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The accurate diagnosis of papillary urothelial carcinoma (PUC) is frequently challenging due to benign mimickers. Other than morphology-based diagnostic criteria, reliable biomarkers for differentiating benign and malignant papillary urothelial neoplasms remain elusive, so we sought to discover new markers to address this challenge. We first performed tandem mass spectrometry-based quantitative proteomics using diverse papillary urothelial lesions, including PUC, urothelial papilloma (UP), inverted urothelial papilloma, and cystitis cystica. We prioritized potential diagnostic biomarkers using machine learning, and subsequently validated through immunohistochemistry (IHC) in two independent cohorts. Metabolism, transport, cell cycle, development, and immune response functions were differentially enriched between malignant and benign papillary neoplasms. RhoB and NT5DC2 were shortlisted as optimal candidate markers for PUC diagnosis. In our pilot study using IHC, NT5DC2 was subsequently selected as its expression consistently differed in PUC (p = 0.007). Further validation of NT5DC2 using 49 low-grade (LG) urothelial lesions, including 15 LG-PUCs and 17 UPs, which are the most common mimickers, concordantly revealed lower IHC expression levels in LG-PUC (p = 0.0298). Independent external validation with eight LG-PUCs and eight UPs confirmed the significant downregulation of NT5DC2 in LG-PUC (p = 0.0104). We suggest that NT5DC2 is a potential IHC biomarker for differentiating LG-PUC from its benign mimickers, especially UP.
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BACKGROUND: Despite the widespread impact of the severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019, COVID-19) and vaccination in South Korea, our understanding of kidney diseases following these events remains limited. We aimed to address this gap by investigating the characteristics of glomerular diseases following the COVID-19 infection and vaccination in South Korea. METHODS: Data from multiple centers were used to identify de novo glomerulonephritis (GN) cases with suspected onset following COVID-19 infection or vaccination. Retrospective surveys were used to determine the COVID-19-related histories of patients who were initially not implicated. Bayesian structural time series and autoregressive integrated moving average models were used to determine causality. RESULTS: Glomerular diseases occurred shortly after the infection or vaccination. The most prevalent postinfection GN was podocytopathy (42.9%), comprising primary focal segmental glomerulosclerosis and minimal change disease, whereas postvaccination GN mainly included immunoglobulin A nephropathy (IgAN; 57.9%) and Henoch-Schönlein purpura nephritis (HSP; 15.8%). No patient progressed to end-stage kidney disease. Among the patients who were initially not implicated, nine patients with IgAN/HSP were recently vaccinated against COVID-19. The proportion of glomerular diseases changed during the pandemic in South Korea, with an increase in acute interstitial nephritis and a decrease in pauci-immune crescentic GN. CONCLUSION: This study showed the characteristics of GNs following COVID-19 infection or vaccination in South Korea. Understanding these associations is crucial for developing effective patient management and vaccination strategies. Further investigation is required to fully comprehend COVID-19's impact on GN.
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BACKGROUND: Accurate classification of breast cancer molecular subtypes is crucial in determining treatment strategies and predicting clinical outcomes. This classification largely depends on the assessment of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) status. However, variability in interpretation among pathologists pose challenges to the accuracy of this classification. This study evaluates the role of artificial intelligence (AI) in enhancing the consistency of these evaluations. METHODS: AI-powered HER2 and ER/PR analyzers, consisting of cell and tissue models, were developed using 1,259 HER2, 744 ER, and 466 PR-stained immunohistochemistry (IHC) whole-slide images of breast cancer. External validation cohort comprising HER2, ER, and PR IHCs of 201 breast cancer cases were analyzed with these AI-powered analyzers. Three board-certified pathologists independently assessed these cases without AI annotation. Then, cases with differing interpretations between pathologists and the AI analyzer were revisited with AI assistance, focusing on evaluating the influence of AI assistance on the concordance among pathologists during the revised evaluation compared to the initial assessment. RESULTS: Reevaluation was required in 61 (30.3%), 42 (20.9%), and 80 (39.8%) of HER2, in 15 (7.5%), 17 (8.5%), and 11 (5.5%) of ER, and in 26 (12.9%), 24 (11.9%), and 28 (13.9%) of PR evaluations by the pathologists, respectively. Compared to initial interpretations, the assistance of AI led to a notable increase in the agreement among three pathologists on the status of HER2 (from 49.3 to 74.1%, p < 0.001), ER (from 93.0 to 96.5%, p = 0.096), and PR (from 84.6 to 91.5%, p = 0.006). This improvement was especially evident in cases of HER2 2+ and 1+, where the concordance significantly increased from 46.2 to 68.4% and from 26.5 to 70.7%, respectively. Consequently, a refinement in the classification of breast cancer molecular subtypes (from 58.2 to 78.6%, p < 0.001) was achieved with AI assistance. CONCLUSIONS: This study underscores the significant role of AI analyzers in improving pathologists' concordance in the classification of breast cancer molecular subtypes.
