Ischemia-Reperfusion Injury in Kidney Transplantation: Mechanisms and Potential Therapeutic Targets.

Kidney transplantation offers a longer life expectancy and a better quality of life than dialysis to patients with end-stage kidney disease. Ischemia-reperfusion injury (IRI) is thought to be a cornerstone in delayed or reduced graft function and increases the risk of rejection by triggering the immunogenicity of the organ. IRI is an unavoidable event that happens when the blood supply is temporarily reduced and then restored to an organ. IRI is the result of several biological pathways, such as transcriptional reprogramming, apoptosis and necrosis, innate and adaptive immune responses, and endothelial dysfunction. Tubular cells mostly depend on fatty acid (FA) ß-oxidation for energy production since more ATP molecules are yielded per substrate molecule than glucose oxidation. Upon ischemia-reperfusion damage, the innate and adaptive immune system activates to achieve tissue clearance and repair. Several cells, cytokines, enzymes, receptors, and ligands are known to take part in these events. The complement cascade might start even before organ procurement in deceased donors. However, additional experimental and clinical data are required to better understand the pathogenic events that take place during this complex process.

The Role of MUC1 in Renal Cell Carcinoma.

Mucins are a family of high-molecular-weight glycoproteins. MUC1 is widely studied for its role in distinct types of cancers. In many human epithelial malignancies, MUC1 is frequently overexpressed, and its intracellular activities are crucial for cell biology. MUC1 overexpression can enhance cancer cell proliferation by modulating cell metabolism. When epithelial cells lose their tight connections, due to the loss of polarity, the mucins become dispersed on both sides of the epithelial membrane, leading to an abnormal mucin interactome with the membrane. Tumor-related MUC1 exhibits certain features, such as loss of apical localization and aberrant glycosylation that might cause the formation of tumor-related antigen epitopes. Renal cell carcinoma (RCC) accounts for approximately 3% of adult malignancies and it is the most common kidney cancer. The exact role of MUC1 in this tumor is unknown. Evidence suggests that it may play a role in several oncogenic pathways, including proliferation, metabolic reprogramming, chemoresistance, and angiogenesis. The purpose of this review is to explore the role of MUC1 and the meaning of its overexpression in epithelial tumors and in particular in RCC.

Complement System and the Kidney: Its Role in Renal Diseases, Kidney Transplantation and Renal Cell Carcinoma.

The crosstalk among the complement system, immune cells, and mediators of inflammation provides an efficient mechanism to protect the organism against infections and support the repair of damaged tissues. Alterations in this complex machinery play a role in the pathogenesis of different diseases. Core complement proteins C3 and C5, their activation fragments, their receptors, and their regulators have been shown to be active intracellularly as the complosome. The kidney is particularly vulnerable to complement-induced damage, and emerging findings have revealed the role of complement system dysregulation in a wide range of kidney disorders, including glomerulopathies and ischemia-reperfusion injury during kidney transplantation. Different studies have shown that activation of the complement system is an important component of tumorigenesis and its elements have been proved to be present in the TME of various human malignancies. The role of the complement system in renal cell carcinoma (RCC) has been recently explored. Clear cell and papillary RCC upregulate most of the complement genes relative to normal kidney tissue. The aim of this narrative review is to provide novel insights into the role of complement in kidney disorders.

Cancer Stem Cells in Renal Cell Carcinoma: Origins and Biomarkers.

The term "cancer stem cell" (CSC) refers to a cancer cell with the following features: clonogenic ability, the expression of stem cell markers, differentiation into cells of different lineages, growth in nonadhesive spheroids, and the in vivo ability to generate serially transplantable tumors that reflect the heterogeneity of primary cancers (tumorigenicity). According to this model, CSCs may arise from normal stem cells, progenitor cells, and/or differentiated cells because of striking genetic/epigenetic mutations or from the fusion of tissue-specific stem cells with circulating bone marrow stem cells (BMSCs). CSCs use signaling pathways similar to those controlling cell fate during early embryogenesis (Notch, Wnt, Hedgehog, bone morphogenetic proteins (BMPs), fibroblast growth factors, leukemia inhibitory factor, and transforming growth factor-ß). Recent studies identified a subpopulation of CD133+/CD24+ cells from ccRCC specimens that displayed self-renewal ability and clonogenic multipotency. The development of agents targeting CSC signaling-specific pathways and not only surface proteins may ultimately become of utmost importance for patients with RCC.

