Cancer Genetics最新文献_第8页

64. A rare finding of triple KRAS mutations with OmniSeq® INSIGHT in a patient with colorectal adenocarcinoma 64.用 OmniSeq® INSIGHT 在一名结直肠腺癌患者身上罕见地发现三重 KRAS 突变

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.066

Durga Prasad Dash , Eric Severson , Kyle Strickland , Heidi Ko , Rebeccaann Previs , Stephanie Hastings , Michelle Green , Paul Depietro , Brian Caveney , Marcia Eisenberg , Taylor Jensen , Jeffrey Conroy , Shakti Ramkissoon , Shengle Zhang

Background

Colorectal cancer (CRC) ranks third in terms of new tumor cases and the second leading cause of cancer-related death worldwide (PMID: 30207593). KRAS is one of the most frequently mutated oncogenes in CRC, with approximately 40% of patients harboring activating missense mutations in KRAS (PMID: 31972237). Patients with KRAS-mutant CRC have a worse prognosis than those with KRAS wild-type CRC [PMID: 20008640; PMID: 28453697). Here we report a rare finding of three clinically significant KRAS mutations co-occurring in a patient with microsatellite stable colorectal adenocarcinoma.

Methods

Comprehensive genomic and immune profiling (CGIP) was performed on a hemicolectomy specimen from a >80 year old patient with advanced colorectal adenocarcinoma with 60% tumor nuclei and more than 1000 neoplastic cells per slide at a CAP/CLIA and NYS CLEP certified reference laboratory with the OmniSeq® INSIGHT test (PMID: 34855780). OmniSeq INSIGHT is a next generation sequencing-based laboratory developed test for both DNA and RNA for the detection of genomic and transcriptomic variants, in formalin-fixed paraffin-embedded (FFPE) tumor tissue.

Results

We identified three co-occurring KRAS mutations (c.35G>A p.G12D, c.38G>A p.G13D and c.351A>T p.K117N) with VAF 10.1%, 9.5% and 4.1% respectively in the same colorectal adenocarcinoma patient specimen. All three mutations are associated with resistance to targeted therapies with cetuximab and panitumumab. In addition, the sequencing utilized was able to reveal that G12D and G13D mutations occurred in different cell clones/populations.

Conclusions

CGIP revealed three distinct KRAS co-mutations at known KRAS hot-spots. In addition, CGIP can distinguish allele-specific KRAS mutations and tumoral sub-clonal populations.

背景直肠癌（CRC）在全球新发肿瘤病例中排名第三，是癌症相关死亡的第二大原因（PMID: 30207593）。KRAS 是 CRC 中最常发生突变的癌基因之一，约 40% 的患者携带 KRAS 激活错义突变（PMID: 31972237）。与 KRAS 野生型 CRC 患者相比，KRAS 突变型 CRC 患者的预后较差 [PMID：20008640；PMID：28453697]。在此，我们报告了在一名微卫星稳定型结直肠腺癌患者中同时发现三个具有临床意义的 KRAS 突变的罕见病例。方法在一家经 CAP/CLIA 和 NYS CLEP 认证的参考实验室，使用 OmniSeq® INSIGHT 测试 (PMID: 34855780)，对一位 80 岁晚期结直肠腺癌患者的血液结肠切除标本进行了全面的基因组和免疫分析 (CGIP)。OmniSeq INSIGHT 是一种基于下一代测序的实验室开发的 DNA 和 RNA 检测方法，用于检测福尔马林固定石蜡包埋（FFPE）肿瘤组织中的基因组和转录组变异。G>A p.G12D、c.38G>A p.G13D和c.351A>T p.K117N），其VAF分别为10.1%、9.5%和4.1%。这三种突变都与西妥昔单抗和帕尼单抗靶向疗法的耐药性有关。此外，利用测序技术还能发现 G12D 和 G13D 突变发生在不同的细胞克隆/群体中。此外，CGIP 还能区分等位基因特异性 KRAS 突变和肿瘤亚克隆群体。

