Search Results (4,815)

Background and Objectives: The worldwide incidence of renal cell carcinoma (RCC) rose by 22% between 2012 and 2022. In Australia, RCC accounted for 2.8% of all cancer diagnoses and contributing to 1.8% of cancer-related deaths. Identification of RCC biomarkers may aid in diagnosis and management. Methods: A systematic review of immunohistochemical markers of RCC studies published between 1990 and 2019 was undertaken to select candidate biomarkers of RCC. Immunohistochemical staining of 73 clear cell RCC tumors and paired normal tissue was undertaken using selected markers. Semi-quantitative and quantitative analysis of staining intensity between paired samples was undertaken to evaluate utility as potential biomarkers, using Chi-square tests and paired t-tests for analysis. As an exploratory analysis, staining intensity was also compared on clinical/demographic variables using linear and logistic regression. Results: There were 123 candidate biomarkers identified in 91 studies. Four candidate markers were selected for further investigation: aminopeptidase A (APA)/cluster of differentiation (CD)249, aminopeptidase N (APN)/CD13, gamma-glutamyl transferase (GGT), and neuron-specific enolase (NSE). APA, GGT, and APN all demonstrated reduced staining intensity in the tumor compared with normal tissue (p < 0.001 for all). NSE demonstrated a statistically significant increase in expression in tumor compared with normal tissue (p < 0.001), and this was more pronounced in patients aged >60 years (p = 0.038). Conclusions: The utility of APA, APN, and GGT as diagnostic biomarkers in clear cell RCC is limited. NSE may have some role as a biomarker for clear cell RCC, particularly among older patients; however, further investigation is required. Full article

Background/Objectives: Breast cancer was the leading cause of malignant tumors among women in 2022. About two-thirds of breast cancer cases are hormone-receptor-positive. In these patients, aromatase inhibitors are a mainstay of treatment, but associated musculoskeletal symptoms can negatively affect patient compliance. Aromatase-inhibitor-induced carpal tunnel syndrome represents one of the main causes of aromatase inhibitor discontinuation, with a non-compliance rate of up to 67%, potentially leading to increased cancer mortality. This study investigates estrogen receptor expression in aromatase-inhibitor-induced carpal tunnel syndrome tissues, in order to better define its etiopathogenesis and derive preventive or therapeutic measures that can improve aromatase inhibitor patient compliance. To our knowledge, there is no study on this subject in the literature. Methods: Between 2023 and 2024, we recruited 14 patients at the Jewish Hospital of Rome, including seven patients with aromatase-inhibitor-induced carpal tunnel syndrome (study group) and seven with postmenopausal idiopathic carpal tunnel syndrome (control group). Each patient was evaluated based on a clinical visit, a questionnaire, instrumental exams, and serum hormone dosages and were treated with open carpal tunnel release surgery, during which transverse carpal ligament and flexor tenosynovium samples were collected. For immunohistochemical experiments, sections were treated with anti-estrogen receptor α and anti-estrogen receptor β antibodies. Results: The immunohistochemical features in the study and control groups were similar, demonstrating that tissues affected by aromatase-inhibitor-induced carpal tunnel syndrome are targets of direct estrogen action and that estrogen deprivation is correlated with disease etiogenesis. Surgery was effective in patient treatment. Conclusions: Aromatase-inhibitor-induced carpal tunnel syndrome represents a newly defined form of the disease. This syndrome represents one of the main causes of aromatase inhibitor discontinuation, due to its negative impact on the patient’s quality of life. The identification by clinicians of aromatase inhibitor use as a possible risk factor for carpal tunnel syndrome development is of essential importance, as early diagnosis and prompt management can improve patient compliance and overall breast cancer treatment outcomes. Full article

