Laboratory Investigation最新文献

c-Met overexpression may identify patients who benefit from MET inhibitor therapy. However, concordance among c-Met immunohistochemistry (IHC) assays and scoring system reliability remain unclear. We retrospectively analyzed 150 lung adenocarcinoma specimens (Dec 2018-Mar 2023) using five c-Met IHC assays (SP44_R, SP44_Z, D1C2, LBP4-C-MET, and 811B7F4), scored by H score, clinical score, 2-tier classifications (H score ≥150 or clinical score 2+/3+ as positive). Next generation sequencing for MET alterations was performed on 107 samples. H scores of the five assays showed excellent inter-assay reliability (Intraclass Correlation Coefficient =0.953). Compared with SP44_R which is the most frequently used antibody in the clinical trial, SP44_Z had the highest correlation with it (ρ=0.851), followed by D1C2 (ρ=0.818), LBP4-C-MET (ρ=0.786), and 811B7F4 (ρ=0.737). Among five assays, Kendall's W for clinical score was 0.697; Fleiss' κ for 2-tier H score was 0.51 and for 2-tier clinical score agreement was 0.494. In comparison to the clinical score 3+ of SP44_R, SP44_Z and 811B7F4 showed moderate reliability (κ=0.483), LBP4-C-MET (κ=0.459), and D1C2 (κ=0.234). Nearly perfect agreement existed between 2-tier H score and clinical score (κ range: 0.944-0.986). In contrast, correlation analysis between H scores across all assays and RNA expression levels revealed weak association (ρ=0.159-0.349). Five c-Met IHC assays demonstrated moderate to strong concordance in detecting c-Met overexpression. SP44_R, SP44_Z, LBP4-C-MET, and 811B7F4 performed reliably, although D1C2 was less consistent for clinical score 3+. Clinical score 2+/3+ or H score ≥150 is associated with high diagnostic consistency, supporting multiple validated IHC assays for c-Met evaluation in lung adenocarcinoma.

Conventional rapid evaluation of donor kidney quality primarily relies on hematoxylin and eosin (H&E) staining, which inadequately visualizes collagen fibers, compromising the assessment of interstitial fibrosis and posing challenges for general pathologists lacking specialized renal training. This study investigated whether artificial intelligence-based virtual staining could enhance donor kidney evaluation, particularly for interstitial fibrosis and chronic pathologies. Using 187 paired whole-slide images of H&E and Masson's trichrome-stained sections, we developed and validated a CycleGAN-based virtual staining model that transforms H&E images into virtual Masson's trichrome (VMT) representations. A renal pathologist (RP) and two general pathologists (GP.1 and GP.2) evaluated interstitial fibrosis and chronic changes using the Remuzzi scoring system, comparing results with and without virtual staining. Prospective validation was performed on 46 frozen sections. Results demonstrated that VMT effectively visualized interstitial collagen fibers, enabling more reliable fibrosis classification. Diagnostic accuracy significantly improved with virtual staining versus H&E alone (weighted kappa: GPs improved from 0.39-0.51 to 0.78-0.82; RP from 0.61 to 0.86), and inter-observer agreement markedly increased (GPs: 55-64% to 84-88%; RP: 71% to 90%). Notably, VMT bridged the expertise gap, allowing GPs to achieve near-specialist performance in fibrosis assessment (weighted κ: GP.1 from 0.48 to 0.82; GP.2 from 0.41 to 0.84). Prospective validation confirmed these advantages, showing superior accuracy when combining VMT with H&E versus H&E alone (weighted κ: GP.1 from 0.27 to 0.65; GP.2 from 0.34 to 0.68). The technology also enhanced glomerulosclerosis detection (GPs' κ=0.82-0.87) and transplant decision-making accuracy (κ=0.84-0.85), elevating general pathologists to specialist-level competence. In conclusion, deep learning-based virtual staining significantly improves the precision of donor kidney evaluations by general pathologists, approaching specialist-level performance. This technology offers an efficient, cost-effective solution for assessing fibrosis and chronic pathologies, potentially eliminating diagnostic disparities between general and specialist pathologists in transplantation medicine.

