Cell Reports Methods最新文献_第7页

Tracing unknown tumor origins with a biological-pathway-based transformer model. 利用基于生物通路的转化器模型追踪未知肿瘤起源

IF 4.3

Cell Reports Methods Pub Date : 2024-06-17 DOI: 10.1016/j.crmeth.2024.100797

Jiajing Xie, Ying Chen, Shijie Luo, Wenxian Yang, Yuxiang Lin, Liansheng Wang, Xin Ding, Mengsha Tong, Rongshan Yu

{"title":"Tracing unknown tumor origins with a biological-pathway-based transformer model.","authors":"Jiajing Xie, Ying Chen, Shijie Luo, Wenxian Yang, Yuxiang Lin, Liansheng Wang, Xin Ding, Mengsha Tong, Rongshan Yu","doi":"10.1016/j.crmeth.2024.100797","DOIUrl":"10.1016/j.crmeth.2024.100797","url":null,"abstract":"Cancer of unknown primary (CUP) represents metastatic cancer where the primary site remains unidentified despite standard diagnostic procedures. To determine the tumor origin in such cases, we developed BPformer, a deep learning method integrating the transformer model with prior knowledge of biological pathways. Trained on transcriptomes from 10,410 primary tumors across 32 cancer types, BPformer achieved remarkable accuracy rates of 94%, 92%, and 89% in primary tumors and primary and metastatic sites of metastatic tumors, respectively, surpassing existing methods. Additionally, BPformer was validated in a retrospective study, demonstrating consistency with tumor sites diagnosed through immunohistochemistry and histopathology. Furthermore, BPformer was able to rank pathways based on their contribution to tumor origin identification, which helped to classify oncogenic signaling pathways into those that are highly conservative among different cancers versus those that are highly variable depending on their origins.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228371/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141421198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Single-cell signatures identify microenvironment factors in tumors associated with patient outcomes. 单细胞特征识别出与患者预后相关的肿瘤微环境因素。

IF 4.3

Cell Reports Methods Pub Date : 2024-06-17 DOI: 10.1016/j.crmeth.2024.100799

Yuanqing Xue, Verena Friedl, Hongxu Ding, Christopher K Wong, Joshua M Stuart

引用次数: 0

Subtype-WGME enables whole-genome-wide multi-omics cancer subtyping. Subtype-WGME 可实现全基因组多组学癌症亚型分析。

IF 3.8

Cell Reports Methods Pub Date : 2024-06-17 Epub Date: 2024-05-17 DOI: 10.1016/j.crmeth.2024.100781

Hai Yang, Liang Zhao, Dongdong Li, Congcong An, Xiaoyang Fang, Yiwen Chen, Jingping Liu, Ting Xiao, Zhe Wang

{"title":"Subtype-WGME enables whole-genome-wide multi-omics cancer subtyping.","authors":"Hai Yang, Liang Zhao, Dongdong Li, Congcong An, Xiaoyang Fang, Yiwen Chen, Jingping Liu, Ting Xiao, Zhe Wang","doi":"10.1016/j.crmeth.2024.100781","DOIUrl":"10.1016/j.crmeth.2024.100781","url":null,"abstract":"We present an innovative strategy for integrating whole-genome-wide multi-omics data, which facilitates adaptive amalgamation by leveraging hidden layer features derived from high-dimensional omics data through a multi-task encoder. Empirical evaluations on eight benchmark cancer datasets substantiated that our proposed framework outstripped the comparative algorithms in cancer subtyping, delivering superior subtyping outcomes. Building upon these subtyping results, we establish a robust pipeline for identifying whole-genome-wide biomarkers, unearthing 195 significant biomarkers. Furthermore, we conduct an exhaustive analysis to assess the importance of each omic and non-coding region features at the whole-genome-wide level during cancer subtyping. Our investigation shows that both omics and non-coding region features substantially impact cancer development and survival prognosis. This study emphasizes the potential and practical implications of integrating genome-wide data in cancer research, demonstrating the potency of comprehensive genomic characterization. Additionally, our findings offer insightful perspectives for multi-omics analysis employing deep learning methodologies.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140960043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Precision nanoscale patterning of TLR ligands for improved cancer immunotherapy. 对 TLR 配体进行精确的纳米级图案化，以改进癌症免疫疗法。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 DOI: 10.1016/j.crmeth.2024.100782

