Search Results (287)

Oral squamous cell carcinoma (OSCC) remains one of the most common malignancies in the head and neck region, often preceded by a spectrum of oral potentially malignant disorders (OPMDs). Despite advances in diagnostic methods, reliable and non-invasive biomarkers for early detection and prognostic stratification are still lacking. In recent years, circulating cell-free DNA (cfDNA) has emerged as a promising liquid biopsy tool in several solid tumors, offering insights into tumor burden, heterogeneity, and molecular dynamics. However, its application in oral oncology remains underexplored. This study aims to review and discuss the current evidence on cfDNA quantification and mutation analysis (including TP53, NOTCH1, and EGFR) in patients with OPMDs and OSCC. Particular attention is given to cfDNA fragmentation patterns, methylation signatures, and tumor-specific mutations as prognostic and predictive biomarkers. Moreover, we highlight the challenges in standardizing pre-analytical and analytical workflows in oral cancer patients and explore the potential role of cfDNA in monitoring oral carcinogenesis. Understanding cfDNA dynamics in the oral cavity might offer a novel, minimally invasive strategy to improve early diagnosis, risk assessment, and treatment decision-making in oral oncology. Full article

Oral cancer, the most common form of head and neck cancer, is worldwide a serious public health problem. Most patients present a locally advanced disease, and face poor prognosis, even with multimodality treatment. They may also develop second primary tumors in the entirety of their upper aerodigestive tract. The most altered signaling pathways are the PI3K/AKT/mTOR, TP53, RB, and the WNT/β-catenin pathways. Genomic and molecular cytogenetic analyses have revealed frequent losses at 3p, 8p, 9p, and 18q, along with gains at 3q, 7p, 8q, and 11q, and several genes frequently affected have been identified, such as TP53, CCND1, CTTN, CDKN2A, EGFR, HRAS, PI3K, ADAM9, MGAM, SIRPB1, and FAT1, among others. Various epigenetic alterations were also found, such as the global hypomethylation and hypermethylation of CDKN2A, APC, MGMT, PTEN, CDH1, TFP12, SOX17, GATA4, ECAD, MGMT, and DAPK. Several microRNAs are upregulated in oral cancer, including miR-21, miR-24, miR-31, miR-184, miR-211, miR-221, and miR-222, while others are downregulated, such as miR-203, miR-100, miR-200, miR-133a, miR-133b, miR-138, and miR-375. The knowledge of this molecular pathogenesis has not yet been translated into clinical practice, apart from the use of cetuximab, an EGFR antibody. Oral tumors are also genetically heterogenous and affect several pathways, which means that, due to the continuous evolution of these genetic alterations, a single biopsy is not sufficient to fully evaluate the most adequate molecular targets when more drugs become available. Liquid biopsies, either resorting to circulating tumor cells, extracellular vesicles or cell-free nucleic acids, have the potential to bypass this problem, and have potential prognostic and staging value. We critically review the current knowledge on the molecular, genetic and epigenetic alterations in oral cancer, as well as the applications and challenges of liquid biopsies in its diagnosis, follow-up, and prognostic stratification. Full article

Head and neck squamous cell carcinomas (HNSCCs) that develop from the mucosal epithelium in the oral cavity, pharynx, and larynx are a heterogeneous group of malignant tumors. A lack of appropriate screening and diagnostic methods leads to late diagnoses, with the majority of patients having locally advanced disease, which is associated with a high risk of local recurrence and a poor prognosis and is usually treated with combination therapies. Biomarkers for predicting the therapy response and risk of recurrence in HNSCC patients are urgently needed. Liquid biopsy, e.g., the profiling of circulating biomarkers in bodily fluids, is a promising approach with increasing utility in the early detection and diagnosis of cancer, monitoring cancer progression, patient stratification and treatment selection, detecting minimal residual disease (MRD), and predicting recurrence across different cancer types, including HNSCC. Among liquid biomarkers, circulating tumor DNA (ctDNA), which is based on detecting tumor-specific mutations, insertions/deletions, copy number alterations, and methylation, is the most promising transformative tool in cancer management and personalized cancer treatment. In this review, we provide an update of recent data on the role of non-viral ctDNA in the management of HNSCC patients. Accumulating data suggests the enormous potential of ctDNA profiling by serial sampling during and after definitive therapy in detecting MRD and predicting recurrence in HNSSC patients treated with a single treatment modality (surgery or radiotherapy) or with combination therapies, including immune-checkpoint-inhibitor-based immunotherapy. By incorporating the latest immunotherapy trials and organizing the data by the treatment modality, this review offers a novel perspective not found in previous surveys. Full article

