A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

Genome Medicine, Journal Year: 2022, Volume and Issue: 14(1)

Published: Feb. 28, 2022

Abstract Rare diseases affect 30 million people in the USA and more than 300–400 worldwide, often causing chronic illness, disability, premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with medical literature. A large number of patients remain undiagnosed for years many even die without an accurate diagnosis. In recent years, gene panels, microarrays, exome sequencing have helped to identify molecular cause such diseases. These technologies allowed diagnoses a sizable proportion (25–35%) patients, actionable findings. However, these undiagnosed. this review, we focus that can be adopted if is unrevealing. We discuss benefits whole genome additional benefit may offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, methyl profiling. highlight computational methods help regionally distant similar phenotypes or genetic mutations. Finally, describe approaches automate accelerate genomic analysis. The strategies discussed here are intended serve as guide clinicians researchers next steps when encountering non-diagnostic exomes.

Language: Английский

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Improving head and neck cancer therapies by immunomodulation of the tumour microenvironment

Nature reviews. Cancer, Journal Year: 2022, Volume and Issue: 23(3), P. 173 - 188

Published: Dec. 1, 2022

Language: Английский

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Pancreatic cancer environment: from patient-derived models to single-cell omics

Molecular Omics, Journal Year: 2024, Volume and Issue: 20(4), P. 220 - 233

Published: Jan. 1, 2024

This review initially presents relevant patient-derived models, including PDXs, PDOs, and PDEs. Subsequently, a comprehensive summary of single-cell analyses conducted on these models is provided.

Language: Английский

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Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research

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

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Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels T cell-related prognostic risk model and tumor immune microenvironment modulation in triple-negative breast cancer

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 161, P. 107066 - 107066

Published: May 27, 2023

Language: Английский

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Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer

Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, Journal Year: 2025, Volume and Issue: unknown, P. 167693 - 167693

Published: Jan. 1, 2025

Language: Английский

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Single-Cell Sequencing: Genomic and Transcriptomic Approaches in Cancer Cell Biology

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(5), P. 2074 - 2074

Published: Feb. 27, 2025

This article reviews the impact of single-cell sequencing (SCS) on cancer biology research. SCS has revolutionized our understanding and tumor heterogeneity, clonal evolution, complex interplay between cells microenvironment. provides high-resolution profiling individual in genomic, transcriptomic, epigenomic landscapes, facilitating detection rare mutations, characterization cellular diversity, integration molecular data with phenotypic traits. The multi-omics provided a multidimensional view states regulatory mechanisms cancer, uncovering novel therapeutic targets. Advances computational tools, artificial intelligence (AI), machine learning have been crucial interpreting vast amounts generated, leading to identification new biomarkers development predictive models for patient stratification. Furthermore, there emerging technologies such as spatial transcriptomics situ sequencing, which promise further enhance microenvironment organization interactions. As its related continue advance, they are expected drive significant advances personalized diagnostics, prognosis, therapy, ultimately improving outcomes era precision oncology.

Language: Английский

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Application of single-cell sequencing to the research of tumor microenvironment

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: Oct. 27, 2023

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional hybrid samples, it has revolutionized our understanding of genetic complexity tumor progression. Moreover, microenvironment (TME) plays crucial role formation, development response to treatment tumors. The application ushered new age TME analysis, revealing not only blueprint pan-cancer immune microenvironment, but also differentiation routes cells, as well predicting prognosis. Thus, combination analysis provides unique opportunity unravel molecular mechanisms underlying In this review, we summarize recent advances highlighting their potential applications cancer research clinical translation.

Language: Английский

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Advances in Melanoma: From Genetic Insights to Therapeutic Innovations

Biomedicines, Journal Year: 2024, Volume and Issue: 12(8), P. 1851 - 1851

Published: Aug. 14, 2024

Advances in melanoma research have unveiled critical insights into its genetic and molecular landscape, leading to significant therapeutic innovations. This review explores the intricate interplay between alterations, such as mutations BRAF, NRAS, KIT, pathogenesis. The MAPK PI3K/Akt/mTOR signaling pathways are highlighted for their roles tumor growth resistance mechanisms. Additionally, this delves impact of epigenetic modifications, including DNA methylation histone changes, on progression. microenvironment, characterized by immune cells, stromal soluble factors, plays a pivotal role modulating behavior treatment responses. Emerging technologies like single-cell sequencing, CRISPR-Cas9, AI-driven diagnostics transforming research, offering precise personalized approaches treatment. Immunotherapy, particularly checkpoint inhibitors mRNA vaccines, has revolutionized therapy enhancing body’s response. Despite these advances, mechanisms remain challenge, underscoring need combined therapies ongoing achieve durable comprehensive overview aims highlight current state transformative impacts advancements clinical practice.

Language: Английский

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Highly Accurate Estimation of Cell Type Abundance in Bulk Tissues Based on Single‐Cell Reference and Domain Adaptive Matching

Advanced Science, Journal Year: 2023, Volume and Issue: 11(7)

Published: Dec. 10, 2023

Abstract Accurately identifies the cellular composition of complex tissues, which is critical for understanding disease pathogenesis, early diagnosis, and prevention. However, current methods deconvoluting bulk RNA sequencing (RNA‐seq) typically rely on matched single‐cell (scRNA‐seq) as a reference, can be limiting due to differences in distribution potential invalid information from references. Hence, novel computational method named SCROAM introduced address these challenges. transforms scRNA‐seq RNA‐seq into shared feature space, effectively eliminating distributional latent space. Subsequently, cell‐type‐specific expression matrices are generated data, facilitating precise identification cell types within tissues. The performance assessed through benchmarking against simulated real datasets, demonstrating its accuracy robustness. To further validate SCROAM's performance, experiments conducted mouse spinal cord tissue, with applied identify tissue. Results indicate that highly effective tool identifying similar types. An integrated analysis liver cancer primary glioblastoma then performed. Overall, this research offers perspective delivering insights pathogenesis therapeutic strategies.

Language: Английский

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