Chung Yi Tseng, Farshad Murtada, Leo Y T Chou

引用次数: 0

A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations. 灰盒框架，利用黑盒优化器优化白盒逻辑模型，模拟细胞对扰动的反应。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 Epub Date: 2024-05-13 DOI: 10.1016/j.crmeth.2024.100773

Yunseong Kim, Younghyun Han, Corbin Hopper, Jonghoon Lee, Jae Il Joo, Jeong-Ryeol Gong, Chun-Kyung Lee, Seong-Hoon Jang, Junsoo Kang, Taeyoung Kim, Kwang-Hyun Cho

{"title":"A gray box framework that optimizes a white box logical model using a black box optimizer for simulating cellular responses to perturbations.","authors":"Yunseong Kim, Younghyun Han, Corbin Hopper, Jonghoon Lee, Jae Il Joo, Jeong-Ryeol Gong, Chun-Kyung Lee, Seong-Hoon Jang, Junsoo Kang, Taeyoung Kim, Kwang-Hyun Cho","doi":"10.1016/j.crmeth.2024.100773","DOIUrl":"10.1016/j.crmeth.2024.100773","url":null,"abstract":"Predicting cellular responses to perturbations requires interpretable insights into molecular regulatory dynamics to perform reliable cell fate control, despite the confounding non-linearity of the underlying interactions. There is a growing interest in developing machine learning-based perturbation response prediction models to handle the non-linearity of perturbation data, but their interpretation in terms of molecular regulatory dynamics remains a challenge. Alternatively, for meaningful biological interpretation, logical network models such as Boolean networks are widely used in systems biology to represent intracellular molecular regulation. However, determining the appropriate regulatory logic of large-scale networks remains an obstacle due to the high-dimensional and discontinuous search space. To tackle these challenges, we present a scalable derivative-free optimizer trained by meta-reinforcement learning for Boolean network models. The logical network model optimized by the trained optimizer successfully predicts anti-cancer drug responses of cancer cell lines, while simultaneously providing insight into their underlying molecular regulatory mechanisms.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11133856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140923518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effective cryopreservation of human brain tissue and neural organoids. 有效冷冻保存人类脑组织和神经器官组织。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 Epub Date: 2024-05-13 DOI: 10.1016/j.crmeth.2024.100777

Weiwei Xue, Huijuan Li, Jinhong Xu, Xiao Yu, Linlin Liu, Huihui Liu, Rui Zhao, Zhicheng Shao

{"title":"Effective cryopreservation of human brain tissue and neural organoids.","authors":"Weiwei Xue, Huijuan Li, Jinhong Xu, Xiao Yu, Linlin Liu, Huihui Liu, Rui Zhao, Zhicheng Shao","doi":"10.1016/j.crmeth.2024.100777","DOIUrl":"10.1016/j.crmeth.2024.100777","url":null,"abstract":"Human brain tissue models and organoids are vital for studying and modeling human neurological disease. However, the high cost of long-term cultured organoids inhibits their wide-ranging application. It is therefore urgent to develop methods for the cryopreservation of brain tissue and organoids. Here, we establish a method using methylcellulose, ethylene glycol, DMSO, and Y27632 (termed MEDY) for the cryopreservation of cortical organoids without disrupting the neural cytoarchitecture or functional activity. MEDY can be applied to multiple brain-region-specific organoids, including the dorsal/ventral forebrain, spinal cord, optic vesicle brain, and epilepsy patient-derived brain organoids. Additionally, MEDY enables the cryopreservation of human brain tissue samples, and pathological features are retained after thawing. Transcriptomic analysis shows that MEDY can protect synaptic function and inhibit the endoplasmic reticulum-mediated apoptosis pathway. MEDY will enable the large-scale and reliable storage of diverse neural organoids and living brain tissue and will facilitate wide-ranging research, medical applications, and drug screening.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11133841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140923523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interactions-based classification of a single microbial sample. 基于相互作用的单一微生物样本分类。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 Epub Date: 2024-05-13 DOI: 10.1016/j.crmeth.2024.100775

Yogev Yonatan, Shaya Kahn, Amir Bashan

引用次数: 0

A computational tool suite to facilitate single-cell lineage tracing analyses. 促进单细胞系谱追踪分析的计算工具套件。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 Epub Date: 2024-05-13 DOI: 10.1016/j.crmeth.2024.100780

