Benign Tissue Research Articles

Dual hyperpolarized [1-13C]pyruvate and [13C]urea magnetic resonance imaging of prostate cancer

BackgroundAlthough multiparametric (mp) 1H magnetic resonance imaging (MRI) is increasingly used to detect and localize prostate cancer (PC), its correlation with tumor grade is limited. Hyperpolarized (HP) carbon-13 (13C) MR is an emerging imaging technique, which can be used to interrogate key biologic processes through in vivo detection of various HP probes. A distinct attribute of HP 13C MRI is the ability to detect multiple HP probes within a single acquisition. Here we report on the first simultaneous dual HP [1-13C]pyruvate and [13C]urea MRI with correlations to histopathologic findings in a patient with localized PC scheduled for radical prostatectomy. Material and methodsPaired HP 13C and standard mp 1H MRI were performed in a patient with biopsy-proven Gleason score 4 + 3 = 7 adenocarcinoma of the prostate scheduled for radical prostatectomy through a first-in-human pilot study of dual-agent HP MRI (NCT02526368). HP 13C MRI was performed using a clinical 3T scanner with 13C transmit-and-receive capabilities. Dynamic series of HP 13C pyruvate, lactate and urea imaging were acquired following intravenous (IV) injection of co-hyperpolarized [13C]urea (25 mM) and [1–13C]pyruvate (125 mM). The [1-13C]pyruvate-to-[1-13C]lactate conversion rate (kPL) was calculated using an inputless two-site exchange model; AUCurea was the [13C]urea signal summed over time. Following radical prostatectomy, whole-mount prostate histopathological slides were prepared and reviewed by an experienced genitourinary pathologist. ResultsFollowing informed consent, the patient underwent paired mp 1H MRI and dual-agent HP MRI. mp 1H MRI revealed a 1.2 cm lesion in the left apical posterior zone. Dual-agent HP MRI identified a focus of increased [1-13C]pyruvate-to-[1-13C]lactate conversion rate (kPL) extending from the left apical posterior peripheral zone to the right gland. A corresponding area of abnormal tissue perfusion (AUCurea) was seen in the left gland. Metabolism-perfusion mismatch (with several foci of increased kPL/AUCurea) was observed throughout the tumor. Tumor extension to the right midgland was confirmed at the time of radical prostatectomy and staining for lactate dehydrogenase-A was increased throughout the tumor relative to surrounding benign prostatic tissue. ConclusionThis first-in-human radiopathologic study demonstrates the feasibility of dual-agent HP MRI in PC patients. Simultaneous assessment of tumor metabolism and perfusion was able to detect occult disease as well as to show a significant mismatch between intra-tumoral metabolism and tissue perfusion in high-grade PC. Prospective validation of these findings is warranted.

Human intermediate prostate cancer stem cells contribute to the initiation and development of prostate adenocarcinoma

BackgroundIntermediate cells are present in the early stages of human prostate development and adenocarcinoma. While primary cells isolated from benign human prostate tissues or tumors exhibit an intermediate phenotype in vitro, they cannot form tumors in vivo unless genetically modified. It is unclear about the stem cell properties and tumorigenicity of intermediate cells.MethodsWe developed a customized medium to culture primary human intermediate prostate cells, which were transplanted into male immunodeficient NCG mice to examine tumorigenicity in vivo. We treated the cells with different concentrations of dihydrotestosterone (DHT) and enzalutamide in vitro and surgically castrated the mice after cell transplantation in vivo. Immunostaining, qRT-PCR, RNA sequencing, and western blotting were performed to characterize the cells in tissues and 2D and 3D cultures.ResultsWe found intermediate cells expressing AR+PSA+CK8+CK5+ in the luminal compartment of human prostate adenocarcinoma by immunostaining. We cultured the primary intermediate cells in vitro, which expressed luminal (AR+PSA+CK8+CK18+), basal (CK5+P63+), intermediate (IVL+), and stem cell (CK4+CK13+PSCA+SOX2+) markers. These cells resisted castration in vitro by upregulating the expression of AR, PSA, and proliferation markers KI67 and PCNA. The intermediate cells had high tumorigenicity in vivo, forming tumors in immunodeficient NCG mice in a month without any genetic modification or co-transplantation with embryonic urogenital sinus mesenchyme (UGSM) cells. We named these cells human castration-resistant intermediate prostate cancer stem cells or CriPCSCs and defined the xenograft model as patient primary cell-derived xenograft (PrDX). Human CriPCSCs resisted castration in vitro and in vivo by upregulating AR expression. Furthermore, human CriPCSCs differentiated into amplifying adenocarcinoma cells of luminal phenotype in PrDX tumors in vivo, which can dedifferentiate into CriPCSCs in vitro.ConclusionsOur study identified and established methods for culturing human CriPCSCs, which had high tumorigenicity in vivo without any genetic modification or UGSM co-transplantation. Human CriPCSCs differentiated into amplifying adenocarcinoma cells of luminal phenotype in the fast-growing tumors in vivo, which hold the potential to dedifferentiate into intermediate stem cells. These cells resisted castration by upregulating AR expression. The human CriPCSC and PrDX methods hold significant potential for advancing prostate cancer research and precision medicine.

