Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity

Numerous software tools exist for data-independent acquisition (DIA) analysis of clinical samples, necessitating their comprehensive benchmarking. We present a benchmark dataset comprising real-world inter-patient heterogeneity, which we use for in-depth benchmarking of DIA data analysis workflows for clinical settings. Combining spectral libraries, DIA software, sparsity reduction, normalization, and statistical tests results in 1428 distinct data analysis workflows, which we evaluate based on their ability to correctly identify differentially abundant proteins. From our dataset, we derive bootstrap datasets of varying sample sizes and use the whole range of bootstrap datasets to robustly evaluate each workflow. We find that all DIA software suites benefit from using a gas-phase fractionated spectral library, irrespective of the library refinement used. Gas-phase fractionation-based libraries perform best against two out of three reference protein lists. Among all investigated statistical tests non-parametric permutation-based statistical tests consistently perform best

BCG Induced Necrosis of the Entire Bladder Urothelium

AbstractInstillation therapy with attenuated tuberculosis bacteria (BCG) can significantly reduce rates of recurrence of non-muscle invasive bladder cancer. Local and systemic side effects such as dysuria, irritative voiding symptoms or partial bladder contracture and systemic inflammation were reported. A 75 year-old male patient with recurrent non muscle invasive bladder cancer developed necrosis of the entire bladder urothelium more than six years after BCG instillation immunotherapy. The resulting irritative voiding symptoms and low bladder capacity required radical cystectomy. BCG instillation can cause severe side effects, which develop gradually and eventually need radical surgical therapy such as cystectomy without tumor recurrence

Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity

Numerous software tools exist for data-independent acquisition (DIA) analysis of clinical samples, necessitating their comprehensive benchmarking. We present a benchmark dataset comprising real-world inter-patient heterogeneity, which we use for in-depth benchmarking of DIA data analysis workflows for clinical settings. Combining spectral libraries, DIA software, sparsity reduction, normalization, and statistical tests results in 1428 distinct data analysis workflows, which we evaluate based on their ability to correctly identify differentially abundant proteins. From our dataset, we derive bootstrap datasets of varying sample sizes and use the whole range of bootstrap datasets to robustly evaluate each workflow. We find that all DIA software suites benefit from using a gas-phase fractionated spectral library, irrespective of the library refinement used. Gas-phase fractionation-based libraries perform best against two out of three reference protein lists. Among all investigated statistical tests non-parametric permutation-based statistical tests consistently perform best

Phosphohistone 3 (PHH3) and lactate dehydrogenase 5 (LDH5) are expressed in ductal carcinoma in situ of the breast: possible clinical implications

Purpose: Proliferation and pre-malignancy are typical features of DCIS. The expression of PHH3 as a marker for proliferation and LDH 5 as an indicator for oxygen independent energy metabolism was investigated in order to assess their potential for an improved characterisation of these lesions. Methods: Archived tissue blocks and clinical records of 130 patients with DCIS. Immunohistochemistry for PHH3, LDH5, estrogen receptor (ER), progesterone receptor (PR), human EGF receptor 2 (HER2). Silverstein nuclear grading. Chi Square test for all factors. Results: Percentage of positive patients was 69% for PHH3, 94% for LDH5, 76% for ER, 67% for PR, and 21% for HER2. Significant correlation was seen between PHH3 and LDH5 expression. No correlation could be found for any of the other comparisons. Conclusion: This is the first description of PHH3 and LDH5 in DCIS. The biological significance of PHH3 remains to be determined in a larger set of patients. LDH5 may be a useful diagnostic marker in the future. Positive HER2 receptors were considerably less frequent than previously reported

The Advocate

Headlines Include: Laurels For Feerick: An Alumnus To Remember; Crime at Fordham; Who\u27s Next?, Film at 11https://ir.lawnet.fordham.edu/student_the_advocate/1007/thumbnail.jp

Circulating Tumor Cells in Pancreatic Cancer: Current Perspectives

Pancreatic cancer is the fourth leading cause of cancer-related death in the USA and Europe; early symptoms and screenings are lacking, and it is usually diagnosed late with a poor prognosis. Circulating tumor cells (CTCs) have been promising new biomarkers in solid tumors. In the last twenty years (1999–2019), 140 articles have contained the key words “Circulating tumor cells, pancreatic cancer, prognosis and diagnosis.” Articles were evaluated for the use of CTCs as prognostic markers and their correlation to survival in pancreatic ductal adenocarcinoma (PDAC). In the final selected 17 articles, the CTC detection rate varied greatly between different enrichment methodologies and ranged from 11% to 92%; the majority of studies used the antigen-dependent CellSearch© system for CTC detection. Fifteen of the reviewed studies showed a correlation between CTC presence and a worse overall survival. The heterogeneity of CTC-detection methods and the lack of uniform results hinder a comparison of the evaluated studies. However, CTCs can be detected in pancreatic cancer and harbor a hope to serve as an early detection tool. Larger studies are needed to corroborate CTCs as valid biomarkers in pancreatic cancer