sCellST: a Multiple Instance Learning approach to predict single-cell gene expression from H&E images using spatial transcriptomics DOI Creative Commons

Loïc Chadoutaud,

Marvin Lerousseau,

Daniel Herrero-Saboya

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 8, 2024

Abstract Advancing our understanding of tissue organization and its disruptions in disease remains a key focus biomedical research. Histological slides stained with Hematoxylin Eosin (H&E) provide an abundant source morphological information, while Spatial Transcriptomics (ST) enables detailed, spatiallyresolved gene expression (GE) analysis, though at high cost limited clinical accessibility. Predicting GE directly from H&E images using ST as reference has thus become attractive objective; however, current patch-based approaches lack single-cell resolution. Here, we present sCellST, multipleinstance learning model that predicts by leveraging cell morphology alone, achieving remarkable predictive accuracy. When tested on pancreatic ductal adenocarcinoma dataset, sCellST outperformed traditional methods, underscoring the value basing predictions rather than patches. Additionally, demonstrate can detect subtle differences among types utilizing marker genes ovarian cancer samples. Our findings suggest this approach could enable level across large cohorts H&E-stained slides, providing innovative means to valorize resource

Language: Английский

Transcending the hegemony of the molecular machine through an organic renewal of biology and biomedicine DOI
Amy E. Shyer, Alan R. Rodrigues

Cells and Development, Journal Year: 2025, Volume and Issue: unknown, P. 204018 - 204018

Published: March 1, 2025

Language: Английский

Citations

0
Efficient Discovery of Robust Prognostic Biomarkers and Signatures in Solid Tumors DOI
Zaoqu Liu, Jinhai Deng, Hui Xu

et al.

Cancer Letters, Journal Year: 2025, Volume and Issue: unknown, P. 217502 - 217502

Published: Jan. 1, 2025

Language: Английский

Citations

0
BarQC: Quality Control and Preprocessing for SPLiT-Seq Data DOI Creative Commons
Maria Rosselló, Sophie Tandonnet, Isabel Almudí

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Abstract Summary SPLiT-seq is a cost-effective single-cell RNA-sequencing method, easy to implement in most laboratories. However, the data preprocessing not straightforward, and no solution currently exists perform basic quality control of data. Here, we present BarQC, tool, which identifies corrects barcodes provides report on distribution each barcode UMI as well an estimation number cells Additionally, BarQC can be incorporated pipeline by constructing sorted BAM file tagged with sequence. Availability Implementation was implemented Python3, its source code freely available GitHub at https://github.com/mayflylab/barQC/ under MIT Licence. has been tested Linux server.

Language: Английский

Citations

0
Comprehensive analysis of lipid metabolic signatures identified CEBPD promotes breast cancer cell proliferation DOI Creative Commons
Yu Zhao,

Huan He,

Linyan Huang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 24, 2025

Breast cancer (BRCA) remains the leading cause of cancer-related mortality worldwide, with lipid metabolism emerging as a critical factor in tumor progression that influences cell proliferation, migration, and immune response. Insights into signatures associated genes may offer new prognostic therapeutic avenues. In this study, we leveraged scRNA-seq bulk transcriptome data to assess expression patterns significance metabolism-related BRCA. Through single-cell transcriptomic analysis primary BRCA samples, identified specific set signature constructed risk model based on these signatures. This enables patient stratification by scores, supporting an integrated metabolism, landscape, clinical outcomes. Importantly, CEBPD, ABCA1, CYP27A1 independent linked functional assays revealing inhibitory role for CEBPD proliferation. Our findings underscore influence adipocytes propose potential target intervention. study provides foundation further exploration metabolism-based strategies enhance

Language: Английский

Citations

0
Single‐Cell Transcriptomic Analysis Reveals an Aggressive Basal‐Like Tumor Cell Subpopulation Associated With Poor Prognosis in Intrahepatic Cholangiocarcinoma DOI

Changyi Liao,

Yuting Zhang, Jing Yang

et al.

