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Atherosclerosis, a complex metabolic-immune disease characterized by chronic inflammation driven by the buildup of lipid-rich plaques within arterial walls, has emerged as a pivotal factor in the intricate interplay between cancer and cardiovascular disease. This bidirectional relationship, marked by shared risk factors and pathophysiological mechanisms, underscores the need for a comprehensive understanding of how these two formidable health challenges intersect and influence each other. Cancer and its treatments can contribute to the progression of atherosclerosis, while atherosclerosis, with its inflammatory microenvironment, can exert profound effects on cancer development and outcomes. Both cancer and cardiovascular disease involve intricate interactions between general and personal exposomes. In this review, we aim to summarize the state of the art of translational data and try to show how oncologic studies on cardiotoxicity can broaden our knowledge of crucial pathways in cardiovascular biology and exert a positive impact on precision cardiology and cardio-oncology.
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Aterosclerose , Doenças Cardiovasculares , Neoplasias , Humanos , Neoplasias/metabolismo , Neoplasias/complicações , Aterosclerose/metabolismo , Aterosclerose/etiologia , Doenças Cardiovasculares/etiologia , Doenças Cardiovasculares/metabolismo , Animais , Fatores de Risco , Pesquisa Translacional BiomédicaRESUMO
Dual-energy CT (DECT) is an innovative technology that is increasingly widespread in clinical practice. DECT allows for tissue characterization beyond that of conventional CT as imaging is performed using different energy spectra that can help differentiate tissues based on their specific attenuation properties at different X-ray energies. The most employed post-processing applications of DECT include virtual monoenergetic images (VMIs), iodine density maps, virtual non-contrast images (VNC), and virtual non-calcium (VNCa) for bone marrow edema (BME) detection. The diverse array of images obtained through DECT acquisitions offers numerous benefits, including enhanced lesion detection and characterization, precise determination of material composition, decreased iodine dose, and reduced artifacts. These versatile applications play an increasingly significant role in tumor assessment and oncologic imaging, encompassing the diagnosis of primary tumors, local and metastatic staging, post-therapy evaluation, and complication management. This article provides a comprehensive review of the principal applications and post-processing techniques of DECT, with a specific focus on its utility in managing oncologic patients.
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Artefatos , Iodo , Humanos , Tomografia Computadorizada por Raios XRESUMO
Background: The efficacy of immunotherapy for brain metastases from small cell lung cancer (SCLC) is relatively low, and the tumor microenvironment of SCLC brain metastases is still unknown. Therefore, we investigated the distribution of tumor-infiltrating lymphocytes (TILs) and the expression of programmed cell death-ligand 1 (PD-L1) in patients with brain metastases from SCLC to explore the tumor microenvironment of SCLC brain metastases. Methods: A retrospective analysis was performed on 12 surgical specimens of brain metastases from patients with SCLC treated in the Department of Neurosurgery of The First Affiliated Hospital of Anhui Medical University from June 2017 to June 2022. The inclusion criteria for this study were the following: (I) a pathologically confirmed diagnosis of SCLC brain metastases; (II) surgical resection of brain metastases; (III) age >18 years; (IV) and complete clinical data. Patient-related data were retrieved from the inpatient medical record system, telephone follow-up of patients date of death, and overall survival (OS). The immunofluorescence-based tissue microenvironment analysis panel (MAP) was utilized for the detection of TILs, including CD3, CD8, programmed cell death 1 (PD-1), and PD-L1, in formalin-fixed and paraffin-embedded archival specimens of brain metastases. The expression levels of PD-L1 in tumor cells were detected by immunohistochemistry. The correlation between the OS and the above-mentioned markers was analyzed in the 12 patients. Results: Twelve patients were included in the study. The patients' ages ranged from 51-78 years with a median of 68 years, with 1 female and 11 males. Among 12 patients with SCLC brain metastases: positive rates of CD3+ TILs in the tumor parenchyma vs. tumor stroma were 0.60%±0.94% vs. 1.76%±2.72% (P=0.01), respectively; positive rates of CD8+ TILs in the tumor parenchyma vs. tumor stroma were 0.80%±0.78% vs. 2.46%±3.72% (P=0.02), respectively. There was no co-expression of CD8+ and PD-1+ TILs in the tumor parenchyma of 11 cases, and the infiltration density of coexpressed CD3+ and PD-1+ TILs was more than 10/mm2 in only 1 case. There was no coexpression of CD3+ and PD-1+ TIL in the stroma of 10 cases, and the infiltration density of CD8+ and PD-1+ TILs was more than 10/mm2 in 2 cases. Immunohistochemistry was used to detect the expression of PD-L1 in 12 cases of SCLC metastatic lesions, and 3 cases (25%) were positive. Survival analysis showed that patients with positive intraepithelial CD3+ TILs had significantly longer OS [hazard ratio 3.383, 95% confidence interval (CI): 0.959-11.940; P=0.04]. Conclusions: Our study further demonstrated the immune microenvironment of SCLC brain metastases. The distribution of TILs in SCLC brain metastases is low and mainly distributed in the stroma, with the expression of PD-L1 in these tumor tissues being low. Further exploration of the immune microenvironment of SCLC brain metastases is of great significance for potential treatment.
