scTour: a deep learning architecture for robust inference and accurate prediction of cellular dynamics DOI Creative Commons
Qian Li

Genome biology, Journal Year: 2023, Volume and Issue: 24(1)

Published: June 23, 2023

Abstract Despite the continued efforts, a batch-insensitive tool that can both infer and predict developmental dynamics using single-cell genomics is lacking. Here, I present scTour, novel deep learning architecture to perform robust inference accurate prediction of cellular with minimal influence from batch effects. For inference, scTour simultaneously estimates pseudotime, delineates vector field, maps transcriptomic latent space under single, integrated framework. prediction, precisely reconstructs underlying unseen states or new independent dataset. scTour’s functionalities are demonstrated in variety biological processes 19 datasets.

Language: Английский

Single-cell profiling to explore pancreatic cancer heterogeneity, plasticity and response to therapy DOI
Stefanie Bärthel, Chiara Falcomatà, Roland Rad

et al.

Nature Cancer, Journal Year: 2023, Volume and Issue: 4(4), P. 454 - 467

Published: March 23, 2023

Language: Английский

Citations

52
scPerturb: harmonized single-cell perturbation data DOI
Stefan Peidli, Tessa D. Green, Ciyue Shen

et al.

Nature Methods, Journal Year: 2024, Volume and Issue: 21(3), P. 531 - 540

Published: Jan. 26, 2024

Language: Английский

Citations

51
Regorafenib plus nivolumab in unresectable hepatocellular carcinoma: the phase 2 RENOBATE trial DOI Creative Commons
Hyung‐Don Kim, Seyoung Jung, Ho Yeong Lim

et al.

Nature Medicine, Journal Year: 2024, Volume and Issue: 30(3), P. 699 - 707

Published: Feb. 19, 2024

Abstract Regorafenib has anti-tumor activity in patients with unresectable hepatocellular carcinoma (uHCC) potential immunomodulatory effects, suggesting that its combination immune checkpoint inhibitor may have clinically meaningful benefits uHCC. The multicenter, single-arm, phase 2 RENOBATE trial tested regorafenib–nivolumab as front-line treatment for Forty-two received nivolumab 480 mg every 4 weeks and regorafenib 80 daily (3-weeks-on/1-week-off schedule). primary endpoint was the investigator-assessed objective response rate (ORR) per Response Evaluation Criteria Solid Tumors (RECIST) version 1.1. secondary endpoints included safety, progression-free survival (PFS) overall (OS). ORR RECIST 1.1 31.0%, meeting endpoint. most common adverse events were palmar-plantar erythrodysesthesia syndrome (38.1%), alopecia (26.2%) skin rash (23.8%). Median PFS 7.38 months. 1-year OS 80.5%, median not reached. Exploratory single-cell RNA sequencing analyses of peripheral blood mononuclear cells showed long-term responders exhibited T cell receptor repertoire diversification, enrichment genes representing immunotherapy responsiveness MKI67 + proliferating CD8 a higher probability M1-directed monocyte polarization. Our data support further clinical development uHCC provide preliminary insights on biomarkers response. ClinicalTrials.gov identifier: NCT04310709 .

Language: Английский

Citations

24
Repression of latent NF-κB enhancers by PDX1 regulates β cell functional heterogeneity DOI Creative Commons
Benjamin J. Weidemann, Biliana Marcheva, Mikoto Kobayashi

et al.

Cell Metabolism, Journal Year: 2024, Volume and Issue: 36(1), P. 90 - 102.e7

Published: Jan. 1, 2024

Interactions between lineage-determining and activity-dependent transcription factors determine single-cell identity function within multicellular tissues through incompletely known mechanisms. By assembling a atlas of chromatin state human islets, we identified β cell subtypes governed by either high or low activity the factor pancreatic duodenal homeobox-1 (PDX1). cells with reduced PDX1 displayed increased accessibility at latent nuclear κB (NF-κB) enhancers. Pdx1 hypomorphic mice exhibited de-repression NF-κB impaired glucose tolerance night. Three-dimensional analyses in tandem immunoprecipitation (ChIP) sequencing revealed that silences circadian inflammatory enhancers long-range contacts involving SIN3A. Conversely, Bmal1 ablation disrupted genome-wide DNA binding. Finally, antagonizing interleukin (IL)-1β receptor, an target, improved insulin secretion islets. Our studies reveal functional single defined gradient identify as target for insulinotropic therapy.

Language: Английский

Citations

18
OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing DOI Creative Commons
Zehua Zeng,

Yuqing Ma,

Lei Hu

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: July 16, 2024

Abstract Single-cell sequencing is frequently affected by “omission” due to limitations in throughput, yet bulk RNA-seq may contain these ostensibly “omitted” cells. Here, we introduce the single cell trajectory blending from Bulk (BulkTrajBlend) algorithm, a component of OmicVerse suite that leverages Beta-Variational AutoEncoder for data deconvolution and graph neural networks discovery overlapping communities. This approach effectively interpolates restores continuity cells within single-cell RNA datasets. Furthermore, provides an extensive toolkit both analysis, offering seamless access diverse methodologies, streamlining computational processes, fostering exquisite visualization, facilitating extraction significant biological insights advance scientific research.

