Circulating tumour cells as a potential biomarker for lung cancer screening: a prospective cohort study

Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study

Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to predict epidermal growth factor receptor (EGFR) mutation status in patients with stage I non-small cell lung cancer (NSCLC). We retrospectively included 438 patients who underwent curative surgery and completed driver-gene mutation tests for stage I NSCLC from four academic medical centers. Predictive models were established by extracting and analyzing radiomic features in intratumoral, peritumoral, and habitat regions of CT images to identify EGFR mutation status in stage I NSCLC. Additionally, three deep learning models based on the intratumoral region were constructed. A nomogram was developed by integrating representative radiomic signatures, deep learning, and clinical features. Model performance was assessed by calculating the area under the receiver operating characteristic (ROC) curve. The established habitat radiomics features demonstrated encouraging performance in discriminating between EGFR mutant and wild-type, with predictive ability superior to other single models (AUC 0.886, 0.812, and 0.790 for the training, validation, and external test sets, respectively). The radiomics-based nomogram exhibited excellent performance, achieving the highest AUC values of 0.917, 0.837, and 0.809 in the training, validation, and external test sets, respectively. Decision curve analysis (DCA) indicated that the nomogram provided a higher net benefit than other radiomics models, offering valuable information for treatment.

Tumor marker-based RecistTM is superior to RECIST as criteria to predict the long-term benefits of targeted therapy in advanced non-small-cell lung cancer with driver gene mutations

BACKGROUND

Tyrosine kinase inhibitors (TKIs) are standard first-line treatments for advanced non-small-cell lung cancer (NSCLC) with driver gene mutations. The Response Evaluation Criteria in Solid Tumors (RECIST) are limited in predicting long-term patient benefits. A tumour marker-based evaluation criteria, RecistTM, was used to investigate the potential for assessing targeted-therapy efficacy in lung cancer treatment.

METHODS

We retrospectively analysed patients with stage IIIA-IV NSCLC and driver gene mutations, whose baseline tumour marker levels exceeded the pre-treatment cut-off value three-fold and who received TKI-targeted therapy as a first-line treatment. We compared efficacy, progression-free survival (PFS), and overall survival (OS) between RecistTM and RECIST.

FINDINGS

The median PFS and OS differed significantly among treatment-response subgroups based on RecistTM but not RECIST. The predicted 1-, 2-, and 3-year disease-progression risk, according to area under the receiver operating characteristic curve, as well as the 1-, 3-, and 5-year mortality risk, differed significantly between RecistTM and RECIST. The median PFS and OS of tmCR according to RecistTM, was significantly longer than (CR+PR) according to RECIST. Imaging analysis revealed that the ΔPFS was 11.27 and 6.17 months in the intervention and non-intervention groups, respectively, suggesting that earlier intervention could extend patients' PFS.

INTERPRETATION

RecistTM can assess targeted-therapy efficacy in patients with advanced NSCLC and driver gene mutations, along with tumour marker abnormalities. RecistTM surpasses RECIST in predicting short- and long-term patient benefits, and allows the early identification of patients resistant to targeted drugs, enabling prompt intervention and extending the imaging-demonstrated time to progression.

Value of circulating tumor cell assisting low-dose computed tomography in screening pulmonary nodules based on existing liquid biopsy techniques: a systematic review with meta-analysis and trial sequential analysis

OBJECTIVE

This study aims to assess the diagnostic utility of circulating tumor cells (CTCs) in conjunction with low-dose computed tomography (LDCT) for differentiating between benign and malignant pulmonary nodules and to substantiate the foundation for their integration into clinical practice.

METHODS

A systematic literature review was performed independently by two researchers utilizing databases including PubMed, Web of Science, The Cochrane Library, Embase, and Medline, to collate studies up to September 15, 2023, that investigated the application of CTCs in diagnosing pulmonary nodules. A meta-analysis was executed employing Stata 15.0 and Revman 5.4 to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curve (AUC). Additionally, trial sequential analysis was conducted using dedicated TSA software.

RESULTS

The selection criteria identified 16 studies, encompassing a total of 3409 patients. The meta-analysis revealed that CTCs achieved a pooled sensitivity of 0.84 (95% CI 0.80 to 0.87), specificity of 0.80 (95% CI 0.73 to 0.86), PLR of 4.23 (95% CI 3.12 to 5.72), NLR of 0.20 (95% CI 0.16 to 0.25), DOR of 20.92 (95% CI 13.52 to 32.36), and AUC of 0.89 (95% CI 0.86 to 0.93).

CONCLUSIONS

Circulating tumor cells demonstrate substantial diagnostic accuracy in distinguishing benign from malignant pulmonary nodules. The incorporation of CTCs into the diagnostic protocol can significantly augment the diagnostic efficacy of LDCT in screening for malignant lung diseases.

Circulating tumor cell detection may offer earlier diagnosis in patients suspected of asbestos-related lung cancer

Asbestos-Related Lung Cancer (ARLC) presents ongoing diagnostic challenges despite improved imaging technologies. The long latency period, coupled with limited access to occupational and environmental data along with the confounding effects of smoking and other carcinogens adds complexity to the diagnostic process. Compounding these challenges is the absence of a specific histopathologic or mutational signature of ARLC. A correlation between PD-L1 expression and response to immune checkpoint inhibition has not yet been proven. Thus, new biomarkers are needed to allow accurate diagnoses of ARLC, to enable prognostication and to offer personalized treatments. Liquid biopsies, encompassing circulating DNA and circulating tumor cells (CTCs), have gained attention as novel diagnostic methods in lung cancer to screen high-risk populations including those exposed to asbestos. CTCs can be enumerated and molecularly profiled to provide predictive and prognostic information. CTC studies have not been undertaken in populations at risk of ARLC to date. The potential of CTCs to provide real-time molecular insight into ARLC biology may significantly improve the diagnosis and management of ARLC patients.

The Role of Biomarkers in Lung Cancer Screening

BACKGROUND

Lung Cancer Screening (LCS) is an evolving field with variations in its implementation in various countries. There are only scarce data from National LCS programs.

AIM

We aim to provide an up-to-date overview of the current evidence regarding the use of biomarkers in LCS.

MATERIALS AND METHODS

A multidisciplinary Task Force experts' panel collaborated and conducted a systematic literature search, followed by screening, review and synthesis of available evidence.

RESULTS

Biomarkers in LCS could be used to improve risk stratification in high-risk participants, improve clarification regarding indeterminate lung nodules and avoid overdiagnosis in suspicious lung findings. Currently, there seem to be promising biomarkers (blood/serum/breath) that have been studied in various trials; however, there is still a lack of solid evidence in clinical validation that would pave the way for their integration into LCS programs.

CONCLUSIONS

Biomarkers are the next logical step in improving the LCS pathway and its efficiency by playing an adjuvant role in a minimally invasive way. National LCS programs and pilot studies should integrate biomarkers to validate their accuracy in real-life LCS participants.

Diagnostic value of circulating tumor cells in patients with thyroid cancer: a retrospective study of 1478 patients

BACKGROUND

Circulating tumor cell (CTC) detection is one form of liquid biopsy. It is a novel technique that is beginning to be applied in the field of thyroid cancer. The present study was designed to evaluate the diagnostic value of CTCs in patients with thyroid cancer.

METHODS

A total of 1478 patients were retrospectively analyzed and divided into malignant group (n = 747) and benign group (n = 731). Peripheral blood was collected, and CTCs were enriched and quantified before surgery. The baseline data of the two groups were matched by Propensity Score Matching (PSM). Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficiency of different indicators for thyroid cancer. The malignant group before PSM was further divided into subgroups according to the BRAF V600E mutation and lymphatic metastasis (N stage), and the number of CTCs in different subgroups was compared.