The impact of benign tissue within cancerous regions in the prostate: Characterizing sparse and dense prostate cancers on whole-mount histopathology and on multiparametric MRI

PurposeTo establish the incidence, size, zonal location and Gleason Score(GS)/Gleason Grade Group(GG) of sparse versus dense prostate cancer (PCa) lesions and to identify the imaging characteristics of sparse versus dense cancers on multiparametric MRI (mpMRI). MethodsSeventy-six men with untreated PCa were scanned prior to prostatectomy with endorectal-coil 3 T MRI including T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced MRI. Cancerous regions were outlined and graded on the whole-mount, processed specimens, with tissue compositions estimated. Regions with cancer comprising <50 % and ≥ 50 % of the tissue were considered sparse and dense respectively. Regions of interest (ROI) were manually drawn on T2-weighted MRI. Within each patient, area-weighted ROI averages were calculated for each imaging measure for each tissue type, GS/GG, and sparse/dense composition. ResultsA large number of cancer regions were identified on histopathology (n = 1193: 939 (peripheral zone (PZ)) and 254 (transition zone (TZ))). Thirty-seven percent of these lesions were sparse. Sparse lesions were primarily low-grade with the majority of PZ and 100 % of TZ sparse lesions ≤GS3 + 3/GG1. Dense lesions were significantly larger than sparse lesions in both PZ and TZ, p < 0.0001. On imaging, 246/45 PZ and 109/8 TZ dense/sparse 2D cancerous ROIs were drawn. Sparse GS3 + 3 and sparse ≥GS3 + 4 cancers did not have significantly different MRI intensities to dense GS3 + 3 cancers, while sparse GS3 + 3/GG1 cancers differed from benign, p < 0.05. ConclusionHistopathologically identified prostate cancer lesions were sparse in 37 % of cases. Sparse cancers were entirely low grade in TZ and predominantly low-grade in PZ and generally small, thus likely posing lower risk for spread and progression than dense lesions. Sparse lesions were not distinguishable from dense lesions on mpMRI, but could be distinguished from benign tissues.

Intracardiac Ectopic Thyroid Tissue: A Case Report

We present the case of a 36-year-old female who visited the OPD of a local hospital in Lahore, Pakistan, with history of chest pain, shortness of breath and palpitations. Echocardiogram and transesophageal echocardiography revealed right ventricular outflow tract mass, dilated coronary sinus and atrial septal defect. Surgery was advised, and successful excision of the mass was done and the specimen later sent to Chughtai Institute of Pathology for histopathological evaluation and diagnosis. The results revealed benign thyroid tissue with no evidence of malignancy. The patient was symptom-free on follow up after 6 months.

Giant cell Fibroma of Lip: A case report

This case report describes a rare presentation of a giant cell fibroma (GCF) on the labial mucosa of a 24-year-old female. GCF is a benign fibrous connective tissue neoplasm, typically occurring on the gingiva and tongue. The patient presented with a small, pedunculated nodule on the lower lip. A clinical diagnosis of irritational fibroma was made, and excisional biopsy confirmed the presence of GCF based on histopathological examination, revealing characteristic stellate-shaped giant fibroblasts. The lesion was successfully excised with no recurrence at the one-year follow-up. This case highlights the importance of considering GCF in the differential diagnosis of benign fibrous lesions, even in atypical locations like the labial mucosa. Increased awareness and reporting of such cases can aid in better understanding the etiology and pathogenesis of GCF, ensuring accurate diagnosis and effective management.

