Featured
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Article
| Open AccessBuffering of transcription rate by mRNA half-life is a conserved feature of Rett syndrome models
Rett syndrome (RTT) is a neurodevelopmental disorder caused by mutations in the transcriptional modulator MECP2. Here, the authors measured transcription rate and mRNA half-life changes in RTT patient-derived neurons to show transcription rate buffered by mRNA half-life changes.
- Deivid C. Rodrigues
- , Marat Mufteev
- & James Ellis
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Article
| Open AccessLacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond
Large-scale disease-association data are widely used for pathomechanism mining, even if disease definitions used for annotation are mostly phenotype-based. Here, the authors show that this bias can lead to a blurred view on disease mechanisms, highlighting the need for close-up studies based on molecular data for well-characterized patient cohorts.
- Sepideh Sadegh
- , James Skelton
- & David B. Blumenthal
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Article
| Open AccessInteroperable slide microscopy viewer and annotation tool for imaging data science and computational pathology
There is a lack of standardisation in slide microscopy imaging data. Here the authors report Slim, an open-source, web-based slide microscopy viewer implementing the Digital Imaging and Communications in Medicine (DICOM) standard to achieve interoperability with a range of existing medical imaging systems.
- Chris Gorman
- , Davide Punzo
- & Markus D. Herrmann
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Article
| Open AccessBenchmarking integration of single-cell differential expression
Integration of single-cell RNA sequencing data between different samples has been a major challenge for analyzing cell populations. Here the authors benchmark 46 workflows for differential expression analysis of single-cell data with multiple batches and suggest several high-performance methods under different conditions based on simulation and real data analyses.
- Hai C. T. Nguyen
- , Bukyung Baik
- & Dougu Nam
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Article
| Open AccessTowards routine chromosome-scale haplotype-resolved reconstruction in cancer genomics
The precise inference of structural variants (SVs) requires suitable sequencing technologies and computational tools. Here, in order to analyse SVs with haplotype resolution, the author applies high-resolution long-read sequencing and long-range Hi-C to a melanoma cell line and develops an efficient graph-based computational framework, pstools.
- Shilpa Garg
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Article
| Open AccessInterpretable and context-free deconvolution of multi-scale whole transcriptomic data with UniCell deconvolve
There is interest in measuring the influence of spatial cellular organization on pathophysiology, which is being accomplished through spatial transcriptomics. There the authors present UniCell Deconvolve, a pre-trained deep learning model that predicts cell identity and deconvolves cell type fractions using a 28 M cell database.
- Daniel Charytonowicz
- , Rachel Brody
- & Robert Sebra
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Article
| Open AccessReconstructing clonal tree for phylo-phenotypic characterization of cancer using single-cell transcriptomics
The functional changes of individual clones in single cell RNA sequencing (scRNA-seq) data remain elusive. Here, the authors develop PhylEx that integrates bulk genomics data with co-occurrences of mutations revealed by scRNA-seq data and apply it to high-grade serous ovarian cancer cell line and breast cancer datasets.
- Seong-Hwan Jun
- , Hosein Toosi
- & Jens Lagergren
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Article
| Open AccessBatch alignment of single-cell transcriptomics data using deep metric learning
The increasing scale of single-cell RNA-seq studies presents new challenge for integrating datasets from different batches. Here, the authors develop scDML, a tool that simultaneously removes batch effects, improves clustering performance, recovers true cell types, and scales well to large datasets.
- Xiaokang Yu
- , Xinyi Xu
- & Xiangjie Li
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Article
| Open AccessGenomic and microenvironmental heterogeneity shaping epithelial-to-mesenchymal trajectories in cancer
The intermediate states of the epithelial-to-mesenchymal transition (EMT) in cancer require further molecular characterisation. Here, the authors develop a method to evaluate EMT transformation and trajectories in cancer transcriptomics data, characterising EMT macro-states, including a hybrid state, and EMT hallmarks.
