Faculty Bibliography

BACKGROUND:Prostate cancer (PCa) is the most common malignant tumor found among men in the United States. Incidence rates of PCa have recently grown in Asian countries, partially due to the comprehensive implementation of early detection systems. Interestingly, a prospective cohort study showed that adopting a westernized dietary pattern was associated with a higher risk of being diagnosed with PCa among Korean and Japanese men. However, a comparison of current clinicopathological features of PCa between American and Chinese men is lacking. In this study, we report the current clinicopathological features of PCa in Chinese men and compare them to those of patients in the USA. MATERIALS AND METHODS/METHODS:Case cohorts included, in total, 871 PCa cases with prostatectomy sequentially treated since 2017, including 299 cases from USA and 572 cases from two different academic hospitals in China. The parameters, including patient's age, preoperative Prostate-Specific Antigen (PSA) level, Gleason score, Grade Group, stage and tumor focality, were collected, analyzed and compared using two sample t-test, Wilcoxon rank sum test, Pearson's Chi-squared test and Fisher's exact test. RESULTS:Significant differences were demonstrated in the mean age of patients, preoperative PSA levels, extra-prostatic extension, Gleason scores, and Grade Groups (p < 0.05). PCa patients in the Chinese group were older than patients in the USA group (67.81 vs. 63.53, p < 0.01). The preoperative PSA levels in the Chinese group were higher than those in the USA group (11.69 v.s 6.30, p < 0.01). A higher percentage of high Grade Groups (Groups 4 and 5) was observed in the Chinese group (25.7%) compared to the USA cohort (17.11%), while Grade Group 2 was more common in the USA group than in the Chinese group (51.68% vs. 32.52%, p < 0.01). CONCLUSIONS:All these data suggest that the clinicopathologic features of PCa are different between the USA and Chinese populations, which may be influenced by treatment strategies (including surgical case selection criteria).

Lymphoma of the urinary tract is relatively rare and comprises of < 5% of all primary extra nodal lymphoma. Diagnoses of these lesions at anearly stage is important as they can disseminate or transform into high grade lesion if there is a delay in the diagnoses. There are only few case series and case reports on the malignant lymphoma of the urinary tract. The aim of this study was to characterize lymphoma involving the urinary bladder and prostate. We retrospectively reviewed the clinical data and histologic findings of the malignant lymphoma involving urinary bladder and prostate at our institution. Lymphoma involving the lower urinary tract clinically presented with lower urinary tract symptoms and usually with concurrent associated urinary bladder cancer or prostatic cancer in our series. Lymphoma should be included in the differential diagnoses especially in patients with prior history of lymphoid disorders. There should be a high index of suspicion when there is any atypical lymphoid infiltrate in routine urinary bladder and prostate surgical specimens.

Background: Artificial intelligence (AI) has been increasingly used in surgical pathology to assist pathologists for diagnosis, grading and staging purposes. We describe in this report a proof of concept study that pathologists themselves could use a commercial deep learning software to develop an AI model to assist the classification of flat urothelial lesions.
Design(s): 227 flat urothelial lesions including normal (N) (66), benign reactive (BR) (53), dysplasia (D) (49) and carcinoma in situ (CIS) (59) from one institution (TMC) were reviewed, and representative H&E micrographs of taken at 10X magnification by pathologists on various cameras attached to microscopes. Fifty % of these images were imported into Cognex VisionPro Deep Learning 2.0 software tool, which was trained to develop a flat urothelial classifier (Model 1) to distinguish between N, BR, D and CIS. The classifier comprised of a chain of 3 deep learning models to first remove the blank space in the images, to identify urothelial regions and finally to classify the urothelial regions. An F-score was used to measure the accuracy of the model to classify the images of flat urothelial lesions. 191 micrographs of flat urothelial lesions from a different institution (NYU), including N (35), BR (52), D (47) and CIS (57), were used as validation cases. Fifty % of latter images were used to train a new model (Model 2) based on the Model 1.
Result(s): The F-score for Model 1 on TMC cases was 96.1%. 97.1%, 85.2%, 100% and 100% of cases in N, BR, D and CIS were correctly classified. When Model 1 was used on NYU cases, the overall F-score was 44.9%. Model 1 was retrained using 50% of NYU images to generate Model 2. The F-score for Model 2 on NYU images improved to 86.8%, while it was 88.9% on TMC images.
Conclusion(s): This proof of concept study confirms that a pathologist with little background in deep learning software development can use a commercially available deep learning software to develop a robust AI model to assist the classification of flat urothelial lesions. While a model developed using one set of images from one lab may not be directly applied to images from a different lab, it could nevertheless be retrained using the images from the second lab to achieve high classification accuracy. Studies are underway to develop AI models for flat urothelial classification on whole slide images

