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Cutaneous malignant melanoma is one of the most aggressive forms of skin cancer and thus, a high mortality has been reported over decades. The prognosis for melanoma varies widely based on several factors, including the stage at which it is diagnosed, the location and thickness of the tumor, the patient's age and overall health, and specific genetic factors associated with melanoma. Therapeutic options include checkpoint inhibitors, regardless of V-Raf Murine Sarcoma Viral Oncogene Homolog B status (BRAF), and targeted therapy (anti-BRAF) in the adjuvant or metastatic setting. Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment but predicting which patients will benefit from these therapies remains challenging. Biomarkers like leukocytes, neutrophils, eosinophils, basophils, platelets, and other peripheral blood biomarkers have been investigated for their potential to predict responses to ICIs. Tumor mutational burden (TMB), circulating tumor DNA (ctDNA), and soluble PD-L1 (sPD-L1) have emerged as potential biomarkers for predicting responses to ICIs. Elevated baseline levels of ctDNA and elevated sPD-L1 levels have been associated with worse prognosis in melanoma patients. High TMB is often associated with better responses to ICIs in melanoma. Here we present a case from our department, of a 57-year-old patient, diagnosed in 2019 with stage IV - pT4cNx cM1 (lymph nodes metastases) and suspicion of lung metastases, BRAF wild-type right hallux malignant melanoma. Due to impressive results, first-line treatment with ICIs nivolumab and ipilimumab was the preferred treatment of choice, which showed a favorable response, with regression of oncological disease after the first cycle, and achieving complete response afterward. Unfortunately, the treatment was discontinued due to severe hepatic and pancreatic toxicity, but the favorable response to immunotherapy has been maintained for four years and is ongoing. Identifying predictive biomarkers is important to achieve the best response for the patient, with minimal adverse events, especially if long-term clinical benefit can be reached.
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Predictive biomarkers for immune checkpoint inhibitors (ICIs) in solid tumors such as melanoma, hepatocellular carcinoma (HCC), colorectal cancer (CRC), non-small cell lung cancer (NSCLC), endometrial carcinoma, renal cell carcinoma (RCC), or urothelial carcinoma (UC) include programmed cell death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), defective deoxyribonucleic acid (DNA) mismatch repair (dMMR), microsatellite instability (MSI), and the tumor microenvironment (TME). Over the past decade, several types of ICIs, including cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors, anti-programmed cell death 1 (PD-1) antibodies, anti-programmed cell death ligand 1 (PD-L1) antibodies, and anti-lymphocyte activation gene-3 (LAG-3) antibodies have been studied and approved by the Food and Drug Administration (FDA), with ongoing research on others. Recent studies highlight the critical role of the gut microbiome in influencing a positive therapeutic response to ICIs, emphasizing the importance of modeling factors that can maintain a healthy microbiome. However, resistance mechanisms can emerge, such as increased expression of alternative immune checkpoints, T-cell immunoglobulin (Ig), mucin domain-containing protein 3 (TIM-3), LAG-3, impaired antigen presentation, and alterations in the TME. This review aims to synthesize the data regarding the interactions between microbiota and immunotherapy (IT). Understanding these mechanisms is essential for optimizing ICI therapy and developing effective combination strategies.