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引用次数: 0

50. TAGVar: A simple, free software tool to annotate genomic variants for clinical review 50.TAGVar：用于注释基因组变异以便临床审查的简单、免费软件工具

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.052

Matthew Croken, Olga Lukatskaya

Comprehensive and whole exome NGS panels can generate large amounts of genomic information for a single specimen. This makes these approaches very powerful, however converting raw signals from the NGS instrument into actionable, clinical information requires specialized data pipelines. The expense and expertise required to deploy these pipelines may place NGS testing out of reach for clinics and research groups in low resource settings. TAGVar (Tertiary Analysis of Genomic Variants) is a freely available software tool that facilitates somatic variant classification in both the clinical and research contexts. The application takes VCF formatted genomic variants and outputs HGVS annotations, predicted effect, and links to external variant databases, like dbSNP, gnomAD, ClinVar, COSMIC, and CancerHotspots.org. TAGVar sorts and categorizes variants based on read coverage, variant allele frequency, inferred transcript effect, description in somatic variant databases, or presence in known cancer-related genes as well as additional user-defined criteria. In the clinic, these classifications streamline the identification of reportable variants. In research, the same classification scheme identifies known and novel somatic variants associated with disease. TAGVar has relatively low memory and CPU requirements and does not require a stable internet connection to run. These design features make TAGVar ideal for use in low resource settings.

综合和全外显子组 NGS 面板可为单个标本生成大量基因组信息。这使得这些方法非常强大，但将 NGS 仪器的原始信号转换为可操作的临床信息需要专门的数据管道。部署这些管道所需的费用和专业知识可能会使资源匮乏的诊所和研究小组无法进行 NGS 检测。TAGVar（基因组变异的三级分析）是一款免费提供的软件工具，有助于临床和研究中的体细胞变异分类。该应用程序采用 VCF 格式的基因组变异，输出 HGVS 注释、预测效应以及外部变异数据库链接，如 dbSNP、gnomAD、ClinVar、COSMIC 和 CancerHotspots.org。TAGVar 根据读取覆盖率、变异等位基因频率、推断转录本效应、体细胞变异数据库中的描述、已知癌症相关基因中的存在情况以及用户自定义的其他标准对变异进行排序和分类。在临床中，这些分类简化了可报告变异的鉴定。在研究中，同样的分类方案可识别与疾病相关的已知和新型体细胞变异。TAGVar 对内存和 CPU 的要求相对较低，运行时不需要稳定的互联网连接。这些设计特点使 TAGVar 非常适合在资源匮乏的环境中使用。

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引用次数: 0

32. pVACsplice: A Computational tool for predicting and prioritizing alternative splicing neoantigens pVACsplice：预测和优先选择替代剪接新抗原的计算工具

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.034

My Hoang, Megan Richters, Susanna Kiwala, Obi Griffith, Malachi Griffith

Splicing neoantigens represent a rich yet underexplored source of tumor-specific targets for immunotherapy. Tumors exhibit increased mis-splicing events compared to normal tissues, which in turn create diverse isoforms that encode novel peptides. These peptides, especially ones derived from frameshifts, are highly distinct from self-antigens, hence presenting an opportunity for enhanced immune recognition.

Though neoantigens arising from somatic single-point mutations in coding regions have been widely targeted by cancer therapies, other neoantigen sources, including alternative splicing neoantigens haven't received the same amount of attention. Here, we develop pVACsplice, a tool that predicts and prioritizes cis-splicing associated neoantigen candidates. pVACsplice takes alternative transcripts as input, translates them into altered peptides, then constructs neoantigens of user-defined sizes. It then estimates binding affinities of neoepitopes with user-input MHC alleles, and prioritizes candidates based on various criteria (binding affinity, solubility, transcript quality, and more).

We then utilize pVACsplice to explore the splicing neoantigen landscape of a Small Cell Lung Cancer (SCLC) cohort. We find numerous neojunctions and neoantigen candidates associated with genes frequently mutated in this malignancy.

