Faculty Bibliography

PURPOSE/UNASSIGNED:Stimulated Raman histology is an innovative technology that generates real-time, high-resolution microscopic images of unprocessed tissue, significantly reducing prostate biopsy interpretation time. This study aims to evaluate the ability for an artificial intelligence convolutional neural network to interpretate prostate biopsy histologic images created with stimulated Raman histology. MATERIALS AND METHODS/UNASSIGNED:Unprocessed, unlabeled prostate biopsies were prospectively imaged using a stimulated Raman histology microscope. Following stimulated Raman histology creation, the cores underwent standard pathological processing and interpretation by at least 2 genitourinary pathologists to establish a ground truth assessment. A network, trained on 303 prostate biopsies from 100 participants, was used to measure the accuracy, sensitivity, and specificity of detecting prostate cancer on stimulated Raman histology relative to conventional pathology. The performance of the artificial intelligence was evaluated on an independent 113-biopsy test set. RESULTS/UNASSIGNED:Prostate biopsy images obtained through stimulated Raman histology can be generated within a time frame of 2 to 2.75 minutes. The artificial intelligence system achieved a rapid classification of prostate biopsies with cancer, with a potential identification time of approximately 1 minute. The artificial intelligence demonstrated an impressive accuracy of 96.5% in detecting prostate cancer. Moreover, the artificial intelligence exhibited a sensitivity of 96.3% and a specificity of 96.6%. CONCLUSIONS/UNASSIGNED:Stimulated Raman histology generates microscopic images capable of accurately identifying prostate cancer in real time, without the need for sectioning or tissue processing. These images can be interpreted by artificial intelligence, providing physicians with near-real-time pathological feedback during the diagnosis or treatment of prostate cancer.

INTRODUCTION/BACKGROUND:Delay between targeted prostate biopsy (PB) and pathologic diagnosis can lead 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, unsectioned tissue. This technology holds potential to decrease the time for PB diagnosis from days to minutes. We evaluated the concordance of pathologist interpretation of PB SRH as compared with traditional hematoxylin and eosin (H&E) stained slides. METHODS:, to create SRH images. The cores were then processed as per normal pathologic protocols. Sixteen PB containing a mix of benign and malignant histology were used as an SRH training cohort for four genitourinary pathologists, who were then tested on a set of 32 PBs imaged by SRH and processed by traditional H&E. Sensitivity, specificity, accuracy, and concordance for prostate cancer (PCa) detection on SRH relative to H&E were assessed. RESULTS:The mean pathologist accuracy for the identification of any PCa on PB SRH was 95.7%. In identifying any PCa or ISUP grade group 2-5 PCa, a pathologist was independently able to achieve good and very good concordance (κ: 0.769 and 0.845, respectively; p < 0.001). After individual assessment was completed a pathology consensus conference was held for the interpretation of the PB SRH; after the consensus conference the pathologists' concordance in identifying any PCa was also very good (κ: 0.925, p < 0.001; sensitivity 95.6%; specificity 100%). CONCLUSION/CONCLUSIONS:SRH produces high-quality microscopic images that allow for accurate identification of PCa in real-time without need for sectioning or tissue processing. The pathologist performance improved through progressive training, showing that ultimately high accuracy can be obtained. Ongoing SRH evaluation in the diagnostic and treatment setting hold promise to reduce time to tissue diagnosis, while interpretation by convolutional neural network may further improve diagnostic characteristics and broaden use.