Journal of Gastroenterology and Hepatology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

ABSTRACT Background and Aim Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer whose incidence increasing globally. However, high tumor heterogeneity of ICC restricts efficacy available systematic therapies. We aim to dissect utilizing high‐resolution single‐cell RNA sequencing identify novel therapeutic targets. Methods performed (scRNA‐seq) 26 samples from 23 patients spatial transcriptomic six sections patients. Bulk RNA‐seq data two public datasets were used for validation. Additionally, immunohistochemical staining multiplex immunofluorescence conducted validate infiltration distribution cells in microenvironment. Results discovered that malignant exhibited a remarkably degree heterogeneity. identified basal‐like cell subpopulation characterized by expression basal epithelial related genes including KRT5, KRT6A, KRT17. The was activation MET signaling extracellular matrix organization associated with invasion correlated poor prognosis. Cell–cell communication analysis further showed significant HGF‐MET interaction between inflammatory cancer–associated fibroblasts (iCAFs) cells. found iCAFs major source HGF environment contributed phenotype formation axis. Conclusions an aggressive subpopulation, which prognosis ICC. pathway contributes aggressiveness serves as target

Language: Английский

Citations

0
Decoding melanoma’s cellular mosaic to unlock immunotherapy potential DOI
Joanna Poźniak, Jean‐Christophe Marine

Trends in Cell Biology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
A highly resolved integrated single-cell atlas of HPV-negative head and neck cancer DOI Creative Commons
Lina Kroehling, Andrew Chen,

Anthony Spinella

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 4, 2025

Abstract Head and Neck Squamous Cell Carcinomas (HNSCC) are the seventh most prevalent form of cancer associated with human papilloma virus infection (HPV-positive) or tobacco alcohol use (HPV-negative). HPV-negative HNSCCs have a high recurrence rate, individual patients’ responses to treatment vary greatly due level cellular heterogeneity tumor its microenvironment. Here, we describe HNSCC single cell atlas, which created by integrating six publicly available datasets encompassing over 230,000 cells across 54 patients. We contextualized relationships between existing signatures populations, identified new subpopulations, show power this large-scale resource robustly identify associations transcriptional clinical phenotypes that would not be possible discover using fewer reveal previously undefined myeloid population, sex-associated changes in type proportions, novel interactions CXCL8-positive fibroblasts vascular endothelial cells. Beyond our findings, atlas will serve as public for high-resolution characterization HNSCC.

Language: Английский

Citations

0
BUB1B promotes cisplatin resistance in gastric cancer via Rad51-mediated DNA damage repair DOI
Zhe Qin,

Fangzhou Ye,

Jiayi Wang

et al.

Translational Oncology, Journal Year: 2025, Volume and Issue: 54, P. 102334 - 102334

Published: March 7, 2025

Language: Английский

Citations

0
Application and Progression of Single‐Cell RNA Sequencing in Diabetes Mellitus and Diabetes Complications DOI Creative Commons

Jiajing Hong,

Shiqi Lu,

Guohui Shan

et al.

Journal of Diabetes Research, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Diabetes is a systemic metabolic disorder primarily caused by insulin deficiency and resistance, leading to chronic hyperglycemia. Prolonged diabetes can result in damage multiple organs, including the heart, brain, liver, muscles, adipose tissue, thereby causing various fatal complications such as diabetic retinopathy, cardiomyopathy, nephropathy. Single‐cell RNA sequencing (scRNA‐seq) has emerged valuable tool for investigating cell diversity pathogenesis of identifying potential therapeutic targets or complications. This review provides comprehensive overview recent applications scRNA‐seq diabetes‐related researches highlights novel biomarkers immunotherapy with cell‐type information its associated

Language: Английский

Citations

0
Lactylation in Glioblastoma: A Novel Epigenetic Modifier Bridging Epigenetic Plasticity and Metabolic Reprogramming DOI Open Access

Qingya Qiu,

Hui Deng,

Ping Song

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(7), P. 3368 - 3368

Published: April 4, 2025

Glioblastoma, the most common and aggressive primary malignant brain tumor, is characterized by a high rate of recurrence, disability, lethality. Therefore, there pressing need to develop more effective prognostic biomarkers treatment approaches for glioblastoma. Lactylation, an emerging form protein post-translational modification, has been closely associated with lactate, metabolite glycolysis. Since initial identification lactylation sites in core histones 2019, accumulating evidence shown critical role that plays glioblastoma development, assessment poor clinical prognosis, immunosuppression, which provides fresh angle investigating connection between metabolic reprogramming epigenetic plasticity cells. The objective this paper present overview roles expanding field research explore practical value developing novel plans combining targeted therapy immunotherapy.

Language: Английский

Citations

0