剪接新抗原是肿瘤特异性免疫疗法靶点的丰富来源，但尚未得到充分开发。与正常组织相比，肿瘤表现出更多的剪接错误，进而产生编码新肽的多种异构体。虽然编码区体细胞单点突变产生的新抗原已成为癌症疗法的广泛靶点，但包括替代剪接新抗原在内的其他新抗原来源还没有得到同等程度的关注。在这里，我们开发了 pVACsplice，这是一种预测顺式剪接相关新抗原候选物并对其进行优先排序的工具。pVACsplice 将替代转录本作为输入，将其转化为改变的肽，然后构建用户定义大小的新抗原。然后，它估算新表位与用户输入的 MHC 等位基因的结合亲和力，并根据各种标准（结合亲和力、溶解度、转录本质量等）对候选基因进行优先排序。然后，我们利用 pVACsplice 探索了小细胞肺癌（SCLC）队列中的剪接新抗原图谱。我们发现许多新连接和新抗原候选基因与这种恶性肿瘤中经常突变的基因有关。

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引用次数: 0

33. Customize your variant interpretation workflow with OpenCRAVAT 33.利用 OpenCRAVAT 自定义变体解释工作流程

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.035

Rachel Karchin , Jasmine Baker , Kyle Moad , Kyle Anderson , Madison Larsen , Supra Gajjala , James Higgins , Ben Busby

OpenCRAVAT is an open-source modular variant meta-annotator designed to make variant interpretation accessible to a wide audience. The modular design allows researchers to design customized workflows and utilize a diverse set of analysis methods, fostering a personalized approach to variant interpretation. While valuable information about variants is scattered across hundreds of databases and computational variant effect predictors, OpenCRAVAT centralizes access to these tools and makes them available through an easy-to-use interface. Hundreds of tools can be installed using point-and-click or simple command-line statements, and results are combined and presented in a variety of output formats. These tools cater to a broad range of variant types, encompassing germline, somatic, common, rare, coding and non-coding variants. We have recently introduced 'Packages', a new feature that consists of pre-configured combinations of annotators, filters, and output layouts that are focused on specific variant-related questions. For example, the Drug Interaction Package is designed to find pharmacogenomic annotations; the Hereditary Cancer Package finds rare variants in known hereditary cancer genes; and the Splicing Package focuses on variants associated with aberrant splicing. We are now adding support for annotation of large structural variants, comparison of genetic variants across user-defined patient cohorts, and a workflow for annotation of very large (UK-Biobank sized) cohorts in the cloud. To support neoantigen discovery, we provide annotations of epitopes in the Cancer Epitope Database and Analysis Resource (CEDAR). Finally, we provide a Single Variant Report application customized to the needs of molecular tumor boards, to assist oncologists in making treatment decisions.

OpenCRAVAT 是一个开源的模块化变异元注释器，旨在为广大受众提供变异解读服务。模块化设计使研究人员能够设计定制的工作流程，并利用各种分析方法，促进个性化的变异解释方法。有关变异的宝贵信息分散在数百个数据库和计算变异效应预测器中，而 OpenCRAVAT 则集中了这些工具，并通过一个易于使用的界面提供给用户。数百种工具可通过点击或简单的命令行语句进行安装，并以多种输出格式合并和显示结果。这些工具适用于广泛的变异类型，包括种系变异、体细胞变异、常见变异、罕见变异、编码变异和非编码变异。我们最近推出了 "软件包"，这是一项新功能，包括注释器、过滤器和输出布局的预配置组合，主要针对特定的变异相关问题。例如，"药物相互作用包 "旨在查找药物基因组注释；"遗传性癌症包 "查找已知遗传性癌症基因中的罕见变异；而 "剪接包 "则侧重于与异常剪接相关的变异。我们现在正在增加对大型结构变异注释的支持、对用户定义的患者队列中遗传变异的比较，以及在云中注释超大型（英国生物库规模）队列的工作流程。为了支持新抗原的发现，我们在癌症表位数据库和分析资源（CEDAR）中提供了表位注释。最后，我们根据分子肿瘤委员会的需求定制了单个变异报告应用程序，以协助肿瘤学家做出治疗决策。