RESULTS

After 1:1 PSM, baseline characteristics of the malignant group and benign group were matched and assigned 315 cases in each group. The number of CTCs and the TPOAb values were comparable in the two groups (p > 0.05). The TgAb values [1.890 (1.110 - 16.010) vs 1.645 (1.030 - 7.073) IU/mL, p = 0.049] were significantly higher in the malignant group than in the benign group. After PSM, ROC analyses showed that the areas under the curve (AUCs) of CTC, TgAb and ultrasound were 0.537 (sensitivity 65.6%, specificity 45.8%), 0.546 (sensitivity 40.0%, specificity 70.8%) and 0.705 (sensitivity 77.1%, specificity 63.2%), respectively. The AUCs of the combined detection of 'CTC + ultrasound' (combine 1) and the combined detection of 'CTC + TgAb + ultrasound' (combine 2) were 0.718 (sensitivity 79.3%, specificity 61.7%) and 0.724 (sensitivity 78.0%, specificity 63.3%), respectively. The AUC of ultrasound was significantly higher than CTC (p < 0.001). There was no statistically significant difference in AUC between combination 1 and ultrasound, and between combination 2 and ultrasound (p > 0.05). The number of CTCs between the N0 and N1 subgroups, and between the BRAF mutant and BRAF wild subgroups was comparable (p > 0.05).

CONCLUSIONS

As an emerging and noninvasive testing tool, the efficacy of CTCs in diagnosing thyroid cancer is limited.

Functionalized tetrahedral DNA frameworks for the capture of circulating tumor cells

Identification and characterization of circulating tumor cells (CTCs) from blood samples of patients with cancer can help monitor parameters such as disease stage, disease progression and therapeutic efficiency. However, the sensitivity and specificity of current multivalent approaches used for CTC capture is limited by the lack of control over the ligands' position. In this Protocol Update, we describe DNA-tetrahedral frameworks anchored with aptamers that can be configured with user-defined spatial arrangements and stoichiometries. The modified tetrahedral DNA frameworks, termed 'n-simplexes', can be used as probes to specifically target receptor-ligand interactions on the cell membrane. Here, we describe the synthesis and use of n-simplexes that target the epithelial cell adhesion molecule expressed on the surface of CTCs. The characterization of the n-simplexes includes measuring the binding affinity to the membrane receptors as a result of the spatial arrangement and stoichiometry of the aptamers. We further detail the capture of CTCs from patient blood samples. The procedure for the preparation and characterization of n-simplexes requires 11.5 h, CTC capture from clinical samples and data processing requires ~5 h per six samples and the downstream analysis of captured cells typically requires 5.5 h. The protocol is suitable for users with basic expertise in molecular biology and handling of clinical samples.

Enumeration and Molecular Characterization of Circulating Tumor Cell Using an Epithelial Cell Adhesion Molecule/Vimentin/Epidermal Growth Factor Receptor Joint Capture System in Lung Cancer

Background

Detection rate and isolation yield of circulating tumor cells (CTCs) are low in lung cancer with approaches due to CTC invasiveness and heterogeneity. In this study, on the basis of the epithelial cell adhesion molecule (EpCAM) phenotype, markers of vimentin and epidermal growth factor receptor (EGFR) phenotype were added to jointly construct a precise and efficient CTC capture system for capture of lung cancer CTCs.

Methods

A CTC capture system combined with EpCAM lipid magnetic bead (Ep-LMB)/vimentin lipid magnetic bead (Vi-LMB)/EGFR lipid magnetic bead (EG-LMB) was constructed, and its performance was tested. The amount of CTC captured in the blood of patients with lung cancer was detected by immunofluorescence identification and analyzed for clinical relevance.

Results

The constructed CTC capture system has low cytotoxicity. The capture efficiency of lung cancer cells in phosphate belanced solution (PBS) system was 95.48%. The capture efficiency in the blood simulation system is 94.55%. The average number of CTCs in the blood of patients with lung cancer was 9.73/2 mL. The quantity distribution of CTCs is significantly correlated with tumor staging and metastasis. The area under the curve (AUC) of CTCs for the diagnosis of lung cancer was 0.9994 (95% CI = 0.9981-1.000, P < .0001). The cutoff value was 4.5/2 mL. The sensitivity was 99.39%, and the specificity was 96.88%.

Conclusion

The EpCAM/vimentin/EGFR combined capture system has feasibility and high sensitivity in the detection of lung cancer CTC typing, which can be used as an auxiliary diagnostic indicator for lung cancer and is expected to promote the clinical application of CTCs.

Integrating artificial intelligence into lung cancer screening: a randomised controlled trial protocol

INTRODUCTION

Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%-25%.Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects.Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting.

METHODS AND ANALYSIS

This open-label randomised controlled study focuses on LCS for patients aged 50-80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant.

ETHICS AND DISSEMINATION

The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations.

TRIAL REGISTRATION NUMBER

NCT05704920.

The diagnostic performance of micro-RNA and metabolites in lung cancer: A meta-analysis

BACKGROUND

The diagnosis of lung cancer is based on the microscopic exam of tissue or liquid. During the recent decade, many biomarkers have been pointed to have a potential diagnostic role. These biomarkers may be assessed in blood, pleural effusion or sputum and they could avoid biopsies or other risky procedures. The authors aimed to assess the diagnostic performances of biomarkers focusing on micro-RNA and metabolites.

METHODS

This meta-analysis was conducted under the PRISMA guidelines during a nine-year-period (2013-2022). the Meta-Disc software 5.4 (free version) was used. Q test and I2 statistics were carried out to explore the heterogeneity among studies. Meta-regression was performed in case of significant heterogeneity. Publication bias was assessed using the funnel plot test and the Egger's test (free version JASP).

RESULTS

According to our inclusion criteria, 165 studies from 79 articles were included. The pooled SEN, SPE and dOR accounted, respectively, for 0.76, 0.79 and 13.927. The AUC was estimated to 0.859 suggesting a good diagnostic accuracy. The heterogeneity in the pooled SEN and SPE was statistically significant. The meta-regression analysis focusing on the technique used, the sample, the number of biomarkers, the biomarker subtype, the tumor stage and the ethnicity revealed the biomarker number (p  =  0.009) and the tumor stage (p  =  0.0241) as potential sources of heterogeneity.

CONCLUSION

Even if this meta-analysis highlighted the potential diagnostic utility of biomarkers, more prospective studies should be performed, especially to assess the biomarkers' diagnostic potential in early-stage lung cancers.

A Prospective Long-Term Follow-Up Study: The Application of Circulating Tumor Cells Analysis to Guide Adjuvant Therapy in Stage II Colorectal Cancer

BACKGROUND

The efficacy of circulating tumor cells (CTCs) in the selection of stage II colorectal cancer (CRC) patients for adjuvant chemotherapy remains inconclusive.

OBJECTIVE

The aim of this study was to validate the necessity of adjuvant chemotherapy for stage II CRC patients with positive postoperative CTCs.

METHODS

The clinicopathological features and overall survival (OS) of a cohort of 70 patients with confirmed CRC were collected and analyzed.

RESULTS

The total rate of positive CTCs was 55.7%, while the average OS was 70.8 months and the OS rate was 75.7% (53/70). These 70 patients were divided into four subgroups, including a CTC-negative group with non-adjuvant chemotherapy (CHEMO-/CTC-) versus a CTC-positive group with non-adjuvant chemotherapy (CHEMO-/CTC+), CHEMO+/CTC- versus CHEMO+/CTC+, CHEMO-/CTC- versus CHEMO+/CTC-, and CHEMO+/CTC+ versus CHEMO-/CTC+; the total numbers in each subgroup were 25 versus 32, 6 versus 7, 25 versus 6, and 7 versus 32, respectively. The average OS of the CHEMO-/CTC- and CHEMO-/CTC+ groups was 82.0 and 68.1 months, respectively (p = 0.020); the average OS of the CHEMO+/CTC- and CHEMO+/CTC+ groups was 83.6 months and 76.4 months, respectively (p = 0.963); the average OS of the CHEMO-/CTC- and CHEMO+/CTC- groups was 82.0 months and 83.6 months, respectively (p = 0.999); and the average OS of the CHEMO+/CTC+ and CHEMO-/CTC+ groups was 76.4 months and 68.1 months, respectively (p = 0.247).