Triple-negative breast cancer (TNBC) is a heterogenous group of breast tumors. This type of breast tumor is relatively difficult to manage, due to the lack of expression of Hormone Receptors (HR) and human epidermal growth factor receptor (HER2). Efforts have been made to understand the factors involved in determining how a triple-negative breast tumor responds to therapy. The standard of treatment in most cases today is a combined modality of immune checkpoint inhibitors (ICIs) and chemotherapy with agents such as anti-mitotic (taxanes) or DNA-damaging agents (alkylating agents, cyclophosphamides, platin salts). In this study, we investigated the predictive and prognostic factors for TNBC, in the neoadjuvant setting; understanding each patient’s response before treatment initiation is crucial to guiding the subsequent approach and finally improving patient outcomes. We focused on tumor-infiltrating lymphocytes at the site of the primary tumor (TILs), circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), the mutational status of protein 53 (p53), and Ki-67, investigating the potential roles of these factors in predicting responses to anti-cancer agents. Full article

The advent of personalized medicine and novel therapeutic strategies has transformed the treatment landscape of non-small cell lung cancer (NSCLC), significantly improving patient survival. However, only a minority of patients experience a durable benefit, as intrinsic or acquired resistance remains a major challenge. Understanding the complex mechanisms of resistance—linked to tumor biology, the tumor microenvironment (TME), and host factors—is crucial to overcoming these barriers. Recent innovations in diagnostics, including artificial intelligence and liquid biopsy, offer promising tools to refine therapeutic decisions. Machine Learning and Deep Learning provide predictive algorithms that enhance diagnostic accuracy and prognostic assessment. Techniques like single-cell RNA sequencing and pathomics offer deeper insights into the role of the TME. Liquid biopsy, as a minimally invasive method, enables real-time detection of circulating tumor components, facilitating the identification of predictive and prognostic biomarkers and illuminating tumor heterogeneity. These translational research advances are revolutionizing the understanding of cancer biology and are key to optimizing personalized treatment strategies. This review highlights emerging tools aimed at improving diagnostic and therapeutic precision in NSCLC, underscoring their role in decoding the interplay between tumor cells, the TME, and the host to ultimately improve patient outcomes. Full article

Breast cancer is a highly heterogeneous disease, with tumors capable of adapting to shifting conditions, making the development of effective personalized therapies particularly challenging. Patient-derived models, such as patient-derived organoids (PDOs) and circulating tumor cell (CTC) cultures, have emerged as powerful tools for investigating intra- and inter-tumor heterogeneity. These models largely retain the genetic, phenotypic, and microenvironmental features of the original tumors, providing valuable insights into disease progression, drug response, and resistance mechanisms. Furthermore, by enabling tumors’ spatiotemporal molecular profiling, PDOs and CTCs offer a dynamic approach to assess treatment efficacy over time. However, to fully capture the complexity of breast cancer heterogeneity, it is required to develop models from multiple tumor and blood samples collected throughout the course of treatment. This review explores the potential of integrating PDOs and CTC models to better understand intra-tumor heterogeneity while addressing key challenges in developing patient-derived models that accurately recapitulate patients’ tumors to advance personalized care. The integration of PDOs and CTCs could represent a paradigm shift in the personalized management of metastatic breast cancer. Full article

