A genetically defined disease model reveals that urothelial cells can initiate divergent bladder cancer phenotypes.

Small cell carcinoma of the bladder (SCCB) is a rare and lethal phenotype of bladder cancer. The pathogenesis and molecular features are unknown. Here, we established a genetically engineered SCCB model and a cohort of patient SCCB and urothelial carcinoma samples to characterize molecular similarities and differences between bladder cancer phenotypes. We demonstrate that SCCB shares a urothelial origin with other bladder cancer phenotypes by showing that urothelial cells driven by a set of defined oncogenic factors give rise to a mixture of tumor phenotypes, including small cell carcinoma, urothelial carcinoma, and squamous cell carcinoma. Tumor-derived single-cell clones also give rise to both SCCB and urothelial carcinoma in xenografts. Despite this shared urothelial origin, clinical SCCB samples have a distinct transcriptional profile and a unique transcriptional regulatory network. Using the transcriptional profile from our cohort, we identified cell surface proteins (CSPs) associated with the SCCB phenotype. We found that the majority of SCCB samples have PD-L1 expression in both tumor cells and tumor-infiltrating lymphocytes, suggesting that immune checkpoint inhibitors could be a treatment option for SCCB. We further demonstrate that our genetically engineered tumor model is a representative tool for investigating CSPs in SCCB by showing that it shares a similar a CSP profile with clinical samples and expresses SCCB-up-regulated CSPs at both the mRNA and protein levels. Our findings reveal distinct molecular features of SCCB and provide a transcriptional dataset and a preclinical model for further investigating SCCB biology.

Predicting Pathological Tumor Size in Prostate Cancer Based on Multiparametric Prostate Magnetic Resonance Imaging and Preoperative Findings.

PURPOSE: Oncologic efficacy of focal therapies in prostate cancer depends heavily on accurate tumor size estimation. We aim to evaluate the agreement between radiologic tumor size and pathological tumor size, and identify predictors of pathological tumor size. MATERIALS AND METHODS: This single arm study cohort included all consecutive patients with biopsy proven prostate cancer and a corresponding PI-RADS®v2 3 or greater index tumor on multiparametric magnetic resonance imaging who subsequently underwent radical prostatectomy. Radiologic tumor size was defined as maximum tumor diameter on multiparametric magnetic resonance imaging and compared to whole mount histopathology tumor correlates. The difference between radiologic tumor size and pathological tumor size was assessed, and clinical, pathological and radiographic predictors of pathological tumor size were examined. RESULTS: A total of 461 consecutive lesions in 441 men were included for statistical analysis. Mean radiologic tumor size and pathological tumor size was 1.57 and 2.37 cm, respectively (p <0.001). Radiologic tumor size consistently underestimated pathological tumor size regardless of the preoperative covariates, and the degree of underestimation increased with smaller radiologic tumor size and lower PI-RADSv2 scores. Pathological tumor size was significantly larger for biopsy Gleason Grade Group (GG) 5 compared to GG1 (mean change 0.37 cm, p=0.014), PI-RADSv2 5 lesions compared to PI-RADSv2 4 (mean change 0.26, p=0.006) and higher prostate specific antigen density. The correlations between radiologic tumor size vs pathological tumor size according to biopsy GG and radiologic covariates were generally low with correlation coefficients ranging between 0.1 and 0.65. CONCLUSIONS: Multiparametric magnetic resonance imaging frequently underestimates pathological tumor size and the degree of underestimation increases with smaller radiologic tumor size and lower PI-RADSv2 scores. Therefore, a larger ablation margin may be required for smaller tumors and lesions with lower PI-RADSv2 scores. These variables must be considered when estimating treatment margins in focal therapy.

Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer.

PURPOSE: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. MATERIALS AND METHODS: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. RESULTS: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p <0.001 and p=0.004, respectively) but was similar to RTB (p=0.71), which used on average 3.8 (22%) fewer cores per patient. In 102 patients who underwent prostatectomy, there was no significant difference in upgrading rates between RTB and combined biopsy (p=0.84). CONCLUSIONS: A RTB approach can maintain state-of-the-art detection rates while requiring fewer retrieved cores. This result informs decision making about biopsy site selection and total retrieved core count.