CONCLUSIONS

Positive CTCs are a potential prognostic marker for stage II CRC.

Early Detection of Lung Cancer Using Small RNAs

INTRODUCTION

Lung cancer remains the deadliest cancer in the world, and lung cancer survival is heavily dependent on tumor stage at the time of detection. Low-dose computed tomography screening can reduce mortality; however, annual screening is limited by low adherence in the United States of America and still not broadly implemented in Europe. As a result, less than 10% of lung cancers are detected through existing programs. Thus, there is a great need for additional screening tests, such as a blood test, that could be deployed in the primary care setting.

METHODS

We prospectively recruited 1384 individuals meeting the National Lung Screening Trial demographic eligibility criteria for lung cancer and collected stabilized whole blood to enable the pipetting-free collection of material, thus minimizing preanalytical noise. Ultra-deep small RNA sequencing (20 million reads per sample) was performed with the addition of a method to remove highly abundant erythroid RNAs, and thus open bandwidth for the detection of less abundant species originating from the plasma or the immune cellular compartment. We used 100 random data splits to train and evaluate an ensemble of logistic regression classifiers using small RNA expression of 943 individuals, discovered an 18-small RNA feature consensus signature (miLung), and validated this signature in an independent cohort (441 individuals). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin.

RESULTS

We generated diagnostic models and report a median receiver-operating characteristic area under the curve of 0.86 (95% confidence interval [CI]: 0.84-0.86) in the discovery cohort and generalized performance of 0.83 in the validation cohort. Diagnostic performance increased in a stage-dependent manner ranging from 0.73 (95% CI: 0.71-0.76) for stage I to 0.90 (95% CI: 0.89-0.90) for stage IV in the discovery cohort and from 0.76 to 0.86 in the validation cohort. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased after surgery with curative intent. In additional experiments, results of dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted through home sampling.

CONCLUSIONS

These data suggest the potential of a small RNA-based blood test as a viable alternative to low-dose computed tomography screening for early detection of smoking-associated lung cancer.

Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules

Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.6 million nodules are incidentally detected every year on chest CT scan images in the United States. This number of nodules identified is likely much larger after accounting for screening-detected nodules. Most of these nodules, whether incidentally or screening detected, are benign. Despite this, many patients undergo unnecessary invasive procedures to rule out cancer because our current stratification approaches are suboptimal, particularly for intermediate probability nodules. Thus, noninvasive strategies are urgently needed. Biomarkers have been developed to assist through the continuum of lung cancer care and include blood protein-based biomarkers, liquid biopsies, quantitative imaging analysis (radiomics), exhaled volatile organic compounds, and bronchial or nasal epithelium genomic classifiers, among others. Although many biomarkers have been developed, few have been integrated into clinical practice as they lack clinical utility studies showing improved patient-centered outcomes. Rapid technologic advances and large network collaborative efforts will continue to drive the discovery and validation of many novel biomarkers. Ultimately, however, randomized clinical utility studies showing improved patient outcomes will be required to bring biomarkers into clinical practice.

Identify the Clinicopathological Characteristics of Lung Carcinoma Patients Being False Negative in Folate Receptor Based Circulating Tumor Cell Detection

In lung cancer diagnosis, folate receptor (FR)-based circulating tumor cell (CTC) has shown its ability to distinguish malignancy from benign disease to some extent. However, there are still some patients that cannot be identified by FR-based CTC detection. And studies comparing the characteristics between true positive (TP) and false negative (FN) patients are few. Thus, the study comprehensively analyzes the clinicopathological characteristics of FN and TP patients in the current study. According to inclusion and exclusion criteria, 3420 patients are enrolled. Combining the pathological diagnosis with CTC results, patients are divided into FN and TP groups, and clinicopathological characteristics are compared between two groups. Compared with TP patients, FN patients have smaller tumor, early T stage, early pathological stage, and without lymph node metastasis. Epidermal growth factor receptor (EGFR) mutation status is different between FN and TP group. And this result is also demonstrated in lung adenocarcinoma subgroup but not in lung squamous cell carcinoma subgroup. Tumor size, T stage, pathological stage, lymph node metastasis, and EGFR mutation status may influence the accuracy of FR-based CTC detection in lung cancer. However, further prospective studies are needed to confirm the findings.

Circulating tumor cells in cancer-risk populations as a cancer interception tool

Cancer interception (CI) is a new approach to cancer prevention and treatment in a cancer-risk population that aims to detect and treat pre-tumoral stages. It has several potential advantages over traditional cancer diagnosis and monitoring methods because it is non-invasive, making it less painful and risky than conventional biopsy procedures. The circulating tumor cells (CTCs), liquid biopsy family members, are essential for the CI approach; then, the liquid biopsy (LB) is used as a CI tool. LB can be performed frequently because of its easy sampling and early pathological stages, which allow repeated non-invasive monitoring of cancer progression and response to treatment. CTCs have been found in the bloodstream of several types of cancer patients, including in early-stage cancer and premalignant lesions, suggesting a tumor development role in cancer's early stages. This chapter will present foundational scientific studies addressing CI and the clinical impact of CTC screening in a population at risk for cancer.

Matched tissue and liquid biopsies for advanced non-small cell lung cancer patients A potentially indispensable complementary approach

The introduction of liquid biopsies (LB) has brought forth a number of therapeutic opportunities into the domain of thoracic oncology. Many of which have been adopted for care of patients presenting with advanced non-squamous non-small cell lung cancer (aNS-NSCLC). For example, one of the most frequent indications to perform a LB in these patients, at least in Europe, is for patients treated with tyrosine kinase inhibitors (TKIs) targeting EGFR and ALK genomic alterations when the tumor progresses. A tissue biopsy (TB) must then be taken, ideally from a site of a tumor that progresses, in particular if the LB does not permit detection of a mechanism of resistance to TKI. A LB from a patient with aNS-NSCLC is recommended before first-line therapy if no tissue and/or cytological material is accessible or if the extracted nucleic acid is insufficient in amount and/or of poor quality. At present a LB and a TB are rarely performed simultaneously before treatment and/or on tumor progression. This complementary/matched testing approach is still controversial but needs to be better evaluated to determine the true benefit to care of patients. This review provides an update on the complementarity of the LB and TB method for care of patients presenting with aNS-NSCLC.

Tumor-educated platelet blood tests for Non-Small Cell Lung Cancer detection and management

Liquid biopsy approaches offer a promising technology for early and minimally invasive cancer detection. Tumor-educated platelets (TEPs) have emerged as a promising liquid biopsy biosource for the detection of various cancer types. In this study, we processed and analyzed the TEPs collected from 466 Non-small Cell Lung Carcinoma (NSCLC) patients and 410 asymptomatic individuals (controls) using the previously established thromboSeq protocol. We developed a novel particle-swarm optimization machine learning algorithm which enabled the selection of an 881 RNA biomarker panel (AUC 0.88). Herein we propose and validate in an independent cohort of samples (n = 558) two approaches for blood samples testing: one with high sensitivity (95% NSCLC detected) and another with high specificity (94% controls detected). Our data explain how TEP-derived spliced RNAs may serve as a biomarker for minimally-invasive clinical blood tests, complement existing imaging tests, and assist the detection and management of lung cancer patients.