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Biomarcadores de Tumor , Resistencia a Antineoplásicos , Inhibidores de Puntos de Control Inmunológico , Neoplasias , Humanos , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inhibidores de Puntos de Control Inmunológico/farmacología , Neoplasias/tratamiento farmacológico , Neoplasias/metabolismo , Neoplasias/inmunología , Biomarcadores de Tumor/metabolismo , Microambiente Tumoral/efectos de los fármacos , Microambiente Tumoral/inmunologíaRESUMEN
Small cell lung cancer (SCLC) is a highly malignant and poor-prognosis cancer, with most cases diagnosed at the extensive stage (ES). Amidst a landscape marked by limited progress in treatment modalities for ES-SCLC over the past few decades, the integration of immune checkpoint inhibitors (ICIs) with platinum-based chemotherapy has provided a milestone approach for improving prognosis, emerging as the new standard for initial therapy in ES-SCLC. However, only a minority of SCLC patients can benefit from ICIs, which frequently come with varying degrees of immune-related adverse events (irAEs). Therefore, it is crucial to investigate predictive biomarkers to screen potential beneficiaries of ICIs, mitigate the risk of side effects, and improve treatment precision. This review summarized potential biomarkers for predicting ICI response in ES-SCLC, with a primary focus on markers sourced from tumor tissue or peripheral blood samples. The former mainly included PD-L1 expression, tumor mutational burden (TMB), along with cellular or molecular components related to the tumor microenvironment (TME) and antigen presentation machinery (APM), molecular subtypes of SCLC, and inflammatory gene expression profiles. Circulating biomarkers predominantly comprised circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), cytokines, plasma autoantibodies, inflammation-related parameters, and blood TMB. We synthesized and analyzed the research progress of these potential markers. Notably, investigations into PD-L1 expression and TMB have been the most extensive, exhibiting preliminary predictive efficacy in salvage immunotherapy; however, consistent conclusions have yet to be reached across studies. Additionally, novel predictive markers developed based on TME composition, APM, transcriptomic and genomic features provide promising tools for precision immunotherapy. Circulating biomarkers offer the advantages of convenience, non-invasiveness, and a comprehensive reflection of tumor molecular characteristics. They may serve as alternative options for predicting immunotherapy efficacy in SCLC. However, there is a scarcity of studies, and the significant heterogeneity in research findings warrants attention.
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Background: Recent studies have shown that the triglyceride glucose index (TyG) and cystatin C (CysC) are closely related to cardiovascular disease, but there is limited research on the prognosis of patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI). The aim of this study was to explore the predictive value of the combination of the TyG index and CysC in predicting major adverse cardiovascular events (MACEs) in ACS patients who underwent PCI. Methods: This retrospective study included 319 ACS patients who underwent PCI. The clinical endpoint was the occurrence of MACEs, including all-cause mortality, heart failure, non-fatal myocardial infarction, target vessel revascularization, and angina requiring hospitalization. Patients were classified into MACEs (65 cases) and non-MACEs (254 cases) groups. Univariate factor and multivariate analysis were used to identify predictors of MACEs. The receiver operating curve (ROC) of the prediction model of MACEs was determined. Additionally, the net reclassification improvement and integrated discrimination improvement indexes were calculated to further assess the additional predictive value of the risk factors for MACEs. Subgroup and interaction analysis between the TyG index combined with CysC and MACEs were conducted in various subgroups. Patients were stratified according to the optimal cutoff point value of the TyG index and the CysC determined by ROC curve analysis. The Kaplan-Meier analysis method was used to construct a survival curve 1 year after PCI. Results: During a median follow-up period of 14 months, 65 (20.38%) patients had experienced at least one primary endpoint event. Multivariate logistic regression analysis indicated that the TyG index and CysC were independently associated with an increased risk of MACEs after PCI (OR, 2.513, 95% CI 1.451-4.351, P= 0.001; and OR, 4.741, 95% CI 1.344-16.731, P=0.016, respectively). The addition of the TyG index and CysC to the baseline risk model had the strongest incremental effect for predicting MACEs in terms of the C-statistic from 0.789 (95% CI 0.723-0.855, P<0.001) to 0.799 (95% CI 0.733-0.865, P<0.001). Furthermore, Kaplan-Meier analysis demonstrated that a TyG index greater than 9.325 and a CysC value greater than 1.065 mg/ml were significantly associated with an increased risk of MACEs (log-rank, all P < 0.01). Conclusion: The TyG index predicts MACEs after PCI in patients with ASC independent of known cardiovascular risk factors. Adjustment of the CysC by the TyG index further improves the predictive ability for MACEs in patients with ACS undergoing PCI. Thus, both of them are expected to become new prognostic indicators for MACEs in patients with ACS after PCI.