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引用次数: 0

22. Advancing personalized prostate cancer care: Utilizing miRNA profiling and machine learning for metastasis prediction 22.推进个性化前列腺癌治疗：利用 miRNA 图谱和机器学习预测转移

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.024

Arun Seth , Gobi Thillainadesan , Yutaka Amemiya , Robert Nam

In the pursuit of advancing personalized medicine for prostate cancer treatment, the identification of critical biomarkers is crucial for tailoring therapies and improving patient outcomes. Building upon our prior research, where we conducted high-throughput small RNA sequencing on 38 post-operative prostate cancer patients matched by Gleason scores, this study aims to refine our understanding and enhance the accuracy of microRNA-based predictions through sophisticated computational biology techniques.

Through meticulous computational approaches and rigorous statistical analysis, we have identified microRNAs exhibiting significant expression differences between metastatic and non-metastatic cases post-surgery. This has led to the identification of six high-confidence microRNAs: miR-6761, miR-93-5p, miR-92a-3p, miR-149-5p, miR-429, and miR-671-5p, marking a significant advancement in post-operative care.

Expanding our dataset with an additional 100 supporting microRNAs, we are pioneering the training of a neural network machine learning algorithm. This innovative approach aims to accurately predict the risk of metastasis after surgery, providing a ground-breaking tool for personalized patient monitoring and treatment decision-making.

By integrating these biomarkers into a neural network model, we anticipate establishing a new standard in post-operative care for prostate cancer patients, ultimately guiding more effective monitoring strategies and improving quality of life. This study not only emphasizes the importance of microRNA profiling in prostate cancer prognosis clinical scenario but also showcases the potential of machine learning in revolutionizing cancer care.

在推进前列腺癌个性化治疗的过程中，关键生物标志物的鉴定对于调整疗法和改善患者预后至关重要。在我们之前的研究基础上，我们对 38 名术后前列腺癌患者进行了高通量小 RNA 测序，并根据格里森评分进行了配对。通过细致的计算方法和严格的统计分析，我们确定了在术后转移性和非转移性病例中表现出显著表达差异的 microRNA。我们通过细致的计算方法和严谨的统计分析，确定了在术后转移和非转移病例中表现出明显表达差异的 microRNA，这标志着我们在术后护理方面取得了重大进展。我们正在扩大数据集，增加 100 个支持性 microRNA，并率先训练神经网络机器学习算法。通过将这些生物标志物整合到神经网络模型中，我们预计将建立前列腺癌患者术后护理的新标准，最终指导更有效的监测策略并提高生活质量。这项研究不仅强调了 microRNA 图谱分析在前列腺癌预后临床方案中的重要性，还展示了机器学习在彻底改变癌症护理方面的潜力。

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引用次数: 0

63. An introduction to publicly available AI-assisted chatbot-style search engines for cancer variant curation 63.介绍用于癌症变异体整理的公开可用的人工智能辅助聊天机器人式搜索引擎

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.065

Beth Pitel, Antonina Wojcik, Christy Koellner, Claire Teigen, Katherine Geiersbach, Patricia Greipp, Xinjie Xu, Cinthya Zepeda Mendoza

Publicly available artificial intelligence (AI) chatbot-style search engines are gaining popularity for various applications, ranging from writing poetry to determining oncogenic cancer variants and genes. However, to our knowledge, a systematic evaluation of the effectiveness of these tools in cancer variant interpretation is lacking in current literature.

In this proof-of-concept study, four free online AI-assisted search engines (ChatGPT, Perplexity AI, Claude AI, and Llama2) were given simple standardized queries to investigate the clinical relevance of multiple gene variants observed in lung adenocarcinoma, glioma, and acute myeloid leukemia. The queries were structured as follows: 'What is the clinical significance of [GENE] [protein-level (p.) nomenclature] in [cancer type]?'

