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81.
颜林林 (2022-07-01 07:57):
#paper doi:10.1101/2022.06.27.497710 bioRxiv, 2022, PaliDIS: A tool for fast discovery of novel insertion sequences. 这是一篇有关的生信工具的文章,通讯作者来自Wellcome Sanger Institute。该工具从宏基因组数据中,寻找彼此之间含有相同重复片段的序列,将其比对到各组装好的微生物基因组上,将连锁位于同一组装序列且彼此反向互补的重复片段筛选出来,并经过一系列质控过滤,从而鉴别出在微生物基因组上发生的倒位形式的移动元件,以此帮助对耐药基因及其在不同菌种之间传播进行研究。类似流程在人类基因组分析中并不少见,且基本都是根据基因组事件及其序列特征直接进行实现,方法本身算不上有什么特别的创新之处。只不过应用于特定场景的特定数据集(在这篇文章里,数据是来自HMP,Human Microbiome Project,人类微生物计划),对分析结果进行(关于该移动元件的)统计描述和分析,倒是可行且常见的研究套路。
Abstract:
The diversity of microbial insertion sequences, crucial mobile genetic elements in generating diversity in microbial genomes, needs to be better represented in current microbial databases. Identification of these sequences in … >>>
The diversity of microbial insertion sequences, crucial mobile genetic elements in generating diversity in microbial genomes, needs to be better represented in current microbial databases. Identification of these sequences in microbiome communities presents some significant problems that have led to their underrepresentation. Here, we present a software tool called PaliDIS that recognises insertion sequences in metagenomic sequence data rapidly by identifying inverted terminal repeat regions from mixed microbial community genomes. Applying this software to 266 human metagenomes identifies 11,681 unique insertion sequences. Querying this catalogue against a large database of isolate genomes reveals evidence of horizontal gene transfer events of clinically relevant antimicrobial resistance genes between classes of bacteria. We will continue to apply this tool more widely, building the Insertion Sequence Catalogue, a valuable resource for researchers wishing to query their microbial genomes for insertion sequences. <<<
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82.
颜林林 (2022-06-30 00:17):
#paper doi:10.1038/s41597-022-01450-y Scientific Data, 2022, HunCRC: annotated pathological slides to enhance deep learning applications in colorectal cancer screening. 《Nature》子刊《Scientific Data》确实是宝藏。这篇来自匈牙利的论文,就分享了一组很有用的数据。取材了200张H&E染色的结直肠癌的肿瘤组织切片,使用40倍高分辨率扫描全片,然后由病理医生进行标注,从中切分出多个不同类别的图像块,可用于后续结直肠癌的各类病理图像分析研究。值得夸赞的是,从样本采集到数据处理,整个过程有详细描述,数据处理代码、带标注的原始图像、处理后的带分类信息的图像块,全部都开放供直接下载使用。 代码地址: https://github.com/qbeer/qupath-binarymask-extension https://github.com/patbaa/crc_data_paper 原始图像数据: https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=91357370 处理后数据: https://figshare.com/articles/dataset/patches_and_local_annotations_slide_200_zoom_124x124_um2/19500266
IF:5.800Q1 Scientific data, 2022-06-28. DOI: 10.1038/s41597-022-01450-y PMID: 35764660
Abstract:
Histopathology is the gold standard method for staging and grading human tumors and provides critical information for the oncoteam's decision making. Highly-trained pathologists are needed for careful microscopic analysis of … >>>
Histopathology is the gold standard method for staging and grading human tumors and provides critical information for the oncoteam's decision making. Highly-trained pathologists are needed for careful microscopic analysis of the slides produced from tissue taken from biopsy. This is a time-consuming process. A reliable decision support system would assist healthcare systems that often suffer from a shortage of pathologists. Recent advances in digital pathology allow for high-resolution digitalization of pathological slides. Digital slide scanners combined with modern computer vision models, such as convolutional neural networks, can help pathologists in their everyday work, resulting in shortened diagnosis times. In this study, 200 digital whole-slide images are published which were collected via hematoxylin-eosin stained colorectal biopsy. Alongside the whole-slide images, detailed region level annotations are also provided for ten relevant pathological classes. The 200 digital slides, after pre-processing, resulted in 101,389 patches. A single patch is a 512 × 512 pixel image, covering 248 × 248 μm tissue area. Versions at higher resolution are available as well. Hopefully, HunCRC, this widely accessible dataset will aid future colorectal cancer computer-aided diagnosis and research. <<<
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83.
颜林林 (2022-06-29 22:30):
#paper doi:10.1002/humu.24424 Human Mutation, 2022, Screening of potential novel candidate genes in schwannomatosis patients. 这篇论文研究的是神经鞘瘤病(Schwannomatosis),是一种由周围神经的神经鞘所形成的肿瘤,该疾病与遗传有很大关系,通常会筛查NF2、SMARCB1和LZTR1这三个基因的胚系突变。然而,仍有相当大比例的患者并不携带这三个基因的突变,提示存在其他致病基因,本文则为寻找这样的基因。研究纳入了来自75个家庭的散发患者,这些患者均经筛查未携带上述三个基因的致病突变,于是采用NGS、MLPA、PCR+Sanger等方法,扩展筛查范围,找到DGCR8、COQ6、CDKN2A和CDKN2B等基因携带致病突变,结合既往文献研究,推断它们与该疾病发生相关,为后续研究该疾病的发病机制提供了证据提示。本文的研究逻辑和方法,也是拓展遗传病致病基因的常规研究套路。
IF:3.300Q2 Human mutation, 2022-10. DOI: 10.1002/humu.24424 PMID: 35723634
Abstract:
Schwannomatosis comprises a group of hereditary tumor predisposition syndromes characterized by, usually benign, multiple nerve sheath tumors, which frequently cause severe pain that does not typically respond to drug treatments. … >>>
Schwannomatosis comprises a group of hereditary tumor predisposition syndromes characterized by, usually benign, multiple nerve sheath tumors, which frequently cause severe pain that does not typically respond to drug treatments. The most common schwannomatosis-associated gene is NF2, but SMARCB1 and LZTR1 are also associated. There are still many cases in which no pathogenic variants (PVs) have been identified, suggesting the existence of as yet unidentified genetic risk factors. In this study, we performed extended genetic screening of 75 unrelated schwannomatosis patients without identified germline PVs in NF2, LZTR1, or SMARCB1. Screening of the coding region of DGCR8, COQ6, CDKN2A, and CDKN2B was carried out, based on previous reports that point to these genes as potential candidate genes for schwannomatosis. Deletions or duplications in CDKN2A, CDKN2B, and adjacent chromosome 9 region were assessed by multiplex ligation-dependent probe amplification analysis. Sequencing analysis of a patient with multiple schwannomas and melanomas identified a novel duplication in the coding region of CDKN2A, disrupting both p14ARF and p16INK4a. Our results suggest that none of these genes are major contributors to schwannomatosis risk but the possibility remains that they may have a role in more complex mechanisms for tumor predisposition. <<<
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84.
