Biomarker For Lung Cancer Research Articles

Utility of neutrophil-to-lymphocyte ratio as an indicator of tumor immune status in non-small cell lung cancer.

Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic biomarker in non-small cell lung cancer (NSCLC); however, the underlying biological rationale remains unclear. The present study aimed to explore the potential utility of NLR as a surrogate biomarker for immune response to cancer and to elucidate the underlying mechanism. This retrospective study included the medical records of 120 patients with NSCLC who underwent surgery at the study institution in 2012. NLR in peripheral blood was determined from blood test within 30days before surgery. Tumor immune status was evaluated using immunohistochemical staining to identify CD3+, CD8+ and FOXP3+ tumor-infiltrating lymphocytes (TILs), and the relationship of NLR, with clinicopathologic characteristics including 5-year overall survival (OS), and the tumor immune status was investigated. The median values of NLR and TIL count were used as cutoff points. The 5-year OS was significantly better in patients with low NLR (<2.2) than in those with high NLR (≥2.2) (70.1% vs. 56.8%, P=0.042) and in patients with high CD3+ TIL count (≥242) than in those with low CD3+ TIL count (<242) (70% vs. 56.8%, P=0.019). Additionally, the CD3+ TIL count was negatively correlated with preoperative NLR (P=0.005). NLR might potentially reflect the immune status of tumor microenvironment, explaining its impact on prognosis of patients with NSCLC.

Five years of advances in electrochemical analysis of protein biomarkers in lung cancer: a systematic review

Lung cancer is the leading cause of cancer death in both men and women. It represents a public health problem that must be addressed through the early detection of specific biomarkers and effective treatment. To address this critical issue, it is imperative to implement effective methodologies for specific biomarker detection of lung cancer in real clinical samples. Electrochemical methods, including microfluidic devices and biosensors, can obtain robust results that reduce time, cost, and assay complexity. This comprehensive review will explore specific studies, methodologies, and detection limits and contribute to the depth of the discussion, making it a valuable resource for researchers and clinicians interested in lung cancer diagnosis.

Strategy to Empower Nontargeted Metabolomics by Triple-Dimensional Combinatorial Derivatization with MS-TDF Software.

Chemical derivatization is a widely employed strategy in metabolomics to enhance metabolite coverage by improving chromatographic behavior and increasing the ionization rates in mass spectroscopy (MS). However, derivatization might complicate MS data, posing challenges for data mining due to the lack of a corresponding benchmark database. To address this issue, we developed a triple-dimensional combinatorial derivatization strategy for nontargeted metabolomics. This strategy utilizes three structurally similar derivatization reagents and is supported by MS-TDF software for accelerated data processing. Notably, simultaneous derivatization of specific metabolite functional groups in biological samples produced compounds with stable but distinct chromatographic retention times and mass numbers, facilitating discrimination by MS-TDF, an in-house MS data processing software. In this study, carbonyl analogues in human plasma were derivatized using a combination of three hydrazide-based derivatization reagents: 2-hydrazinopyridine, 2-hydrazino-5-methylpyridine, and 2-hydrazino-5-cyanopyridine (6-hydrazinonicotinonitrile). This approach was applied to identify potential carbonyl biomarkers in lung cancer. Analysis and validation of human plasma samples demonstrated that our strategy improved the recognition accuracy of metabolites and reduced the risk of false positives, providing a useful method for nontargeted metabolomics studies. The MATLAB code for MS-TDF is available on GitHub at https://github.com/CaixiaYuan/MS-TDF.

Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs.

Lung cancer is the leading cause of cancer-related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster, and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already been shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterized by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation to their metabolic pathways and in light of the altered cancer metabolism.

Human epididymal protein 4 and its combined detection show good diagnostic value in lung cancer: A retrospective study.