Subject(s)
Breast Neoplasms , Humans , Female , Breast Neoplasms/diagnosis , Breast Neoplasms/metabolism , Receptors, Estrogen/metabolism , Biomarkers, Tumor/metabolism , Artificial Intelligence , Observer Variation , Receptors, Progesterone/metabolism , Receptor, ErbB-2/metabolismABSTRACT
BACKGROUND: Although a combination of immune checkpoint inhibitors (ICIs) is recommended as the first line treatment option for metastatic renal cell carcinoma (mRCC), several immune-related adverse events (irAEs) occur, especially hepatitis. We explored the therapeutic benefits and safety profile of combining oncolytic vaccinia virus, JX-594, with a programmed cell death protein-1 (PD-1) inhibitor. METHODS: We used early-stage and advanced-stage orthotopic murine mRCC models developed by our group. PD-1 inhibitor monotherapy or a PD-1 inhibitor combined with either JX-594 or a cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) inhibitor were systemically injected through the peritoneum. An immunofluorescence analysis was performed to analyze the tumor immune microenvironment (TIME). irAEs were assessed in terms of hepatitis. RESULTS: In the early-stage mRCC model mice, the combination of JX-594 and a PD-1 inhibitor significantly decreased the primary tumor size and number of lung nodules, compared with the ICI combination, but the JX-594 and PD-1 inhibitor combination and ICI combination did not differ significantly in the advanced-stage mRCC model mice. The JX-594 and PD-1 inhibitor combination induced tumor-suppressing TIME changes in both the early- and advanced-stage mRCC models. Furthermore, mice treated with the ICI combination had significantly greater hepatic injuries than those treated with the JX-594 and PD-1 inhibitor combination which was evaluated in early-stage mRCC model. CONCLUSIONS: The JX-594 and PD-1 inhibitor combination effectively reduced primary tumors and the metastatic burden, similar to ICI combination therapy, through dynamic remodeling of the TIME. Furthermore, hepatitis was significantly decreased in the JX-594 and PD-1 inhibitor combination group, suggesting the potential benefit of that combination for reducing ICI-induced toxicity.
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BACKGROUND: Aquaporin (AQP) expression has been investigated in various malignant neoplasms, and the overexpression of AQP is related to poor prognosis in some malignancies. However, the expression of AQP protein in clear cell renal cell carcinoma (ccRCC) has not been extensively investigated by immunohistochemistry with large sample size. METHODS: We evaluated the AQP expression in 827 ccRCC with immunohistochemical staining in tissue microarray blocks and classified the cases into two categories, high and low expression. RESULTS: High expression of aquaporin-1 (AQP1) was found in 320 cases (38.7%), but aquaporin-3 was not expressed in ccRCC. High AQP1 expression was significantly related to younger age, low TNM stage, low World Health Organization/International Society of Urologic Pathology nuclear grade, and absence of distant metastasis. Furthermore, high AQP1 expression was also significantly associated with longer overall survival (OS; p<.001) and progression-specific survival (PFS; p<.001) and was an independent predictor of OS and PFS in ccRCC. CONCLUSIONS: Our study revealed the prognostic significance of AQP1 protein expression in ccRCC. These findings could be applied to predict the prognosis of ccRCC.