Cellular and Molecular Players in the Tumor Microenvironment of Renal Cell Carcinoma.

Globally, clear-cell renal cell carcinoma (ccRCC) represents the most prevalent type of kidney cancer. Surgery plays a key role in the treatment of this cancer, although one third of patients are diagnosed with metastatic ccRCC and about 25% of patients will develop a recurrence after nephrectomy with curative intent. Molecular-target-based agents, such as tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), are recommended for advanced cancers. In addition to cancer cells, the tumor microenvironment (TME) includes non-malignant cell types embedded in an altered extracellular matrix (ECM). The evidence confirms that interactions among cancer cells and TME elements exist and are thought to play crucial roles in the development of cancer, making them promising therapeutic targets. In the TME, an unfavorable pH, waste product accumulation, and competition for nutrients between cancer and immune cells may be regarded as further possible mechanisms of immune escape. To enhance immunotherapies and reduce resistance, it is crucial first to understand how the immune cells work and interact with cancer and other cancer-associated cells in such a complex tumor microenvironment.

Immune Checkpoint Inhibitors in Renal Cell Carcinoma: Molecular Basis and Rationale for Their Use in Clinical Practice.

Renal cell carcinoma (RCC) is the seventh most common cancer in men and the ninth most common cancer in women worldwide. There is plenty of evidence about the role of the immune system in surveillance against tumors. Thanks to a better understanding of immunosurveillance mechanisms, immunotherapy has been introduced as a promising cancer treatment in recent years. Renal cell carcinoma (RCC) has long been thought chemoresistant but highly immunogenic. Considering that up to 30% of the patients present metastatic disease at diagnosis, and around 20-30% of patients undergoing surgery will suffer recurrence, we need to identify novel therapeutic targets. The introduction of immune checkpoint inhibitors (ICIs) in the clinical management of RCC has revolutionized the therapeutic approach against this tumor. Several clinical trials have shown that therapy with ICIs in combination or ICIs and the tyrosine kinase inhibitor has a very good response rate. In this review article we summarize the mechanisms of immunity modulation and immune checkpoints in RCC and discuss the potential therapeutic strategies in renal cancer treatment.

Assessing the cost-effectiveness of waiting list reduction strategies for a breast radiology department: a real-life case study.

BACKGROUND: A timely diagnosis is essential for improving breast cancer patients' survival and designing targeted therapeutic plans. For this purpose, the screening timing, as well as the related waiting lists, are decisive. Nonetheless, even in economically advanced countries, breast cancer radiology centres fail in providing effective screening programs. Actually, a careful hospital governance should encourage waiting lists reduction programs, not only for improving patients care, but also for minimizing costs associated with the treatment of advanced cancers. Thus, in this work, we proposed a model to evaluate several scenarios for an optimal distribution of the resources invested in a Department of Breast Radiodiagnosis. MATERIALS AND METHODS: Particularly, we performed a cost-benefit analysis as a technology assessment method to estimate both costs and health effects of the screening program, to maximise both benefits related to the quality of care and resources employed by the Department of Breast Radiodiagnosis of Istituto Tumori "Giovanni Paolo II" of Bari in 2019. Specifically, we determined the Quality-Adjusted Life Year (QALY) for estimating health outcomes, in terms of usefulness of two hypothetical screening strategies with respect to the current one. While the first hypothetical strategy adds one team made up of a doctor, a technician and a nurse, along with an ultrasound and a mammograph, the second one adds two afternoon teams. RESULTS: This study showed that the most cost-effective incremental ratio could be achieved by reducing current waiting lists from 32 to 16 months. Finally, our analysis revealed that this strategy would also allow to include more people in the screening programs (60,000 patients in 3 years).

MUC1 Expression Affects the Immunoflogosis in Renal Cell Carcinoma Microenvironment through Complement System Activation and Immune Infiltrate Modulation.