- Guidantonio Malagoli Tagliazucchi
- , Anna J. Wiecek
- & Maria Secrier
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Article
| Open AccessReanalysis of ribosome profiling datasets reveals a function of rocaglamide A in perturbing the dynamics of translation elongation via eIF4A
The compound Rocaglamide A (RocA) is known for repressing translation initiation. Here the authors identify a dual mode of action for RocA in blocking translation initiation and elongation via eIF4A using previous datasets and new analyses.
- Fajin Li
- , Jianhuo Fang
- & Xuerui Yang
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Article
| Open AccessDecision level integration of unimodal and multimodal single cell data with scTriangulate
Single-cell genomics has expanded to measure diverse molecular modalities within the same cell. Here the authors provide a computational framework called scTriangulate to integrate cluster annotations from diverse independent sources, algorithms, and modalities to define statistically stable populations.
- Guangyuan Li
- , Baobao Song
- & Nathan Salomonis
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Article
| Open AccessscMoMaT jointly performs single cell mosaic integration and multi-modal bio-marker detection
Many methods for single cell data integration have been developed, though mosaic integration remains challenging. Here the authors present scMoMaT, a mosaic integration method for single cell multi-modality data from multiple batches, that jointly learns cell representations and marker features across modalities for different cell clusters, to interpret the cell clusters from different modalities.
- Ziqi Zhang
- , Haoran Sun
- & Xiuwei Zhang
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Article
| Open AccessProbabilistic embedding, clustering, and alignment for integrating spatial transcriptomics data with PRECAST
Methods that perform data integration are needed to analyse spatial transcriptomics data from multiple tissue slides. Here, the authors present PRECAST, an efficient data integration method for multiple spatial transcriptomics datasets with complex batch or biological effects between slides.
- Wei Liu
- , Xu Liao
- & Jin Liu
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Article
| Open AccessQuantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases
The mechanism by which DNA methylation might affect complex traits is not well understood. Here, the authors use Mendelian randomization to reveal a substantial role of transcript levels in mediating DNA methylation effects on complex traits and diseases.
- Marie C. Sadler
- , Chiara Auwerx
- & Zoltán Kutalik
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Article
| Open AccessGraph-based autoencoder integrates spatial transcriptomics with chromatin images and identifies joint biomarkers for Alzheimer’s disease
Methods for jointly analysing the different spatial data modalities in 3D are lacking. Here the authors report the computational framework STACI (Spatial Transcriptomic data using over-parameterized graph-based Autoencoders with Chromatin Imaging data) which they apply to an Alzheimer’s disease mouse model.
- Xinyi Zhang
- , Xiao Wang
- & Caroline Uhler
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Article
| Open AccessReference panel guided topological structure annotation of Hi-C data
Predicting topological structures from Hi-C data provides insight into comprehending gene expression and regulation. Here, the authors present RefHiC, an attention-based deep learning framework that leverages a reference panel of Hi-C datasets to assist topological structure annotation from a given study sample.
- Yanlin Zhang
- & Mathieu Blanchette
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Article
| Open AccessA unified computational framework for single-cell data integration with optimal transport
Integrating heterogeneous single-cell multi-omics as well as spatially resolved transcriptomic data remains a major challenge. Here the authors report a unified single-cell data integration framework using an unbalanced optimal transport-based deep network.
- Kai Cao
- , Qiyu Gong
- & Lin Wan
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Article
| Open AccessA flexible cross-platform single-cell data processing pipeline
As the throughput of single-cell RNA-seq studies increases, there is a need for tools that can make the data analysis steps more streamlined and convenient. Here, the authors develop UniverSC, a tool that unifies single-cell RNA-seq analysis workflows and also facilitates their use for non-experts.
- Kai Battenberg
- , S. Thomas Kelly
- & Aki Minoda
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Article
| Open AccessSystematic tissue annotations of genomics samples by modeling unstructured metadata
The 1+ million publicly-available human –omics samples currently remain acutely underused. Here the authors present an approach combining natural language processing and machine learning to infer the source tissue of public genomics samples based on their plain text descriptions, making these samples easy to discover and reuse.
