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Article ; Online: A new genomic framework to categorize pediatric acute myeloid leukemia.

2024 Volume 56, Issue 2, Page(s) 281–293

Abstract: Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we ... ...

Abstract	Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.
MeSH term(s)	Humans ; Child ; Leukemia, Myeloid, Acute/genetics ; Mutation ; Prognosis ; Genomics ; Transcription Factors/genetics ; Repressor Proteins/genetics ; Tumor Suppressor Proteins/genetics
Chemical Substances	Transcription Factors ; BCL11B protein, human ; Repressor Proteins ; Tumor Suppressor Proteins
Language	English
Publishing date	2024-01-11
Publishing country	United States
Document type	Journal Article
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-023-01640-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: NetBID2 provides comprehensive hidden driver analysis.

Dong, Xinran / Ding, Liang / Thrasher, Andrew / Wang, Xinge / Liu, Jingjing / Pan, Qingfei / Rash, Jordan / Dhungana, Yogesh / Yang, Xu / Risch, Isabel / Li, Yuxin / Yan, Lei / Rusch, Michael / McLeod, Clay / Yan, Koon-Kiu / Peng, Junmin / Chi, Hongbo / Zhang, Jinghui / Yu, Jiyang

Nature communications

2023 Volume 14, Issue 1, Page(s) 2581

Abstract: Many signaling and other genes known as "hidden" drivers may not be genetically or epigenetically altered or differentially expressed at the mRNA or protein levels, but, rather, drive a phenotype such as tumorigenesis via post-translational modification ... ...

Abstract	Many signaling and other genes known as "hidden" drivers may not be genetically or epigenetically altered or differentially expressed at the mRNA or protein levels, but, rather, drive a phenotype such as tumorigenesis via post-translational modification or other mechanisms. However, conventional approaches based on genomics or differential expression are limited in exposing such hidden drivers. Here, we present a comprehensive algorithm and toolkit NetBID2 (data-driven network-based Bayesian inference of drivers, version 2), which reverse-engineers context-specific interactomes and integrates network activity inferred from large-scale multi-omics data, empowering the identification of hidden drivers that could not be detected by traditional analyses. NetBID2 has substantially re-engineered the previous prototype version by providing versatile data visualization and sophisticated statistical analyses, which strongly facilitate researchers for result interpretation through end-to-end multi-omics data analysis. We demonstrate the power of NetBID2 using three hidden driver examples. We deploy NetBID2 Viewer, Runner, and Cloud apps with 145 context-specific gene regulatory and signaling networks across normal tissues and paediatric and adult cancers to facilitate end-to-end analysis, real-time interactive visualization and cloud-based data sharing. NetBID2 is freely available at https://jyyulab.github.io/NetBID .
MeSH term(s)	Humans ; Bayes Theorem ; Genomics ; Algorithms ; Cell Transformation, Neoplastic/genetics ; Research Design ; Software
Language	English
Publishing date	2023-05-04
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-38335-6
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data.

Ding, Liang / Shi, Hao / Qian, Chenxi / Burdyshaw, Chad / Veloso, Joao Pedro / Khatamian, Alireza / Pan, Qingfei / Dhungana, Yogesh / Xie, Zhen / Risch, Isabel / Yang, Xu / Huang, Xin / Yan, Lei / Rusch, Michael / Brewer, Michael / Yan, Koon-Kiu / Chi, Hongbo / Yu, Jiyang

bioRxiv : the preprint server for biology

2023

Abstract: The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to ... ...

Abstract	The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.
Language	English
Publishing date	2023-01-27
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.01.26.523391
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: scMINER: a mutual information-based framework for identifying hidden drivers from single-cell omics data.

Research square

2023

Abstract	The sparse nature of single-cell omics data makes it challenging to dissect the wiring and rewiring of the transcriptional and signaling drivers that regulate cellular states. Many of the drivers, referred to as "hidden drivers", are difficult to identify via conventional expression analysis due to low expression and inconsistency between RNA and protein activity caused by post-translational and other modifications. To address this issue, we developed scMINER, a mutual information (MI)-based computational framework for unsupervised clustering analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We designed scMINER to capture nonlinear cell-cell and gene-gene relationships and infer driver activities. Systematic benchmarking showed that scMINER outperforms popular single-cell clustering algorithms, especially in distinguishing similar cell types. With respect to network inference, scMINER does not rely on the binding motifs which are available for a limited set of transcription factors, therefore scMINER can provide quantitative activity assessment for more than 6,000 transcription and signaling drivers from a scRNA-seq experiment. As demonstrations, we used scMINER to expose hidden transcription and signaling drivers and dissect their regulon rewiring in immune cell heterogeneity, lineage differentiation, and tissue specification. Overall, activity-based scMINER is a widely applicable, highly accurate, reproducible and scalable method for inferring cellular transcriptional and signaling networks in each cell state from scRNA-seq data. The scMINER software is publicly accessible via: https://github.com/jyyulab/scMINER.
Language	English
Publishing date	2023-01-27
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-2476875/v1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The landscape of coding RNA editing events in pediatric cancer.

Wen, Ji / Rusch, Michael / Brady, Samuel W / Shao, Ying / Edmonson, Michael N / Shaw, Timothy I / Powers, Brent B / Tian, Liqing / Easton, John / Mullighan, Charles G / Gruber, Tanja / Ellison, David / Zhang, Jinghui

BMC cancer

2021 Volume 21, Issue 1, Page(s) 1233

Abstract: Background: RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. We sought to elucidate the landscape of RNA editing events across pediatric cancers.: Methods: Using RNA-Seq data mapped ... ...

