Diagnostic and Prognostic Implications of FGFR3(high)/Ki67(high) Papillary Bladder Cancers

Prognostic/therapeutic stratification of papillary urothelial cancers is solely based upon histology, despite activated FGFR3-signaling was found to be associated with low grade tumors and favorable outcome. However, there are FGFR3-overexpressing tumors showing high proliferation-a paradox of coexisting favorable and adverse features. Therefore, our study aimed to decipher the relevance of FGFR3-overexpression/proliferation for histopathological grading and risk stratification. N = 142 (n = 82 pTa, n = 42 pT1, n = 18 pT2-4) morphologically G1-G3 tumors were analyzed for immunohistochemical expression of FGFR3 and Ki67. Mutation analysis of FGFR3 and TP53 and FISH for FGFR3 amplification and rearrangement was performed. SPSS 23.0 was used for statistical analysis. Overall FGFR3(high)/Ki67(high) status (n = 58) resulted in a reduced Delta mean progression-free survival (PFS) (p < 0.01) of 63.92 months, and shorter progression-free survival (p < 0.01;mean PFS: 55.89 months) in pTa tumors (n = 50). FGFR3(mut)/TP53(mut) double mutations led to a reduced Delta mean PFS (p < 0.01) of 80.30 months in all tumors, and FGFR3(mut)/TP53(mut) pTa tumors presented a dramatically reduced PFS (p < 0.001;mean PFS: 5.00 months). Our results identified FGFR3(high)/Ki67(high) papillary pTa tumors as a subgroup with poor prognosis and encourage histological grading as high grade tumors. Tumor grading should possibly be augmented by immunohistochemical stainings and suitable clinical surveillance by endoscopy should be performed

Identification and validation of potential new biomarkers for prostate cancer diagnosis and prognosis using 2D-DIGE and MS

This study was designed to identify and validate potential new biomarkers for prostate cancer and to distinguish patients with and without biochemical relapse. Prostate tissue samples analyzed by 2D-DIGE (two-dimensional difference in gel electrophoresis) and mass spectrometry (MS) revealed downregulation of secernin-1 (P < 0.044) in prostate cancer, while vinculin showed significant upregulation (P < 0.001). Secernin-1 overexpression in prostate tissue was validated using Western blot and immunohistochemistry while vinculin expression was validated using immunohistochemistry. These findings indicate that secernin-1 and vinculin are potential new tissue biomarkers for prostate cancer diagnosis and prognosis, respectively. For validation, protein levels in urine were also examined by Western blot analysis. Urinary vinculin levels in prostate cancer patients were significantly higher than in urine from nontumor patients (P = 0.006). Using multiple reaction monitoring-MS (MRM-MS) analysis, prostatic acid phosphatase (PAP) showed significant higher levels in the urine of prostate cancer patients compared to controls (P = 0.012), while galectin-3 showed significant lower levels in the urine of prostate cancer patients with biochemical relapse, compared to those without relapse (P = 0.017). Three proteins were successfully differentiated between patients with and without prostate cancer and patients with and without relapse by using MRM. Thus, this technique shows promise for implementation as a noninvasive clinical diagnostic technique

Brief inhalation of nitric oxide increases resuscitation success and improves 7-day-survival after cardiac arrest in rats: a randomized controlled animal study

