Benign mimics of prostatic adenocarcinoma

Interactions and communications in the prostate tumour microenvironment: evolving towards effective cancer therapy

Prostate cancer is one of the most common malignancies in men. The tumour microenvironment (TME) has a critical role in the initiation, progression, and metastasis of prostate cancer. TME contains various cell types, including cancer-associated fibroblasts (CAFs), endothelial cells, immune cells such as macrophages, lymphocytes B and T, natural killer (NK) cells, and other proteins such as extracellular matrix (ECM) components. The interactions and communications between these cells within the TME are crucial for the growth and response of various solid tumours, such as prostate cancer to different anticancer modalities. In this review article, we exemplify the various mechanisms by which the TME influences prostate cancer progression. The roles of different cells, cytokines, chemokines, and growth factors in modulating the immune response and prostate tumour growth will be discussed. The impact of these cells and factors and other ECM components on tumour cell invasion and metastasis will also be discussed. We explain how these interactions in TME can affect the response of prostate cancer to therapy. We also highlight the importance of understanding these interactions to develop novel therapeutic approaches for prostate cancer.

Evaluation of A Computer-Aided Detection Software for Prostate Cancer Prediction: Excellent Diagnostic Accuracy Independent of Preanalytical Factors

Prostate cancer (PCa) is the most common noncutaneous cancer in men in the Western world. In addition to accurate diagnosis, Gleason grading and tumor volume estimates are critical for patient management. Computer-aided detection (CADe) software can be used to facilitate the diagnosis and improve the diagnostic accuracy and reporting consistency. However, preanalytical factors such as fixation and staining of prostate biopsy specimens and whole slide images (WSI) on scanners can vary significantly between pathology laboratories and may, therefore, impact the quality of WSI and utility of CADe algorithms. We evaluated the performance of a CADe software in predicting PCa on WSIs of prostate biopsy specimens and focused on whether there were any significant differences in image quality between WSIs obtained on different scanners and specimens from different histopathology laboratories. Thirty prostate biopsy specimens from 2 histopathology laboratories in the United States were included in this study. The hematoxylin and eosin slides of the biopsy specimens were scanned on 3 scanners, generating 90 WSIs. These WSIs were then analyzed using a CADe software (INIFY Prostate, Algorithm), which identified and annotated all areas suspicious for PCa and calculated the tumor volume (percentage area of the biopsy core involved). Study pathologists then reviewed the Algorithm's annotations and tumor volume calculation to confirm the diagnosis and identify benign glands that were misclassified as cancer (false positive) and cancer glands that were misclassified as benign (false negative). The CADe software worked equally well on WSIs from all 3 scanners and from both laboratories, with similar sensitivity and specificity. The overall sensitivity was 99.4%, and specificity was 97%. The percentage of suspicious cancer areas calculated by the Algorithm was similar for all 3 scanners. For WSIs with small foci of cancer (<1 mm), the Algorithm identified all cancer glands (sensitivity, 100%). Preanalytical factors had no significant impact on whole slide imaging and subsequent application of a CADe software. Prediction accuracy could potentially be further improved by processing biopsy specimens in a centralized histology laboratory and training the Algorithm on WSIs from the same laboratory in order to minimize variations in preanalytical factors and optimize the diagnostic performance of the Algorithm.

Artifactual Cystic Spaces in Prostatic Transurethral Resections and Related Specimens: A Potential Diagnostic Confounder

Aims. Histopathologic benign mimickers of prostate cancer have mostly focused on glandular mimics, with non-glandular mimics mainly limited to inflammatory conditions. While there is a paucity of literature recognizing small cystic (presumably artifactual) spaces in transurethral resection specimens, in some instances they can become florid enough to mimic vascular or epithelial neoplasms. Herein, we detailed histologic, immunophenotypic, and clinicopathologic findings in a large series of specimens showing prominent diagnostically confounding cystic spaces. Methods and Results. Sixty specimens were obtained (50 transurethral resections, 7 aquablations, 3 laser enucleations), from 17 different surgeons. Seven specimens had concurrent genitourinary pathology (4 prostatic adenocarcinoma, 1 solitary fibrous tumor, 1 prostatic atypia, 1 urothelial carcinoma in situ). The extent of cystic change among overall tissue examined ranged from 1 mm-8 mm (mean 3.4 mm), with luminal content of cystic spaces characterized as empty (72%), both empty and fluid-like (17%), and both empty and mucin-like (11%; mucin histochemical stain was negative on all specimens). Notable differences in degree of tissue cautery artifact or inflammation was not found. Immunohistochemistry performed on 30 specimens showed cystic spaces negative for S100, ERG, pankeratin, and CD45. Conclusion. Although artifactual in nature, in some instances small cystic spaces encountered in prostatic transurethral resections and more novel related procedures can become florid enough to warrant recognition as a potential diagnostic confounder of vascular or epithelial neoplasms.