Background: Magnetic resonance imaging (MRI) targeted prostate biopsy has become an increasingly common method of diagnosing prostate cancer. Previous study from our institution demonstrates the biopsy global Gleason grade (gGG) and highest Gleason grade (hGG) show substantial concordance with the radical prostatectomy Gleason grade (RPGG) while the discordance predominantly comprise of upgrading in gGG and downgrading in hGG. We performed a larger cohort focused analysis on the agreement of gGG and hGG to the RPGG when they differ.
Design(s): A retrospective review of radical prostatectomy specimens between 10/2016 and 12/2020 from our institution with prior MRI-targeted biopsies was conducted. A gGG (aggregate GG of all positive cores) and a hGG (highest GG in any core) was assigned to each MRI-targeted lesion. Only cases with different gGG versus hGG were selected for further analysis. The concordance of gGG and hGG with RPGG was evaluated using kappa coefficient analyses. The power of pre-biopsy PSA and PIRADS scores to predict upgrading based on gGG was also analyzed.
Result(s): Of the 489 radical prostatectomy specimens with prior MRI-targeted biopsies, 82 cases (17%) differed in gGG versus hGG. Using the gGG, 33 cases (40%), 46 cases (56%), and 3 cases (4%) were upgraded, unchanged, and downgraded at radical prostatectomy, respectively (Kappa = 0.302, weighted Kappa = 0.334). Based on the hGG, 9 cases (11%), 24 cases (29%), and 49 cases (60%) were upgraded, unchanged, and downgraded at radical prostatectomy, respectively (Kappa = 0.040, weighted Kappa = 0.198) (Figure 1). When stratified by RPGG, gGG shows the best concordance in RPGG2 and RPGG3 lesions. The hGG resulted in substantial downgrading at RPGG4 or less and upgrading at RPGG5 (Figure 2). No significant difference in the mean PSA [H(2) = 5.89, p = 0.053] or PI-RADS score [H(2) = 4.48, p = 0.107] was found among the cases upgraded, unchanged, and downgraded based on the gGG. Neither the pre-biopsy PSA (OR = 1.92, 95% CI = 0.65-5.64, p = 0.117) nor the PI-RADS score (OR = 0.899, 95% CI = 0.31-2.607, p = 0.423) was predictive of upgrading based on gGG.
Conclusion(s): When the gGG and hGG differ, the gGG correlates better with the RPGG than the hGG in the majority of cases for RPGG2 and RPGG3 lesions (46 cases, 74%). It results in upgrading in high grade lesions (GG4 and GG5) with potentially minimal impact on clinical management. Further studies are needed to substantiate a standard GG reporting method for MRI-targeted prostate biopsies