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Atypical hemolytic uremic syndrome (aHUS) is a form of thrombotic microangiopathy (TMA) that can result in end-stage renal disease. Patients with aHUS often have predisposing dysfunction in the complement pathway, and continuous activation of complement proteins can be triggered after transplantation. Here, we report the first successful case of aHUS treatment in a kidney transplant recipient with early use of a C5 inhibitor, eculizumab, in South Korea. The patient was a 32-year-old man, and the donor was his 60-year-old mother. The graft showed immediate good function. On postoperative day (POD) 3, the clinical diagnosis of TMA was made. Persistent renal dysfunction despite 10 plasma exchange (PE) sessions prompted eculizumab treatment on POD 18 under suspicion of aHUS. Next-generation sequencing reported gene mutations classified as variants of unknown significance in coagulation-associated genes. The patient was discharged after three doses of eculizumab with serum creatinine of 1.82 mg/dL. In total, 16 doses of eculizumab were administered. At the last follow-up, 21 months after eculizumab discontinuation, the graft was well functioning. De novo TMA after kidney transplantation can be caused by sustained activation of the complement pathway, and early eculizumab treatment appears important in the successful treatment of aHUS refractory to PE.
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BACKGROUND: The relationship between cystitis glandularis (CG) and bladder malignancy remains unclear. METHODS: We identified the oncologic significance of CG at the molecular level using liquid chromatography-tandem mass spectrometry-based proteomic analysis of 10 CG, 12 urothelial carcinoma (UC), and nine normal urothelium (NU) specimens. Differentially expressed proteins (DEPs) were identified based on an analysis of variance false discovery rate < 0.05, and their functional enrichment was analyzed using a network model, Gene Set Enrichment Analysis, and Gene Ontology annotation. RESULTS: We identified 9,890 proteins across all samples and 1,139 DEPs among the three entities. A substantial number of DEPs overlapped in CG/NU, distinct from UC. Interestingly, we found that a subset of DEP clusters (n = 53, 5%) was differentially expressed in NU but similarly between CG and UC. This "UC-like signature" was enriched for reactive oxygen species (ROS) and energy metabolism, growth and DNA repair, transport, motility, epithelial-mesenchymal transition, and cell survival. Using the top 10 shortlisted DEPs, including SOD2, PRKCD, CYCS, and HCLS1, we identified functional elements related to ROS metabolism, development, and transport using network analysis. The abundance of these four molecules in UC/CG than in NU was consistent with the oncologic functions in CG. CONCLUSIONS: Using a proteomic approach, we identified a predominantly non-neoplastic landscape of CG, which was closer to NU than to UC. We also confirmed a small subset of common DEPs in UC and CG, suggesting that altered ROS metabolism might imply potential cancerous risks in CG.
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Muscle-invasive urothelial carcinoma (MIUC) of the bladder shows highly aggressive tumor behavior, which has prompted the quest for robust biomarkers predicting invasion. To discover such biomarkers, we first employed high-throughput proteomic method and analyzed tissue biopsy cohorts from patients with bladder urothelial carcinoma (BUC), stratifying them according to their pT stage. Candidate biomarkers were selected through bioinformatic analysis, followed by validation. The latter comprised 2D and 3D invasion and migration assays, also a selection of external public datasets to evaluate mRNA expression and an in-house patient-derived tissue microarray (TMA) cohort to evaluate protein expression with immunohistochemistry (IHC). Our multilayered platform-based analysis identified tubulin beta 6 class V (TUBB6) as a promising prognostic biomarker predicting MIUC of the bladder. The in vitro 2D and 3D migration and invasion assays consistently showed that inhibition of TUBB6 mRNA significantly reduced cell migration and invasion ability in two BUC cell lines with aggressive phenotype (TUBB6 migration, P = .0509 and P < .0001; invasion, P = .0002 and P = .0044; TGFBI migration, P = .0214 and P = .0026; invasion, P < .0001 and P = .0001; T24 and J82, respectively). Validation through multiple public datasets, including The Cancer Genome Atlas (TCGA) and selected GSE (Genomic Spatial Event) databases, confirmed TUBB6 as a potential biomarker predicting MIUC. Further protein-based validation with our TMA cohort revealed concordant results, highlighting the clinical implication of TUBB6 expression in BUC patients (overall survival: P < .001). We propose TUBB6 as a novel IHC biomarker to predict invasion and poor prognosis, also select the optimal treatment in BUC patients.