Detection of malignant breast tissue using SAR observation with microwave imaging and convolutional neural network

The research paper introduces a deep learning approach for distinguishing between benign and malignant breast tissues using Ultra Wide Band (UWB) microwave imaging. A multi-resonant monopole microstrip patch antenna was crafted and placed on a female breast phantom model containing a tumor. The phantom’s dielectric properties were adjusted to mimic those of benign and malignant tissues. The Specific Absorption Rate (SAR) was analyzed by rotating the antenna at various angles throughout the phantom’s trajectory. Images capturing the SAR distribution over the breast phantom at different antenna resonances were obtained. The popular Convolutional Neural Network (CNN) based AlexNet model was employed for autonomous feature learning from SAR images. To address the challenge of overfitting with a limited dataset, the study utilized image augmentation and transfer learning methods. The proposed model achieved an impressive 98.59% accuracy in classifying benign and malignant breast phantom images, surpassing the performance of three other CNN models—VggNet16, GoogleNet, and ResNet. Notably, this microwave imaging system based on SAR images detected tumors as small as 1 mm with an accuracy of 97.08% outperforming existing malignancy screening techniques.

INTRAMUSCULAR MYXOMA OF THE VASTUS LATERALIS MUSCLE: A CASE REPORT

Introduction: Intramuscular myxoma is a rare benign soft tissue tumor which usually affects large muscle groups in patients aged between forty and sixty years. It is composed of hypocellular myxoid tissue. Incidence of intramuscular myxoma varies from 0.1 to 0.3 per 100,000 individuals. The aim of this study: to present the process of diagnosis and treatment of a patient with the rare soft tissue tumor. Case description: A 41-year-old female came to the Orthopedic Clinic with a 2-year history of a lump on the lateral side of her right thigh. Noticeable growth of the lesion and pain complaints started after skiing injury 7 months before the examination. The magnetic resonance imaging test demonstrated encapsulated intramuscular mass which measured 6 x 2 x 2 cm located in Vastus lateralis muscle. Due to an increasing pain and a significant size of the lesion, the patient was qualified for an excisional biopsy. After an excision, the lesion was found on histopathology to be an intramuscular myxoma. The patient did not complain of any neurological deficits, walking disorders. The follow-up imaging examination 3 months after surgery show no recurrence and the further observation was planned.

A comparative study of histotripsy parameters for the treatment of fibrotic ex-vivo human benign prostatic hyperplasia tissue

Histotripsy is a noninvasive focused ultrasound therapy that mechanically fractionates tissue to create well-defined lesions. In a previous clinical pilot trial to treat benign prostatic hyperplasia (BPH), histotripsy did not result in consistent objective improvements in symptoms, potentially because of the fibrotic and mechanically tough nature of this tissue. In this study, we aimed to identify the dosage required to homogenize BPH tissue by different histotripsy modalities, including boiling histotripsy (BH) and cavitation histotripsy (CH). A method for histotripsy lesion quantification via entropy (HLQE) analysis was developed and utilized to quantify lesion area of the respective treatments. These data were correlated to changes in mechanical stiffness measured by ultrasound shear-wave elastography before and after treatment with each parameter set and dose. Time points corresponding to histologically observed complete lesions were qualitatively evaluated and quantitatively measured. For the BH treatment, complete lesions occurred with > = 30 s treatment time, with a corresponding maximum reduction in stiffness of −90.9 ± 7.2(s.d.)%. High pulse repetition frequency (PRF) CH achieved a similar reduction to that of BH at 288 s (−91.6 ± 6.0(s.d.)%), and low-PRF CH achieved a (−82.1 ± 5.1(s.d.)%) reduction in stiffness at dose > = 144 s. Receiver operating characteristic curve analysis showed that a > ~ 75% reduction in stiffness positively correlated with complete lesions observed histologically, and can provide an alternative metric to track treatment progression.