As anticipated, variants of uncertain significance (VUS) illustrated challenges for using AI-assisted search engines in cancer variant interpretation. Each tool incorrectly attributed oncogenicity to at least 1 of the 6 VUS investigated: Perplexity AI (1/6 VUS incorrectly represented as oncogenic), ChatGPT (2/6), Llama2 (4/6), Claude AI (5/6).

The overestimation of oncogenicity in these tools may be driven by conditioning of these AI-assisted search engines by past and current users for positive assignation attributes or from application of a response format with incorrect extrapolation of studies describing variants in the same gene without the ability to draw nuanced conclusions from studies focusing on different aspects of gene function. While there are challenges in using AI-assisted search engines in the clinical genomic space currently, this rapidly improving technology could provide a useful supplement for cancer variant analysts when combined with caution and expert human oversight.

公共可用的人工智能（AI）聊天机器人式搜索引擎在从写诗到确定致癌变异体和基因等各种应用中越来越受欢迎。在这项概念验证研究中，我们给四个免费的在线人工智能辅助搜索引擎（ChatGPT、Perplexity AI、Claude AI 和 Llama2）提供了简单的标准化查询，以调查在肺腺癌、胶质瘤和急性髓性白血病中观察到的多个基因变异的临床相关性。查询的结构如下'[基因][蛋白质级（p.）命名法]在[癌症类型]中的临床意义是什么？"正如预期的那样，意义不确定的变异（VUS）说明了在癌症变异解释中使用人工智能辅助搜索引擎所面临的挑战。在所调查的 6 个 VUS 中，每个工具都至少有 1 个错误地归因于致癌性：这些工具对致癌性的高估可能是由于过去和现在的用户对这些人工智能辅助搜索引擎的正向分配属性进行了调节，或者是由于应用了一种响应格式，对描述同一基因中变异的研究进行了错误的外推，而无法从关注基因功能不同方面的研究中得出细微的结论。虽然目前在临床基因组学领域使用人工智能辅助搜索引擎还存在一些挑战，但这种快速进步的技术如果能与谨慎和专家的人工监督相结合，就能为癌症变异分析人员提供有益的补充。

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引用次数: 0

1. Enrichment of Hodgkin and Reed-Sternberg (HRS) cells using size-based microfiltration 1.利用基于尺寸的微过滤富集霍奇金和里德-斯特恩伯格（HRS）细胞

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.003

Brianna Munnich , Kilannin Krysiak , Becca Brown , Richard Cote , Abdulrahman Saadalla , Anthony Williams , Mark Watson , Todd Fehniger , Siddarth Rawal

Large, multinucleated Reed-Sternberg and mononuclear Hodgkin (HRS) cells (50-100 µm and 20-30 µm, respectively) are pathognomonic features in Hodgkin Lymphoma (HL). Current methods available to isolate these cells are challenging, time-consuming, and low yield, making them unsuitable for clinical assays. To address these challenges, we sought to develop a method for HRS cell enrichment using size-based microfiltration. Originally created to enrich rare cells in the blood, these microfilters have 40,000, 8 µm pores which will remove small lymphocytes while capturing larger HRS cells of interest.

Using mixtures of L428s, an HL cell line, spiked into dissociated lymph node (LN), we demonstrated the ability to capture on average 93% of the input L428s. In our model, CD30, a cell surface marker expressed on HRS cells, was employed to identify the L428s from the background via immunofluorescent staining on-chip. Concurrently, we optimized a method for DNA extraction directly from the microfilter and reliably yielded over 3 µg of DNA. This DNA was then used for single nucleotide polymorphism genotyping which further verified our ability to enrich L428s from the LN. Finally, these experiments were replicated with a primary human HL sample with 3.75% HRS cells pre-enrichment and 58.25% HRS cells post-filtration. This level of enrichment and DNA yield will be sufficient to accomplish downstream clinical assays including high-throughput sequencing, liquid biopsy, and fluorescence in situ hybridization. Clinically, this workflow may allow us to ask new questions about the initiation of Hodgkins and the driving factors leading to metastasis and relapse.

