Liquid biopsy for early stage lung cancer

Highly consistency of PIK3CA mutation spectrum between circulating tumor DNA and paired tissue in lung cancer patients

Background

Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha ( PIK3CA) mutations are associated with drug resistance and prognosis in lung cancer; however, the consistency and clinical value of PIK3CA mutations between tissue and liquid samples are unknown.

Methods

Circulating tumor DNA (ctDNA) and matched tumor tissue samples from 405 advanced lung cancer patients were collected at Jilin Cancer Hospital between 2018 and 2022, and the PIK3CA mutation status was sequenced using next-generation sequencing based on a 520 gene panel. The viability of different mutant lung cancer cells was detected using MTT assay.

Results

PIK3CA mutations were detected in 46 (5.68 %) of 810 lung cancer samples, with 21 (5.19 %) of 405 plasma samples and 25 (6.17 %) of 405 matched tissues. p.Glu542Lys, p.Glu545Lys, and p.His1047Arg were the most common mutation types of PIK3CA in both the ctDNA and tissue samples. The concordance of PIK3CA mutations was 97.53 % between ctDNA and matched tissues (kappa: 0.770, P = 0.000), with sensitivity/true positive rate of 72.0 %, specificity/true negative rate of 99.2 %, and negative predictive value and positive predictive value of 0.982 and 0.857, respectively (AUC = 0.856, P = 0.000). Furthermore, the concordance of PIK3CA mutations was 98.26 % in lung adenocarcinoma and 96.43 % in lung squamous cell carcinoma. TP53 and EGFR were the most common concomitant mutations in ctDNA and tissues. Patients with PIK3CA mutations showed a high tumor mutational burden (TMB) (P < 0.001) and a significant correlation between bTMB and tTMB (r = 0.5986, P = 0.0041). For the tPIK3CAmut/ctDNA PIK3CAmut cohort, PI3K pathways alteration was associated with male sex (P = 0.022), old age (P = 0.007), and smoking (P = 0.001); tPIK3CAmut/ctDNA PIK3CAwt patients harbored clinicopathological factors of adenocarcinoma stage IV, with low PS score (≤1) and TMB.

Conclusion

This study showed that ctDNA is highly concordant and sensitive for identifying PIK3CA mutations, suggesting that PIK3CA mutation detection in liquid samples may be an alternative clinical practice for tissues.

Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously by SERS since the Raman signals of exosomes detected by conventional colloidal nanocrystals or two-dimensional SERS substrates are incomplete and complex. Herein, we develop a novel three-dimensional (3D) surround-enhancing SERS platform, named 3D se-SERS, for the multiplex detection of exosomal proteins. In this 3D se-SERS, proteins and exosomes are covered with "hotspots" generated by the gold nanoparticles, which surround the analytes densely and three-dimensionally, providing sensitive and comprehensive SERS signals. Combining this 3D se-SERS with a deep learning model, we successfully quantitatively profiled seven proteins including CD63, CD81, CD9, CD151, CD171, TSPAN8, and PD-L1 on the surface of plasma exosomes from patients, which can predict the occurrence and advancement of lung cancer. This 3D se-SERS integrating deep learning technique benefits from high sensitivity and significant multiplexing ability for comprehensive analysis of proteins and exosomes, demonstrating the potential of deep learning-driven 3D se-SERS technology for plasma exosome-based early cancer diagnosis.

Liquid biopsy for early detection of lung cancer

Lung cancer is the leading cause of cancer-related mortality worldwide. Early cancer detection plays an important role in improving treatment success and patient prognosis. In the past decade, liquid biopsy became an important tool for cancer diagnosis, as well as for treatment selection and response monitoring. Liquid biopsy is a broad term that defines a non-invasive test done on a sample of blood or other body fluid to look for cancer cells or other analytes that can include DNA, RNA, or other molecules released by tumor cells. Liquid biopsies mainly include circulating tumor DNA, circulating RNA, microRNA, proteins, circulating tumor cells, exosomes, and tumor-educated platelets. This review summarizes the progress and clinical application potential of liquid biopsy for early detection of lung cancer.

miRNA as biomarker in lung cancer

Lung cancer has a high prevalence and mortality due to its late diagnosis and limited treatment, so it is essential to find biomarkers that allow a faster diagnosis and improve the survival of these patients. In this sense, biomarkers based on miRNAs have supposed a considerable advance. miRNAs, which are small RNA sequences, can regulate gene expression, so they play an essential role not only as a diagnostic biomarker but also as a therapeutic and prognostic one. Also, miRNA biomarkers can be obtained from liquid biopsies, which are less intrusive than lung biopsies, and have better accessibility, safety and repeatability, which allows using those biomarkers both for diagnosis and monitoring of patients. In this review, we highlight the importance of miRNAs and collect the existing evidence of their relationship with lung cancer.