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Síndrome Coronario Agudo , Glucemia , Cistatina C , Intervención Coronaria Percutánea , Valor Predictivo de las Pruebas , Triglicéridos , Humanos , Síndrome Coronario Agudo/sangre , Síndrome Coronario Agudo/diagnóstico , Síndrome Coronario Agudo/mortalidad , Femenino , Masculino , Cistatina C/sangre , Estudios Retrospectivos , Pronóstico , Persona de Mediana Edad , Triglicéridos/sangre , Anciano , Glucemia/análisis , Glucemia/metabolismo , Biomarcadores/sangre , Factores de RiesgoRESUMEN
The CAR-T cell therapy has marked the dawn of new era in the cancer therapeutics and cell engineering techniques. The review emphasizes on the challenges that obstruct the therapeutic efficiency caused by cell toxicities, immunosuppressive tumor environment, and decreased T cell infiltration. In the interest of achieving the overall survival (OS) and event-free survival (EFS) of patients, the conceptual background of potential target selection and various CAR-T cell design techniques are described which can minimize the off-target effects, reduce toxicity, and thus increase the resilience of CAR-T cell treatment in the haematological malignancies as well as in solid tumors. Furthermore, it delves into cutting-edge technologies like gene editing and synthetic biology, providing new opportunities to enhance the functionality of CAR-T cells and overcome mechanisms of immune evasion. This review provides a comprehensive understanding of the complex and diverse aspects of CAR-T cell-based gene treatments, including both scientific and clinical aspects. By effectively addressing the obstacles and utilizing the capabilities of cutting-edge technology, CAR-T cell therapy shows potential in fundamentally changing immunotherapy and reshaping the approach to cancer treatment.
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Ovarian carcinoma (OC) still represents an insidious and fatal malignancy, and few significant results have been obtained in the last two decades to improve patient survival. Novel targeted therapies such as poly (ADP-ribose) polymerase inhibitors (PARPi) have been successfully introduced in the clinical management of OC, but not all patients will benefit, and drug resistance almost inevitably occurs. The identification of patients who are likely to respond to PARPi-based therapies relies on homologous recombination deficiency (HRD) tests, as this condition is associated with response to these treatments. This review summarizes the genomic and functional HRD assays currently used in clinical practice and those under evaluation, the clinical implications of HRD testing in OC, and their current pitfalls and limitations. Special emphasis will be placed on the functional HRD assays under development and the use of machine learning and artificial intelligence technologies as novel strategies to overcome the current limitations of HRD tests for a better-personalized treatment to improve patient outcomes.
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Background: Advances in targeted therapy development and tumor sequencing technology are reclassifying cancers into smaller biomarker-defined diseases. Randomized controlled trials (RCTs) are often impractical in rare diseases, leading to calls for single-arm studies to be sufficient to inform clinical practice based on a strong biological rationale. However, without RCTs, favorable outcomes are often attributed to therapy but may be due to a more indolent disease course or other biases. When the clinical benefit of targeted therapy in a common cancer is established in RCTs, this benefit may extend to rarer cancers sharing the same biomarker. However, careful consideration of the appropriateness of extending the existing trial evidence beyond specific cancer types is required. A framework for extrapolating evidence for biomarker-targeted therapies to rare cancers is needed to support transparent decision-making. Objectives: To construct a framework outlining the breadth of criteria essential for extrapolating evidence for a biomarker-targeted therapy generated from RCTs in common cancers to different rare cancers sharing the same biomarker. Design: A series of questions articulating essential criteria for extrapolation. Methods: The framework was developed from the core topics for extrapolation identified from a previous scoping review of methodological guidance. Principles for extrapolation outlined in guidance documents from the European Medicines Agency, the US Food and Drug Administration, and Australia's Medical Services Advisory Committee were incorporated. Results: We propose a framework for assessing key assumptions of similarity of the disease and treatment outcomes between the common and rare cancer for five essential components: prognosis of the biomarker-defined cancer, biomarker test analytical validity, biomarker actionability, treatment efficacy, and safety. Knowledge gaps identified can be used to prioritize future studies. Conclusion: This framework will allow systematic assessment, standardize regulatory, reimbursement and clinical decision-making, and facilitate transparent discussions between key stakeholders in drug assessment for rare biomarker-defined cancers.