Intestinal mucormycosis initially identified by next-generation sequencing of cell-free DNA.

Mucormycosis is a rare fungal infection that typically affects severely immunocompromised individuals, often resulting in significant morbidity and mortality. Although early and aggressive intervention is necessary to prevent poor outcomes, diagnosis of this infection remains difficult. We report the first case, to our knowledge, of invasive gastrointestinal mucormycosis initially identified by next-generation sequencing of cfDNA from the blood, and discuss the various benefits and challenges which come with new molecular diagnostic techniques.

Prostate Microstructure in Prostate Cancer Using 3-T MRI with Diffusion-Relaxation Correlation Spectrum Imaging: Validation with Whole-Mount Digital Histopathology.

Background Microstructural MRI has the potential to improve diagnosis and characterization of prostate cancer (PCa), but validation with histopathology is lacking. Purpose To validate ex vivo diffusion-relaxation correlation spectrum imaging (DR-CSI) in the characterization of microstructural tissue compartments in prostate specimens from men with PCa by using registered whole-mount digital histopathology (WMHP) as the reference standard. Materials and Methods Men with PCa who underwent 3-T MRI and robotic-assisted radical prostatectomy between June 2018 and January 2019 were prospectively studied. After prostatectomy, the fresh whole prostate specimens were imaged in patient-specific three-dimensionally printed molds by using 3-T MRI with DR-CSI and were then sliced to create coregistered WMHP slides. The DR-CSI spectral signal component fractions (fA, fB, fC) were compared with epithelial, stromal, and luminal area fractions (fepithelium, fstroma, flumen) quantified in PCa and benign tissue regions. A linear mixed-effects model assessed the correlations between (fA, fB, fC) and (fepithelium, fstroma, flumen), and the strength of correlations was evaluated by using Spearman correlation coefficients. Differences between PCa and benign tissues in terms of DR-CSI signal components and microscopic tissue compartments were assessed using two-sided t tests. Results Prostate specimens from nine men (mean age, 65 years ± 7 [standard deviation]) were evaluated; 20 regions from 17 PCas, along with 20 benign tissue regions of interest, were analyzed. Three DR-CSI spectral signal components (spectral peaks) were consistently identified. The fA, fB, and fC were correlated with fepithelium, fstroma, and flumen (all P < .001), with Spearman correlation coefficients of 0.74 (95% confidence interval [CI]: 0.62, 0.83), 0.80 (95% CI: 0.66, 0.89), and 0.67 (95% CI: 0.51, 0.81), respectively. PCa exhibited differences compared with benign tissues in terms of increased fA (PCa vs benign, 0.37 ± 0.05 vs 0.27 ± 0.06; P < .001), decreased fC (PCa vs benign, 0.18 ± 0.06 vs 0.31 ± 0.13; P = .01), increased fepithelium (PCa vs benign, 0.44 ± 0.13 vs 0.26 ± 0.16; P < .001), and decreased flumen (PCa vs benign, 0.14 ± 0.08 vs 0.27 ± 0.18; P = .004). Conclusion Diffusion-relaxation correlation spectrum imaging signal components correlate with microscopic tissue compartments in the prostate and differ between cancer and benign tissue. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Lee and Hectors in this issue.

Cancer core length from targeted biopsy: an index of prostate cancer volume and pathological stage.

