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Diagnostics
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New Promising Diagnostic Signatures in Histopathological Diagnosis
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New Promising Diagnostic Signatures in Histopathological Diagnosis

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 4452

Special Issue Editor

Prof. Dr. Ovidiu Laurean Pop

E-Mail Website
Guest Editor
Department of Pathology, County Clinical Emergency Hospital, Faculty of Medicine and Pharmacy, University of Oradea, 1 December Sq. No. 10, 410087 Oradea, Romania
Interests: molecular diagnosis; biomarkers; histopathology; immune response

Special Issue Information

Dear Colleagues,

Histopathological diagnosis has been at the backbone of clinical medicine for over a century, as the microscopic examination of tissue samples can provide detailed insights into the nature, origin, and progression of diseases. Recent advancements in molecular biology, imaging techniques, and data analytics have led to the discovery of new diagnostic signatures. Some general areas where these new promising signatures have been emerging: artificial intelligence and machine learning, immunohistochemistry (IHC) markers, molecular diagnostics, digital pathology, liquid biopsies, quantitative histopathology, deep learning, and convolutional neural networks.

It's crucial to understand that while these advancements hold promise, they also come with challenges. The interpretation of complex data sets, integration of various diagnostic tools, and establishing robustness and reproducibility are all areas that need further work. The integration of various diagnostic signatures from multiple sources (like combining genomic data with histopathological images) will likely provide even more refined and accurate diagnostic tools for clinicians.

The purpose of this Special Issue is to explore the new frontiers in pathology as well as the integration of these new perspectives for the benefit of the patient.

Prof. Dr. Ovidiu Laurean Pop
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • AI
  • IHC
  • digital pathology
  • liquid biopsies
  • deep learning
  • neural network

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Published Papers (3 papers)

