In Vivo Expression of miR-32 Induces Proliferation in Prostate Epithelium

Deformation equivariant cross-modality image synthesis with paired non-aligned training data

Cross-modality image synthesis is an active research topic with multiple medical clinically relevant applications. Recently, methods allowing training with paired but misaligned data have started to emerge. However, no robust and well-performing methods applicable to a wide range of real world data sets exist. In this work, we propose a generic solution to the problem of cross-modality image synthesis with paired but non-aligned data by introducing new deformation equivariance encouraging loss functions. The method consists of joint training of an image synthesis network together with separate registration networks and allows adversarial training conditioned on the input even with misaligned data. The work lowers the bar for new clinical applications by allowing effortless training of cross-modality image synthesis networks for more difficult data sets.

The effect of neural network architecture on virtual H&E staining: Systematic assessment of histological feasibility

Conventional histopathology has relied on chemical staining for over a century. The staining process makes tissue sections visible to the human eye through a tedious and labor-intensive procedure that alters the tissue irreversibly, preventing repeated use of the sample. Deep learning-based virtual staining can potentially alleviate these shortcomings. Here, we used standard brightfield microscopy on unstained tissue sections and studied the impact of increased network capacity on the resulting virtually stained H&E images. Using the generative adversarial neural network model pix2pix as a baseline, we observed that replacing simple convolutions with dense convolution units increased the structural similarity score, peak signal-to-noise ratio, and nuclei reproduction accuracy. We also demonstrated highly accurate reproduction of histology, especially with increased network capacity, and demonstrated applicability to several tissues. We show that network architecture optimization can improve the image translation accuracy of virtual H&E staining, highlighting the potential of virtual staining in streamlining histopathological analysis.

Unstained Tissue Imaging and Virtual Hematoxylin and Eosin Staining of Histologic Whole Slide Images

Tissue structures, phenotypes, and pathology are routinely investigated based on histology. This includes chemically staining the transparent tissue sections to make them visible to the human eye. Although chemical staining is fast and routine, it permanently alters the tissue and often consumes hazardous reagents. On the other hand, on using adjacent tissue sections for combined measurements, the cell-wise resolution is lost owing to sections representing different parts of the tissue. Hence, techniques providing visual information of the basic tissue structure enabling additional measurements from the exact same tissue section are required. Here we tested unstained tissue imaging for the development of computational hematoxylin and eosin (HE) staining. We used unsupervised deep learning (CycleGAN) and whole slide images of prostate tissue sections to compare the performance of imaging tissue in paraffin, as deparaffinized in air, and as deparaffinized in mounting medium with section thicknesses varying between 3 and 20 μm. We showed that although thicker sections increase the information content of tissue structures in the images, thinner sections generally perform better in providing information that can be reproduced in virtual staining. According to our results, tissue imaged in paraffin and as deparaffinized provides a good overall representation of the tissue for virtually HE-stained images. Further, using a pix2pix model, we showed that the reproduction of overall tissue histology can be clearly improved with image-to-image translation using supervised learning and pixel-wise ground truth. We also showed that virtual HE staining can be used for various tissues and used with both 20× and 40× imaging magnifications. Although the performance and methods of virtual staining need further development, our study provides evidence of the feasibility of whole slide unstained microscopy as a fast, cheap, and feasible approach to producing virtual staining of tissue histology while sparing the exact same tissue section ready for subsequent utilization with follow-up methods at single-cell resolution.