颜林林 (2022-06-28 07:39):
#paper doi:10.1101/2022.06.22.497216 bioRxiv, 2022, Intratumoral mregDC and CXCL13 T helper niches enable local differentiation of CD8 T cells following PD-1 blockade. 这篇文章来自西奈山伊坎医学院,其病例队列出自一项用于非小细胞肺癌(NSCLC)、肝细胞癌(HCC)和头颈部鳞癌(HNSCC)的手术前抗PD-1免疫药物(西米普利单抗,Cemiplimab)新辅助治疗的多中心II期临床试验(NCT03916627,该临床试验尚在进行中,始于2019年,预计2024年完成)。本文仅针对其中的肝细胞癌患者,通过对其新辅助治疗后手术取样组织,开展TCR测序、全外显子测序、单细胞转录组测序、多重免疫组化等实验,寻找与新辅助治疗疗效相关的特定细胞类群。通过免疫组化和免疫荧光方法,确认在肿瘤中确实富含T细胞并浸润其中的患者,仍有部分患者对PD-1药物并无响应。对比响应者与无响应者之间的细胞类群组成差异,找到一个细胞类群组合,成熟调节树突状细胞(mregDC,LAMP3+)与 CXCL13+ CD4+ 辅助性T细胞,它们与 PD-1高表达的CD8+ T细胞前体结合,形成三元组,促使后者形成 PD-1高表达的 GZMK+ 效应T细胞。而在没有这两类细胞的情况下,后者将形成耗竭型CD8+ T细胞。这导致了该新辅助治疗的不同预后结局。这项研究也为进一步揭示免疫治疗相关机制提供了新的证据。
Abstract:
Here, we leveraged a large neoadjuvant PD-1 blockade trial in patients with hepatocellular carcinoma (HCC) to search for correlates of response to immune checkpoint blockade (ICB) within T cell-rich tumors. … >>>
Here, we leveraged a large neoadjuvant PD-1 blockade trial in patients with hepatocellular carcinoma (HCC) to search for correlates of response to immune checkpoint blockade (ICB) within T cell-rich tumors. We show that ICB response correlated with the clonal expansion of intratumoral CXCL13+ CH25H+ IL-21+ PD-1+ CD4 T helper cells (CXCL13+ Th) and Granzyme K+ PD-1+ effector-like CD8 T cells, whereas terminally exhausted CD39hi TOXhi PD-1hi CD8 T cells dominated in non-responders. Strikingly, most T cell receptor (TCR) clones that expanded post-treatment were found in pre-treatment biopsies. Notably, PD-1+ TCF-1+ progenitor-like CD8 T cells were present in tumors of responders and non-responders and shared clones mainly with effector-like cells in responders or terminally differentiated cells in non-responders, suggesting that local CD8 T cell differentiation occurs upon ICB. We found that these progenitor CD8 T cells interact with CXCL13+ Th cells within cellular triads around dendritic cells enriched in maturation and regulatory molecules, or "mregDC". Receptor-ligand analysis revealed unique interactions within these triads that may promote the differentiation of progenitor CD8 T cells into effector-like cells upon ICB. These results suggest that discrete intratumoral niches that include mregDC and CXCL13+ Th cells control the differentiation of tumor-specific progenitor CD8 T cell clones in patients treated with ICB. <<<
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85.
颜林林 (2022-06-27 00:24):
#paper doi:10.3390/diagnostics12061493 Diagnostics, 2022, MixPatch: A New Method for Training Histopathology Image Classifiers. 病理图像分析中,由于原始全片数据量太大(通常为5万x5万像素),很难直接丢入DNN模型,故通常会进行切分,形成大量图块(patch),逐一进行分析(训练或预测)。对于每个图块,一般会由病理医生进行注释,确定其临床特征(如是否恶性肿瘤区域)。该临床特征一般是“是或否”的二分状态。然而,事实上很多分块会同时包含良性或恶性的不同类型区域,这种“不确定”的图块,会造成模型的误判和性能损失。本文的研究,采取最小图块(128x128像素,被病理医生认为最小可识别区域),以便给出“干净”的金标准数据集,并在此基础上,合并相邻最小图块(一般9个或16个,即3x3或4x4),得到“混合的图块(mix patch)”,并根据组合前原始信息,给出对该“混合图块”的结果的可信度估计。这其实是个模糊集合的理念。而通过这般操作,使得病理分析的性能得到了提升,且在对全片水平(slide level)进行的预测中也取得了更好的结果。
Abstract:
CNN-based image processing has been actively applied to histopathological analysis to detect and classify cancerous tumors automatically. However, CNN-based classifiers generally predict a label with overconfidence, which becomes a serious … >>>
CNN-based image processing has been actively applied to histopathological analysis to detect and classify cancerous tumors automatically. However, CNN-based classifiers generally predict a label with overconfidence, which becomes a serious problem in the medical domain. The objective of this study is to propose a new training method, called MixPatch, designed to improve a CNN-based classifier by specifically addressing the prediction uncertainty problem and examine its effectiveness in improving diagnosis performance in the context of histopathological image analysis. MixPatch generates and uses a new sub-training dataset, which consists of mixed-patches and their predefined ground-truth labels, for every single mini-batch. Mixed-patches are generated using a small size of clean patches confirmed by pathologists while their ground-truth labels are defined using a proportion-based soft labeling method. Our results obtained using a large histopathological image dataset shows that the proposed method performs better and alleviates overconfidence more effectively than any other method examined in the study. More specifically, our model showed 97.06% accuracy, an increase of 1.6% to 12.18%, while achieving 0.76% of expected calibration error, a decrease of 0.6% to 6.3%, over the other models. By specifically considering the mixed-region variation characteristics of histopathology images, MixPatch augments the extant mixed image methods for medical image analysis in which prediction uncertainty is a crucial issue. The proposed method provides a new way to systematically alleviate the overconfidence problem of CNN-based classifiers and improve their prediction accuracy, contributing toward more calibrated and reliable histopathology image analysis. <<<
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86.