- Nathaniel T. Hawkins
- , Marc Maldaver
- & Arjun Krishnan
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Article
| Open AccessThe hypoxia response pathway promotes PEP carboxykinase and gluconeogenesis in C. elegans
The hypoxia response pathway can counter pathological damage caused by low oxygen availability. Here the authors employ a multiomics approach to show how the pathway reprograms metabolism towards gluconeogenesis to combat oxidative stress.
- Mehul Vora
- , Stephanie M. Pyonteck
- & Christopher Rongo
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Article
| Open AccessOnline single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space
Integrative analyses of single-cell datasets are facing new challenges as data size and complexity grow. Here the authors present SCALEX, which projects cells from different datasets into a common latent space, allowing accurate online integration as well as cross-referencing with atlas-scale data.
- Lei Xiong
- , Kang Tian
- & Qiangfeng Cliff Zhang
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Article
| Open AccessElucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning
Multi-view graph approaches could enhance the analysis of tissue heterogeneity in spatial transcriptomics. Here, the authors develop the Spatial Transcriptomics data analysis by Multiple View Collaborative-learning - stMVC - framework, and apply it to detect spatial domains and cell states in brain and tumor tissues.
- Chunman Zuo
- , Yijian Zhang
- & Luonan Chen
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Article
| Open AccessPIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest
Protein kinase-mediated phosphorylation plays a critical role in many biological processes. Here the authors develop a trans-omics-based algorithm called Central Kinase Inference to integrate quantitative transcriptomic and phosphoproteomic data, finding that PIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest.
- Yangyang Yuan
- , Chenwei Wang
- & Pengyu Huang
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Article
| Open AccessTranscriptomic diversity in human medullary thymic epithelial cells
The thymus generates all T cells, including those that underly autoimmune diseases. Here, using deep sequencing, the authors profile human medullary thymic epithelial cells and establish a web portal to query their transcriptome, which may serve as a tool to help identify the drivers of autoimmunity.
- Jason A. Carter
- , Léonie Strömich
- & Hannah V. Meyer
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Article
| Open AccessMyasthenia gravis-specific aberrant neuromuscular gene expression by medullary thymic epithelial cells in thymoma
Myasthenia Gravis and thymoma are frequently associated with patients suffering from both diseases. Here the authors perform single cell sequencing of thymoma and find that there are autoimmune antigens such as neuromuscular proteins expressed aberrantly in neuromuscular mTECs in patients with both diseases.
- Yoshiaki Yasumizu
- , Naganari Ohkura
- & Hideki Mochizuki
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Article
| Open AccessIntegration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer
Some cancer patients with impaired HLA-I still respond to immunotherapy. Here the authors combine a cytotoxic gene signature from CD4+ and CD8+ T cells with tumor mutational burden to predict immunotherapy response in NSCLC patients, including those with HLA-LOH.
- Denise Lau
- , Sonal Khare
- & Aly A. Khan
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Article
| Open AccessGenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases
Many transcriptomic profiles have been deposited in public archives but are underused for the interpretation of experiments. Here the authors report GenomicSuperSignature for interpreting new transcriptomic datasets through comparison to public archives, without high-performance computing requirements.
- Sehyun Oh
- , Ludwig Geistlinger
- & Sean Davis
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Article
| Open AccessHarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values
Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Here the authors present “HarmonizR”, a tool for missing data tolerant experimental variance reduction in large, integrated but independently generated datasets without data imputation, adjustable for individual dataset modalities, correction algorithm, and user preferences.
- Hannah Voß
- , Simon Schlumbohm
- & Christoph Krisp
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Comment
| Open AccessDiagonal integration of multimodal single-cell data: potential pitfalls and paths forward
Diagonal integration of multimodal single-cell data emerges as a trending topic. However, empowering diagonal methods for novel biological discoveries requires bridging huge gaps. Here, we comment on potential risks and future directions of diagonal integration for multimodal single-cell data.
