The Role of Liquid Biopsy in Early Diagnosis of Lung Cancer

Exploring the potential of multiomics liquid biopsy testing in the clinical setting of lung cancer

The transformative role of artificial intelligence (AI) and multiomics could enhance the diagnostic and prognostic capabilities of liquid biopsy (LB) for lung cancer (LC). Despite advances, the transition from tissue biopsies to more sophisticated, non-invasive methods like LB has been impeded by challenges such as the heterogeneity of biomarkers and the low concentration of tumour-related analytes. The advent of multiomics - enabled by deep learning algorithms - offers a solution by allowing the simultaneous analysis of various analytes across multiple biological fluids, presenting a paradigm shift in cancer diagnostics. Through multi-marker, multi-analyte and multi-source approaches, this review showcases how AI and multiomics are identifying clinically valuable biomarker combinations that correlate with patients' health statuses. However, the path towards clinical implementation is fraught with challenges, including study reproducibility and lack of methodological standardization, thus necessitating urgent solutions to solve these common issues.

Predicting Lung Cancer Survival to the Future: Population-Based Cancer Survival Modeling Study

BACKGROUND

Lung cancer remains the leading cause of cancer-related mortality globally, with late diagnoses often resulting in poor prognosis. In response, the Lung Ambition Alliance aims to double the 5-year survival rate by 2025.

OBJECTIVE

Using the Taiwan Cancer Registry, this study uses the survivorship-period-cohort model to assess the feasibility of achieving this goal by predicting future survival rates of patients with lung cancer in Taiwan.

METHODS

This retrospective study analyzed data from 205,104 patients with lung cancer registered between 1997 and 2018. Survival rates were calculated using the survivorship-period-cohort model, focusing on 1-year interval survival rates and extrapolating to predict 5-year outcomes for diagnoses up to 2020, as viewed from 2025. Model validation involved comparing predicted rates with actual data using symmetric mean absolute percentage error.

RESULTS

The study identified notable improvements in survival rates beginning in 2004, with the predicted 5-year survival rate for 2020 reaching 38.7%, marking a considerable increase from the most recent available data of 23.8% for patients diagnosed in 2013. Subgroup analysis revealed varied survival improvements across different demographics and histological types. Predictions based on current trends indicate that achieving the Lung Ambition Alliance's goal could be within reach.

CONCLUSIONS

The analysis demonstrates notable improvements in lung cancer survival rates in Taiwan, driven by the adoption of low-dose computed tomography screening, alongside advances in diagnostic technologies and treatment strategies. While the ambitious target set by the Lung Ambition Alliance appears achievable, ongoing advancements in medical technology and health policies will be crucial. The study underscores the potential impact of continued enhancements in lung cancer management and the importance of strategic health interventions to further improve survival outcomes.

Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques

Machine learning offers significant potential for lung cancer detection, enabling early diagnosis and potentially improving patient outcomes. Feature extraction remains a crucial challenge in this domain. Combining the most relevant features can further enhance detection accuracy. This study employed a hybrid feature extraction approach, which integrates both Gray-level co-occurrence matrix (GLCM) with Haralick and autoencoder features with an autoencoder. These features were subsequently fed into supervised machine learning methods. Support Vector Machine (SVM) Radial Base Function (RBF) and SVM Gaussian achieved perfect performance measures, while SVM polynomial produced an accuracy of 99.89% when utilizing GLCM with an autoencoder, Haralick, and autoencoder features. SVM Gaussian achieved an accuracy of 99.56%, while SVM RBF achieved an accuracy of 99.35% when utilizing GLCM with Haralick features. These results demonstrate the potential of the proposed approach for developing improved diagnostic and prognostic lung cancer treatment planning and decision-making systems.

Circulating cell-free DNA-based methylation pattern in plasma for early diagnosis of esophagus cancer

With the increased awareness of early tumor detection, the importance of detecting and diagnosing esophageal cancer in its early stages has been underscored. Studies have consistently demonstrated the crucial role of methylation levels in circulating cell-free DNA (cfDNA) in identifying and diagnosing early-stage cancer. cfDNA methylation pertains to the methylation state within the genomic scope of cfDNA and is strongly associated with cancer development and progression. Several research teams have delved into the potential application of cfDNA methylation in identifying early-stage esophageal cancer and have achieved promising outcomes. Recent research supports the high sensitivity and specificity of cfDNA methylation in early esophageal cancer diagnosis, providing a more accurate and efficient approach for early detection and improved clinical management. Accordingly, this review aims to present an overview of methylation-based cfDNA research with a focus on the latest developments in the early detection of esophageal cancer. Additionally, this review summarizes advanced analytical technologies for cfDNA methylation that have significantly benefited from recent advancements in separation and detection techniques, such as methylated DNA immunoprecipitation sequencing (MeDIP-seq). Recent findings suggest that biomarkers based on cfDNA methylation may soon find successful applications in the early detection of esophageal cancer. However, large-scale prospective clinical trials are required to identify the potential of these biomarkers.

A comparative study on ctDNA and tumor DNA mutations in lung cancer and benign cases with a high number of CTCs and CTECs

BACKGROUND

Liquid biopsy provides a non-invasive approach that enables detecting circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) using blood specimens and theoretically benefits early finding primary tumor or monitoring treatment response as well as tumor recurrence. Despite many studies on these novel biomarkers, their clinical relevance remains controversial. This study aims to investigate the correlation between ctDNA, CTCs, and circulating tumor-derived endothelial cells (CTECs)  while also evaluating whether mutation profiling in ctDNA is consistent with that in tumor tissue from lung cancer patients. These findings will help the evaluation and utilization of these approaches in clinical practice.

