Prostate Cancer Tissue Microarrays Research Articles

UBE2N promotes cell viability and glycolysis by promoting Axin1 ubiquitination in prostate cancer cells

BackgroundUbiquitin-conjugating enzyme E2 N (UBE2N) is recognized in the progression of some cancers; however, little research has been conducted to describe its role in prostate cancer. The purpose of this paper is to explore the function and mechanism of UBE2N in prostate cancer cells.MethodsUBE2N expression was detected in Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) data, prostate cancer tissue microarrays, and prostate cancer cell lines, respectively. UBE2N knockdown or overexpression was used to analyze its role in cell viability and glycolysis of prostate cancer cells and tumor growth. XAV939 or Axin1 overexpression was co-treated with UBE2N overexpression to detect the involvement of the Wnt/β-catenin signaling and Axin1 in the UBE2N function. UBE2N interacting with Axin1 was analyzed by co-immunoprecipitation assay.ResultsUBE2N was upregulated in prostate cancer and the UBE2N-high expression correlated with the poor prognosis of prostate cancer. UBE2N knockdown inhibited cell viability and glycolysis in prostate cancer cells and restricted tumor formation in tumor-bearing mice. Wnt/β-catenin inhibition and Axin1 overexpression reversed the promoting viability and glycolysis function of UBE2N. UBE2N promoted Axin1 ubiquitination and decreased Axin1 protein level.

The estrogen signaling pathway reprograms prostate cancer cell metabolism and supports proliferation and disease progression.

Just like the androgen receptor (AR), the estrogen receptor α (ERα) is expressed in the prostate and is thought to influence prostate cancer (PCa) biology. Yet the incomplete understanding of ERα functions in PCa hinders our ability to fully comprehend its clinical relevance and restricts the repurposing of estrogen-targeted therapies for the treatment of this disease. Using 2 human PCa tissue microarray cohorts, we first demonstrate that nuclear ERα expression was heterogeneous among patients, being detected in only half of the tumors. Positive nuclear ERα levels were correlated with disease recurrence, progression to metastatic PCa, and patient survival. Using in vitro and in vivo models of the normal prostate and PCa, bulk and single-cell RNA-Seq analyses revealed that estrogens partially mimicked the androgen transcriptional response and activated specific biological pathways linked to proliferation and metabolism. Bioenergetic flux assays and metabolomics confirmed the regulation of cancer metabolism by estrogens, supporting proliferation. Using cancer cell lines and patient-derived organoids, selective estrogen receptor modulators, a pure anti-estrogen, and genetic approaches impaired cancer cell proliferation and growth in an ERα-dependent manner. Overall, our study revealed that, when expressed, ERα functionally reprogrammed PCa metabolism, was associated with disease progression, and could be targeted for therapeutic purposes.

The Role of Adipocytokines and their Receptors in Prostate Cancer: Adiponectin May Protect Against Progression.

Obesity is correlated with an increased risk of developing malignancies, including prostate cancer. Adipocytokines, such as leptin and adiponectin, are a family of hormones derived from adipose tissue that are involved not only in metabolism, but also in the development and progression of various malignancies. However, little is known about their role in prostate cancer. This study aimed to determine how leptin, adiponectin, and their receptors impact the spread of prostate cancer. We first performed immunohistochemical analysis of prostate cancer tissue microarrays to detect leptin, leptin receptor (Ob-R), adiponectin, and adiponectin receptors 1 and 2 (AdipoR1 and AdipoR2). Wound healing assays and western blot analysis were then performed in human prostate cancer cell lines. Immunohistochemistry showed that prostate tissue was not significantly positive for adiponectin. However, its expression tended to decrease according to the International Society of Urological Pathology (ISUP) grade of prostate cancer (p=0.056). In prostate cancer cell lines, administration of the synthetic adiponectin AdipoRon suppressed cell migration as well as the expression of phospho-NF-[Formula: see text]B and cyclooxygenase-2, whereas leptin stimulated these effects. Adiponectin expression tended to be suppressed according to ISUP grade in prostate cancer tissues. In vitro, tumor cell migration was induced by leptin but suppressed by adiponectin. Targeting adipocytokines could be a novel treatment strategy for prostate cancer.