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Mismatch repair proficient (MMRp) tumors of colorectal origin are one of the prevalent yet unpredictable clinical challenges. Despite earnest efforts, optimal treatment modalities have yet to emerge for this class. The poor prognosis and limited actionability of MMRp are ascribed to a low neoantigen burden and a desert-like microenvironment. This review focuses on the critical roadblocks orchestrated by an immune evasive mechanistic milieu in the context of MMRp. The low density of effector immune cells, their weak spatiotemporal underpinnings, and the high-handedness of the IL-17-TGF-ß signaling are intertwined and present formidable challenges for the existing therapies. Microbiome niche decorated by Fusobacterium nucleatum alters the metabolic program to maintain an immunosuppressive state. We also highlight the evolving strategies to repolarize and reinvigorate this microenvironment. Reconstruction of anti-tumor chemokine signaling, rational drug combinations eliciting T cell activation, and reprograming the maladapted microbiome are exciting developments in this direction. Alternative vulnerability of other DNA damage repair pathways is gaining momentum. Integration of liquid biopsy and ex vivo functional platforms provide precision oncology insights. We illustrated the perspectives and changing landscape of MMRp-CRC. The emerging opportunities discussed in this review can turn the tide in favor of fighting the treatment dilemma for this elusive cancer.
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Reparación de la Incompatibilidad de ADN , Microambiente Tumoral , Humanos , Microambiente Tumoral/inmunología , Medicina de Precisión , Animales , Neoplasias Colorrectales/inmunología , Neoplasias Colorrectales/terapia , Transducción de SeñalRESUMEN
Traditionally, immunotherapy agent selection and treatment strategies are guided by biopsy-based histological information. However, biopsies are limited in that they are invasive, provide static information regarding the tumor immune microenvironment, and only sample a small part of one tumor site. The tumor microenvironment is dynamic and heterogenous. As a result, the immune milieu at one site may be distinct from other metastatic sites. These factors make identifying which patients are likely to respond to different immunotherapies and which harbor intrinsic resistance mechanisms difficult to identify based on a biopsy alone. As such, there is significant interest in alternative methodologies that better characterize the tumor immune microenvironment and monitor immunotherapy response. PET imaging potentially offers a non-invasive way to characterize the tumor immune microenvironment at the primary tumor and metastases and allow for longitudinal characterization. Herein, we review pre-clinically and clinically tested T cell-targeted PET radiopharmaceuticals, as T cells have been the dominant immunotherapy target, and their utility in both evaluating response to immunotherapy and in understanding the systemic immune response to treatment with immunotherapeutics.
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Claudin-18.2 (CLDN18.2) expression evaluated by immunohistochemistry is a new biomarker for gastric and gastroesophageal junction adenocarcinomas that will soon have market authorization for implementation into routine clinical practice. Despite successful testing in the setting of clinical trials, no specific practical testing guidelines have been proposed. Several preanalytical and analytical variables may interfere with adequate CLDN18.2 staining interpretation; thus, this article provides practical guidance on CLDN18.2 testing and scoring in gastric and gastroesophageal junction adenocarcinomas to identify patients who may respond to targeted therapy with monoclonal antibodies directed against CLDN18.2. Based on available data, moderate to strong (2+/3+) membrane staining in ≥75% of adenocarcinoma cells is the proposed cutoff for clinical use of monoclonal antibody anti-CLDN18.2 (zolbetuximab).