International expert consensus on diagnosis and treatment of lung cancer complicated by chronic obstructive pulmonary disease

Background

Lung cancer combined by chronic obstructive pulmonary disease (LC-COPD) is a common comorbidity and their interaction with each other poses significant clinical challenges. However, there is a lack of well-established consensus on the diagnosis and treatment of LC-COPD.

Methods

A panel of experts, comprising specialists in oncology, respiratory medicine, radiology, interventional medicine, and thoracic surgery, was convened. The panel was presented with a comprehensive review of the current evidence pertaining to LC-COPD. After thorough discussions, the panel reached a consensus on 17 recommendations with over 70% agreement in voting to enhance the management of LC-COPD and optimize the care of these patients.

Results

The 17 statements focused on pathogenic mechanisms (n=2), general strategies (n=4), and clinical application in COPD (n=2) and lung cancer (n=9) were developed and modified. These statements provide guidance on early screening and treatment selection of LC-COPD, the interplay of lung cancer and COPD on treatment, and considerations during treatment. This consensus also emphasizes patient-centered and personalized treatment in the management of LC-COPD.

Conclusions

The consensus highlights the need for concurrent treatment for both lung cancer and COPD in LC-COPD patients, while being mindful of the mutual influence of the two conditions on treatment and monitoring for adverse reactions.

Early detection of lung cancer in a real-world cohort via tumor-associated immune autoantibody and imaging combination

Background

Efficient early detection methods for lung cancer can significantly decrease patient mortality. One promising approach is the use of tumor-associated autoantibodies (TAABs) as a diagnostic tool. In this study, the researchers aimed to evaluate the potential of seven TAABs in detecting lung cancer within a population undergoing routine health examinations. The results of this study could provide valuable insights into the utility of TAABs for lung cancer screening and diagnosis.

Methods

In this study, the serum concentrations of specific antibodies were measured using enzyme-linked immunosorbent assay (ELISA) in a cohort of 15,430 subjects. The efficacy of both a 7-TAAB panel and LDCT for lung cancer detection were evaluated through receiver operating characteristic (ROC) analyses, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) being assessed and compared. These results could have significant implications for the development of improved screening methods for lung cancer.

Results

Over the 12-month observation period, 26 individuals were diagnosed with lung cancer. The 7-TAAB panel demonstrated promising sensitivity (61.5%) and a high degree of specificity (88.5%). The panel’s area under the receiver operating characteristic (ROC) curve was 0.8062, which was superior to that of any individual TAAB. In stage I patients, the sensitivity of the panel was 50%. In our cohort, there was no gender or age bias observed. This 7-TAAB panel showed a sensitivity of approximately 60% in detecting lung cancer, regardless of histological subtype or lesion size. Notably, ground-glass nodules had a higher diagnostic rate than solid nodules (83.3% vs. 36.4%, P = 0.021). The ROC analyses further revealed that the combination of LDCT with the 7-TAAB assay exhibited a significantly superior diagnostic efficacy than LDCT alone.

Conclusion

In the context of the study, it was demonstrated that the 7-TAAB panel showed improved detective efficacy of LDCT, thus serving as an effective aid for the detection of lung cancer in real-world scenarios.

Value of contrast-enhanced magnetic resonance imaging-T2WI-based radiomic features in distinguishing lung adenocarcinoma from lung squamous cell carcinoma with solid components >8 mm

Background

Radiomics is one of the research frontiers in the field of imaging and has excellent diagnostic performance. However, there is a lack of magnetic resonance imaging (MRI)-based omics studies on identifying pathological subtypes of lung cancer. Here we explored the value of the contrast-enhanced MRI-T2-weighted imaging (T2WI)-based radiomic analysis in distinguishing adenocarcinoma (Ade) from squamous cell carcinoma (Squ) with solid components >8 mm.