Abstract 299: FAP/αSMA association with tumor visibility and progression in prostate cancer

Abstract Introduction Prostate cancer (PCa) ranks as the second most frequently diagnosed cancer in the male population worldwide. The challenge in effectively managing PCa is the absence of well-established biological markers, which often leads to both over and under treatment. To address this issue, a deeper understanding of the molecular alterations within PCa is essential for more accurate patient stratification. In this research, we embark on a comprehensive examination of how the presence of fibroblast activation protein (FAP) and alpha smooth muscle actin (αSMA) in PCa tissue associates with the visibility of the disease in Magnetic Resonance Imaging (MRI) and their impact on cancer progression. The objective of this study is to analyze cell compartmental expression of FAP and aSMA using an AI based image analysis method. We also study the role of FAP and αSMA expression in predicting disease progression and mortality. Materials and Methods We applied FAP (ab207178, Abcam)/αSMA (M0851, DAKO) double chromogen immunohistochemical (IHC) staining to three independent cohorts of formalin-fixed paraffin-embedded (FFPE) prostate cancer tissue microarrays. All together, we analyzed 835 patients’ samples. First cohort consists of 387 patients with preoperative multiparametric MRI and robot-assisted laparoscopic prostatectomy (RALP) as primary treatment. Second cohort was case vs control cohort of Grade group 2-4 localized PCa at radical prostatectomy (RP) with 168 patients. Third cohort consists PCa patents from continuous, population-based collection of radical prostatectomies of 319 patients. Image analysis was performed with Aiforia Create, which is cloud-based deep-learning artificial intelligence software that provides platform for training and validating automated image analysis pipelines using convolutional neural networks. Analysis algorithm in this project was based on semantic, pixel-level area segmentation. Results FAP expression was higher and αSMA lower in MRI-visible tumors compared with MRI-invisible tumors. Stromal and epithelial FAP expression associate with tumor progression. We could also see statistically significant differences in FAP positivity between clinically significant (GS ≥7) and insignificant (GS ≤6) tumors. Hazard ratios imply that FAP and αSMA have significant impact on risk of biochemical recurrence in patients with MRI-visible tumors. Conclusions FAP is closely linked to tumor MRI visibility, cancer progression, and Gleason scores, marking it as a valuable biomarker in PCa assessment. High stromal αSMA is primarily associated with MRI visibility. Our automated AI-based image analysis method has demonstrated reliability, aligning with our previous findings. This advances the potential for more accurate and efficient prostate cancer diagnosis and prognosis, offering a potential benefit to future patient care. Citation Format: Jenni Säilä, Timo-Pekka Lehto, Annabrita Schoonenberg, Katja Välimäki, Andrew Erickson, Antti Rannikko, Olli Kallioniemi, Tuomas Mirtti, Teijo Pellinen. FAP/αSMA association with tumor visibility and progression in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 299.

Abstract 6962: Shed Trop2 drives prostate cancer progression and Trop2 is a novel tissue prognostic biomarker and a candidate urinary marker for prostate cancer

Abstract Distinguishing indolent from clinically significant localized prostate cancer and treatment of metastatic prostate cancer are two major clinical challenges in prostate cancer. The development of novel predictive biomarkers will help with risk stratification, and influence clinical decision-making between treatment and active surveillance, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2, an oncogenic transmembrane surface protein, is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that higher Trop2 expression is correlated with worse clinical features and elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detected shed Trop2 in urine from men with clinically significant prostate cancer. We further define the functional role of shed Trop2 on metastasis in prostate cancer and identify that shed Trop2 increases cell migration, invasion, metastatic colonization, and spontaneous metastasis in vitro and in vivo. Proteomic profiling reveals that shed Trop2 modulates a set of proteins associated with invasion, migration, mTOR signaling, and epithelial-to-mesenchymal transition. shed Trop2 binds to EGFR and results in the activation of the EGFR-PI3K-AKT-mTOR pathway in prostate cancer. Our study reveals the new function of shed Trop2 in driving prostate cancer progression and identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer that could be used to optimize treatment decision-making. Citation Format: Shiqin Liu, Sarah Hawley, Christian Kunder, En-Chi Hsu, Michelle Shen, Merve Aslan, Fernando J. Marques, Chung S. Lee, Abel Bermudez, Lennart Westphalen, Heidi Auman, Lisa F. Newcomb, Daniel W. Lin, Peter S. Nelson, Ziding Feng, Maria S. Tretiakova, Lawrence D. True, Funda Vakar-Lopez, Peter R. Carroll, Jeffry Simko, Martin E. Gleave, Dean A. Troyer, Jesse K. McKenney, Donna Peehl, Sharon J. Pitteri, James D. Brooks, Michael A. Liss, Tanya Stoyanova. Shed Trop2 drives prostate cancer progression and Trop2 is a novel tissue prognostic biomarker and a candidate urinary marker for prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6962.