OBJECTIVE: To study the relationship of maximum cancer core length (MCCL), on targeted biopsy (TB) of magnetic resonance imaging (MRI)-visible index lesions, to volume of that tumour found at radical prostatectomy (RP). PATIENTS AND METHODS: In all, 205 men undergoing fusion biopsy and RP were divided into two groups: 136 in whom the MCCL came from an index MRI-visible lesion (TB) and 69 in whom MCCL came from a non-targeted lesion (non-targeted biopsy [NTB]). MRI was 3-T multi-parametric and biopsy was via MRI-ultrasonography fusion. RESULTS: In the TB group, MCCL correlated with volume of clinically significant index tumours (ρ = 0.44-0.60, P < 0.01). The correlation was similar for first and repeat biopsy and for transition and peripheral zone lesions (ρ = 0.42-0.49, P < 0.01). No correlations were found in the NTB group. TB MCCL (6-10 and >10 mm) and MRI lesion diameter (>20 mm) were independently associated with tumour volume. TB MCCLs >10 mm and Gleason scores >7 were each associated with pathological T3 disease (odds ratios 5.73 and 5.04, respectively), but MRI lesion diameter lesion was not. CONCLUSIONS: MCCL on a TB from an MRI-visible lesion is an independent predictor of both cancer volume and pathological stage. This relationship does not exist for MCCL from a NTB core. Quantifying CCL on MRI-TBs may have a value, not previously described, to risk-stratify patients with prostate cancer before treatment.

Apparent Diffusion Coefficient (ADC) Ratio Versus Conventional ADC for Detecting Clinically Significant Prostate Cancer With 3-T MRI.

OBJECTIVE. The purpose of this study is to evaluate the performance of the apparent diffusion coefficient ratio (ADCratio; the ADC of the suspected prostate cancer [PCa] focus on MRI divided by the ADC in a noncancerous reference area) with that of conventional ADC for detection of high-grade PCa (Gleason score [GS] ≥ 3 + 4) versus low-grade PCa (GS = 3 + 3) with whole-mount (WM) histopathologic analysis used as a reference. MATERIALS AND METHODS. The cohort of this retrospective study included 218 men with 240 unilateral PCa lesions assessed by both 3-T multiparametric MRI and whole-mount histopathologic analysis. ROIs were placed on individual lesions verified by WM histopathologic analysis, to calculate the mean ADC (ADCtumor_mean) and lowest ADC within each lesion (ADCtumor_min), and within non-tumor-containing regions of the same tumor zone but on the contralateral side (ADCbenign), to calculate the background ADC. The ADCratio_mean (the ADCtumor_mean divided by the ADCbenign) was calculated. The performance of individual ADCtumor and ADCratio_mean values in discriminating PCa with a GS of 3 + 3 from PCa with a GS of 3 + 4 or greater was assessed using the AUC value. RESULTS. The ADCratio_mean had a higher AUC value for discriminating PCa lesions with a GS of 3 + 3 from those with a GS of 3 + 4 or greater (the AUC value increased from 0.70 using the ADCtumor_mean and 0.67 using the ADCtumor_min [the minimum ADC of the PCa lesion] to 0.80 for the ADCratio_mean and 0.72 for the ADCratio_min [the ADCtumor_min divided by the ADCbenign]; p = 0.043). When stratified by PCa zonal location, the ADCratio_mean had significantly more robust accuracy in the transition zone (the AUC value increased from 0.63 for ADCtumor_mean to 0.87 for ADCratio_mean; p = 0.019) compared with the peripheral zone (the AUC value increased from 0.74 for ADCtumor_mean to 0.78 for ADCratio_mean; p = 0.44). When analyzed on the basis of endorectal coil use, the ADCratio_mean performed nonsignificantly better in both the endorectal coil and non-endorectal coil subcohorts, although it performed better in the former. CONCLUSION. As an intrapatient-normalized diagnostic tool, the ADC ratio provided the best AUC value for discrimination of low-grade from high-grade PCa on 3-T MRI.

A 17-Gene Genomic Prostate Score Assay Provides Independent Information on Adverse Pathology in the Setting of Combined Multiparametric Magnetic Resonance Imaging Fusion Targeted and Systematic Prostate Biopsy.