Methods

A retrospective analysis was performed of a total of 71 lung cancer patients who undergoing contrast-enhanced MRI and computed tomography (CT) before treatment, and the nodules had solid components ≥8 mm in our center from January 2020 to September 2021. All enrolled patients were divided into Squ and Ade groups according to the pathological results. In addition, the two groups were randomly divided into training set and validation set in a ratio of about 7:3. Radiomics software was used to extract the relevant radiomic features. The least absolute shrinkage and selection operator (Lasso) was used to screen radiomic features that were most relevant to lung cancer subtypes, thus calculating the radiomic scores (Rad-score) and constructing the radiomic models. Multivariate logistic regression was used to combine relevant clinical features with Rad-score to form combined model nomograms. The receiver operating characteristic (ROC) curves. the area under the ROC curve (AUC), the decision curve analysis (DCA) and the DeLong's test were used to evaluate the clinical application potentials.

Results

The sensitivity and specificity of the clinical model based on smoking was 75.0% and 93.8%. The AUC of the constructed magnetic resonance (MR)-Rad model for differentiating the pathological subtypes of lung cancer was 0.8651 in the validation sets. The AUC of the CT-Rad model in the validation set were 0.9286. The combined model constructed by combining clinical features and Rad-score had AUC of 0.8016, for identifying the 2 pathological subtypes of lung cancer in the validation set. There was no significant difference in diagnostic performance between MR-Rad model and CT-Rad model (P>0.05).

Conclusions

The MR-Rad model has a diagnostic performance similar to that of CT-Rad model, while the diagnostic performance of the combined mode was better than the single MR model.

Increased levels of N6-methyladenosine in peripheral blood RNA: a perspective diagnostic biomarker and therapeutic target for non-small cell lung cancer

OBJECTIVES

Due to lack of effective biomarkers for non-small cell lung cancer (NSCLC), many patients are diagnosed at an advanced stage, which leads to poor prognosis. Dysregulation of N6-methyladenosine (m⁶A) RNA contributes significantly to tumorigenesis and tumor progression. However, the diagnostic value of m⁶A RNA status in peripheral blood to screen NSCLC remains unclear.

METHODS

Peripheral blood samples from 152 NSCLC patients and 64 normal controls (NCs) were applied to assess the m⁶A RNA levels. Bioinformatics and qRT-PCR analysis were performed to identify the specific immune cells in peripheral blood cells and investigate the mechanism of the alteration of m⁶A RNA levels.

RESULTS

Robust elevation of m⁶A RNA levels of peripheral blood cells was exhibited in the NSCLC group. Moreover, the m⁶A levels increased as NSCLC progressed, and reduced after treatment. The m⁶A levels contained area under the curve (AUC) was 0.912, which was remarkably greater than the AUCs for CEA (0.740), CA125 (0.743), SCC (0.654), and Cyfra21-1 (0.730). Furthermore, the combination of these traditional biomarkers with m⁶A levels elevated the AUC to 0.970. Further analysis established that the expression of m⁶A erasers FTO and ALKBH5 were both markedly reduced and negatively correlated with m⁶A levels in peripheral blood of NSCLC. Additionally, GEO database and flow cytometry analysis implied that FTO and ALKBH5 attributes to peripheral CD4⁺ T cells proportion and activated the immune functions of T cells.

CONCLUSIONS

These findings unraveled that m⁶A RNA of peripheral blood immune cells was a prospective biomarker for the diagnosis of NSCLC.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Combined measurement of circulating tumor cell counts and serum tumor marker levels enhances the screening efficiency for malignant versus benign pulmonary nodules

BACKGROUND

The high false-positive rate for pulmonary nodules (PNs) from using low-dose computed tomography (LDCT) screening can lead to overuse of invasive procedures, overtreatment, and patient anxiety. Therefore, it is very important to develop new diagnostic methods.

METHODS

A negative enrichment-fluorescence in situ hybridization (NE-FISH) approach was used to detect circulating tumor cells (CTCs) in patients with PNs. We evaluated whether or not the combination of CTC counts with serum tumor marker levels (CEA, CA 125, CYFRA 21-1, SCC) could improve the diagnostic ability for distinguishing patients with malignant pulmonary nodules (MPNs) from those with benign pulmonary nodules (BPNs). Moreover, the potential clinical application of this combination for the diagnosis of solitary pulmonary nodules (SPNs) with a diameter ≤2 cm was also investigated.

RESULTS

The combination of CTC counts and tumor marker levels had a sensitivity of 80.12% and the area under the receiver operating characteristics curve (AUC_ROC ) of 0.853 (95% confidence interval [CI]: 0.800-0.897, p < 0.001) for the differential diagnosis of PNs. For early cancer stages, the sensitivity was 75.38% (AUC_ROC  = 0.780, 95% CI: 0.713-0.838, p < 0.001). In addition, for SPNs within 2 cm the combination of CTC counts and tumor marker levels was still the most valuable diagnostic tool with a sensitivity of 78.95% and AUC_ROC of 0.888.