Revolutionizing Colon Histopathology Glandular Segmentation Using an Ensemble Network With Watershed Algorithm

ABSTRACTColorectal adenocarcinoma, the most prevalent form of colon cancer, originates in the glandular structures of the intestines, presenting histopathological abnormalities in affected tissues. Accurate gland segmentation is crucial for identifying these potentially fatal abnormalities. While recent methodologies have shown success in segmenting glands in benign tissues, their efficacy diminishes when applied to malignant tissue segmentation. This study aims to develop a robust learning algorithm using a convolutional neural network (CNN) to segment glandular structures in colon histology images. The methodology employs a CNN based on the U‐Net architecture, augmented by a weighted ensemble network that integrates DenseNet 169, Inception V3, and Efficientnet B3 as backbone models. Additionally, the segmented gland boundaries are refined using the watershed algorithm. Evaluation on the Warwick‐QU dataset demonstrates promising results for the ensemble model, by achieving an F1 score of 0.928 and 0.913, object dice coefficient of 0.923 and 0.911, and Hausdorff distances of 38.97 and 33.76 on test sets A and B, respectively. These results are compared with outcomes from the GlaS challenge (MICCAI 2015) and existing research findings. Furthermore, our model is validated with a publicly available dataset named LC25000, and visual inspection reveals promising results, further validating the efficacy of our approach. The proposed ensemble methodology underscores the advantages of amalgamating diverse models, highlighting the potential of ensemble techniques to enhance segmentation tasks beyond individual model capabilities.

Overcoming challenges in conducting early phase breast cancer prevention trials: Bazedoxifene and conjugated estrogens vs waitlist control

BackgroundThe combination of bazedoxifene 20 mg (BZA) and conjugated estrogens 0.45 mg (CE) marketed as Duavee® is approved for vasomotor symptom relief and osteoporosis prevention. Our pilot study suggested it had potential breast cancer risk reduction, and we proposed a multisite Phase IIB primary prevention trial assessing change in breast imaging and tissue risk biomarkers. By the time funding was acquired in February 2021, Duavee® was unavailable with an uncertain return date. A redesign was needed to salvage the study. MethodsThe basic trial design was minimally altered. Women age 45–64 at elevated risk for breast cancer with vasomotor symptoms and no menses for at least 2 months have mammography, phlebotomy, and benign breast tissue sampling before and after 6 months of intervention. However, instead of Duavee® (single pill) vs placebo, women are randomized to 6 months of BZA + CE vs Waitlist. Those initially randomized to Waitlist can receive BZA + CE after 6 months. The primary endpoint is between arm difference in change in a fully automated measure of mammographic density with blood and tissue-based secondary endpoints. OutcomesAccrual initiation was delayed due to contractual difficulties surrounding BZA importation during COVID-19 and deploying a fully automated method (Volpara®) to assess the primary endpoint. To accommodate this delay, a mid-grant no cost extension along with amended eligibility requirements were employed. 61/120 participants needed were entered in the initial 27 months of accrual and 37 months of funding. Despite a late start, accrual is likely to be completed within the funding period.

Establishing and Characterizing the Molecular Profiles, Cellular Features, and Clinical Utility of a Patient-Derived Xenograft Model Using Benign Prostatic Tissues

Benign prostatic hyperplasia (BPH) is a common condition marked by the enlargement of the prostate gland, which often leads to significant urinary symptoms and a decreased quality of life. The development of clinically relevant animal models is crucial for understanding the pathophysiology of BPH and improving treatment options. This study aims to establish a patient-derived xenograft (PDX) model using benign prostatic tissues to explore the molecular and cellular mechanisms of BPH. PDXs were generated by implanting fresh BPH (transition zone) and paired normal (peripheral zone) prostate tissue from 8 patients under the renal capsule of immunodeficient male mice. Tissue weight, architecture, cellular proliferation, apoptosis, prostate-specific marker expression, and molecular profiles of PDXs were assessed after 1 week and 1, 2, or 3 months of implantation by immunohistochemistry, enzyme-linked immunosorbent assay, transcriptomics, and proteomics. Responses to finasteride, a standard-of-care therapy, were evaluated. PDXs maintained histologic and molecular characteristics of the parental human tissues. BPH, but not normal PDXs, demonstrated significant increases in weight and cellular proliferation, particularly at 1 month. Molecular profiling revealed specific gene and protein expression patterns correlating with BPH pathophysiology. Specifically, an increased immune and stress response was observed at 1 week, followed by increased expression of proliferation markers and BPH-specific stromal signaling molecules, such as BMP5 and CXCL13, at 1 month. Graft stabilization to preimplant characteristics was apparent between 2 and 3 months. Treatment with finasteride reduced proliferation, increased apoptosis, and induced morphologic changes consistent with therapeutic responses observed in human BPH. Our PDX model recapitulates the morphologic, histologic, and molecular features of human BPH, offering a significant advancement in modeling the complex interactions of cell types in BPH microenvironments. These PDXs respond to therapeutic intervention as expected, providing a valuable tool for preclinical testing of new therapeutics that will improve the well-being of BPH patients.