miR-32 promotes MYC-driven prostate cancer

miR-32 is an androgen receptor (AR)-regulated microRNA, expression of which is increased in castration-resistant prostate cancer (PC). We have previously shown that overexpression of miR-32 in the prostate of transgenic mice potentiates proliferation in prostate epithelium. Here, we set out to determine whether increased expression of miR-32 influences growth or phenotype in prostate adenocarcinoma in vivo. We studied transgenic mice expressing MYC oncogene (hiMYC mice) to induce tumorigenesis in the mouse prostate and discovered that transgenic overexpression of miR-32 resulted in increased tumor burden as well as a more aggressive tumor phenotype in this model. Elevated expression of miR-32 increased proliferation as assessed by Ki-67 immunohistochemistry, increased nuclear density, and higher mitotic index in the tumors. By gene expression analysis of the tumorous prostate tissue, we confirmed earlier findings that miR-32 expression regulates prostate secretome by modulating expression levels of several PC-related target genes such as Spink1, Spink5, and Msmb. Further, we identified Pdk4 as a tumor-associated miR-32 target in the mouse prostate. Expression analysis of PDK4 in human PC reveals an inverse correlation with miR-32 expression and Gleason score, a decrease in castration-resistant and metastatic tumors compared to untreated primary PC, and an association of low PDK4 expression with a shorter recurrence-free survival of patients. Although decreased PDK4 expression induces the higher metabolic activity of PC cells, induced expression of PDK4 reduces both mitotic respiration and glycolysis rates as well as inhibits cell growth. In conclusion, we show that miR-32 promotes MYC-induced prostate adenocarcinoma and identifies PDK4 as a PC-relevant metabolic target of miR-32-3p.

SPINKs in Tumors: Potential Therapeutic Targets

The serine protease inhibitor Kazal type (SPINK) family includes SPINK1-14 and is the largest branch in the serine protease inhibitor family. SPINKs play an important role in pancreatic physiology and disease, sperm maturation and capacitation, Nager syndrome, inflammation and the skin barrier. Evidence shows that the unregulated expression of SPINK1, 2, 4, 5, 6, 7, and 13 is closely related to human tumors. Different SPINKs exhibit various regulatory modes in different tumors and can be used as tumor prognostic markers. This article reviews the role of SPINK1, 2, 4, 5, 6, 7, and 13 in different human cancer processes and helps to identify new cancer treatment targets.

Spatial analysis of histology in 3D: quantification and visualization of organ and tumor level tissue environment

Histological changes in tissue are of primary importance in pathological research and diagnosis. Automated histological analysis requires ability to computationally separate pathological alterations from normal tissue. Conventional histopathological assessments are performed from individual tissue sections, leading to the loss of three-dimensional context of the tissue. Yet, the tissue context and spatial determinants are critical in several pathologies, such as in understanding growth patterns of cancer in its local environment. Here, we develop computational methods for visualization and quantitative assessment of histopathological alterations in three dimensions. First, we reconstruct the 3D representation of the whole organ from serial sectioned tissue. Then, we proceed to analyze the histological characteristics and regions of interest in 3D. As our example cases, we use whole slide images representing hematoxylin-eosin stained whole mouse prostates in a Pten+/- mouse prostate tumor model. We show that quantitative assessment of tumor sizes, shapes, and separation between spatial locations within the organ enable characterizing and grouping tumors. Further, we show that 3D visualization of tissue with computationally quantified features provides an intuitive way to observe tissue pathology. Our results underline the heterogeneity in composition and cellular organization within individual tumors. As an example, we show how prostate tumors have nuclear density gradients indicating areas of tumor growth directions and reflecting varying pressure from the surrounding tissue. The methods presented here are applicable to any tissue and different types of pathologies. This work provides a proof-of-principle for gaining a comprehensive view from histology by studying it quantitatively in 3D.

Regulation of Neuroendocrine-like Differentiation in Prostate Cancer by Non-Coding RNAs

Neuroendocrine prostate cancer (NEPC) represents a variant of prostate cancer that occurs in response to treatment resistance or, to a much lesser extent, de novo. Unravelling the molecular mechanisms behind transdifferentiation of cancer cells to neuroendocrine-like cancer cells is essential for development of new treatment opportunities. This review focuses on summarizing the role of small molecules, predominantly microRNAs, in this phenomenon. A published literature search was performed to identify microRNAs, which are reported and experimentally validated to modulate neuroendocrine markers and/or regulators and to affect the complex neuroendocrine phenotype. Next, available patients’ expression datasets were surveyed to identify deregulated microRNAs, and their effect on NEPC and prostate cancer progression is summarized. Finally, possibilities of miRNA detection and quantification in body fluids of prostate cancer patients and their possible use as liquid biopsy in prostate cancer monitoring are discussed. All the addressed clinical and experimental contexts point to an association of NEPC with upregulation of miR-375 and downregulation of miR-34a and miR-19b-3p. Together, this review provides an overview of different roles of non-coding RNAs in the emergence of neuroendocrine prostate cancer.

Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration

Background

Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualization of 3D histology data, creating a novel interface for digital pathology to aid cancer research.

Methods

Our contribution includes 3D modeling of a whole organ and embedded objects of interest, fusing the models with associated quantitative features and full resolution serial section patches, and implementing the virtual reality application. Our VR application is multi-scale in nature, covering two object levels representing different ranges of detail, namely organ level and sub-organ level. In addition, the application includes several data layers, including the measured histology image layer and multiple representations of quantitative features computed from the histology.

Results

In our interactive VR application, the user can set visualization properties, select different samples and features, and interact with various objects, which is not possible in the traditional 2D-image view used in digital pathology. In this work, we used whole mouse prostates (organ level) with prostate cancer tumors (sub-organ objects of interest) as example cases, and included quantitative histological features relevant for tumor biology in the VR model.

Conclusions

Our application enables a novel way for exploration of high-resolution, multidimensional data for biomedical research purposes, and can also be used in teaching and researcher training. Due to automated processing of the histology data, our application can be easily adopted to visualize other organs and pathologies from various origins.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08542-9.

Magic and mystery of microRNA-32

MicroRNAs (miRNAs) are a group of endogenous, small (∼22 nts in length) noncoding RNA molecules that function specifically by base pairing with the mRNA of genes and regulate gene expression at the post-transcriptional level. Alterations in miR-32 expression have been found in numerous diseases and shown to play a vital role in cell proliferation, apoptosis, oncogenesis, invasion, metastasis and drug resistance. MiR-32 has been documented as an oncomiR in the majority of related studies but has been also verified as a tumour suppressor miRNA in conflicting reports. Moreover, it has a crucial role in metabolic and cardiovascular disorders. This review provides an in-depth look into the most recent finding regarding miR-32, which is involved in the expression, regulation and functions in different diseases, especially tumours. Additionally, this review outlines novel findings suggesting that miR-32 may be useful as a noninvasive biomarker and as a targeted therapeutic in several diseases.

Expression analysis of microRNAs and their target mRNAs of testes with high and low sperm motility in domestic pigeons (Columba livia)

Sperm motility is one of the most important indicators to evaluate poultry fertility. In order to explore key molecular regulation roles related to sperm motility, we employed testicular RNA sequencing of pigeon. A total of 705 known and 385 novel microRNAs were identified. Compared with the low sperm motility group, four upregulated and two downregulated miRNAs in the high sperm motility group were identified. A total of 3567 target mRNAs were predicted and four target mRNAs were selected to validate by qPCR. The miRNA-mRNA interaction network analysis, indicated that mmu-miR-183-5p /FOXO1 and PC-3p-244994_31/CHDH pairs might affect sperm motility. GO and KEGG annotation analysis showed that target genes of differentially expressed miRNAs were related to serine/threonine kinase activity, ATP binding, Wnt and MAPK signaling pathway. The study provided a global miRNAs transcriptome of pigeon and a novel insight into the expression of the miRNAs in testes that associated with sperm motility.