Joshua J Waterfall, Adil Midoun, Leïla Perié

引用次数: 0

A platform for rapid patient-derived cutaneous neurofibroma organoid establishment and screening. 快速建立和筛选源自患者的皮肤神经纤维瘤类器官的平台。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 Epub Date: 2024-05-13 DOI: 10.1016/j.crmeth.2024.100772

Huyen Thi Lam Nguyen, Emily Kohl, Jessica Bade, Stefan E Eng, Anela Tosevska, Ahmad Al Shihabi, Peyton J Tebon, Jenny J Hong, Sarah Dry, Paul C Boutros, Andre Panossian, Sara J C Gosline, Alice Soragni

{"title":"A platform for rapid patient-derived cutaneous neurofibroma organoid establishment and screening.","authors":"Huyen Thi Lam Nguyen, Emily Kohl, Jessica Bade, Stefan E Eng, Anela Tosevska, Ahmad Al Shihabi, Peyton J Tebon, Jenny J Hong, Sarah Dry, Paul C Boutros, Andre Panossian, Sara J C Gosline, Alice Soragni","doi":"10.1016/j.crmeth.2024.100772","DOIUrl":"10.1016/j.crmeth.2024.100772","url":null,"abstract":"Localized cutaneous neurofibromas (cNFs) are benign tumors that arise in the dermis of patients affected by neurofibromatosis type 1 syndrome. cNFs are benign lesions: they do not undergo malignant transformation or metastasize. Nevertheless, they can cover a significant proportion of the body, with some individuals developing hundreds to thousands of lesions. cNFs can cause pain, itching, and disfigurement resulting in substantial socio-emotional repercussions. Currently, surgery and laser desiccation are the sole treatment options but may result in scarring and potential regrowth from incomplete removal. To identify effective systemic therapies, we introduce an approach to establish and screen cNF organoids. We optimized conditions to support the ex vivo growth of genomically diverse cNFs. Patient-derived cNF organoids closely recapitulate cellular and molecular features of parental tumors as measured by immunohistopathology, methylation, RNA sequencing, and flow cytometry. Our cNF organoid platform enables rapid screening of hundreds of compounds in a patient- and tumor-specific manner.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11133839/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140923519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling alcohol-associated liver disease in humans using adipose stromal or stem cell-derived organoids. 利用脂肪基质或干细胞衍生的器官组织模拟人类酒精相关性肝病。

IF 3.8

Cell Reports Methods Pub Date : 2024-05-20 Epub Date: 2024-05-14 DOI: 10.1016/j.crmeth.2024.100778

Guoyun Bi, Xuan Zhang, Weihong Li, Xin Lu, Xu He, Yaqiong Li, Rixing Bai, Haiyan Zhang

{"title":"Modeling alcohol-associated liver disease in humans using adipose stromal or stem cell-derived organoids.","authors":"Guoyun Bi, Xuan Zhang, Weihong Li, Xin Lu, Xu He, Yaqiong Li, Rixing Bai, Haiyan Zhang","doi":"10.1016/j.crmeth.2024.100778","DOIUrl":"10.1016/j.crmeth.2024.100778","url":null,"abstract":"Alcohol-associated liver disease (ALD) is a prevalent liver disease, yet research is hampered by the lack of suitable and reliable human ALD models. Herein, we generated human adipose stromal/stem cell (hASC)-derived hepatocellular organoids (hAHOs) and hASC-derived liver organoids (hALOs) in a three-dimensional system using hASC-derived hepatocyte-like cells and endodermal progenitor cells, respectively. The hAHOs were composed of major hepatocytes and cholangiocytes. The hALOs contained hepatocytes and nonparenchymal cells and possessed a more mature liver function than hAHOs. Upon ethanol treatment, both steatosis and inflammation were present in hAHOs and hALOs. The incubation of hALOs with ethanol resulted in increases in the levels of oxidative stress, the endoplasmic reticulum protein thioredoxin domain-containing protein 5 (TXNDC5), the alcohol-metabolizing enzymes ADH1B and ALDH1B1, and extracellular matrix accumulation, similar to those of liver tissues from patients with ALD. These results present a useful approach for understanding the pathogenesis of ALD in humans, thus facilitating the discovery of effective treatments.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":3.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11133832/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0