PURPOSE: Multiparametric magnetic resonance imaging and biopsy based molecular tests such as the 17-gene Oncotype DX® Genomic Prostate Score™ assay are increasingly performed to improve risk stratification in men with clinically localized prostate cancer. The prostate score assay was previously shown to be a significant independent predictor of adverse pathology findings at radical prostatectomy in men diagnosed by systematic biopsies only. Therefore, we investigated the ability of the prostate score assay to predict adverse pathology findings in the setting of magnetic resonance imaging guided prostate biopsy. MATERIALS AND METHODS: We identified men diagnosed with NCCN® (National Comprehensive Cancer Network®) very low, low or intermediate risk prostate cancer who underwent simultaneous multiparametric magnetic resonance imaging fusion targeted and systematic prostate biopsy with subsequent radical prostatectomy within 6 months. Prostate score assay testing was performed on biopsy tissue with the highest Gleason score. The primary outcome of the study was adverse pathology findings, defined as Gleason score 4 + 3 or greater disease and/or pT3+ at radical prostatectomy. Independent predictors of adverse pathology findings were determined in a multivariable model to adjust for clinical parameters. RESULTS: A total of 134 men were eligible for primary analysis. On univariable analysis the UCLA score, magnetic resonance imaging, prostate score assay results and biopsy Gleason score were significant predictors of adverse pathology findings. After multivariable adjustment prostate score assay values remained a significant predictor of adverse pathology results (prostate score assay per 20 U OR 3.28, 95% CI 1.74-6.62, p <0.001). A wide and overlapping distribution of prostate score assay results was seen across PI-RADS® (Prostate Imaging Reporting and Data System) version 2 scores. CONCLUSIONS: The prostate score assay result is an independent predictor of adverse pathology findings in patients who were diagnosed with very low, low or intermediate risk prostate cancer in the setting of multiparametric magnetic resonance imaging fusion prostate biopsy. This assay can be useful as an independent technology or an adjunct technology to multiparametric magnetic resonance imaging to individualize risk stratification of low and intermediate risk prostate cancer.

Adrenal schwannoma can be FDG-Avid on PET/CT: case report and review of historic institutional pathology.

Schwannomas are benign, generally indolent tumors of neural crest origin and comprise the most common histologic tumor of peripheral nerves. Schwannomas are a rare histology for retroperitoneal tumors and very rare histologic findings for tumors of the adrenal gland with fewer than 50 cases in the reported literature. Here we present a case report of a non-hormonally functional but metabolically active adrenal tumor with indeterminate imaging characteristics with final pathology showing a 6.1 cm adrenal schwannoma as well as historical institutional pathology review revealing two additional cases.

Trichomonas vaginalis adherence phenotypes and extracellular vesicles impact parasite survival in a novel in vivo model of pathogenesis.

Trichomonas vaginalis is a human infective parasite responsible for trichomoniasis-the most common, non-viral, sexually transmitted infection worldwide. T. vaginalis resides exclusively in the urogenital tract of both men and women. In women, T. vaginalis has been found colonizing the cervix and vaginal tract while in men it has been identified in the upper and lower urogenital tract and in secreted fluids such as semen, urethral discharge, urine, and prostatic fluid. Despite the over 270 million cases of trichomoniasis annually worldwide, T. vaginalis continues to be a highly neglected organism and thus poorly studied. Here we have developed a male mouse model for studying T. vaginalis pathogenesis in vivo by delivering parasites into the murine urogenital tract (MUT) via transurethral catheterization. Parasite burden was assessed ex-vivo using a nanoluciferase-based gene expression assay which allowed quantification of parasites pre- and post-inoculation. Using this model and read-out approach, we show that T. vaginalis can be found within MUT tissue up to 72 hrs post-inoculation. Furthermore, we also demonstrate that parasites that exhibit increased parasite adherence in vitro also have higher parasite burden in mice in vivo. These data provide evidence that parasite adherence to host cells aids in parasite persistence in vivo and molecular determinants found to correlate with host cell adherence in vitro are applicable to infection in vivo. Finally, we show that co-inoculation of T. vaginalis extracellular vesicles (TvEVs) and parasites results in higher parasite burden in vivo. These findings confirm our previous in vitro-based predictions that TvEVs assist the parasite in colonizing the host. The establishment of this pathogenesis model for T. vaginalis sets the stage for identifying and examining parasite factors that contribute to and influence infection outcomes.

