Multi-Scale Relational Graph Convolutional Network for Multiple Instance Learning in Histopathology Images

Graph convolutional neural networks have shown significant potential in natural and histopathology images. However, their use has only been studied in a single magnification or multi-magnification with late fusion. In order to leverage the multi-magnification information and early fusion with graph convolutional networks, we handle different embedding spaces at each magnification by introducing the Multi-Scale Relational Graph Convolutional Network (MS-RGCN) as a multiple instance learning method. We model histopathology image patches and their relation with neighboring patches and patches at other scales (i.e., magnifications) as a graph. To pass the information between different magnification embedding spaces, we define separate message-passing neural networks based on the node and edge type. We experiment on prostate cancer histopathology images to predict the grade groups based on the extracted features from patches. We also compare our MS-RGCN with multiple state-of-the-art methods with evaluations on several source and held-out datasets. Our method outperforms the state-of-the-art on all of the datasets and image types consisting of tissue microarrays, whole-mount slide regions, and whole-slide images. Through an ablation study, we test and show the value of the pertinent design features of the MS-RGCN

Steroidogenesis in peripheral and transition zones of human prostate cancer tissue

The peripheral zone (PZ) and transition zone (TZ) represent about 70% of the human prostate gland with each zone having differential ability to develop prostate cancer. Androgens and their receptor are the primary driving cause of prostate cancer growth and eventually castration-resistant prostate cancer (CRPC). De novo steroidogenesis has been identified as a key mechanism that develops during CRPC. Currently, there is very limited information available on human prostate tissue steroidogenesis. The purpose of the present study was to investigate steroid metabolism in human prostate cancer tissues with comparison between PZ and TZ. Human prostate cancer tumors were procured from the patients who underwent radical prostatectomy without any neoadjuvant therapy. Human prostate homogenates were used to quantify steroid levels intrinsically present in the tissues as well as formed after incubation with 2 µg/mL of 17-hydroxypregnenolone (17-OH-pregnenolone) or progesterone. A Waters Acquity ultraperformance liquid chromatography coupled to a Quattro Premier XE tandem quadrupole mass spectrometer using a C18 column was used to measure thirteen steroids from the classical and backdoor steroidogenesis pathways. The intrinsic prostate tissue steroid levels were similar between PZ and TZ with dehydroepiandrosterone (DHEA), dihydrotestosterone (DHT), pregnenolone and 17-OH-pregnenolone levels higher than the other steroids measured. Interestingly, 5-pregnan-3,20-dione, 5-pregnan-3-ol-20-one, and 5-pregnan-17-ol-3,20-dione formation was significantly higher in both the zones of prostate tissues, whereas, androstenedione, testosterone, DHT, and progesterone levels were significantly lower after 60 min incubation compared to the 0 min control incubations. The incubations with progesterone had a similar outcome with 5-pregnan-3,20-dione and 5-pregnan-3-ol-20-one levels were elevated and the levels of DHT were lower in both PZ and TZ tissues. The net changes in steroid formation after the incubation were more observable with 17-OH-pregnenolone than with progesterone. In our knowledge, this is the first report of comprehensive analyses of intrinsic prostate tissue steroids and precursor-driven steroid metabolism using a sensitive liquid chromatography-mass spectrometry assay. In summary, the PZ and TZ of human prostate exhibited similar steroidogenic ability with distinction in the manner each zone utilizes the steroid precursors to divert the activity towards backdoor pathway through a complex matrix of steroidogenic mechanisms

MicroRNAs Associated with Metastatic Prostate Cancer

Metastasis is the most common cause of death of prostate cancer patients. Identification of specific metastasis biomarkers and novel therapeutic targets is considered essential for improved prognosis and management of the disease. MicroRNAs (miRNAs) form a class of non-coding small RNA molecules considered to be key regulators of gene expression. Their dysregulation has been shown to play a role in cancer onset, progression and metastasis, and miRNAs represent a promising new class of cancer biomarkers. The objective of this study was to identify down- and up-regulated miRNAs in prostate cancer that could provide potential biomarkers and/or therapeutic targets for prostate cancer metastasis. into NOD/SCID mice, a methodology that tends to preserve properties of the original cancers (e.g., tumor heterogeneity, genetic profiles).Differentially expressed known miRNAs, isomiRs and 36 novel miRNAs were identified. A number of these miRNAs (21/104) have previously been reported to show similar down- or up-regulation in prostate cancers relative to normal prostate tissue, and some of them (e.g., miR-16, miR-34a, miR-126*, miR-145, miR-205) have been linked to prostate cancer metastasis, supporting the validity of the analytical approach.The use of metastatic and non-metastatic prostate cancer subrenal capsule xenografts derived from one patient's cancer makes it likely that the differentially expressed miRNAs identified in this study include potential biomarkers and/or therapeutic targets for human prostate cancer metastasis

Boolean analysis identifies CD38 as a biomarker of aggressive localized prostate cancer.