颜林林 (2022-06-26 22:13):
#paper doi:10.1371/journal.pcbi.1009730 PLOS Computational Biology, 2022, Improved transcriptome assembly using a hybrid of long and short reads with StringTie. 这篇文章来自Johns Hopkins,开发了一个能够混合使用长读长及短读长测序数据进行转录组拼装的工具。高通量测序数据中,短读长平台的准确性高,但读长较短,难以覆盖完整转录本,而长读长平台虽然可以跨越多个外显子,帮助确定转录本剪切方式,但由于碱基准确度相对较差,因而也容易在比对时造成错误,影响转录本的确定。本文的工具,展示了由于测序错误导致的“嘈杂”比对,以及由此导致的搜索空间大幅增加。通过使用图论中的最大流量问题的解法,以及在“嘈杂”比对局部使用更准确的短读长数据,帮助确定正确的剪切位点,从而实现综合两种平台(长读长与短读长)的优势,且运算速度也并不弱于以往使用单一数据的工具算法。为评估此工具,本文除了使用模拟数据外,同时也选择了拟南芥、小鼠和人的多套真实数据集,在组装精读和输出的可正确注释的转录本等方面,都表现出符合预期的更好成绩。
Abstract:
Short-read RNA sequencing and long-read RNA sequencing each have their strengths and weaknesses for transcriptome assembly. While short reads are highly accurate, they are rarely able to span multiple exons. … >>>
Short-read RNA sequencing and long-read RNA sequencing each have their strengths and weaknesses for transcriptome assembly. While short reads are highly accurate, they are rarely able to span multiple exons. Long-read technology can capture full-length transcripts, but its relatively high error rate often leads to mis-identified splice sites. Here we present a new release of StringTie that performs hybrid-read assembly. By taking advantage of the strengths of both long and short reads, hybrid-read assembly with StringTie is more accurate than long-read only or short-read only assembly, and on some datasets it can more than double the number of correctly assembled transcripts, while obtaining substantially higher precision than the long-read data assembly alone. Here we demonstrate the improved accuracy on simulated data and real data from Arabidopsis thaliana, Mus musculus, and human. We also show that hybrid-read assembly is more accurate than correcting long reads prior to assembly while also being substantially faster. StringTie is freely available as open source software at https://github.com/gpertea/stringtie. <<<
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87.
颜林林 (2022-06-25 20:26):
#paper doi:10.3390/s22124409 Sensors, 2022, Deep Neural Networks Applied to Stock Market Sentiment Analysis. 这篇来自葡萄牙的关于深度学习技术应用的论文,被发现和推送自PubMed(PMID:35746192)。文章主要介绍了如何使用深度神经网络,从社交网站(Twitter、Reddit等)的文字内容,推断其情绪分类(积极或消极),并利用此情绪结果,进行模拟投资,以评估其投资收益率。文章内容算不上有太多创新价值,不过其认真介绍DL技术原理、实现和评估过程,倒是有点像一篇教程。反而是关于股市及投资的内容,显得有些割裂,像是强行补充。因为其深度模型的性能评估,也还是仅仅针对情绪分类进行的。作者在文末展望之处还提到,后续打算引入数据流技术(data streaming technology),使该分析过程能够实时进行,倒或许会指出更多合适的新应用场景。
Abstract:
The volume of data is growing exponentially and becoming more valuable to organizations that collect it, from e-commerce data, shipping, audio and video logs, text messages, internet search queries, stock … >>>
The volume of data is growing exponentially and becoming more valuable to organizations that collect it, from e-commerce data, shipping, audio and video logs, text messages, internet search queries, stock market activity, financial transactions, the Internet of Things, and various other sources. The major challenges are related with the way to extract insights from such a rich data environment and whether Deep Learning can be successful with Big Data. To get some insight on these topics, social network data are employed as a case study on how sentiments can affect decisions in stock market environments. In this paper, we propose a generalized Deep Learning-based classification framework for Stock Market Sentiment Analysis. This work comprises the study, the development, and implementation of an automatic classification system based on Deep Learning and the validation of its adequacy and efficiency in any scenario, particularly Stock Market Sentiment Analysis. Distinct datasets and several Deep Learning approaches with different layers and embedded techniques are used, and their performances are evaluated. These developments show how Deep Learning reacts to distinct contexts. The results also give context on how different techniques with different parameter combinations react to certain types of data. Convolution obtained the best results when dealing with complex data inputs, and long short-term layers kept a memory of data, allowing inputs which are not as common to still be considered for decisions. The models that resulted from Stock Market Sentiment Analysis datasets were applied with some success to real-life problems. The best models reached accuracies of 73% in training and 69% in certain test datasets. In a simulation, a model was able to provide a Return on Investment of 4.4%. The results contribute to understanding how to process Big Data efficiently using Deep Learning and specialized hardware techniques. <<<
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88.