Tumor-agnostic cancer therapy using antibodies targeting oncofetal chondroitin sulfate

Molecular similarities between embryonic and malignant cells can be exploited to target tumors through specific signatures absent in healthy adult tissues. One such embryonic signature tumors express is oncofetal chondroitin sulfate (ofCS), which supports disease progression and dissemination in cancer. Here, we report the identification and characterization of phage display-derived antibody fragments recognizing two distinct ofCS epitopes. These antibody fragments show binding affinity to ofCS in the low nanomolar range across a broad selection of solid tumor types in vitro and in vivo with minimal binding to normal, inflamed, or benign tumor tissues. Anti-ofCS antibody drug conjugates and bispecific immune cell engagers based on these targeting moieties disrupt tumor progression in animal models of human and murine cancers. Thus, anti-ofCS antibody fragments hold promise for the development of broadly effective therapeutic and diagnostic applications targeting human malignancies.

Epigenetic profiling of prostate cancer reveals potential prognostic signatures

PurposeWhile epigenetic profiling discovered biomarkers in several tumor entities, its application in prostate cancer is still limited. We explored DNA methylation-based deconvolution of benign and malignant prostate tissue for biomarker discovery and the potential of radiomics as a non-invasive surrogate.MethodsWe retrospectively included 30 patients (63 [58–79] years) with prostate cancer (PCa) who had a multiparametric MRI of the prostate before radical prostatectomy between 2014 and 2019. The control group comprised four patients with benign prostate tissue adjacent to the PCa lesions and four patients with benign prostatic hyperplasia. Tissue punches of all lesions were obtained. DNA methylation analysis and reference-free in silico deconvolution were conducted to retrieve Latent Methylation Components (LCMs). LCM-based clustering was analyzed for cellular composition and correlated with clinical disease parameters. Additionally, PCa and adjacent benign lesions were analyzed using radiomics to predict the epigenetic signatures non-invasively.ResultsLCMs identified two clusters with potential prognostic impact. Cluster one was associated with malignant prostate tissue (p < 0.001) and reduced immune-cell-related signatures (p = 0.004) of CD19 and CD4 cells. Cluster one comprised exclusively malignant prostate tissue enriched for significant prostate cancer and advanced tumor stages (p < 0.03 for both). No radiomics model could non-invasively predict the epigenetic clusters.ConclusionEpigenetic clusters were associated with prognostically and clinically relevant metrics in prostate cancer. Further, immune cell-related signatures differed significantly between prognostically favorable and unfavorable clusters. Further research is necessary to explore potential diagnostic and therapeutic implications.

Microwave dielectric properties of normal, fibroelastotic, and malignant human lung tissue

Technological development of microwave treatment and detection techniques for lung cancer requires accurate and comprehensive knowledge of the microwave dielectric properties of human lung tissue. We characterize the dielectric properties of room temperature human lung tissue from 0.5 to 10 GHz for three lung tissue groups: normal, fibroelastotic, and malignant. We fit a two-pole Debye model to the measured frequency-dependent complex permittivity and calculate the median Debye parameters for the three groups. We find that malignant lung tissue is approximately 10% higher in relative permittivity and conductivity compared to normal lung tissue; this trend matches previously reported normal versus malignant data for other biological tissues. There is little contrast between benign lung tissue with fibroelastosis and malignant lung tissue. We extrapolate our data from room temperature to 37 °C using a temperature-dependence model for animal lung tissue and use the Maxwell-Garnett dielectric mixing model to predict the dielectric properties of inflation-dynamic human lung tissue; both approximations correspond with previously reported dielectric data of bovine and porcine lung tissue.

The Overexpressed MicroRNAs miRs-182, 155, 493, 454, and U6 snRNA and Underexpressed let-7c, miR-328, and miR-451a as Potential Biomarkers in Invasive Breast Cancer and Their Clinicopathological Significance.

