Search Results (127)

Liquid biopsy (LB) has gained attention as a valuable approach for cancer diagnostics, providing a minimally invasive option compared to conventional tissue biopsies and helping to overcome issues related to patient discomfort and procedural invasiveness. Recent advances in biosensor technologies, particularly photonic sensors, have improved the accuracy, speed, and real-time capabilities for detecting circulating biomarkers in biological fluids. Incorporating these tools into clinical practice facilitates more informed therapeutic choices and contributes to tailoring treatments to individual patient profiles. This review highlights the clinical potential of LB, examines technological limitations, and outlines future research directions. Departing from traditional biosensor focused reviews, it adopts a reverse-mapping approach grounded in clinically relevant tumor biomarkers. Specifically, biomarkers associated with prevalent cancers, such as breast, prostate, and lung cancers, serve as the starting point for identifying the most suitable photonic sensing platforms. The analysis underscores the need to align sensor design with the physicochemical properties of each biomarker and the operational requirements of the application. No photonic platform is universally optimal; rather, each exhibits specific strengths depending on performance metrics such as sensitivity, limit of detection, and easy system integration. Within this framework, the review provides a comprehensive assessment of emerging photonic biosensors and outlines key priorities to support their effective clinical translation in cancer diagnostics. 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

Lung cancer remains the leading cause of cancer-related mortality globally, largely due to late-stage diagnoses. While low-dose computed tomography (LDCT) has improved early detection and reduced mortality in high-risk populations, traditional screening strategies often adopt a one-size-fits-all approach based primarily on age and smoking history. This can lead to limitations, such as overdiagnosis, false positives, and the underrepresentation of non-smokers, which are especially prevalent in Asian populations. Precision medicine offers a transformative solution by tailoring screening protocols to individual risk profiles through the integration of clinical, genetic, environmental, and radiological data. Emerging tools, such as risk prediction models, radiomics, artificial intelligence (AI), and liquid biopsies, enhance the accuracy of screening, allowing for the identification of high-risk individuals who may not meet conventional criteria. Polygenic risk scores (PRSs) and molecular biomarkers further refine stratification, enabling more personalized and effective screening intervals. Incorporating these innovations into clinical workflows, alongside shared decision-making (SDM) and robust data infrastructure, represents a paradigm shift in lung cancer prevention. However, implementation must also address challenges related to health equity, algorithmic bias, and system integration. As precision medicine continues to evolve, it holds the promise of optimizing early detection, minimizing harm, and extending the benefits of lung cancer screening to broader and more diverse populations. This review explores the current landscape and future directions of precision medicine in lung cancer screening, emphasizing the need for interdisciplinary collaboration and population-specific strategies to realize its full potential in reducing the global burden of lung cancer. Full article

Background: Identifying liquid biopsy biomarkers with high efficacy is crucial for cancer diagnosis. Exosomal cargo, including miRNAs and proteins, offers enhanced stability in biofluids compared with their free circulating forms, but direct comparisons of their diagnostic performance remain limited. This study evaluates and compares the diagnostic value of selected miRNAs and protein markers in exosomal versus non-exosomal fractions across stages of lung carcinogenesis in a rat model. Methods: Lung cancer was induced in rats, and blood and lung tissue samples were collected at consecutive stages of tumor induction. We investigated the expression patterns of key miRNAs (miR-19b, miR-21, and miR-145) in exosomes, serum, and tissue and quantified levels of tumor biomarkers CEA and CYFRA 21-1 in exosomal and serum fractions. Results: Our results revealed distinct expression patterns of the evaluated miRNAs across exosomes, serum, and tissue, throughout different stages of tumor induction. The expression of exosomal miRNAs dynamically changed in parallel with the tumor induction process, demonstrating high diagnostic efficacy. Specifically, exosomal miR-19b and miR-21 were significantly upregulated from an early induction stage, whereas their serum and tissue forms increased only during the late stages of induction. On the other hand, miR-145 was consistently downregulated across all fractions at every stage. Both exosomal and serum CEA levels increased significantly during tumor induction, while serum CYFRA 21-1 outperformed its exosomal counterpart. Strong positive correlations linked exosomal miR-19b and miR-145 with their non-exosomal counterparts, while moderate correlations were seen for miR-21 and the protein markers. Conclusions: Our findings underscore the value of integrating exosomal biomarkers in liquid biopsies, highlighting their potential to improve early detection and monitoring of lung cancer development. Full article