Subject(s)
Carcinoma, Transitional Cell , Urinary Bladder Neoplasms , Humans , Urinary Bladder Neoplasms/genetics , Proteomics , Biomarkers , Muscles , RNA, Messenger/genetics , Prognosis , Tubulin/geneticsABSTRACT
Methods of computational pathology applied to the analysis of whole-slide images (WSIs) do not typically consider histopathological features from the tumour microenvironment. Here, we show that a graph deep neural network that considers such contextual features in gigapixel-sized WSIs in a semi-supervised manner can provide interpretable prognostic biomarkers. We designed a neural-network model that leverages attention techniques to learn features of the heterogeneous tumour microenvironment from memory-efficient representations of aggregates of highly correlated image patches. We trained the model with WSIs of kidney, breast, lung and uterine cancers and validated it by predicting the prognosis of 3,950 patients with these four different types of cancer. We also show that the model provides interpretable contextual features of clear cell renal cell carcinoma that allowed for the risk-based retrospective stratification of 1,333 patients. Deep graph neural networks that derive contextual histopathological features from WSIs may aid diagnostic and prognostic tasks.
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Although the density of tumor-infiltrating lymphocytes (TILs) is known to be linked to prognosis in various cancers, the prognostic impact and immunologic significance of the spatial heterogeneity of TILs have been rarely investigated. In this study, CD3+ and CD8+ TILs were quantified in independent cohorts (discovery, n = 73; and external validation, n = 93) of colorectal carcinomas (CRCs) with microsatellite instability-high (MSI-H) utilizing whole-slide image analysis of CD3/CD8 immunohistochemistry. The Shannon and Simpson indices, which measure intratumoral patch-to-patch evenness of TIL densities, were used to quantitatively assess the spatial heterogeneity of TILs in each case. To uncover immune-related gene expression signatures of spatial heterogeneity-based TIL subgroups of MSI-H CRCs, representative cases were subjected to GeoMx digital spatial profiler (DSP) analysis. As expected, a low density of TILs was significantly associated with poor disease-free survival (DFS) in MSI-H CRCs. The TIL-low tumors were further classified into two subgroups based on the spatial heterogeneity of TILs: TIL-low/heterogeneity-high and TIL-low/heterogeneity-low subgroups. In both discovery and validation cohorts, the TIL-low/heterogeneity-high, TIL-low/heterogeneity-low, and TIL-high subgroups were significantly associated with poor, intermediate, and good DFS, respectively. In the DSP analysis, the TIL-low/heterogeneity-high subgroup showed higher spatial diversity in the expression of immune-related genes than that of the TIL-low/heterogeneity-low subgroup and exhibited upregulation of genes related to immune checkpoints, chemokine/cytokine receptors, and myeloid cells. TIL-low/heterogeneity-high tumors were also enriched with gene sets related to good response to immune checkpoint inhibitor therapy. In conclusion, TIL-low MSI-H CRCs are prognostically heterogeneous and can be divided into prognostically and immunologically distinct subgroups by considering the spatial heterogeneity of TILs. Our data suggest that intratumoral spatial heterogeneity of TILs can be used as a key element for clinically relevant immunologic subtyping of tumors.
Subject(s)
Colonic Neoplasms , Colorectal Neoplasms , Humans , Colonic Neoplasms/pathology , Colorectal Neoplasms/pathology , Lymphocytes, Tumor-Infiltrating , Microsatellite Instability , PrognosisABSTRACT
Background: The molecular biology of inverted urothelial papilloma (IUP) as a precursor disease of urothelial carcinoma is poorly understood. Furthermore, the overlapping histology between IUP and papillary urothelial carcinoma (PUC) with inverted growth is a diagnostic pitfall leading to frequent misdiagnoses. Methods: To identify the oncologic significance of IUP and discover a novel biomarker for its diagnosis, we employed mass spectrometry-based proteomic analysis of IUP, PUC, and normal urothelium (NU). Machine learning analysis shortlisted candidate proteins, while subsequent immunohistochemical validation was performed in an independent sample cohort. Results: From the overall proteomic landscape, we found divergent 'NU-like' (low-risk) and 'PUC-like' (high-risk) signatures in IUP. The latter were characterized by altered metabolism, biosynthesis, and cell-cell interaction functions, indicating oncologic significance. Further machine learning-based analysis revealed SERPINH1, PKP2, and PYGB as potential diagnostic biomarkers discriminating IUP from PUC. The immunohistochemical validation confirmed PYGB as a specific biomarker to distinguish between IUP and PUC with inverted growth. Conclusion: In conclusion, we suggest PYGB as a promising immunohistochemical marker for IUP diagnosis in routine practice.