An update on computational pathology tools for genitourinary pathology practice: A review paper from the Genitourinary Pathology Society (GUPS)

Machine learning has been leveraged for image analysis applications throughout a multitude of subspecialties. This position paper provides a perspective on the evolutionary trajectory of practical deep learning tools for genitourinary pathology through evaluating the most recent iterations of such algorithmic devices. Deep learning tools for genitourinary pathology demonstrate potential to enhance prognostic and predictive capacity for tumor assessment including grading, staging, and subtype identification, yet limitations in data availability, regulation, and standardization have stymied their implementation.

Deep UV Microscopy Identifies Prostatic Basal Cells: An Important Biomarker for Prostate Cancer Diagnostics

Objective and Impact Statement. Identifying benign mimics of prostatic adenocarcinoma remains a significant diagnostic challenge. In this work, we developed an approach based on label-free, high-resolution molecular imaging with multispectral deep ultraviolet (UV) microscopy which identifies important prostate tissue components, including basal cells. This work has significant implications towards improving the pathologic assessment and diagnosis of prostate cancer. Introduction. One of the most important indicators of prostate cancer is the absence of basal cells in glands and ducts. However, identifying basal cells using hematoxylin and eosin (H&E) stains, which is the standard of care, can be difficult in a subset of cases. In such situations, pathologists often resort to immunohistochemical (IHC) stains for a definitive diagnosis. However, IHC is expensive and time-consuming and requires more tissue sections which may not be available. In addition, IHC is subject to false-negative or false-positive stains which can potentially lead to an incorrect diagnosis. Methods. We leverage the rich molecular information of label-free multispectral deep UV microscopy to uniquely identify basal cells, luminal cells, and inflammatory cells. The method applies an unsupervised geometrical representation of principal component analysis to separate the various components of prostate tissue leading to multiple image representations of the molecular information. Results. Our results show that this method accurately and efficiently identifies benign and malignant glands with high fidelity, free of any staining procedures, based on the presence or absence of basal cells. We further use the molecular information to directly generate a high-resolution virtual IHC stain that clearly identifies basal cells, even in cases where IHC stains fail. Conclusion. Our simple, low-cost, and label-free deep UV method has the potential to improve and facilitate prostate cancer diagnosis by enabling robust identification of basal cells and other important prostate tissue components.

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices and machine-learning (ML) software fashioned to mitigate challenges, e.g., practitioner shortage while preparing clinicians for emerging interconnectivity of environments and diagnostic information in the era of big data. As computer vision shapes new constructs for the modern world and intertwines with clinical medicine, cultivating clarity of our new terrain through examining the trajectory and current scope of computational pathology and its pertinence to clinical practice is vital. Through review of numerous studies, we find developmental efforts for ML migrating from research to standardized clinical frameworks while overcoming obstacles that have formerly curtailed adoption of these tools, e.g., generalizability, data availability, and user-friendly accessibility. Groundbreaking validatory efforts have facilitated the clinical deployment of ML tools demonstrating the capacity to effectively aid in distinguishing tumor subtype and grade, classify early vs. advanced cancer stages, and assist in quality control and primary diagnosis applications. Case studies have demonstrated the benefits of streamlined, digitized workflows for practitioners alleviated by decreased burdens.

Mucinous metaplasia in Pten conditional knockout mice and mucin family genes as prognostic markers for prostate cancer

AIMS

This study evaluated the association of mucinous metaplasia (MM) with tumor cell proliferation, androgen receptor (AR) expression and invasiveness in Pten conditional knockout mice and the prognostic value of MM markers for patients with PCa.

MAIN METHODS

Prostatic lobes samples from genetic engineered mouse model Pten^f/f and Pb-Cre4/Pten^f/f were submitted for histopathological analysis and tissue expression of AR, the proliferation marker Ki67, alpha-smooth muscle actin, and laminin. RNAseq data of prostatic lobes samples were analyzed searching for MM gene expression patterns. We also investigated gene and protein expression related to MM in human PCa public databases.

KEY FINDINGS

All knockout animals analyzed showed at least one area of stroma-invading MM, which was absent in the control animals. The tumoral regions of MM showed a proliferative index 5 times higher than other tumoral areas and low expression of the AR (less than 20% of the cells were AR-positive). Disrupted basement membrane areas were observed in MM. The mouse and human PCa transcriptomes exhibited increased expression of the MM markers such as MUC1, MUC19, MUC4, MUC5AC, MUC5B, and TFF3. Gene expression profile was associated with castration-resistant prostate cancer (CRPC) and with a lower probability of freedom from biochemical recurrence.

SIGNIFICANCE

The expression of goblet cell genes, such as MUC1, MUC5AC, MUC5B, and TFF3 have significant prognostic value for PCa patients and represent another class of potential therapeutic targets.

