Plasma Of Lung Cancer Patients Research Articles

Comparison of cell-free and small extracellular-vesicle-associated DNA by sequencing plasma of lung cancer patients

Blood contains multiple analytes that can be used as liquid biopsy to analyze cancer. Mutations have been detected in DNA associated with small extracellular vesicles (sEVs). The genome-wide composition and structure of sEV DNA remains poorly characterized, and whether sEVs are enriched in tumor signal compared to cell-free DNA (cfDNA) is unclear. Here, using whole-genome sequencing from lung cancer patients we determined that the tumor fraction and heterogeneity are comparable between DNA associated with sEV (<200nm) and matched plasma cfDNA. sEV DNA, obtained with size-exclusion chromatography, is composed of short ∼150-180bp fragments and long >1000bp fragments poor in tumor signal. The structural patterns of sEV DNA are related to plasma cfDNA. Mitochondrial DNA is relatively enriched in the sEV fractions. Our results suggest that DNA associated to sEV (including exosomes) is not preferentially enriched in tumor signal and is less abundant than cfDNA.

Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.Graphical 1. Integrating multiple biomarkers or trans-omics results improves diagnostic accuracy and reliability in heterogeneous lung cancer.2. Metabolomics and lipidomics, along with clinical phenotypes, construct a comprehensive metabolic profile of lung cancer patients.3. TAG expression shows strong positive correlation with polar metabolites, potentially impacting clinical phenotypic changes in lung cancer patients.

Circulating microbiome DNA as biomarkers for early diagnosis and recurrence of lung cancer

Lung cancer mortality is exacerbated by late-stage diagnosis. Emerging evidence indicates the potential clinical significance of distinct microbial signatures as diagnostic and prognostic biomarkers across various cancers. However, circulating microbiome DNA (cmDNA) profiles are underexplored in lung cancer (LC). Here, whole-genome sequencing is performed on plasma of LC patients and healthy controls (HCs). Differentially enriched microbial species are identified between LC and HC. A diagnostic model is developed, which has a high sensitivity of 87.7% and achieves an AUC of 93.2% in the independent validation dataset. Crucially, this model demonstrates the capability to detect early-stage LC, achieving a sensitivity of 86.5% for stage I and 87.1% for tumors <1cm. In addition, we construct a cmDNA model for recurrence, which precisely predicts LC recurrence after surgery. Overall, this study highlights the significant alterations of cmDNA profiles in LC, indicating its potential as biomarkers for early diagnosis and recurrence.

Abstract 1299: Cost-effectiveness analysis of circulating tumor DNA-based molecular profiling platforms for the detection of EGFR mutations in lung cancer

Abstract Background The detection of mutations in circulating tumor DNA (ctDNA) in blood plasma of lung cancer patients can be used to monitor the tumor-response to therapy and for the early detection of resistance mechanisms. In 2017, the Roche Cobas® EGFR Mutation Test v2 for the detection of the EGFR c.2369C&amp;gt;T p.(T790M) mutation in plasma-derived ctDNA was FDA-approved to identify patients eligible for osimertinib treatment. Today, different platforms are available for EGFR mutation testing in plasma-derived cell-free DNA (cfDNA). In this study we compared the clinical utility of five platforms for the detection of EGFR mutations in cfDNA offering insights into their operational costs, target coverage, hands-on-time and turn-around-time. Methods Four PCR-based platforms and one NGS-based approach for the detection of EGFR mutations were compared. Operational, maintenance, material and personnel costs were calculated for each platform and used as input variables for our recently developed ctDNA micro-costing framework (doi.org/10.1016/j.jmoldx.2022.10.004). This was compared to target coverage and turn-around-time of each platform in the context of therapy resistance. Results Per sample costs decreased for all platforms at maximal weekly throughput. The BioCartis Idylla™ demonstrated the shortest turn-around-time while the Roche Cobas® was the least expensive. Despite being the most expensive and time-consuming, the AVENIO ctDNA Expanded kit covered the most known resistance mechanisms to EGFR inhibitors, many of which are targetable with other TKIs. Conclusion EGFR ctDNA mutation analysis is only cost-effective when the throughput is high. This implies that centralization of cfDNA-testing is necessary to optimize cost-efficiency. With the advent of ctDNA analysis beyond EGFR in the context of targeted therapies for lung cancer, multigene detection assays will become more cost-effective with high throughput. Overview of results Platform Turn-around time at maximal weekly throughput Per sample cost at maximal weekly throughput Coverage of resistance mutations in EGFR 1Additional testing necessary Coverage of genome-wide resistance mutations to EGFR-TKI 1Additional testing necessary BioCartis Idylla™ ctEGFR Mutation Assay 2,5 hours €571 33% 12%1 Roche Cobas® EGFR Mutation Test v2 4 hours €497 33% 6% Bio-Rad QX200 droplet digital PCR (ddPCR) 7,5 hours €766 100%1 24%1 Agena MassARRAY® UltraSEEK® Lung Panel 2 days €613 53% 12% Roche AVENIO ctDNA Expanded kit 1 week €1551 100% 65% Citation Format: Pim Rozendal, Paul van der Leest, Elise M. van der Logt, Naomi Rifaela, Inge Platteel, Frank J. Scherpen, Harry J. Groen, Léon C. van Kempen, Ed M. Schuuring. Cost-effectiveness analysis of circulating tumor DNA-based molecular profiling platforms for the detection of EGFR mutations in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1299.

