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1.
Carlos Casas-Arozamena Cristian Pablo Moiola Ana Vilar Marta Bouso Juan Cueva Silvia Cabrera Victoria Sampayo Efigenia Arias Alicia Abalo Ángel García Ramón Manuel Lago-Lestón Sara Oltra Eva Díaz Juan Ruiz-Bañobre Rafael López-López Gema Moreno-Bueno Antonio Gil-Moreno Eva Colás Miguel Abal Laura Muinelo-Romay 《International journal of cancer. Journal international du cancer》2023,152(10):2206-2217
The analysis of mismatch repair proteins in solid tissue is the standard of care (SoC) for the microsatellite instability (MSI) characterization in endometrial cancer (EC). Uterine aspirates (UAs) or circulating-DNA (cfDNA) samples capture the intratumor heterogeneity and provide a more comprehensive and dynamic molecular diagnosis. Thus, MSI analysis by droplet-digital PCR (ddPCR) in UAs and cfDNA can provide a reliable tool to characterize and follow-up the disease. The UAs, paraffin-embedded tumor tissue (FFPE) and longitudinal plasma samples from a cohort of 90 EC patients were analyzed using ddPCR panel and compared to the SoC. A high concordance (96.67%) was obtained between the analysis of MSI markers in UAs and the SoC. Three discordant cases were validated as unstable by ddPCR on FFPE samples. Besides, a good overall concordance (70.27%) was obtained when comparing the performance of the ddPCR assay on UAs and cfDNA in high-risk tumors. Importantly, our results also evidenced the value of MSI analysis to monitor the disease evolution. MSI evaluation in minimally invasive samples shows great accuracy and sensitivity and provides a valuable tool for the molecular characterization and follow-up of endometrial tumors, opening new opportunities for personalized management of EC. 相似文献
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We propose a Deep learning-based weak label learning method for analyzing whole slide images (WSIs) of Hematoxylin and Eosin (H&E) stained tumor tissue not requiring pixel-level or tile-level annotations using Self-supervised pre-training and heterogeneity-aware deep Multiple Instance LEarning (DeepSMILE). We apply DeepSMILE to the task of Homologous recombination deficiency (HRD) and microsatellite instability (MSI) prediction. We utilize contrastive self-supervised learning to pre-train a feature extractor on histopathology tiles of cancer tissue. Additionally, we use variability-aware deep multiple instance learning to learn the tile feature aggregation function while modeling tumor heterogeneity. For MSI prediction in a tumor-annotated and color normalized subset of TCGA-CRC (n=360 patients), contrastive self-supervised learning improves the tile supervision baseline from 0.77 to 0.87 AUROC, on par with our proposed DeepSMILE method. On TCGA-BC (n=1041 patients) without any manual annotations, DeepSMILE improves HRD classification performance from 0.77 to 0.81 AUROC compared to tile supervision with either a self-supervised or ImageNet pre-trained feature extractor. Our proposed methods reach the baseline performance using only 40% of the labeled data on both datasets. These improvements suggest we can use standard self-supervised learning techniques combined with multiple instance learning in the histopathology domain to improve genomic label classification performance with fewer labeled data. 相似文献
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Mohamed E. Salem J. Nicholas Bodor Alberto Puccini Joanne Xiu Richard M. Goldberg Axel Grothey W. Michael Korn Anthony F. Shields William M Worrilow Edward S. Kim Heinz-Josef Lenz John L. Marshall Michael J. Hall 《International journal of cancer. Journal international du cancer》2020,147(10):2948-2956
Microsatellite instability-high (MSI-H) and tumor mutational burden (TMB) are predictive biomarkers for immune-checkpoint inhibitors (ICIs). Still, the relationship between the underlying cause(s) of MSI and TMB in tumors remains poorly defined. We investigated associations of TMB to mismatch repair (MMR) protein expression patterns by immunohistochemistry (IHC) and MMR mutations in a diverse sample of tumors. Hypothesized differences were identified by the protein/gene affected/mutated and the tumor histology/primary site. Overall, 1057 MSI-H tumors were identified from the 32 932 tested. MSI was examined by NGS using 7000+ target microsatellite loci. TMB was calculated using only nonsynonymous missense mutations sequenced with a 592-gene panel; a subset of MSI-H tumors also had MMR IHC performed. Analyses examined TMB by MMR protein heterodimer impacted (loss of MLH1/PMS2 vs. MSH2/MSH6 expression) and gene-specific mutations. The sample was 54.6% female; mean age was 63.5 years. Among IHC tested tumors, loss of co-expression of MLH1/PMS2 was more common (n = 544/705, 77.2%) than loss of MSH2/MSH6 (n = 81/705, 11.5%; P < .0001), and was associated with lower mean TMB (MLH1/PMS2: 25.03 mut/Mb vs MSH2/MSH6 46.83 mut/Mb; P < .0001). TMB also varied by tumor histology: colorectal cancers demonstrating MLH1/PMS2 loss had higher TMBs (33.14 mut/Mb) than endometrial cancers (20.60 mut/Mb) and other tumors (25.59 mut/Mb; P < .0001). MMR gene mutations were detected in 42.0% of tumors; among these, MSH6 mutations were most common (25.7%). MSH6 mutation patterns showed variability by tumor histology and TMB. TMB varies by underlying cause(s) of MSI and tumor histology; this heterogeneity may contribute to differences in response to ICI. 相似文献