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Small biopsies of lung are routinely obtained by many methods, including several that result in cytologic specimens. Because lung cancer is often diagnosed at a stage for which primary resection is not an option, it is critical that all diagnostic, predictive, and prognostic information be derived from such small biopsy specimens. As the number of available diagnostic and predictive markers expands, cytopathologists must familiarize themselves with current requirements for specimen acquisition, handling, results reporting, and molecular and other ancillary testing, all of which are reviewed here.
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Neoplasias Pulmonares , Humanos , Biomarcadores de Tumor , Biopsia/métodos , Biopsia/tendencias , Pulmón/patología , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/diagnóstico , Atención al Paciente , Manejo de Especímenes/métodosRESUMEN
In recent years, the influence of specific biomarkers in the diagnosis and prognosis of solid organ malignancies has been increasingly prominent. The relevance of the use of predictive biomarkers, which predict cancer response to specific forms of treatment provided, is playing a more significant role than ever before, as it affects diagnosis and initiation of treatment, monitoring for efficacy and side effects of treatment, and adjustment in treatment regimen in the long term. In the current review, we explored the use of predictive biomarkers in the treatment of solid organ malignancies, including common cancers such as colorectal cancer, breast cancer, lung cancer, prostate cancer, and cancers associated with high mortalities, such as pancreatic cancer, liver cancer, kidney cancer and cancers of the central nervous system. We additionally analyzed the goals and types of personalized treatment using predictive biomarkers, and the management of various types of solid organ malignancies using predictive biomarkers and their relative efficacies so far in the clinical settings.
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Hepatocellular carcinoma (HCC) is the most common liver cancer and is among the leading causes of cancer-related death worldwide. There is no reliable biomarker for the early diagnosis of HCC. Circulating microRNAs (miRNAs) have attracted attention as potential biomarkers of disease. By small-RNA next-generation sequencing, the analysis of serum miRNAs led to the identification of molecular signatures able to discriminate advanced HCC from early HCC (n = 246); advanced HCC from CIRRHOSIS (n = 299); advanced HCC from HEALTHY (n = 320); HEALTHY from early HCC (n = 343); and HEALTHY from CIRRHOSIS (n = 414). Cirrhotic patients and early HCC patients exhibited similar serum miRNA profiles, yet a small number of miRNAs (n = 57) were able to distinguish these two classes of patients. A second objective of the study was to identify serum miRNAs capable of predicting the response to therapy in patients with advanced HCC. All patients were treated with sorafenib as first-line therapy: 24 were nonresponsive and 24 responsive. Analysis of circulating miRNAs revealed a 54 miRNAs signature able to separate the two subgroups. This study suggested that circulating miRNAs could be useful biomarkers for monitoring patients with liver diseases ranging from cirrhosis to advanced HCC and possibly predicting susceptibility to first-line treatment based on sorafenib.
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Biomarcadores de Tumor , Carcinoma Hepatocelular , MicroARN Circulante , Progresión de la Enfermedad , Neoplasias Hepáticas , Humanos , Neoplasias Hepáticas/sangre , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/tratamiento farmacológico , Neoplasias Hepáticas/diagnóstico , Biomarcadores de Tumor/sangre , Biomarcadores de Tumor/genética , MicroARN Circulante/sangre , MicroARN Circulante/genética , Carcinoma Hepatocelular/sangre , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/tratamiento farmacológico , Carcinoma Hepatocelular/diagnóstico , Masculino , Femenino , Persona de Mediana Edad , Anciano , Cirrosis Hepática/sangre , Cirrosis Hepática/diagnóstico , Cirrosis Hepática/genética , Cirrosis Hepática/tratamiento farmacológico , Sorafenib/uso terapéutico , MicroARNs/sangre , MicroARNs/genética , AdultoRESUMEN
Over the last decade, cancer diagnostics has undergone a notable transformation with increasing complexity. Minimally invasive diagnostic tests, driven by advanced imaging and early detection protocols, are redefining patient care and reducing the need for more invasive procedures. Modern cytopathologists now safeguard patient samples for vital biomarker and molecular testing. In this article, we explore ancillary testing modalities and the role of biomarkers in organ-specific contexts, underscoring the transformative impact of precision medicine. Finally, the advent of more than 80 Food and Drug Administration-approved predictive biomarkers signals a new era, guiding cancer care toward personalized and targeted strategies.
