CystAnalyser: A new software tool for the automatic detection and quantification of cysts in Polycystic Kidney and Liver Disease, and other cystic disorders

OralImmunoAnalyser: a software tool for immunohistochemical assessment of oral leukoplakia using image segmentation and classification models

Oral cancer ranks sixteenth amongst types of cancer by number of deaths. Many oral cancers are developed from potentially malignant disorders such as oral leukoplakia, whose most frequent predictor is the presence of epithelial dysplasia. Immunohistochemical staining using cell proliferation biomarkers such as ki67 is a complementary technique to improve the diagnosis and prognosis of oral leukoplakia. The cell counting of these images was traditionally done manually, which is time-consuming and not very reproducible due to intra- and inter-observer variability. The software presently available is not suitable for this task. This article presents the OralImmunoAnalyser software (registered by the University of Santiago de Compostela-USC), which combines automatic image processing with a friendly graphical user interface that allows investigators to oversee and easily correct the automatically recognized cells before quantification. OralImmunoAnalyser is able to count the number of cells in three staining levels and each epithelial layer. Operating in the daily work of the Odontology Faculty, it registered a sensitivity of 64.4% and specificity of 93% for automatic cell detection, with an accuracy of 79.8% for cell classification. Although expert supervision is needed before quantification, OIA reduces the expert analysis time by 56.5% compared to manual counting, avoiding mistakes because the user can check the cells counted. Hence, the SUS questionnaire reported a mean score of 80.9, which means that the system was perceived from good to excellent. OralImmunoAnalyser is accurate, trustworthy, and easy to use in daily practice in biomedical labs. The software, for Windows and Linux, with the images used in this study, can be downloaded from https://citius.usc.es/transferencia/software/oralimmunoanalyser for research purposes upon acceptance.

Software BreastAnalyser for the semi-automatic analysis of breast cancer immunohistochemical images

Breast cancer is the most diagnosed cancer worldwide and represents the fifth cause of cancer mortality globally. It is a highly heterogeneous disease, that comprises various molecular subtypes, often diagnosed by immunohistochemistry. This technique is widely employed in basic, translational and pathological anatomy research, where it can support the oncological diagnosis, therapeutic decisions and biomarker discovery. Nevertheless, its evaluation is often qualitative, raising the need for accurate quantitation methodologies. We present the software BreastAnalyser, a valuable and reliable tool to automatically measure the area of 3,3'-diaminobenzidine tetrahydrocholoride (DAB)-brown-stained proteins detected by immunohistochemistry. BreastAnalyser also automatically counts cell nuclei and classifies them according to their DAB-brown-staining level. This is performed using sophisticated segmentation algorithms that consider intrinsic image variability and save image normalization time. BreastAnalyser has a clean, friendly and intuitive interface that allows to supervise the quantitations performed by the user, to annotate images and to unify the experts' criteria. BreastAnalyser was validated in representative human breast cancer immunohistochemistry images detecting various antigens. According to the automatic processing, the DAB-brown area was almost perfectly recognized, being the average difference between true and computer DAB-brown percentage lower than 0.7 points for all sets. The detection of nuclei allowed proper cell density relativization of the brown signal for comparison purposes between the different patients. BreastAnalyser obtained a score of 85.5 using the system usability scale questionnaire, which means that the tool is perceived as excellent by the experts. In the biomedical context, the connexin43 (Cx43) protein was found to be significantly downregulated in human core needle invasive breast cancer samples when compared to normal breast, with a trend to decrease as the subtype malignancy increased. Higher Cx43 protein levels were significantly associated to lower cancer recurrence risk in Oncotype DX-tested luminal B HER2- breast cancer tissues. BreastAnalyser and the annotated images are publically available https://citius.usc.es/transferencia/software/breastanalyser for research purposes.

AI models for automated segmentation of engineered polycystic kidney tubules

Autosomal dominant polycystic kidney disease (ADPKD) is a monogenic, rare disease, characterized by the formation of multiple cysts that grow out of the renal tubules. Despite intensive attempts to develop new drugs or repurpose existing ones, there is currently no definitive cure for ADPKD. This is primarily due to the complex and variable pathogenesis of the disease and the lack of models that can faithfully reproduce the human phenotype. Therefore, the development of models that allow automated detection of cysts' growth directly on human kidney tissue is a crucial step in the search for efficient therapeutic solutions. Artificial Intelligence methods, and deep learning algorithms in particular, can provide powerful and effective solutions to such tasks, and indeed various architectures have been proposed in the literature in recent years. Here, we comparatively review state-of-the-art deep learning segmentation models, using as a testbed a set of sequential RGB immunofluorescence images from 4 in vitro experiments with 32 engineered polycystic kidney tubules. To gain a deeper understanding of the detection process, we implemented both pixel-wise and cyst-wise performance metrics to evaluate the algorithms. Overall, two models stand out as the best performing, namely UNet++ and UACANet: the latter uses a self-attention mechanism introducing some explainability aspects that can be further exploited in future developments, thus making it the most promising algorithm to build upon towards a more refined cyst-detection platform. UACANet model achieves a cyst-wise Intersection over Union of 0.83, 0.91 for Recall, and 0.92 for Precision when applied to detect large-size cysts. On all-size cysts, UACANet averages at 0.624 pixel-wise Intersection over Union. The code to reproduce all results is freely available in a public GitHub repository.