Circulating free DNA (cfDNA) is genetic material released from various cells into bodily fluids. Among its fractions, circulating tumor DNA (ctDNA) originates from tumor cells and reflects their genetic material, including mutations and epigenetic changes. Methods commonly employed for detecting ctDNA in blood include next-generation sequencing (NGS) and various types of PCR. The presence of ctDNA can be utilized in liquid biopsies for many diagnostic purposes related to various cancers. It is a minimally invasive method of sampling molecular compounds from tumor cells. In this paper, we focus on current knowledge regarding the liquid biopsy of blood ctDNA in the context of lung cancer, one of the leading causes of cancer-related mortality. Currently, as a clinically approved method, liquid biopsy serves as a complementary technique in NSCLC diagnostic and genetic profiling. Other applications of liquid biopsy that are still being investigated include the detection of minimal residual disease (MRD) after curative treatment and response monitoring to systemic treatment. This review discusses current and future potential directions for the development and implementation of ctDNA for patients with NSCLC. Full article

Background: Liquid biopsy using plasma cfDNA has been established as a tool for informing the management of advanced-stage NSCLC. However, its effectiveness in early lung cancer detection, including the identification of high-risk cases, remains to be determined. Methods: We analyzed plasma cfDNA and matched tumors from 117 stage I–IV lung adenocarcinoma cases and compared the variants identified across all stages using the Oncomine Precision Assay on the Genexus^TM next-generation sequencing platform. Results: Cancer-specific mutations were detected in plasma from approximately 72% (84/117) of cases (all stages), with detection rates increasing by stage. Concordance between cfDNA and tumor tissue also increased with stage 0% (stage I), 19% (stage II), 45% (stage III), and 75% (stage IV). KRAS mutations were concordant in approximately 22% (6/27) of stage II and 46% (11/24) of stage III cases. Clinically important EGFR variants showed concordance in 11% (1/9) of stage II and 80% (8/10) in stage III/IV cases. Actionable mutations, targetable with FDA-approved drugs, were detected in 11% (4/37) of stage II, 27% (12/45) of stage III, and 55% (4/9) of stage IV cases, underscoring the potential of liquid biopsy for early detection of therapeutic targets. Moreover, co-occurring mutations with varying actionability were identified more frequently in plasma than in tumor tissues. Plasma detection of clinically important KRAS and EGFR variants was mostly associated with advanced-stage disease, suggesting the presence of these variants in plasma as a potential indication of disease progression. Conclusions: Liquid biopsy holds promise for identifying high-risk lung adenocarcinoma cases and serves as a complementary diagnostic tool in advanced stages, enhancing disease management strategies. Full article

MicroRNAs (miRNAs) are small RNA molecules that do not have coding functions but play essential roles in various biological processes. In lung cancer, miRNAs affect the processes of tumor initiation, progression, metastasis, and resistance to treatment by regulating gene expression. Tumor-suppressive miRNAs inhibit oncogenic pathways, while oncogenic miRNAs, known as oncomiRs, promote malignant transformation and tumor growth. These dual roles position miRNAs as critical players in lung cancer biology. Studies in recent years have shown the significant potential of miRNAs as both prognostic and diagnostic biomarkers. Circulating miRNAs in plasma or sputum demonstrate specificity and sensitivity in detecting early-stage lung cancer. Liquid biopsy-based miRNA panels distinguish malignant from benign lesions, and specific miRNA expression patterns correlate with disease progression, response to treatment, and overall survival. Therapeutically, miRNAs hold promise for targeted interventions. Strategies such as miRNA replacement therapy using mimics for tumor-suppressive miRNAs and inhibition of oncomiRs with antagomiRs or miRNA sponges have shown preclinical success. Key miRNAs, including the let-7 family, miR-34a, and miR-21, are under investigation for their therapeutic potential. It should be emphasized that delivery difficulties, side effects, and limited stability of therapeutic miRNA molecules remain obstacles to their clinical use. This article examines the roles of miRNAs in lung cancer by indicating their mechanisms of action, diagnostic significance, and therapeutic potential. By addressing current limitations, miRNA-based approaches could revolutionize lung cancer management, offering precise, personalized, and minimally invasive solutions for diagnosis and treatment. Full article

Lung cancer is the leading cause of cancer-related death worldwide, with 1.8 million deaths annually. Early detection is vital for improving patient outcomes; however, survival rates remain low due to late-stage diagnoses. Accumulating data supports the idea that screening methods are useful for improving early diagnosis in high-risk patients. However, several barriers limit the application of lung cancer screening in real-world settings. The widespread diffusion of artificial intelligence (AI), radiomics, and machine learning has dramatically changed the current diagnostic landscape. This review explores the potential of AI and biomarker-driven methods, particularly liquid biopsy, in enhancing early lung cancer detection. We report the findings of major randomized controlled trials, cohort studies, and research on AI algorithms that use multi-modal imaging (e.g., CT and PET scans) and liquid biopsy to identify early molecular alterations. AI algorithms enhance diagnostic accuracy by automating image analysis and reducing inter-reader variability. Biomarker-driven methods identify molecular alterations in patients before imaging signs of cancer are evident. Both AI and liquid biopsy show the potential to improve sensitivity and specificity, enabling the detection of early-stage cancers that traditional methods, like low-dose CT (LDCT) scans, might miss. Integrating AI and biomarker-driven methods offers significant promise for transforming lung cancer screening. These technologies could enable earlier, more accurate detection, ultimately improving survival outcomes. AI-driven lung cancer screening can achieve over 90% sensitivity, compared to 70–80% with traditional methods, and can reduce false positives by up to 30%. AI also boosts specificity to 85–90%, with faster processing times (a few minutes vs. 30–60 min for radiologists). However, challenges remain in standardizing these approaches and integrating them into clinical practice. Ongoing research is essential to fully realize their clinical benefits and enhance timely interventions. Full article