Breast cancer comprises the leading cause of cancer-related death in women. MicroRNAs (miRNAs) have emerged as important factors with concern to carcinogenesis and have potential for use as biomarkers. This study provides a comprehensive evaluation of the microRNA expression in invasive breast carcinoma of no special type tissues compared with benign tissues via large-scale screening and the candidate-specific validation of 15 miRNAs and U6 snRNA applying qPCR and the examination of clinicopathological data. Of the six downregulated miRNAs, let-7c was identified as the most promising miRNA biomarker and its lower expression was linked with Ki-67 positivity, luminal B versus luminal A samples, multifocality, lymph node metastasis, and inferior PFS. Of the 9 upregulated sncRNAs, the data on U6 snRNA, miR-493 and miR-454 highlighted their potential oncogenic functions. An elevated U6 snRNA expression was associated with the tumor grade, Ki-67 positivity, luminal B versus A samples, lymph node metastasis, and worsened PFS (and OS) outcomes. An elevated miR-454 expression was detected in higher grades, Ki-67 positive and luminal B versus A samples. Higher miR-493 levels were noted for the tumor stage (and grade) and worse patient outcomes (PFS, OS). The data also suggested that miR-451a and miR-328 may have tumor suppressor roles, and miR-182 and miR-200c pro-oncogenic functions, while the remaining sncRNAs did not evince any significant associations. We showed particular microRNAs and U6 snRNA as differentially expressed between tumors and benign tissues and associated with clinicopathological parameters, thus potentially corresponding with important roles in breast carcinogenesis. Their importance should be further investigated and evaluated in follow-up studies to reveal their potential in clinical practice.

Visible-short wavelength near infrared hyperspectral imaging coupled with multivariate curve resolution-alternating least squares for diagnosis of breast cancer

This study investigates the application of visible-short wavelength near-infrared hyperspectral imaging (Vis-SWNIR HSI) in the wavelength range of 400–950 nm and advanced chemometric techniques for diagnosing breast cancer (BC). The research involved 56 ex-vivo samples encompassing both cancerous and non-cancerous breast tissue from females. First, HSI images were analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to exploit pure spatial and spectral profiles of active components. Then, the MCR-ALS resolved spatial profiles were arranged in a new data matrix for exploration and discrimination between benign and cancerous tissue samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA classification accuracy of 82.1 % showed the potential of HSI and chemometrics for non-invasive detection of BC. Additionally, the resolved spectral profiles by MCR-ALS can be used to track the changes in the breast tissue during cancer and treatment. It is concluded that the proposed strategy in this work can effectively differentiate between cancerous and non-cancerous breast tissue and pave the way for further studies and potential clinical implementation of this innovative approach, offering a promising avenue for improving early detection and treatment outcomes in BC patients.

Automated system utilizing non-invasive technique mammograms for breast cancer detection

In order to increase the likelihood of obtaining treatment and achieving a complete recovery, early illness identification and diagnosis are crucial. Artificial intelligence is helpful with this process by allowing us to rapidly start the necessary protocol for treatment in the early stages of disease development. Artificial intelligence is a major contributor to the improvement of medical treatment for patients. In order to prevent and foresee this problem on the individual, family, and generational levels, Monitoring the patient's therapy and recovery is crucial. This study's objective is to outline a non-invasive method for using mammograms to detect breast abnormalities, classify breast disorders, and identify cancerous or benign tumor tissue in the breast. We used classification models on a dataset that has been pre-processed so that the number of samples is balanced, unlike previous work on the same dataset. Identifying cancerous or benign breast tissue requires the use of supervised learning techniques and algorithms, such as random forest (RF) and decision tree (DT) classifiers, to examine up to thirty features, such as breast size, mass, diameter, circumference, and the nature of the tumor (solid or cystic). To ascertain if the tissue is malignant or benign, the examination's findings are employed. These features are mostly what determines how effectively anything may be categorized. The DT classifier was able to get a score of 95.32%, while the RF satisfied a far higher 98.83 percent.

Alterations in Tumor Aggression Following Androgen Receptor Signaling Restoration in Canine Prostate Cancer Cell Lines.