Abstract 7558: Novel liquid biopsy based determination of lung cancer histology using a comprehensive epigenomic platform reveals enhancer activity as a key determinant for accurate classification

Abstract BACKGROUND: Accurate molecular characterization of lung cancer including histology classification and therapeutic target profiling is critical for treatment planning and resistance monitoring. For example, detecting lineage transformation from lung adenocarcinoma (LUAD) to small cell lung carcinoma (SCLC) following treatment, an established resistance mechanism, is challenging due to deteriorating patient health and complicated invasive procedures. Here, we describe an accurate lung cancer histological classification using an innovative, multimodal epigenomic liquid biopsy method that comprehensively profiles tumor-specific transcription activation from 1 mL of patient plasma. METHODS: 37 LUAD, 34 SCLC patient plasma samples collected from commercial biobanks, and reference cell lines were profiled for enhancer, promoter and DNA methylation activity to identify epigenomic loci characteristic of LUAD and SCLC. The resulting map of select quantified loci was used as input to a machine learning algorithm that distinguishes SCLC from LUAD, in a cross validated training and testing approach. RESULTS: The epigenomic maps derived from lung cancer patient plasma were highly informative of the regulatory programming of the tumor cells. The enhancers and promoters most strongly linked to lung cancer profiles across the patient population include key, histology-specific driver genes such as NKX2-1, FOXA1, FOXA2, ONECUT2, DLL3, and ASCL1. The resulting classifier was able to accurately predict histology with a cross validated AUC greater than 0.94. In silico simulation results suggest that accurate classification can be achieved with ctDNA content below 1%. Further correlative examination of the SCLC enhancer landscape revealed a partitioning of SCLC patients into molecular subtypes characterized by active enhancer marks at subtype-specific transcripts, including ASCL1, POU2F3, NEUROD1, and YAP1. The transcriptional regulation of ADC targets is apparent through comprehensive epigenomic profiling of plasma in both SCLC and LUAD, with the expression of Claudin 18.2, SEZ6, and others showing a strong dynamic range independent of ctDNA levels. This represents a novel liquid biopsy approach to distinguish LUAD from SCLC and provide simultaneous insight into expression of key targets at clinically relevant ctDNA levels. CONCLUSION: These data demonstrate the feasibility of epigenomic mapping from 1mL of plasma in lung cancer patients to distinguish lung cancer histology. The resulting data is biologically interpretable through the lens of transcriptional activation of key histology specific genes. This liquid-biopsy based approach may provide a non-invasive alternative to invasive and challenging tissue biopsies for biomarker investigation and therapeutic decision making. Citation Format: Jamey Guess, Aparna Gorthi, Anthony D'ippolity, Jonathan Beagan, Travis Clark, Michael Coyne, Tyrone Tamakloe, Baovy Tran, Hyun-Hwan Jeong, Kristian Cibulskis, Hathairat Sawaengsri, Juliann Chmielecki, Corrie A. Painter, J Carl Barrett, Matthew Eaton. Novel liquid biopsy based determination of lung cancer histology using a comprehensive epigenomic platform reveals enhancer activity as a key determinant for accurate classification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7558.