Circulating tumour cells for early detection of clinically relevant cancer

Given that cancer mortality is usually a result of late diagnosis, efforts in the field of early detection are paramount to reducing cancer-related deaths and improving patient outcomes. Increasing evidence indicates that metastasis is an early event in patients with aggressive cancers, often occurring even before primary lesions are clinically detectable. Metastases are usually formed from cancer cells that spread to distant non-malignant tissues via the blood circulation, termed circulating tumour cells (CTCs). CTCs have been detected in patients with early stage cancers and, owing to their association with metastasis, might indicate the presence of aggressive disease, thus providing a possible means to expedite diagnosis and treatment initiation for such patients while avoiding overdiagnosis and overtreatment of those with slow-growing, indolent tumours. The utility of CTCs as an early diagnostic tool has been investigated, although further improvements in the efficiency of CTC detection are required. In this Perspective, we discuss the clinical significance of early haematogenous dissemination of cancer cells, the potential of CTCs to facilitate early detection of clinically relevant cancers, and the technological advances that might improve CTC capture and, thus, diagnostic performance in this setting.

Utilization of Circulating Tumor Cells in the Management of Solid Tumors

Circulating tumor cells (CTCs) are tumor cells shed from the primary tumor into circulation, with clusters of CTCs responsible for cancer metastases. CTC detection and isolation from the bloodstream are based on properties distinguishing CTCs from normal blood cells. Current CTC detection techniques can be divided into two main categories: label dependent, which depends upon antibodies that selectively bind cell surface antigens present on CTCs, or label-independent detection, which is detection based on the size, deformability, and biophysical properties of CTCs. CTCs may play significant roles in cancer screening, diagnosis, treatment navigation, including prognostication and precision medicine, and surveillance. In cancer screening, capturing and evaluating CTCs from peripheral blood could be a strategy to detect cancer at its earliest stage. Cancer diagnosis using liquid biopsy could also have tremendous benefits. Full utilization of CTCs in the clinical management of malignancies may be feasible in the near future; however, several challenges still exist. CTC assays currently lack adequate sensitivity, especially in early-stage solid malignancies, due to low numbers of detectable CTCs. As assays improve and more trials evaluate the clinical utility of CTC detection in guiding therapies, we anticipate increased use in cancer management.

Role of circulating-tumor DNA in the early-stage non-small cell lung carcinoma as a predictive biomarker

Lung cancer is one of the most common solid malignancies. Tissue biopsy is the standard method for accurately diagnosing lung and many other malignancies over decades. However, molecular profiling of tumors leads to establishing a new horizon in the field of precision medicine, which has now entered the mainstream in clinical practice. In this context, a minimally invasive complementary method has been proposed as a liquid biopsy (LB) which is a blood-based test that is gaining popularity as it provides the opportunity to test genotypes in a unique, less invasive manner. Circulating tumor cells (CTC) captivating the Circulating-tumor DNA (Ct-DNA) are often present in the blood of lung cancer patients and are the fundamental concept behind LB. There are multiple clinical uses of Ct-DNA, including its role in prognostic and therapeutic purposes. The treatment of lung cancer has drastically evolved over time. Therefore, this review article mainly focuses on the current literature on circulating tumor DNA and its clinical implications and future goals in non-small cell lung cancer.

The prevalence of comorbidity in the lung cancer screening population: A systematic review and meta-analysis

OBJECTIVE

Comorbidity is associated with adverse outcomes for all lung cancer patients, but its burden is less understood in the context of screening. This review synthesises the prevalence of comorbidities among lung cancer screening (LCS) candidates and summarises the clinical recommendations for screening comorbid individuals.

METHODS

We searched MEDLINE, EMBASE, EBM Reviews, and CINAHL databases from January 1990 to February 2021. We included LCS studies that reported a prevalence of comorbidity, as a prevalence of a particular condition, or as a summary score. We also summarised LCS clinical guidelines that addressed comorbidity or frailty for LCS as a secondary objective for this review. Meta-analysis was used with inverse-variance weights obtained from a random-effects model to estimate the prevalence of selected comorbidities.

RESULTS

We included 69 studies in the review; seven reported comorbidity summary scores, two reported performance status, 48 reported individual comorbidities, and 12 were clinical guideline papers. The meta-analysis of individual comorbidities resulted in an estimated prevalence of 35.2% for hypertension, 23.5% for history of chronic obstructive pulmonary disease (COPD) (10.7% for severe COPD), 16.6% for ischaemic heart disease (IHD), 13.1% for peripheral vascular disease (PVD), 12.9% for asthma, 12.5% for diabetes, 4.5% for bronchiectasis, 2.2% for stroke, and 0.5% for pulmonary fibrosis.

CONCLUSIONS

Comorbidities were highly prevalent in LCS populations and likely to be more prevalent than in other cancer screening programmes. Further research on the burden of comorbid disease and its impact on screening uptake and outcomes is needed. Identifying individuals with frailty and comorbidities who might not benefit from screening should become a priority in LCS research.

Clinical Utility and Application of Liquid Biopsy Genotyping in Lung Cancer: A Comprehensive Review

Precision medicine has revolutionized the therapeutic management of cancer patients with a major impact on non-small cell lung cancer (NSCLC), particularly lung adenocarcinoma, where advances have been remarkable. Tissue biopsy, required for tumor molecular testing, has significant limitations due to the difficulty of the biopsy site or the inadequacy of the histological specimen. In this context, liquid biopsy, consisting of the analysis of tumor-released materials circulating in body fluids, such as blood, is increasingly emerging as a valuable and non-invasive biomarker for detecting circulating tumor DNA (ctDNA) carrying molecular tumor signatures. In advanced/metastatic NSCLC, liquid biopsy drives target therapy by monitoring response to treatment and identifying eventual genomic mechanisms of resistance. In addition, recent data have shown a significant ability to detect minimal residual disease in early-stage lung cancer, underlying the potential application of liquid biopsy in the adjuvant setting, in early detection of recurrence, and also in the screening field. In this article, we present a review of the currently available data about the utility and application of liquid biopsy in lung cancer, with a particular focus on the approach to different techniques of analysis for liquid biopsy and a comparison with tissue samples as well as the potential practical uses in early and advanced/metastatic NSCLC.

Circulating tumor cells dynamics during chemotherapy predict survival and response in advanced non-small-cell lung cancer patients

Background

Circulating tumor cells (CTCs) are prognostic biomarker in non-small-cell lung cancer (NSCLC). CTCs could also be used as predictor of efficacy of systemic treatments in advanced NSCLC.

Objectives

We described the dynamic changes of CTCs during first-line platinum-based chemotherapy in advanced NSCLC and clarified the correlation between CTC counts and efficacy of chemotherapy.

Design

Chemotherapy is administered and blood specimens are collected at four time points from baseline to disease progression for CTC detection.

Methods

This multicenter prospective study enrolled patients with previously untreated stage III or IV NSCLC fit for standard platinum-based chemotherapy. Bloods were sampled as per standard operating procedures at baseline, cycle 1 and cycle 4 of chemotherapy, and at disease progression for CTC analysis using the CellSearch system.

Results

Among 150 patients enrolled, median overall survival (OS) was 13.8, 8.4, and 7.9 months in patients with CTC^-, KIT^-CTC, and KIT⁺CTC at baseline (p = 0.002). Patients with persistent negative CTC (46.0%) had longer progression-free survival [5.7 months, 95% confidence interval (CI): 5.0-6.5 versus 3.0 months, 0.6-5.4; hazard ratio (HR): 0.34, 95% CI: 0.18-0.67) and OS (13.1 months, 10.9-15.3 versus 5.6 months, 4.1-7.1; HR: 0.17, 0.08-0.36) compared with patients with persistent positive CTC (10.7%), which was not impacted by chemotherapy. Chemotherapy decreased CTC from 36.0% (54/150) to 13.7% (13/95).

