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1.
Oncoimmunology ; 13(1): 2347441, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38694625

RESUMO

In clinical practice, the administration of adjuvant chemotherapy (ACT) following tumor surgical resection raises a critical dilemma for stage II colon cancer (CC) patients. The prognostic features used to identify high-risk CC patients rely on the pathological assessment of tumor cells. Currently, these factors are considered for stratifying patients who may benefit from ACT at early CC stages. However, the extent to which these factors predict clinical outcomes (i.e. recurrence, survival) remains highly controversial, also uncertainty persists regarding patients' response to treatment, necessitating further investigation. Therefore, an imperious need is to explore novel biomarkers that can reliably stratify patients at risk, to optimize adjuvant treatment decisions. Recently, we evaluated the prognostic and predictive value of Immunoscore (IS), an immune digital-pathology assay, in stage II CC patients. IS emerged as the sole significant parameter for predicting disease-free survival (DFS) in high-risk patients. Moreover, IS effectively stratified patients who would benefit most from ACT based on their risk of recurrence, thus predicting their outcomes. Notably, our findings revealed that digital IS outperformed the visual quantitative assessment of the immune response conducted by expert pathologists. The latest edition of the WHO classification for digestive tumor has introduced the evaluation of the immune response, as assessed by IS, as desirable and essential diagnostic criterion. This supports the revision of current cancer guidelines and strongly recommends the implementation of IS into clinical practice as a patient stratification tool, to guide CC treatment decisions. This approach may provide appropriate personalized therapeutic decisions that could critically impact early-stage CC patient care.


Assuntos
Neoplasias do Colo , Humanos , Neoplasias do Colo/imunologia , Neoplasias do Colo/patologia , Medição de Risco , Quimioterapia Adjuvante , Prognóstico , Estadiamento de Neoplasias , Biomarcadores Tumorais/metabolismo , Recidiva Local de Neoplasia/imunologia , Intervalo Livre de Doença
2.
Cancers (Basel) ; 16(9)2024 Apr 26.
Artigo em Inglês | MEDLINE | ID: mdl-38730638

RESUMO

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

3.
Cancers (Basel) ; 15(16)2023 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-37627073

RESUMO

BACKGROUND: The Immunoscore (IS) is a quantitative digital pathology assay that evaluates the immune response in cancer patients. This study reports on the reproducibility of pathologists' visual assessment of CD3+- and CD8+-stained colon tumors, compared to IS quantification. METHODS: An international group of expert pathologists evaluated 540 images from 270 randomly selected colon cancer (CC) cases. Concordance between pathologists' T-score, corresponding hematoxylin-eosin (H&E) slides, and the digital IS was evaluated for two- and three-category IS. RESULTS: Non-concordant T-scores were reported in more than 92% of cases. Disagreement between semi-quantitative visual assessment of T-score and the reference IS was observed in 91% and 96% of cases before and after training, respectively. Statistical analyses showed that the concordance index between pathologists and the digital IS was weak in two- and three-category IS, respectively. After training, 42% of cases had a change in T-score, but no improvement was observed with a Kappa of 0.465 and 0.374. For the 20% of patients around the cut points, no concordance was observed between pathologists and digital pathology analysis in both two- and three-category IS, before or after training (all Kappa < 0.12). CONCLUSIONS: The standardized IS assay outperformed expert pathologists' T-score evaluation in the clinical setting. This study demonstrates that digital pathology, in particular digital IS, represents a novel generation of immune pathology tools for reproducible and quantitative assessment of tumor-infiltrated immune cell subtypes.