Dealing with prostate cancer? Don’t let histiocytic lesions fool you!

Background

Prostate adenocarcinoma has well known benign mimickers. Histiocytic proliferations usually impose differential diagnosis with high-grade component of acinar adenocarcinoma (Gleason pattern 5).

Case presentation

We present herein three cases of histiocytic lesions of the prostate in which accurate recognition avoided inappropriate upgrading (malakoplakia associated with prostate adenocarcinoma, two cases) and false positive diagnosis at biopsy (xanthoma with signet ring morphology).

Conclusion

In needle biopsies, pathologists should have a low threshold to perform immunostains when considering a differential diagnosis between high-grade carcinoma and a histiocytic lesion. In prostatectomy specimens, abrupt transition to solid areas in low and intermediate grade tumors should raise concern to exclude malakoplakia. PAS and von Kossa stains are inexpensive and a valuable tool to highlight typical Michaelis–Gutmann bodies.

NKX3.1 expression in cervical 'adenoid basal cell carcinoma': another gynaecological lesion with prostatic differentiation?

Adenoid basal cell carcinoma (ABC) is considered a rare cervical neoplasm which when present in 'pure' form, uniquely amongst apparently malignant cervical tumours, has never been reported to metastasise or lead to fatal patient outcome. We recently encountered a case of ABC that was morphologically reminiscent of prostatic differentiation, more specifically basal cell hyperplasia of the prostate. Immunohistochemistry was strongly positive for the prostate related marker NKX3.1 in the glandular cells, but there was no expression of prostate specific antigen (PSA) or prostatic acid phosphatase (PAP). However, subsequent review of five additional cervical ABCs demonstrated focal PAP expression in two of four tested cases, and all were NKX3.1 positive. NKX3.1 expression was also demonstrated in the glandular epithelium of 10 additional gynaecological lesions considered to show prostatic differentiation including five cases of cervical ectopic prostatic tissue, three ovarian teratomas with prostatic differentiation, and two vaginal tubulosquamous polyps. We suggest that some lesions traditionally classified as ABC may in fact represent a variant of prostatic differentiation within the cervix, possibly analogous to basal cell hyperplasia of the prostate.

[Verumontanum mucosal hyperplasia as a differential diagnosis of a local recurrence following radical prostatectomy]

Verumontanum mucosal gland hyperplasia (VMGH) is a benign microacinar proliferative lesion, which occurs exclusively in the verumontanum and the posterior urethra and is one of the lesions that may be confused with a low-risk adenocarcinoma of the prostate gland.We present the case of a 72-year-old male patient who underwent radical prostatectomy due to an adenocarcinoma of the prostate gland (pT2c pN0 cM0 R0, Gleason Score: 3 + 3 = 6). Five years after the operation, we sonographically detected a 3x2 cm large tumour in the prostate bed. While our first assumption was a PSA-negative local recurrence following radical prostatectomy, a comprehensive histological examination along with the clinical evaluation led us to the diagnosis of a VMGH. VMGH is a less well-known differential diagnosis of PSA-negative local recurrence following radical prostatectomy, whose clinical manifestation should be presented.

Histopathologic False-positive Diagnoses of Prostate Cancer in the Age of Immunohistochemistry

There are few studies into the rate and causes of histopathologic false-positive diagnosis of prostate cancer. Only 2 of these, including a previous one from our group, incorporate survival data. In addition, in none of the previous studies had immunohistochemistry (IHC) been originally requested on any of the misdiagnosed cases. Diagnostic biopsies (n=1080) and transurethral resection of prostate specimens (n=314) from 1394 men with clinically localized prostate cancer diagnosed in the United Kingdom but treated conservatively between 1990 and 2003 were reviewed by a panel of 3 genitourinary pathologists. Thirty-five cases were excluded for being potentially incomplete. Of the remaining 1359, 30 (2.2%) were reassigned to a nonmalignant category (26 benign and 4 suspicious for malignancy). IHC had been originally performed on 7 of these. The reasons for the errors were recorded on each case: adenosis (19), partial atrophy (3), prostatic intraepithelial neoplasia (2), seminal vesicle epithelium (1), and hyperplasia (1). Follow-up of these men revealed only one prostate cancer-related death, possibly due to unsampled tumor. In conclusion, a relatively small number of prostate cancer mimics were responsible for a large proportion of the false-positive prostate cancer diagnoses and the use of IHC did not prevent the overcall of benign entities as cancer in approximately a quarter of these cases. Targeting these mimics at educational events and raising awareness of the pitfalls in the interpretation of IHC in prostate cancer diagnosis, emphasizing that glands within a suspicious focus should be treated as a whole rather than individually, may be beneficial in lowering the rate of false-positive diagnosis.