METHODS

104 participants (49 with lung cancer and 31 with benign lesions) underwent CTCs and CTECs detection using integrating subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH) strategy. The circulating cell-free DNA (cfDNA) concentration was measured and the mutational profiles of ctDNA were examined by Roche AVENIO ctDNA Expanded Kit (targeted total of 77 genes) by next generation sequencing (NGS) in 28 patients (20 with lung cancer and 8 with benign lesions) with highest numbers of CTCs and CTECs. Mutation validation in matched tumor tissue DNA was then performed in 9 patients with ctDNA mutations using a customized xGen pan-solid tumor kit (targeted total of 474 genes) by NGS.

RESULTS

The sensitivity and specificity of total number of CTCs and CTECs for the diagnosis of NSCLC were 67.3% and 77.6% [AUC (95%CI): 0.815 (0.722-0.907)], 83.9% and 77.4% [AUC (95%CI): 0.739 (0.618-0.860)]. The concentration of cfDNA in plasma was statistically correlated with the size of the primary tumor (r = 0.430, P = 0.022) and CYFRA 21-1 (r = 0.411, P = 0.041), but not with the numbers of CTCs and CTECs. In this study, mutations were found to be poorly consistent between ctDNA and tumor DNA (tDNA) in patients, even when numerous CTCs and CTECs were present.

CONCLUSION

Detection of CTCs and CTECs could be the potential adjunct tool for the early finding of lung cancer. The cfDNA levels are associated with the tumor burden, rather than the CTCs or CTECs counts. Moreover, the poorly consistent mutations between ctDNA and tDNA require further exploration.

Liquid Biopsy as an Adjunct to Lung Screening Imaging

Current lung cancer screening protocols use low-dose computed tomography scans in selected high-risk individuals. Unfortunately, utilization is low, and the rate of false-positive screens is high. Peripheral biomarkers carry meaningful promise in diagnosing and monitoring cancer with added potential advantages reducing invasive procedures and improving turnaround time. Herein, the use of such blood-based assays is considered as an adjunct to further utilization and accuracy of lung cancer screening.

Exploring the Potential of Non-Coding RNAs as Liquid Biopsy Biomarkers for Lung Cancer Screening: A Literature Review

Lung cancer represent the leading cause of cancer mortality, so several efforts have been focused on the development of a screening program. To address the issue of high overdiagnosis and false positive rates associated to LDCT-based screening, there is a need for new diagnostic biomarkers, with liquid biopsy ncRNAs detection emerging as a promising approach. In this scenario, this work provides an updated summary of the literature evidence about the role of non-coding RNAs in lung cancer screening. A literature search on PubMed was performed including studies which investigated liquid biopsy non-coding RNAs biomarker lung cancer patients and a control cohort. Micro RNAs were the most widely studied biomarkers in this setting but some preliminary evidence was found also for other non-coding RNAs, suggesting that a multi-biomarker based liquid biopsy approach could enhance their efficacy in the screening context. However, further studies are needed in order to optimize detection techniques as well as diagnostic accuracy before introducing novel biomarkers in the early diagnosis setting.

Immunomagnetic Isolation of HER2-Positive Breast Cancer Cells Using a Microfluidic Device

Analysis of circulating tumor cells (CTCs) as a tool for monitoring metastatic cancers, early diagnosis, and evaluation of disease prognosis paves the way toward personalized cancer treatment. Developing an effective, feasible, and low-cost method to facilitate CTC isolation is, therefore, vital. In the present study, we integrated magnetic nanoparticles (MNPs) with microfluidics and used them for the isolation of HER2-positive breast cancer cells. Iron oxide MNPs were synthesized and functionalized with the anti-HER2 antibody. The chemical conjugation was verified by Fourier transform infrared spectroscopy, energy-dispersive X-ray spectroscopy, and dynamic light scattering/zeta potential analysis. The specificity of the functionalized NPs for the separation of HER2-positive from HER2-negative cells was demonstrated in an off-chip test setting. The off-chip isolation efficiency was 59.38%. The efficiency of SK-BR-3 cell isolation using a microfluidic chip with a S-shaped microchannel was considerably enhanced to 96% (a flow rate of 0.5 mL/h) without chip clogging. Besides, the analysis time for the on-chip cell separation was 50% faster. The clear advantages of the present microfluidic system offer a competitive solution in clinical applications.

The presence of circulating genetically abnormal cells in blood predicts risk of lung cancer in individuals with indeterminate pulmonary nodules

PURPOSE

Computed tomography is the standard method by which pulmonary nodules are detected. Greater than 40% of pulmonary biopsies are not lung cancer and therefore not necessary, suggesting that improved diagnostic tools are needed. The LungLB™ blood test was developed to aid the clinical assessment of indeterminate nodules suspicious for lung cancer. LungLB™ identifies circulating genetically abnormal cells (CGACs) that are present early in lung cancer pathogenesis.

METHODS

LungLB™ is a 4-color fluorescence in-situ hybridization assay for detecting CGACs from peripheral blood. A prospective correlational study was performed on 151 participants scheduled for a pulmonary nodule biopsy. Mann-Whitney, Fisher's Exact and Chi-Square tests were used to assess participant demographics and correlation of LungLB™ with biopsy results, and sensitivity and specificity were also evaluated.