Ciliary ARL13B inhibits developmental kidney cystogenesis in mouse

ARL13B is a small GTPase enriched in cilia. Deletion of Arl13b in mouse kidney results in renal cysts and an associated absence of primary cilia. Similarly, ablation of cilia leads to kidney cysts. To investigate whether ARL13B functions from within cilia to direct kidney development, we examined kidneys of mice expressing an engineered cilia-excluded ARL13B variant, ARL13BV358A. These mice retained renal cilia and developed cystic kidneys. Because ARL13B functions as a guanine nucleotide exchange factor (GEF) for ARL3, we examined kidneys of mice expressing an ARL13B variant that lacks ARL3 GEF activity, ARL13BR79Q. We found normal kidney development with no evidence of cysts in these mice. Taken together, our results show that ARL13B functions within cilia to inhibit renal cystogenesis during mouse development, and that this function does not depend on its role as a GEF for ARL3.

Ciliary ARL13B inhibits developmental kidney cystogenesis in mouse

ARL13B is a small GTPase enriched in cilia. Deletion of Arl13b in mouse kidney results in renal cysts and an associated absence of primary cilia. Similarly, ablation of cilia leads to kidney cysts. To investigate whether ARL13B functions from within cilia to direct kidney development, we examined kidneys of mice expressing an engineered cilia-excluded ARL13B variant, ARL13BV358A. These mice retained renal cilia and developed cystic kidneys. Because ARL13B functions as a guanine nucleotide exchange factor (GEF) for ARL3, we examined kidneys of mice expressing an ARL13B variant that lacks ARL3 GEF activity, ARL13BR79Q. We found normal kidney development with no evidence of cysts in these mice. Taken together, our results show that ARL13B functions within cilia to inhibit renal cystogenesis during mouse development, and that this function does not depend on its role as a GEF for ARL3.

Pharmacological intervention of the FGF-PTH axis as a potential therapeutic for craniofacial ciliopathies

Ciliopathies represent a disease class characterized by a broad range of phenotypes including polycystic kidneys and skeletal anomalies. Ciliopathic skeletal phenotypes are among the most common and most difficult to treat due to a poor understanding of the pathological mechanisms leading to disease. Using an avian model (talpid2) for a human ciliopathy with both kidney and skeletal anomalies (Orofaciodigital syndrome 14), we identified disruptions in the FGF23-PTH axis that resulted in reduced calcium uptake in the developing mandible and subsequent micrognathia. While pharmacological intervention with the FDA-approved pan-FGFR inhibitor AZD4547 alone rescued expression of the FGF target Sprouty2, it did not significantly rescue micrognathia. In contrast, treatment with a cocktail of AZD4547 and Teriparatide acetate, a PTH agonist and FDA-approved treatment for osteoporosis, resulted in a molecular, cellular, and phenotypic rescue of ciliopathic micrognathia in talpid2 mutants. Together, these data provide novel insight into pathological molecular mechanisms associated with ciliopathic skeletal phenotypes and a potential therapeutic strategy for a pleiotropic disease class with limited to no treatment options.

Quantitative Proteomic Study Unmasks Fibrinogen Pathway in Polycystic Liver Disease

(1) Background: Polycystic liver disease (PLD) is a heterogeneous group of congenital disorders characterized by bile duct dilatation and cyst development derived from cholangiocytes. Nevertheless, the cystogenesis mechanism is currently unknown and the PLD treatment is limited to liver transplantation. Novel and efficient therapeutic approaches are th6us needed. In this context, the present work has a principal aim to find novel molecular pathways, as well as new therapeutic targets, involved in the hepatic cystogenesis process. (2) Methods: Quantitative proteomics based on SWATH-MS technology were performed comparing hepatic proteomes of Wild Type and mutant/polycystic livers in a polycystic kidney disease (PKD) murine model (Pkd1cond/cond;Tam-Cre-/+). (3) Results: We identified several proteins altered in abundance, with two-fold cut-off up-regulation or down-regulation and an adjusted p-value significantly related to hepatic cystogenesis. Then, we performed enrichment and a protein-protein analysis identifying a cluster focused on hepatic fibrinogens. Finally, we validated a selection of targets by RT-qPCR, Western blotting and immunohistochemistry, finding a high correlation with quantitative proteomics data and validating the fibrinogen complex. (4) Conclusions: This work identified a novel molecular pathway in cystic liver disease, highlighting the fibrinogen complex as a possible new therapeutic target for PLD.

TWEAK Signaling Pathway Blockade Slows Cyst Growth and Disease Progression in Autosomal Dominant Polycystic Kidney Disease

BACKGROUND

In autosomal dominant polycystic kidney disease (ADPKD), cyst development and enlargement lead to ESKD. Macrophage recruitment and interstitial inflammation promote cyst growth. TWEAK is a TNF superfamily (TNFSF) cytokine that regulates inflammatory responses, cell proliferation, and cell death, and its receptor Fn14 (TNFRSF12a) is expressed in macrophage and nephron epithelia.

METHODS

To evaluate the role of the TWEAK signaling pathway in cystic disease, we evaluated Fn14 expression in human and in an orthologous murine model of ADPKD. We also explored the cystic response to TWEAK signaling pathway activation and inhibition by peritoneal injection.

RESULTS

Meta-analysis of published animal-model data of cystic disease reveals mRNA upregulation of several components of the TWEAK signaling pathway. We also observed that TWEAK and Fn14 were overexpressed in mouse ADPKD kidney cysts, and TWEAK was significantly high in urine and cystic fluid from patients with ADPKD. TWEAK administration induced cystogenesis and increased cystic growth, worsening the phenotype in a murine ADPKD model. Anti-TWEAK antibodies significantly slowed the progression of ADPKD, preserved renal function, and improved survival. Furthermore, the anti-TWEAK cystogenesis reduction is related to decreased cell proliferation-related MAPK signaling, decreased NF-κB pathway activation, a slight reduction of fibrosis and apoptosis, and an indirect decrease in macrophage recruitment.

CONCLUSIONS

This study identifies the TWEAK signaling pathway as a new disease mechanism involved in cystogenesis and cystic growth and may lead to a new therapeutic approach in ADPKD.