颜林林 (2022-06-24 21:32):
#paper doi:10.1038/s41587-022-01294-2 Nature Biotechnology, 2022, The clinical progress of mRNA vaccines and immunotherapies. 这是一篇关于mRNA疫苗的长篇综述。使用mRNA作为载体开发疫苗的概念,始于1990年,它通过借用接种者身体内的蛋白质翻译机制来产生靶蛋白,而非直接注射(灭活或减活)病原体或靶蛋白本身。这种方式带来一系列优点,诸如设计简便、固有免疫原性、可快速量产等。当然,它也存在诸如稳定性差、疫苗在体内递送至目标位置困难等缺点或挑战。在新冠疫情爆发以来的这三年里,借着大量资金投入增加、紧急使用授权等机会,mRNA疫苗的研发及投产使用得到了极大加速。本文对这些发展,包括给药递送方法,针对传染病的疫苗研发、使用及优化,针对癌症治疗的疫苗方法,mRNA疫苗在蛋白质和细胞免疫治疗中的使用等,都做了比较详细的综述介绍,并据此讨论了当前存在的问题和未来研发方向。通篇读下来,能对mRNA疫苗及其技术路线形成比较深入的了解,也确实能体会到这是个潜力巨大、值得探索和继续研发的重要技术体系。
IF:33.100Q1 Nature biotechnology, 2022-06. DOI: 10.1038/s41587-022-01294-2 PMID: 35534554
Abstract:
The emergency use authorizations (EUAs) of two mRNA-based severe acute respiratory syndrome coronavirus (SARS-CoV)-2 vaccines approximately 11 months after publication of the viral sequence highlights the transformative potential of this … >>>
The emergency use authorizations (EUAs) of two mRNA-based severe acute respiratory syndrome coronavirus (SARS-CoV)-2 vaccines approximately 11 months after publication of the viral sequence highlights the transformative potential of this nucleic acid technology. Most clinical applications of mRNA to date have focused on vaccines for infectious disease and cancer for which low doses, low protein expression and local delivery can be effective because of the inherent immunostimulatory properties of some mRNA species and formulations. In addition, work on mRNA-encoded protein or cellular immunotherapies has also begun, for which minimal immune stimulation, high protein expression in target cells and tissues, and the need for repeated administration have led to additional manufacturing and formulation challenges for clinical translation. Building on this momentum, the past year has seen clinical progress with second-generation coronavirus disease 2019 (COVID-19) vaccines, Omicron-specific boosters and vaccines against seasonal influenza, Epstein-Barr virus, human immunodeficiency virus (HIV) and cancer. Here we review the clinical progress of mRNA therapy as well as provide an overview and future outlook of the transformative technology behind these mRNA-based drugs. <<<
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89.
颜林林 (2022-06-23 07:02):
#paper doi:10.1186/s12859-022-04768-x BMC Bioinformatics, 2022, Using BERT to identify drug-target interactions from whole PubMed. 这篇文章通过使用自然语言处理技术中BERT模型,批量分析了PubMed和PMC的全数据库,从文章中识别出药物和蛋白质信息,并提取药物-靶点相互作用(DTI)数据,包括对应所使用的实验方法类别等重要信息。通过本文的方法,新识别出的60万篇文章,都未被公共DTI数据库所包含。通过人工抽查审核和较差验证的方法,确认了该方法的准确度(99%以上)。通常这类数据的文献挖掘和整理,都依赖于人工,在效率上存在很大局限。诸如本文的人工智能方法,将为药物发现和重定位、加快药物开发等提供帮助。
IF:2.900Q1 BMC bioinformatics, 2022-Jun-21. DOI: 10.1186/s12859-022-04768-x PMID: 35729494
Abstract:
BACKGROUND: Drug-target interactions (DTIs) are critical for drug repurposing and elucidation of drug mechanisms, and are manually curated by large databases, such as ChEMBL, BindingDB, DrugBank and DrugTargetCommons. However, the … >>>
BACKGROUND: Drug-target interactions (DTIs) are critical for drug repurposing and elucidation of drug mechanisms, and are manually curated by large databases, such as ChEMBL, BindingDB, DrugBank and DrugTargetCommons. However, the number of curated articles likely constitutes only a fraction of all the articles that contain experimentally determined DTIs. Finding such articles and extracting the experimental information is a challenging task, and there is a pressing need for systematic approaches to assist the curation of DTIs. To this end, we applied Bidirectional Encoder Representations from Transformers (BERT) to identify such articles. Because DTI data intimately depends on the type of assays used to generate it, we also aimed to incorporate functions to predict the assay format.RESULTS: Our novel method identified 0.6 million articles (along with drug and protein information) which are not previously included in public DTI databases. Using 10-fold cross-validation, we obtained ~ 99% accuracy for identifying articles containing quantitative drug-target profiles. The F1 micro for the prediction of assay format is 88%, which leaves room for improvement in future studies.CONCLUSION: The BERT model in this study is robust and the proposed pipeline can be used to identify previously overlooked articles containing quantitative DTIs. Overall, our method provides a significant advancement in machine-assisted DTI extraction and curation. We expect it to be a useful addition to drug mechanism discovery and repurposing. <<<
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90.
颜林林 (2022-06-22 00:43):
#paper doi:10.1038/s41591-022-01768-5 Nature Medicine, 2022, Swarm learning for decentralized artificial intelligence in cancer histopathology. 前段时间刚在Nature上一篇文章(doi:10.1038/s41586-021-03583-3)读到Swarm learning(群体学习),该文提及一种在不违反隐私法规的前提下进行临床数据共享,从而帮助针对那些普遍存在异质性的疾病开展精准医学研究。本文则是针对肿瘤病理图像分析,也使用群体学习技术。病理图像分析,是典型的需要依赖大量高质量数据集的研究方向,群体学习正好使得合作单位可以共同训练AI模型,同时又避免数据传输和数据垄断。本文基于来自爱尔兰、德国和美国的三个结直肠癌患者队列训练了模型,该模型通过分析患者的H&E染色切片,预测其驱动基因突变、dMMR突变和微卫星不稳定性状态(MSI)等,并在来自英国的两个独立队列数据集中进行模型的性能验证。在训练模型的三个数据节点(研究中心)之间,并不直接传递原始数据,而是在每次迭代步骤中,通过去中心化的区块链技术,进行模型参数的同步。也因此,各数据节点之间是对等的,并没有需要汇总其他节点的特殊中心节点。这种模式为将来拓展到更大范围、更多机构的合作,提供了可能性,也将使病理图像分析模型得到更大进步。
IF:58.700Q1 Nature medicine, 2022-06. DOI: 10.1038/s41591-022-01768-5 PMID: 35469069 PMCID:PMC9205774
Abstract:
Artificial intelligence (AI) can predict the presence of molecular alterations directly from routine histopathology slides. However, training robust AI systems requires large datasets for which data collection faces practical, ethical … >>>
Artificial intelligence (AI) can predict the presence of molecular alterations directly from routine histopathology slides. However, training robust AI systems requires large datasets for which data collection faces practical, ethical and legal obstacles. These obstacles could be overcome with swarm learning (SL), in which partners jointly train AI models while avoiding data transfer and monopolistic data governance. Here, we demonstrate the successful use of SL in large, multicentric datasets of gigapixel histopathology images from over 5,000 patients. We show that AI models trained using SL can predict BRAF mutational status and microsatellite instability directly from hematoxylin and eosin (H&E)-stained pathology slides of colorectal cancer. We trained AI models on three patient cohorts from Northern Ireland, Germany and the United States, and validated the prediction performance in two independent datasets from the United Kingdom. Our data show that SL-trained AI models outperform most locally trained models, and perform on par with models that are trained on the merged datasets. In addition, we show that SL-based AI models are data efficient. In the future, SL can be used to train distributed AI models for any histopathology image analysis task, eliminating the need for data transfer. <<<
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91.