Plasma exosomal miR-1290 and miR-29c-3p as diagnostic biomarkers for lung cancer

BackgroundEnhancing the diagnostic efficacy of early-stage lung cancer is crucial for improving prognosis. The objective of this study was to ascertain dependable exosomal miRNAs as biomarkers for the diagnosis of lung cancer. MethodsExosomal miRNA candidates were identified through miRNA sequencing and subsequently validated in various case-control sets using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). The correlation between the expression of exosomal miRNAs and the clinicopathological features of lung cancer was investigated. To assess the diagnostic efficacy of exosomal miRNAs for lung cancer, the receiver operating characteristic (ROC) curve analysis was conducted. The optimal cutoff value of exosomal miRNAs was determined in the testing cohort and subsequently confirmed in the validation cohort. ResultsThe results showed that the expression of exosomal miR-1290 was significantly elevated, while that of miR-29c-3p was significantly decreased in the plasma of lung cancer patients, especially in those with early-stage lung cancer, compared to individuals with benign lung conditions (P < 0.01). Exosomal miR-1290 and miR-29c-3p demonstrated superior diagnostic efficacy compared to conventional tumor biomarkers in distinguishing between lung cancer and benign lung diseases, as evidenced by their respective area under the curve (AUC) values of 0.934 and 0.868. Furthermore, exosomal miR-1290 and miR-29c-3p exhibited higher diagnostic efficiency in early-stage lung cancer than traditional tumor markers, with AUC values of 0.947 and 0.895, respectively. Notably, both exosomal miR-1290 and miR-29c-3p displayed substantial discriminatory capacity in distinguishing between non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as indicated by their respective AUC values of 0.810 and 0.842. ConclusionsThe findings of this study provided evidence that exosomal miR-1290 and miR-29c-3p hold significant potential as biomarkers for the early detection of lung cancer, as well as for differentiating between NSCLC and SCLC.

TIMP1 is an early biomarker for detection and prognosis of lung cancer.

Lung cancer remains the major cause of cancer-related deaths worldwide. Early stages of lung cancer are characterized by long asymptomatic periods that are ineffectively identified with the current screening programs. This deficiency represents a lost opportunity to improve the overall survival of patients. Serum biomarkers are among the most effective strategies for cancer screening and follow up. Using bead-based multiplexing assays we screened plasma and tumours of the KrasG12D/+; Lkb1f/f (KL) mouse model of lung cancer for cytokines that could be used as biomarkers. We identified tissue inhibitor of metalloproteinase 1 (TIMP1) as an early biomarker and validated this finding in the plasma of lung cancer patients. We used immunohistochemistry (IHC), previously published single-cell RNA-seq and bulk RNA-seq data to assess the source and expression of TIMP1in the tumour. The prognostic value of TIMP1 was assessed using publicly available human proteomic and transcriptomic databases. We found that TIMP1 is a tumour-secreted protein with high sensitivity and specificity for aggressive cancer, even at early stages in mice. We showed that TIMP1 levels in the tumour and serum correlate with tumour burden and worse survival in mice. We validated this finding using clinical samples from our institution and publicly available human proteomic and transcriptomic databases. These data support the finding that high tumour expression of TIMP1 correlates with an unfavorable prognosis in lung cancer patients. TIMP1 is a suitable biomarker for lung cancer detection.

Epitomics: Analysis of Plasma C9 Epitope Heterogeneity in the Plasma of Lung Cancer Patients and Control Subjects.