4.
Oncoimmunology ; 12(1): 2243169, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37554310

RESUMO

In the last decade, a plethora of immunotherapeutic strategies have been designed to modulate the tumor immune microenvironment. In particular, immune checkpoint (IC) blockade therapies present the most promising advances made in cancer treatment in recent years. In non-small cell lung cancer (NSCLC), biomarkers predicting response to IC treatments are currently lacking. We have recently identified Immunoscore-IC, a powerful biomarker that predicts the efficiency of immune-checkpoint inhibitors (ICIs) in NSCLC patients. Immunoscore-IC is an in vitro diagnostic assay that quantifies densities of PD-L1+, CD8+ cells, and distances between CD8+ and PD-L1+ cells in the tumor microenvironment. Immunoscore-IC can classify responder vs non-responder NSCLC patients for ICIs therapy and is revealed as a promising predictive marker of response to anti-PD-1/PD-L1 immunotherapy in these patients. Immunoscore-IC has also shown a significant predictive value, superior to the currently used PD-L1 marker. In colorectal cancer (CRC), the addition of atezolizumab to first-line FOLFOXIRI plus bevacizumab improved progression-free survival (PFS) in patients with previously untreated metastatic CRC. In the AtezoTRIBE trial, Immunoscore-IC emerged as the first biomarker with robust predictive value in stratifying pMMR metastatic CRC patients who critically benefit from checkpoint inhibitors. Thus, Immunoscore-IC could be a universal biomarker to predict response to PD-1/PD-L1 checkpoint inhibitor immunotherapy across multiple cancer indications. Therefore, cancer patient stratification (by Immunoscore-IC), based on the presence of T lymphocytes and PD-L1 potentially provides support for clinicians to guide them through combination cancer treatment decisions.


Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Neoplasias Pulmonares/tratamento farmacológico , Antígeno B7-H1 , Linfócitos T CD8-Positivos , Imunoterapia , Microambiente Tumoral
5.
PLoS One ; 6(3): e17763, 2011 Mar 15.
Artigo em Inglês | MEDLINE | ID: mdl-21423573

RESUMO

BACKGROUND: Genetic analysis of the Drosophila septate junctions has greatly contributed to our understanding of the mechanisms controlling the assembly of these adhesion structures, which bear strong similarities with the vertebrate tight junctions and the paranodal septate junctions. These adhesion complexes share conserved molecular components and have a common function: the formation of paracellular barriers restraining the diffusion of solutes through epithelial and glial envelopes. METHODOLOGY/PRINCIPAL FINDINGS: In this work we characterise the function of the Drosophila cold gene, that codes for a protein belonging to the Ly6 superfamily of extracellular ligands. Analysis of cold mutants shows that this gene is specifically required for the organisation of the septate junctions in epithelial tissues and in the nervous system, where its contribution is essential for the maintenance of the blood-brain barrier. We show that cold acts in a cell autonomous way, and we present evidence indicating that this protein could act as a septate junction component. CONCLUSION/SIGNIFICANCE: We discuss the specific roles of cold and three other Drosophila members of the Ly6 superfamily that have been shown to participate in a non-redundant way in the process of septate junction assembly. We propose that vertebrate Ly6 proteins could fulfill analogous roles in tight junctions and/or paranodal septate junctions.


Assuntos
Barreira Hematoencefálica/metabolismo , Proteínas de Drosophila/metabolismo , Drosophila melanogaster/metabolismo , Junções Íntimas/metabolismo , Sequência de Aminoácidos , Animais , Membrana Celular/metabolismo , Proteínas de Drosophila/química , Proteínas de Drosophila/genética , Drosophila melanogaster/citologia , Drosophila melanogaster/embriologia , Ectoderma/citologia , Ectoderma/metabolismo , Embrião não Mamífero/citologia , Embrião não Mamífero/metabolismo , Células Epiteliais/citologia , Células Epiteliais/metabolismo , Genes de Insetos/genética , Larva/citologia , Larva/metabolismo , Dados de Sequência Molecular , Morfogênese , Neuroglia/citologia , Neuroglia/metabolismo , Fenótipo , Transporte Proteico , Glândulas Salivares/citologia , Glândulas Salivares/metabolismo , Frações Subcelulares/metabolismo , Traqueia/citologia , Traqueia/embriologia , Traqueia/metabolismo , Asas de Animais/citologia , Asas de Animais/metabolismo
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