颜林林 (2022-06-21 00:03):
#paper doi:10.1016/j.jmoldx.2022.05.003 The Journal of Molecular Diagnostics, 2022, Comprehensive Validation of Diagnostic Next-Generation Sequencing Panels for Acute Myeloid Leukemia (AML) Patients. 这是来自瑞士和德国的一篇关于血液肿瘤基因检测panel验证的文章。通常认为,肿瘤是遗传病,即由于遗传物质发生突变而导致的疾病。因此,在诊断和治疗决策过程中,会需要开展特定基因的检测。在临床实践上,可以采取panel富集特定DNA片段进行测序的方法,这也是目前肿瘤相关基因检测商业服务的基本模式。这种检测服务得以上市的前提,是需要经过充分的验证。本文便是这样一个验证过程的实例。本文的验证对象,是为诊断AML(急性髓系白血病)的panel,验证过程纳入了26例AML患者的33个DNA样本(骨髓或外周血),以及Acrometrix Oncology Hotspot Control DNA作为对照。对这些样本中携带的AML相关突变进行了检测和性能评价。而临床样本中的突变,也采用qPCR、Sanger测序等方法进行了确认。通过评估,从四个不同panel及多种分析软件中,选出了针对血液病性能最佳的panel及软件组合。
Abstract:
Next-generation sequencing has greatly advanced the molecular diagnostics of malignant hematological diseases and provides useful information for clinical decision making. Studies have shown that certain mutations are associated with prognosis … >>>
Next-generation sequencing has greatly advanced the molecular diagnostics of malignant hematological diseases and provides useful information for clinical decision making. Studies have shown that certain mutations are associated with prognosis and have a direct impact on treatment of affected patients. Therefore, reliable detection of pathogenic variants is critically important. Here, we compared four sequencing panels with different characteristics, from number of genes covered to technical aspects of library preparation and data analysis workflows, to find the panel with the best clinical utility for myeloid neoplasms with a special focus on acute myeloid leukemia. Using the Acrometrix Oncology Hotspot Control DNA and DNA from acute myeloid leukemia patients, panel performance was evaluated in terms of coverage, precision, recall, and reproducibility and different bioinformatics tools that can be used for the evaluation of any next-generation sequencing panel were tested. Taken together, our results support the reliability of the Acrometrix Oncology Hotspot Control to validate and compare sequencing panels for hematological diseases and show which panel-software combination (platform) has the best performance. <<<
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92.
颜林林 (2022-06-20 07:48):
#paper doi:10.1016/j.gpb.2022.03.002 Genomics, Proteomics & Bioinformatics, 2022, Cancer is a survival process under persistent microenvironmental and cellular stresses. 这篇综述是关于癌症发生发展的机制,提出了一个新的框架看法。相较于传统以突变为核心的理解,该新看法的关键点在于,认为癌细胞的持续分裂是其生存的“必须”行为,而非仅受遗传物质突变所指导的被动结果。针对这个看法,文章从代谢模式变化、胞质pH状态、慢性炎症、过量铁积累负荷、芬顿反应等角度分别进行了阐释。对于某些癌种随年龄增长其发病率反而下降,以及某些物种很少发生或几乎不会发生癌症,这种看法也提供了新的解释。
93.
颜林林 (2022-06-19 00:14):
#paper doi:10.1186/s13073-022-01069-z Genome Medicine, 2022, Reanalysis of exome negative patients with rare disease: a pragmatic workflow for diagnostic applications. 过去这些年里,我们经常会对罕见遗传病患者开展全外显子组测序,以便确认其致病基因并形成诊断结论。然而,受限于技术和积累的知识,大部分患者在测序后也仍然无法确诊。这篇来自荷兰拉德堡德大学(Radboud University)的文章,回顾了其医学中心在2011年11月至2015年1月期间到访的疑似罹患复杂神经系统遗传疾病的150名儿童患者,对其中103名未得到确诊的患者进行了随访调查,通过重新查阅评估表型信息、重新分析其全外显子测序数据,以及对仍无法确诊的患者(使用新的实验流程和外显子panel)重新进行测序和分析。这一系列操作,让32名之前未被诊断的患者得到确诊,诊断率从31%(47/150)提升到53%(79/150)。其结果也支持了在临床护理和后续随访过程中,应该对未确诊患者进行重新分析和系统评估,新的临床证据信息、新的技术方法和分析方法,都有助于改善诊治,使患者获益。
IF:10.400Q1 Genome medicine, 2022-06-17. DOI: 10.1186/s13073-022-01069-z PMID: 35710456
Abstract:
BACKGROUND: Approximately two third of patients with a rare genetic disease remain undiagnosed after exome sequencing (ES). As part of our post-test counseling procedures, patients without a conclusive diagnosis are … >>>
BACKGROUND: Approximately two third of patients with a rare genetic disease remain undiagnosed after exome sequencing (ES). As part of our post-test counseling procedures, patients without a conclusive diagnosis are advised to recontact their referring clinician to discuss new diagnostic opportunities in due time. We performed a systematic study of genetically undiagnosed patients 5 years after their initial negative ES report to determine the efficiency of diverse reanalysis strategies.METHODS: We revisited a cohort of 150 pediatric neurology patients originally enrolled at Radboud University Medical Center, of whom 103 initially remained genetically undiagnosed. We monitored uptake of physician-initiated routine clinical and/or genetic re-evaluation (ad hoc re-evaluation) and performed systematic reanalysis, including ES-based resequencing, of all genetically undiagnosed patients (systematic re-evaluation).RESULTS: Ad hoc re-evaluation was initiated for 45 of 103 patients and yielded 18 diagnoses (including 1 non-genetic). Subsequent systematic re-evaluation identified another 14 diagnoses, increasing the diagnostic yield in our cohort from 31% (47/150) to 53% (79/150). New genetic diagnoses were established by reclassification of previously identified variants (10%, 3/31), reanalysis with enhanced bioinformatic pipelines (19%, 6/31), improved coverage after resequencing (29%, 9/31), and new disease-gene associations (42%, 13/31). Crucially, our systematic study also showed that 11 of the 14 further conclusive genetic diagnoses were made in patients without a genetic diagnosis that did not recontact their referring clinician.CONCLUSIONS: We find that upon re-evaluation of undiagnosed patients, both reanalysis of existing ES data as well as resequencing strategies are needed to identify additional genetic diagnoses. Importantly, not all patients are routinely re-evaluated in clinical care, prolonging their diagnostic trajectory, unless systematic reanalysis is facilitated. We have translated our observations into considerations for systematic and ad hoc reanalysis in routine genetic care. <<<
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94.