Abstract 3046: The estrogen signaling pathway reprograms prostate cancer cell metabolism and supports proliferation and disease progression

Abstract Just as the androgen receptor (AR), the estrogen receptor α (ERα) is expressed in the prostate and is thought to influence prostate cancer (PCa) biology. Yet, the incomplete understanding of ERα cellular functions in PCa hinders our ability to fully comprehend its clinical relevance and restricts the repurposing of estrogen-targeted therapies for treatment of this disease. Using two human PCa tissue microarray cohorts, we first demonstrated that nuclear ERα expression was heterogeneous between patients, being only detected in half of tumors. Positive nuclear ERα levels were correlated with disease recurrence, progression to metastatic PCa, and patient survival. Using in vitro and in vivo models of the normal prostate and PCa, bulk and single cell RNA-seq analyses revealed that estrogens partially mimic the androgen transcriptional response and induce specific biological pathways linked to cellular proliferation and metabolism. Bioenergetic flux assays and metabolomics confirmed regulation of cancer metabolism by estrogens, supporting proliferation. Using cancer cell lines and patient-derived organoids, selective estrogen receptor modulators, a pure anti-estrogen, and genetic approaches impaired cancer cell proliferation and growth in an ERα-dependent manner. Overall, our study revealed that, when expressed, ERα functionally reprograms PCa metabolism, is associated with disease progression, and could be targeted for therapeutic purposes. Citation Format: Camille Lafront, Lucas Germain, Gabriel H. Campolina-Silva, Cindy Weidmann, Line Berthiaume, Hélène Hovington, Hervé Brisson, Cynthia Jobin, Lilianne Frégeau-Proulx, Raul Cotau, Kevin Gonthier, Aurélie Lacouture, Patrick Caron, Claire Ménard, Chantal Atallah, Julie Riopel, Éva Latulippe, Alain Bergeron, Paul Toren, Chantal Guillemette, Martin Pelletier, Yves Fradet, Clémence Belleannée, Frédéric Pouliot, Louis Lacombe, Éric Lévesque, Étienne Audet-Walsh. The estrogen signaling pathway reprograms prostate cancer cell metabolism and supports proliferation and disease progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3046.

High expression of Trop2 is associated with aggressive localized prostate cancer and is a candidate urinary biomarker

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

Transfer Learning with Pretrained Convolutional Neural Network for Automated Gleason Grading of Prostate Cancer Tissue Microarrays.

The Gleason grading system has been the most effective prediction for prostate cancer patients. This grading system provides this possibility to assess prostate cancer's aggressiveness and then constitutes an important factor for stratification and therapeutic decisions. However, determining Gleason grade requires highly-trained pathologists and is time-consuming and tedious, and suffers from inter-pathologist variability. To remedy these limitations, this paper introduces an automatic methodology based on transfer learning with pretrained convolutional neural networks (CNNs) for automatic Gleason grading of prostate cancer tissue microarray (TMA). Fifteen pretrained (CNNs): Efficient Nets (B0-B5), NasNetLarge, NasNetMobile, InceptionV3, ResNet-50, SeResnet 50, Xception, DenseNet121, ResNext50, and inception_resnet_v2 were fine-tuned on a dataset of prostate carcinoma TMA images. Six pathologists separately identified benign and cancerous areas for each prostate TMA image by allocating benign, 3, 4, or 5 Gleason grade for 244 patients. The dataset was labeled by these pathologists and majority vote was applied on pixel-wise annotations to obtain a unified label. Results showed the NasnetLarge architecture is the best model among them in the classification of prostate TMA images of 244 patients with accuracy of 0.93 and area under the curve of 0.98. Our study can act as a highly trained pathologist to categorize the prostate cancer stages with more objective and reproducible results.

Regulation of SELENOF translation by eIF4a3: Possible role in prostate cancer progression.