CONCLUSION

The combination of CTC counts and serum tumor marker levels is helpful for improving the diagnosis of PNs, especially in the early stages of cancer and for SPNs within 2 cm.

Rapid immunomagnetic co-capture assay for quantification of lung Cancer associated exosomes

Exosomes derived from biological fluids have the potential to serve as a biomarker for the early detection of various cancers. However, the lack of reliable enrichment and detection methods posed a challenge for its clinical utility. In this work, we designed a rapid co-capture-based approach for targeted enrichment and detection of lung cancer-derived exosomes from human plasma. This method relies on the formation of a sandwich complex around the exosomes that involves magnetic nanoparticles coupled to CD151 to assist in the immunomagnetic selection of lung-derived exosomes and a secondary detection antibody (CD81) coupled to horseradish peroxidase for signal amplification. The performance of the co-capture method to detect exosomes has been optimized with known exosome concentrations in human plasma and exhibited good linearity (10⁸-10⁵ exosomes mL^-1) with a detection limit of 60.4 exosomes μL^-1. This study further investigated the potential of the developed assay to differentiate healthy and lung cancer patients using 18 clinical samples by quantifying the CD151+/ CD81+ lung-derived exosomes. In conclusion, this study demonstrated a rapid co-capture-based approach that offers simultaneous isolation and detection of exosomes compatible with low sample volume for detecting lung cancer patients.

MicroRNAs as Predictors of Lung-Cancer Resistance and Sensitivity to Cisplatin

BACKGROUND

Platinum-based chemotherapy, cisplatin (DDP) specifically, is the main strategy for treating lung cancer (LC). However, currently, there is a lack of predictive drug-resistance markers, and there is increased interest in the development of a reliable and sensitive panels of markers for DDP chemotherapy-effectiveness prediction. MicroRNAs represent a perspective pool of markers for chemotherapy effectiveness.

OBJECTIVES

Data on miRNAs associated with LC DDP chemotherapy response are summarized and analyzed.

MATERIALS AND METHODS

A comprehensive review of the data in the literature and an analysis of bioinformatics resources were performed. The gene targets of miRNAs, as well as their reciprocal relationships with miRNAs, were studied using several databases.

RESULTS AND DISCUSSION

The complex analysis of bioinformatics resources and the literature indicated that the expressions of 12 miRNAs have a high predictive potential for LC DDP chemotherapy responses. The obtained information was discussed from the point of view of the main mechanisms of LC chemoresistance.

CONCLUSIONS

An overview of the published data and bioinformatics resources, with respect to the predictive microRNA markers of chemotherapy response, is presented in this review. The selected microRNAs and gene panel have a high potential for predicting LC DDP sensitiveness or DDP resistance as well as for the development of a DDP co-therapy.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

GCC2 as a New Early Diagnostic Biomarker for Non-Small Cell Lung Cancer

Simple Summary

Lung cancer, including non-small cell lung cancer, is the leading cause of cancer-related death worldwide. A better prognosis is associated with early diagnosis of lung cancer patients. Although annual screening guidelines for lung cancer are recommended, using various tools such as chest X-ray, low-dose computed tomography, and positron emission tomography, these screening procedures are expensive and difficult to repeat. They are also invasive and have a high risk of radiation exposure. Therefore, a low-risk, convenient diagnostic method using liquid biopsy and biomarkers is required for the early diagnosis of lung cancer. The newly proposed biomarker GCC2 was identified through proteomic analysis of exosomes secreted from lung cancer cell lines. GCC2 expression levels in peripheral blood of the patients showed high specificity and sensitivity in early lung cancer, demonstrating that our novel exosomal biomarker GCC2 can greatly contribute to improving the diagnosis of lung cancer patients, even though it has been tested in only a few pilot studies.

Abstract

No specific markers have been identified to detect non-small cell lung cancer (NSCLC) cell-derived exosomes circulating in the blood. Here, we report a new biomarker that distinguishes between cancer and non-cancer cell-derived exosomes. Exosomes isolated from patient plasmas at various pathological stages of NSCLC, NSCLC cell lines, and human pulmonary alveolar epithelial cells isolated using size exclusion chromatography were characterized. The GRIP and coiled-coil domain-containing 2 (GCC2) protein, involved in endosome-to-Golgi transport, was identified by proteomics analysis of NSCLC cell line-derived exosomes. GCC2 protein levels in the exosomes derived from early-stage NSCLC patients were higher than those from healthy controls. Receiver operating characteristic curve analysis revealed the diagnostic sensitivity and specificity of exosomal GCC2 to be 90% and 75%, respectively. A high area under the curve, 0.844, confirmed that GCC2 levels could effectively distinguish between the exosomes. These results demonstrate GCC2 as a promising early diagnostic biomarker for NSCLC.