Introduction: Inhaled nitric oxide (iNO) improves outcomes when given post systemic ischemia/reperfusion injury. iNO given during cardiopulmonary resuscitation (CPR) may therefore improve return of spontaneous circulation (ROSC) rates and functional outcome after cardiac arrest (CA). Methods: Thirty male Sprague-Dawley rats were subjected to 10 minutes of CA and at least 3 minutes of CPR. Animals were randomized to receive either 0 (n = 10, Control), 20 (n = 10, 20 ppm), or 40 (n = 10, 40 ppm) ppm iNO during CPR until 30 minutes after ROSC. A neurological deficit score was assessed daily for seven days following the experiment. On day 7, brains, hearts, and blood were sampled for histological and biochemical evaluation. Results: During CPR, 20 ppm iNO significantly increased diastolic arterial pressure (Control: 57 ± 5.04 mmHg; 20 ppm: 71.57 ± 57.3 mmHg, p < 0.046) and decreased time to ROSC (Control: 842 ± 21 s; 20 ppm: 792 ± 5 s, (p = 0.02)). Thirty minutes following ROSC, 20 ppm iNO resulted in an increase in mean arterial pressure (Control: 83 ± 4 mmHg; 20 ppm: 98 ± 4 mmHg, p = 0.035), a less pronounced rise in lactate and inflammatory cytokine levels, and attenuated cardiac damage. Inhalation of NO at 20 ppm improved neurological outcomes in rats 2 to 7 days after CA and CPR. This translated into increases in 7 day survival (Control: 4; 20 ppm: 10; 40 ppm 6, (p ≤ 0.05 20 ppm vs Control and 40 ppm). Conclusions: Our study revealed that breathing NO during CPR markedly improved resuscitation success, 7-day neurological outcomes and survival in a rat model of VF-induced cardiac arrest and CPR. These results support the beneficial effects of NO inhalation after cardiac arrest and CPR

Clinical sequencing identifies potential actionable alterations in a high rate of urachal and primary bladder adenocarcinomas.

OBJECTIVE Administration of targeted therapies provides a promising treatment strategy for urachal adenocarcinoma (UrC) or primary bladder adenocarcinoma (PBAC); however, the selection of appropriate drugs remains difficult. Here, we aimed to establish a routine compatible methodological pipeline for the identification of the most important therapeutic targets and potentially effective drugs for UrC and PBAC. METHODS Next-generation sequencing, using a 161 cancer driver gene panel, was performed on 41 UrC and 13 PBAC samples. Clinically relevant alterations were filtered, and therapeutic interpretation was performed by in silico evaluation of drug-gene interactions. RESULTS After data processing, 45/54 samples passed the quality control. Sequencing analysis revealed 191 pathogenic mutations in 68 genes. The most frequent gain-of-function mutations in UrC were found in KRAS (33%), and MYC (15%), while in PBAC KRAS (25%), MYC (25%), FLT3 (17%) and TERT (17%) were recurrently affected. The most frequently affected pathways were the cell cycle regulation, and the DNA damage control pathway. Actionable mutations with at least one available approved drug were identified in 31/33 (94%) UrC and 8/12 (67%) PBAC patients. CONCLUSIONS In this study, we developed a data-processing pipeline for the detection and therapeutic interpretation of genetic alterations in two rare cancers. Our analyses revealed actionable mutations in a high rate of cases, suggesting that this approach is a potentially feasible strategy for both UrC and PBAC treatments

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised: the ground truth is only known for the slide, not for every single tile. In classical weakly-supervised analysis pipelines, all tiles inherit the slide label while in multiple-instance learning (MIL), only bags of tiles inherit the label. However, it is still unclear how these widely used but markedly different approaches perform relative to each other. We implemented and systematically compared six methods in six clinically relevant end-to-end prediction tasks using data from N=2980 patients for training with rigorous external validation. We tested three classical weakly-supervised approaches with convolutional neural networks and vision transformers (ViT) and three MIL-based approaches with and without an additional attention module. Our results empirically demonstrate that histological tumor subtyping of renal cell carcinoma is an easy task in which all approaches achieve an area under the receiver operating curve (AUROC) of above 0.9. In contrast, we report significant performance differences for clinically relevant tasks of mutation prediction in colorectal, gastric, and bladder cancer. In these mutation prediction tasks, classical weakly-supervised workflows outperformed MIL-based weakly-supervised methods for mutation prediction, which is surprising given their simplicity. This shows that new end-to-end image analysis pipelines in computational pathology should be compared to classical weakly-supervised methods. Also, these findings motivate the development of new methods which combine the elegant assumptions of MIL with the empirically observed higher performance of classical weakly-supervised approaches. We make all source codes publicly available at https://github.com/KatherLab/HIA, allowing easy application of all methods to any similar task