RESULTS

Participants from Mount Sinai Hospital (n = 83) and MD Anderson (n = 68), scheduled for a pulmonary biopsy were enrolled to have a LungLB™ test. Additional clinical variables including smoking history, previous cancer, lesion size, and nodule appearance were also collected. LungLB™ achieved 77% sensitivity and 72% specificity with an AUC of 0.78 for predicting lung cancer in the associated needle biopsy. Multivariate analysis found that clinical and radiological factors commonly used in malignancy prediction models did not impact the test performance. High test performance was observed across all participant characteristics, including clinical categories where other tests perform poorly (Mayo Clinic Model, AUC = 0.52).

CONCLUSION

Early clinical performance of the LungLB™ test supports a role in the discrimination of benign from malignant pulmonary nodules. Extended studies are underway.

Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis

Liquid biopsies have emerged as a promising tool for the detection of metastases as well as local and regional recurrence in lung cancer. Liquid biopsy tests involve analyzing a patient's blood, urine, or other body fluids for the detection of biomarkers, including circulating tumor cells or tumor-derived DNA/RNA that have been shed into the bloodstream. Studies have shown that liquid biopsies can detect lung cancer metastases with high accuracy and sensitivity, even before they are visible on imaging scans. Such tests are valuable for early intervention and personalized treatment, aiming to improve patient outcomes. Liquid biopsies are also minimally invasive compared to traditional tissue biopsies, which require the removal of a sample of the tumor for further analysis. This makes liquid biopsies a more convenient and less risky option for patients, particularly those who are not good candidates for invasive procedures due to other medical conditions. While liquid biopsies for lung cancer metastases and relapse are still being developed and validated, they hold great promise for improving the detection and treatment of this deadly disease. Herein, we summarize available and novel approaches to liquid biopsy tests for lung cancer metastases and recurrence detection and describe their applications in clinical practice.

Diagnostic value of liquid biopsy in the era of precision medicine: 10 years of clinical evidence in cancer

Liquid biopsy is a diagnostic repeatable test, which in last years has emerged as a powerful tool for profiling cancer genomes in real-time with minimal invasiveness and tailoring oncological decision-making. It analyzes different blood-circulating biomarkers and circulating tumor DNA (ctDNA) is the preferred one. Nevertheless, tissue biopsy remains the gold standard for molecular evaluation of solid tumors whereas liquid biopsy is a complementary tool in many different clinical settings, such as treatment selection, monitoring treatment response, cancer clonal evolution, prognostic evaluation, as well as the detection of early disease and minimal residual disease (MRD). A wide number of technologies have been developed with the aim of increasing their sensitivity and specificity with acceptable costs. Moreover, several preclinical and clinical studies have been conducted to better understand liquid biopsy clinical utility. Anyway, several issues are still a limitation of its use such as false positive and negative results, results interpretation, and standardization of the panel tests. Although there has been rapid development of the research in these fields and recent advances in the clinical setting, many clinical trials and studies are still needed to make liquid biopsy an instrument of clinical routine. This review provides an overview of the current and future clinical applications and opening questions of liquid biopsy in different oncological settings, with particular attention to ctDNA liquid biopsy.

Radiomics in Lung Metastases: A Systematic Review

Due to the rich vascularization and lymphatic drainage of the pulmonary tissue, lung metastases (LM) are not uncommon in patients with cancer. Radiomics is an active research field aimed at the extraction of quantitative data from diagnostic images, which can serve as useful imaging biomarkers for a more effective, personalized patient care. Our purpose is to illustrate the current applications, strengths and weaknesses of radiomics for lesion characterization, treatment planning and prognostic assessment in patients with LM, based on a systematic review of the literature.

Tubulin Alpha-1b as a Potential Biomarker for Lung Adenocarcinoma Diagnosis and Prognosis

Background: Because lung cancer is the main cause of cancer deaths and lung adenocarcinoma (LUAD) accounts for more than 40% of all lung malignancies, it is essential to develop clinically useful biomarkers for the disease. The aim of this investigation is to assess the potential application of tubulin alpha-1b (TUBA1B) as a biomarker for diagnosing and monitoring the outcome of LUAD. Methods: The clinical data of the LUAD patients was retrospectively analyzed. Immunohistochemistry (IHC) analysis of a tissue microarray containing 90 LUAD cases was implemented to examine the expression of TUBA1B. The protein and mRNA levels of TUBA1B in serum were detected by enzyme-linked immunosorbent assay (ELISA) and quantitative real-time PCR (qRT-PCR) analysis respectively. UALCAN was employed to confirm the expression levels and survival probability of TUBA1B in LUAD patients. Results: Compared to adjacent non-cancerous tissues in the microarray, the expression of TUBA1B in LUAD tissues was much higher. The expression of TUBA1B in LUAD was statistically correlated with lymph node status (P = .031). Moreover, patients with higher TUBA1B expression had shorter overall survival (P < .0001). Furthermore, cox multi-factor analysis also suggested that TUBA1B may be an independent predictor for LUAD prognosis (P = .030). The results of TCGA data analysis by UALCAN were consistent with the microarray results, except for that TUBA1B was also significantly correlated with clinical tumor stages. Protein levels of TUBA1B in serum were obviously elevated in LUAD patients than control (P < .0001), and the area under the ROC curve was 0.99. TUBA1B also showed better sensitivity of 92.9% for LUAD than common clinical biomarkers. Conclusion: TUBA1B may be a non-invasive prognostic and diagnostic biomarker for LUAD patients.