Review: Multiplexed profiling of biomarkers in extracellular vesicles for cancer diagnosis and therapy monitoring

Extracellular vesicles (EVs) are nanoscale vesicles secreted by normal and pathological cells. The types and levels of surface proteins and internal nucleic acids in EVs are closely related to their original cells, tumor occurrence, and development. Thus, the sensitive and accurate detection of EV biomarkers is a reliable approach for noninvasive disease diagnosis and treatment response monitoring. However, the purification and molecular profiling of these EVs are technically challenging. Much effort has been dedicated to developing new methods for the detection of multiple EV biomarkers. In this review, we summarize the recent progress in EV protein and nucleic acid biomarker analysis. Additionally, we systematically discuss the advantages of multiplexed EV biomarker detection for accurate cancer diagnosis, therapy monitoring, and cancer screening. This article aims to present an overview of all kinds of analytical technologies for assessing EVs and their applications in clinical settings.

Consistency of genotyping data from simultaneously collected plasma circulating tumor DNA and tumor-DNA in lung cancer patients

Background

To clarify the rate of concordance between the results of concurrent sequencing of circulating tumor DNA (ctDNA) and tumor tissue samples based in clinic settings, and to explore potential factors influencing consistency.

Methods

A retrospective analysis of 27 patients with lung cancer who underwent gene sequencing at the Department of Biotherapy of Tianjin Medical University Cancer Hospital from February 2016 to April 2019, was conducted by synchronous sequencing of tumor and plasma DNA samples and the concordance of mutations in nine known driver genes was calculated.

Results

The overall concordance, sensitivity, and specificity for sequencing driver genes in plasma samples, were 85.2%, 87.0%, and 75%, respectively, relative to tumor samples. Concordance was 100% in patients with bone metastases, while the rate in those without bone metastases was 69.2%. Moreover, in patients where both the driver gene and TP53 mutations in plasma were detected, the findings of plasma sequencing of the driver gene were identical to those of tumor sequencing (concordance: 100%).

Conclusions

Overall, our data show that circulating tumor DNA (ctDNA) was able to identify 75% of the identical information in driver genes, with higher rates of concordance in lung cancer patients with bone metastases or TP53 mutation-positive plasma samples.

Can autoantibody tests enhance lung cancer screening?-an evaluation of EarlyCDT®-Lung in context of the German Lung Cancer Screening Intervention Trial (LUSI)

Background

Tumor-associated autoantibodies are considered promising markers for early lung cancer detection; so far, however, their capacity to detect cancer has been tested mostly in a clinical context, but not in population screening settings. This study evaluates the early detection accuracy, in terms of sensitivity and specificity, of EarlyCDT^®-Lung-a test panel of seven tumor-associated autoantibodies optimized for lung cancer detection-using blood samples originally collected as part of the German Lung Cancer Screening Intervention Trial.

Methods

The EarlyCDT^®-Lung test was performed for all participants with lung cancer detected via low-dose computed tomography and with available blood samples taken at detection, and for 180 retrospectively selected cancer-free participants at the end of follow-up: 90 randomly selected from among all cancer-free participants (baseline controls) and 90 randomly selected from among cancer-free participants with suspicious imaging findings (suspicious nodules controls). Sensitivity and specificity of lung cancer detection were estimated in the case group and the two control groups, respectively.

Results

In the case group, the test panel showed a sensitivity of only 13.0% (95% CI: 4.9-26.3%). Specificity was estimated at 88.9% (95% CI: 80.5-94.5%) in the baseline control group, and 91.1% (95% CI: 83.2-96.1%) among controls presenting CT-detected nodules.

Conclusions

The test panel showed insufficient sensitivity for detecting lung cancer at an equally early stage as with low-dose computed tomography screening.

Multiomics profiling of primary lung cancers and distant metastases reveals immunosuppression as a common characteristic of tumor cells with metastatic plasticity

BACKGROUND

Metastasis is the primary cause of cancer mortality accounting for 90% of cancer deaths. Our understanding of the molecular mechanisms driving metastasis is rudimentary.