The human proteome is more complex than the genetic code predicts it to be. Epitomics, or protein epitome profiling, is a tool for understanding sub-protein level variation. With the ultimate goal to explore C9 proteoforms and their relevance to lung cancer, here we report plasma C9 epitope-associated molecular heterogeneity in plasma samples of lung cancer patients and control subjects. We show three C9 epitopes (BSI0449, BSI0581, BSI0639) with markedly different association with lung cancer ("unaltered", "upregulated" and "downregulated"). In order to exclude confounding effects, we show first that the three epitope-defining mAbs recognize C9 in purified form and in the natural context, in the human plasma. Then, we present data demonstrating the lack of major epitope interdependence or overlap. The next experiments represent a quest toward the understanding of the molecular basis of apparent disparate association with lung cancer. Using immunochemistry, SDS PAGE and LC-MS/MS technologies, we demonstrate that epitope-specific immunoprecipitates of plasma C9 seem identical regarding peptide sequence. However, we found epitope-specific posttranslational modification and coprecipitated protein composition differences with respect to control and lung cancer plasma. Epitope profiling enabled the classification of hypothetical C9 proteoforms through differential association with lung cancer.

Cell-free plasma miRNAs analysis for low invasive lung cancer diagnostics

Introduction. The high mortality rate in patients with lung cancer (LC) is due to the lack of highly sensitive diagnostic markers of this disease. Genetic and epigenetic alterations in tumor cells, for example, aberrant microRNA expression, can be proposed. It is known that extracellular/circulating microRNA of biological fluids, in complexes with proteins, or packaged in extracellular vesicles is of interest for the diagnosis of tumor diseases.Aim. To perform a comparative analysis of miRNA expression in plasma and plasma extracellular vesicles of LC patients and healthy donors. Based on the obtained results, to propose a diagnostic panel to identify patients with LC.Materials and methods. Blood plasma was obtained from blood samples of healthy donors and LC patients by sequential centrifugation. Then, a fraction of extracellular vesicles (40–150 nm in size) was isolated from a part of the obtained plasma supernatant by the method of aggregation-precipitation with polyethylene glycol/blue dextran. MicroRNAs were isolated from both blood plasma fractions of patients and healthy donors using guanidine isothiocyanate and octanoic acid. Expression of 17 miRNAs most characteristic for the development of LC according to our and literature data in the above-mentioned blood plasma fractions was analyzed by stem-loop reverse transcription polymerase chain reaction.Results. 29 and 10 miRNA pairs were differentially expressed in plasma extracellular vesicles and plasma of lung cancer patients and donors. Thus, plasma extracellular vesicles are characterized by greater potential as a source for miRNA based lung cancer diagnostic panels in comparison with blood plasma. Diagnostic algorithm based on aberrant miRNA expression of 8 different miRNAs (miRNA-30e, -1, -125b, -133, -222, -374, -425, -660) composed in 6 pairs was designed. This algorithm allows to diagnose 100 % of patients with lung cancer stages II–IV.Conclusion. Extracellular plasma vesicles represent a promising source of diagnostically significant microRNAs compared to plasma microRNAs. For the diagnosis of patients with non-small cell lung cancer with 100 % sensitivity and specificity, a panel of 8 microRNAs (6 miRNA pairs) was proposed.

Longitudinal tracking of ALK-positive lung cancer from plasma using circulating-tumor RNA and circulating-tumor DNA in the BRIGHTSTAR clinical trial.