The levels of the SELENOF selenoprotein are dramatically reduced in prostate cancer compared to adjacent benign tissue and reducing SELENOF in prostate epithelial cells results in the acquisition of features of the transformed phenotype. It was hypothesized that the aberrant increase in the eiF4a3 translation factor, which has an established role in RNA splicing and the regulation of selenoprotein translation, contributes to the lower levels of SELENOF. Using the available databases, eIF4a3messenger RNA (mRNA) levels are elevated in prostate cancer compared to normal tissue as is the hypomethylation of the corresponding gene. Using a prostate cancer tissue microarray, we established that eiF4a3 levels are higher in prostate cancer tissue. Ectopic expression of eIF4a3 in prostate cancer cells reduced SELENOF levels and attenuated the readthrough of the UGA codon using a specialized reporter construct designed to examine UGA decoding, with the opposite effects observed using eIF4a3 knock-down constructs. Direct binding of eIF4a3 to the regulatory regions of SELENOF mRNA was established with pull-down experiments. Lastly, we show that an eIF4a3 inhibitor, eIF4a3-IN-2, increases SELENOF levels, UGA readthrough, and reduces binding of eIF4a3 to the SELENOF mRNA 3'-UTR in exposed cells. These data establish eIF4a3 as a likely prostate cancer oncogene and a regulator of SELENOF translation.

Development and characterization of an ETV1 rabbit monoclonal antibody for the immunohistochemical detection of ETV1 expression in cancer tissue specimens

BackgroundAberrant ETV1 overexpression arising from gene rearrangements or mutations occur frequently in prostate cancer, round cell sarcomas, gastrointestinal stromal tumors, gliomas, and other malignancies. The absence of specific monoclonal antibodies (mAb) has limited its detection and our understanding of its oncogenic function. MethodsAn ETV1 specific rabbit mAb (29E4) was raised using an immunogenic peptide. Key residues essential for its binding were probed by ELISA and its binding kinetics were measured by surface plasmon resonance imaging (SPRi). Its selective binding to ETV1 was assessed by immunoblots and immunofluorescence assays (IFA), and by both single and double-immuno-histochemistry (IHC) assays on prostate cancer tissue specimens. ResultsImmunoblot results showed that the mAb is highly specific and lacked cross-reactivity with other ETS factors. A minimal epitope with two phenylalanine residues at its core was found to be required for effective mAb binding. SPRi measurements revealed an equilibrium dissociation constant in the picomolar range, confirming its high affinity. ETV1 (+) tumors were detected in prostate cancer tissue microarray cases evaluated. IHC staining of whole-mounted sections revealed glands with a mosaic staining pattern of cells that are partly ETV1 (+) and interspersed with ETV1 (−) cells. Duplex IHC, using ETV1 and ERG mAbs, detected collision tumors containing glands with distinct ETV1 (+) and ERG (+) cells. ConclusionsThe selective detection of ETV1 by the 29E4 mAb in immunoblots, IFA, and IHC assays using human prostate tissue specimens reveals a potential utility for the diagnosis, the prognosis of prostate adenocarcinoma and other cancers, and the stratification of patients for treatment by ETV1 inhibitors.

Abstract 2091: Open-source single-cell spatial image analysis pipeline for ten-plex immunofluorescence of histological prostate cancer tissue sections

Abstract Introduction: Multiplexed fluorescence immunohistochemistry (mfIHC) allows the detection of multiple protein markers on the same histological tissue section, generating valuable information on specific cell subsets and cellular states in their spatial tissue context. Here, we demonstrate a proof-of-concept study for profiling different tumor microenvironment cell subsets in formalin-fixed paraffin-embedded prostate cancer tissue microarrays. Materials and methods: We applied automated mfIHC simultaneous staining of 31 slides with 3.5-µm sections using an Autostainer (Epredia, Kalamazoo, USA). The protocol included four rounds of cyclic staining and scanning of the slides with AxioScanZ.1 (Zeiss, Germany). Each cycle included DAPI for nuclear staining. Here, we applied this pipeline to detect the following targets: D2-40 (lymphatics), CD3 (T lymphocytes), CD56 (NK cells/neural cells/neuroendocrine cells), CD11b+ myeloid cells, PDGFRB (fibroblasts/pericytes), CD20 (B lymphocytes), CD31 (endothelium), CD45 (leukocytes), HLADR+ antigene-presenting cells, as well as a cocktail with PanCK and ECADH to detect epithelial cells. Three different prostate cancer TMA cohorts with n=907 patient samples were analyzed here using this approach.The scanned images were exported as Big TIFF individual channel whole-slide images. Individual TMA spot images were marked with Fiji ROI1 1-Click Tool macro (ImageJ 1.53t), and separate rounds were registered with Python (version 3.11.0, Python Software Foundation) using DAPI channel as reference. Nuclear segmentation was created with nucleAIzer trained modified Mask R-CNN model (https://github.com/lopaavol/nuclei_segmentation). All TMA spot images were run through image curation, where artefacts are excluded by machine learning using ilastik software (version 1.3.3post3). Then, CellProfiler (version 4.2.1) was applied to combine image curated tissue masks and segmented nuclei for cell-based channel intensity measurements. Finally, Jupyter Notebook was applied to classify cell subsets into specific phenotypes using intensity-based thresholding for each channel. Results and Conclusions: We present a detailed pipeline for 10-plex mfIHC with open-source single-cell image analysis tools. The approach can be applied to histological laboratories when combined with a standard five fluorescent channel scanner or imager and with basic computing skills. As the system applies secondary antibodies for the detection, it is flexible for optimizing new antibody panels, and the user is not limited to pre-labelled antibody panels often connected with commercial staining and imaging systems. The approach is especially suited for large-scale high-throughput tissue profiling studies when high n-values are needed for linking associated patient clinical data with spatial phenotype data. Citation Format: Jenni Säilä, Annabrita Schoonenberg, Katja Välimäki, Timo-Pekka Lehto, Carolin Stürenberg, Andrew Erickson, Antti Rannikko, Olli Kallioniemi, Lassi Paavolainen, Tuomas Mirtti, Teijo Pellinen. Open-source single-cell spatial image analysis pipeline for ten-plex immunofluorescence of histological prostate cancer tissue sections [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2091.

