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Editorial
. 2022 Jul;257(4):379-382.
doi: 10.1002/path.5972.

Recent Advances in Pathology: the 2022 Annual Review Issue of The Journal of Pathology

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Editorial

Recent Advances in Pathology: the 2022 Annual Review Issue of The Journal of Pathology

C Simon Herrington et al. J Pathol. 2022 Jul.

Abstract

The 2022 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 15 invited reviews on research areas of growing importance in pathology. This year, the articles include those that focus on digital pathology, employing modern imaging techniques and software to enable improved diagnostic and research applications to study human diseases. This subject area includes the ability to identify specific genetic alterations through the morphological changes they induce, as well as integrating digital and computational pathology with 'omics technologies. Other reviews in this issue include an updated evaluation of mutational patterns (mutation signatures) in cancer, the applications of lineage tracing in human tissues, and single cell sequencing technologies to uncover tumour evolution and tumour heterogeneity. The tissue microenvironment is covered in reviews specifically dealing with proteolytic control of epidermal differentiation, cancer-associated fibroblasts, field cancerisation, and host factors that determine tumour immunity. All of the reviews contained in this issue are the work of invited experts selected to discuss the considerable recent progress in their respective fields and are freely available online (https://onlinelibrary.wiley.com/journal/10969896). © 2022 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Keywords: 3D reconstruction; DNA sequencing; PAR1; PAR2; QuPath; adult stem cells; artificial intelligence; asthma; biomarkers; breast cancer; cancer; cancer-adjacent tissues; cancer-associated fibroblasts; chromothripsis; chronic obstructive pulmonary disease; clonal dynamics; clonality analysis; colon; computational pathology; convolutional neural networks; copy number aberrations; copy number signatures; cystic fibrosis; data repository; desquamation; digital pathology; epidermal inflammation; epidermis; epithelial transition states; extrachromosomal DNA; field cancerisation; filaggrin; functional pathology; genomics; haemopoietic stem cells; host; idiopathic pulmonary fibrosis; image analysis; image processing; immune checkpoint inhibitors; immune system; immunotherapy; in situ hybridisation; in vivo models; intestinal stem cells; intra-tumour heterogeneity; kallikrein-related peptidases; lineage tracing; lung atlas; lung diseases; lung progenitors; lung stem cells; machine learning; metabolome; microbiome; mutational signatures; open science; patient stratification; prediction; prognosis; protease inhibitors; proteolytic cascades; quantitative methods; single cell DNA sequencing; single cell RNA sequencing; single cell transcriptomics; skin diseases; skin physiology; software; structural variants; subclone; tumour evolution; tumour phylogeny; virtual slide; whole genome sequencing; whole-slide imaging; whole-slide scanning.

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References

    1. Zarella MD, Alvarez KR. High throughput whole-slide scanning to enable large-scale data repository building. J Pathol 2022; 257: 383-390.
    1. Bankhead P. Developing image analysis methods for digital pathology. J Pathol 2022; 257: 391-402.
    1. Kramer CJH, Vreeswijk MPG, Thijssen B, et al. Beyond the snapshot: optimizing prognostication and prediction by moving from fixed to functional multidimensional cancer pathology. J Pathol 2022; 257: 403-412.
    1. Viswanthan VS, Toro P, Corredor G, et al. The state of the art for artificial intelligence in lung digital pathology. J Pathol 2022; 257: 413-429.
    1. Cifci D, Foersch S, Kather JN. Artificial intelligence to identify genetic alterations in conventional histopathology. J Pathol 2022; 257: 430-444.

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