Conversations under a Tung Tree

<p>Secreted frizzled related protein 3 (SFRP3) contains a cysteine-rich domain (CRD) that shares homology with Frizzled CRD and regulates WNT signaling. Independent studies showed epigenetic silencing of <i>SFRP3</i> in melanoma and hepatocellular carcinoma. Moreover, a tumor suppressive function of SFRP3 was shown in androgen-independent prostate and gastric cancer cells. The current study is the first to investigate <i>SFRP3</i> expression and its potential clinical impact on non-small cell lung carcinoma (NSCLC). WNT signaling components present on NSCLC subtypes were preliminary elucidated by expression data of The Cancer Genome Atlas (TCGA). We identified a distinct expression signature of relevant WNT signaling components that differ between adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Of interest, canonical WNT signaling is predominant in LUAD samples and non-canonical WNT signaling is predominant in LUSC. In line, high SFRP3 expression resulted in beneficial clinical outcome for LUAD but not for LUSC patients. Furthermore, <i>SFRP3</i> mRNA expression was significantly decreased in NSCLC tissue compared to normal lung samples. TCGA data verified the reduction of <i>SFRP3</i> in LUAD and LUSC patients. Moreover, DNA hypermethylation of <i>SFRP3</i> was evaluated in the TCGA methylation dataset resulting in epigenetic inactivation of <i>SFRP3</i> expression in LUAD, but not in LUSC, and was validated by pyrosequencing of our NSCLC tissue cohort and <i>in vitro</i> demethylation experiments. Immunohistochemistry confirmed SFRP3 protein downregulation in primary NSCLC and indicated abundant expression in normal lung tissue. Two adenocarcinoma gain-of-function models were used to analyze the functional impact of SFRP3 on cell proliferation and regulation of <i>CyclinD1</i> expression <i>in vitro</i>. Our results indicate that <i>SFRP3</i> acts as a novel putative tumor suppressor gene in adenocarcinoma of the lung possibly regulating canonical WNT signaling.</p

Liver Phenotypes of European Adults Heterozygous or Homozygous for Pi∗Z Variant of AAT (Pi∗MZ vs Pi∗ZZ genotype) and Noncarriers

Homozygosity for the Pi∗Z variant of the gene that encodes the alpha-1 antitrypsin peptide (AAT), called the Pi∗ZZ genotype, causes a liver and lung disease called alpha-1 antitrypsin deficiency. Heterozygosity (the Pi∗MZ genotype) is a risk factor for cirrhosis in individuals with liver disease. Up to 4% of Europeans have the Pi∗MZ genotype; we compared features of adults with and without Pi∗MZ genotype among persons without preexisting liver disease.info:eu-repo/semantics/publishedVersio

Clinical-grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning

Background and Aims: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and cheaper than molecular assays. But clinical application of this technology requires high performance and multisite validation, which have not yet been performed. Methods: We collected hematoxylin and eosin-stained slides, and findings from molecular analyses for MSI and dMMR, from 8836 colorectal tumors (of all stages) included in the MSIDETECT consortium study, from Germany, the Netherlands, the United Kingdom, and the United States. Specimens with dMMR were identified by immunohistochemistry analyses of tissue microarrays for loss of MLH1, MSH2, MSH6, and/or PMS2. Specimens with MSI were identified by genetic analyses. We trained a deep-learning detector to identify samples with MSI from these slides; performance was assessed by cross-validation (n=6406 specimens) and validated in an external cohort (n=771 specimens). Prespecified endpoints were area under the receiver operating characteristic (AUROC) curve and area under the precision-recall curve (AUPRC). Results: The deep-learning detector identified specimens with dMMR or MSI with a mean AUROC curve of 0.92 (lower bound 0.91, upper bound 0.93) and an AUPRC of 0.63 (range, 0.59–0.65), or 67% specificity and 95% sensitivity, in the cross-validation development cohort. In the validation cohort, the classifier identified samples with dMMR with an AUROC curve of 0.95 (range, 0.92–0.96) without image-preprocessing and an AUROC curve of 0.96 (range, 0.93–0.98) after color normalization. Conclusions: We developed a deep-learning system that detects colorectal cancer specimens with dMMR or MSI using hematoxylin and eosin-stained slides; it detected tissues with dMMR with an AUROC of 0.96 in a large, international validation cohort. This system might be used for high-throughput, low-cost evaluation of colorectal tissue specimens