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Lysosomal "mottled appearance", or uneven electron-dense content related to monoclonal gammopathy (MG), has been mainly described in light chain proximal tubulopathy (LCPT). We aimed to determine the ultrastructural characteristics of lysosomal mottled appearance in kidney biopsies and its association with LCPT and MG. Seventy-seven biopsies were grouped into LCPT (n = 5), MG conditions other than LCPT (n = 43), and non-MG conditions (n = 29). The mottled lysosomes in the renal tubules were evaluated using transmission electron microscopy and morphometric analysis. Mottled lysosomes were more prevalent (% of present cases) and frequent (no. of mottled lysosomes/20,000× ultramicroscopic field) in the LCPT group (100% and 8.20 ± 4.15/field) than in the MG (41.9% and 1.13 ± 2.05/field) and non-MG (37.9% and 0.80 ± 1.44/field) groups. In morphometric analysis of all mottled lysosomes (n = 520) detected from the 34 biopsies (5 LCPT, 18 MG, and 11 non-MG), we found that mottled lysosomes were larger, more irregular, and more electron-dense for the LCPT group than for the MG and non-MG groups. Therefore, mottled lysosomes can be present in disorders other than LCPT or even without MG. The morphological characteristics of mottled lysosomes could provide objective guidance for the diagnosis of LCPT.
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CONTEXT.: A wide spectrum of mesenchymal tumors harboring ALK gene rearrangements has been identified outside the archetypal example of ALK-positive inflammatory myofibroblastic tumors. OBJECTIVE.: To evaluate the molecular pathology of unusual ALK-positive mesenchymal tumors and their response to ALK-targeted treatments. DESIGN.: Seven patients with ALK-positive mesenchymal tumors, including inflammatory epithelioid cell sarcoma, undifferentiated sarcoma, histiocytic neoplasm, smooth muscle tumor of uncertain malignant potential (STUMP), and atypical fibrohistiocytic tumor, were included on the basis of aberrant ALK immunoexpression. Patients with inflammatory myofibroblastic tumors were excluded from the study. ALK gene rearrangement was investigated either by fluorescence in situ hybridization or next-generation sequencing. RESULTS.: ALK was immunolabeled in all patients, diffusely (≥50%) in 6 patients and partially (10%-50%) in 1 patient. ALK gene rearrangement was discovered in 5 of the 6 available patients. The 3'-partners of ALK fusion were identified in 3 of 4 investigated patients as follows: PRKAR1A-ALK (ALK-positive histiocytic neoplasm), TNS1-ALK (STUMP), and KIF5B-ALK (ALK-positive atypical fibrohistiocytic tumor). We failed to discover ALK translocation in 1 patient with ALK-positive inflammatory epithelioid cell sarcoma. However, transcriptomic investigation showed that this tumor was significantly enriched with ALK-related pathways, which suggested activation of ALK through a nontranslocation pathway, as a constitutive oncogenic mark in this tumor. ALK-targeted inhibitors, which were administered to 3 patients with metastatic diseases, achieved partial remission in 1 patient with ALK-positive inflammatory epithelioid cell sarcoma and stable disease in patients with ALK-positive undifferentiated sarcoma and STUMP. CONCLUSIONS.: Molecular investigation of ALK-positive mesenchymal neoplasms could allow for an accurate diagnosis and personalized treatment.