Importance/UNASSIGNED:There is clinical equipoise for COVID-19 convalescent plasma (CCP) use in patients hospitalized with COVID-19. Objective/UNASSIGNED:To determine the safety and efficacy of CCP compared with placebo in hospitalized patients with COVID-19 receiving noninvasive supplemental oxygen. Design, Setting, and Participants/UNASSIGNED:CONTAIN COVID-19, a randomized, double-blind, placebo-controlled trial of CCP in hospitalized adults with COVID-19, was conducted at 21 US hospitals from April 17, 2020, to March 15, 2021. The trial enrolled 941 participants who were hospitalized for 3 or less days or presented 7 or less days after symptom onset and required noninvasive oxygen supplementation. Interventions/UNASSIGNED:A unit of approximately 250 mL of CCP or equivalent volume of placebo (normal saline). Main Outcomes and Measures/UNASSIGNED:The primary outcome was participant scores on the 11-point World Health Organization (WHO) Ordinal Scale for Clinical Improvement on day 14 after randomization; the secondary outcome was WHO scores determined on day 28. Subgroups were analyzed with respect to age, baseline WHO score, concomitant medications, symptom duration, CCP SARS-CoV-2 titer, baseline SARS-CoV-2 serostatus, and enrollment quarter. Outcomes were analyzed using a bayesian proportional cumulative odds model. Efficacy of CCP was defined as a cumulative adjusted odds ratio (cOR) less than 1 and a clinically meaningful effect as cOR less than 0.8. Results/UNASSIGNED:Of 941 participants randomized (473 to placebo and 468 to CCP), 556 were men (59.1%); median age was 63 years (IQR, 52-73); 373 (39.6%) were Hispanic and 132 (14.0%) were non-Hispanic Black. The cOR for the primary outcome adjusted for site, baseline risk, WHO score, age, sex, and symptom duration was 0.94 (95% credible interval [CrI], 0.75-1.18) with posterior probability (P[cOR<1] = 72%); the cOR for the secondary adjusted outcome was 0.92 (95% CrI, 0.74-1.16; P[cOR<1] = 76%). Exploratory subgroup analyses suggested heterogeneity of treatment effect: at day 28, cORs were 0.72 (95% CrI, 0.46-1.13; P[cOR<1] = 93%) for participants enrolled in April-June 2020 and 0.65 (95% CrI, 0.41 to 1.02; P[cOR<1] = 97%) for those not receiving remdesivir and not receiving corticosteroids at randomization. Median CCP SARS-CoV-2 neutralizing titer used in April to June 2020 was 1:175 (IQR, 76-379). Any adverse events (excluding transfusion reactions) were reported for 39 (8.2%) placebo recipients and 44 (9.4%) CCP recipients (P = .57). Transfusion reactions occurred in 2 (0.4) placebo recipients and 8 (1.7) CCP recipients (P = .06). Conclusions and Relevance/UNASSIGNED:In this trial, CCP did not meet the prespecified primary and secondary outcomes for CCP efficacy. However, high-titer CCP may have benefited participants early in the pandemic when remdesivir and corticosteroids were not in use. Trial Registration/UNASSIGNED:ClinicalTrials.gov Identifier: NCT04364737.