e21072 Background: While the administration of specific tyrosine-kinase inhibitors (TKIs) in ALK-fusion positive lung cancer has led to significant improvement in clinical outcomes, detection of gene fusions remains challenging, especially from liquid biopsies. In tissue biopsies, assays which incorporate RNA-based detection have demonstrated increased sensitivity for gene fusion detection. We therefore hypothesized that a liquid biopsy assay equally including assessment of gene fusions using circulating-tumor RNA (ctRNA) in addition to circulating-tumor DNA (ctDNA), will improve detection. Furthermore, we hypothesized that detection of gene fusions as well as mutations will also correlate with clinical treatment. Methods: We retrospectively analyzed 89 samples from 35 patients included in the BRIGHTSTAR clinical trial assessing local consolidative therapy (LCT) and brigatinib in patients with stage IV or recurrent Non-small Cell Lung Cancer and confirmed ALK rearrangement (NCT03707938). Samples were included at baseline (N = 31), prior to LCT after 8 weeks of brigatinib treatment (N = 29), after LCT ( &lt; 3 weeks; N = 25) and at progression (N = 4). We used a targeted next generation sequencing (NGS) assay assessing both ctDNA as well as ctRNA (LiquidHALLMARK, Lucence Health, Palo Alto) to detect ALK fusions as well as mutations in 80 genes. Up to 5 ml of plasma was analyzed per sample. Results: At baseline, ALK fusions were detected in 15/31 patients (48%) of which 8 were detected using both ctDNA and ctRNA, while four were exclusively detected in ctDNA and three in ctRNA. Plasma ctDNA concentrations for patients with detectable ALK fusions at baseline were significantly higher than for those without detectable gene fusions (mean 26.1 ng/mL versus 16.6 ng/mL; p = 0.0044). ALK fusions were detected in two patients pre-LCT, exclusively in ctRNA, while ALK fusions cleared completely post-LCT. At progression, ALK fusions were detected in 2/4 samples (50%) in both ctDNA and ctRNA. Of the two negative samples tissue biopsies were available confirming the absence of an ALK rearrangement, including one transformation to squamous cell carcinoma. Overall, including analysis of ctRNA led to a 36% relative additional detection of ALK fusions compared to analyzing ctDNA alone. Furthermore, ctDNA mutation positivity in genes other than ALK was 17/31 (55%), 9/29 (31%), 8/25 (32%) and 3/4 (75%) for baseline, pre-LCT, post-LCT and progression, respectively. Conclusions: We highlight that ALK fusions can be reliably detected in plasma of lung cancer patients and detectability of ALK fusions correlate with exposure to treatment. Analyzing ctRNA in addition to ctDNA improves sensitivity of fusion detection and is a highly promising strategy in this setting.

Porous PDMS‐Based Microsystem (ExoSponge) for Rapid Cost‐Effective Tumor Extracellular Vesicle Isolation and Mass Spectrometry‐Based Metabolic Biomarker Screening

AbstractPolydimethylsiloxane (PDMS) is an inexpensive robust polymer that is commonly used as the fundamental fabrication material for soft‐lithography‐based microfluidic devices. Owing to its versatile material properties, there are some attempts to use PDMS as a porous 3D structure for sensing. However, reliable and easy fabrication has been challenging along with the inherent hydrophobic nature of PDMS hindering its use in biomedical sensing applications. Herein, a cleanroom‐free inexpensive method to create 3D porous PDMS structures, “ExoSponge” and the effective surface modification to functionalize its 3D porous structure is reported. The ability of ExoSponge to recover cancer‐associated extracellular vesicles (EVs) from complex biological samples of up to 10 mL in volume is demonstrated. When compared to ultracentrifugation, the ExoSponge showes a significant increase in cancer EV isolation of more than 210%. Targeted ultra‐high pressure liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) is further employed to profile 70 metabolites in the EVs recovered from the lung cancer patient's plasma. The resulting profiles reveal the potential intraexosomal metabolite biomarker, phenylacetylglutamine (PAG), in non‐small cell lung cancer. The high sensitivity, simple usage, and cost‐effectiveness of the ExoSponge platform creates huge potential for rapid, economical and yet specific isolation of exosomes enabling future diagnostic applications of EVs in cancers.

A direct and multiplex digital PCR chip for EGFR mutation

Digital PCR is a sensitive detection method, which has important applicability in liquid biopsy through the measurement of ctDNA. However, the current sample pre-processing of ctDNA and the multiplex detection capability of digital PCR have limitations. In view of the above two aspects, we developed a digital PCR chip with multiplex capability and established a direct amplification detection method without nucleic acid extraction. Through the design and processing of the chip, we established a self-priming multiplex digital PCR chip, which can detect 4 targets using single fluorescence. This method can be applied to most digital PCR chips. In addition, we used the plasma of lung cancer patients to establish a direct digital PCR detection method based on the chip, thereby avoiding disadvantages caused by the ctDNA extraction process. As a proof of concept, we prepared blood plasma samples with different concentration of ctDNA to prove the chip's multiplex detection capabilities and the results suggested that this multiplex digital PCR is accurate. Overall, our platform provides a novel and promising option for the detection of ctDNA.

Plasma CXCL14 as a Candidate Biomarker for the Diagnosis of Lung Cancer.