Cushing's Syndrome in Adenocarcinoma of Lung Responding to Osilodrostat

Cushing's syndrome (CS), secondary to paraneoplastic syndrome, is more commonly seen in small cell lung cancer but never before reported in epidermal growth factor receptor-mutated adenocarcinoma of the lung. Here, we present a case of a patient whose symptoms of hypokalemia, hypertension, and progressive abnormal glucose levels led to further workup that revealed adrenocorticotropic hormone-dependent hypercortisolism. Her cortisol levels dropped after 1 month of osilodrostat treatment, while lung cancer was treated with osimertinib. The use of osilodrostat in paraneoplastic CS has been previously reported in only 3 patients.

Application of tumor-educated platelets as new fluid biopsy markers in various tumors

The incidence of malignant tumors is increasing year by year. Early detection and diagnosis of malignant tumors can improve the prognosis of patients and prolong their life. Pathological biopsy is the current gold standard for diagnosis, but the results of pathological biopsy are affected by the sampling site and cannot fully reflect the nature of the disease. Moreover, the invasive nature of pathological biopsy limits repeated detection. Liquid biopsies are non-invasive and can be used for early detection and monitoring of tumors, which considered to represent a promising tool. Platelets make themselves to be one of the richest liquid biopsy sources by the capacity to take up proteins and nucleic acids and alter their megakaryocyte-derived transcripts and proteins in response to external signals, which are called tumor-educated platelets (TEPs). In this article, we will review the application of tumor-educated platelets in various malignancies (nasopharyngeal carcinoma, prostate cancer, lung cancer, glioblastoma, colorectal cancer, pancreas cancer, ovarian cancer, sarcoma, breast cancer and hepatocellular carcinoma) and provide theoretical basis for the research of TEPs in tumor diagnosis, monitoring and treatment.

Overexpression of BCL2, BCL6, VEGFR1 and TWIST1 in Circulating Tumor Cells Derived from Patients with DLBCL Decreases Event-Free Survival

Purpose

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignant lymphoid neoplasm and is the most common subtype of non-Hodgkin lymphoma in adults. More than half of patients with DLBCL can achieve remission with standard R-CHOP regimes; however, approximately 30-40% of patients are still failing this standard therapy, which remains as an important cause of progression and mortality of this disease. It is necessary to have diagnostic and monitoring tools that allow us to improve the accuracy of prognosis in these patients. Circulating tumor cells (CTCs) identification through molecular biomarkers is one of the novel strategies that have been used in other types of cancer, and we aim to use this tool to analyze the potential role in DLBCL.

Patients and Methods

We analyzed 138 blood samples of patients with DLBCL, of which CTCs were isolated by density gradient for subsequent detection and quantitation of molecular biomarkers using RT-qPCR with TaqMan probes. Survival analysis was performed using Kaplan-Meier curves.

Results

We found overexpression of ABCB1, αSMA, BCL2, BCL6 and VEGFR1 genes, as well as the presence of CK19, EpCAM, KI67, MAGE-A4, SNAIL and TWIST1 genes. CK19 and EpCAM expression were associated with a minor OS (85.7% vs 98.1%, p = 0.002). The overexpression of BCL2, BCL6, VEGFR1 and TWIST1 was related to a minor EFS (p = 0.001).

Conclusion

This study showed that in liquid biopsies analyzed, the presence of CTCs can be confirmed through molecular biomarkers, and it has an impact on OS and EFs, making this detection useful in the follow-up and prognosis of patients with DLBCL.

The Convergence of FTIR and EVs: Emergence Strategy for Non-Invasive Cancer Markers Discovery

In conjunction with imaging analysis, pathology-based assessments of biopsied tissue are the gold standard for diagnosing solid tumors. However, the disadvantages of tissue biopsies, such as being invasive, time-consuming, and labor-intensive, have urged the development of an alternate method, liquid biopsy, that involves sampling and clinical assessment of various bodily fluids for cancer diagnosis. Meanwhile, extracellular vesicles (EVs) are circulating biomarkers that carry molecular profiles of their cell or tissue origins and have emerged as one of the most promising biomarkers for cancer. Owing to the biological information that can be obtained through EVs' membrane surface markers and their cargo loaded with biomolecules such as nucleic acids, proteins, and lipids, EVs have become useful in cancer diagnosis and therapeutic applications. Fourier-transform infrared spectroscopy (FTIR) allows rapid, non-destructive, label-free molecular profiling of EVs with minimal sample preparation. Since the heterogeneity of EV subpopulations may result in complicated FTIR spectra that are highly diverse, computational-assisted FTIR spectroscopy is employed in many studies to provide fingerprint spectra of malignant and non-malignant samples, allowing classification with high accuracy, specificity, and sensitivity. In view of this, FTIR-EV approach carries a great potential in cancer detection. The progression of FTIR-based biomarker identification in EV research, the rationale of the integration of a computationally assisted approach, along with the challenges of clinical translation are the focus of this review.