Background/Objectives: In recent years, lipids have emerged as critical regulators of different disease processes, being involved in cancer pathogenesis, progression, and outcome. Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) has significantly expanded the technology’s reach, enabling spatially resolved profiling of lipids directly from tissue, including formalin-fixed paraffin-embedded (FFPE) specimens. In this context, MALDI matrix selection is crucial for lipid extraction and ionization, influencing key aspects such as molecular coverage and sensitivity, especially in such specimens with already depleted lipid content. Thus, in this work, we aim to explore the feasibility of mapping lipid species in FFPE clinical samples with MALDI-MSI using 6-aza-2-thiothymine (ATT) as a matrix of choice. Methods: To do so, ATT performances were first compared to those two other matrices commonly used for lipidomic analyses, 2′,5′-dihydroxybenzoic acid (DHB) and Norharmane (NOR), on lipid standards. Results: As a proof-of-concept, we then assessed ATT’s performance for the MALDI-MSI analysis of lipids in FFPE brain sections, both in positive and negative ion modes, comparing results with those obtained from other commonly used dual-polarity matrices. In this context, ATT enabled the putative annotation of 98 lipids while maintaining a well-balanced detection of glycerophospholipids (60.2%) and sphingolipids (32.7%) in positive ion mode. It outperformed both DHB and NOR in the identification of glycolipids (3%) and fatty acids (4%). Additionally, ATT exceeded DHB in terms of total lipid count (62 vs. 21) and class diversity and demonstrated performance comparable to NOR in negative ion mode. Moreover, ATT was applied to a FFPE glioblastoma tissue microarray (TMA) evaluating the ability of this matrix to reveal biologically relevant lipid features capable of distinguishing normal brain tissue from glioblastoma regions. Conclusions: Altogether, the results presented in this work suggest that ATT is a suitable matrix for pathology imaging applications, even at higher lateral resolutions of 20 μm, not only for proteomic but also for lipidomic analysis. This could enable the use of the same matrix type for the analysis of both lipids and peptides on the same tissue section, offering a unique strategic advantage for multi-omics studies, while also supporting acquisition in both positive and negative ionization modes. Full article

To deliver the most effective cancer treatment, clinicians require rapid and accurate diagnoses that delineate tumor type, stage, and prognosis. Consequently, minimizing the need for repetitive and invasive procedures like biopsies and myelograms, along with their associated risks, is a critical challenge. Non-invasive monitoring offers a promising avenue for tumor detection, screening, and prognostication. While the identification of oncogenes and biomarkers from circulating tumor cells or tissue biopsies is currently standard practice for cancer diagnosis and classification, accumulating evidence underscores the significant role of epigenetics in regulating stem cell fate, including proliferation, self-renewal, and malignant transformation. This highlights the importance of analyzing the methylome, exosomes, and circulating RNA for detecting cellular transformation. The development of diagnostic assays that integrate liquid biopsies with epigenetic analysis holds immense potential for revolutionizing tumor management by enabling rapid, non-invasive diagnosis, real-time monitoring, and personalized treatment decisions. This review covers current studies exploring the use of epigenetic regulation, specifically the methylome and circulating RNA, as diagnostic tools derived from liquid biopsies. This approach shows promise in facilitating the differentiation between primary central nervous system lymphoma and other central nervous system tumors and may enable the detection and monitoring of acute myeloid/lymphoid leukemia. We also discuss the current limitations hindering the rapid clinical translation of these technologies. Full article

Cancer is a major global health issue, with rising incidence rates highlighting the urgent need for more effective treatments. Despite advances in cancer therapy, challenges such as adverse effects and limitations of existing treatments remain. Immunotherapy, which harnesses the body’s immune system to target cancer cells, offers promising solutions. Gamma delta (γδ) T cells are noteworthy due to their potent ability to kill various cancer cells without needing conventional antigen presentation. Recent studies have focused on the role of γδ T cells in α-galactosylceramide (α-GalCer)-mediated immunity, opening new possibilities for cancer immunotherapy. We engineered humanized T cell receptor (HuTCR)-T1 γδ mice by replacing mouse sequences with human counterparts. This study investigates the cytotoxic activity of humanized γδ T cells against several human cancer cell lines (A431, HT-29, K562, and Daudi) in vitro, aiming to elucidate mechanisms underlying their anticancer efficacy. Human cancer cells were co-cultured with humanized γδ T cells, with and without α-GalCer, for 24 h. The humanized γδ T cells showed enhanced cytotoxicity across all tested cancer cell lines compared to wild-type γδ T cells. Additionally, γδ T cells from HuTCR-T1 mice exhibited higher levels of anticancer cytokines (IFN-γ, TNF-α, and IL-17) and Granzyme B, indicating their potential as potent mediators of anticancer immune responses. Blocking γδ T cells’ cytotoxicity confirmed their γδ-mediated function. These findings represent a significant step in preclinical development of γδ T cell-based cancer immunotherapies, providing insights into their mechanisms of action, optimization of therapeutic strategies, and identification of predictive biomarkers for clinical application. Full article