Conclusions

CTC persistent presence during treatment represents poor prognosis and resistance to chemotherapy in advanced NSCLC. Chemotherapy could effectively eliminate CTCs. Molecular characterization and the functionalization of CTC will be warranted for further intensive investigation.

Trial registration

NCT01740804.

SCLC: Epidemiology, Risk Factors, Genetic Susceptibility, Molecular Pathology, Screening, and Early Detection

We review research regarding the epidemiology, risk factors, genetic susceptibility, molecular pathology, and early detection of SCLC, a deadly tumor that accounts for 14% of lung cancers. We first summarize the changing incidences of SCLC globally and in the United States among males and females. We then review the established risk factor (i.e., tobacco smoking) and suspected nonsmoking-related risk factors for SCLC, and emphasize the importance of continued effort in tobacco control worldwide. Review of genetic susceptibility and molecular pathology suggests different molecular pathways in SCLC development compared with other types of lung cancer. Last, we comment on the limited utility of low-dose computed tomography screening in SCLC and on several promising blood-based molecular biomarkers as potential tools in SCLC early detection.

Potential Value and Application of Liquid Biopsy in Tumor, Neurodegeneration, and Muscle Degenerative Diseases

Liquid biopsy provides a promising alternative for the detection of disease-specific markers due to its superior noninvasive and original tissue representativeness. Liquid biopsies have a wide range of health and disease applications involving components ranging from circulating cells to acellular nucleic acid molecules and other metabolites. Here, we review the different components of liquid biopsy and investigate the most advanced noninvasive methods for detecting these components as well as their existing problems and trends. In particular, we emphasize the importance of analyzing liquid biopsy data from extracellular vesicles and small nucleic acids in neurological and muscle degeneration, with the aim of using this technique to enhance personalized healthcare. Although previous reviews have focused on cancer, this review mainly emphasizes the potential application of extracellular vesicles and microRNAs in liquid biopsy in neurodegeneration and muscle degeneration.

Glycoproteomics revealed novel N-glycosylation biomarkers for early diagnosis of lung adenocarcinoma cancers

Circulating biomarkers play important roles in diagnosis of malignant tumors. N-glycosylation is an important post-translation patter and obviously affect biological behaviors of malignant tumor cells. However, the role of N-glycosylation sites in early diagnosis of tumors still remains further investigation. In this study, plasma from 20 lung adenocarcinoma (LUAD), which were all classified as stage I, as well as 20 normal controls (NL) were labeled and screened by mass spectrometry (MS). Total 39 differential N-glycosylation sites were detected in LUAD, 17 were up-regulated and 22 were down-regulated. In all differential sites, ITGB3-680 showed highest potential in LUAD which showed 99.2% AUC, 95.0% SP and 95.0% SN. Besides, APOB-1523 (AUC: 89.0%, SP: 95.0%, SN: 70.0%), APOB-2982 (AUC: 86.8%, SP: 95.0%, SN: 45.0%) and LPAL2-101 (AUC: 81.1%, SP: 95.0%, SN: 47.4%) also acted as candidate biomarkers in LUAD. Combination analysis was then performed by random forest model, all samples were divided into training group (16 cases) and testing group (4 cases) and conducted by feature selection, machine learning, integrated model of classifier and model evaluation. And the results indicated that combination of differential sites could reach 100% AUC in both training and testing group. Taken together, our study revealed multiple N-glycosylation sites which could be applied as candidate biomarkers for early diagnosis diagnosis of LUAD.

Liquid Biopsy Analysis as a Tool for TKI-Based Treatment in Non-Small Cell Lung Cancer

The treatment of non-small cell lung cancer (NSCLC) has recently evolved with the introduction of targeted therapy based on the use of tyrosine kinase inhibitors (TKIs) in patients with certain gene alterations, including EGFR, ALK, ROS1, BRAF, and MET genes. Molecular targeted therapy based on TKIs has improved clinical outcomes in a large number of NSCLC patients with advanced disease, enabling significantly longer progression-free survival (PFS). Liquid biopsy is an increasingly popular diagnostic tool for treating TKI-based NSCLC. The studies presented in this article show that detection and analysis based on liquid biopsy elements such as circulating tumor cells (CTCs), cell-free DNA (cfDNA), exosomes, and/or tumor-educated platelets (TEPs) can contribute to the appropriate selection and monitoring of targeted therapy in NSCLC patients as complementary to invasive tissue biopsy. The detection of these elements, combined with their molecular analysis (using, e.g., digital PCR (dPCR), next generation sequencing (NGS), shallow whole genome sequencing (sWGS)), enables the detection of mutations, which are required for the TKI treatment. Despite such promising results obtained by many research teams, it is still necessary to carry out prospective studies on a larger group of patients in order to validate these methods before their application in clinical practice.

Delineating the role of extracellular vesicles in cancer metastasis: A comprehensive review

Extracellular vesicles (EVs) are subcellular messengers that aid in the formation and spread of cancer by enabling tumor-stroma communication. EVs develop from the very porous structure of late endosomes and hold information on both the intrinsic “status” of the cell and the extracellular signals absorbed by the cells from their surroundings. These EVs contain physiologically useful components, including as nucleic acids, lipids, and proteins, which have been found to activate important signaling pathways in tumor and tumor microenvironment (TME) cells, aggravating tumor growth. We highlight critical cell biology mechanisms that link EVS formation to cargo sorting in cancer cells in this review.Sorting out the signals that control EVs creation, cargo, and delivery will aid our understanding of carcinogenesis. Furthermore, we reviewed how cancer development and spreading behaviors are affected by coordinated communication between malignant and non-malignant cells. Herein, we studied the reciprocal exchanges via EVs in various cancer types. Further research into the pathophysiological functions of various EVs in tumor growth is likely to lead to the discovery of new biomarkers in liquid biopsy and the development of tumor-specific therapies.

Extracellular Vesicles and Circulating Tumour Cells - complementary liquid biopsies or standalone concepts?

Liquid biopsies do promise a lot, but are they keeping it? In the past decade, additional novel biomarkers qualified to be called like that, of which, some took necessary hurdles resulting in FDA approval and clinical use. Some others are since a while around, well known and were once regarded to be a game changer in cancer diagnosis or cancer screening. But, during their clinical use limitations were observed from statistical significance and questions raised regarding their robustness, that eventually led to be dropped from associated clinical guidelines for certain applications including cancer diagnosis. The purpose of this review isn't to give a broad overview of all current liquid biopsy as biomarkers, weight them and promise a brighter future in cancer prevention, but rather to take a deeper look on two of those who do qualify to be called liquid biopsies now or then. These two are probably of greatest interest conceptually and methodically, and likely have the highest chances to be in clinical use soon, with a portfolio extension over their original conceptual usage. We aim to dig deeper beyond cancer diagnosis or cancer screening. Actually, we aim to review in depth extracellular vesicles (EVs) and compare with circulating tumour cells (CTCs). The latter methodology is partially FDA approved and in clinical use. We will lay out similarities as taking advantage of surface antigens on EVs and CTCs in case of characterization and quantification. But drawing readers' attention to downstream application based on capture/isolation methodology and simply on their overall nature, here apparently being living material eventually recoverable as CTCs are vs. dead material with transient effects on recipient cell as in case of EVs. All this we try to bring in perspective, compare and conclude towards which future direction we are aiming for, or should aim for. Do we announce a winner between CTCs vs EVs? No, but we provide good reasons to intensify research on them.