Language: Английский

Citations

17
Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research DOI Creative Commons

Getnet Molla Desta,

Alemayehu Godana Birhanu

Acta Biochimica Polonica, Journal Year: 2025, Volume and Issue: 72

Published: Feb. 5, 2025

In recent years, significant advancements in biochemistry, materials science, engineering, and computer-aided testing have driven the development of high-throughput tools for profiling genetic information. Single-cell RNA sequencing (scRNA-seq) technologies established themselves as key dissecting sequences at level single cells. These reveal cellular diversity allow exploration cell states transformations with exceptional resolution. Unlike bulk sequencing, which provides population-averaged data, scRNA-seq can detect subtypes or gene expression variations that would otherwise be overlooked. However, a limitation is its inability to preserve spatial information about transcriptome, process requires tissue dissociation isolation. Spatial transcriptomics pivotal advancement medical biotechnology, facilitating identification molecules such their original context within sections single-cell level. This capability offers substantial advantage over traditional techniques. valuable insights into wide range biomedical fields, including neurology, embryology, cancer research, immunology, histology. review highlights approaches, technological developments, associated challenges, various techniques data analysis, applications disciplines microbiology, neuroscience, reproductive biology, immunology. It critical role characterizing dynamic nature individual

Language: Английский

Citations

6
Updates on Immunotherapy and Immune Landscape in Renal Clear Cell Carcinoma DOI Open Access
Myung‐Chul Kim, Jin Zeng, Ryan Kolb

et al.

Cancers, Journal Year: 2021, Volume and Issue: 13(22), P. 5856 - 5856

Published: Nov. 22, 2021

Several clinicopathological features of clear cell renal carcinomas (ccRCC) contribute to make an “atypical” cancer, including resistance chemotherapy, sensitivity anti-angiogenesis therapy and ICIs despite a low mutational burden, CD8+ T infiltration being the predictor for poor prognosis–normally is good prognostic factor in cancer patients. These have brought researchers investigate molecular immunological mechanisms that lead increased infiltrates relatively burdens, as well decipher immune landscape leads better response ICIs. In present study, we summarize past ongoing pivotal clinical trials immunotherapies ccRCC, emphasizing potential cellular success or failure ICI therapy. Single-cell analysis ccRCC has provided more thorough detailed understanding tumor microenvironment facilitated discovery biomarkers from tumor-infiltrating cells. We herein will focus on discussion some major cells, cells tumor-associated macrophages (TAM) ccRCC. further provide perspectives using derived these types potentially improve rate

Language: Английский

Citations

59
DeepVelo : Single-cell transcriptomic deep velocity field learning with neural ordinary differential equations DOI Creative Commons
Zhanlin Chen, William C. King, Ahyeon Hwang

et al.

Science Advances, Journal Year: 2022, Volume and Issue: 8(48)

Published: Nov. 30, 2022

Recent advances in single-cell sequencing technologies have provided unprecedented opportunities to measure the gene expression profile and RNA velocity of individual cells. However, modeling transcriptional dynamics is computationally challenging because high-dimensional, sparse nature measurements nonlinear regulatory relationships. Here, we present DeepVelo , a neural network–based ordinary differential equation that can model complex transcriptome by describing continuous-time changes within We apply public datasets from different platforms (i) formulate on time scales, (ii) instability cell states, (iii) identify developmental driver genes via perturbation analysis. Benchmarking against state-of-the-art methods shows learn more accurate representation field. Furthermore, our studies reveal dynamical systems could exhibit chaotic properties. In summary, allows data-driven discoveries equations delineate dynamics.

Language: Английский

Citations

59
Recent advances in the field of single-cell proteomics DOI Creative Commons
Valdemaras Petrosius, Erwin M. Schoof

Translational Oncology, Journal Year: 2022, Volume and Issue: 27, P. 101556 - 101556

Published: Oct. 19, 2022

The field of single-cell omics is rapidly progressing. Although DNA and RNA sequencing-based methods have dominated the to date, global proteome profiling has also entered main stage. Single-cell proteomics was facilitated by advancements in different aspects mass spectrometry (MS)-based proteomics, such as instrument design, sample preparation, chromatography ion mobility. (scp-MS) moved beyond being a mere technical development, now able deliver actual biological application been successfully applied characterize cell states. Here, we review some key developments scp-MS, provide background field, discuss various available foresee possible future directions.

Language: Английский

Citations

53
Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding DOI Creative Commons
Rongbo Shen, Lin Liu, Zihan Wu

et al.

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Dec. 10, 2022

Spatially resolved transcriptomics provides the opportunity to investigate gene expression profiles and spatial context of cells in naive state, but at low transcript detection sensitivity or with limited throughput. Comprehensive annotating cell types spatially understand biological processes single level remains challenging. Here we propose Spatial-ID, a supervision-based typing method, that combines existing knowledge reference single-cell RNA-seq data information data. We present series benchmarking analyses on publicly available datasets, demonstrate superiority Spatial-ID compared state-of-the-art methods. Besides, apply self-collected mouse brain hemisphere dataset measured by Stereo-seq, shows scalability three-dimensional large field tissues subcellular resolution.

Language: Английский

Citations

52