BackgroundEffective biomarkers for early diagnosis of lung cancer are needed. Previous studies have indicated positive associations between abnormal circulating cytokines and the etiology of lung cancer.MethodsBlood samples were obtained from 286 patients with pretreatment lung cancer and 80 healthy volunteers. Circulating cytokine levels were detected with a Luminex assay and enzyme-linked immunosorbent assay (ELISA). Urine samples were obtained from 284 patients and 122 healthy volunteers. CXC chemokine ligand 14 (CXCL14) expression in tumors and nontumor regions of lung tissues from 133 lung cancer cases was detected by immunohistochemical (IHC) staining and immunofluorescence (IF) staining of formalin fixed paraffin-embedded (FFPE) tissues.ResultsCompared with healthy volunteers, a 65.7-fold increase was observed in the level of CXCL14 in the plasma of lung cancer patients, and a 1.7-fold increase was observed in the level of CXCL14 in the urine of lung cancer patients, achieving a 0.9464 AUC (area under the curve) value and a 0.6476 AUC value for differentiating between lung cancer patients and healthy volunteers, respectively. Stromal CXCL14 expression was significantly associated with advanced pathologic stage (P<0.001), pathologic N stage (P<0.001), and recurrence and metastasis (P=0.014). Moreover, multivariate analysis suggested stromal CXCL14 expression as an independent predictor of DFS and OS.ConclusionsOur study demonstrates that CXCL14 might serve as a potential diagnostic and prognostic biomarker in patients with lung cancer.ImpactCXCL14 might serve as a potential diagnostic and prognostic biomarker in patients with lung cancer.

Methods for Collection of Extracellular Vesicles and Their Content RNA as Liquid Biopsy for Lung Cancer Detection: Application of Differential Centrifugation and Annexin A5 Coated Beads.

Extracellular vesicles (EVs) contain abundant extracellular RNA (exRNA), which can be a valuable source of liquid biopsy. However, as various RNA species exist in different types of EVs, lack of detailed characterization of these RNA species and efficient collection methods limits the clinical application of exRNA. In the present study, we measured two mRNAs, CK19 and PCTK1; one lncRNA, MALAT1; and two miRNAs, miR21 and miR155, in different EV fractions separated by differential centrifugation or captured by magnetic beads coated with annexin A5 (ANX beads). The results showed that in a cultured medium, the majority of mRNA and lncRNA exist in larger EVs, whereas miRNA exist in both large and small EVs from the differential centrifugation fractions. All these RNA species exist in ANX beads captured EVs. We then used ANX beads to capture EVs in plasma samples from non-small-cell lung cancer patients and age-matched healthy volunteers. We found that the ANX bead capturing could efficiently improve RNA detection from human plasma, compared with direct extraction of RNA from plasma. Using ANX-bead capturing and reverse transcription and quantitative PCR, we detected significantly higher levels of CK19 mRNA, MALAT1 lncRNA, and miR155 miRNA in the plasma of lung cancer patients. These facts suggested the collection methods strongly affect the results of exRNA measurement from EVs, and that ANX beads can be a useful tool for detecting exRNA from plasma samples in clinical application.

Detection of leucine-rich alpha-2-glycoprotein 1 containing immunocomplexes in the plasma of lung cancer patients with epitope-specific mAbs.

Lung cancer is the leading cause of cancer-related deaths worldwide. With the expectation of improved survival, tremendous efforts and resources have been invested in the discovery of specific biomarkers for early detection of the disease. Several investigators have reported the presence of cancer-associated autoantibodies in the plasma or serum of lung cancer patients. Previously, we used a monoclonal antibody (mAb) proteomics technology platform for the discovery of novel lung cancer-associated proteins. The identification of specific protein epitopes associated with various cancers is a promising method in biomarker discovery. Here, in a preliminary study, we aimed to detect autoantibody-leucine-rich alpha-2-glycoprotein 1 (LRG1) immunocomplexes using epitope-specific monoclonal antibodies (mAbs). We performed sandwich ELISA assays using the LRG1 epitope-specific capture mAbs, Bsi0352 and Bsi0392, and an IgG-specific polyclonal antibody coupled to a reporter system as the detection reagent. We tested the plasma of lung cancer patients and apparently healthy controls. Depending on the epitope specificity of the capture mAb, we were either unable to distinguish the control from LC-groups or showed a higher level of LRG1 and IgG autoantibody containing immunocomplexes in the plasma of non-small cell lung cancer and small cell lung cancer subgroups of lung cancer patients than in the plasma of control subjects. Our findings underline the importance of protein epitope-specific antibody targeted approaches in biomarker research, as this may increase the accuracy of previously described tests, which will need further validation in large clinical cohorts.