Background: Lung cancer is the leading cause of cancer-related mortality globally, with late-stage diagnoses contributing to poor survival rates. While lung cancer screening with low-dose computed tomography (LDCT) has proven effective in reducing mortality among heavy smokers, its limitations, including high false-positive rates and resource intensiveness, restrict widespread use. Liquid biopsy, particularly using microRNA (miRNA) biomarkers, offers a promising adjunct to current screening strategies. This study aimed to evaluate the predictive power of a panel of serum miRNA biomarkers for lung cancer detection. Patients and Methods: A case-control study was conducted at two tertiary hospitals, enrolling 82 lung cancer cases and 123 controls. We performed an extensive literature review to shortlist 25 candidate miRNAs, of which 16 showed a significant two-fold increase in expression compared to the controls. Machine learning techniques, including Random Forest, K-Nearest Neighbors, Neural Networks, and Support Vector Machines, were employed to identify the top six miRNAs. We then evaluated predictive models, incorporating these biomarkers with lung nodule characteristics on LDCT. Results: A prediction model utilising six miRNA biomarkers (mir-196a, mir-1268, mir-130b, mir-1290, mir-106b and mir-1246) alone achieved area under the curve (AUC) values ranging from 0.78 to 0.86, with sensitivities of 70–78% and specificities of 73–85%. Incorporating lung nodule size significantly improved model performance, yielding AUC values between 0.96 and 0.99, with sensitivities of 92–98% and specificities of 93–98%. Conclusions: A prediction model combining serum miRNA biomarkers and nodule size showed high predictive power for lung cancer. Integration of the prediction model into current lung cancer screening protocols may improve patient outcomes. Full article

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Advances in tissue-based biomarkers have significantly enhanced diagnostic and therapeutic approaches in NSCLC, enabling precision medicine strategies. This review provides a comprehensive analysis of the molecular pathologist’s practical approach to assessing NSCLC biomarkers across various specimen types (liquid biopsy, broncho–alveolar lavage, transbronchial biopsy/endobronchial ultrasound-guided biopsy, and surgical specimen), including challenges such as biological heterogeneity and preanalytical variability. We discuss the role of programmed death ligand 1 (PD-L1) immunohistochemistry in predicting immunotherapy response, the practice of histopathological tumor regression grading after neoadjuvant chemoimmunotherapy, and the application of DNA- and RNA-based techniques for detecting actionable molecular alterations. Finally, we emphasize the critical need for quality management to ensure the reliability and reproducibility of biomarker testing in NSCLC. Full article

Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy has shown significant promise in the context of liquid biopsy, offering a potential tool for cancer diagnostics. Unlike traditional tissue biopsies, which may not fully capture the clonal heterogeneity of tumors, liquid biopsy reflects the dynamic state of the disease and its progression more comprehensively. Biofluids such as serum and plasma are low-cost, minimally invasive diagnostic media with well-established clinical uses. This review assesses the use of ATR-FTIR spectroscopy to detect biochemical changes in biofluids linked to various malignancies, including breast, ovarian, endometrial, prostate, bladder, kidney, pancreatic, colorectal, hepatic, esophageal, gastric, lung, and brain cancers. While ATR-FTIR offers the advantages of rapid, minimally invasive detection and real-time disease monitoring, its integration into clinical practice faces challenges, particularly in terms of reproducibility due to variability in sample preparation, spectral acquisition, and data processing. The translation of ATR-FTIR into routine diagnostics will require validation through large-scale cohort studies and multicenter trials to ensure its clinical reliability and effectiveness. Full article