- Yang Xu
- & Rachel Patton McCord
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Article
| Open AccessOrgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder
Cerebral organoids can be used to gain insights into neuropsychiatric disorders. Here the authors carry out RNAseq characterization from organoids derived from donors with autism spectrum disorder to identify associated cell type specific driver genes.
- Elaine T. Lim
- , Yingleong Chan
- & George M. Church
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Article
| Open AccessDynamic nucleosome landscape elicits a noncanonical GATA2 pioneer model
Here the authors provide a multi-omic study of the nucleosome landscape in LNCaP cells and observe nine functional nucleosome states each with characteristic nucleosome footprints. Upon androgen stimulation, they observed changes in these nucleosome states accompanied by changes in binding and function of pioneer factors, including GATA2.
- Tianbao Li
- , Qi Liu
- & Victor X. Jin
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Matters Arising
| Open AccessVariant calling from scRNA-seq data allows the assessment of cellular identity in patient-derived cell lines
- Daniele Ramazzotti
- , Fabrizio Angaroni
- & Alex Graudenzi
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Article
| Open AccessReconstruct high-resolution 3D genome structures for diverse cell-types using FLAMINGO
High-resolution reconstruction of spatial chromosome organisation is in demand. Here the authors report FLAMINGO, for reconstructing high-resolution 3D Genome Organisation from HiC data which they use to generate both 5 kb and 1 kb-resolution 3D chromosomal structures for the human genome.
- Hao Wang
- , Jiaxin Yang
- & Jianrong Wang
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Article
| Open AccessLeveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes
3’ untranslated regions (3’UTRs) play a crucial role in regulating gene expression, but our 3’UTR catalogue is incomplete. Here, the authors develop a machine learning-based framework to predict previously unannotated 3’UTRs in 39 human tissues.
- Siddharth Sethi
- , David Zhang
- & Juan A. Botia
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Article
| Open AccesscyCombine allows for robust integration of single-cell cytometry datasets within and across technologies
Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. Here, the authors present a method to robustly integrate cytometry data from different batches, experiments, or even different experimental techniques.
- Christina Bligaard Pedersen
- , Søren Helweg Dam
- & Lars Rønn Olsen
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Article
| Open AccessDLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models
A lossless, one-shot and privacy-preserving distributed algorithm was revealed for fitting linear mixed models on multi-site data. The algorithm was applied to a study of 120,609 COVID-19 patients using only minimal aggregated data from each of 14 sites.
- Chongliang Luo
- , Md. Nazmul Islam
- & Yong Chen
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Article
| Open AccessCytofIn enables integrated analysis of public mass cytometry datasets using generalized anchors
Challenges in batch normalization and data integration limit the comparison of existing mass cytometry datasets. Here, the authors report CytofIn that can integrate mass cytometry datasets from the public domain and reveal cellular features associated with immune oncology by analyzing five public cancer datasets.
- Yu-Chen Lo
- , Timothy J. Keyes
- & Kara L. Davis
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Article
| Open AccessA platform for oncogenomic reporting and interpretation
The interpretation of somatic variants in cancer is challenging due to the scale and complexity of sequencing data. Here, the authors present PORI, an open-source framework for interpreting somatic variants in cancer using graph knowledge base tools, automated reporting, and manual curation.
- Caralyn Reisle
- , Laura M. Williamson
- & Steven J. M. Jones
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Article
| Open AccessUINMF performs mosaic integration of single-cell multi-omic datasets using nonnegative matrix factorization
Single-cell genomic technologies present unique data integration challenges. Here the authors introduce an integrative nonnegative matrix factorization algorithm that incorporates features unshared between datasets when performing dataset integrations, improving integration results for spatial transcriptomic, cross-modality, and cross-species data.