Abstract	Background: RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. We sought to elucidate the landscape of RNA editing events across pediatric cancers. Methods: Using RNA-Seq data mapped by a pipeline designed to minimize mapping ambiguity, we investigated RNA editing in 711 pediatric cancers from the St. Jude/Washington University Pediatric Cancer Genome Project focusing on coding variants which can potentially increase protein sequence diversity. We combined de novo detection using paired tumor DNA-RNA data with analysis of known RNA editing sites. Results: We identified 722 unique RNA editing sites in coding regions across pediatric cancers, 70% of which were nonsynonymous recoding variants. Nearly all editing sites represented the canonical A-to-I (n = 706) or C-to-U sites (n = 14). RNA editing was enriched in brain tumors compared to other cancers, including editing of glutamate receptors and ion channels involved in neurotransmitter signaling. RNA editing profiles of each pediatric cancer subtype resembled those of the corresponding normal tissue profiled by the Genotype-Tissue Expression (GTEx) project. Conclusions: In this first comprehensive analysis of RNA editing events in pediatric cancer, we found that the RNA editing profile of each cancer subtype is similar to its normal tissue of origin. Tumor-specific RNA editing events were not identified indicating that successful immunotherapeutic targeting of RNA-edited peptides in pediatric cancer should rely on increased antigen presentation on tumor cells compared to normal but not on tumor-specific RNA editing per se.
MeSH term(s)	Brain Neoplasms/genetics ; Child ; DNA, Neoplasm ; Humans ; Immunotherapy ; Neoplasms/genetics ; Neoplasms/metabolism ; Neoplasms/therapy ; Open Reading Frames ; Organ Specificity ; RNA Editing ; RNA, Neoplasm ; Sequence Analysis, RNA/methods ; Whole Genome Sequencing
Chemical Substances	DNA, Neoplasm ; RNA, Neoplasm
Language	English
Publishing date	2021-11-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2041352-X
ISSN	1471-2407 ; 1471-2407
ISSN (online)	1471-2407
ISSN	1471-2407
DOI	10.1186/s12885-021-08956-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Proposal of a new genomic framework for categorization of pediatric acute myeloid leukemia associated with prognosis.

Research square

2023

Abstract	Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 895 pAML into 23 molecular categories that are mutually distinct from one another, including new entities such as
Language	English
Publishing date	2023-05-29
Publishing country	United States
Document type	Preprint
DOI	10.21203/rs.3.rs-2925426/v1
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book: Synthese und spektroskopische Charakterisierung von Substratanaloga der H+-ATPase und Untersuchung der Ladungsrekombination in Reaktionszentren von Rhodobacter sphaeroides

Rusch, Michael

2001

Author's details	von Michael Rusch
Keywords	Dissertation
Language	German
Size	71 Bl, graph. Darst., Tab., Ill
Document type	Book
Note	Freiburg i. Br., Univ., Diss., 2001
Database	Federal Institute for Risk Assessment

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Book ; Thesis: Synthese und spektroskopische Charakterisierung von Substratanaloga der H+-ATPase und Untersuchung der Ladungsrekombination in Reaktionszentren von Rhodobacter sphaeroides

Rusch, Michael

2001

Author's details	vorgelegt von Michael Rusch
Keywords	Rhodobacter sphaeroides ; Photosynthetisches Reaktionszentrum ; Reaktionsmechanismus ; Elektronentransfer ; Chemische Synthese ; Spektroskopie ; Enzymsubstrat ; Wasserstoff-ATPase
Language	German
Size	xvi, 149 S, 21 cm
Publisher	Logos-Verl
Publishing place	Berlin
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Univ., Diss--Freiburg (Breisgau), 2001
ISBN	3897226960 ; 9783897226968
Database	Former special subject collection: coastal and deep sea fishing

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Book ; Thesis: Synthese und spektroskopische Charakterisierung von Substratanaloga der H+-ATPase und Untersuchung der Ladungsrekombination in Reaktionszentren von Rhodobacter sphaeroides

Rusch, Michael

2001

Author's details	vorgelegt von Michael Rusch
Keywords	Rhodobacter sphaeroides ; Photosynthetisches Reaktionszentrum ; Reaktionsmechanismus ; Elektronentransfer ; Chemische Synthese ; Spektroskopie ; Enzymsubstrat ; Wasserstoff-ATPase
Language	German
Size	xvi, 149 S, 21 cm
Publisher	Logos-Verl
Publishing place	Berlin
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Univ., Diss--Freiburg (Breisgau), 2001
ISBN	3897226960 ; 9783897226968
Database	Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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Article ; Online: RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.

Hagiwara, Kohei / Ding, Liang / Edmonson, Michael N / Rice, Stephen V / Newman, Scott / Easton, John / Dai, Juncheng / Meshinchi, Soheil / Ries, Rhonda E / Rusch, Michael / Zhang, Jinghui

Bioinformatics (Oxford, England)

2020 Volume 36, Issue 14, Page(s) 4231

Language	English
Publishing date	2020-03-06
Publishing country	England
Document type	Journal Article ; Published Erratum
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btaa247
Database	MEDical Literature Analysis and Retrieval System OnLINE

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bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

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