited islands in tropical Asia, and hosts an astonishing array of human diversity that remains largely underrepresented in modern biological surveys. The region is unique for its key role in both the early and recent evolution of Homo outside of Africa. It has one of the first traces of anatomically modern humans in Eurasia, and was the focus of extensive interaction between archaic hominins and humans – both in the likely co-existence of H. floresiensis with modern humans, and in the introgression of Denisovans into the ancestors of its present inhabitants. More recently, Indonesia was a center of the spread of Neolithic culture by Austronesian speakers. Advancing maritime technologies allowed farming populations to treat this region as a springboard to reach oceanic islands as remote as Madagascar, Hawaii, Easter Island and New Zealand. Here we present complete human genomes from healthy individuals from multiple key islands in Indonesia and Papua. The genomes were sequenced to high depth (30x). The purpose of this dataset is to address different questions of human evolution in Island Southeast Asia and beyond, including early settlement of the area by anatomically modern humans, population structure, genetic admixture and adaptation, and contacts with archaic hominins. We employed a sampling strategy to capture a broad range of diversity across the region incorporating an average of 12 samples from each of 14 islands spanning Indonesia and Papua, from Sumatra in the west to New Britain in the east. Genomes from this dataset form part of an ongoing project to describe and understand human evolutionary history in Island Southeast Asia and Eurasia in general.

  Study EGAS00001003054

• Characterization of a human iPSC-derived endocrine pancreas model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Study EGAS00001001803

• Matching of actionable mutations with therapies in cancer patients: comparison of three commercial decision support platforms

  Purpose: In oncology, precision medicine centers on tailoring the most appropriate therapy to a patient according to their tumor molecular profile. We addressed the question whether there is a consensus in the classification of actionability of somatic variants and their alignment to treatment recommendations. To this end, we evaluated three commercial clinical decision support tools to assess their variant classification and drug matching strategies.Methods: In this two centers study 48 patients with metastatic breast (n=12), colorectal (n=17) or non-small cell lung cancer (n=19) were recruited based on circulating tumor DNA levels in peripheral blood. In individual patients’ plasma samples, we established somatic copy number alterations and somatic mutations across a 77 cancer-associated gene panel and exposed the obtained molecular profiles to the decision support packages NAVIFY Mutation Profiler (NMP; Roche), Qiagen Clinical Insight (QCI) Interpret (Qiagen) and CureMatch Bionov (CureMatch).Results: In the plasma samples, altogether 492 somatic alterations were assessed. Each decision support platform varied in their format of data input, mode of variant classification and strategies for identifying druggable targets and clinical trials, which resulted in discrepancies in tier classification as well as designations of actionability. The frequency of concordant actionable events for tier I-A or tier I-B classifications, i.e. those with the strongest clinical evidence, was only 4.3%, 9.5% and 28.4% when comparing NMP with QCI, NMP with CureMatch, and CureMatch with QCI, respectively. As a consequence, the obtained treatment recommendations differed drastically, and alignment of treatment recommendations was limited to established predictive markers.Conclusions: The lack of standards for the extraction of treatment recommendations from comprehensive tumor molecular profiling data challenge the promising concepts of precision oncology.

  Study EGAS00001004383

• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• Functional Mapping of AKT Signaling and Biomarkers of Response From the FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer

  Purpose: Despite extensive genomic and transcriptomic profiling, it remains unknown how signaling pathways are differentially activated and how tumors are differentially sensitized to certain perturbations. Here, we aim to characterize AKT signaling activity and its association with other genomic or immunohistochemistry-based PI3K/AKT pathway biomarkers as well as the clinical activity of ipatasertib (AKT inhibitor) in the FAIRLANE trial. Experimental Design: In FAIRLANE, 151 patients with early triple-negative breast cancer were randomized 1:1 to receive paclitaxel with ipatasertib or placebo for 12 weeks prior to surgery. Adding ipatasertib did not increase pathologic complete response rate and numerically improved overall response rate by magnetic resonance imaging (MRI). We used reverse-phase protein microarrays (RPPA) to examine the total level and/or phosphorylation states of over 100 proteins in various signaling or cell processes including PI3K/AKT and mTOR signaling. 125 baseline and 127 on-treatment samples were evaluable by RPPA, with 110 paired samples at both time points. Results: Tumors with genomic/protein alterations in PIK3CA/AKT1/PTEN were associated with higher levels of AKT phosphorylation. In addition, phosphorylated(p)AKT levels exhibited a significant association with enriched clinical benefit of ipatasertib, and identified patients who received benefit in the absence of PIK3CA/AKT1/PTEN alterations. Ipatasertib treatment led to a down-regulation of AKT/mTORC1 signaling, which was more pronounced among the tumors with PIK3CA/AKT1/PTEN alterations or among the responders to the treatment. Conclusions: We showed that the high baseline pAKT levels are associated with the alterations of PI3K/AKT pathway components and enriched benefit of ipatasertib in TNBC.

  Study EGAS00001005892

• cfDNA dataset from the urine supernatant of ovarian cancer patients and healthy controls

  Background Ovarian cancer is the deadliest gynecological malignancy worldwide, due to frequent diagnosis at advanced stage. Simple and non-invasive methods for earlier and accurate detection are urgently needed. Here, the presence of tumor-derived DNA in home-collected urine, cervicovaginal self-samples and clinician-taken cervical scrapes of ovarian cancer patients was explored by DNA methylation and copy number analysis. Methods A total of 428 samples (urine, cervicovaginal self-samples, and clinician-taken cervical scrapes) of 110 healthy controls and 54 patients with benign (n=25) or malignant (n=29) ovarian masses were analyzed. Different urine fractions were examined (full void urine, urine supernatant, and urine sediment). All samples were tested for 12 methylation markers by quantitative methylation-specific PCR. Shallow whole-genome sequencing was performed to detect copy number aberrations and verify the presence of tumor-derived DNA. Results Full void urine was most discriminatory between healthy controls and ovarian cancer patients (C2CD4D, p=0.008; CDO1, p=0.022; MAL, p=0.008), followed by cervical scrapes (C2CD4D, p=0.001; CDO1, p=0.004). A significant difference between benign and malignant ovarian masses was only observed for GHSR in the urine sediment (p=0.024). Methylation levels in cervicovaginal self-samples did not discriminate between healthy controls, benign and malignant ovarian masses. Copy number changes were identified in 17% of urine supernatant samples and smaller fragment sizes were seen in urine supernatant samples with a high tumor fraction. Conclusions This study demonstrates the presence of ovarian cancer-derived DNA in home-collected urine. Additional studies are warranted to further explore the clinical applicability of this approach.

  Study EGAS00001007238

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• Using genetics to identify cell types and mechanisms underlying susceptibility to primary sclerosing cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001011815

• Multi-region sequencing of RCC with VTT and metastasis using WES and RNAseq

  This dataset contains multi-region sequencing of 16 RCC patients with venous tumor thrombus (VTT), 11 of which were either metastatic on diagnosis or recurred with metastasis. Whole exome sequencing is available for 94 samples across all 16 patients, including 1 matched normal sample per patient, 2-3 primary tumor samples per patient, 1-2 VTT samples per patient, and 0-3 metastasis samples per patient (metastatic lesions were only sampled for 8 of the 11 metastatic patients). RNAseq, generated by exome capture, is available for 67 samples across 12 patients, including 0-1 matched normal samples per patient, 3 primary tumor samples per patient, 0-1 VTT samples per patient, and 0-3 metastasis samples per patient (RNAseq was only available for 4 of the 8 patients from whom metastatic lesions were sampled).

  Dataset EGAD00001008441