This study aimed to assess the diagnostic value of human epididymal protein 4 (HE4), a potential novel biomarker for lung cancer, and its combined detection with five other conventional biomarkers in lung cancer diagnosis and subtyping. In this retrospective study, 115 lung cancer patients, 50 patients with benign pulmonary disease, and 50 healthy controls were included. Serum HE4, progastrin-releasing peptide (ProGRP), squamous cell carcinoma (SCC) antigen, cytokeratin-19 fragment (CYFRA21-1), neuron-specific enolase (NSE), and carcinoembryonic antigen (CEA) were analyzed using the electrochemiluminescence immunoassay and chemiluminescence immunoassay. The receiver operating characteristic curve was performed to analyze the diagnostic efficacy of individual biomarkers in identifying both lung cancer and its histologic subtypes. All six biomarkers showed significantly elevated levels in the lung cancer group compared to both benign pulmonary disease and control groups (P < 0.05). Among the biomarkers evaluated, HE4 exhibited the highest diagnostic performance for lung cancer, lung adenocarcinoma, and lung squamous cell carcinoma with area under the curve (AUC) values of 0.921, 0.891, and 0.937, respectively. ProGRP was the optimal biomarker for small cell lung cancer with an AUC of 0.973. The combination of all six biomarkers yielded the largest AUCs in the diagnosis of lung cancer subtypes (0.937 for lung adenocarcinoma, 0.998 for lung squamous cell carcinoma, and 0.985 for small cell lung cancer). Furthermore, specific combinations, such as HE4 + CEA, HE4 + SCC, and ProGRP + HE4 + NSE, showed strong diagnostic performance in lung cancer. HE4 and its combined detection held substantial clinical significance in the diagnosis of lung cancer and its histologic subtyping, especially for lung adenocarcinoma and lung squamous cell carcinoma.

RACGAP1 promotes lung cancer cell proliferation through the PI3K/AKT signaling pathway

We aimed to investigate the expression and clinic significance of Rac GTPase Activating Protein 1 (RACGAP1) in human lung adenocarcinoma (LUAD). Online database analysis revealed a significant increase in RACGAP1 mRNA expression among 26 types of tumor tissues, including LUAD tissues. Online database and tissue microarray analyses indicated that RACGAP1 expression was significantly upregulated in LUAD tissues. Genetic variation analysis identified four different genetic variations of RACGAPs in LUAD. Moreover, online database analysis showed that RACGAP1 upregulation was correlated with shorter survival in patients with LUAD. After silencing RACGAP1 expression in A549 cells using siRNA and assessing its protein levels via Western blotting, we found that RACGAP1 knockdown inhibited cell growth and induced apoptosis determined using the Cell Counting Kit-8 assay, colony formation assay, and flow cytometry. Mechanistically, western blot analysis indicated that Bax expression increased, whereas Bcl-2 expression decreased. Moreover, RACGAP1 knockdown attenuated PI3K/AKT pathway activation in lung cancer cells. Taken together, our findings showed that RACGAP1 was overexpressed in LUAD tissues and played an important role in lung cancer by increasing cell growth through the PI3K/AKT signaling pathway. This study suggests recommends evaluating RACGAP1 in clinical settings as a novel biomarker and potential therapeutic target for lung cancer.

Photodynamic therapy upregulates expression of HIF-1α and PD-L1 in related pathways and its clinical relevance in non-small-cell lung cancer

BackgroundPhotodynamic therapy (PDT) is a promising interventional treatment approach that contributes to antitumor immunity. It has been reported that PDT can enhance the effectiveness of immune checkpoint inhibitors (ICIs), but its mechanism is yet unclear. Herein, we implemented bioinformatics analysis to detect common pathways and potential biomarkers in non-small cell lung cancer (NSCLC), PDT, and NSCLC immunotherapy to investigate potential links between PDT, immunotherapy and NSCLC, and their clinical impact.MethodsDifferentially expressed genes in NSCLC- and NSCLC immunotherapy-related data in the GEO database were intersected with PDT-related genes in the GeneCards database to obtain candidate genes and shared pathways. Enrichment analysis and protein–protein interaction were established to identify key genes in functionally enriched pathways. The expression profiles and the prognostic significance of key genes were depicted.ResultsBioinformatics analysis showed that HIF-1α was screened as a prognostic gene in hypoxia, HIF-1, and PD-L1-related signaling pathways, which was associated with clinical response in NSCLC patients after PDT and immunotherapy. In vivo experiments showed that PDT could inhibit tumor growth and upregulate HIF-1α and PD-L1 expressions in NSCLC tissues with a positive correlation, which might influence the blocking activity of ICIs on the HIF-1, and PD-L1-related signaling pathways.ConclusionsPDT might improve the clinical response of ICIs by upregulating tumor HIF-1α and PD-L1 expressions in NSCLC.