Colorectal cancer (CRC) and lung cancer (LC) are leading causes of cancer-related mortality, highlighting the need for minimally invasive diagnostic, prognostic, and predictive markers for these cancers. Proteins secreted by a tumor into the extracellular space directly, known as the tumor secretome, as well as proteins in the extra-cellular vesicles (EVs), represent an attractive source of biomarkers for CRC and LC. We performed proteomic analyses on secretome and EV samples from LC (A549, NCI-H23, NCI-H460) and CRC (Caco2, HCT116, HT-29) cell lines and targeted mass spectrometry on EVs from plasma samples of 20 patients with CRC and 19 healthy controls. A total of 782 proteins were identified across the CRC and LC secretome and EV samples. Of these, 22 and 44 protein markers were significantly elevated in the CRC and LC samples, respectively. Functional annotation revealed enrichment in proteins linked to metastasis and tumor progression for both cancer types. In EVs isolated from the plasma of patients with CRC, ITGB3, HSPA8, TUBA4A, and TLN1 were reduced, whereas FN1, SERPINA1, and CST3 were elevated, compared to healthy controls. These findings support the development of minimally invasive liquid biopsy methods for the detection, prognosis, and treatment monitoring of LC and CRC. Full article

Background: Lung cancer remains the leading cause of cancer mortality globally with EGFR mutations representing a significant driver in advanced non-small cell lung cancer (aNSCLC). The timely detection of these mutations is critical for initiating targeted therapy, yet tissue biopsy limitations often delay treatment. Methods: This multicenter prospective study evaluated the clinical utility of liquid biopsy (LBx) in real-life settings for the early diagnosis of EGFR mutations in patients with suspected aNSCLC. Circulating tumor DNA (ctDNA) was analyzed using the Cobas EGFR Mutation Test and compared to tissue-based next-generation sequencing (NGS). Results: Among 366 aNSCLC patients tested, LBx demonstrated a significantly shorter median turnaround time (TAT) of 3 days compared to 26 days for tissue NGS (p < 0.001) with 100% specificity and 65% sensitivity for EGFR mutation detection. LBx identified actionable EGFR mutations in cases where tissue biopsy was insufficient or unavailable, enabling 43.7% of patients to commence targeted therapy based on ctDNA results prior to biopsy confirmation. Conclusions: These findings highlight the potential of LBx to reduce diagnostic delays and improve access to personalized therapies in a real-world setting. Integrating LBx into routine diagnostic workflows may address current gaps in molecular testing, ensuring timely and precise treatment for aNSCLC patients. Full article

Exosome-derived microRNAs (miRNAs) are potential biomarkers for lung cancer detection and monitoring through liquid biopsy. These small, non-coding RNA molecules are found within exosomes, which are extracellular vesicles released from cells. Their stability in biofluids, such as blood, positions them as candidates for minimally invasive diagnostics. Multiple studies have shown that lung cancer patients exhibit distinct miRNA profiles compared to healthy individuals. This finding suggests that exosome-derived miRNAs could serve as valuable biomarkers for diagnosis, prognosis, and evaluating therapeutic responses. This review summarizes recent research on exosome-derived miRNAs in liquid biopsies, including blood, pleural effusion, and pleural lavage, as biomarkers for lung cancer, focusing on publications from the last five years. Full article

Liquid biopsy enables real-time monitoring of tumor development and response to therapy through the analysis of CTCs and ctDNA. NALCN is a sodium leak channel that is frequently involved in tumor evolution and immunity and acts as a tumor suppressor. Deletion of NALCN has been shown to increase cancer metastasis and the number of CTCs in peripheral blood. In this study, we investigated for the first time NALCN promoter methylation in (a) Aza-treated cell lines (A549, TE671, BT20, and MDA-MB-468), (b) paired NSCLC tissues (n = 22), and (c) plasma cell-free DNA (ctDNA) from patients with NSCLC (early stage n = 39, metastatic n = 39) and DNA from 10 healthy donors (HD) using a newly developed highly specific and sensitive real-time MSP method. Treatment with 5′-aza-dC induced the expression of NALCN only in the A549 cell line, suggesting that DNA methylation regulates its expression in certain cancers. The mRNA expression levels of NALCN were quantified in non-small cell lung cancer (NSCLC) and adjacent non-cancerous tissues, and it was found to be underexpressed in 54.5% of tumor tissues, with significantly higher expression in recurrence-free patients (p = 0.009) than in patients who relapsed. The NALCN methylation level was not statisticallysignificantlycorrelated with the corresponding expression (p = 0.439), while Kaplan–Meier analysis showed an association between NALCN promoter hypermethylation and worse disease-free intervals (DFIs) (p = 0.017). Evaluation of NALCN methylation in ctDNA revealed that it was detected in 5.1% of early and 10.2% of advanced cases. Our results strongly suggest that epigenetic inactivation of NALCN may be a predictor of metastasis in NSCLC. Our results should be validated in further studies based on a larger patient cohort to further investigate whether DNA methylation of the NALCN promoter could serve as a potential prognostic DNA methylation biomarker and predictor of metastasis in NSCLC. Full article