Preclinical Efficacy of a PARP-1 Targeted Auger-Emitting Radionuclide in Prostate Cancer.

There is an unmet need for better therapeutic strategies for advanced prostate cancer. Poly (ADP-ribose) polymerase-1 (PARP-1) is a chromatin-binding DNA repair enzyme overexpressed in prostate cancer. This study evaluates whether PARP-1, on account of its proximity to the cell's DNA, would be a good target for delivering high-linear energy transfer Auger radiation to induce lethal DNA damage in prostate cancer cells. We analyzed the correlation between PARP-1 expression and Gleason score in a prostate cancer tissue microarray. A radio-brominated Auger emitting inhibitor ([77Br]Br-WC-DZ) targeting PARP-1 was synthesized. The ability of [77Br]Br-WC-DZ to induce cytotoxicity and DNA damage was assessed in vitro. The antitumor efficacy of [77Br]Br-WC-DZ was investigated in prostate cancer xenograft models. PARP-1 expression was found to be positively correlated with the Gleason score, thus making it an attractive target for Auger therapy in advanced diseases. The Auger emitter, [77Br]Br-WC-DZ, induced DNA damage, G2-M cell cycle phase arrest, and cytotoxicity in PC-3 and IGR-CaP1 prostate cancer cells. A single dose of [77Br]Br-WC-DZ inhibited the growth of prostate cancer xenografts and improved the survival of tumor-bearing mice. Our studies establish the fact that PARP-1 targeting Auger emitters could have therapeutic implications in advanced prostate cancer and provides a strong rationale for future clinical investigation.

Abstract C017: Detection of wild-type and truncated HMGA2 in prostate cancer tissues using RNA in situ hybridization

Abstract High mobility group A2 (HMGA2), a non-histone protein, is known to promote epithelial-mesenchymal transition (EMT), which plays a critical role in prostate cancer progression and metastasis. Both full-length HMGA2 (WT-HMGA2) and truncated (lacking the 3’UTR) HMGA2 (TR-HMGA2) isoforms are overexpressed in several cancers such as lung carcinomas, ovarian cancer, breast cancer, and gastric cancer. However, there is no study investigating the expression and differential roles of WT vs truncated HMGA2 isoforms in prostate cancer. Our previous results indicated that the overexpression of HMGA2 in LNCaP cells increased cell viability and migration for both wild-type and truncated HMGA2. Promotion of EMT was observed in wild-type, but not truncated HMGA2. Reactive oxygen species (ROS) levels were increased with truncated HMGA2 more than wild-type HMGA2. Therefore, wild-type and truncated HMGA2 may play different roles on cancer progression and metastasis. The goal of this study is to examine the expression of wild-type vs. truncated HMGA2 in prostate cancer patient tissue. We have developed a way to detect location and expression of wild-type and truncated HMGA2 using RNA in situ hybridization (RISH). The specific probes’ hybridization followed by a serial signal amplification process allows us to locate and quantify the HMGA2 isoforms in Formalin-Fixed Paraffin-Embedded (FFPE) tissue specimens from cancer patients. Several prostate tissue samples and a prostate cancer tissue microarray that includes 35 patients from different races, stages of cancer, and metastasis status was analyzed. Our results showed increased HMGA2 expression (both wild-type and truncated) in several prostate cancer samples with higher stage cancer. We also observed that most wild-type and truncated HMGA2 is located within the nucleus, while some wild-type isoforms were detected within the cytoplasm. We will further quantify the expression levels to examine whether they are associated with tumor stage and/or race. These studies are the first to examine HMGA2 isoform expression and localization in prostate patient tissue and may offer novel therapeutic intervention strategies based on HMGA2 isoform expression. Citation Format: Bor-Jang Hwang, Mojisoluwa Awolowo, Taaliah Campbell, Ohuod Hawsawi, Sharon Harrison, Denise Gibbs, Camille Ragin, Valerie Odero-Marah. Detection of wild-type and truncated HMGA2 in prostate cancer tissues using RNA in situ hybridization [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C017.