Construction and Validation of Early Warning Model of Lung Cancer Based on Machine Learning: A Retrospective Study

Background: This study is a retrospective study. The purpose of this study is to construct and validate an early warning model of lung cancer through machine learning. Methods: The CDKN2A gene expression profile and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database and divided into a tumor group and a normal group (n = 57). The top 5 somatic mutation-related genes were extracted from 567 somatic mutation data downloaded from TCGA database using random forest algorithm. Cox proportional hazard model and nomogram were constructed combining CDKN2A, 5 somatic mutation-related genes, gender, and smoking index. Patients were divided into high-risk and low-risk groups according to risk score. The predictability of the model in the prognosis of lung cancer was estimated by Kaplan-Meier survival analysis and receiver operating characteristics curve. Results: We constructed a prognostic model consisting of 5 somatic mutation-related genes (sphingosine 1-phosphate receptor 1 [S1PR1], dedicator of cytokinesis 7 [DOCK7], DEAD-box helicase 4 [DDX4], laminin subunit beta 3 [LAMB3], and importin 5 [IPO5]), cyclin-dependent kinase inhibitor 2A (CDKN2A), gender, and smoking indicators. The high-risk group had a lower overall survival rate compared to the low-risk group (hazard ratio = 2.14, P = 0 .0323). The area under the curve predicted for 3-year, 5-year, and 10-year survival rates are 0.609, 0.673, and 0.698, respectively. The accuracy, sensitivity, and specificity of the model for predicting the 10-year survival rate of lung cancer are 76.19%, 56.71%, and 86.23%. Conclusion: The lung cancer early warning model and nomogram may provide an essential reference for patients with lung cancer management in the clinic.

The evolving role of liquid biopsy in lung cancer

Liquid biopsy has revolutionized the management of cancer patients. In particular, liquid biopsy-based testing has proven to be highly beneficial for identifying actionable cancer markers, especially when solid tissue biopsies are insufficient or unattainable. Beyond the predictive role, liquid biopsy may be a useful tool for comprehensive tumor genotyping, identification of emergent resistance mechanisms, monitoring of minimal residual disease, early detection, and cancer interception. The application of next generation sequencing to liquid biopsy has led to the "quantum leap" of predictive molecular pathology. Here, we review the evolving role of liquid biopsy in lung cancer.

Noncoding RNome as Enabling Biomarkers for Precision Health

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

Molecular Targets in Lung Cancer: Study of the Evolution of Biomarkers Associated with Treatment with Tyrosine Kinase Inhibitors—Has NF1 Tumor Suppressor a Key Role in Acquired Resistance?

Simple Summary

Resistance to tyrosine kinase inhibitors in patients with EGFR-mutated non-small cell lung cancer is crucial in the development of the disease. Detecting the mechanisms of this resistance is fundamental in lung cancer research, so we evaluated the presence of EGFR mutations in circulating free DNA in plasma of patients with NSCLC under oncological treatment. We studied the role of EGFR and other driver mutations in their involvement in acquired resistance to treatment with EGFR-TKIs and we analyzed the role of liquid biopsy as a non-invasive diagnostic method. Our results showed that liquid biopsy is a very useful tool monitoring the evolution of the disease and the resistance to TKIs. The detection of other concomitant mutations in driver genes is also key in this regard, so we found that alterations in the NFI tumor suppressor gene could be playing a role in disease progression and resistance to targeted therapies.

Abstract

The application to clinical practice of liquid biopsy in patients with lung cancer has led to an advance in the diagnosis and monitoring of the disease. Detection of alterations in EGFR genes related to TKI treatment in EGFR-mutated non-small cell lung cancer patients is a routine method in pathology laboratories. The primary objective of this work was to analyze the presence of EGFR mutations in cfDNA of 86 patients with lung cancer undergoing oncological treatment related to response to treatment with TKIs. Secondarily, we evaluated the dynamics of EGFR mutations, the presence of the T790M alteration and its relationship with drug resistance and analyzed by NGS molecular alterations in cfDNA of patients with discordant progression. Our results demonstrate that understanding the mutational status of patients treated with TKIs over time is essential to monitor disease progression. In this context, liquid biopsy is a fundamental key. In addition, it is not only necessary to detect EGFR mutations, but also other concomitant mutations that would be influencing the development of the disease. In this sense, we have discovered that mutations in the NF1 tumor suppressor gene could be exerting an as yet unknown function in lung cancer.

On the way for the best imaging features from CT images to predict EGFR Mutation Status in Lung Cancer

Artificial Intelligence-based tools have shown promising results to help clinicians in diagnosis tasks. Radio-genomics would aid in the genotype characterization using information from radiologic images. The prediction of the mutations status of main oncogenes associated with lung cancer will help the clinicians to have a more accurate diagnosis and a personalized treatment plan, decreasing the need to use the biopsy. In this work, novel and objective features were extracted from the lung that contained the nodule, and several machine learning methods were combined with feature selection techniques to select the best approach to predict the EGFR mutation status in lung cancer CT images. An AUC of 0.756 ± 0.055 was obtained using a logistic regression and independent component analysis as feature selector, supporting the hypothesis that CT images can capture pathophysiological information with great value for clinical assessment and personalized medicine of lung cancer. Clinical Relevance - Radiogenomic approaches could be an interesting help for lung cancer characterization. This work represents a preliminary study for the development of computer-aided decision systems to provide a more accurate and fast characterization of lung cancer which is fundamental for an adequate treatment plan for lung cancer patients.

Liquid First Is "Solid" in Naïve Non-Small Cell Lung Cancer Patients: Faster Turnaround Time With High Concordance to Solid Next-Generation Sequencing

Purpose

Molecular profiling is crucial in naïve non-small cell lung cancer (NSCLC). While tissue-based analysis is challenged by turnaround time and scarcity of tissue, there is increasing demand for liquid biopsy. We aimed to analyze the use of upfront liquid biopsy as a molecular profiling approach.