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Biomarcadores de Tumor , Citodiagnóstico , Neoplasias , Medicina de Precisión , Humanos , Biomarcadores de Tumor/genética , Citodiagnóstico/métodos , Citodiagnóstico/tendencias , Neoplasias/patología , Neoplasias/diagnóstico , Neoplasias/genéticaRESUMEN
BACKGROUND: Immunotherapy has improved survival rates in cancer patients, but identifying those who will respond to treatment remains a challenge. Recent advances in proteomic technologies have enabled the identification and quantification of nearly all expressed proteins in a single experiment. Integration of mass spectrometry with other high-throughput technologies has paved the way for comprehensive and systematic analysis of the plasma proteome in cancer, facilitating early diagnosis and personalized treatment. In this context, the objective of our study was to investigate the predictive and prognostic value of plasma proteome analysis using the SWATH-MS (Sequential Window Acquisition of All Theoretical Mass Spectra) strategy in newly diagnosed NSCLC patients who received pembrolizumab therapy. METHODS: For this purpose, 64 newly diagnosed advanced NSCLC patients treated with pembrolizumab therapy were enrolled and blood samples were collected from all patients before and during therapy. In total 171 blood samples were collected, and plasma samples were analysed employing SWATH-MS strategy. Next, we compared the plasma protein expression of metastatic NSCLC patients prior to receiving pembrolizumab treatment and divided the cohort into two groups in order to identify a proteomic signature that allow us to predict immunotherapy response. RESULTS: Proteomic analyses by SWATH-MS strategy allow us to identified 324 differentially expressed proteins between responder and non-responder patients. In addition, we developed a predictive model and found a combination of seven proteins, including ATG9A, DCDC2, HPS5, FIL1L, LZTL1, PGTA, and SPTN2, with stronger predictive value than PD-L1 expression alone. Additionally, survival analyses showed that low levels of ATG9A, DCDC2, and HPS5 were associated with longer progression-free survival (PFS) and overall survival (OS), while low levels of SPTN2 were associated with worse OS. CONCLUSIONS: Our work highlights the potential value of proteomic technologies to detect predictive biomarkers in blood samples of NSCLC patients. These analyses shed light on the correlation between the response to immunotherapy in patients with NSCLC and the set of 7 proteins.
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Although immune checkpoint blockade (ICB) is currently approved for the treatment of extensive-stage small-cell lung cancer (SCLC) in combination with chemotherapy, relatively few patients have demonstrated durable clinical benefit (DCB) to these therapies. Biomarkers predicting responses are needed. Biopsies from 35 SCLC patients treated with ICB were subjected to transcriptomic analysis; gene signatures were assessed for associations with responses. Twenty-one patients were treated with ICB in the first-line setting in combination with platinum-based chemotherapy; fourteen patients were treated in the second-line setting with ICB alone. DCB after ICB in SCLC in the second-line setting (3 of 14 patients) was associated with statistically higher transcriptomic levels of genes associated with inflammation (p = 0.003), antigen presentation machinery (p = 0.03), interferon responses (p < 0.05), and increased CD8 T cells (p = 0.02). In contrast, these gene signatures were not significantly different in the first-line setting. Our data suggest that responses to ICB in SCLC in the second-line setting can be predicted by the baseline inflammatory state of the tumor; however, this strong association with inflammation was not seen in the first-line setting. We postulate that chemotherapy alters the immune milieu allowing a response to ICB. Other biomarkers will be needed to predict responses in first-line therapy patients.