Cryotherapy for partial gland ablation of prostate cancer: Oncologic and safety outcomes.

BACKGROUND: Partial gland ablation (PGA) is a new option for treatment of prostate cancer (PCa). Cryotherapy, an early method of PGA, has had favorable evaluations, but few studies have employed a strict protocol using biopsy endpoints in men with clinically significant prostate cancer (csPCa). METHODS: 143 men with unilateral csPCa were enrolled in a prospective, observational trial of outpatient PGA-cryotherapy. Treatment was a 2-cycle freeze of the affected prostate part. Participants were evaluated with MRI-guided biopsy (MRGB) at baseline and at 6 months and 18 months after treatment. Absence of csPCa upon MRGB was the primary endpoint; quality-of-life at baseline and at 6 months after treatment was assessed by EPIC-CP questionnaires in the domains of urinary and sexual function. RESULTS: Of the 143 participants, 136 (95%) completed MRGB at 6 months after treatment. In 103/136 (76%), the biopsy revealed no csPCa. Of the 103, 71 subsequently had an 18-month comprehensive biopsy; of the 71 with 18-month biopsies, 46 (65%) were found to have no csPCa. MRI lesions became undetectable in 96/130 (74%); declines in median serum PSA levels (6.9 to 2.5 ng/mL), PSA density (0.15 to 0.07), and prostate volume (42 to 34cc) were observed (all p < 0.01). Neither lesion disappearance on MRI nor PSA decline correlated with biopsy outcome. Urinary function was affected only slightly and sexual function moderately. CONCLUSION: In the near to intermediate term, partial gland ablation with cryotherapy was found to be a safe and moderately effective treatment of intermediate-risk prostate cancer. Eradication of cancer was better determined by MRI-guided biopsy than by MRI or PSA.

PathAL: An Active Learning Framework for Histopathology Image Analysis.

Deep neural networks, in particular convolutional networks, have rapidly become a popular choice for analyzing histopathology images. However, training these models relies heavily on a large number of samples manually annotated by experts, which is cumbersome and expensive. In addition, it is difficult to obtain a perfect set of labels due to the variability between expert annotations. This paper presents a novel active learning (AL) framework for histopathology image analysis, named PathAL. To reduce the required number of expert annotations, PathAL selects two groups of unlabeled data in each training iteration: one "informative" sample that requires additional expert annotation, and one "confident predictive" sample that is automatically added to the training set using the model's pseudo-labels. To reduce the impact of the noisy-labeled samples in the training set, PathAL systematically identifies noisy samples and excludes them to improve the generalization of the model. Our model advances the existing AL method for medical image analysis in two ways. First, we present a selection strategy to improve classification performance with fewer manual annotations. Unlike traditional methods focusing only on finding the most uncertain samples with low prediction confidence, we discover a large number of high confidence samples from the unlabeled set and automatically add them for training with assigned pseudo-labels. Second, we design a method to distinguish between noisy samples and hard samples using a heuristic approach. We exclude the noisy samples while preserving the hard samples to improve model performance. Extensive experiments demonstrate that our proposed PathAL framework achieves promising results on a prostate cancer Gleason grading task, obtaining similar performance with 40% fewer annotations compared to the fully supervised learning scenario. An ablation study is provided to analyze the effectiveness of each component in PathAL, and a pathologist reader study is conducted to validate our proposed algorithm.

Prostate cancer multiparametric magnetic resonance imaging visibility is a tumor-intrinsic phenomena.

Multiparametric magnetic resonance imaging (mpMRI) is an emerging standard for diagnosing and prognosing prostate cancer, but ~ 20% of clinically significant tumors are invisible to mpMRI, as defined by the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score of one or two. To understand the biological underpinnings of tumor visibility on mpMRI, we examined the proteomes of forty clinically significant tumors (i.e., International Society of Urological Pathology (ISUP) Grade Group 2)-twenty mpMRI-visible and twenty mpMRI-invisible, with matched histologically normal prostate. Normal prostate tissue was indistinguishable between patients with visible and invisible tumors, and invisible tumors closely resembled the normal prostate. These data indicate that mpMRI-visibility arises when tumor evolution leads to large-magnitude proteomic divergences from histologically normal prostate.