Choosing the optimal first-line treatment for patients with advanced non-small cell lung cancer (NSCLC) with anaplastic lymphoma kinase (ALK) rearrangements can be challenging in daily practice. Although clinical trials with next-generation ALK-tyrosine kinase inhibitors (TKIs) have played a key role in evaluating their efficacy and safety, which patients benefit from a specific ALK-TKI may still be questioned. The methodological inconsistencies in these trials, which led to the inclusion of different patient populations, appear to have been inadequately addressed. ALK-rearranged NSCLC is a heterogeneous disease, and co-existing molecular alterations may affect the outcome. The questions explored in these trials appear insufficient to support a personalized approach to the first-line treatment, while defining long-term responders and early progressors would be clinically useful. This narrative review presents several considerations from oncologists’ and pathologists’ perspectives. We propose defining favorable and unfavorable features, such as histology, type of ALK fusion, co-existing molecular alterations, plasma circulating tumor DNA (ctDNA, performance status, and brain metastases, to help identify patients with lower and higher risk of progression. Consequently, the most potent ALK-TKI to date, Lorlatinib, may be considered as the first-line treatment for high-risk patients with unfavorable features, while sequencing of ALK-TKIs may be appropriate for low-risk patients with favorable features. Although ALK signal inhibition is critical in this disease, it may not be sufficient for clinical control due to de novo co-alterations. A more personalized approach to first-line therapy requires consideration of risk factors for each patient. Full article

Background/Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized advanced melanoma treatment, yet many patients fail to achieve sustained clinical benefit. Several biomarkers, including tumor microenvironment (TME) signature, PD-1/PD-L1 expression, and IFN-γ signaling, have been proposed. However, robust predictive markers remain elusive. This study aimed to identify molecular markers of response by analyzing tumor and peripheral immune signatures. Methods: This study analyzed 21 advanced melanoma patients treated with ICIs. Formalin-fixed, paraffin-embedded tumors underwent RNA-sequencing targeting 1392 immuno-oncology probes. Genes significantly associated with progression-free survival (PFS) by log-rank test underwent hierarchical clustering analysis (HCA). Differential expression and xCell analyses were then performed on the resulting clusters. Cox multivariate analysis was applied to identify independent PFS predictors. Pre-treatment peripheral blood mononuclear cells were analyzed by mass cytometry, followed by FlowSOM and UMAP clustering. Results: Fifty-five genes significantly associated with PFS identified two molecular clusters via HCA. Cluster A demonstrated prolonged PFS (59.4 vs. 2.4 months, p = 0.0004), while Cluster B was characterized by downregulated IFN-γ signaling, antigen presentation pathways, and reduced immune score. Multivariate Cox analysis confirmed molecular cluster as an independent PFS predictor (p < 0.001). Mass cytometry revealed higher frequencies of circulating PD-1+ CD4+ effector memory (EM) T subpopulations among responders. Conclusions: This study highlights the potential role of molecular and immune profiling in predicting ICI response in advanced melanoma. The identification of distinct molecular clusters underscores significant TME heterogeneity, with immune-cold tumor clusters associated with poorer outcomes. Furthermore, circulating PD-1+ T subpopulations emerged as potential markers of ICI response, suggesting their value in improving patient stratification. Full article

Circulating tumor cells (CTCs) are multifaceted biomarkers with significant potential for precision oncology, offering opportunities to refine diagnoses and personalize treatments across various cancer types, including colorectal and breast cancer. CTC assays serve as reliable prognostic indicators, even during chemotherapy and/or molecularly targeted therapies. Notably, CTCs exhibit heterogeneity that gradually develops during carcinogenesis and becomes more pronounced in advanced disease stages. These intra- and intertumoral heterogeneities pose challenges, particularly when drug-resistant clones emerge following therapy. The dynamic behavior of CTCs provides valuable insights into treatment response and prognosis. Extensive efforts have led to the development of technologies for effective CTC isolation, accelerating their clinical implementation. While both CTC and circulating tumor DNA (ctDNA) tests offer prognostic value, they reflect different aspects of tumor biology: CTC counts indicate tumor progression, while ctDNA levels correlate with tumor burden. The combined analysis is expected to yield complementary insights. CTC tests are feasible in general hospitals and may serve as tumor markers comparable to, or even superior to, conventional markers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) for colorectal cancer, and CA15-3 for breast cancer. Early incorporation of CTC tests into routine blood panels appears to be a rational and promising approach. Full article