Methods

This retrospective multicenter, non-interventional study compared findings and turnaround times of liquid vs. standard-of-care (SOC) tissue-biopsy molecular profiling. The study included naïve advanced NSCLC patients with available liquid biopsy (Guardant360 CDx).

Results

A total of 42 consecutive patients (60% men; median age, 69.5 [39-87] years; 86% stage IV NSCLC) were identified between September 2017 and December 2020. Liquid-biopsy analysis provided results for all 42 patients, whereas the tissue-based analysis failed in 5 (12%) patients due to insufficient tumor samples. In 17 patients, 18 actionable driver mutations were identified. Eleven mutations were detected by both approaches (i.e., concordance of 61%), 4 only by liquid biopsy and 3 only by tissue biopsy. The median time from the molecular request to receiving the molecular solid report on the last biomarker was 21 (range: 5-66) days, whereas the median time from blood draw to the liquid-biopsy results was 10.5 (7-19) days. The median time between the availability of liquid-biopsy findings and that of the last biomarker was 5 days. Treatment changes following the liquid-biopsy results were observed in 3 (7%) patients.

Conclusion

Performing liquid-biopsy upfront is feasible and accurate and allows a shorter time for treatment in NSCLC, especially when tumor tissue is scarce.

Precision Oncology: Artificial Intelligence and DNA Methylation Analysis of Circulating Cell-Free DNA for Lung Cancer Detection

Background

Lung cancer (LC) is a leading cause of cancer-deaths globally. Its lethality is due in large part to the paucity of accurate screening markers. Precision Medicine includes the use of omics technology and novel analytic approaches for biomarker development. We combined Artificial Intelligence (AI) and DNA methylation analysis of circulating cell-free tumor DNA (ctDNA), to identify putative biomarkers for and to elucidate the pathogenesis of LC.

Methods

Illumina Infinium MethylationEPIC BeadChip array analysis was used to measure cytosine (CpG) methylation changes across the genome in LC. Six different AI platforms including support vector machine (SVM) and Deep Learning (DL) were used to identify CpG biomarkers and for LC detection. Training set and validation sets were generated, and 10-fold cross validation performed. Gene enrichment analysis using g:profiler and GREAT enrichment was used to elucidate the LC pathogenesis.

Results

Using a stringent GWAS significance threshold, p-value <5x10^-8, we identified 4389 CpGs (cytosine methylation loci) in coding genes and 1812 CpGs in non-protein coding DNA regions that were differentially methylated in LC. SVM and three other AI platforms achieved an AUC=1.00; 95% CI (0.90-1.00) for LC detection. DL achieved an AUC=1.00; 95% CI (0.95-1.00) and 100% sensitivity and specificity. High diagnostic accuracies were achieved with only intragenic or only intergenic CpG loci. Gene enrichment analysis found dysregulation of molecular pathways involved in the development of small cell and non-small cell LC.

Conclusion

Using AI and DNA methylation analysis of ctDNA, high LC detection rates were achieved. Further, many of the genes that were epigenetically altered are known to be involved in the biology of neoplasms in general and lung cancer in particular.

In vitro cultures of circulating tumor cells: a potential tool to unravel drug sensitivity

Since taking part as leading actors in driving the metastatic process, circulating tumor cells (CTCs) have displayed a wide range of potential applications in the cancer-related research field. Besides their well-proved prognostic value, the role of CTCs in both predictive and diagnostics terms might be extremely informative about cancer properties and therefore highly helpful in the clinical decision-making process. Unfortunately, CTCs are scarcely released in the blood circulation and their counts vary a lot among different types of cancer, therefore CTC detection and consequent characterization are still highly challenging. In this context, in vitro CTC cultures could potentially offer a great opportunity to expand the number of tumor cells isolated at different stages of the disease and thus simplify the analysis of their biological and molecular features, allowing a deeper comprehension of the nature of neoplastic diseases. The aim of this review is to highlight the main attempts to establish in vitro CTC cultures from patients harboring different tumor types in order to highlight how powerful this practice could be, especially in optimizing the therapeutic strategies available in clinical practice and potentially preventing or contrasting the development of treatment resistance.

Liquid biopsies to occult brain metastasis

Brain metastasis (BrM) is a major problem associated with cancer-related mortality, and currently, no specific biomarkers are available in clinical settings for early detection. Liquid biopsy is widely accepted as a non-invasive method for diagnosing cancer and other diseases. We have reviewed the evidence that shows how the molecular alterations are involved in BrM, majorly from breast cancer (BC), lung cancer (LC), and melanoma, with an inception in how they can be employed for biomarker development. We discussed genetic and epigenetic changes that influence cancer cells to breach the blood-brain barrier (BBB) and help to establish metastatic lesions in the uniquely distinct brain microenvironment. Keeping abreast with the recent breakthroughs in the context of various biomolecules detections and identifications, the circulating tumor cells (CTC), cell-free nucleotides, non-coding RNAs, secretory proteins, and metabolites can be pursued in human body fluids such as blood, serum, cerebrospinal fluid (CSF), and urine to obtain potential candidates for biomarker development. The liquid biopsy-based biomarkers can overlay with current imaging techniques to amplify the signal viable for improving the early detection and treatments of occult BrM.