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目的:山白树是中国特有珍稀濒危植物。分析微卫星特征,开发其微卫星分子标记。方法:采用Illumina二代测序技术建立山白树基因组文库和微卫星文库,分析微卫星组成类型,设计山白树引物,用5个山白树种群进行扩增和检测以分析其多态性。结果:二代测序共返回38,942,660条100 bp配对序列,通过质量修剪及拼接得到200,386条拼接序列,其中长度 335 bp的为7 614条;在7 614条序列中检测出微卫星位点694个,其中单核苷酸重复最多,单核苷酸重复中A/T重复数量最多;二核苷酸长度变异最大,其中AG/CT重复数量最多,重复长度变异情况与微卫星丰度呈正相关。为36条山白树微卫星重复次数高的序列设计引物,经聚合酶链式反应(PCR)扩增和聚丙烯酰胺凝胶电泳检测,20对引物多态性丰富且条带清晰,等位基因数(NA)在3~6之间,平均为4,多态性信息含量(PIC) 0. 535 5~0. 754 0,平均值0. 615 5。对5个山白树种群的群体遗传分析发现,该物种遗传多样性较高(h=0. 697 5,I=1. 436 8,HE=0. 702 2),种群遗传分化显著(Fst=0. 374)。结论:通过部分山白树的群体遗传也可以说明本次开发的引物可用性较好。该研究开发了山白树微卫星分子标记引物,为山白树分子遗传学奠定了基础。 相似文献
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In this Annual Review Issue of The Journal of Pathology, we present 15 invited reviews on topical aspects of pathology, ranging from the impacts of the microbiome in human disease through mechanisms of cell death and autophagy to recent advances in immunity and the uses of genomics for understanding, classifying and treating human cancers. Each of the reviews is authored by experts in their fields and our intention is to provide comprehensive updates in specific areas of pathology in which there has been considerable recent progress. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. 相似文献
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目的 由于不同基原和产地的党参有效成分差异较大,开发党参特异分子标记对于党参种质资源准确鉴定意义重大。方法 该研究应用生物信息学软件Primer 5.0,NTSYS-pc 2.10e,PopGene 32,对小党参Codonopsis minima叶绿体、秦岭党参C. tsinlingensis叶绿体和轮叶党参C. lanceolata线粒体基因组序列进行简单重复序列标记(SSR)位点搜索,利用Primer 5.0软件设计出120对SSR引物,筛选效果好且多态性高的16对cpSSR引物和10对mtSSR引物对20份党参材料进行种间通用性分析。结果 结果显示,分别从基因组序列中搜索到66个cpSSR位点和26个mtSSR位点,其中小党参叶绿体中单核苷酸(86.20%),二核苷酸(6.9%),三核苷酸(6.9%);秦岭党参叶绿体中单核苷酸(83.78%),二核苷酸(13.51%),三核苷酸(2.71%);轮叶党参线粒体中单核苷酸(46.15%),二核苷酸(53.85%)。聚合酶链式反应(PCR)鉴定结果表明开发的26对SSR引物在党参属内具有很好的适用性。NTSYS-pc 2.10e软件分析显示20份党参材料的遗传相似系数在0.38~1.00,在阈值0.53处分为2个亚群。运用PopGene 32软件对20份党参进行多样性分析并筛选出4对多态性引物,分析发现观测等位基因数(Na)共为12个,有效等位基因数(Ne)为1.362 9~2.605 9个,各位点多态性位点百分率(PPL)均为100%,遗传学参数Ho,He,香浓指数(I)的平均值分别为0.555 8,0.444 2,0.753 2,说明各位点的多态性水平较高。以筛选出的4对引物对20份党参材料进行DNA指纹图谱绘制,发现DNA指纹图谱可将20份材料进行鉴别。结论 该研究可为党参属种间的亲缘关系和种内遗传分化研究提供分子依据。 相似文献
8.
Richard Gallon Harsh Sheth Christine Hayes Lisa Redford Ghanim Alhilal Ottilia O'Brien Helena Spiewak Amanda Waltham Ciaron McAnulty Osagie G. Izuogu Mark J. Arends Anca Oniscu Angel M. Alonso Sira M. Laguna Gillian M. Borthwick Mauro Santibanez‐Koref Michael S. Jackson John Burn 《Human mutation》2020,41(1):332-341
Microsatellite instability (MSI) testing of colorectal cancers (CRCs) is used to screen for Lynch syndrome (LS), a hereditary cancer‐predisposition, and can be used to predict response to immunotherapy. Here, we present a single‐molecule molecular inversion probe and sequencing‐based MSI assay and demonstrate its clinical validity according to existing guidelines. We amplified 24 microsatellites in multiplex and trained a classifier using 98 CRCs, which accommodates marker specific sensitivities to MSI. Sample classification achieved 100% concordance with the MSI Analysis System v1.2 (Promega) in three independent cohorts, totaling 220 CRCs. Backward–forward stepwise selection was used to identify a 6‐marker subset of equal accuracy to the 24‐marker panel. Assessment of assay detection limits showed that the 24‐marker panel is marginally more robust to sample variables than the 6‐marker subset, detecting as little as 3% high levels of MSI DNA in sample mixtures, and requiring a minimum of 10 template molecules to be sequenced per marker for >95% accuracy. BRAF c.1799 mutation analysis was also included to streamline LS testing, with all c.1799T>A variants being correctly identified. The assay, therefore, provides a cheap, robust, automatable, and scalable MSI test with internal quality controls, suitable for clinical cancer diagnostics. 相似文献
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Isabella Nicácio de Freitas Fábio Guilherm Caserta Maryssael de Campos Venancio Avancini Ferreira Alves Juliana Magalh?es Cavalcante Dirce Carraro Renata de Almeida Coudry Márcio Augusto Diniz Sérgio Carlos Nahas Ulysses Ribeiro Jr 《Journal of gastrointestinal oncology.》2015,6(6):628-637