颜林林 (2022-06-18 14:39):
#paper doi:10.1021/acssynbio.2c00120 ACS Synthetic Biology, 2022, Graph Computation Using Algorithmic Self-Assembly of DNA Molecules. 利用DNA等生物分子进行计算,可以追溯至上世纪90年代初,该领域这些年来不断进步并取得新成果,本文便是这样的一个案例。本文另辟蹊径,使用了一种称为DNA折纸的技术(即通过精巧地设计DNA序列,使其折叠成为某种特定形状),来解决一个“六顶点三色涂色”的图论计算问题。宏观上极少量的生物物质,其实包含着数量庞大的分子,因而,使用这些分子进行计算,是一个天然能提供巨大算力的策略,可以很轻松实现大量排列组合的暴力穷举,这就是生物计算概念提出的基本出发点之一。虽说被称为“DNA computing”,但它其实还远不及我们日常认识的通用电子计算机。本文的研究,是在特定图论问题上,人为列举出各个待求顶点的所有可能颜色,以及利用DNA链互补特性,设计相应序列,实现控制哪些顶点之间可以互相连接的规则。然后大量合成这样的分子,使其在特定实验条件下自由组合,最终利用AFM(原子力显微镜)扫描,找到符合特定结构形状的答案。由于使用了DNA折纸技术,AFM可以直接观察并识别出各顶点的“颜色”及连接组合,从而给出问题的求解。文章所解决的问题,被限定在特定范围,且只是概念验证阶段,未来要扩展到更多应用场景,使其具备“通用”或一定程度“通用”的程度,还有很长的路要走。
IF:3.700Q1 ACS synthetic biology, 2022-07-15. DOI: 10.1021/acssynbio.2c00120 PMID: 35703038
Abstract:
DNA molecules have been used as novel computing tools, by which Synthetic DNA was designed to execute computing processes with a programmable sequence. Here, we proposed a parallel computing method … >>>
DNA molecules have been used as novel computing tools, by which Synthetic DNA was designed to execute computing processes with a programmable sequence. Here, we proposed a parallel computing method using DNA origamis as agents to solve the three-color problem, an example of the graph problem. Each agent was fabricated with a DNA origami of ∼50 nm diameter and contained DNA probes with programmable sticky ends that execute preset computing processes. With the interaction of different nanoagents, DNA molecules self-assemble into spatial nanostructures, which embody the computation results of the three-color problem with polynomial numbers of computing nanoagents in a one-pot annealing step. The computing results were confirmed by atomic force microscopy. Our method is completely different from existing DNA computing methods in its computing algorithm, and it has an advantage in terms of computational complexity and results detection for solving graph problems. <<<
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95.
颜林林 (2022-06-17 22:10):
#paper doi:10.1101/2022.06.12.495839 bioRxiv, 2022, Accurate Estimation of Molecular Counts from Amplicon Sequence Data with Unique Molecular Identifiers. 高通量测序数据中充满由PCR扩增和测序过程导致的错误,为解决此问题,人们通常会引入分子标签(UMI)技术,即用一段随机序列来标记出哪些序列来自同一原始模板分子,而哪些不是。很多工具在处理UMI时,都简单粗暴地将相同UMI的序列直接进行合并,而由于UMI序列本身也存在突变,会导致还原样本中原始模板分子信息的过程被误判。这个过程在扩增子测序(amplicon-seq)中尤为明显。本文通过构建一个单步隐马科夫模型(one step HMM),来处理PCR和测序过程中的错误,并用C语言实现了一套EM算法,对UMI测序数据的真实原始模板分子数进行估算。在模拟数据和真实数据中,分别进行了评测,对比既往其他类似工具,本文开发的工具(DAUMI),能有效识别出UMI冲突(UMI collision),表现出更优异的性能。
Abstract:
Motivation: Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured … >>>
Motivation: Amplicon sequencing is widely applied to explore heterogeneity and rare variants in genetic populations. Resolving true biological variants and quantifying their abundance is crucial for downstream analyses, but measured abundances are distorted by stochasticity and bias in amplification, plus errors during Polymerase Chain Reaction (PCR) and sequencing. One solution attaches Unique Molecular Identifiers (UMIs) to sample sequences before amplification eliminating amplification bias by clustering reads on UMI and counting clusters to quantify abundance. While modern methods improve over naive clustering by UMI identity, most do not account for UMI reuse, or collision, and they do not adequately model PCR and sequencing errors in the UMIs and sample sequences. Results: We introduce Deduplication and accurate Abundance estimation with UMIs (DAUMI), a probabilistic framework to detect true biological sequences and accurately estimate their deduplicated abundance from amplicon sequence data. DAUMI recognizes UMI collision, even on highly similar sequences, and detects and corrects most PCR and sequencing errors in the UMI and sampled sequences. We demonstrate DAUMI performs better on simulated and real data compared to other UMI-aware clustering methods. Availability: Source code is available at https://github.com/xiyupeng/AmpliCI-UMI. <<<
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96.