大的多核里德-斯滕伯格细胞和单核霍奇金（HRS）细胞（分别为 50-100 微米和 20-30 微米）是霍奇金淋巴瘤（HL）的病理特征。目前可用来分离这些细胞的方法具有挑战性、耗时且产量低，因此不适合用于临床检测。为了应对这些挑战，我们试图开发一种利用基于尺寸的微过滤富集 HRS 细胞的方法。这些微滤器最初是为富集血液中的稀有细胞而设计的，有 40,000 个 8 µm 的孔，可以去除小的淋巴细胞，同时捕获感兴趣的较大的 HRS 细胞。我们使用 L428s（一种 HL 细胞系）混合物，将其添加到离体淋巴结（LN）中，证明了平均捕获 93% 输入 L428s 的能力。在我们的模型中，CD30 是一种在 HRS 细胞上表达的细胞表面标记物，通过芯片上的免疫荧光染色从背景中识别出 L428s。同时，我们优化了直接从微滤器中提取 DNA 的方法，并可靠地获得了超过 3 µg 的 DNA。这些 DNA 随后被用于单核苷酸多态性基因分型，进一步验证了我们从 LN 中富集 L428s 的能力。最后，这些实验在原代人类 HL 样本中进行了复制，富集前 HRS 细胞占 3.75%，过滤后 HRS 细胞占 58.25%。这种富集水平和DNA产量足以完成下游临床检测，包括高通量测序、液体活检和荧光原位杂交。在临床上，这种工作流程可以让我们提出有关霍奇金病的起始以及导致转移和复发的驱动因素的新问题。

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引用次数: 0

5. Implementation of Automatic Slide Processing for Aneuploidy FISH Test 5.为非整倍体 FISH 检测实现自动切片处理

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.007

Wenhua Zhou, Eric Fredrickson, Maria Longhurst, Emily Aston, Bo Hong

The AneuVysion FISH probe kit is FDA approved for detecting aneuploidy of chromosomes X, Y, 13, 18 and 21 on amniocytes (AF). Clinically, this kit is also used to identify numerical abnormalities in other specimen types, including chorionic villi sampling (CVS), cord blood, and peripheral blood. Currently, the majority of FISH tests in our lab have been adapted to the automatic slide processing system - BioDot instruments. Therefore, a validation was conducted to integrate the procedure of aforementioned Aneuploidy FISH test into the BioDot instruments. During the development phase, 34 cases were processed following the standard BioDot protocol with the exception of AF and CVS. Cell pellets from AF and CVS being manually applied onto slides due to the low cellularity. The FISH signal intensity and background were compared based on a 0 -7 scale. The FISH signal intensity was comparable between the slides processed by Biodot protocol and the lab current protocol (5.0 vs 4.8, p =4.8); the background score improved on the slides with the Biodot procedure (5.3 vs 5.1, p = 0.01). Subsequently, 21 cases for accuracy and 12 cases for precision (between run and within run) were tested on BioDot instruments for validation. These cases demonstrated 100% concordant FISH results with those from the current manual procedures. This study suggests that the traditional FDA-approved FISH Aneuvysion test can be seamlessly adapted to our standard Biodot FISH slide processing. This transition will streamline lab workflow, increase work efficiency, better FISH test quality and improve cost effectiveness.