In prostate cancer (PCa), androgens upregulate tumorigenesis, whereas in benign tissue, the revival of androgen receptor (AR) signaling suppresses aggressive behaviors, suggesting therapeutic potential. Dogs, natural PCa models, often lack AR in PCa. We restored AR in dog PCa to investigate resultant characteristics. Three AR-null canine PCa lines (1508, Leo, 1258) were transfected with canine wild-type AR and treated with dihydrotestosterone (DHT). In 1508, AR restoration decreased clonogenicity (p = 0.03), viability (p = 0.004), migration (p = 0.03), invasion (p = 0.01), and increased expression of the tumor suppressor NKX3.1, an AR transcriptional target (p = 0.001). In Leo, AR decreased clonogenicity (p = 0.04) and the expression of another AR transcriptional target FOLH1 (p < 0.001) and increased the expression of NKX3.1 (p = 0.01). In 1258, AR increased migration (p = 0.006) and invasion (p = 0.03). Epithelial-mesenchymal transition (EMT) marker (Vimentin, N-cadherin, SNAIL1) expression increased with AR restoration in Leo and 1258 but not 1508; siRNA vimentin knockdown abrogated AR-induced 1258 migration only. Overall, 1508 showed AR-mediated tumor suppression; AR affected proliferation in Leo but not migration or invasion; and EMT and AR regulated migration and invasion in 1258 but not proliferation. This study highlights the heterogeneous nature of PCa in dogs and cell line-specific effects of AR abrogation on aggressive behaviors.

Prostate Type Malignancies Arising in Ovarian Teratomas - A Report of Two Patients.

The identification of benign prostatic tissue within ovarian and testicular mature teratomas is an unusual occurrence. While a few documented reports exist in the literature regarding the emergence of benign prostatic tissue within teratomas, the occurrence of prostatic-type adenocarcinoma in a mature ovarian teratoma is an exceptionally rare phenomenon. To date, only two prior reports have documented such instances, and no tumors have been previously reported with prostate-type tissue with morphologically two different malignancies. We outline our experience with two tumors involving prostatic-type carcinoma, both arising in ovarian mature teratomas. Microscopic examination of the first tumor revealed small areas of infiltrative atypical glandular proliferation within the mature teratoma. In the second tumor, prostate-type tissue exhibited a low-grade basal cell carcinoma. Additionally, adjacent minute foci of adenocarcinoma of the prostate (Gleason score 3 + 4 = 7, <5% pattern 4) were identified. Goblet cell adenocarcinoma of appendiceal type was also evident in the latter tumor. In both tumors, immunostains (NKX3.1, PSA) were performed to establish the prostatic origin of these atypical glands and PIN4 was performed to document the absence of basal cell in the atypical glands. On clinical follow-up, both patients have no signs of recurrence at 14 and 11 months after the surgery. Further reports on such neoplasms would contribute to a better understanding of the prognosis and management of such occurrences.

Detection of differentially methylated CpGs between tumour and adjacent benign cells in diagnostic prostate cancer samples

Differentially methylated CpG sites (dmCpGs) that distinguish prostate tumour from adjacent benign tissue could aid in the diagnosis and prognosis of prostate cancer. Previously, the identification of such dmCpGs has only been undertaken in radical prostatectomy (RP) samples and not primary diagnostic tumour samples (needle biopsy or transurethral resection of the prostate). We interrogated an Australian dataset comprising 125 tumour and 43 adjacent histologically benign diagnostic tissue samples, including 41 paired samples, using the Infinium Human Methylation450 BeadChip. Regression analyses of paired tumour and adjacent benign samples identified 2,386 significant dmCpGs (Bonferroni p < 0.01; delta-β ≥ 40%), with LASSO regression selecting 16 dmCpGs that distinguished tumour samples in the full Australian diagnostic dataset (AUC = 0.99). Results were validated in independent North American (npaired = 19; AUC = 0.87) and The Cancer Genome Atlas (TCGA; npaired = 50; AUC = 0.94) RP datasets. Two of the 16 dmCpGs were in genes that were significantly down-regulated in Australian tumour samples (Bonferroni p < 0.01; GSTM2 and PRKCB). Ten additional dmCpGs distinguished low (n = 34) and high Gleason (n = 88) score tumours in the diagnostic Australian dataset (AUC = 0.95), but these performed poorly when applied to the RP datasets (North American: AUC = 0.66; TCGA: AUC = 0.62). The DNA methylation marks identified here could augment and improve current diagnostic tests and/or form the basis of future prognostic tests.