Overexpression of Ubiquitin-Conjugating Enzyme E2C Is Associated with Worsened Prognosis in Prostate Cancer.

To evaluate the role of ubiquitin-conjugating enzyme E2C (UBE2C) in prostate cancer (PCa) progression and prognosis, the TCGA and our PCa tissue microarray cohort were included in the study. Weighted gene co-expression network analysis (WGCNA) and non-negative matrix factorization were used to cluster patients and to screen genes that play a vital role in PCa progression (hub gene). Immunohistochemistry staining was used to evaluate the protein level of UBE2C in prostatic tissues. Through WGCNA, we found a gene co-expression module (named the purple module) that is strongly associated with the Gleason score, pathologic T stage, and biochemical recurrent status. Genes in the purple module are enriched in cell cycle and P53 signaling and help us to cluster patients into two groups with distinctive biochemical recurrent survival rates and TP53 mutation statuses. Further analysis showed UBE2C served as a hub gene in the purple module. The expression of UBE2C in PCa was significantly higher than that in paracancerous tissues and was remarkably associated with pathologic grade, Gleason score, and prognosis in PCa patients. To conclude, UBE2C is a PCa-progress-related gene and a biomarker for PCa patients. Therapy targeting UBE2C may serve as a promising treatment of PCa in the future.

A deep learning network for Gleason grading of prostate biopsies using EfficientNet.

The most crucial part in the diagnosis of cancer is severity grading. Gleason's score is a widely used grading system for prostate cancer. Manual examination of the microscopic images and grading them is tiresome and consumes a lot of time. Hence to automate the Gleason grading process, a novel deep learning network is proposed in this work. In this work, a deep learning network for Gleason grading of prostate cancer is proposed based on EfficientNet architecture. It applies a compound scaling method to balance the dimensions of the underlying network. Also, an additional attention branch is added to EfficientNet-B7 for precise feature weighting. To the best of our knowledge, this is the first work that integrates an additional attention branch with EfficientNet architecture for Gleason grading. The proposed models were trained using H&E-stained samples from prostate cancer Tissue Microarrays (TMAs) in the Harvard Dataverse dataset. The proposed network was able to outperform the existing methods and it achieved an Kappa score of 0.5775.

Spatial Profiling of the Prostate Cancer Tumor Microenvironment Reveals Multiple Differences in Gene Expression and Correlation with Recurrence Risk.