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally, driven by chronic liver disease and a complex tumor microenvironment (TME). Recent advances in spatial omics, single-cell analyses, and AI-driven digital pathology have shed light on the intricate heterogeneity of HCC, highlighting key roles for immune suppression, angiogenesis, and fibrosis in tumor progression. This review synthesizes current epidemiological trends, noting a shift from viral hepatitis to metabolic syndrome as a primary etiology in Western populations, and elucidates how TME components—such as tumor-associated macrophages, cancer-associated fibroblasts, vascular endothelial cells, and immunosuppressive cytokines—contribute to resistance against conventional therapies. We detail the evolution of immunotherapeutic strategies from monotherapy to combination regimens, including dual immune checkpoint blockade and the integration of antiangiogenic agents. Emerging circulating and tissue-based biomarkers offer promise for enhanced patient stratification and real-time monitoring of treatment responses. Collectively, these innovations herald a paradigm shift toward TME-directed precision oncology in HCC, emphasizing the need for multi-targeted approaches to synergistically modulate interacting cellular constituents and ultimately improve clinical outcomes. Full article

Liquid biopsy through the analysis of circulating tumor DNA (ctDNA) is emerging as a powerful and non-invasive tool complementing tissue biopsy in lymphoma management. Whilst tissue biopsy remains the diagnostic gold standard, it fails to detect the molecular heterogeneity of the tumor’s multiple compartments and poses challenges for sequential disease monitoring. In diffuse large-B-cell lymphoma (DLBCL), ctDNA facilitates non-invasive genotyping by identifying hallmark mutations (e.g., MYD88, CD79B, EZH2), enabling molecular cluster classification. Dynamic changes in ctDNA levels during DLBCL treatment correlate strongly with progression-free survival and overall survival, underscoring its value as a predictive and prognostic biomarker. In Hodgkin’s lymphoma, characterized by a scarcity of malignant cells in tissue biopsies, ctDNA provides reliable molecular insights into tumor biology, response to therapy, and relapse risk. In primary central nervous system lymphoma, the detection of MYD88 L265P in ctDNA offers a highly sensitive, specific, and minimally invasive diagnostic option. Likewise, in aggressive T-cell lymphomas, ctDNA supports molecular profiling, aligns with tumor burden, and shows high concordance with tissue-based results. Ongoing and future clinical trials will be critical for validating and standardizing ctDNA applications, ultimately integrating liquid biopsy into routine clinical practice and enabling more personalized and dynamic lymphoma care. Full article

Breast cancer (BC) is a heterogeneous disease with high metastasis potential, especially in the bones, liver, and lungs. Circulating tumor cells (CTCs), which emerge from active tumors, represent an early step toward metastasis and are associated with poor prognosis. CTCs of carcinoma origin are believed to express EpCAM and cytokeratins (CKs), common epithelial markers that are frequently used to identify them. However, in practice, the most aggressive CTCs lose the expression of those markers, leading to the partial loss of important information. Thus, finding some novel markers that identify CTCs regardless of their heterogeneity is crucial. A specific bioinformatics workflow integrating primary tumor and diverse BC cell lines transcriptomic expression analysis was developed and compared with single CTC transcriptomic analyses. We have identified a set of genes that are overexpressed in primary BC cells and are commonly upregulated among BC cell lines. Fifty of them were also found to be expressed in BC CTCs by single-cell transcriptomic analysis. Further in silico sorting narrowed this list to 12 genes. Using ScreenCell technology to isolate cancer cells spiked into normal blood, we tested the protein expression of all corresponding genes in vitro using the double immunocytochemistry method and validated MARCKSL1, SLC9A3R1, and RHOD as the most expressed markers. We then isolated the CTCs of 40 LN-invaded BC patients and 18 healthy donors using ScreenCell technology and showed that the combination of these three markers resulted in significantly better recognition of CTCs compared to EpCAM and CK conventional markers. Employing these novel markers, we found a clear distinction between blood samples from patients and healthy donors. In conclusion, through a specific bioinformatics workflow, in addition to in vitro and further clinical validations, we found three novel markers to precisely identify CTCs. These markers, when used together, enable a significantly more efficient identification of CTCs compared to conventional epithelial markers. Full article