High-grade serous ovarian cancer (HGSC) is a heterogeneous disease. RNA sequencing (RNAseq) of bulk solid tissue is of limited use in these populations due to heterogeneity. Single-cell RNA-seq (scRNA-seq) allows for the identification of diverse genetic compositions of heterogeneous cell populations. New computational methodologies are now available that use scRNAseq results to estimate cell type proportions in bulk RNAseq data. We performed bulk RNA-seq gene expression analysis on 112 HGSC specimens and 12 benign fallopian tube (FT) controls. We identified several publicly available scRNAseq datasets for use as annotation and reference datasets. Deconvolution was performed with MUlti-Subject SIngle Cell Deconvolution (MuSiC) to estimate cell type proportions in the bulk RNA-seq data. Datasets from the Cancer Genome Atlas (TCGA). HGSC repositories were also evaluated. Clinical variables and percentages of cell types were compared for differences in clinical outcomes and treatment results. Pathway enrichment analysis was also performed. Different annotations for referenced scRNA-seq datasets used for deconvolution of bulk RNA-seq data revealed different cellular proportions that were significantly associated with clinical outcomes; for example, higher proportions of macrophages were associated with a better response to primary chemotherapy. Our deconvolution study of bulk RNAseq HGSC samples identified cell populations within the tumor that may be associated with some of the observed clinical outcomes. Full article

Prostate cancer is among the most prevalent malignancies in men worldwide, underscoring the need for early and accurate diagnostic tools. This study presents a proof-of-concept and pilot clinical validation of a novel bioelectric impedance-based biosensor for the detection of prostate-specific antigen (PSA) in human serum. The system integrates Molecular Identification through Membrane Engineering (MIME) with the xCELLigence real-time cell analysis platform, employing Vero cells electroinserted with anti-PSA antibodies. Optimization experiments identified 15,000 cells/well as the optimal configuration for impedance response. The biosensor exhibited specific, concentration-dependent changes in impedance upon exposure to PSA standard solutions and demonstrated significant differentiation between PSA-positive and PSA-negative human serum samples relative to the clinical threshold of 4 ng/mL. The biosensor offered rapid results within one minute, unlike standard immunoradiometric assay (IRMA), while showing strong diagnostic agreement. The system’s specificity, sensitivity, and reproducibility support its potential for integration into point-of-care screening workflows. This bioelectric assay represents one of the fastest PSA detection approaches reported to date and offers a promising solution for reducing overdiagnosis while improving clinical decision-making and patient outcomes. Full article