RESULTS

We perform whole exome sequencing (WES), RNA sequencing, methylation microarray, and immunohistochemistry (IHC) on 8 pairs of non-small cell lung cancer (NSCLC) primary tumors and matched distant metastases. Furthermore, we analyze published WES data from 35 primary NSCLC and metastasis pairs, and transcriptomic data from 4 autopsy cases with metastatic NSCLC and one metastatic lung cancer mouse model. The majority of somatic mutations are shared between primary tumors and paired distant metastases although mutational signatures suggest different mutagenesis processes in play before and after metastatic spread. Subclonal analysis reveals evidence of monoclonal seeding in 41 of 42 patients. Pathway analysis of transcriptomic data reveals that downregulated pathways in metastases are mainly immune-related. Further deconvolution analysis reveals significantly lower infiltration of various immune cell types in metastases with the exception of CD4+ T cells and M2 macrophages. These results are in line with lower densities of immune cells and higher CD4/CD8 ratios in metastases shown by IHC. Analysis of transcriptomic data from autopsy cases and animal models confirms that immunosuppression is also present in extracranial metastases. Significantly higher somatic copy number aberration and allelic imbalance burdens are identified in metastases.

CONCLUSIONS

Metastasis is a molecularly late event, and immunosuppression driven by different molecular events, including somatic copy number aberration, may be a common characteristic of tumors with metastatic plasticity.

Detection of circulating genetically abnormal cells in peripheral blood for early diagnosis of non-small cell lung cancer

BACKGROUND

Circulating genetically abnormal cells (CACs) with specific chromosome variations have been confirmed to be present in non-small cell lung cancer (NSCLC). However, the diagnostic performance of CAC detection remains unclear. This study aimed to evaluate the potential clinical application of the CAC test for the early diagnosis of NSCLC.

METHODS

In this prospective study, a total of 339 participants (261 lung cancer patients and 78 healthy volunteers) were enrolled. An antigen-independent fluorescence in situ hybridization was used to enumerate the number of CACs in peripheral blood.

RESULTS

Patients with early-stage NSCLC were found to have a significantly higher number of CACs than those of healthy participants (1.34 vs. 0.19; P < 0.001). The CAC test displayed an area under the receiver operating characteristic (ROC) curve of 0.76139 for discriminating stage I NSCLC from healthy participants with 67.2% sensitivity and 80.8% specificity, respectively. Compared with serum tumor markers, the sensitivity of CAC assays for distinguishing early-stage NSCLC was higher (67.2% vs. 48.7%, P < 0.001), especially in NSCLC patients with small nodules (65.4% vs. 36.5%, P = 0.003) and ground-glass nodules (pure GGNs: 66.7% vs. 40.9%, P = 0.003; mixed GGNs: 73.0% vs. 43.2%, P < 0.001).

CONCLUSIONS

CAC detection in early stage NSCLC was feasible. Our study showed that CACs could be used as a promising noninvasive biomarker for the early diagnosis of NSCLC.

KEY POINTS

What this study adds: This study aimed to evaluate the potential clinical application of the CAC test for the early diagnosis of NSCLC. Significant findings of the study: CAC detection in early stage NSCLC was feasible. Our study showed that CACs could be used as a promising noninvasive biomarker for the early diagnosis of NSCLC.

Baseline Plasma EGFR Circulating Tumour DNA Levels in a Pilot Cohort of EGFR-Mutant Limited-Stage Lung Adenocarcinoma Patients Undergoing Radical Lung Radiotherapy

The use of circulating cell-free tumour DNA (ctDNA) is established in metastatic lung adenocarcinoma to detect and monitor sensitising EGFR mutations. In early-stage disease, there is very little data supporting its role as a potential biomarker. We report on a prospective cohort of 9 limited-stage EGFR mutant lung cancer patients who were treated with radical radiotherapy. We looked at baseline plasma EGFR ctDNA and noted the detection rates to be higher in locally advanced disease. At a median follow-up of 13.5 months, an association between a detectable pre-radiotherapy plasma EGFR ctDNA and early tumour relapse (155 days vs. NR, p = 0.004) was noted. One patient with persistent plasma EGFR ctDNA predated radiological progression. The role of ctDNA in early-stage lung cancer is developing. Plasma EGFR ctDNA could be a useful biomarker in lung cancer patients undergoing radical treatments for staging, prognostication, and follow-up. These preliminary findings should be explored in larger studies.