Detection of circulating tumor cells: opportunities and challenges

Circulating tumor cells (CTCs) are cells that shed from a primary tumor and travel through the bloodstream. Studying the functional and molecular characteristics of CTCs may provide in-depth knowledge regarding highly lethal tumor diseases. Researchers are working to design devices and develop analytical methods that can capture and detect CTCs in whole blood from cancer patients with improved sensitivity and specificity. Techniques using whole blood samples utilize physical prosperity, immunoaffinity or a combination of the above methods and positive and negative enrichment during separation. Further analysis of CTCs is helpful in cancer monitoring, efficacy evaluation and designing of targeted cancer treatment methods. Although many advances have been achieved in the detection and molecular characterization of CTCs, several challenges still exist that limit the current use of this burgeoning diagnostic approach. In this review, a brief summary of the biological characterization of CTCs is presented. We focus on the current existing CTC detection methods and the potential clinical implications and challenges of CTCs. We also put forward our own views regarding the future development direction of CTCs.

Specific Tumor Cell Detection by a Metabolically Targeted Aggregation-Induced Emission-Based Gold Nanoprobe

Detection of circulating tumor cells (CTCs) could be widely used for early diagnosis and real-time monitoring of tumor progression in liquid biopsy samples. Compared with normal cells, tumor cells exhibit relatively strong negative surface charges due to the high rate of glycolysis. In this study, a cationic fluorescence "turn-on" aggregation-induced emission (AIE) nanoprobe based on gold nanorods (GNRs) was designed and tested to detect tumor cells specifically. In brief, tetraphenylethene (TPE), an AIE dye, was conjugated to the cationic polymer polyethylenimine (PEI) yielding TPEI. TPEI-PEG-SH was obtained by further functionalizing TPEI with a thiol group. TPEI-PEG-SH was grafted to the surface of GNRs, yielding the cationic AIE nanoprobe, named as GNRs-PEG-TPEI. The nanoprobe was characterized to have a uniform particle size of 172 nm, a strong positive surface charge (+54.87 mV), and a surface modification load of ∼40%. The in vitro stability of GNRs-PEG-TPEI was verified. The cellular imaging results demonstrated that the nanoprobe could efficiently recognize several types of tumor cells including MCF-7, HepG2, and Caco-2 while exhibiting specific fluorescence signals only after interacting with tumor cells and minimal background interference. In addition, the study investigated the toxicity of the nanoprobe to the captured cells and proved the safety of the nanoprobe. In conclusion, a specific and efficient nanoprobe was developed for capture and detection of different types of tumor cells based on their unique metabolic characteristics. It holds great promise for achieving early diagnosis and monitoring the tumor progression by detecting the CTCs in clinical liquid biopsy samples.

An electrochemical biosensor based on few-layer MoS2 nanosheets for highly sensitive detection of tumor marker ctDNA

An electrochemical biosensor based on few-layer molybdenum disulfide (MoS₂) nanosheets was fabricated for the highly sensitive detection of tumor marker circulating tumor DNA (ctDNA) in this paper. The MoS₂ nanosheets with few layers were prepared by the shear stripping. Compared with the mechanical stripping method and the lithium ion intercalation method, this method is simpler to operate, and the prepared MoS₂ nanosheets had good electrochemical activity. The biosensing platform was fabricated based on the discriminative affinity of MoS₂ nanosheets towards single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA). Methylene blue (MB) was used as the signal molecule. The results showed that the detection of ctDNA by this sensor showed an excellent linear relationship in the concentration range of 1.0 × 10^-7 M to 1.0 × 10^-16 M, and the detection limit was 2.5 × 10^-18 M. In addition, this sensor exhibited outstanding stability and specificity. This strategy provides an alternative approach for ctDNA detection and an effective sensing strategy for future in vitro cancer diagnosis by label-free detection.

Advances in lung cancer screening and early detection

Lung cancer is associated with a heavy cancer-related burden in terms of patients' physical and mental health worldwide. Two randomized controlled trials, the US-National Lung Screening Trial (NLST) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON), indicated that low-dose CT (LDCT) screening results in a statistically significant decrease in mortality in patients with lung cancer, LDCT has become the standard approach for lung cancer screening. However, many issues in lung cancer screening remain unresolved, such as the screening criteria, high false-positive rate, and radiation exposure. This review first summarizes recent studies on lung cancer screening from the US, Europe, and Asia, and discusses risk-based selection for screening and the related issues. Second, an overview of novel techniques for the differential diagnosis of pulmonary nodules, including artificial intelligence and molecular biomarker-based screening, is presented. Third, current explorations of strategies for suspected malignancy are summarized. Overall, this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.

Circulating Tumor-Macrophage Fusion Cells and Circulating Tumor Cells Complement Non-Small-Cell Lung Cancer Screening in Patients With Suspicious Lung-RADS 4 Nodules

PURPOSE

Low-dose computed tomography (LDCT) screening of high-risk patients decreases lung cancer-related mortality. However, high false-positive rates associated with LDCT result in unnecessary interventions. To distinguish non-small-cell lung cancer (NSCLC) from benign nodules, in the present study, we integrated cellular liquid biomarkers in patients with suspicious lung nodules (lung cancer screening reporting and data system [Lung-RADS] 4).

METHODS

Prospectively, 7.5 mL of blood was collected from 221 individuals (training set: 90 nonscreened NSCLC patients, 74 high-risk screening patients with no/benign nodules [Lung-RADS 1-3], and 20 never smokers; validation set: 37 patients with suspicious nodules [Lung-RADS 4]). Circulating tumor cells (CTCs), CTC clusters, and tumor-macrophage fusion (TMF) cells were identified by blinded analyses. Screening patients underwent a median of two LDCTs (range, 1-4) with a median surveillance time of 30 (range, 11-50) months.

RESULTS

In the validation set of 37 Lung-RADS 4 patients, all circulating cellular biomarker counts (P < .005; Wilcoxon test) and positivity rates were significantly higher in 23 biopsy-proven NSCLC patients (CTCs: 23 of 23 [100%], CTC clusters: 6 of 23 [26.1%], and TMF cells: 15 of 23 [65.2%]) than in 14 patients with biopsy-proven benign nodules (6 of 14 [42.9%], 0 of 14 [0%], and 2 of 14 [14.3%]). On the basis of cutoff values from the training set, logistic regression with receiver operating characteristic and area under the curve analyses demonstrated that CTCs (sensitivity: 0.870, specificity: 1.0, and area under the curve: 0.989) and TMF cells (0.652; 0.880; 0.790) complement LDCT in diagnosing NSCLC in Lung-RADS 4 patients.

CONCLUSION

Cellular liquid biomarkers have a potential to complement LDCT interpretation of suspicious Lung-RADS 4 nodules to distinguish NSCLC from benign lung nodules. A future prospective, large-scale, multicenter clinical trial should validate the role of cellular liquid biomarkers in improving diagnostic accuracy in high-risk patients with Lung-RADS 4 nodules.

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.

Tobacco carcinogen 4-[methyl(nitroso)amino]-1-(3-pyridinyl)-1-butanone (NNK) drives metabolic rewiring and epigenetic reprograming in A/J mice lung cancer model and prevention with diallyl sulphide (DAS)

Early detection of biomarkers in lung cancer is one of the best preventive strategies. Although many attempts have been made to understand the early events of lung carcinogenesis including cigarette smoking (CS) induced lung carcinogenesis, the integrative metabolomics and next-generation sequencing approaches are lacking. In this study, we treated the female A/J mice with CS carcinogen 4-[methyl(nitroso)amino]-1-(3-pyridinyl)-1-butanone (NNK) and naturally occurring organosulphur compound, diallyl sulphide (DAS) for 2 and 4 weeks after NNK injection and examined the metabolomic and DNA CpG methylomic and RNA transcriptomic profiles in the lung tissues. NNK drives metabolic changes including mitochondrial tricarboxylic acid (TCA) metabolites and pathways including Nicotine and its derivatives like nicotinamide and nicotinic acid. RNA-seq analysis and Reactome pathway analysis demonstrated metabolism pathways including Phase I and II drug metabolizing enzymes, mitochondrial oxidation and signaling kinase activation pathways modulated in a sequential manner. DNA CpG methyl-seq analyses showed differential global methylation patterns of lung tissues from week 2 versus week 4 in A/J mice including Adenylate Cyclase 6 (ADCY6), Ras-related C3 botulinum toxin substrate 3 (Rac3). Oral DAS treatment partially reversed some of the mitochondrial metabolic pathways, global methylation and transcriptomic changes during this early lung carcinogenesis stage. In summary, our result provides insights into CS carcinogen NNK's effects on driving alterations of metabolomics, epigenomics and transcriptomics and the chemopreventive effect of DAS in early stages of sequential lung carcinogenesis in A/J mouse model.