Targeted Prostate Biopsy: Umbra, Penumbra, and Value of Perilesional Sampling.

BACKGROUND: Systematic prostate biopsies add to the cancer detection rate of targeted biopsies, but the explanation for that increased sensitivity is not yet clear. OBJECTIVE: To determine and quantify the utility of perilesional biopsies in the detection of clinically significant prostate cancer (csPCa). DESIGN, SETTING, AND PARTICIPANTS: Participants were 2048 men with magnetic resonance imaging (MRI) lesions (grades 3-5) who underwent targeted and systematic prostate biopsy via MRI/ultrasound fusion at University of California Los Angeles and Cornell between 2011 and 2019. The study is a retrospective examination of prospectively acquired data. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: All biopsy cores (30191), locations of which had been stored digitally in the image-fusion device, were analyzed for tissue pathology and relationship with MRI lesions. A validated Matlab script was used to determine the distance between MRI lesions and cores containing csPCa (3552 cores from 927 men). Significance of distance measurements was determined by multilevel, multivariable logistic regression to account for within patient-biopsy correlation and control for patient characteristics. RESULTS AND LIMITATIONS: Overall, 90% (95% confidence interval [CI] = 89-91) of csPCa cores (3206/3552) were located within a radius of 10 mm from the nearest lesion: 65% (95% CI = 63-67) within the region of interest (ROI) and 26% (95% CI = 24-27) outside the ROI but within the 10-mm "penumbra." The width of the penumbra or concentric band, which enclosed 90% of csPCa, was primarily related to MRI grade of lesion: grade 5, 5 mm; grade 4, 12 mm; grade 3, 16 mm. In 18% (95% CI = 15-20) of patients (166/927), csPCa was diagnosed only by sampling outside the MRI lesion, the yield decreasing with increasing distance. Limitations of MRI interpretation and fusion biopsy performance could affect the utility of these data in individual patients. CONCLUSIONS: Perilesional biopsies, that is, samples taken from a band of 10-mm radius outside MRI lesions (the penumbra), contain most cores of csPCa that are not present within the lesion. These data may help increase the performance characteristics of targeted prostate biopsy. PATIENT SUMMARY: We studied the locations of cancer within the prostate in men undergoing magnetic resonance imaging (MRI)-guided biopsy. We found that not all cancers are located within the MRI lesion, but 90% (95% confidence interval = 89-91) of the cancers arewithin 1 cm of the lesions. Biopsies taken from both within and around MRI lesions provide greater sensitivity for cancer detection than samples taken from the lesion only.

Head-to-Head Comparison of 68Ga-PSMA-11 PET/CT and mpMRI with a Histopathology Gold Standard in the Detection, Intraprostatic Localization, and Determination of Local Extension of Primary Prostate Cancer: Results from a Prospective Single-Center Imaging Trial.

