Comparative expression of immunohistochemical biomarkers in cribriform and pattern 4 non-cribriform prostatic adenocarcinoma

© 2020 Elsevier Inc. The morphology of Gleason 4 prostate cancer (PCa) can be subdivided into cribriform and non-cribriform patterns. A large body of evidence has shown that pattern 4 cribriform PCa (especially non-glomeruloid type) is associated with adverse pathologic features and clinical outcomes compared with non-cribriform pattern 4 PCa. The underlying mechanisms for the aggressiveness of cribriform PCa are not fully understood. The aim of this study is to compare the immunohistochemical expression of various biomarkers and to determine the potential proteins that may account for their biologic and clinical differences. A total of 14 biomarkers were studied. The number of non-glomeruloid cribriform PCa cases studied for each biomarker ranged from 18 to 74 and the number of non-cribriform pattern 4 PCa studied for each biomarker ranged from 29 to 112. We demonstrated that, compared with non-cribriform Gleason pattern 4 PCa, EGFR was significantly upregulated and standard CD44 (CD44s) was significantly downregulated in cribriform PCa; no significant differences were found in the expression of AR, NKX3.1, ERG, EZH2, p53, Rb, C-Myc, BCL2, p16, CyclinD1, Her2/Neu, and Synaptophysin between these two groups of pattern 4 PCa. The study also showed, compared to non-cribriform PCa, cribriform PCa presented with significantly higher serum PSA and more advanced tumor stage. The significant overexpression of EGFR and downregulation of CD44s in non-glomeruloid cribriform PCa may, at least, partly explain the unfavorable pathology and clinical results for this growth pattern. Given that EGFR targeted inhibitors are now available, the findings may also have significant therapeutic implications

Syndromes associated with multiple pilomatricomas: When should clinicians be concerned?

BACKGROUND: Multiple pilomatricomas have been linked to various syndromes. However, these associations are poorly defined, leaving practitioners conflicted on management of these patients. OBJECTIVE: To perform a comprehensive review to clarify the strength of these relationships and identify which patients may benefit from additional screening and/or genetic screening. METHODS: A literature search was performed using the PubMed, Ovid, and Cochrane databases. Syndromic, familial, and sporadic cases of multiple pilomatricomas were stratified based on number of pilomatricomas. This information was graphed for visual comparison. RESULTS: Sixty-six syndromic cases from 52 publications were identified, with the majority (54) of cases representing myotonic dystrophy, familial adenomatous polyposis-related syndromes (including Gardner syndrome), Turner syndrome, or Rubinstein-Taybi syndrome. Twenty-five of the 54 cases (46.3%) had six or more pilomatricomas. Of sporadic cases, 128 out of 134 (95.5%) had five or less pilomatricomas. LIMITATIONS: Most articles were case reports and series, which are vulnerable to publication bias. Specific details were not explicitly noted in some original articles, and incomplete data could not always be included in analysis. Syndromes may have been missed in sporadic cases. CONCLUSION: The presence of six or more pilomatricomas is highly suggestive of an underlying syndrome (\u3e95% specificity). These patients should undergo additional screening. Patients with less than six pilomatricomas and family history of myotonic dystrophy, first-degree relative with colon cancer or FAP-related syndrome, or family history of pilomatricomas should also undergo further screening

Seismic Hazard Analyses From Geologic and Geomorphic Data: Current and Future Challenges

AbstractThe loss of life and economic consequences caused by several recent earthquakes demonstrate the importance of developing seismically safe building codes. The quantification of seismic hazard, which describes the likelihood of earthquake‐induced ground shaking at a site for a specific time period, is a key component of a building code, as it helps ensure that structures are designed to withstand the ground shaking caused by a potential earthquake. Geologic or geomorphic data represent important inputs to the most common seismic hazard model (probabilistic seismic hazard analyses, or PSHAs), as they can characterize the magnitudes, locations, and types of earthquakes that occur over long intervals (thousands of years). However, several recent earthquakes and a growing body of work challenge many of our previous assumptions about the characteristics of active faults and their rupture behavior, and these complexities can be challenging to accurately represent in PSHA. Here, we discuss several of the outstanding challenges surrounding geologic and geomorphic data sets frequently used in PSHA. The topics we discuss include how to utilize paleoseismic records in fault slip rate estimates, understanding and modeling earthquake recurrence and fault complexity, the development and use of fault‐scaling relationships, and characterizing enigmatic faults using topography. Making headway in these areas will likely require advancements in our understanding of the fundamental science behind processes such as fault triggering, complex rupture, earthquake clustering, and fault scaling. Progress in these topics will be important if we wish to accurately capture earthquake behavior in a variety of settings using PSHA in the future