A Classifier for Improving Early Lung Cancer Diagnosis Incorporating Artificial Intelligence and Liquid Biopsy

Lung cancer is the leading cause of cancer-related deaths worldwide and in China. Screening for lung cancer by low dose computed tomography (LDCT) can reduce mortality but has resulted in a dramatic rise in the incidence of indeterminate pulmonary nodules, which presents a major diagnostic challenge for clinicians regarding their underlying pathology and can lead to overdiagnosis. To address the significant gap in evaluating pulmonary nodules, we conducted a prospective study to develop a prediction model for individuals at intermediate to high risk of developing lung cancer. Univariate and multivariate logistic analyses were applied to the training cohort (n = 560) to develop an early lung cancer prediction model. The results indicated that a model integrating clinical characteristics (age and smoking history), radiological characteristics of pulmonary nodules (nodule diameter, nodule count, upper lobe location, malignant sign at the nodule edge, subsolid status), artificial intelligence analysis of LDCT data, and liquid biopsy achieved the best diagnostic performance in the training cohort (sensitivity 89.53%, specificity 81.31%, area under the curve [AUC] = 0.880). In the independent validation cohort (n = 168), this model had an AUC of 0.895, which was greater than that of the Mayo Clinic Model (AUC = 0.772) and Veterans' Affairs Model (AUC = 0.740). These results were significantly better for predicting the presence of cancer than radiological features and artificial intelligence risk scores alone. Applying this classifier prospectively may lead to improved early lung cancer diagnosis and early treatment for patients with malignant nodules while sparing patients with benign entities from unnecessary and potentially harmful surgery.

Clinical Trial Registration Number

ChiCTR1900026233, URL: http://www.chictr.org.cn/showproj.aspx?proj=43370.

Three-Dimensional Convolutional Neural Network-Based Prediction of Epidermal Growth Factor Receptor Expression Status in Patients With Non-Small Cell Lung Cancer

Objectives

EGFR testing is a mandatory step before targeted therapy for non-small cell lung cancer patients. Combining some quantifiable features to establish a predictive model of EGFR expression status, break the limitations of tissue biopsy.

Materials and Methods

We retrospectively analyzed 1074 patients of non-small cell lung cancer with complete reports of EGFR gene testing. Then manually segmented VOI, captured the clinicopathological features, analyzed traditional radiology features, and extracted radiomic, and deep learning features. The cases were randomly divided into training and test set. We carried out feature screening; then applied the light GBM algorithm, Resnet-101 algorithm, logistic regression to develop sole models, and fused models to predict EGFR mutation conditions. The efficiency of models was evaluated by ROC and PRC curves.

Results

We successfully established Model_clinical, Model_radiomic, Model_CNN (based on clinical-radiology, radiomic and deep learning features respectively), Model_{radiomic+clinical} (combining clinical-radiology and radiomic features), and Model_{CNN+radiomic+clinical} (combining clinical-radiology, radiomic, and deep learning features). Among the prediction models, Model_{CNN+radiomic+clinical} showed the highest performance, followed by Model_CNN, and then Model_{radiomic+clinical}. All three models were able to accurately predict EGFR mutation with AUC values of 0.751, 0.738, and 0.684, respectively. There was no significant difference in the AUC values between Model_{CNN+radiomic+clinical} and Model_CNN. Further analysis showed that Model_{CNN+radiomic+clinical} effectively improved the efficacy of Model_{radiomic+clinical} and showed better efficacy than Model_CNN. The inclusion of clinical-radiology features did not effectively improve the efficacy of Model_radiomic.

Conclusions

Either deep learning or radiomic signature-based models can provide a fairly accurate non-invasive prediction of EGFR expression status. The model combined both features effectively enhanced the performance of radiomic models and provided marginal enhancement to deep learning models. Collectively, fusion models offer a novel and more reliable way of providing the efficacy of currently developed prediction models, and have far-reaching potential for the optimization of noninvasive EGFR mutation status prediction methods.

Differences in detection patterns, characteristics, and outcomes of central and peripheral lung cancers in low-dose computed tomography screening

Background

Although low-dose computed tomography (LDCT) screening is known to be effective for the detection of lung cancers localized in peripheral lung regions at a curable stage, limited data is available regarding the characteristics and outcomes of central lung cancers diagnosed in a screening cohort. This study aimed to determine whether LDCT screening could effectively detect central lung cancers at an early stage and offer survival benefits.

Methods

We analyzed 52,615 adults who underwent lung cancer screening with LDCT between May 2003 and Dec 2019 at a tertiary center in South Korea. Characteristics and outcomes of those diagnosed with lung cancer, stratified by screen-detection status and cancer location, were evaluated.

Results

A total of 352 individuals (281 screen-detected, 71 non-screen-detected) were diagnosed with lung cancer. Compared to screen-detected cancers, non-screen-detected cancers tended to be centrally-located (11.4% vs. 64.8%, P<0.001). Most non-screen-detected central cancers (89.1%) had a negative result on prior LDCT screening. Multivariable regression analyses revealed that for peripheral cancers, screen-detection was associated with a significantly lower probability of diagnosis at an advanced stage [III/IV, odds ratio (OR) =0.15, 95% confidence interval (CI): 0.05-0.45] and mortality [hazard ratio (HR) =0.33, 95% CI: 0.13-0.84]; however, the association was insignificant for central cancers. For screen-detected cancers, central location, compared to peripheral location, was significantly associated with a higher risk of diagnosis at an advanced stage (OR =20.83, 95% CI: 6.67-64.98) and mortality (HR =4.98, 95% CI: 2.26-10.97).

Conclusions

Unlike for peripheral cancers, LDCT screening did not demonstrate an improvement in outcomes of central lung cancers, indicating an important limitation of LDCT screening and the need for developing novel modalities to screen and treat central lung cancer.

Nanoplateletsomes restrain metastatic tumor formation through decoy and active targeting in a preclinical mouse model

Platelets buoy up cancer metastasis via arresting cancer cells, enhancing their adhesion, and facilitating their extravasation through the vasculature. When deprived of intracellular and granular contents, platelet decoys could prevent metastatic tumor formation. Inspired by these, we developed nanoplatesomes by fusing platelet membranes with lipid membranes (P-Lipo) to restrain metastatic tumor formation more efficiently. It was shown nanoplateletsomes bound with circulating tumor cells (CTC) efficiently, interfered with CTC arrest by vessel endothelial cells, CTC extravasation through endothelial layers, and epithelial-mesenchymal transition of tumor cells as nanodecoys. More importantly, in the mouse breast tumor metastasis model, nanoplateletsomes could decrease CTC survival in the blood and counteract metastatic tumor growth efficiently by inhibiting the inflammation and suppressing CTC escape. Therefore, nanoplatelesomes might usher in a new avenue to suppress lung metastasis.