Integrative Analyses of Circulating mRNA and lncRNA Expression Profile in Plasma of Lung Cancer Patients

Circulating-free RNAs (cfRNAs) have been regarded as potential biomarkers for “liquid biopsy” in cancers. However, the circulating messenger RNA (mRNA) and long noncoding RNA (lncRNA) profiles of lung cancer have not been fully characterized. In this study, we profiled circulating mRNA and lncRNA profiles of 16 lung cancer patients and 4 patients with benign pulmonary nodules. Compared with benign pulmonary nodules, 806 mRNAs and 1,762 lncRNAs were differentially expressed in plasma of lung adenocarcinoma patients. For lung squamous cell carcinomas, 256 mRNAs and 946 lncRNAs were differentially expressed. A total of 231 mRNAs and 298 lncRNAs were differentially expressed in small cell lung cancer. Eleven mRNAs, 51 lncRNAs, and 207 canonical pathways were differentially expressed in lung cancer in total. Forty-five blood samples were collected to verify our findings via performing qPCR. There are plenty of meaningful mRNAs and lncRNAs that were found. MYC, a transcription regulator associated with the stemness of cancer cells, is overexpressed in lung adenocarcinoma. Transforming growth factor beta (TGFB1), which plays pleiotropic roles in cancer progression, was found to be upregulated in lung squamous carcinoma. MALAT1, a well-known oncogenic lncRNA, was also found to be upregulated in lung squamous carcinoma. Thus, this study provided a systematic resource of mRNA and lncRNA expression profiles in lung cancer plasma.

Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition.

The proteins of extracellular vesicles (EVs) that originate from tumors reflect the producer cells’ proteomes and can be detected in biological fluids. Thus, EVs provide proteomic signatures that are of great interest for screening and predictive cancer diagnostics. By applying targeted mass spectrometry with stable isotope-labeled peptide standards, we assessed the levels of 28 EV-associated proteins, including the conventional exosome markers CD9, CD63, CD81, CD82, and HSPA8, in vesicles derived from the lung cancer cell lines NCI-H23 and A549. Furthermore, we evaluated the detectability of these proteins and their abundance in plasma samples from 34 lung cancer patients and 23 healthy volunteers. The abundance of TLN1, TUBA4A, HSPA8, ITGB3, TSG101, and PACSIN2 in the plasma of lung cancer patients was measured using targeted mass spectrometry and compared to that in plasma from healthy volunteers. The most diagnostically potent markers were TLN1 (AUC, 0.95), TUBA4A (AUC, 0.91), and HSPA8 (AUC, 0.88). The obtained EV proteomic signature allowed us to distinguish between the lung adenocarcinoma and squamous cell carcinoma histological types. The proteomic cargo of the extracellular vesicles represents a promising source of potential biomarkers.

MicroRNA-550a-3-5p controls the brain metastasis of lung cancer by directly targeting YAP1