Background/Objectives: Liver and tumor-infiltrating T cells in hepatocellular carcinoma (HCC) are heterogeneous, comprising the CD69⁺ tissue-resident T-cell and the CD69⁻ circulating T-cell populations. However, the impact of these distinct T-cell populations on patient prognosis is unclear; hence, further studies are needed. Methods: Tumor and distant liver tissues from 57 HCC patients with various chronic liver disease etiologies were analyzed. Single-cell dissociation and flow cytometry were used to assess CD69⁺ and CD69⁻ T-cell populations and their correlation with recurrence-free survival (RFS). Results: CD69⁺/CD69⁻ subpopulations within CD4⁺ and CD8⁺ T cells varied by patient and alcohol etiology. CD69⁻ populations among CD4⁺ T cells were less frequent in both tumor and non-tumor tissues of alcohol-related HCC patients (p < 0.05). Higher frequencies of CD69⁻CD4⁺ and CD8⁺ T cells in tumors and CD69⁺CD103⁺CD8⁺ T cells in liver tissues were associated with better RFS. CD69- T cells expressed lower PD-1 levels, indicating less exhaustion, with PD-1 expression inversely correlated with CD69⁻ frequency. PD-1 expression was higher in CD69⁻CD4⁺ T cells in alcohol-related HCC. Conclusions: We provided a detailed analysis of the heterogeneous characteristics of tumor- and liver-infiltrating T cells in HCC, emphasizing the distinct roles of CD69⁺ and CD69⁻ cell populations and their impact on RFS. CD69⁺ T cells were associated with immune exhaustion and tumor aggressiveness, whereas CD69⁻ T cells appeared to significantly contribute to the influence of alcohol intake on the immune landscape of HCC in the tumor microenvironment. However, further research should validate these findings in larger cohorts to enhance our understanding. Full article

Glioblastoma (GBM) is the most prevalent and aggressive primary central nervous system (CNS) tumor in adults. GBMs exhibit genetic and epigenetic heterogeneity, posing difficulties in surveillance and being associated with high rates of recurrence and mortality. Nevertheless, due to the high infiltrating ability of glioblastoma cells, and regardless of the considerable progress made in radiotherapeutic, chemotherapeutic, and surgical protocols, the treatment of GBM is still inefficient. Conventional diagnostic approaches, such as neuroimaging techniques and tissue biopsies, which are invasive maneuvers, present certain challenges and limitations in providing real-time information, and are incapable of differentiating pseudo-progression related to treatment from real tumor progression. Liquid biopsy, the analysis of biomarkers such as nucleic acids (DNA/RNA), circulating tumor cells (CTCs), extracellular vesicles (EVs), or tumor-educated platelets (TEPs) that are present in body fluids, provides a minimally invasive and dynamic method of diagnosis and continuous monitoring for GBM. It represents a new preferred approach that enables a superior manner to obtain data on possible tumor risk, prognosis, and recurrence assessment. This article is a literature review that aims to provide updated information about GBM biomarkers in body fluids and to analyze their clinical efficiency. Full article

The advent of immune checkpoint blockade (ICB) has transformed cancer immunotherapy, enabling remarkable long-term outcomes and improved survival, particularly with ICB combination treatments. However, clinical benefits remain confined to a subset of patients, and life-threatening immune-related adverse effects pose a significant challenge. This limited efficacy is attributed to cancer heterogeneity, which is mediated by ligand–receptor interactions, exosomes, secreted factors, and key transcription factors. Oncogenic regulators like E2F1 and MYC drive metastatic tumor environments and intertwine with immunoregulatory pathways, impairing T cell function and reducing immunotherapy effectiveness. To address these challenges, FDA-approved biomarkers, such as tumor mutational burden (TMB) and programmed cell death-ligand 1 (PD-L1) expression, help to identify patients most likely to benefit from ICB. Yet, current biomarkers have limitations, making treatment decisions difficult. Recently, T cells—the primary target of ICB—have emerged as promising biomarkers. This review explores the relationship between cancer drivers and immune response, and emphasizes the role of CD8+ T cells in predicting and monitoring ICB efficacy. Tumor-infiltrating CD8+ T cells correlate with positive clinical outcomes in many cancers, yet obtaining tumor tissue remains complex, limiting its practical use. Conversely, circulating T cell subsets are more accessible and have shown promise as predictive biomarkers. Specifically, memory and progenitor exhausted T cells are associated with favorable immunotherapy responses, while terminally exhausted T cells negatively correlate with ICB efficacy. Ultimately, combining biomarkers enhances predictive accuracy, as demonstrated by integrating TMB/PD-L1 expression with CD8+ T cell frequency. Computational models incorporating cancer and immune signatures could further refine patient stratification, advancing personalized immunotherapy. Full article