Mucin1 (MUC1), a glycoprotein associated with an aggressive cancer phenotype and chemoresistance, is aberrantly overexpressed in a subset of clear cell renal cell carcinoma (ccRCC). Recent studies suggest that MUC1 plays a role in modulating cancer cell metabolism, but its role in regulating immunoflogosis in the tumor microenvironment remains poorly understood. In a previous study, we showed that pentraxin-3 (PTX3) can affect the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system (C1q) and releasing proangiogenic factors (C3a, C5a). In this scenario, we evaluated the PTX3 expression and analyzed the potential role of complement system activation on tumor site and immune microenvironment modulation, stratifying samples in tumors with high (MUC1H) versus tumors with low MUC1 expression (MUC1L). We found that PTX3 tissue expression was significantly higher in MUC1H ccRCC. In addition, C1q deposition and the expressions of CD59, C3aR, and C5aR were extensively present in MUC1H ccRCC tissue samples and colocalized with PTX3. Finally, MUC1 expression was associated with an increased number of infiltrating mast cells, M2-macrophage, and IDO1+ cells, and a reduced number of CD8+ T cells. Taken together, our results suggest that expression of MUC1 can modulate the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system and regulating the immune infiltrate, promoting an immune-silent microenvironment.

The dark side of lipid metabolism in prostate and renal carcinoma: novel insights into molecular diagnostic and biomarker discovery.

INTRODUCTION: Lipidomics focuses on the in-depth analysis of lipids, which are crucial macromolecules involved in a wide range of metabolic pathways. The increased intracellular accumulation of different classes of lipids in renal cell carcinoma (RCC) and prostate cancer (PCa) cells may be caused by elevated absorption or by increased de novo lipogenesis as a consequence of lipid metabolism reprogramming. The involvement of cholesterol metabolism in cancer's aberrant pathways has also been demonstrated. AREAS COVERED: This review provides an update on the most important lipidomics studies and applications in RCC and PCa, with a particular focus on how knowledge of aberrant lipid pathways may be used to identify biomarkers and novel therapeutic targets. In addition, the application of this methodologies have led to novel cancer subtypes identification and patient's risk stratification. Tracking tumor progression using specific biofluid metabolite profiles offers a huge translational opportunity for urological malignancies. EXPERT OPINION: Lipidomics is a promising branch of 'omics' approach and should include in next decade new standardized analysis methods and randomized clinical trials in order to reach the aim to use this high-throughput technique in patient-tailored therapy perspective.

A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients.

The application of deep learning on whole-slide histological images (WSIs) can reveal insights for clinical and basic tumor science investigations. Finding quantitative imaging biomarkers from WSIs directly for the prediction of disease-free survival (DFS) in stage I-III melanoma patients is crucial to optimize patient management. In this study, we designed a deep learning-based model with the aim of learning prognostic biomarkers from WSIs to predict 1-year DFS in cutaneous melanoma patients. First, WSIs referred to a cohort of 43 patients (31 DF cases, 12 non-DF cases) from the Clinical Proteomic Tumor Analysis Consortium Cutaneous Melanoma (CPTAC-CM) public database were firstly annotated by our expert pathologists and then automatically split into crops, which were later employed to train and validate the proposed model using a fivefold cross-validation scheme for 5 rounds. Then, the model was further validated on WSIs related to an independent test, i.e. a validation cohort of 11 melanoma patients (8 DF cases, 3 non-DF cases), whose data were collected from Istituto Tumori 'Giovanni Paolo II' in Bari, Italy. The quantitative imaging biomarkers extracted by the proposed model showed prognostic power, achieving a median AUC value of 69.5% and a median accuracy of 72.7% on the public cohort of patients. These results remained comparable on the validation cohort of patients with an AUC value of 66.7% and an accuracy value of 72.7%, respectively. This work is contributing to the recently undertaken investigation on how treat features extracted from raw WSIs to fulfil prognostic tasks involving melanoma patients. The promising results make this study as a valuable basis for future research investigation on wider cohorts of patients referred to our Institute.