MicroRNA-32 promotes ovarian cancer cell proliferation and motility by targeting SMG1

Ovarian cancer (OC) is the most lethal gynecological malignancy and one of the leading causes of cancer-related deaths among women. Metastasis is the main cause of poor prognosis in OC. MicroRNA (miRNA/miR) has been shown to play an important role in tumorigenesis and metastasis in various cancer types by affecting the expression of its targets. In the present study, the role of miR-32 (miR-32-5p) in OC was explored. Reverse transcription-quantitative PCR results showed that miR-32 expression was significantly upregulated in both OC tissues and cell lines. Inhibition of miR-32 by transfection with miR-32 inhibitor in OC cells markedly suppressed cell proliferation, migration and invasion. In addition, a luciferase assay showed that suppressor of morphogenesis in genitalia 1 (SMG1) is a direct target of miR-32, and interference in SMG1 expression with transfection of SMG1 small hairpin RNA restored miR-32-mediated OC cell proliferation, migration and invasion. Taken together, these results indicate that miR-32 may promote OC cell growth and motility by targeting SMG1. The data of the present study suggest that miR-32 may serve as a potential therapeutic target for OC treatment in the future.

Oncogenic and tumor-suppressive microRNAs in prostate cancer

MicroRNAs are known to be dysregulated in prostate cancer. These small noncoding RNAs can function as biomarkers and are involved in the biology of prostate cancer. The canonical mechanism for microRNAs is post-transcription regulation of gene expression via binding to the 3' untranslated region of mRNAs, resulting in RNA degradation and/or translational repression. Thus, oncogenic microRNAs, also known as oncomiRs, often have high expression in prostate cancer and target the mRNAs of tumor suppressors. Conversely, tumor-suppressive microRNAs have reduced expression in cancer and typically target oncogenes. Some microRNAs function outside the classical mechanism and serve to stabilize their mRNA targets. Herein, we review contemporary studies that demonstrate oncogenic and tumor-suppressive activity of microRNAs in prostate cancer.

Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach

Prostate cancer is the most common cancer type in men in Finland and second worldwide. In this paper, we analyze almost 150, 000 published papers about prostate cancer, authored by ten thousands of scientists worldwide, with an integrated text mining and computational network theory approach. We demonstrate how to integrate text mining with network analysis investigating research contributions of countries and collaborations within and between countries. Furthermore, we study the time evolution of individually and collectively studied genes. Finally, we investigate a collaboration network of Finland and compare studied genes with globally studied genes in prostate cancer genetics. Overall, our results provide a global overview of prostate cancer research in genetics. In addition, we present a specific discussion for Finland. Our results shed light on trends within the last 30 years and are useful for translational researchers within the full range from genetics to public health management and health policy.

miR-32 promotes esophageal squamous cell carcinoma metastasis by targeting CXXC5

MicroRNA-32 (miR-32) functioned as a tumor oncogene in some cancer, which control genes involved in important biological and pathological functions and facilitate the tumor growth and metastasis. However, the role of miR-32 modulates esophageal squamous cell carcinoma (ESCC) malignant transformation has not been clarified. Here, we focused on the function and the underlying molecular mechanism of miR-32 in ESCC. Results discovered a significant increased expression of miR-32 in ESCC tissues and cells. Downregulation of miR-32 inhibited the migration, invasion, adhesion of ESCC cell lines (EC9706 and KYSE450), and the levels of EMT protein in vitro. In vivo, miR-32 inhibitors decrease tumor size, tumor weight, and the number of metastatic nodules. Hematoxylin and eosin (H&E) results revealed that inhibition of miR-32 attenuate lung metastasis. Immunohistochemistry and immunofluorescence assay showed increased level of E-cadherin and decreased level of N-cadherin and Vimentin with treatment of miR-32 inhibitors. Furthermore, miR-32 targeted the 3'-untranslated region (3'-UTR) of CXXC5, and inhibited the level of mRNA and protein of CXXC5. There is a negative correlation between the expressions of CXXC5 and miR-32. Then, after EC9706 and KYSE450 cells cotransfected with si-CXXC5 and miR-32 inhibitors, the ability of cell migration, invasion, and adhesion was significantly reduced. In addition, the protein expression of EMT and TGF-β signaling was also depressed. Collectively, these data supply an insight into the positive role of miR-32 in ESCC progression and metastasis, and its biological effects may attribute the inhibition of TGF-β signaling mediated by CXXC5.