Application of an Ultrasensitive NGS-Based Blood Test for the Diagnosis of Early-Stage Lung Cancer: Sensitivity, a Hurdle Still Difficult to Overcome

Simple Summary

Currently, an accurate diagnosis of lung cancer relies on the microscopic examination of tissue biopsies. These samples can, however, only be obtained by invasive procedures. The aim of our study was to evaluate the use of a liquid biopsy for early-stage lung cancer detection in patients with a lung lesion on imaging. This approach would be particularly relevant for suspected lung lesions that are difficult to reach for a tissue-based diagnosis. Despite technical improvements for the use of liquid biopsy-based cell-free DNA analysis, its application for the detection of early-stage lung cancer is currently limited by sensitivity and a biological background of somatic variants.

Abstract

Diagnosis of lung cancer requires histological examination of a tissue sample, which in turn requires an invasive procedure that cannot always be obtained. Circulating tumor DNA can be reliably detected in blood samples of advanced-stage lung cancer patients and might also be a minimally invasive alternative for early-stage lung cancer detection. We wanted to explore the potential of targeted deep sequencing as a test for the diagnosis of early-stage lung cancer in combination with imaging. Mutation detection on cell-free DNA from pretreatment plasma samples of 51 patients with operable non-small cell lung cancer was performed and results were compared with 12 control patients undergoing surgery for a non-malignant lung lesion. By using a variant allele frequency threshold of 1%, somatic variants were detected in 23.5% of patients with a median variant allele fraction of 3.65%. By using this threshold, we could almost perfectly discriminate early-stage lung cancer patients from controls. Our study results are discussed in the light of those from other studies. Notwithstanding the potential of today’s techniques for the use of liquid biopsy-based cell-free DNA analysis, sensitivity of this application for early-stage lung cancer detection is currently limited by a biological background of somatic variants with low variant allele fraction.

Clinical Applications of Circulating Tumour Cells and Circulating Tumour DNA in Non-Small Cell Lung Cancer-An Update

Despite efforts to improve earlier diagnosis of non-small cell lung cancer (NSCLC), most patients present with advanced stage disease, which is often associated with poor survival outcomes with only 15% surviving for 5 years from their diagnosis. Tumour tissue biopsy is the current mainstream for cancer diagnosis and prognosis in many parts of the world. However, due to tumour heterogeneity and accessibility issues, liquid biopsy is emerging as a game changer for both cancer diagnosis and prognosis. Liquid biopsy is the analysis of tumour-derived biomarkers in body fluids, which has remarkable advantages over the use of traditional tumour biopsy. Circulating tumour cells (CTCs) and circulating tumour DNA (ctDNA) are two main derivatives of liquid biopsy. CTC enumeration and molecular analysis enable monitoring of cancer progression, recurrence, and treatment response earlier than traditional biopsy through a minimally invasive liquid biopsy approach. CTC-derived ex-vivo cultures are essential to understanding CTC biology and their role in metastasis, provide a means for personalized drug testing, and guide treatment selection. Just like CTCs, ctDNA provides opportunity for screening, monitoring, treatment evaluation, and disease surveillance. We present an updated review highlighting the prognostic and therapeutic significance of CTCs and ctDNA in NSCLC.

Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges

Advancements in the development of computer-aided decision (CAD) systems for clinical routines provide unquestionable benefits in connecting human medical expertise with machine intelligence, to achieve better quality healthcare. Considering the large number of incidences and mortality numbers associated with lung cancer, there is a need for the most accurate clinical procedures; thus, the possibility of using artificial intelligence (AI) tools for decision support is becoming a closer reality. At any stage of the lung cancer clinical pathway, specific obstacles are identified and “motivate” the application of innovative AI solutions. This work provides a comprehensive review of the most recent research dedicated toward the development of CAD tools using computed tomography images for lung cancer-related tasks. We discuss the major challenges and provide critical perspectives on future directions. Although we focus on lung cancer in this review, we also provide a more clear definition of the path used to integrate AI in healthcare, emphasizing fundamental research points that are crucial for overcoming current barriers.

Liquid biopsy: the value of different bodily fluids

Liquid biopsies have gained an increasing interest in the last years among medical and scientific communities. Indeed, the value of liquid effusions, while less invasive and more accurate techniques, has been markedly highlighted. Peripheral blood comprises the most often analyzed sample, but recent evidences have pointed out the huge importance of other bodily fluids, including pleural and peritoneal fluids, urine, saliva and cerebrospinal fluid in the detection and monitoring of different tumor types. In face to these advances, this review aims to provide an overview of the value of tumor-associated mutations, detectable in different effusions, and how they can be used in clinical practice, namely in prognosis assessment and early disease and minimal disease recurrence detection, and in predicting the treatment response or acquired-resistance development.

The Role of Circulating Biomarkers in Lung Cancer

Lung cancer is the leading cause of cancer morbidity and mortality worldwide and early diagnosis is crucial for the management and treatment of this disease. Non-invasive means of determining tumour information is an appealing diagnostic approach for lung cancers as often accessing and removing tumour tissue can be a limiting factor. In recent years, liquid biopsies have been developed to explore potential circulating tumour biomarkers which are considered reliable surrogates for understanding tumour biology in a non-invasive manner. Most common components assessed in liquid biopsy include circulating tumour cells (CTCs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), microRNA and exosomes. This review explores the clinical use of circulating tumour biomarkers found in liquid biopsy for screening, early diagnosis and prognostication of lung cancer patients.