The introduction of serum Prostate Specific Antigen (PSA) testing nearly 30 years ago has been associated with a significant shift towards localized disease and decreased deaths due to prostate cancer. Recognition that PSA testing has caused over diagnosis and over treatment of prostate cancer has generated considerable controversy over its value, and has spurred efforts to identify prognostic biomarkers to distinguish patients who need treatment from those that can be observed. Recent studies show that cancer is heterogeneous and forms a hierarchy of tumor cell populations. We developed a method of identifying prostate cancer differentiation states related to androgen signaling using Boolean logic. Using gene expression data, we identified two markers, CD38 and ARG2, that group prostate cancer into three differentiation states. Cancers with CD38-, ARG2- expression patterns, corresponding to an undifferentiated state, had significantly lower 10-year recurrence-free survival compared to the most differentiated group (CD38+ARG2+). We carried out immunohistochemical (IHC) staining for these two markers in a single institution (Stanford; n = 234) and multi-institution (Canary; n = 1326) cohorts. IHC staining for CD38 and ARG2 in the Stanford cohort demonstrated that combined expression of CD38 and ARG2 was prognostic. In the Canary cohort, low CD38 protein expression by IHC was significantly associated with recurrence-free survival (RFS), seminal vesicle invasion (SVI), extra-capsular extension (ECE) in univariable analysis. In multivariable analysis, ARG2 and CD38 IHC staining results were not independently associated with RFS, overall survival, or disease-specific survival after adjusting for other factors including SVI, ECE, Gleason score, pre-operative PSA, and surgical margins

Clusterin Regulates Drug-Resistance in Melanoma Cells

Clusterin has recently been shown to act as an antiapoptotic protein that confers drug-resistance in models of epithelial tumors. The aim of our work was to provide an insight into a possible role of clusterin in the regulation of drug-resistance in melanoma. In tissue samples, clusterin expression was low in nevi, but high in primary melanoma and melanoma metastases. Clusterin was also strongly expressed in melanoma cell lines, but was barely detectable in cultured melanocytes. To elucidate a possible role of clusterin in drug-resistance of melanoma, clusterin expression was regulated by either plasmid-driven overexpression or by antisense-mediated downregulation. Clusterin overexpression was associated with an increase in drug-resistance, i.e., with an increased survival of melanoma cells in the presence of cytotoxic drugs. In contrast, downregulation of clusterin by 2′-O-(2-methoxy)ethyl (2′MOE)-modified antisense oligonucleotides (AS-ODN) directed against clusterin mRNA significantly reduced drug-resistance, i.e., decreased survival of melanoma cells in the presence of cytotoxic drugs. To evaluate the effects of clusterin-antisense treatment in vivo, we applied an SCID-mouse/human-melanoma xenotransplantation model. Pre-treatment of mice with the 2′MOE-modified clusterin AS-ODN was associated with a significantly improved tumor response to dacarbazine as compared with animals pretreated with a scrambled control oligonucleotide. Taken together, we show that clusterin is strongly expressed in melanoma. Downregulation of clusterin reduces drug-resistance, i.e., reduces melanoma cell survival in response to cytotoxic drugs in vitro and in vivo. Thus, reducing clusterin expression may provide a novel tool to overcome drug-resistance in melanoma

Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS).

BackgroundFor men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification.MethodsUrine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to ≥34%. The association of biomarker scores, adjusted for common clinical variables, with short- and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSeven hundred and eighty-two men contributed 2069 urine specimens. After adjusting for PSA, prostate size, and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (OR = 1.3; 95% CI 1.0-1.7, p = 0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker nor marker kinetics was associated with time to reclassification in subsequent biopsies.ConclusionsPCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies

Developing consensus standard operating procedures (SOPs) to evaluate new types of insecticide-treated nets

In response to growing concerns over the sustained effectiveness of pyrethroid-only based control tools, new products are being developed and evaluated. Some examples of these are dual-active ingredient (AI) insecticide-treated nets (ITNs) which contain secondary insecticides, or syner-gist ITNs which contain insecticide synergist, both in combination with a pyrethroid. These net types are often termed 'next-generation' insecticide-treated nets. Several of these new types of ITNs are being evaluated in large-scale randomized control trials (RCTs) and pilot deployment schemes at a country level. However, no methods for measuring the biological durability of the AIs or synergists on these products are currently recommended. In this publication, we describe a pipeline used to collate and interrogate several different methods to produce a singular 'consensus standard operating procedure (SOP)', for monitoring the biological durability of three new types of ITNs: pyrethroid + piperonyl butoxide (PBO), pyrethroid + pyriproxyfen (PPF), and pyrethroid + chlorfenapyr (CFP). This process, convened under the auspices of the Innovation to Impact programme, sought to align methodologies used for conducting durability monitoring activities of next-generation ITNs. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Loss of Nuclear Functions of HOXA10 Is Associated With Testicular Cancer Proliferation

Background: HOXA10 is a key transcriptional factor that regulates testis development as reported from previous transgenic mouse models and human inherited diseases. However, whether it also plays important roles in promoting the development of testicular cancer is not well-understood.Objective: To study the expression of HOXA10 and its regulated signaling pathways in testicular cancers.Design, Setting, and Participants: A tissue microarray was constructed with benign and cancerous testis. TCam2, NT-2, and NCCIT cell models were applied in this study.Intervention: Immunohistochemistry and immunofluorescence were performed to measure the expression and cellular localization of HOXA10 in testicular cancer tissues and cell models. Cell proliferation and cell cycling rates were determined by BrdU incorporation and flow cytometry assays. HOXA10 transcriptomes were profiled with Ampliseq RNA-seq in testicular cancer cells. Immunoblotting assays were used to detect HOXA10-regulated signaling.Results: HOXA10 is a nuclear protein in benign spermatocytes. Reduced nuclear expression and increased cytoplasmic expression of HOXA10 are associated with testicular cancers. These changes are consistent in both seminoma and non-seminoma. Enhanced HOXA10 expression in testicular cancer cell models inhibits cell proliferation and delays cell cycle progression through G2/M phases. These functions of HOXA10 mainly affect the TP53, cKit, STAT3, AKT, and ERK signaling pathways.Conclusions: Loss of nuclear functions of HOXA10 enhances proliferation of testicular cancer cells, suggesting that downregulation of HOXA10 transcription activity may promote the development of testicular cancers