Background: Breast and hematological cancer treatments, especially with anthracyclines, have been shown to be associated with an increased risk of cardiotoxicity (CTX). An accurate prediction of cardiotoxicity risk and early detection of myocardial injury may allow for effective cardioprotection to be instituted and tailored to reverse cardiac dysfunction and prevent the discontinuation of essential cancer treatments. Objectives: The PRoactive Evaluation of Function to Evade Cardio Toxicity (PREFECT) study sought to evaluate the ability of fast-strain-encoded (F-SENC) cardiac magnetic resonance imaging (CMR) and 2D echocardiography (2D Echo) to stratify patients at risk of CTX prior to initiating cancer treatment, detect early signs of cardiac dysfunction, including subclinical CTX (sub-CTX) and CTX, and monitor for recovery (REC) during cardioprotective therapy. Methods: Fifty-nine patients with breast cancer or lymphoma were prospectively monitored for CTX with F-SENC CMR and 2D Echo over at least 1 year for evidence of cardiac dysfunction during anthracycline based chemotherapy. F-SENC CMR also monitored myocardial deformation in 37 left ventricular (LV) segments to obtain a MyoHealth risk score based on both longitudinal and circumferential strain. Sub-CTX and CTX were classified based on pre-specified cardiotoxicity definitions. Results: CTX was observed in 9/59 (15%) and sub-CTX in 24/59 (41%) patients undergoing chemotherapy. F-SENC CMR parameters at baseline predicted CTX with a lower LVEF (57 ± 5% vs. 61 ± 5% for all, p = 0.05), as well as a lower MyoHealth (70 ± 9 vs. 79 ± 11 for all, p = 0.004) and a worse global circumferential strain (GCS) (−18 ± 1 vs. −20 ± 1 for all, p < 0.001). Pre-chemotherapy MyoHealth had a higher accuracy in predicting the development of CTX compared to CMR LVEF and 2D Echo LVEF (AUC = 0.85, 0.69, and 0.57, respectively). The 2D Echo parameters on baseline imaging did not stratify CTX risk. F-SENC CMR obtained good or excellent images in 320/322 (99.4%) scans. During cancer treatment, MyoHealth had a high accuracy of detecting sub-CTX or CTX (AUC = 0.950), and the highest log likelihood ratio (indicating a higher probability of detecting CTX) followed by F-SENC GLS and F-SENC GCS. CMR LVEF and CMR LV stroke volume index (LVSVI) also significantly worsened in patients developing CTX during cancer treatment. Conclusions: F-SENC CMR provided a reliable and accurate assessment of myocardial function during anthracycline-based chemotherapy, and demonstrated accurate early detection of CTX. In addition, MyoHealth allows for the robust identification of patients at risk for CTX prior to treatment with higher accuracy than LVEF. Full article

Aizoon africanum (L.) Klak (Synonym Galenia africana L.) is traditionally used for a variety of medicinal purposes; however, it has been reported to cause liver damage and severe ascites, particularly in sheep and Angora goats in the arid regions of the Western Cape. This study explores its cytotoxic properties to identify potential cytotoxic compound(s) in the plant. The methanolic extract of A. africanum was re-investigated and subjected to various chromatographic techniques, including preparative HPLC, resulting in the isolation of eight compounds (1–8). Structural elucidation was primarily based on NMR data. Among the isolated compounds, four were flavanones, one was a flavonone, and three were chalcones. Notably, compound 8 was identified as a new chalcone, while compounds 2 and 3 were reported for the first time from this plant. The toxicity of these isolated compounds was evaluated against the HepG2 and SH-SY5Y cancer cell lines using the MTT assay. We further investigated markers of cell death using spectrophotometric and luminometric methods. Among the isolated compounds, 7 and 8 exhibited cytotoxic activities within the range of 3.0–20.0 µg/mL. Notably, the compounds demonstrated greater cytotoxicity towards liver-derived HepG2 cells compared to the neuronal SH-SY5Y cell line. Compound 7 (2′,4′-dihydroxychalcone) was identified as inducing apoptosis through the intrinsic pathway without causing overt necrosis. The findings indicate that the phytochemicals derived from A. africanum exhibit differential cytotoxic effects based on cell type, suggesting potential for developing novel anticancer agents, particularly compound 7. Additionally, the identification of compound 8 provides insight into the liver toxicity of this plant observed in sheep in South Africa. Full article