Simple SummaryIn prostate cancer (PCa), the tumor microenvironment plays a crucial role in both the development and progression of the disease. We used Digital Spatial Profiling multiplex technology to assess the expression of 58 protein and 1825 RNA transcripts in traditionally challenging samples (i.e., archived FFPE samples) while maintaining the spatial context of expression. First, we identified differences in protein and RNA expression among multiple cell types (stromal, epithelial, and immune cells). Second, we used a PCa tissue microarray of 1547 cores (97 patients) to further validate the protein expression of selected genes in a larger cohort of prostate cancer patients. We also computed survival models testing the relationship between OX40L, CTLA4, and CD11c protein expression in both tumor and tumor-adjacent stroma samples with time to biochemical relapse.The tumor microenvironment plays a crucial role in both the development and progression of prostate cancer. Furthermore, identifying protein and gene expression differences between different regions is valuable for treatment development. We applied Digital Spatial Profiling multiplex analysis to formalin-fixed paraffin embedded prostatectomy tissue blocks to investigate protein and transcriptome differences between tumor, tumor-adjacent stroma (TAS), CD45+ tumor, and CD45+ TAS tissue. Differential expression of an immunology/oncology protein panel (n = 58) was measured. OX40L and CTLA4 were expressed at higher levels while 22 other proteins, including CD11c, were expressed at lower levels (FDR < 0.2 and p-value < 0.05) in TAS as compared to tumor epithelia. A tissue microarray analysis of 97 patients with 1547 cores found positive correlations between high expression of CD11c and increased time to recurrence in tumor and TAS, and inverse relationships for CTLA4 and OX40L, where higher expression in tumor correlated with lower time to recurrence, but higher time to recurrence in TAS. Spatial transcriptomic analysis using a Cancer Transcriptome Atlas panel (n = 1825 genes) identified 162 genes downregulated and 69 upregulated in TAS versus tumor, 26 downregulated and 6 upregulated in CD45+ TAS versus CD45+ tumor. We utilized CIBERSORTx to estimate the relative immune cell fractions using CD45+ gene expression and found higher average fractions for memory B, naïve B, and T cells in TAS. In summary, the combination of protein expression differences, immune cell fractions, and correlations of protein expression with time to recurrence suggest that closely examining the tumor microenvironment provides valuable data that can improve prognostication and treatment techniques.

Identification and Classification of Prostate Cancer Identification and Classification Based on Improved Convolution Neural Network.

Prostate cancer is one of the most common cancers in men worldwide, second only to lung cancer. The most common method used in diagnosing prostate cancer is the microscopic observation of stained biopsies by a pathologist and the Gleason score of the tissue microarray images. However, scoring prostate cancer tissue microarrays by pathologists using Gleason mode under many tissue microarray images is time-consuming, susceptible to subjective factors between different observers, and has low reproducibility. We have used the two most common technologies, deep learning, and computer vision, in this research, as the development of deep learning and computer vision has made pathology computer-aided diagnosis systems more objective and repeatable. Furthermore, the U-Net network, which is used in our study, is the most extensively used network in medical image segmentation. Unlike the classifiers used in previous studies, a region segmentation model based on an improved U-Net network is proposed in our research, which fuses deep and shallow layers through densely connected blocks. At the same time, the features of each scale are supervised. As an outcome of the research, the network parameters can be reduced, the computational efficiency can be improved, and the method's effectiveness is verified on a fully annotated dataset.

Abstract 330: Targeting B7-H3 in prostate cancer: Preclinical proof of concept with MGC018, an investigational anti-B7-H3 antibody-drug conjugate

Abstract Introduction: Prostate cancer is the second most common cancer among men worldwide. In 2021, it is estimated that 248,530 men in the United States will be diagnosed with prostate cancer, and 34,130 will die from the disease. Although current treatments have success initially, development of resistance commonly leads to recurrence of an incurable castrate-resistant form of the disease. Thus, significant need for novel therapies to improve the outcome of castrate-resistant prostate cancer remains. B7-H3 (CD276), a member of the B7 family of immunomodulatory molecules, is overexpressed in primary and metastatic prostate cancer, and correlates with disease severity and poor clinical outcome. MGC018, a duocarmycin-based B7-H3 antibody-drug conjugate, is currently being evaluated in clinical studies. Here, MGC018 was explored preclinically to assess the potential for targeting B7-H3 in prostate cancer. Methods: Immunohistochemistry studies were performed to define the expression of B7-H3 in prostate cancer tissue microarrays (TMA). In vivo efficacy studies were conducted with human prostate cancer cell line-derived xenograft (CDX) models to explore the antitumor activity of MGC018 as a single agent and in combination with Poly (ADP-ribose) polymerase (PARP) and androgen receptor (AR) inhibitors. Based on the results in the CDX studies, in vivo efficacy studies were extended to a panel of metastatic prostate cancer patient-derived xenograft (PDX) models, which exhibit heterogenous expression of B7-H3 and more closely mimic the biological characteristics of patient tumors. Results: Staining of prostate tumor TMAs revealed high expression of B7-H3 in primary and metastatic prostate cancer. Of the prostate samples evaluated, 95% (38/40) of the tumor samples were positive for B7-H3 (H-score ≥ 20): 65% had H-scores greater than 200, while 20% and 10% had H-scores between 101-200 and 1-100, respectively. MGC018 demonstrated in vitro cytotoxicity toward B7-H3-positive human prostate cancer cell lines. The in vitro cytotoxicity translated to potent antitumor activity in vivo toward prostate cancer CDX models, and the antitumor activity of MGC018 was enhanced when combined with inhibitors of PARP or AR. In PDX models of metastatic prostate cancer, MGC018 was active as a single agent toward heterogeneous B7-H3-expressing tumors, and combining MGC018 with inhibitors of PARP or AR led to a greater response in some models. Conclusion: B7-H3 is frequently overexpressed in prostate cancer. MGC018 demonstrated potent antitumor activity in vivo toward CDX and PDX models of prostate cancer, and enhanced antitumor activity when combined with inhibitors of PARP or AR. These results support prostate cancer as an indication that may be responsive to ADC-based treatments directed toward B7-H3. MGC018 is being investigated in metastatic prostate cancer in a Phase 1/2 clinical study. Citation Format: Juniper A. Scribner, Francine Z. Chen, Anushka De Costa, Ying Li, Michael Chiechi, Thomas Son, Jeff Hooley, Jonathan Li, Scott Koenig, Chet Bohac, Ezio Bonvini, Paul A. Moore, Deryk Loo. Targeting B7-H3 in prostate cancer: Preclinical proof of concept with MGC018, an investigational anti-B7-H3 antibody-drug conjugate [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 330.