BACKGROUND:Dickkopf-related protein 1 (DKK1) is a Wingless-related integrate site (Wnt) signaling modulator that is upregulated in prostate cancers (PCa) with low androgen receptor expression. DKN-01, an IgG4 that neutralizes DKK1, delays PCa growth in pre-clinical DKK1-expressing models. These data provided the rationale for a clinical trial testing DKN-01 in patients with metastatic castration-resistant PCa (mCRPC). METHODS:(combination) for men with mCRPC who progressed on ≥1 AR signaling inhibitors. DKK1 status was determined by RNA in-situ expression. The primary endpoint of the phase 1 dose escalation cohorts was the determination of the recommended phase 2 dose (RP2D). The primary endpoint of the phase 2 expansion cohorts was objective response rate by iRECIST criteria in patients treated with the combination. RESULTS:18 pts were enrolled into the study-10 patients in the monotherapy cohorts and 8 patients in the combination cohorts. No DLTs were observed and DKN-01 600 mg was determined as the RP2D. A best overall response of stable disease occurred in two out of seven (29%) evaluable patients in the monotherapy cohort. In the combination cohort, five out of seven (71%) evaluable patients had a partial response (PR). A median rPFS of 5.7 months was observed in the combination cohort. In the combination cohort, the median tumoral DKK1 expression H-score was 0.75 and the rPFS observed was similar between patients with DKK1 H-score ≥1 versus H-score = 0. CONCLUSION/CONCLUSIONS:DKN-01 600 mg was well tolerated. DKK1 blockade has modest anti-tumor activity as a monotherapy for mCRPC. Anti-tumor activity was observed in the combination cohorts, but the response duration was limited. DKK1 expression in the majority of mCRPC is low and did not clearly correlate with anti-tumor activity of DKN-01 plus docetaxel.

Prostate cancer (PC) develops in a microenvironment where the stromal cells modulate adjacent tumor growth and progression. Here, we demonstrated elevated levels of monoamine oxidase B (MAOB), a mitochondrial enzyme that degrades biogenic and dietary monoamines, in human PC stroma, which was associated with poor clinical outcomes of PC patients. Knockdown or overexpression of MAOB in human prostate stromal fibroblasts indicated that MAOB promotes cocultured PC cell proliferation, migration, and invasion and co-inoculated prostate tumor growth in mice. Mechanistically, MAOB induces a reactive stroma with activated marker expression, increased extracellular matrix remodeling, and acquisition of a protumorigenic phenotype through enhanced production of reactive oxygen species. Moreover, MAOB transcriptionally activates CXCL12 through Twist1 synergizing with TGFβ1-dependent Smads in prostate stroma, which stimulates tumor-expressed CXCR4-Src/JNK signaling in a paracrine manner. Pharmacological inhibition of stromal MAOB restricted PC xenograft growth in mice. Collectively, these findings characterize the contribution of MAOB to PC and suggest MAOB as a potential stroma-based therapeutic target.

IMPORTANCE/OBJECTIVE:SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or organ dysfunction after the acute phase of infection, termed Post-Acute Sequelae of SARS-CoV-2 (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are poorly understood. The objectives of the Researching COVID to Enhance Recovery (RECOVER) tissue pathology study (RECOVER-Pathology) are to: (1) characterize prevalence and types of organ injury/disease and pathology occurring with PASC; (2) characterize the association of pathologic findings with clinical and other characteristics; (3) define the pathophysiology and mechanisms of PASC, and possible mediation via viral persistence; and (4) establish a post-mortem tissue biobank and post-mortem brain imaging biorepository. METHODS:RECOVER-Pathology is a cross-sectional study of decedents dying at least 15 days following initial SARS-CoV-2 infection. Eligible decedents must meet WHO criteria for suspected, probable, or confirmed infection and must be aged 18 years or more at the time of death. Enrollment occurs at 7 sites in four U.S. states and Washington, DC. Comprehensive autopsies are conducted according to a standardized protocol within 24 hours of death; tissue samples are sent to the PASC Biorepository for later analyses. Data on clinical history are collected from the medical records and/or next of kin. The primary study outcomes include an array of pathologic features organized by organ system. Causal inference methods will be employed to investigate associations between risk factors and pathologic outcomes. DISCUSSION/CONCLUSIONS:RECOVER-Pathology is the largest autopsy study addressing PASC among US adults. Results of this study are intended to elucidate mechanisms of organ injury and disease and enhance our understanding of the pathophysiology of PASC.

We present single-shot high-performance quantitative phase imaging with a physics-inspired plug-and-play denoiser for polarization differential interference contrast (PDIC) microscopy. The quantitative phase is recovered by the alternating direction method of multipliers (ADMM), balancing total variance regularization and a pre-trained dense residual U-net (DRUNet) denoiser. The custom DRUNet uses the Tanh activation function to guarantee the symmetry requirement for phase retrieval. In addition, we introduce an adaptive strategy accelerating convergence and explicitly incorporating measurement noise. After validating this deep denoiser-enhanced PDIC microscopy on simulated data and phantom experiments, we demonstrated high-performance phase imaging of histological tissue sections. The phase retrieval by the denoiser-enhanced PDIC microscopy achieves significantly higher quality and accuracy than the solution based on Fourier transforms or the iterative solution with total variance regularization alone.

