Trends and Challenges of the Modern Pathology Laboratory for Biopharmaceutical Research Excellence DOI Creative Commons
Sílvia Sisó, Anoop Kavirayani, Suzana Couto

et al.

Toxicologic Pathology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 13, 2024

Pathology, a fundamental discipline that bridges basic scientific discovery to the clinic, is integral successful drug development. Intrinsically multimodal and multidimensional, anatomic pathology continues be empowered by advancements in molecular digital technologies enabling spatial tissue detection of biomolecules such as genes, transcripts, proteins. Over past two decades, breakthroughs biology automation digitization laboratory processes have enabled implementation higher throughput assays generation extensive data sets from sections biopharmaceutical research development units. It our goal provide readers with some rationale, advice, ideas help establish modern meet emerging needs research. This manuscript provides (1) high-level overview current state future vision for excellence practice (2) shared perspectives on how optimally leverage expertise discovery, toxicologic, translational pathologists effective spatial, molecular, support discovery. captures insights experiences, challenges, solutions laboratories various organizations, including their approaches troubleshooting adopting new technologies.

Language: Английский

THItoGene: a deep learning method for predicting spatial transcriptomics from histological images DOI Creative Commons

Yuran Jia,

Junliang Liu, Li Chen

et al.

Briefings in Bioinformatics, Journal Year: 2023, Volume and Issue: 25(1)

Published: Nov. 22, 2023

Abstract Spatial transcriptomics unveils the complex dynamics of cell regulation and transcriptomes, but it is typically cost-prohibitive. Predicting spatial gene expression from histological images via artificial intelligence offers a more affordable option, yet existing methods fall short in extracting deep-level information pathological images. In this paper, we present THItoGene, hybrid neural network that utilizes dynamic convolutional capsule networks to adaptively sense potential molecular signals for exploring relationship between high-resolution pathology image phenotypes expression. A comprehensive benchmark evaluation using datasets human breast cancer cutaneous squamous carcinoma has demonstrated superior performance THItoGene prediction. Moreover, its capacity decipher both context enrichment within specific tissue regions. can be freely accessed at https://github.com/yrjia1015/THItoGene.

Language: Английский

Citations

29
Points to Consider From the ESTP Pathology 2.0 Working Group: Overview on Spatial Omics Technologies Supporting Drug Discovery and Development DOI
Kerstin Hahn, Bettina Amberg, Josep M. Monné Rodríguez

et al.

Toxicologic Pathology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 10, 2025

Recent advances in bioanalytical and imaging technologies have revolutionized our ability to assess complex biological pathological changes within tissue samples. Spatial omics, a rapidly evolving technology, enables the simultaneous detection of multiple biomolecules sections, allowing for high-dimensional molecular profiling microanatomical contexts. This offers powerful opportunity precise, multidimensional exploration disease pathophysiology. The Pathology 2.0 working group European Society Toxicologic (ESTP) includes subgroup dedicated spatial omics technologies. Their primary goal is raise awareness about these emerging their potential applications discovery toxicologic pathology. review provides an overview commonly used, commercially available platforms transcriptomic, proteomic, multiomic analysis, discussing technical aspects illustrative examples applications. To harness power translational drug human safety risk assessment, we emphasize important role pathologists at every stage workflow—from hypothesis generation sample preparation, data interpretation. offer novel opportunities target discovery, lead selection, preclinical clinical development compound development.

Language: Английский

Citations

1
Enablers and challenges of spatial omics, a melting pot of technologies DOI Creative Commons
Theodore Alexandrov, Julio Sáez-Rodríguez, Sinem K. Saka

et al.

Molecular Systems Biology, Journal Year: 2023, Volume and Issue: 19(11)

Published: Oct. 16, 2023

Abstract Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information any data type on spatial scales ranging from subcellular to organismal. From technology development perspective, is highly interdisciplinary that integrates imaging omics, molecular analyses, sequencing mass spectrometry, image analysis bioinformatics. The emergence this not only opened window into biology, but also created multiple opportunities, questions, challenges method developers. Here, we provide the perspective developers what makes unique. After providing brief overview state art, discuss technological enablers present our vision about future applications impact melting pot.

Language: Английский

Citations

17
Recent Advancements in Subcellular Proteomics: Growing Impact of Organellar Protein Niches on the Understanding of Cell Biology DOI
Vanya Bhushan, Aleksandra Nita‐Lazar

Journal of Proteome Research, Journal Year: 2024, Volume and Issue: 23(8), P. 2700 - 2722

Published: March 7, 2024

The mammalian cell is a complex entity, with membrane-bound and membrane-less organelles playing vital roles in regulating cellular homeostasis. Organellar protein niches drive discrete biological processes functions, thus maintaining equilibrium. Cellular such as signaling, growth, proliferation, motility, programmed death require dynamic movements between compartments. Aberrant localization associated wide range of diseases. Therefore, analyzing the subcellular proteome can provide comprehensive overview biology. With recent advancements mass spectrometry, imaging technology, computational tools, deep machine learning algorithms, studies pertaining to their distributions are gaining momentum. These reveal changing interaction networks because "moonlighting proteins" serve discovery tool for disease network mechanisms. Consequently, this review aims repository proteomics subcontexting methods, challenges, future perspectives method developers. In summary, crucial understanding fundamental mechanisms

Language: Английский

Citations

4
DOT: a flexible multi-objective optimization framework for transferring features across single-cell and spatial omics DOI Creative Commons

Arezou Rahimi,

Luís A. Vale-Silva,

Maria Fälth Savitski

et al.