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Research

18 pages, 7292 KiB  
Article
Concurrent Viewing of H&E and Multiplex Immunohistochemistry in Clinical Specimens
by Larry E. Morrison, Tania M. Larrinaga, Brian D. Kelly, Mark R. Lefever, Rachel C. Beck and Daniel R. Bauer
Diagnostics 2025, 15(2), 164; https://doi.org/10.3390/diagnostics15020164 - 13 Jan 2025
Viewed by 953
Abstract
Background/Objectives: Performing hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC) on the same specimen slide provides advantages that include specimen conservation and the ability to combine the H&E context with biomarker expression at the individual cell level. We previously used invisible deposited chromogens [...] Read more.
Background/Objectives: Performing hematoxylin and eosin (H&E) staining and immunohistochemistry (IHC) on the same specimen slide provides advantages that include specimen conservation and the ability to combine the H&E context with biomarker expression at the individual cell level. We previously used invisible deposited chromogens and dual-camera imaging, including monochrome and color cameras, to implement simultaneous H&E and IHC. Using this approach, conventional H&E staining could be simultaneously viewed in color on a computer monitor alongside a monochrome video of the invisible IHC staining, while manually scanning the specimen. Methods: We have now simplified the microscope system to a single camera and increased the IHC multiplexing to four biomarkers using translational assays. The color camera used in this approach also enabled multispectral imaging, similar to monochrome cameras. Results: Application is made to several clinically relevant specimens, including breast cancer (HER2, ER, and PR), prostate cancer (PSMA, P504S, basal cell, and CD8), Hodgkin’s lymphoma (CD15 and CD30), and melanoma (LAG3). Additionally, invisible chromogenic IHC was combined with conventional DAB IHC to present a multiplex IHC assay with unobscured DAB staining, suitable for visual interrogation. Conclusions: Simultaneous staining and detection, as described here, provides the pathologist a means to evaluate complex multiplexed assays, while seated at the microscope, with the added multispectral imaging capability to support digital pathology and artificial intelligence workflows of the future. Full article
(This article belongs to the Special Issue New Promising Diagnostic Signatures in Histopathological Diagnosis)
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11 pages, 4286 KiB  
Article
Novel Immunohistochemical Profiling of Small-Cell Lung Cancer: Correlations Between Tumor Subtypes and Immune Microenvironment
by Alon Vigdorovits, Gheorghe-Emilian Olteanu, Andrei-Vasile Pascalau, Radu Pirlog, Ioana Berindan-Neagoe and Ovidiu-Laurean Pop
Diagnostics 2024, 14(23), 2660; https://doi.org/10.3390/diagnostics14232660 - 26 Nov 2024
Viewed by 1343
Abstract
Background/Objectives: Small-cell lung cancer (SCLC) is a highly aggressive malignancy with an emerging molecular classification based on the expression of the transcription factors ASCL1, NEUROD1, and POU2F3. This study aimed to explore the relationship between these novel subtypes and the tumor immune microenvironment [...] Read more.
Background/Objectives: Small-cell lung cancer (SCLC) is a highly aggressive malignancy with an emerging molecular classification based on the expression of the transcription factors ASCL1, NEUROD1, and POU2F3. This study aimed to explore the relationship between these novel subtypes and the tumor immune microenvironment (TIME), particularly CD8+ and CD4+ tumor-infiltrating lymphocytes (TILs). Methods: In 51 cases of patients with SCLC, immunohistochemical (IHC) stains for ASCL1, NEUROD1, POU2F3, CD56, Ki67, CD8, and CD4 were performed. H-scores for the novel transcription factors were calculated to determine tumor subtype. CD8+ and CD4+ TIL counts were averaged across 10 high-power fields. The Kruskal–Wallis test and subsequent post hoc Dunn tests were used to determine the differences in transcription factor expression and TILs across subtypes. Results: In our cohort, 68.62% of our cases were SCLC-A, 9.80% were SCLC-N, 7.84% were SCLC-P, and 13.72% were SCLC-I. Significant differences were observed in the expression of ASCL1, NEUROD1, and POU2F3 across subtypes. CD8+ TILs were more abundant in SCLC-P and SCLC-I. CD8+ TILs were negatively correlated with ASCL1 expression (p < 0.05) and positively correlated with POU2F3 expression (p < 0.005). Conclusions: This study highlights the need to integrate the novel SCLC classification with data regarding the TIME to better inform patient prognosis and treatment. Full article
(This article belongs to the Special Issue New Promising Diagnostic Signatures in Histopathological Diagnosis)
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11 pages, 978 KiB  
Article
Is There an Immunohistochemical PD-L1 Cut-Off Point That Serves as a Prognostic Indicator for Large B-Cell Lymphomas?
by Selcuk Cin, Suat Hilal Aki, Tugrul Elverdi, Deniz Ozmen and Ayse Salihoglu
Diagnostics 2024, 14(11), 1167; https://doi.org/10.3390/diagnostics14111167 - 31 May 2024
Viewed by 1026
Abstract
The aim of this study is to investigate whether there is a cut-off value for PD-L1 expression in large B-cell lymphomas that predicts prognosis, and to clarify the relationship between PD-L1 expression and histopathological as well as clinical parameters. The study included a [...] Read more.
The aim of this study is to investigate whether there is a cut-off value for PD-L1 expression in large B-cell lymphomas that predicts prognosis, and to clarify the relationship between PD-L1 expression and histopathological as well as clinical parameters. The study included a total of 130 patients who were diagnosed with large B-cell lymphoma at Istanbul University-Cerrahpasa, Cerrahpasa Faculty of Medicine, Pathology Department. Biopsy samples were assessed using the PD-L1 immunohistochemical antibody (Dako, 22C3 clone). The patients had a mean age of 54 ± 17 years, with a median age of 56 years. No statistically significant difference was observed between the groups in terms of survival when the 30% cut-off value was used. However, a noteworthy discrepancy in survival became apparent when the cut-off point was established at 70%. Among the diffuse large B-cell lymphoma-not otherwise specified (DLBCL-NOS) category, the activated B-cell-like (ABC-like) phenotype showed higher PD-L1 expression compared to the germinal center B-cell-like (GCB-like) phenotype. Immunohistochemical PD-L1 expression emerged as a prognostic factor, particularly significant in the ABC-like phenotype. Full article
(This article belongs to the Special Issue New Promising Diagnostic Signatures in Histopathological Diagnosis)
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