颜林林 (2022-06-16 00:40):
#paper doi:10.1038/s41588-022-01075-2 Nature Genetics, 2022, Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms. 这又是一篇只有两位作者署名的论文。如今,司空见惯了一篇文章动辄好几十位甚至成百上千位作者的情况,见到这类一两位作者“单打独斗”的作品,还是挺佩服的。从这篇文章,我学到个新词“调节组(regulome)”;相应地,其关联分析方法,被称为“regulome-wide associations study (RWAS)”。这篇文章还有个特点,它并未通过湿实验产出新数据,而是完全使用公开数据进行分析,包括结果验证,也是在公共数据库中进行。从概念到方法上进行创新,而成果发表到Nature子刊上,挺值得学习的。作者使用了来自TCGA的406例ATAC-seq数据,涵盖23个不同癌种,识别出7262个胚系allele-specific accessibility QTLs (as-aQTLs),即把染色质开放程度当做一种数量性状来研究,这个aQTL也是仿照eQTL提出的概念,的确很有意思。而通过RWAS,在各个癌种中鉴别出与癌症发生风险相关的as-aQTL位点,且发现它们在癌症风险遗传力方面的富集度甚至优于其他功能注释。这不仅实现了对非编码的“垃圾DNA(junk DNA)”区间的功能研究和解释,也开辟了肿瘤治疗的新思路,即针对这些调控区间及其相关机制来开展治疗。
IF:31.700Q1 Nature genetics, 2022-06. DOI: 10.1038/s41588-022-01075-2 PMID: 35697866
Abstract:
While many germline cancer risk variants have been identified through genome-wide association studies (GWAS), the mechanisms by which these variants operate remain largely unknown. Here we used 406 cancer ATAC-Seq … >>>
While many germline cancer risk variants have been identified through genome-wide association studies (GWAS), the mechanisms by which these variants operate remain largely unknown. Here we used 406 cancer ATAC-Seq samples across 23 cancer types to identify 7,262 germline allele-specific accessibility QTLs (as-aQTLs). Cancer as-aQTLs had stronger enrichment for cancer risk heritability (up to 145 fold) than any other functional annotation across seven cancer GWAS. Most cancer as-aQTLs directly altered transcription factor (TF) motifs and exhibited differential TF binding and gene expression in functional screens. To connect as-aQTLs to putative risk mechanisms, we introduced the regulome-wide associations study (RWAS). RWAS identified genetically associated accessible peaks at >70% of known breast and prostate loci and discovered new risk loci in all examined cancer types. Integrating as-aQTL discovery, motif analysis and RWAS identified candidate causal regulatory elements and their probable upstream regulators. Our work establishes cancer as-aQTLs and RWAS analysis as powerful tools to study the genetic architecture of cancer risk. <<<
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97.
颜林林 (2022-06-15 06:27):
#paper doi:10.1186/s12859-022-04783-y BMC Bioinformatics, 2022, CancerNet: a unified deep learning network for pan-cancer diagnostics. 这篇文章建立了一个通用的深度神经网络模型,基于来自TCGA的33种癌症的甲基化数据,检测癌症及其起源组织。同样的任务在2022年已有相应工作,能够达到96%的总体准确率。本文则通过同时使用无监督与有监督的方法,让模型在输出34个分类结果(33个癌种+1个正常非癌)的同时,也额外生成一组重新构造的CpG岛甲基化信息,并将生成的此信息,与用于模型输入的CpG到甲基化信息进行比对,损失函数中同时纳入了该比对差异。通过这种方式,模型整体性能得到进一步提高,总体准确率达到99.6%。此外,本文也同时考察了年龄、转移等混杂因素对模型的影响,并为未来研究和开发模型的可解释性提供了基础。整个研究基于OSF(开放科学框架)进行,数据和源代码都完全开放,是一份不错的学习材料。
IF:2.900Q1 BMC bioinformatics, 2022-Jun-13. DOI: 10.1186/s12859-022-04783-y PMID: 35698059
Abstract:
BACKGROUND: Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are … >>>
BACKGROUND: Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technological advances in machine learning or artificial intelligence to design a novel framework for cancer diagnostics. Our proposed framework detects cancers and their tissues of origin using a unified model of cancers encompassing 33 cancers represented in The Cancer Genome Atlas (TCGA). Our model exploits the learned features of different cancers reflected in the respective dysregulated epigenomes, which arise early in carcinogenesis and differ remarkably between different cancer types or subtypes, thus holding a great promise in early cancer detection.RESULTS: Our comprehensive assessment of the proposed model on the 33 different tissues of origin demonstrates its ability to detect and classify cancers to a high accuracy (> 99% overall F-measure). Furthermore, our model distinguishes cancers from pre-cancerous lesions to metastatic tumors and discriminates between hypomethylation changes due to age related epigenetic drift and true cancer.CONCLUSIONS: Beyond detection of primary cancers, our proposed computational model also robustly detects tissues of origin of secondary cancers, including metastatic cancers, second primary cancers, and cancers of unknown primaries. Our assessment revealed the ability of this model to characterize pre-cancer samples, a significant step forward in early cancer detection. Deployed broadly this model can deliver accurate diagnosis for a greatly expanded target patient population. <<<
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98.