Cutaneous malignant melanoma is an extraordinarily aggressive and heterogeneous cancer that contains a small subpopulation of tumor stem cells (CSCs) responsible for tumor initiation, metastasis, and recurrence. Identification and characterization of CSCs in melanoma is challenging due to tumor heterogeneity and the lack of specific markers (CD271, ABCB5, ALDH, Nanog) and the ability of cells to dynamically change their phenotype. Phenotype-maintaining signaling pathways (Wnt/β-catenin, Notch, Hedgehog, HIF-1) promote self-renewal, treatment resistance, and epithelial–mesenchymal transitions. Tumor plasticity reflects the ability of differentiated cells to acquire stem-like traits and phenotypic flexibility under stress conditions. The interaction of CSCs with the tumor microenvironment accelerates disease progression: they induce the formation of cancer-associated fibroblasts (CAFs) and neo-angiogenesis, extracellular matrix remodeling, and recruitment of immunosuppressive cells, facilitating immune evasion. Emerging therapeutic strategies include immunotherapy (immune checkpoint inhibitors), epigenetic inhibitors, and nanotechnologies (targeted nanoparticles) for delivery of chemotherapeutic agents. Understanding the role of CSCs and tumor plasticity paves the way for more effective innovative therapies against melanoma. Full article

Mitomycin C (MMC) is a widely employed chemotherapeutic agent, particularly in non-muscle invasive bladder cancer (NMIBC), where it functions by inducing DNA cross-linking and promoting tumor cell apoptosis. However, the tumor microenvironment (TME) significantly influences the therapeutic efficacy of MMC. Among the key regulators within the TME, the complement system and the coagulation pathway play a crucial role in modulating immune responses to cancer therapies, including MMC. This article explores the interaction between platinum nanoparticles (PtNPs) with human serum (HS) of NMIBC patients (T1 and Ta subtypes) at three different points: before the chemotherapy instillation of MMC (t₀) and three (t₃) and six months (t₆) after the treatment with MMC. This novel nanoproteomic strategy allowed the identification of a TME proteomic signature associated with the response to MMC treatment. Importantly, two proteins involved in the immune response were found to be deregulated across all patients (T1 and Ta subtypes) during MMC treatment: prothrombin (F2) downregulated and complement component C7 (C7) upregulated. By understanding how these biomarker proteins interact with MMC treatment, novel therapeutic strategies can be developed to enhance treatment outcomes and overcome resistance in NMIBC. Full article

Cancer metabolic reprogramming plays a critical role in tumor progression and therapeutic resistance, underscoring the need for advanced analytical strategies. Metabolomics, leveraging mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, offers a comprehensive and functional readout of tumor biochemistry. By enabling both targeted metabolite quantification and untargeted profiling, metabolomics captures the dynamic metabolic alterations associated with cancer. The integration of metabolomics with machine learning (ML) approaches further enhances the interpretation of these complex, high-dimensional datasets, providing powerful insights into cancer biology from biomarker discovery to therapeutic targeting. This review systematically examines the transformative role of ML in cancer metabolomics. We discuss how various ML methodologies—including supervised algorithms (e.g., Support Vector Machine, Random Forest), unsupervised techniques (e.g., Principal Component Analysis, t-SNE), and deep learning frameworks—are advancing cancer research. Specifically, we highlight three major applications of ML–metabolomics integration: (1) cancer subtyping, exemplified by the use of Similarity Network Fusion (SNF) and LASSO regression to classify triple-negative breast cancer into subtypes with distinct survival outcomes; (2) biomarker discovery, where Random Forest and Partial Least Squares Discriminant Analysis (PLS-DA) models have achieved >90% accuracy in detecting breast and colorectal cancers through biofluid metabolomics; and (3) prognostic modeling, demonstrated by the identification of race-specific metabolic signatures in breast cancer and the prediction of clinical outcomes in lung and ovarian cancers. Beyond these areas, we explore applications across prostate, thyroid, and pancreatic cancers, where ML-driven metabolomics is contributing to earlier detection, improved risk stratification, and personalized treatment planning. We also address critical challenges, including issues of data quality (e.g., batch effects, missing values), model interpretability, and barriers to clinical translation. Emerging solutions, such as explainable artificial intelligence (XAI) approaches and standardized multi-omics integration pipelines, are discussed as pathways to overcome these hurdles. By synthesizing recent advances, this review illustrates how ML-enhanced metabolomics bridges the gap between fundamental cancer metabolism research and clinical application, offering new avenues for precision oncology through improved diagnosis, prognosis, and tailored therapeutic strategies. Full article