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This study aimed to explore advances in biomarkers related to anti-angiogenic therapy in patients with non-small cell lung cancer (NSCLC), thereby enhancing treatment selection, advancing personalized and precision medicine to improve treatment outcomes and patient survival rates. This article reviews key discoveries in predictive biomarkers for anti-angiogenic therapy in NSCLC in recent years, such as (1) liquid biopsy predictive biomarkers: studies have identified activated circulating endothelial cells (aCECs) via liquid biopsy as potential predictive biomarkers for the efficacy of anti-angiogenic therapy; (2) imaging biomarkers: advanced imaging technologies, such as dynamic contrast-enhanced integrated magnetic resonance positron emission tomography (MR-PET), are used to assess tumor angiogenesis in patients with NSCLC and evaluate the clinical efficacy of anti-angiogenic drugs; (3) genetic predictive biomarkers: research has explored polymorphisms of Vascular Endothelial Growth Factor Receptor-1 (VEGFR-1) and vascular endothelial growth factor-A (VEGF-A), as well as how plasma levels of VEGF-A can predict the outcomes and prognosis of patients with non-squamous NSCLC undergoing chemotherapy combined with bevacizumab. Despite progress in identifying biomarkers related to anti-angiogenic therapy, several challenges remain, including limitations in clinical trials, heterogeneity in NSCLC, and technical hurdles. Future research will require extensive clinical validation and in-depth mechanistic studies to fully exploit the potential of these biomarkers for personalized treatment.
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Inhibidores de la Angiogénesis , Biomarcadores de Tumor , Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Humanos , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Carcinoma de Pulmón de Células no Pequeñas/genética , Neoplasias Pulmonares/tratamiento farmacológico , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/genética , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/sangre , Inhibidores de la Angiogénesis/uso terapéutico , Neovascularización Patológica/tratamiento farmacológico , PronósticoRESUMEN
The role of CD161+CD127+CD8+ T cells in non-small cell lung cancer (NSCLC) patients with diabetes remains unexplored. This study determined the prevalence, phenotype, and function of CD8+ T cell subsets in NSCLC with diabetes. We recruited NSCLC patients (n = 436) treated with anti-PD-1 immunotherapy as first-line treatment. The progression-free survival (PFS), overall survival (OS), T cells infiltration, and peripheral blood immunological characteristics were analyzed in NSCLC patients with or without diabetes. NSCLC patients with diabetes exhibited shorter PFS and OS (p = 0.0069 and p = 0.012, respectively) and significantly lower CD8+ T cells infiltration. Mass cytometry by time-of-flight (CyTOF) showed a higher percentage of CD161+CD127+CD8+ T cells among CD8+T cells in NSCLC with diabetes before anti-PD-1 treatment (p = 0.0071) than that in NSCLC without diabetes and this trend continued after anti-PD-1 treatment (p = 0.0393). Flow cytometry and multiple-immunofluorescence confirmed that NSCLC with diabetes had significantly higher CD161+CD127+CD8+ T cells to CD8+T cells ratios than NSCLC patients without diabetes. The RNA-sequencing analysis revealed immune-cytotoxic genes were reduced in the CD161+CD127+CD8+ T cell subset compared to CD161+CD127-CD8+ T cells in NSCLC with diabetes. CD161+CD127+CD8+ T cells exhibited more T cell-exhausted phenotypes in NSCLC with diabetes. NSCLC patients with diabetes with ≥ 6.3% CD161+CD127+CD8+ T cells to CD8+T cells ratios showed worse PFS. These findings indicate that diabetes is a risk factor for NSCLC patients who undergo anti-PD-1 immunotherapy.CD161+CD127+CD8+ T cells could be a key indicator of a poor prognosis in NSCLC with diabetes. Our findings would help in advancing anti-PD-1 therapy in NSCLC patients with diabetes.