The role of prostate-specific membrane antigen (PSMA)-targeted PET in comparison to multiparametric MRI (mpMRI) in the evaluation of intraprostatic cancer foci is not well defined. The aim of our study was to compare the diagnostic performance of 68Ga-PSMA-11 PET/CT (PSMA PET/CT), mpMRI, and PSMA PET/CT + mpMRI using 3 independent masked readers for each modality and with histopathology as the gold standard in the detection, intraprostatic localization, and determination of local extension of primary prostate cancer. Methods: Patients with intermediate- or high-risk prostate cancer who underwent PSMA PET/CT as part of a prospective trial (NCT03368547) and mpMRI before radical prostatectomy were included. Each imaging modality was interpreted by 3 independent readers who were unaware of the other modality result. A central majority rule was applied (2:1). Pathologic examination of whole-mount slices was used as the gold standard. Imaging scans and whole-mount slices were interpreted using the same standardized approach on a segment level and a lesion level. A "neighboring" approach was used to define imaging-pathology correlation for the detection of individual prostate cancer foci. Accuracy in determining the location, extraprostatic extension (EPE), and seminal vesicle invasion (SVI) of prostate cancer foci was assessed using receiver-operating-characteristic curve analysis. Interreader agreement was calculated using intraclass correlation coefficient analysis. Results: The final analysis included 74 patients (14 [19%] with intermediate risk and 60 [81%] with high risk). The cancer detection rate (lesion-based analysis) was 85%, 83%, and 87% for PSMA PET/CT, mpMRI, and PSMA PET/CT + mpMRI, respectively. The change in AUC was statistically significant between PSMA PET/CT + mpMRI and the 2 imaging modalities alone for delineation of tumor localization (segment-based analysis) (P < 0.001) but not between PSMA PET/CT and mpMRI (P = 0.093). mpMRI outperformed PSMA PET/CT in detecting EPE (P = 0.002) and SVI (P = 0.001). In the segment-level analysis, intraclass correlation coefficient analysis showed moderate reliability among PSMA PET/CT and mpMRI readers using a 5-point Likert scale (range, 0.53-0.64). In the evaluation of T staging, poor reliability was found among PSMA PET/CT readers and poor to moderate reliability was found for mpMRI readers. Conclusion: PSMA PET/CT and mpMRI have similar accuracy in the detection and intraprostatic localization of prostate cancer foci. mpMRI performs better in identifying EPE and SVI. For the T-staging evaluation of intermediate to high-risk prostate cancer, mpMRI should still be considered the imaging modality of reference. Whenever available, PSMA PET/MRI or the coregistration or fusion of PSMA PET/CT and mpMRI (PSMA PET/CT + mpMRI) should be used as it improves tumor extent delineation.

Papillary renal cell carcinoma: Review.

Kidney cancer is the 13th most common malignancy globally, and the incidence is rising. Papillary renal cell carcinoma is the second most common subtype, comprising 10-15% of renal cell carcinomas. Though the histologic features of this subtype were initially described in the 1990's, our understanding of the genetic and molecular characteristics of this disease have rapidly evolved over the past decade. In this review, we summarize the contemporary understanding of the clinical, morphologic, radiographic, and genetic characteristics of papillary renal cell carcinoma, as well as clinical considerations, current options for management, and prognosis.

Kidney allograft infarction associated with transplant renal artery stenosis in a COVID-19 kidney transplant recipient.

Kidney allograft infarction is rare, but an urgent condition that requires prompt intervention to avoid allograft loss. Renal artery thrombosis is the leading cause of infarction. Apart from traditional risk factors for thrombosis, emerging SARS-CoV-2 predisposes patients to thrombotic diseases both in arterial and venous vasculatures. We report a case of kidney transplant recipient with known transplant renal artery stenosis (TRAS) status post angioplasty with severe COVID-19, complicated by oliguric acute kidney injury requiring continuous renal replacement therapy (CRRT). She did not have a history of thromboembolic disease. The hospital course was complicated by new-onset atrial and ventricular fibrillation and cardiac arrest requiring multiple rounds of cardiopulmonary resuscitation. She had no signs of renal recovery, and an abdominal CT scan showed evidence of allograft infarcts. She underwent an allograft nephrectomy. Pathology revealed diffuse thrombotic microangiopathy involving glomeruli, arterioles, and arteries associated with diffuse cortical infarction with negative SARS-CoV-2 immunostain and in situ hybridization. This is the first case of kidney allograft infarct with a history of TRAS in a COVID-19 patient. Underlying TRAS and COVID-19-associated thrombosis in this patient are unique and likely play a key role in allograft infarction from arterial thrombosis. Recognizing risk factors and early therapy for allograft infarction may improve transplant outcomes.

Deep learning-based transformation of H&E stained tissues into special stains.

Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H&E) stain is most commonly used, special stains can provide additional contrast to different tissue components. Here, we demonstrate the utility of supervised learning-based computational stain transformation from H&E to special stains (Masson's Trichrome, periodic acid-Schiff and Jones silver stain) using kidney needle core biopsy tissue sections. Based on the evaluation by three renal pathologists, followed by adjudication by a fourth pathologist, we show that the generation of virtual special stains from existing H&E images improves the diagnosis of several non-neoplastic kidney diseases, sampled from 58 unique subjects (P = 0.0095). A second study found that the quality of the computationally generated special stains was statistically equivalent to those which were histochemically stained. This stain-to-stain transformation framework can improve preliminary diagnoses when additional special stains are needed, also providing significant savings in time and cost.

Serial Molecular Profiling of Low-grade Prostate Cancer to Assess Tumor Upgrading: A Longitudinal Cohort Study.

BACKGROUND: The potential for low-grade (grade group 1 [GG1]) prostate cancer (PCa) to progress to high-grade disease remains unclear. OBJECTIVE: To interrogate the molecular and biological features of low-grade PCa serially over time. DESIGN, SETTING, AND PARTICIPANTS: Nested longitudinal cohort study in an academic active surveillance (AS) program. Men were on AS for GG1 PCa from 2012 to 2017. INTERVENTION: Electronic tracking and resampling of PCa using magnetic resonance imaging/ultrasound fusion biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: ERG immunohistochemistry (IHC) and targeted DNA/RNA next-generation sequencing were performed on initial and repeat biopsies. Tumor clonality was assessed. Molecular data were compared between men who upgraded and those who did not upgrade to GG ≥ 2 cancer. RESULTS AND LIMITATIONS: Sixty-six men with median age 64 yr (interquartile range [IQR], 59-69) and prostate-specific antigen 4.9 ng/mL (IQR, 3.3-6.4) underwent repeat sampling of a tracked tumor focus (median interval, 11 mo; IQR, 6-13). IHC-based ERG fusion status was concordant at initial and repeat biopsies in 63 men (95% vs expected 50%, p < 0.001), and RNAseq-based fusion and isoform expression were concordant in nine of 13 (69%) ERG+ patients, supporting focal resampling. Among 15 men who upgraded with complete data at both time points, integrated DNA/RNAseq analysis provided evidence of shared clonality in at least five cases. Such cases could reflect initial undersampling, but also support the possibility of clonal temporal progression of low-grade cancer. Our assessment was limited by sample size and use of targeted sequencing. CONCLUSIONS: Repeat molecular assessment of low-grade tumors suggests that clonal progression could be one mechanism of upgrading. These data underscore the importance of serial tumor assessment in men pursuing AS of low-grade PCa. PATIENT SUMMARY: We performed targeted rebiopsy and molecular testing of low-grade tumors on active surveillance. Our findings highlight the importance of periodic biopsy as a component of monitoring for cancer upgrading during surveillance.

Regulation of telomere homeostasis and genomic stability in cancer by N 6-adenosine methylation (m6A).

The role of RNA methylation on N 6-adenosine (m6A) in cancer has been acknowledged, but the underlying mechanisms remain obscure. Here, we identified homeobox containing 1 (HMBOX1) as an authentic target mRNA of m6A machinery, which is highly methylated in malignant cells compared to the normal counterparts and subject to expedited degradation upon the modification. m6A-mediated down-regulation of HMBOX1 causes telomere dysfunction and inactivation of p53 signaling, which leads to chromosome abnormalities and aggressive phenotypes. CRISPR-based, m6A-editing tools further prove that the methyl groups on HMBOX1 per se contribute to the generation of altered cancer genome. In multiple types of human cancers, expression of the RNA methyltransferase METTL3 is negatively correlated with the telomere length but favorably with fractions of altered cancer genome, whereas HMBOX1 mRNA levels show the opposite patterns. Our work suggests that the cancer-driving genomic alterations may potentially be fixed by rectifying particular epitranscriptomic program.