BackgroundThis study aimed to explore the potential regulatory mechanisms of brain metastasis and to identify novel underlying targets of lung cancer with brain metastasis.MethodsExosomes were isolated from the plasma of lung cancer patients with or without brain metastasis and low or high metastatic lung cancer cells, and small RNA from plasma-derived exosomes were sequenced. Differentially expressed miRNAs (DE-miRNAs) were identified. Human brain microvascular endothelial cells (HBMECs) were transfected with miR-550a-3-5p mimics or inhibitors and exosomes. Cell viability, migration, and apoptosis/cycle were determined using Cell Counting Kit-8 (CCK-8), Transwell, and flow cytometry, respectively. Western blotting was used to measure the expression of the associated proteins. Finally, a dual-luciferase reporter gene assay was performed to confirm the miR-550a-3-5p target.ResultsTransmission electron microscopy, NanoSight, and western blotting showed that exosomes were successfully isolated and cell-derived exosomes could be taken up by HBMECs. Sequencing identified 22 DE-miRNAs which were enriched in the MAPK, chemokine, PPAR, and Wnt signaling pathways. MiR-550a-3-5p was significantly enriched in brain metastatic exosomes. Cellular experiments showed that miR-550a-3-5p and exosome enrichment significantly inhibited cell viability and migration, promoted apoptosis, and regulated the cell cycle of HBMECs compared with the controls (P < 0.05). Compared with the controls, high levels of both miR-550a-3-5p and exosomes markedly upregulated cleaved-PARP expression, but downregulated the expression of pRB, CDK6, YAP1, CTGF, and CYR61 (P < 0.05). Finally, YAP1 was confirmed to bind directly to miR-550a-3-5p.ConclusionOur results indicate that miR-550a-3-5p and YAP1 may be novel potential targets for controlling brain metastasis.

Increased microRNA-30a levels in bronchoalveolar lavage fluid as a diagnostic biomarker for lung cancer.

BackgroundMicroRNA-30a (miRNA-30a) levels have been shown to increase in the plasma of lung cancer patients. Herein, we evaluated the miRNA-30a levels in the bronchoalveolar lavage fluid (BALF) of lung cancer patients as a potential biomarker for lung cancer diagnosis.MethodsBALF miRNA-30a expression of 174 subjects was quantified using quantitative real-time reverse transcription-polymerase chain reaction and compared between lung cancer patients and control patients with benign lung diseases. Moreover, its diagnostic value was evaluated by performing receiver operating characteristic (ROC) curve analysis.ResultsThe relative BALF miRNA-30a expression was significantly higher in the lung cancer patients than in the controls (0.74 ± 0.55 versus 0.07 ± 0.48, respectively, p < 0.001) as well as in lung cancer patients with stage I–IIA disease than in those with stage IIB–IV disease (0.98 ± 0.64 versus 0.66 ± 0.54, respectively, p < 0.05). Additionally, miRNA-30a distinguished benign lung diseases from lung cancers, with an area under the ROC curve (AUC) of 0.822. ROC analysis also revealed an AUC of 0.875 for the Youden index-based optimal cut-off points for stage I–IIA adenocarcinoma. Thus, increased miRNA-30a levels in BALF may be a useful biomarker for non-small-cell lung cancer diagnosis.

Plasma biopsy by Tag-sequencing: an acceptable alternative to tumor tissue profiling in non-small-cell lung cancer.

Tag-sequencing is amodified next-generation sequencing (NGS) approach wherein targeted regions are tagged with unique molecular identifiers enabling error-free detection ofrare genomic alterations. We aimed to perform this high- fidelity sequencing to identify actionable variants from theplasma oflung cancer patients. Targeted sequencing was performed from plasma-derived cell-free nucleic acid in twenty-one advanced, treatment naïve, non-small-cell lung cancer (NSCLC) patients. Clinically significant genetic alterations were compared with matched tumor NGS profile for each patient (patient-level), and separately for each alteration (variant-level). Cross-platform validation was done for EGFR and KRAS mutations (real-time PCR) and ALK1 rearrangement (immunohistochemistry). Forty-seven alterations (26 in plasma and 21 in tumor tissue) were detected in 19/21 tested cases. Overall-concordance between thetwo assays was 94.87% (κ of0.71, 95% CI: 0.54-0.89). Patient-level and genic-concordance was 57.1% (12/21 cases) and 67.86%, respectively. Almost perfect agreement was reached for detecting actionable EGFR mutations and ALK1 rearrangement (κ of0.89 and κ of1, respectively), which was confirmed by single-gene testing. Substantial agreement between theassays makes Tag-sequencing aviable option for identifying multibiomarkers from theplasma ofadvanced NSCLC patients in special circumstances where tissue has depleted/tumor is inaccessible/high risk ofbiopsy due to existing comorbidities.