PLK4 is upregulated in prostate cancer and its inhibition reduces centrosome amplification and causes senescence.

BackgroundIdentification of novel molecular target(s) is important for designing newer mechanistically driven approaches for the treatment of prostate cancer (PCa), which is one of the main causes of morbidity and mortality in men. In this study, we determined the role of polo‐like kinase 4 (PLK4), which regulates centriole duplication and centrosome amplification (CA), in PCa.Materials and MethodsEmploying human PCa tissue microarrays, we assessed the prevalence of CA, correlated with Gleason score, and estimated major causes of CA in PCa (cell doubling vs. centriole overduplication) by staining for mother/mature centrioles. We also assessed PLK4 expression and correlated it with CA in human PCa tissues and cell lines. Further, we determined the effects of PLK4 inhibition in human PCa cells.ResultsCompared to benign prostate, human PCa demonstrated significantly higher CA, which was also positively correlated with the Gleason score. Further, most cases of CA were found to arise by centriole overduplication rather than cell doubling events (e.g., cytokinesis failure) in PCa. In addition, PLK4 was overexpressed in human PCa cell lines and tumors. Moreover, PLK4 inhibitors CFI‐400945 and centrinone‐B inhibited cell growth, viability, and colony formation of both androgen‐responsive and androgen‐independent PCa cell lines. PLK4 inhibition also induced cell cycle arrest and senescence in human PCa cells.ConclusionsCA is prevalent in PCa and arises predominantly by centriole overduplication as opposed to cell doubling events. Loss of centrioles is cellular stress that can promote senescence and suggests that PLK4 inhibition may be a viable therapeutic strategy in PCa.

The Movember Global Action Plan 1 (GAP1): Unique Prostate Cancer Tissue Microarray Resource.

The need to better understand the molecular underpinnings of the heterogeneous outcomes of patients with prostate cancer is a pressing global problem and a key research priority for Movember. To address this, the Movember Global Action Plan 1 Unique tissue microarray (GAP1-UTMA) project constructed a set of unique and richly annotated tissue microarrays (TMA) from prostate cancer samples obtained from multiple institutions across several global locations. Three separate TMA sets were built that differ by purpose and disease state. The intended use of TMA1 (Primary Matched LN) is to validate biomarkers that help determine which clinically localized prostate cancers with associated lymph node metastasis have a high risk of progression to lethal castration-resistant metastatic disease, and to compare molecular properties of high-risk index lesions within the prostate to regional lymph node metastases resected at the time of prostatectomy. TMA2 (Pre vs. Post ADT) was designed to address questions regarding risk of castration-resistant prostate cancer (CRPC) and response to suppression of the androgen receptor/androgen axis, and characterization of the castration-resistant phenotype. TMA3 (CRPC Met Heterogeneity)'s intended use is to assess the heterogeneity of molecular markers across different anatomic sites in lethal prostate cancer metastases. The GAP1-UTMA project has succeeded in combining a large set of tissue specimens from 501 patients with prostate cancer with rich clinical annotation. This resource is now available to the prostate cancer community as a tool for biomarker validation to address important unanswered clinical questions around disease progression and response to treatment.