- April R. Kriebel
- & Joshua D. Welch
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Article
| Open AccessDeep phenotyping of Alzheimer’s disease leveraging electronic medical records identifies sex-specific clinical associations
Sex modifies Alzheimer’s Disease vulnerability, but the reasons for this are largely unknown. Here, the authors utilize two independent electronic medical record systems to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations.
- Alice S. Tang
- , Tomiko Oskotsky
- & Marina Sirota
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Article
| Open AccessAge influences on the molecular presentation of tumours
Ageing is a known risk factor in the development of cancers, but its association with molecular alterations is not fully explored. Here, the authors analyse pan-cancer age-associated molecular alterations in datasets from the TCGA, PCAWG and AACR-GENIE projects and identify prognostic biomarkers.
- Constance H. Li
- , Syed Haider
- & Paul C. Boutros
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Article
| Open AccessPrediction of biomarkers and therapeutic combinations for anti-PD-1 immunotherapy using the global gene network association
A lot of cancer patients are not responsive to anti-PD1 therapy. Here, the authors develop a network approach to identify genes, pathways and potential therapeutic combinations and develop an MHC-I gene immunoscore associated with tumour response to anti-PD1.
- Chia-Chin Wu
- , Y. Alan Wang
- & P. Andrew Futreal
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Article
| Open AccessIntegrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension
Prioritizing drug repurposing candidates for downstream studies remains challenging. Here, the authors present a high-throughput approach to identify and validate drug repurposing candidates, integrating human gene expression, drug perturbation, and clinical data from publicly available resources.
- Patrick Wu
- , QiPing Feng
- & Wei-Qi Wei
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Article
| Open AccessClonal architecture predicts clinical outcomes and drug sensitivity in acute myeloid leukemia
Individual studies have been underpowered to draw clear associations between clonal heterogeneity and response to therapy in acute myeloid leukemia (AML). Here, the authors aggregate multiple AML cohorts and are able to correlate the clonal abundance of somatic mutations with clinical outcomes and drug sensitivity.
- Brooks A. Benard
- , Logan B. Leak
- & Ravindra Majeti
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Article
| Open AccessNetwork medicine for disease module identification and drug repurposing with the NeDRex platform
There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. Here, the authors close this gap with NeDRex, an integrative and interactive platform.
- Sepideh Sadegh
- , James Skelton
- & Tim Kacprowski
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Article
| Open AccessMachine learning of genomic features in organotropic metastases stratifies progression risk of primary tumors
The location and timing of metastasis are still fundamentally unpredictable. Here the authors present the Metastatic Network model, a machine learning framework that integrates clinical data and DNA alterations to predict the risk of metastasis to specific organs as well as clinical outcomes
- Biaobin Jiang
- , Quanhua Mu
- & Jiguang Wang
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Article
| Open AccessMesmerize is a dynamically adaptable user-friendly analysis platform for 2D and 3D calcium imaging data
Calcium imaging is valuable for understanding neuro and cell biology, but is challenging to analyze, organize, and access. Here, the authors present an efficient, expandable and user-friendly platform, which encapsulates the entire analysis process all to way to interactive visualizations.
- Kushal Kolar
- , Daniel Dondorp
- & Marios Chatzigeorgiou
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Article
| Open AccessNetwork analysis reveals rare disease signatures across multiple levels of biological organization
Despite the clear causal relationship between genotype and phenotype in rare diseases, identifying the pathobiological mechanisms at various levels of biological organization remains a practical and conceptual challenge. Here, the authors introduce a network approach for evaluating the impact of rare gene defects across biological scales.
- Pisanu Buphamalai
- , Tomislav Kokotovic
- & Jörg Menche
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Article
| Open AccessMulti-omics analysis identifies therapeutic vulnerabilities in triple-negative breast cancer subtypes
Triple negative breast cancer can be divided into additional subtypes. Here, using omics analyses, the authors show that in the mesenchymal subtype expression of MHC-1 is repressed and that this can be restored by using drugs that target subunits of the epigenetic modifier PRC2.
- Brian D. Lehmann
- , Antonio Colaprico
- & X. Steven Chen