AneuVysion FISH 探针试剂盒经 FDA 批准用于检测羊膜细胞（AF）上 X、Y、13、18 和 21 染色体的非整倍体。在临床上，该试剂盒还可用于鉴定其他类型标本中的染色体数目异常，包括绒毛取样（CVS）、脐带血和外周血。目前，我们实验室的大多数 FISH 检测都已适用于自动玻片处理系统 - BioDot 仪器。因此，我们进行了一项验证，将上述非整倍体 FISH 检测程序整合到 BioDot 仪器中。在开发阶段，除 AF 和 CVS 外，按照标准 BioDot 方案处理了 34 个病例。由于 AF 和 CVS 中的细胞颗粒较少，因此采用手工将细胞颗粒贴在载玻片上。FISH 信号强度和背景根据 0-7 级进行比较。采用 Biodot 方案和实验室现行方案处理的玻片的 FISH 信号强度相当（5.0 vs 4.8，p =4.8）；采用 Biodot 方案处理的玻片的背景得分有所提高（5.3 vs 5.1，p =0.01）。随后，在 BioDot 仪器上对 21 个病例的准确性和 12 个病例的精确性（运行间和运行内）进行了验证测试。这些病例的 FISH 结果与当前手动程序的结果 100%一致。这项研究表明，传统的 FDA 批准的 FISH Aneuvysion 检验可以无缝地适应我们的标准 Biodot FISH 玻片处理。这一转变将简化实验室工作流程、提高工作效率、改善 FISH 检测质量并提高成本效益。

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引用次数: 0

38. Formation of a tumor-specific gene list: The Central Nervous System (CNS) tumor taskforce experience 38.制定肿瘤特异性基因列表：中枢神经系统（CNS）肿瘤工作组的经验

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.040

Madina Sukhanova , Cristiane Ida , Xiaolin Hu , Pouya Jamshidi , Malak Abedalthgafi , Stewart Neil , Laveniya Satgunaseelan

Modern molecular diagnostic tests allow detection of various genomic aberrations simultaneously. There are multiple recommendations to guide analysis of gene alterations in the somatic setting. However, resources for interpretation of tumor-type specific gene(s) are limited but are imperative for reliable and timely reporting of oncological molecular test results. Tumor-type specific gene lists enable the compilation of a comprehensive set of scrutinized genes with clinical implication. Our group extracted 670 genes from the TCGA CNS database, WHO Classification of CNS tumors and EANO guidelines. Gene-specific information including association with different tumor entities, type of alterations, mechanism of action, and hereditary risk if germline, were assessed. We applied the proposed framework for curation of cancer-specific gene lists created by collaborative effort of two Cancer Genomics Consortium Committees (Educational and GRDC) and modified the proposed criteria, including gene list creation and standardization. Each gene was reviewed independently by two reviewers who conducted literature searches for patient-based studies. We then assembled a detailed list of genes altered in CNS tumors and assessed their clinical relevance using categories of diagnostic, prognostic and therapeutic significance. Level of significance for each category was graded; 1 as 'recognized by guidelines', 2 as having 'supportive level of significance' in guidelines, and 3 as evidence of 'emerging data' for inclusion. Here we present the final list of 450 prioritized genes with specific criteria for assessment of significance pertaining to CNS tumors. Genes with insufficient evidence for inclusion were moved to a 'parking lot' list for future re-evaluation.

现代分子诊断测试可同时检测各种基因组畸变。有多种建议指导体细胞基因改变的分析。然而，用于解读肿瘤类型特异基因的资源有限，但这对于可靠、及时地报告肿瘤分子检测结果至关重要。肿瘤类型特异性基因列表可以汇编一套具有临床意义的全面的受检基因。我们小组从 TCGA 中枢神经系统数据库、世界卫生组织中枢神经系统肿瘤分类和 EANO 指南中提取了 670 个基因。我们评估了基因的特异性信息，包括与不同肿瘤实体的关联、改变类型、作用机制以及种系遗传风险。我们采用了由两个癌症基因组学联盟委员会（教育委员会和癌症基因组学委员会）合作创建的癌症特异性基因列表整理框架，并修改了建议的标准，包括基因列表的创建和标准化。每个基因都由两名审稿人独立审查，他们对基于患者的研究进行文献检索。然后，我们汇总了中枢神经系统肿瘤中发生改变的基因的详细列表，并按照诊断、预后和治疗意义的类别对其临床相关性进行了评估。对每个类别的重要性程度进行了分级：1 级为 "得到指南认可"，2 级为在指南中具有 "支持性意义"，3 级为有证据表明存在 "新出现的数据"，可以纳入。在此，我们列出了 450 个优先基因的最终清单，并附有中枢神经系统肿瘤相关重要性的具体评估标准。没有足够证据纳入的基因被移至 "停车场 "列表，以便将来重新评估。