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Linfocitos T CD8-positivos , Carcinoma de Pulmón de Células no Pequeñas , Neoplasias Pulmonares , Humanos , Carcinoma de Pulmón de Células no Pequeñas/inmunología , Carcinoma de Pulmón de Células no Pequeñas/tratamiento farmacológico , Neoplasias Pulmonares/inmunología , Neoplasias Pulmonares/tratamiento farmacológico , Masculino , Femenino , Linfocitos T CD8-positivos/inmunología , Persona de Mediana Edad , Anciano , Inmunoterapia/métodos , Receptor de Muerte Celular Programada 1/antagonistas & inhibidores , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Inhibidores de Puntos de Control Inmunológico/farmacología , Subunidad alfa del Receptor de Interleucina-7/metabolismo , Diabetes Mellitus/inmunología , Diabetes Mellitus/tratamiento farmacológico , Subgrupos de Linfocitos T/inmunología , Subgrupos de Linfocitos T/metabolismo , Subgrupos de Linfocitos T/efectos de los fármacos , Pronóstico , AdultoRESUMEN
Frailty is a geriatric, multi-dimensional syndrome that reflects multisystem physiological change and is a transversal measure of reduced resilience to negative events. It is characterized by weakness, frequent falls, cognitive decline, increased hospitalization and dead and represents a risk factor for the development of Alzheimer's disease (AD). The fact that frailty is recognized as a reversible condition encourages the identification of earlier biomarkers to timely predict and prevent its occurrence. SAMP8 (Senescence-Accelerated Mouse Prone-8) mice represent the most appropriate preclinical model to this aim and were used in this study to carry transcriptional and metabolic analyses in the brain and plasma, respectively, upon a characterization at cognitive, motor, structural, and neuropathological level at 2.5, 6, and 9 months of age. At 2.5 months, SAMP8 mice started displaying memory deficits, muscle weakness, and motor impairment. Functional alterations were associated with a neurodevelopmental deficiency associated with reduced neuronal density and glial cell loss. Through transcriptomics, we identified specific genetic signatures well distinguishing SAMP8 mice at 6 months, whereas plasma metabolomics allowed to segregate SAMP8 mice from SAMR1 already at 2.5 months of age by detecting constitutively lower levels of acylcarnitines and lipids in SAMP8 at all ages investigated correlating with functional deficits and neuropathological signs. Our findings suggest that specific genetic alterations at central level, as well as metabolomic changes in plasma, might allow to early assess a frail condition leading to dementia development, which paves the foundation for future investigation in a clinical setting.
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Immune checkpoint inhibitors (ICIs) are approved to treat colorectal cancer (CRC) with mismatch-repair gene deficiency, but the response rate remains low. Value of current biomarkers to predict CRC patients' response to ICIs is unclear due to heterogeneous study designs and small sample sizes. Here, we aim to assess and quantify the magnitude of multiple biomarkers for predicting the efficacy of ICIs in CRC patients. We systematically searched MEDLINE, Embase, the Cochrane Library, and Web of Science databases (to June 2023) for clinical studies examining biomarkers for efficacy of ICIs in CRC patients. Random-effect models were performed for meta-analysis. We pooled odds ratio (OR) and hazard ratio (HR) with 95% confidence interval (CI) for biomarkers predicting response rate and survival. 36 studies with 1867 patients were included in systematic review. We found that a lower pre-treatment blood neutrophil-to-lymphocyte ratio (n=4, HR 0.37, 95%CI 0.21-0.67) predicts good prognosis, higher tumor mutation burden (n=10, OR 4.83, 95%CI 2.16-10.78) predicts response to ICIs, and liver metastasis (n=16, OR 0.32, 95%CI 0.16-0.63) indicates resistance to ICIs, especially when combined with VEGFR inhibitors. But the predictive value of tumor PD-L1 expression (n=9, OR 1.01, 95%CI 0.48-2.14) was insignificant in CRC. Blood neutrophil-to-lymphocyte ratio, tumor mutation burden, and liver metastasis, but not tumor PD-L1 expression, function as significant biomarkers to predict efficacy of ICIs in CRC patients. These findings help stratify CRC patients suitable for ICI treatments, improving efficacy of immunotherapy through precise patient management. (PROSPERO, CRD42022346716).