Background: The identification of pathogenic variants in the Breast Cancer Genes 1 and 2 (BRCA1/2) is a critical predictive biomarker for poly (ADP-ribose) polymerase inhibitor (PARPi) therapy in epithelial ovarian cancer (EOC). The aim of this study is to define real-world rates and determinants of germline and somatic BRCA1/2 testing and subsequent PARPi utilisation in Australia using a national clinical quality registry. Methods: This multi-centre cohort study analysed data from 1503 women with non-mucinous EOC diagnosed between May 2017 and July 2022, captured by the Australian National Gynae-Oncology Registry (NGOR). We evaluated rates of germline and somatic testing and PARPi use, using multivariate logistic regression to identify associated clinical and demographic factors. Results: Overall germline and somatic testing rates were 68% and 32%, respectively. For the high-grade serous ovarian cancer (HGSOC) cohort, rates were higher, at 78% and 39%, respectively. Germline testing was significantly less likely for women aged >80 years (OR 0.49), those in regional areas (OR 0.61), and those receiving single-modality treatment. Somatic testing uptake increased significantly following public reimbursement for PARPi (p = 0.004). Among eligible women with a newly diagnosed BRCA pathogenic variant and advanced disease (n = 110), 52% commenced first-line maintenance PARPi. Conclusions: This national study offers valuable insights into Australian ovarian cancer care, highlighting opportunities to enhance testing equity for older women (aged >80) and regional patients. Furthermore, it identifies the translation of a positive test into PARPi therapy as a complex area that warrants further collaborative investigation to optimise patient outcomes. Full article

Background: The identification and clinical implementation of robust biomarkers are essential for improving diagnosis, prognosis, and treatment across a wide range of diseases. Pancreatic stone protein (PSP) has recently emerged as a promising candidate biomarker. Objective: This narrative review aims to provide an updated and comprehensive overview of the clinical applications of PSP in infectious, oncological, metabolic, and surgical contexts. Methods: We conducted a structured literature search using PubMed^®, applying the SANRA framework for narrative reviews. Boolean operators were used to retrieve relevant studies on PSP in a wide range of clinical conditions, including sepsis, gastrointestinal cancers, diabetes, and ventilator-associated pneumonia. Results: PSP has shown strong diagnostic and prognostic potential in sepsis, where it may outperform traditional markers such as CRP and PCT. It has also demonstrated relevance in gastrointestinal cancers, type 1 and type 2 diabetes, and perioperative infections. PSP levels appear to rise earlier than other inflammatory markers and may be less affected by sterile inflammation. Conclusion: PSP represents a versatile and clinically valuable biomarker. Its integration into diagnostic protocols could enhance early detection and risk stratification in critical care and oncology settings. However, widespread adoption is currently limited by the availability of point-of-care assay platforms. Full article

Stage IV colorectal cancer has a poor prognosis, and liver metastases are prone to recurrence, even after resection. This study aimed to identify common cancer antigens, using immunohistochemical staining, as promising targets for antigen-specific immunotherapies in colorectal cancer. We analyzed expression levels and intracellular localization of seven common cancer antigens, CLDN1, EphB4, LAT1, FOXM1, HSP105α, ROBO1, and SPARC, and human leukocyte antigen (HLA) class I via immunohistochemical staining of 85 surgical specimens from primaries and liver metastases. Staining intensity and positive staining were scored to evaluate antigen expression. In 25 primaries, seven cancer antigens were expressed in 88–96% of cases, while HLA class I was expressed on the cell membrane in 80.0% of cases. In 60 liver metastases, FOXM1 and SPARC expression were approximately half that observed in the primaries. Other antigens and HLA class I were highly expressed in both. Most of the primaries and liver metastases may benefit from chimeric antigen receptor-T cell therapy targeting CLDN1, EphB4, and LAT1. Cases with high HLA class I expression may be suitable for vaccine-based and T cell receptor-T cell therapy targeting CLDN1, EphB4, LAT1, FOXM1, HSP105α, ROBO1, and SPARC for primaries and targeting antigens, excluding FOXM1 and SPARC, for liver metastases. Full article