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Introduction: Combinations of immune checkpoint inhibitors (ICIs) and angiogenesis inhibitors (AIs) have been investigated for the treatment of several tumor types. Both ICIs and AIs may lead to cardiovascular adverse events, and their combination may potentially increase the risk for cardiovascular toxicity. In the present meta-analysis, we aim to assess the cardiovascular toxicity of ICIs plus AIs vs. AIs alone. Secondary objectives are non-cardiovascular adverse events and efficacy. Methods: Systematic review was performed according to PRISMA statement. Phase II and III randomized clinical trials were identified by searching the MEDLINE/PubMed, Cochrane Library and ASCO Meeting abstracts, from inception to June 2022. The pooled risks for overall response rate (ORR), 1-year progression-free survival (PFS), adverse events (AEs), immune-related AEs, (irAEs), hypertension, and vascular events defined as stroke, myocardial infarction and pulmonary embolisms, were calculated. Results: In terms of cardiovascular toxicity, we found higher risk for severe hypertension among patients treated with ICIs plus AIs as compared with those receiving AIs (OR 1.24, 95% CI: 1.01-1.53), but no significant difference was found for any-grade hypertension, and for vascular events. There was also no difference in terms of overall AEs, whereas the incidence of irAEs was increased in the ICIs plus AIs arm, as expected. In terms of efficacy, ICIs plus AIs achieved better ORR (OR 2.25, 95% CI: 1.70-2.97) and PFS (HR 0.49, 95% CI: 0.39-0.63) as compared to AIs alone. Conclusion: The addition of ICIs to AIs significantly increased the risk of high-grade hypertension, but not that of acute vascular events.
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Anthracycline-induced cardiomyopathies and sarcopenia are frequently seen in cancer patients, affecting their overall survival and quality of life; therefore, new cardioprotective and anti-sarcopenic strategies are needed. Vericiguat is a new oral guanylate cyclase activator that reduces heart failure hospitalizations or cardiovascular death. This study highlighted the potential cardioprotective and anti-sarcopenic properties of vericiguat during anthracycline therapy. Human cardiomyocytes and primary skeletal muscle cells were exposed to doxorubicin (DOXO) with or without a pre-treatment with vericiguat. Mitochondrial cell viability, LDH, and Cytochrome C release were performed to study cytoprotective properties. Intracellular Ca++ content, TUNEL assay, cGMP, NLRP-3, Myd-88, and cytokine intracellular levels were quantified through colorimetric and selective ELISA methods. Vericiguat exerts significant cytoprotective and anti-apoptotic effects during exposure to doxorubicin. A drastic increase in cGMP expression and reduction in NLRP-3, MyD-88 levels were also seen in Vericiguat-DOXO groups vs. DOXO groups (p < 0.001) in both cardiomyocytes and human muscle cells. GCa vericiguat reduces cytokines and chemokines involved in heart failure and sarcopenia. The findings that emerged from this study could provide the rationale for further preclinical and clinical investigations aimed at reducing anthracycline cardiotoxicity and sarcopenia in cancer patients.
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BACKGROUND: Cancer-related fatigue (CRF) is still undertreated in most patients, as evidence for pharmacological treatments is limited and conflicting. Also, the efficacy of the pharmacological agents relative to each other is still unclear. Therefore, medications that may potentially contribute to improving CRF will be investigated in this head-to-head trial. Our main objective is to compare the efficacy of methylphenidate vs. bupropion vs. ginseng vs. amantadine vs. placebo in patients with advanced cancer. METHODS: The 5-EPIFAT study is a 5-arm, randomized, multi-blind, placebo-controlled, multicenter trial that will use a parallel-group design with an equal allocation ratio comparing the efficacy and safety of four medications (Methylphenidate vs. Bupropion vs. Ginseng vs. Amantadine) versus placebo for management of CRF. We will recruit 255 adult patients with advanced cancer who experience fatigue intensity ≥ 4 based on a 0-10 scale. The study period includes a 4-week intervention and a 4-week follow-up with repeated measurements over time. The primary outcome is the cancer-related fatigue level over time, which will be measured by the functional assessment of chronic illness therapy-fatigue (FACIT-F) scale. To evaluate safety, the secondary outcome is the symptomatic adverse events, which will be assessed using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events in cancer clinical trials (PRO-CTCAE). Also, a subgroup analysis based on a decision tree-based machine learning algorithm will be employed for the clinical prediction of different agents in homogeneous subgroups. DISCUSSION: The findings of the 5-EPIFAT trial could be helpful to guide clinical decision-making, personalization treatment approach, design of future trials, as well as the development of CRF management guidelines. TRIAL REGISTRATION: IRCT.ir IRCT20150302021307N6. Registered on 13 May 2023.
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Metilfenidato , Neoplasias , Panax , Adulto , Humanos , Amantadina/uso terapêutico , Bupropiona/uso terapêutico , Fadiga/diagnóstico , Fadiga/tratamento farmacológico , Fadiga/etiologia , Metilfenidato/uso terapêutico , Estudos Multicêntricos como Assunto , Neoplasias/terapia , Ensaios Clínicos Controlados Aleatórios como Assunto , Resultado do TratamentoRESUMO
INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). METHODS AND OBJECTIVES: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. CONCLUSION: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project.