The accuracy of immunohistochemical techniques depends critically on the preservation of antigenic integrity in tissue samples. Although formalin-fixed paraffin-embedded tissues are commonly used for long-term storage, several studies reported signal degradation over time. However, the extent of this degradation and the influence of storage conditions on a wide range of markers remain poorly characterized. In this study, tissue blocks collected over an eight-year period and tissue sections stored under different conditions (room temperature, 4°C, -20°C, -80°C) were analyzed. Twenty-five antibodies targeting immune, stromal, and structural markers were used to stain four different tissue sections. Samples were acquired using imaging mass cytometry (IMC). Signal intensities were first quantified, then the data were analyzed, before and after normalization using imcRtools pipeline. A gradual loss of signal intensity was observed in blocks stored at room temperature for more than six years, affecting the detection of certain markers regardless of tissue type. For some sections, significant signal degradation was observed after only one week at room temperature and for others after one month of storage. Markers such as CD20, CD45, and CD45RA proved to be particularly sensitive. Storage at -20°C or -80°C preserved the quality of the staining, whereas storage at 4°C only allowed partial preservation. Normalization corrected some variations but did not enable the recovery of signals that were severely altered or absent. Commonly used room temperature storage causes gradual reduction in IMC-detected immunoreactivity, which may affect scientific interpretation and diagnosis. Storing sections at -20°C is, therefore, an effective and accessible solution. For retrospective studies, we recommend using blocks that are less than six years old. Overall, these results highlight the importance of pre-established standardized preservation protocols to ensure the reproducibility of analyses.

Renal transplant recipients are at significantly higher risk of developing malignancies due to chronic immunosuppression. While DNA polymerase epsilon (POLE)-mutated endometrioid carcinoma (EC) typically presents as early-stage disease with an excellent prognosis and rare metastasis, we conducted a study on POLE-mutated EC in a transplant recipient that rapidly progressed and metastasized. We aimed to first elucidate the molecular and immunological mechanisms of rapid and malignant progression in the tumor. To understand the mechanisms underlying this atypical clinical course, we performed histological and immunohistochemical comparisons of the primary endometrial tumor and metastatic peritoneal lesions, alongside next-generation sequencing and RNA-sequencing analyses. The primary and metastatic lesions shared 17 somatic mutations, indicating a common origin, but demonstrated divergent evolution. Gene expression profiling revealed low CD8+ T cell infiltration and weak interferon gamma signaling, suggesting an immunologically inactive or "immune desert" tumor microenvironment. Clonal evolution analysis showed that the POLE p.S297F mutation initiated hypermutation and clonal diversification in the primary tumor. In contrast, metastatic lesions exhibited POLE loss and activation of the BRAF V600E/PIK3CD pathway, leading to progress and immune evasion. These findings highlight a distinct evolutionary trajectory of POLE-mutated EC under immunosuppressive conditions in this case and underscore the need for tailored oncological surveillance and treatment strategies in transplant recipients.

Accurate pathological assessment of tissue samples is key for diagnosis and optimal treatment decisions. Traditional pathology techniques suffer from subjectivity resulting in inter-observer variability, and limitations in identifying subtle molecular changes. Omics approaches provide both molecular evidence and unbiased classification, which increases the quality and reliability of final tissue assessment. Here, we focus on mass spectrometry (MS)-based proteomics as a method to reveal biopsy tissue differences. For MS data to be useful, molecular information collected from formalin fixed paraffin embedded (FFPE) biopsy tissues needs to be consistent and quantitatively accurate and contain sufficient clinically relevant molecular information. Therefore, we developed an MS-based workflow and assessed the analytical repeatability on 36 kidney biopsies, ultimately analysing molecular differences and similarities of over 5000 proteins per biopsy. Additional 301 transplant biopsies were analysed to understand other physical parameters including effects of tissue size, standing time in autosampler, and the effect on clinical validation. MS data were acquired using Data-Independent Acquisition (DIA) which provides gigabytes of data per sample in the form of high proteome representation, at exquisitely high quantitative accuracy. The FFPE-based method optimised here provides a coefficient of variation below 20%, analysing more than 5000 proteins per sample in parallel. We also observed that tissue thickness does affect the outcome of the data quality: 5 μm sections show more variation in the same sample than 10 μm sections. Notably, our data reveals an excellent agreement for the relative abundance of known protein biomarkers with kidney transplantation lesion scores used in clinical pathological diagnostics. The findings presented here demonstrate the ease, speed, and robustness of the MS-based method, where a wealth of molecular data from minute tissue sections can be used to assist and expand pathology, and possibly reduce the inter-observer variability.