Metabolomic Fingerprinting for the Detection of Early-Stage Lung Cancer: From the Genome to the Metabolome

The five-year survival rate of lung cancer patients is very low, mainly because most newly diagnosed patients present with locally advanced or metastatic disease. Therefore, early diagnosis is key to the successful treatment and management of lung cancer. Unfortunately, early detection methods of lung cancer are not ideal. In this brief review, we described early detection methods such as chest X-rays followed by bronchoscopy, sputum analysis followed by cytological analysis, and low-dose computed tomography (LDCT). In addition, we discussed the potential of metabolomic fingerprinting, compared to that of other biomarkers, including molecular targets, as a low-cost, high-throughput blood-based test that is both feasible and affordable for early-stage lung cancer screening of at-risk populations. Accordingly, we proposed a paradigm shift to metabolomics as an alternative to molecular and proteomic-based markers in lung cancer screening, which will enable blood-based routine testing and be accessible to those patients at the highest risk for lung cancer.

Recent advances in fecal gene detection for colorectal cancer diagnosis

There has been a gradual increase in the incidence of colorectal cancer (CRC) in recent years. Most patients lack obvious early symptoms, but are commonly in mid and advanced stages when the symptoms become evident, with rather high mortalities. Early diagnosis, treatment and recurrence monitoring are crucial to improving the recovery rate of CRC. Studies have shown that tumor-related genes can be detected in the feces of CRC patients. Owing to non-invasiveness, convenient sampling and continuous dynamic monitoring, fecal gene detection may be applicable to CRC screening, diagnosis, prognostic assessment and recurrence monitoring. Herein, we review the research advances in fecal gene detection for CRC diagnosis.

Exosomes in Lung Cancer: Actors and Heralds of Tumor Development

Lung cancer is a leading cause of cancer-related death worldwide and in most cases, diagnosis is reached when the tumor has already spread and prognosis is quite poor. For that reason, the research for new biomarkers that could improve early diagnosis and its management is essential. Exosomes are microvesicles actively secreted by cells, especially by tumor cells, hauling molecules that mimic molecules of the producing cells. There are multiple methods for exosome isolation and analysis, although not standardized, and cancer exosomes from biological fluids are especially difficult to study. Exosomes' cargo proteins, RNA, and DNA participate in the communication between cells, favoring lung cancer development by delivering signals for growth, metastasis, epithelial mesenchymal transition, angiogenesis, immunosuppression and even drug resistance. Exosome analysis can be useful as a type of liquid biopsy in the diagnosis, prognosis and follow-up of lung cancer. In this review, we will discuss recent advances in the role of exosomes in lung cancer and their utility as liquid biopsy, with special attention to isolating methods.

Association of Exosomal miR-210 with Signaling Pathways Implicated in Lung Cancer

MicroRNA is a class of non-coding RNA involved in post-transcriptional gene regulation. Aberrant expression of miRNAs is well-documented in molecular cancer biology. Extensive research has shown that miR-210 is implicated in the progression of multiple cancers including that of the lung, bladder, colon, and renal cell carcinoma. In recent years, exosomes have been evidenced to facilitate cell–cell communication and signaling through packaging and transporting active biomolecules such as miRNAs and thereby modify the cellular microenvironment favorable for lung cancers. MiRNAs encapsulated inside the lipid bilayer of exosomes are stabilized and transmitted to target cells to exert alterations in the epigenetic landscape. The currently available literature indicates that exosomal miR-210 is involved in the regulation of various lung cancer-related signaling molecules and pathways, including STAT3, TIMP-1, KRAS/BACH2/GATA-3/RIP3, and PI3K/AKT. Here, we highlight major findings and progress on the roles of exosomal miR-210 in lung cancer.

The Evolving Concept of Complete Resection in Lung Cancer Surgery

Simple Summary

In the surgical treatment of lung cancer, the complete removal of the portion of the lung where the cancer is and of the involved adjacent structures is of paramount importance to achieve long-term survival. The International Association for the Study of Lung Cancer (IASLC) proposed a definition of complete resection that included a well-defined type of removal of the regional lymph nodes as a fundamental step. The lymph nodes may contain cancer cells and, if left behind, cancer will soon progress. The IASLC also defined incomplete resection when there is any evidence of persistent cancer after the operation. It also defined an intermediate condition, uncertain resection, when no evidence of residual disease can be proved, but all the conditions of complete resection are not fulfilled. Four validations of the definitions have proved their prognostic value and, therefore, the definitions should be followed when a surgical resection of lung cancer is planned.

Abstract

Different definitions of complete resection were formulated to complement the residual tumor (R) descriptor proposed by the American Joint Committee on Cancer in 1977. The definitions went beyond resection margins to include the status of the visceral pleura, the most distant nodes and the nodal capsule and the performance of a complete mediastinal lymphadenectomy. In 2005, the International Association for the Study of Lung Cancer (IASLC) proposed definitions for complete, incomplete and uncertain resections for international implementation. Central to the IASLC definition of complete resection is an adequate nodal evaluation either by systematic nodal dissection or lobe-specific systematic nodal dissection, as well as the integrity of the highest mediastinal node, the nodal capsule and the resection margins. When there is evidence of cancer remaining after treatment, the resection is incomplete, and when all margins are free of tumor, but the conditions for complete resection are not fulfilled, the resection is defined as uncertain. The prognostic relevance of the definitions has been validated by four studies. The definitions can be improved in the future by considering the cells spread through air spaces, the residual tumor cells, DNA or RNA in the blood, and the determination of the adequate margins and lymphadenectomy in sublobar resections.