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

Published: June 11, 2024

Single-cell transcriptomics and spatially-resolved imaging/sequencing technologies have revolutionized biomedical research. However, they suffer from lack of spatial information a trade-off resolution gene coverage, respectively. We propose DOT, multi-objective optimization framework for transferring cellular features across these data modalities, thus integrating their complementary information. DOT uses genes beyond those common to the exploits local context, transfers cell-type information, infers absolute/relative abundance cell populations at tissue locations. Thus, bridges single-cell with both high- low-resolution data. Moreover, combines practical aspects related composition, heterogeneity, technical effects, integration prior knowledge. Our fast implementation based on Frank-Wolfe algorithm achieves state-of-the-art or improved performance in localizing estimating expression unmeasured low-coverage

Language: Английский

Citations

4
Integrating Spatially‐Resolved Transcriptomics Data Across Tissues and Individuals: Challenges and Opportunities DOI Creative Commons
Boyi Guo, Wodan Ling, Sang Ho Kwon

et al.

Small Methods, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. The lowering cost SRT data generation presents an unprecedented opportunity create large-scale spatial atlases and enable population-level investigation, integrating across multiple tissues, individuals, species, or phenotypes. Here, unique challenges are described integration, where analytic impact varying resolutions is characterized explored. A succinct review spatially-aware integration strategies provided. Exciting opportunities advance algorithms amenable atlas-scale datasets along with standardized preprocessing methods, leading improved sensitivity reproducibility future further highlighted.

Language: Английский

Citations

0
Evaluation of the microenvironment formed by interferon-β DOI Creative Commons
Mai Yamagishi, Yutaka Hori,

Nobutake Suzuki

et al.

Frontiers in Chemical Biology, Journal Year: 2025, Volume and Issue: 3

Published: Jan. 21, 2025

Heterogeneity in the cellular microenvironment vivo affects variability of reactivity among immune cells. Individual-specific microenvironmental differences play a crucial role determining macroscopic outcomes, such as efficacy immunotherapy and disease progression. The is also featured by cytokines released from cells, significantly regulating cell function. However, overall understanding, at single-cell resolution, how shape promote paracrine signaling remains unclear. In this manuscript, we propose methodology that addresses both itself response to comprehend behavior level. Our objective contribute basic understanding interplay between cells their microenvironment, with particular relevance implications for

Language: Английский

Citations

0
Integrated spatial transcriptome and metabolism study reveals metabolic heterogeneity in human bladder cancer DOI Creative Commons
Yu Lu, Fangdie Ye,

Xuedan Han

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Abstract Bladder cancer (BC) is a malignancy that originates from the cells lining bladder and one of most common cancers urinary system, capable occurring in any part bladder. However, molecular mechanisms underlying malignant transformation BC have not been systematically studied. This study integrated cutting-edge techniques spatial transcriptomics (ST) metabolomics (SM) to capture transcriptomic metabolomic landscapes both adjacent normal tissues. ST results revealed significant upregulation genes associated with choline metabolism glucose metabolism, while related sphingolipid tryptophan were significantly downregulated. Additionally, metabolic reprogramming was observed tissues, including as well downregulation metabolism. These alterations may play crucial role promoting tumorigenesis immune evasion BC. The interpretation SM data this offers new insights into progression provides valuable clues for prevention treatment

Language: Английский

Citations

0
An overview of single-cell omics, spatial omics, and omics integration in axon regeneration DOI
Michael Coronado, Emily Neag,

Nikhil Gandikota

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 425 - 437

Published: Jan. 1, 2025

Language: Английский

Citations

0
A perspective on FAIR quality control in multiplexed imaging data processing DOI Creative Commons
Wouter-Michiel Vierdag, Sinem K. Saka

Frontiers in Bioinformatics, Journal Year: 2024, Volume and Issue: 4

Published: Feb. 9, 2024

Multiplexed imaging approaches are getting increasingly adopted for of large tissue areas, yielding big datasets both in terms the number samples and size image data per sample. The processing analysis these is complex owing to frequent technical artifacts heterogeneous profiles from a high stained targets To streamline multiplexed images, automated pipelines making use state-of-the-art algorithms have been developed. In pipelines, output quality one step typically dependent on previous errors each step, even when they appear minor, can propagate confound results. Thus, rigorous control (QC) at different steps pipeline paramount importance proper interpretation results ensuring reusability data. Ideally, QC should become an integral easily retrievable part process. Yet, limitations currently available frameworks make integration interactive difficult Given increasing complexity datasets, we present challenges integrating as well suggest possible solutions that build top recent advances bioimage analysis.

Language: Английский

Citations

2