Glioblastoma IDH-wild type (GBM) is the most lethal and, concurrently, the most common malignant primary brain tumor. Its aggressive behavior is associated with the presence of a subpopulation of glioblastoma stem cells (GSC) that drive resistance to therapy and early relapse. PIWI-interacting RNAs (piRNAs), which are characteristically expressed in undifferentiated cells, are thought to play an important role in GSC biology. To identify piRNAs associated with GSCs, we selected 24 paired GSC and the non-GSC cultures from GBM patients based on the expression of stem cell markers CD133 and Sox2, ability of GSCs to form spheres in culture, to differentiate and to replicate tumors in immunodeficient mice. Global piRNA profiling using next generation sequencing revealed 98 significantly differentially expressed piRNAs in GSCs compared to non-GSCs, including piR-9491, whose dysregulation in GBM has been previously described. Downregulation of piR-9491 in GSCs led to decreased viability, growth, invasion, and increased apoptosis. Significance of piRNA pathway for GBM pathology was further highlighted by identification of 34 piRNAs connected to patient's survival. These molecules were further used for the establishment of piRNA signature predicting survival of GBM patients. Our results, not only, confirm the important role of piR-9491 in GSCs, but also indicate potentially significant role of piRNAs in the biology of GBM.

Mucin 1 (MUC1) is a highly O-glycosylated transmembrane glycoprotein. Tumor-associated MUC1, characterized by aberrant O-linked glycans, is overexpressed in cancer cells; however, conventional MUC1 antibodies show limited specificity for tumor-associated glycan structures. Recently, a novel epitope-defined antibody (MUC1-Tn antigen epitope-defined antibody [MUC1-Tn ED Ab]) that specifically recognizes the Tn-MUC1 antigen was developed. In this study, we evaluated the potential of MUC1-Tn ED Abs as diagnostic markers of breast cancer. Tissue microarray sections from 124 patients with invasive breast carcinoma (IBC) and 26 whole tissue sections, including multiple neoplastic lesions-flat epithelial atypia (n = 24), ductal carcinoma in situ (n = 26), and IBC (n = 16)-were analyzed. Immunohistochemical distributions of Tn-MUC1 and MUC1 were assessed using the MUC1-Tn ED Ab (clone SN102) and a conventional antibody (clone Ma552), respectively. In tissue microarray analysis, Tn-MUC1 exhibited minimal immunoreactivity in nonneoplastic areas and high specificity for IBC. In IBC tissues, immunoreactivity with Tn-MUC1 was predominantly cytoplasmic, unlike conventional MUC1 staining observed in both the cytoplasm and membrane. In multilesion analysis, cytoplasmic Tn-MUC1 expression was rarely detected in nonneoplastic areas but progressively increased across flat epithelial atypia, ductal carcinoma in situ, and IBC. Knockdown assays in breast cancer cell lines demonstrated that core 1 β1,3-galactosyltransferase 1 (C1GALT1), an enzyme involved in galactosylation of the Tn antigen, significantly influenced the cellular localization of Tn-MUC1. This study demonstrates that Tn-MUC1, as detected by the MUC1-Tn ED Ab, has high specificity for breast cancer and may act as a novel immunohistochemical marker reflecting tumor progression.