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引用次数: 0

40. Prioritization of defining and supportive diagnostic variants in pediatric tumors 40.确定儿科肿瘤定义性和支持性诊断变异的优先次序

IF 1.4 4区医学 Q4 GENETICS & HEREDITY

Cancer Genetics

Pub Date : 2024-08-01 DOI: 10.1016/j.cancergen.2024.08.042

Laura B. Corson , Jason Saliba , Laveniya Satgunaseelan , Dianne E. Sylvester , Sara Akhavanfard , Yassmine Akkari , Alanna J. Church , Arpad Danos , Annie Garcia , Shivani Golem , Bo Hong , Jianling Ji , Kilannin Krysiak , Minjie Luo , Mariam T. Mathew , Elena Repnikova , Zonggao Shi , Morteza Seifi , Madina Sukhanova , Yiming Zhong , Gordana Raca

Roughly half of the genomic alterations in pediatric cancers are not present in common adult cancers and are underrepresented in oncology knowledgebases. As many of these are fusions or large genomic rearrangements, they may be missed by standard analytic pipelines. Additionally, gene panels (biased towards adult cancers) may not include critical genes recurrently mutated in pediatric cancers. Therefore, it is important for sequencing centers processing pediatric tumor samples to have a comprehensive list of variants that have clinical impact in pediatric cancers.

To facilitate and improve tumor profiling for pediatric patients, the Pediatric Taskforce of the ClinGen Somatic Cancer Clinical Domain Working Group has used the Pediatric Tumours volume of the WHO Classification of Tumours Online to extract recurrent genomic alterations in non-benign diagnoses with diagnostic, prognostic, or therapeutic significance. Diagnostic variants were divided into 2 categories, 'defining' and 'supportive'. Defining variants, such as MYOD1 L122R (spindle cell/sclerosing rhabdomyosarcoma), provide a strong indication of the diagnosis in the absence of any additional tumor information. Supportive diagnostic variants, like SMARCB1 loss in malignant rhabdoid tumors, may aid in diagnosis when coupled with additional information such as tumor histology or location. Due to the importance of recognizing these alterations in pediatric tumors, we have prioritized 99 defining variants and 71 supportive variants considered essential for diagnosis in 105 pediatric malignancies for curation in CIViC (www.civicdb.org). This includes 134 fusions/rearrangements and 36 SNVs/CNVs that will be discussed in this presentation.

儿科癌症中约有一半的基因组改变在常见的成人癌症中并不存在，在肿瘤学知识库中的代表性不足。由于其中许多是融合或大的基因组重排，标准的分析管道可能会漏掉它们。此外，基因面板（偏重于成人癌症）可能不包括儿科癌症中反复突变的关键基因。因此，对于处理儿科肿瘤样本的测序中心来说，拥有一份对儿科癌症有临床影响的变异的综合列表非常重要。为了促进和改善儿科患者的肿瘤图谱分析，ClinGen体细胞癌症临床领域工作组儿科专责小组利用《世界卫生组织肿瘤分类在线》的儿科肿瘤卷提取了非良性诊断中具有诊断、预后或治疗意义的复发性基因组改变。诊断性变异分为两类："定义性 "和 "支持性"。定义性变异，如 MYOD1 L122R（纺锤形细胞/硬化性横纹肌肉瘤），可在没有任何其他肿瘤信息的情况下提供强有力的诊断提示。辅助诊断变异，如恶性横纹肌瘤中的 SMARCB1 缺失，如果与肿瘤组织学或位置等其他信息相结合，可能有助于诊断。鉴于识别儿科肿瘤中这些变异的重要性，我们在 105 种儿科恶性肿瘤中优先选择了 99 个定义性变异和 71 个辅助性变异，认为这些变异对诊断至关重要，并在 CIViC 中进行了整理 (www.civicdb.org)。其中包括 134 个融合/重排变异和 36 个 SNV/CNV，这些变异将在本报告中讨论。

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引用次数: 0