颜林林 (2022-06-14 00:32):
#paper doi:10.1002/humu.24378 Human Mutation, 2022, Short amplicon reverse transcription-polymerase chain reaction detects aberrant splicing in genes with low expression in blood missed by ribonucleic acid sequencing analysis for clinical diagnosis. 这篇文章的标题很守规矩,把一大堆缩写都展开写全了,害我仔细辨认了半天:“reverse transcription-polymerase chain reaction” 其实是 rt-PCR,“ribonucleic acid sequencing” 其实是 RNA-seq。原来这是个说明“在某些情况下,rt-PCR相比RNA-seq更好”的故事。文章从另一个研究(Splicing and Disease Research Study)中选出了13个实际临床病例,它们在一些血液中通常低表达的基因上,已知存在诸如“外显子跳跃”这样的剪切相关突变,将这些病例的外周血样本,提取RNA后,分别进行RNA-seq和rt-PCR,确认了短片段rt-PCR的确能够有效且更灵敏地检出这些突变,而在RNA-seq中因为表达量太低而难以检出。从而验证了短片段rt-PCR方法可用于此类低表达基因的剪切相关突变的检测。
IF:3.300Q2 Human mutation, 2022-07. DOI: 10.1002/humu.24378 PMID: 35476365
Abstract:
Use of blood RNA sequencing (RNA-seq) as a splicing analysis tool for clinical interpretation of variants of uncertain significance (VUSs) found via whole-genome and exome sequencing can be difficult for … >>>
Use of blood RNA sequencing (RNA-seq) as a splicing analysis tool for clinical interpretation of variants of uncertain significance (VUSs) found via whole-genome and exome sequencing can be difficult for genes that have low expression in the blood due to insufficient read count coverage aligned to specific genes of interest. Here, we present a short amplicon reverse transcription-polymerase chain reaction(RT-PCR) for the detection of genes with low blood expression. Short amplicon RT-PCR, is designed to span three exons where an exon harboring a variant is flanked by one upstream and one downstream exon. We tested short amplicon RT-PCRs for genes that have median transcripts per million (TPM) values less than one according to the genotype-tissue expression database. Median TPM values of genes analyzed in this study are SYN1 = 0.8549, COL1A1 = 0.6275, TCF4 = 0.4009, DSP = .2894, TTN = 0.2851, COL5A2 = 0.1036, TERT = 0.04452, NTRK2 = 0.0344, ABCA4 = 0.00744, PRPH = 0, and WT1 = 0. All these genes show insufficient exon-spanning read coverage in our RNA-seq data to allow splicing analysis. We successfully detected all genes tested except PRPH and WT1. Aberrant splicing was detected in SYN1, TCF4, NTRK2, TTN, and TERT VUSs. Therefore, our results show short amplicon RT-PCR is a useful alternative for the analysis of splicing events in genes with low TPM in blood RNA for clinical diagnostics. <<<
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99.
颜林林 (2022-06-13 05:47):
#paper doi:10.1038/s41588-022-01082-3 Nature Genetics, 2022, Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer. 本文研究导管原位癌(DCIS)。该疾病常见于乳腺癌筛查,即使经过治疗,也仍然有小部分患者会恶化复发成为浸润性乳腺癌。本文试图研究,恶化的这些患者,是否都来自原发性DCIS的复发克隆,亦或仅是新发的无关疾病。为此,本研究纳入了129对DCIS复发病例样本(即原位DCIS样本和复发样本;同时也包含匹配的癌旁对照组织),通过开展全外显子组测序、SNP芯片检测或靶向基因组panel测序(这里技术平台方法存在差别,是因为样本及其实验,分别来自和开展于荷兰、英国和美国的三家不同单位),进行基因组突变分析和拷贝数变异分析。同时也从中选取了4例病例,将其原发与复发组织,分别进行解离并开展单细胞基因组测序。针对这两种策略,都分别进行了克隆演化分析,最终确认并非所有同侧浸润性乳腺癌都与先前的 DCIS 有克隆相关性,其中有约五分之一其实为新发原发性癌症。此结果也在更大范围且更详细的程度上,验证了前人的研究结果。
IF:31.700Q1 Nature genetics, 2022-06. DOI: 10.1038/s41588-022-01082-3 PMID: 35681052
Abstract:
Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental … >>>
Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers. <<<
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颜林林 (2022-06-12 07:49):
#paper doi:10.1038/s41598-022-13336-5 Scientific Reports, 2022, Omics-based integrated analysis identified IKZF2 as a biomarker associated with lupus nephritis. 相信很多人知道系统性红斑狼疮(SLE)这个疾病,跟我一样都来自二十多年前的一部火遍大江南北的虐心小说《第一次亲密接触》。而这篇文章所研究的,正是SLE的重要并发症和主要致死因素狼疮性肾炎(LN)。本文收集并挖掘了肾脏组织的公共数据,包括LN患者的肾小管间质和肾小体组织,也包括肾移植捐献者的健康肾组织,由这些数据找到26个常见差异表达基因(co-DEGs)。在此基础上,将其中的 IKZF2 基因作为重点,通过功能富集、蛋白-蛋白相互作用网络、ceRNA网络构建、免疫浸润、风险评估等常用生信方法进行分析,从而确定了 IKZF2 基因在 LN 疾病方面的预测和评估价值。文章的方法本身没有多少亮点,属于常见的套路玩法,应该是所选择的临床问题,为其提供了一定创新性和研究价值。
IF:3.800Q1 Scientific reports, 2022-06-10. DOI: 10.1038/s41598-022-13336-5 PMID: 35688845
Abstract:
Lupus nephritis (LN) is a crucial complication of systemic lupus erythematosus (SLE). IKZF2 was identified as a lupus susceptibility locus, while its exact molecular function in LN is unknown. We … >>>
Lupus nephritis (LN) is a crucial complication of systemic lupus erythematosus (SLE). IKZF2 was identified as a lupus susceptibility locus, while its exact molecular function in LN is unknown. We aimed to explore the relationship between IKZF2 and LN based on multi-omics data. In our study, we carried out a meta-analysis of publicly available data, including not only tubulointerstitium, but also glomerulus tissue samples from LN patients and controls. Based on the common differentially expressed genes (co-DEGs) and previous researches, we selected IKZF2 for further analysis. Then, we analyzed potential molecular mechanisms of co-DEGs and IKZF2 in LN. To explore the possible targets of IKZF2, protein-protein interaction network (PPI) network and ceRNA network of IKZF2 were also constructed. Moreover, we performed immune infiltration analysis and evaluated clinical value of IKZF2. A total of 26 co-DEGs were observed in the integration of the above DEGs coming from the four sets of data, of which IKZF2 was selected for further analysis. Functional enrichment analysis from IKZF2 and related PPI network confirmed the tight relationship between IKZF2 and the immune reaction. Moreover, immune filtration analysis revealed the significant correlation between IKZF2 and naïve B cell, NK cell activation, NK cell rest and other immune cells. Receiver operating characteristic (ROC) analysis showed that the areas under the ROC curves were 0.721, 0.80, 0.682, and 0.859 for IKZF2 in four datasets, which demonstrated the clinical value of IKZF2. Our study revealed that IKZF2 may play an essential role in the molecular function and development of LN, and might be a potential biomarker for distinguishing LN patients and healthy ones. <<<
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