Subject(s)
Liver Neoplasms , Sarcoma , Smooth Muscle Tumor , Soft Tissue Neoplasms , Humans , In Situ Hybridization, Fluorescence , Anaplastic Lymphoma Kinase/genetics , Sarcoma/diagnosis , Sarcoma/genetics , Sarcoma/pathology , Soft Tissue Neoplasms/diagnosis , Soft Tissue Neoplasms/genetics , Protein Kinase InhibitorsABSTRACT
Accurate diagnosis and grading of needle biopsies are crucial for prostate cancer management. A uropathologist-level artificial intelligence (AI) system could help make unbiased decisions and improve pathologists' efficiency. We previously reported an artificial neural network-based, automated, diagnostic software for prostate biopsy, DeepDx® Prostate (DeepDx). Using an independent external dataset, we aimed to validate the performance of DeepDx at the levels of prostate cancer diagnosis and grading and evaluate its potential value to the general pathologist. A dataset composed of 593 whole-slide images of prostate biopsies (130 normal and 463 adenocarcinomas) was assembled, including their original pathology reports. The Gleason scores (GSs) and grade groups (GGs) determined by three uropathology experts were considered as the reference standard. A general pathologist conducted user validation by scoring the dataset with and without AI assistance. DeepDx was accurate for prostate cancer detection at a similar level to the original pathology report, whereas it was more concordant than the latter with the reference GGs and GSs (kappa/quadratic-weighted kappa = 0.713/0.922 vs. 0.619/0.873 for GGs and 0.654/0.904 vs. 0.576/0.858 for GSs). Notably, it outperformed the original report, especially in the detection of Gleason patterns 4/5, and achieved excellent agreement in quantifying the Gleason pattern 4. When the general pathologist used AI assistance, the concordance of GG between the user and the reference standard increased (kappa/quadratic-weighted kappa, 0.621/0.876 to 0.741/0.925), while the average slide examination time was substantially decreased (55.7 to 36.8 s/case). Overall, DeepDx was capable of making expert-level diagnosis in prostate core biopsies. In addition, its remarkable performance in detecting high-grade Gleason patterns and enhancing the general pathologist's diagnostic performance supports its potential value in routine practice.
Subject(s)
Artificial Intelligence , Prostatic Neoplasms , Biopsy , Biopsy, Large-Core Needle , Humans , Male , Neoplasm Grading , Observer Variation , Prostatic Neoplasms/diagnosis , Prostatic Neoplasms/pathologyABSTRACT
Metabolic dysregulation is an important hallmark of cancer. Nicotinamide (NAM), a water-soluble amide form of niacin (vitamin B3), is currently available as a supplement for maintaining general physiologic functions. NAM is a crucial regulator of mitochondrial metabolism and redox reactions. In this study, we aimed to identify the mechanistic link between NAM-induced metabolic regulation and the therapeutic efficacy of NAM in triple-negative breast cancer (TNBC). The combined analysis using multiomics systems biology showed that NAM decreased mitochondrial membrane potential and ATP production, but increased the activities of reverse electron transport (RET), fatty acid ß-oxidation and glycerophospholipid/sphingolipid metabolic pathways in TNBC, collectively leading to an increase in the levels of reactive oxygen species (ROS). The increased ROS levels triggered apoptosis and suppressed tumour growth and metastasis of TNBC in both human organoids and xenograft mouse models. Our results showed that NAM treatment leads to cancer cell death in TNBC via mitochondrial dysfunction and activation of ROS by bifurcating metabolic pathways (RET and lipid metabolism); this provides insights into the repositioning of NAM supplement as a next-generation anti-metabolic agent for TNBC treatment.