Early Detection of Non-Small Cell Lung Cancer by Using a 12-microRNA Panel and a Nomogram for Assistant Diagnosis

Background: We previously identified a 12-microRNA (miRNA) panel (miRNA-17, miRNA-146a, miRNA-200b, miRNA-182, miRNA-155, miRNA-221, miRNA-205, miRNA-126, miRNA-7, miRNA-21, miRNA-145, and miRNA-210) that aided in the early diagnosis of non-small cell lung cancer (NSCLC). We validated the diagnostic value of this miRNA panel and compared it with that of traditional tumor markers and radiological diagnosis. We constructed a nomogram based on the miRNA panel's results to predict the risk of NSCLC.

Methods: Eighty-two participants with pulmonary nodules on a CT scan and who underwent a pathological examination and surgical treatment were enrolled in our study. Patients were randomly divided into a training group or a validation group. The miRNA concentrations were quantified by RT-PCR and log-transformed for analysis. The cutoff value was determined in the training group and then applied in the validation group. A comparison between the miRNAs and traditional tumor markers [CEA, NSE, and cytokeratin 19 fragment 21-1 (Cyfra21-1)] and radiological diagnosis was performed. A nomogram based on the miRNA panel's results to predict the risk of NSCLC was constructed.

Results: The expression level of these 12 miRNAs was significantly higher in NSCLC patients than in benign patients. In the validation group, the specificity and positive predictive value were 96.4 and 95.8%, respectively, which were significantly higher than those using traditional tumor markers or radiological diagnosis. The sensitivity was 42.6%, which was also higher than that using tumor markers. Moreover, the sensitivity increased to 63.6% when the nodule diameters were larger than 2 cm. The miRNAs and seven clinical factors were integrated into the nomogram, and the calibration curves showed optimal agreement between the predicted and actual probabilities.

Conclusions: Our miRNA panel has clinical value for the early detection of NSCLC. A nomogram was constructed and internally validated, and the results indicate that it can assist clinicians in making treatment recommendations in the clinic.

Compared to plasma, bronchial washing fluid shows higher diagnostic yields for detecting EGFR-TKI sensitizing mutations by ddPCR in lung cancer

BACKGROUND

The rate of diagnosis of advanced lung adenocarcinoma must be improved. In this study, we compared the detection rates of EGFR-tyrosine kinase inhibitor-sensitizing mutations (mEGFRs) in bronchial washing fluid (BWF) and the plasma of patients with lung adenocarcinoma using the tissue genotype as the standard reference.

METHODS

Paired blood and BWF specimens were collected from 73 patients with lung cancer. The tumor EGFR mutation status was determined by genotyping of the plasma and BWF samples using droplet digital PCR (ddPCR).

RESULTS

The study cohort included 26, 10, 10, and 27 patients with stage I, II, III, and IV disease. Of the 73 cases, 35 had a wild-type EGFR, and 19 had the L858R substitution and exon 19 deletion mutations. The areas under the receiver operator characteristic curves for sensitivity vs. specificity of ddPCR were 0.895 [95% confidence interval (CI): 0.822-0.969] for BWF and 0.686 (95% CI: 0.592-0.780) for plasma (p < 0.001). The fractional abundance was higher in BWF of the mEGFR-positive cases than in the plasma (p = 0.004), facilitating easy threshold setting and discrimination between mEGFR-positive and negative cases. When genotyping results obtained using plasma and BWF were compared for early lung cancer (stages I-IIIA), the diagnostic yields were significantly higher for BWF ddPCR, and the same tendency was observed for the advanced stages, suggesting that the BWF data may reflect the genotype status in early-stage patients.

CONCLUSIONS

The mEGFR genotyping results obtained using BWF showed a higher diagnostic efficacy than did those obtained using the plasma. Thus, BWF-based genotyping may be a useful substitute for that using plasma in lung cancer.

Early-Stage Lung Cancer Diagnosis by Deep Learning-Based Spectroscopic Analysis of Circulating Exosomes

Lung cancer has a high mortality rate, but an early diagnosis can contribute to a favorable prognosis. A liquid biopsy that captures and detects tumor-related biomarkers in body fluids has great potential for early-stage diagnosis. Exosomes, nanosized extracellular vesicles found in blood, have been proposed as promising biomarkers for liquid biopsy. Here, we demonstrate an accurate diagnosis of early-stage lung cancer, using deep learning-based surface-enhanced Raman spectroscopy (SERS) of the exosomes. Our approach was to explore the features of cell exosomes through deep learning and figure out the similarity in human plasma exosomes, without learning insufficient human data. The deep learning model was trained with SERS signals of exosomes derived from normal and lung cancer cell lines and could classify them with an accuracy of 95%. In 43 patients, including stage I and II cancer patients, the deep learning model predicted that plasma exosomes of 90.7% patients had higher similarity to lung cancer cell exosomes than the average of the healthy controls. Such similarity was proportional to the progression of cancer. Notably, the model predicted lung cancer with an area under the curve (AUC) of 0.912 for the whole cohort and stage I patients with an AUC of 0.910. These results suggest the great potential of the combination of exosome analysis and deep learning as a method for early-stage liquid biopsy of lung cancer.