Blood-based liquid biopsy: Insights into early detection and clinical management of lung cancer

Currently, early detection of lung cancer relies on the characterisation of images generated from computed tomography (CT). However, lung tissue biopsy, a highly invasive surgical procedure, is required to confirm CT-derived diagnostic results with very high false-positive rates. Hence, a non-invasive or minimally invasive biomarkers is essential to complement the existing low-dose CT (LDCT) for early detection, improve responses to a certain treatment, predict cancer recurrence, and to evaluate prognosis. In the past decade, liquid biopsies (e.g., blood) have been demonstrated to be highly effective for lung cancer biomarker discovery. In this review, the roles of emerging liquid biopsy-derived biomarkers such as circulating nucleic acids, circulating tumour cells (CTCs), long non-coding RNA (lncRNA), and microRNA (miRNA), as well as exosomes, have been highlighted. The advantages and limitations of these blood-based minimally invasive biomarkers have been discussed. Furthermore, the current progress of the identified biomarkers for clinical management of lung cancer has been summarised. Finally, a potential strategy for the early detection of lung cancer, using a combination of LDCT scans and well-validated biomarkers, has been discussed.

Potential of Stem Cells and CART as a Potential Polytherapy for Small Cell Lung Cancer

Despite the increasing urgency of the problem of treating small cell lung cancer (SCLC), information on the causes of its development is fragmentary. There is no complete understanding of the features of antitumor immunity and the role of the microenvironment in the development of SCLC resistance. This impedes the development of new methods for the diagnosis and treatment of SCLC. Lung cancer and chronic obstructive pulmonary disease (COPD) have common pathogenetic factors. COPD is a risk factor for lung cancer including SCLC. Therefore, the search for effective approaches to prevention, diagnosis, and treatment of SCLC in patients with COPD is an urgent task. This review provides information on the etiology and pathogenesis of SCLC, analyses the effectiveness of current treatment options, and critically evaluates the potential of chimeric antigen receptor T cells therapy (CART therapy) in SCLC. Moreover, we discuss potential links between lung cancer and COPD and the role of endothelium in the development of COPD. Finally, we propose a new approach for increasing the efficacy of CART therapy in SCLC.

Detection of circulating rare cells benefitted the diagnosis of malignant solitary pulmonary nodules

INTRODUCTION

Solitary pulmonary nodules (SPNs) are challenging in differentiating between benignancy and malignancy. Therefore, more effective non-invasive biomarkers are urgently needed. The purpose of this investigation was to examine whether circulating rare cells (CRCs) could facilitate the differentiation between benign and malignant SPNs as well as its sensitivity and specificity.

METHODS

164 patients diagnosed with SPNs, 24 healthy volunteers, and 25 patients diagnosed with advanced-stage lung cancer were included. CT/PET-CT images, serum tumor markers, and biopsy results were collected. The CRCs were examined using subtraction enrichment and immunostaining-fluorescence in situ hybridization (SE-iFISH) and their relationship with malignant or benign SPNs was analyzed.

RESULTS

The total CRC numbers from patients with malignant SPNs diagnosed by biopsy were significantly greater compared to those with benign SPNs (P < 0.0001), but not significantly different from patients with advanced lung cancer (P > 0.05). The total CRCs, with a cut-off value of 21.5 units, showed 67.6% sensitivity and 73.3% specificity [area under curve (AUC) 95% CI, 0.778 (0.666-0.889)] in discriminating benign and malignant SPNs and the triploid CRCs exhibited a high positive likelihood ratio of 8.4, which suggested that CRCs appeared to have a distinct advantage in discriminating benign and malignant SPNs compared to CT/PET-CT images and serum tumor markers and could be a potential screening indicator for lung cancer in the high-risk population.

CONCLUSIONS

SE-iFISH could effectively detect CRCs including circulating tumor cells (CTCs) and circulating tumor-derived endothelial cells (CTECs) and the detection of CRCs could benefit the differentiation of patients with benign and malignant SPNs.

Folate-Receptor Positive Circulating Tumor Cell Is a Potential Diagnostic Marker of Prostate Cancer

Folate-receptor positive circulating tumor cells (FR+CTCs) shows an important role in the diagnosis and dynamic monitoring for many solid tumors; however, the application of FR+CTCs in prostate cancer remains unclear. We explored the potential application of FR+CTCs in this retrospective study. The levels of FR+CTCs were detected in 30 prostate cancer patients and 7 bladder cancer patients in Peking University Cancer Hospital from August 2017 to August 2021. Clinical and pathology data were collected. One-way ANOVA was used to compare the difference in FR+CTCs levels in patients with prostate cancer, bladder cancer, and benign disease. The area under the receiver operating curve (AUROC) was used to compare the accuracy of FR+CTCs and tPSA in the diagnosis of prostate cancer. We found that levels of FR+CTCs were significantly higher in cancer patients (both prostate and bladder cancer) than in patients with benign urinary disease (p < 0.001). Besides, FR+CTCs level was consistently high in the prostate cancer patients with different tPSA levels (p < 0.001), and it was significantly higher in the patients with f/tPSA levels <0.16 than in those patients with f/tPSA levels >0.16 (12.20 ± 1.31 vs. 8.73 ± 0.92 FU/3 ml, p = 0.043). The diagnosis efficiency of FR+CTCs is better than the tPSA in prostate cancer patients with tPSA <10 ng/ml (0.871 vs. 0.857). In the prostate cancer patients with tPSA <10 ng/ml and f/tPSA <0.16, a combination of FR+CTCs and tPSA (AUROC, 0.934) further increased the diagnosis efficiency of each of these biomarkers alone (FR+CTCs, 0.912; tPSA, 0.857). Therefore, FR+CTCs could serve as an early diagnosis marker in the prostate cancer patients with uncertain tPSA levels.

[Advances in Clinical Application of Liquid Biopsy in Non-small Cell Lung Cancer]

Lung cancer, with the highest incidence in China, is the leading cause of death in cancer patients. Of these, about 85% are patients with non-small cell lung cancer (NSCLC). Therefore, the diagnosis and treatment of patients with lung cancer have always been a top priority nowadays. Fluid biopsy has many advantages, such as safety, convenience, repeatability, low trauma and so on, which are not available in traditional invasive biopsy. In recent years, with the rapid progress of molecular biological detection technology, fluid biopsy, as a new technology, has become the focus of attention. What's more, it contributes to the development of precision treatment and individualized treatment of lung cancer. Liquid biopsy mainly detects circulating tumor DNA (ctDNA), circulating tumor cells (CTCs) and exosomes in peripheral blood. We will make an introduce to the detection and clinical applications of ctDNA, CTCs and exocrine in this article, in order that it can provide insights into future clinical treatment for NSCLC.
.

New Advances in Liquid Biopsy Technologies for Anaplastic Lymphoma Kinase (ALK)-Positive Cancer

Cancer cells are characterized by high genetic instability, that favors tumor relapse. The identification of the genetic causes of relapse can direct next-line therapeutic choices. As tumor tissue rebiopsy at disease progression is not always feasible, noninvasive alternative methods are being explored. Liquid biopsy is emerging as a non-invasive, easy and repeatable tool to identify specific molecular alterations and monitor disease response during treatment. The dynamic follow-up provided by this analysis can provide useful predictive information and allow prompt therapeutic actions, tailored to the genetic profile of the recurring disease, several months before radiographic relapse. Oncogenic fusion genes are particularly suited for this type of analysis. Anaplastic Lymphoma Kinase (ALK) is the dominant driver oncogene in several tumors, including Anaplastic Large-Cell Lymphoma (ALCL), Non-Small Cell Lung Cancer (NSCLC) and others. Here we review recent findings in liquid biopsy technologies, including ctDNA, CTCs, exosomes, and other markers that can be investigated from plasma samples, in ALK-positive cancers.