Subject(s)
Niacin , Triple Negative Breast Neoplasms , Animals , Apoptosis , Cell Line, Tumor , Drug Repositioning , Humans , Lipid Metabolism , Mice , Niacin/pharmacology , Niacin/therapeutic use , Niacinamide/pharmacology , Niacinamide/therapeutic use , Reactive Oxygen Species/metabolism , Triple Negative Breast Neoplasms/pathologyABSTRACT
Receptor tyrosine kinases (RTKs) are important targets for clear cell renal cell carcinoma (ccRCC) treatment. Myoferlin is a strong regulator of RTKs. To identify myoferlin-associated RTKs and their prognostic implications in ccRCC, we investigated the expression of RTKs and myoferlin using proteome-based evaluation and immunohistochemical staining in tissue microarray. Multivariate Cox analysis adjusted for TNM stage and WHO grade was performed (n = 410 and 506). Proteomic analysis suggested c-Met and EPHA7 as novel candidates for myoferlin-associated RTKs. We immunohistochemically validated the positive association between c-Met and myoferlin expression. High c-Met expression was independently associated with overall (hazard ratio (HR) = 1.153-2.919) and cancer-specific survival (HR = 1.150-3.389). The prognostic effect of high c-Met expression was also determined in an independent cohort (overall survival, HR = 1.503-3.771). Although expression of EPHA7 and myoferlin was not correlated, EPHA7 expression was independently associated with progression-free (HR = 1.237-4.319) and cancer-specific survival (HR = 1.214-4.558). In addition, network-based prioritization showed co-functional enrichment of c-Met and myoferlin, suggesting a novel regulatory function of myoferlin in c-Met signaling. This study indicates that c-Met and EPHA7 might be useful prognostic biomarkers, and the presumed myoferlin/c-Met pathway could be a novel therapeutic target in ccRCC.
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OBJECTIVE: Pathological features indicating metastatic mucinous carcinoma to the ovary (MMCO) have been rarely reported in primary mucinous ovarian carcinoma (PMOC). However, little is known about how often they are observed in PMOC and how they relate to patient prognosis. In this study, we investigated the pathological features indicating MMCO in a large cohort of PMOCs and analyzed their association with patient prognosis. METHODS: We reviewed surgically treated PMOC patients diagnosed at the Seoul National University Hospital from 1995 to 2019, according to the updated WHO classification, and investigated the presence of pathological features indicating MMCO. RESULTS: A total of 144 patients with PMOCs were included. The 5 pathological findings indicating MMCO, including an infiltrative invasive pattern, the absence of benign or borderline components, a smaller tumor size, the presence of signet ring cells and the presence of extracellular mucin were observed in PMOC (21.6%, 43.1%, 20.8%, 4.3% and 12.9%, respectively), and were significantly correlated with poor overall and progression-free survival rates in PMOC. The patient's prognosis worsened as the extent of the infiltrative invasive pattern increased (p<0.001). In addition, the prognostic power was stronger when the 5 pathological factors were analyzed together (new grouping system) than when analyzed individually (p<0.001) and the new grouping system was identified as an independent prognostic factor regardless of FIGO stage. CONCLUSION: Five pathological findings indicating MMCO in PMOC were significantly associated with poor prognosis in PMOC patients. Also, the new grouping system combining these findings was identified as an independent prognostic factor.
Subject(s)
Adenocarcinoma, Mucinous , Ovarian Neoplasms , Adenocarcinoma, Mucinous/pathology , Carcinoma, Ovarian Epithelial/pathology , Female , Humans , Neoplasm Staging , Ovarian Neoplasms/pathology , PrognosisABSTRACT
NUT carcinoma is an aggressive epithelial malignancy defined by NUTM1 translocation, usually arising in the head/neck or thorax regions and showing squamous differentiation. Herein, we describe an extraordinary case of NUT carcinoma in the pelvic cavity. The patient was a 54-yr-old woman who was found to have a large pelvic mass with multiple metastases, suggestive of advanced ovarian cancer. Peritoneal seeding nodules were resected and subjected to pathologic examination. Upon microscopic investigation, infiltration of tumor cells showing monotonous-round morphology without squamous features was observed. Immunohistochemical analysis revealed faint/dot-like expression of cytokeratin, focal expression of vimentin, and diffuse expression of the estrogen receptor, but there was no detection of p40, p63, and Myc. NUT was diffusely and strongly expressed in nuclei, in which it exhibited a speckled pattern. Subsequent dual-color break-apart fluorescence in situ hybridization of NUTM1 confirmed a genetic translocation. Next, target-enriched next-generation sequencing covering ~200 major cancer-associated genes found no other significant alterations. After 2 cycles of chemotherapy, bilateral pleural effusion developed that were diagnosed as metastatic NUT carcinoma. The data suggest that NUT carcinoma should be enlisted in the differential diagnosis of poorly differentiated malignancies arising in the pelvic organs.