The diagnostic value of a seven-autoantibody panel and a nomogram with a scoring table for predicting the risk of non-small-cell lung cancer

The early detection of non-small-cell lung cancer (NSCLC) remains a common concern. The aim of our study was to validate the diagnostic value of a seven-autoantibody (7-AAB) panel compared with radiological diagnosis for NSCLC. We constructed a nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC. We prospectively enrolled 268 patients who presented with radiological lesions and underwent both the 7-AAB panel test and pathological diagnosis by surgical resection. A comparison between the 7-AAB panel and radiological diagnosis was performed. A nomogram and a scoring table based on the 7-AAB panel's result to predict the risk of NSCLC were constructed and internally validated. The 7-AAB panel test had a specificity of 90.2% and a positive predictive value (PPV) of 92.7%, which were significantly higher than those of the radiological diagnosis. The 7-AAB panel also showed a preferable sensitivity in patients with early-stage disease. Seven factors, including the 7-AAB panel results, were integrated into the nomogram. For more convenient application, we formulated a scoring table based on the nomogram. The area under the receiver operating characteristic curve was 0.840 and 0.860 in the training group and validation group, respectively, which was higher than that using the 7-AAB panel or radiological diagnosis alone. This study reveals that our 7-AAB panel has clinical value in the diagnosis of NSCLC. The utility of our nomogram and the scoring table indicated that they have the potential to assist clinicians in avoiding unnecessary treatment or needless follow-up.

Translational Application of Circulating DNA in Oncology: Review of the Last Decades Achievements

In recent years, the introduction of new molecular techniques in experimental and clinical settings has allowed researchers and clinicians to propose circulating-tumor DNA (ctDNA) analysis and liquid biopsy as novel promising strategies for the early diagnosis of cancer and for the definition of patients' prognosis. It was widely demonstrated that through the non-invasive analysis of ctDNA, it is possible to identify and characterize the mutational status of tumors while avoiding invasive diagnostic strategies. Although a number of studies on ctDNA in patients' samples significantly contributed to the improvement of oncology practice, some investigations generated conflicting data about the diagnostic and prognostic significance of ctDNA. Hence, to highlight the relevant achievements obtained so far in this field, a clearer description of the current methodologies used, as well as the obtained results, are strongly needed. On these bases, this review discusses the most relevant studies on ctDNA analysis in cancer, as well as the future directions and applications of liquid biopsy. In particular, special attention was paid to the early diagnosis of primary cancer, to the diagnosis of tumors with an unknown primary location, and finally to the prognosis of cancer patients. Furthermore, the current limitations of ctDNA-based approaches and possible strategies to overcome these limitations are presented.

Proceedings of the fourth international molecular pathological epidemiology (MPE) meeting

An important premise of epidemiology is that individuals with the same disease share similar underlying etiologies and clinical outcomes. In the past few decades, our knowledge of disease pathogenesis has improved, and disease classification systems have evolved to the point where no complex disease processes are considered homogenous. As a result, pathology and epidemiology have been integrated into the single, unified field of molecular pathological epidemiology (MPE). Advancing integrative molecular and population-level health sciences and addressing the unique research challenges specific to the field of MPE necessitates assembling experts in diverse fields, including epidemiology, pathology, biostatistics, computational biology, bioinformatics, genomics, immunology, and nutritional and environmental sciences. Integrating these seemingly divergent fields can lead to a greater understanding of pathogenic processes. The International MPE Meeting Series fosters discussion that addresses the specific research questions and challenges in this emerging field. The purpose of the meeting series is to: discuss novel methods to integrate pathology and epidemiology; discuss studies that provide pathogenic insights into population impact; and educate next-generation scientists. Herein, we share the proceedings of the Fourth International MPE Meeting, held in Boston, MA, USA, on 30 May-1 June, 2018. Major themes of this meeting included 'integrated genetic and molecular pathologic epidemiology', 'immunology-MPE', and 'novel disease phenotyping'. The key priority areas for future research identified by meeting attendees included integration of tumor immunology and cancer disparities into epidemiologic studies, further collaboration between computational and population-level scientists to gain new insight on exposure-disease associations, and future pooling projects of studies with comparable data.