OBJECTIVES/OBJECTIVE:To determine the prognostic significance of the maximum allowable percentage of Gleason pattern 4 (GP4) at prostate biopsy compared with adverse pathology observed at radical prostatectomy (RP) to expand active surveillance eligibility among a cohort with intermediate risk of prostate cancer. METHODS:A retrospective study of patients with grade group (GG) 1 or 2 prostate cancer on prostate biopsy with subsequent RP was performed at our institution. A Fisher exact test was used to understand the relationship among GP4 subgroups (0%, ≤5%, 6%-10%, and 11%-49%) assigned at biopsy and adverse pathologic findings at RP. Additional analyses comparing the GP4 ≤5% cohort's prebiopsy prostate-specific antigen (PSA) level and GP4 length with adverse pathology at RP were also performed. RESULTS:No statistically significant difference in adverse pathology at RP was observed between the active surveillance-eligible control (GP4 0%) and the GP4 ≤5% subgroup. In total, 68.9% of the GP4 ≤5% cohort showed favorable pathologic outcomes. A separate analysis of the GP4 ≤5% subgroup revealed that neither prebiopsy serum PSA levels nor GP4 length showed statistical correlation with adverse pathology at RP. CONCLUSIONS:Active surveillance may be a reasonable option for management of patients in the GP4 ≤5% group until long-term follow-up data become available.

BACKGROUND:For the representative problem of prostate cancer grading, we sought to simultaneously model both the continuous nature of the case spectrum and the decision thresholds of individual pathologists, allowing quantitative comparison of how they handle cases at the borderline between diagnostic categories. METHODS:Experts and pathology residents each rated a standardized set of prostate cancer histopathological images on the International Society of Urological Pathologists (ISUP) scale used in clinical practice. They diagnosed 50 histologic cases with a range of malignancy, including intermediate cases in which clear distinction was difficult. We report a statistical model showing the degree to which each individual participant can separate the cases along the latent decision spectrum. RESULTS:The slides were rated by 36 physicians in total: 23 ISUP pathologists and 13 residents. As anticipated, the cases showed a full continuous range of diagnostic severity. Cases ranged along a logit scale consistent with the consensus rating (Consensus ISUP 1: mean -0.93 [95% confidence interval {CI} -1.10 to -0.78], ISUP 2: -0.19 logits [-0.27 to -0.12]; ISUP 3: 0.56 logits [0.06-1.06]; ISUP 4 1.24 logits [1.10-1.38]; ISUP 5: 1.92 [1.80-2.04]). The best raters were able to meaningfully discriminate between all 5 ISUP categories, showing intercategory thresholds that were quantifiably precise and meaningful. CONCLUSIONS:We present a method that allows simultaneous quantification of both the confusability of a particular case and the skill with which raters can distinguish the cases. IMPLICATIONS/CONCLUSIONS:The technique generalizes beyond the current example to other clinical situations in which a diagnostician must impose an ordinal rating on a biological spectrum. HIGHLIGHTS/CONCLUSIONS:

BACKGROUND:Evading immune surveillance is a hallmark for the development of multiple cancer types. Whether immune evasion contributes to the pathogenesis of high-grade prostate cancer (HGPCa) remains an area of active inquiry. METHODS:Through single-cell RNA sequencing and multicolor flow cytometry of freshly isolated prostatectomy specimens and matched peripheral blood, we aimed to characterize the tumor immune microenvironment (TME) of localized prostate cancer (PCa), including HGPCa and low-grade prostate cancer (LGPCa). RESULTS: TILs. The PCa TME was infiltrated by macrophages but these did not clearly cluster by M1 and M2 markers. CONCLUSIONS:T cell exhaustion in localized PCa, a finding enriched in HGPCa relative to LGPCa. These studies suggest a possible link between the clinical-pathologic risk of PCa and the associated TME. Our results have implications for our understanding of the immunologic mechanisms of PCa pathogenesis and the implementation of immunotherapy for localized PCa.