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1.
Front Immunol ; 15: 1404640, 2024.
Article in English | MEDLINE | ID: mdl-39007128

ABSTRACT

Introduction: Deep learning (DL) models predicting biomarker expression in images of hematoxylin and eosin (H&E)-stained tissues can improve access to multi-marker immunophenotyping, crucial for therapeutic monitoring, biomarker discovery, and personalized treatment development. Conventionally, these models are trained on ground truth cell labels derived from IHC-stained tissue sections adjacent to H&E-stained ones, which might be less accurate than labels from the same section. Although many such DL models have been developed, the impact of ground truth cell label derivation methods on their performance has not been studied. Methodology: In this study, we assess the impact of cell label derivation on H&E model performance, with CD3+ T-cells in lung cancer tissues as a proof-of-concept. We compare two Pix2Pix generative adversarial network (P2P-GAN)-based virtual staining models: one trained with cell labels obtained from the same tissue section as the H&E-stained section (the 'same-section' model) and one trained on cell labels from an adjacent tissue section (the 'serial-section' model). Results: We show that the same-section model exhibited significantly improved prediction performance compared to the 'serial-section' model. Furthermore, the same-section model outperformed the serial-section model in stratifying lung cancer patients within a public lung cancer cohort based on survival outcomes, demonstrating its potential clinical utility. Discussion: Collectively, our findings suggest that employing ground truth cell labels obtained through the same-section approach boosts immunophenotyping DL solutions.


Subject(s)
Deep Learning , Immunophenotyping , Lung Neoplasms , Staining and Labeling , Humans , Lung Neoplasms/immunology , Lung Neoplasms/pathology , Staining and Labeling/methods , Biomarkers, Tumor/metabolism , Male , T-Lymphocytes/immunology , Female
2.
Elife ; 112022 08 08.
Article in English | MEDLINE | ID: mdl-35938926

ABSTRACT

Monitoring autophagic flux is necessary for most autophagy studies. The autophagic flux assays currently available for mammalian cells are generally complicated and do not yield highly quantitative results. Yeast autophagic flux is routinely monitored with the green fluorescence protein (GFP)-based processing assay, whereby the amount of GFP proteolytically released from GFP-containing reporters (e.g. GFP-Atg8), detected by immunoblotting, reflects autophagic flux. However, this simple and effective assay is typically inapplicable to mammalian cells because GFP is efficiently degraded in lysosomes while the more proteolytically resistant red fluorescent protein (RFP) accumulates in lysosomes under basal conditions. Here, we report a HaloTag (Halo)-based reporter processing assay to monitor mammalian autophagic flux. We found that Halo is sensitive to lysosomal proteolysis but becomes resistant upon ligand binding. When delivered into lysosomes by autophagy, pulse-labeled Halo-based reporters (e.g. Halo-LC3 and Halo-GFP) are proteolytically processed to generate Haloligand when delivered into lysosomes by autophagy. Hence, the amount of free Haloligand detected by immunoblotting or in-gel fluorescence imaging reflects autophagic flux. We demonstrate the applications of this assay by monitoring the autophagy pathways, macroautophagy, selective autophagy, and even bulk nonselective autophagy. With the Halo-based processing assay, mammalian autophagic flux and lysosome-mediated degradation can be monitored easily and precisely.


Subject(s)
Autophagy , Lysosomes , Animals , Green Fluorescent Proteins/genetics , Green Fluorescent Proteins/metabolism , Hydrolases , Ligands , Lysosomes/metabolism , Mammals/metabolism , Microtubule-Associated Proteins/metabolism
3.
FEBS Lett ; 596(8): 991-1003, 2022 04.
Article in English | MEDLINE | ID: mdl-35274304

ABSTRACT

Damaged lysosomes can be repaired by calcium release-dependent recruitment of the ESCRT machinery. However, the involvement of annexins, another group of calcium-responding membrane repair proteins, has not been fully addressed. Here, we show that although all ubiquitously expressed annexins (ANXA1, A2, A4, A5, A6, A7, and A11) localize to damaged lysosomes, only ANXA1 and ANXA2 are important for repair. Their recruitment is calcium-dependent, ESCRT-independent, and selective towards lysosomes with large injuries. Lysosomal leakage was more severe when ANXA1 or ANXA2 was depleted compared to that of ESCRT components. These findings suggest that ANXA1 and ANXA2 constitute an additional repair mechanism that serves to minimize leakage from damaged lysosomes.


Subject(s)
Annexin A1 , Annexin A1/genetics , Annexin A1/metabolism , Calcium/metabolism , Endosomal Sorting Complexes Required for Transport/genetics , Endosomal Sorting Complexes Required for Transport/metabolism , Lysosomes/metabolism , Membrane Proteins/metabolism
4.
Autophagy ; 18(7): 1648-1661, 2022 07.
Article in English | MEDLINE | ID: mdl-34812110

ABSTRACT

After its discovery in the 1950 s, the autophagy research field has seen its annual number of publications climb from tens to thousands. The ever-growing number of autophagy publications is a wealth of information but presents a challenge to researchers, especially those new to the field, who are looking for a general overview of the field to, for example, determine current topics of the field or formulate new hypotheses. Here, we employed text mining tools to extract research trends in the autophagy field, including those of genes, terms, and topics. The publication trend of the field can be separated into three phases. The exponential rise in publication number began in the last phase and is most likely spurred by a series of highly cited research papers published in previous phases. The exponential increase in papers has resulted in a larger variety of research topics, with the majority involving those that are directly physiologically relevant, such as disease and modulating autophagy. Our findings provide researchers a summary of the history of the autophagy research field and perhaps hints of what is to come.Abbreviations: 5Y-IF: 5-year impact factor; AIS: article influence score; EM: electron microscopy; HGNC: HUGO gene nomenclature committee; LDA: latent Dirichlet allocation; MeSH: medical subject headings; ncRNA: non-coding RNA.


Subject(s)
Autophagy , Data Mining , Autophagy/genetics , Data Mining/methods , RNA, Untranslated
5.
Dev Cell ; 56(4): 400-402, 2021 02 22.
Article in English | MEDLINE | ID: mdl-33621488

ABSTRACT

Many pathogens are capable of disrupting autophagy within host cells. In this issue of Developmental Cell, Miao et al. discover that the SARS-CoV-2 protein ORF3a inhibits autophagosome-lysosome fusion by dysregulating the HOPS complex.


Subject(s)
Autophagosomes , COVID-19 , Autophagy , Humans , Lysosomes , Membrane Fusion , SARS-CoV-2
6.
Cell Discov ; 6: 6, 2020.
Article in English | MEDLINE | ID: mdl-32047650

ABSTRACT

Autophagy is a major intracellular degradation system that derives its degradative abilities from the lysosome. The most well-studied form of autophagy is macroautophagy, which delivers cytoplasmic material to lysosomes via the double-membraned autophagosome. Other forms of autophagy, namely chaperone-mediated autophagy and microautophagy, occur directly on the lysosome. Besides providing the means for degradation, lysosomes are also involved in autophagy regulation and can become substrates of autophagy when damaged. During autophagy, they exhibit notable changes, including increased acidification, enhanced enzymatic activity, and perinuclear localization. Despite their importance to autophagy, details on autophagy-specific regulation of lysosomes remain relatively scarce. This review aims to provide a summary of current understanding on the behaviour of lysosomes during autophagy and outline unexplored areas of autophagy-specific lysosome research.

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