Introduction & Objectives: Delay between prostate biopsy (PB) and pathologic diagnosis leads to a concern of inadequate sampling and repeated biopsy. Stimulated Raman Histology (SRH) is a novel microscopic technique allowing real time, label-free, high-resolution microscopic images of unprocessed, un-sectioned tissue. We evaluated the accuracy of pathologist interpretation of PB SRH as compared to traditional hematoxylin and eosin (H&E) stained slides.
Material(s) and Method(s): Men undergoing prostatectomy were included in an IRB approved prospective study. 18-gauge PB cores, taken ex vivo from prostatectomy specimen, were scanned in a SRH microscope at 20 microns depth over 10-14 minutes using two Raman shifts: 2845cm-1 and 2930cm-1, to create SRH images. The cores were then processed as per normal pathologic protocols. 16 PB containing benign/prostate cancer histology were used as a SRH training cohort for 4 GU pathologists (1, 3, 2x >15 yrs experience), who were then tested on a set of 32 PB imaged by SRH and processed by traditional H&E. Sensitivity, specificity, and concordance for PCa detection on SRH relative to a consensus H&E were assessed. With a two-sided alpha level of 5%, it was calculated 32 SRH imaged biopsies would provide 90% power to detect concordance (k).
Result(s): PB cores were imaged in 2-3 separate strips (11-21 minutes) shown in Figure 1. In identifying any cancer, pathologists achieved moderate concordance (k=0.570; p<0.001) which improved when identifying GGG 2-5 PCa only (k=0.640, p<0001; sensitivity 96.4%; specificity 58.3%). In predicting Gleason score, the concordance for each pathologist varied from poor to moderate (k range -0.163 to 0.457). After individual assessment was completed a pathology consensus conference was held for the interpretation of the SRH PB. In identifying any prostate cancer, pathologists achieved near perfect concordance (k=0.925; p<0.001; sensitivity 95.6%; specificity 100%). When evaluating SRH in a consensus conference, the group prediction of Gleason score improved to moderate concordance (k=0.470; p<0.001). (Figure Presented) (Figure Presented)
Conclusion(s): SRH produces high quality microscopic images that allow for accurate identification of PCa in real-time without need for sectioning or tissue-processing. Individual pathologist performance varied highly suggesting potential for improvement with further training. Future SRH interpretation by convolutional neural network may further enhance GGG prediction
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When multiple cores are biopsied from a single magnetic resonance imaging (MRI)-targeted lesion, Gleason grade may be assigned for each core separately or for all cores of the lesion in aggregate. Because of the potential for disparate grades, an optimal method for pathology reporting MRI lesion grade awaits validation. We examined our institutional experience on the concordance of biopsy grade with subsequent radical prostatectomy (RP) grade of targeted lesions when grade is determined on individual versus aggregate core basis. For 317 patients (with 367 lesions) who underwent MRI-targeted biopsy followed by RP, targeted lesion grade was assigned as (1) global Grade Group (GG), aggregated positive cores; (2) highest GG (highest grade in single biopsy core); and (3) largest volume GG (grade in the core with longest cancer linear length). The 3 biopsy grades were compared (equivalence, upgrade, or downgrade) with the final grade of the lesion in the RP, using κ and weighted κ coefficients. The biopsy global, highest, and largest GGs were the same as the final RP GG in 73%, 68%, 62% cases, respectively (weighted κ: 0.77, 0.79, and 0.71). For cases where the targeted lesion biopsy grade scores differed from each other when assigned by global, highest, and largest GG, the concordance with the targeted lesion RP GG was 69%, 52%, 31% for biopsy global, highest, and largest GGs tumors (weighted κ: 0.65, 0.68, 0.59). Overall, global, highest, and largest GG of the targeted biopsy show substantial agreement with RP-targeted lesion GG, however targeted global GG yields slightly better agreement than either targeted highest or largest GG. This becomes more apparent in nearly one third of cases when each of the 3 targeted lesion level biopsy scores differ. These results support the use of global (aggregate) GG for reporting of MRI lesion-targeted biopsies, while further validations are awaited.

Prostate cancer is the most frequently diagnosed cancer in males and its development and progression remains an important area of study. Recently, long non-coding RNAs (lncRNAs) have been evidenced as key players in cancer pathogenesis. Specifically, dysregulation of long non-coding RNA (lncRNA) expression has shown to affect tumor proliferation and metastasis, acting as either tumor suppressors or oncogenes. However, its specific mechanisms and functions in prostate cancer remain unclear. This review provides an overview of currently available information on prostate cancer-related lncRNAs, including GAS5, GAS-007, MEG3, PCA3, PCAT14, PCAT1, PVT1, UCA1, SChLAP1, MALAT1, HOTAIR, and NEAT1. Notable tumor growth inhibitors include GAS5 and MEG3. GAS5 is evidenced to interfere with the AKT/MTOR signaling pathway through targeting microRNA mir-103. MEG3, however, is proposed to inhibit the cycle, sponge miR-9-5p, and induce gene silencing. PCAT1, PVT1, and UCA1 are important tumor growth promoters. PCAT1 is indicated to be a transcriptional repressor, a mir-145-5P sponge, and a P13K/AKT pathway activator. Studies suggest that PVT1 acts via microRNA targeting and regulating proliferating cell nuclear antigen. UCA1 may sponge miR-204 and miR-331-3p as well as regulate myosin VI. Thorough understanding of these lncRNAs may elucidate new aspects of prostate cancer pathology and serve a pivotal role in developing novel diagnostic and prognostic techniques.