Potential application of C-MoS2 monolayer for identifying lung cancer biomarkers in exhaled breath: a DFT study

Potential application of C-MoS2 monolayer for identifying lung cancer biomarkers in exhaled breath: a DFT study

Composition of the sputum bacterial microbiome of patients with different pathomorphological forms of non-small-cell lung cancer.

Recent studies have shown that the bacterial microbiome of the respiratory tract influences the development of lung cancer. Changes in the composition of the microbiome are observed in patients with chronic inflammatory processes. Such microbiome changes may include the occurrence of bacteria that cause oxidative stress and that are capable of causing genome damage in the cells of the host organism directly and indirectly. To date, the composition of the respiratory microbiome in patients with various histological variants of lung cancer has not been studied. In the present study, we determined the taxonomic composition of the sputum microbiome of 52 patients with squamous cell carcinoma of the lung, 52 patients with lung adenocarcinoma and 52 healthy control donors, using next-generation sequencing (NGS) on the V3-V4 region of the bacterial gene encoding 16S rRNA. The sputum microbiomes of patients with different histological types of lung cancer and controls did not show significant differences in terms of the species richness index (Shannon); however, the patients differed from the controls in terms of evenness index (Pielou). The structures of bacterial communities (beta diversity) in the adenocarcinoma and squamous cell carcinoma groups were also similar; however, when analyzed according to the matrix constructed by the Bray-Curtis method, there were differences between patients with squamous cell carcinoma and healthy subjects, but not between those with adenocarcinoma and controls. Using the LEFse method it was possible to identify an increase in the content of Bacillota (Streptococcus and Bacillus) and Actinomycetota (Rothia) in the sputum of patients with squamous cell carcinoma when compared with samples from patients with adenocarcinoma. There were no differences in the content of bacteria between the samples of patients with adenocarcinoma and the control ones. The content of representatives of the genera Streptococcus, Bacillus, Peptostreptococcus (phylum Bacillota), Prevotella, Macellibacteroides (phylum Bacteroidota), Rothia (phylum Actinomycetota) and Actinobacillus (phylum Pseudomonadota) was increased in the microbiome of sputum samples from patients with squamous cell carcinoma, compared with the control. Thus, the sputum bacterial microbiome of patients with different histological types of non-small-cell lung cancer has significant differences. Further research should be devoted to the search for microbiome biomarkers of lung cancer at the level of bacterial species using whole-genome sequencing.

LncRNA XIST modulates miR-328-3p ectopic expression in lung injury induced by tobacco-specific lung carcinogen NNK both in vitro and in vivo.

It is well acknowledged that tobacco-derived lung carcinogens can induce lung injury and even lung cancer through a complex mechanism. MicroRNAs (MiRNAs) are differentially expressed in tobacco-derived carcinogen nicotine-derived nitrosamine ketone (NNK)-treated A/J mice. RNA sequencing was used to detect the level of long non-coding RNAs (lncRNAs). Murine and human lung normal and cancer cells were used to evaluate the function of lncRNA XIST and miR-328-3p in vitro, and NNK-treated A/J mice were used to test their function in vivo. In vivo levels of miR-328-3p and lncRNA XIST were analysed, using in situ hybridization. miR-328-3p agomir and lncRNA XIST-specific siRNA were used to manipulate in vivo levels of miR-328-3p and lncRNA XIST in A/J mice. LncRNA XIST was up-regulated in NNK-induced lung injury and dominated the NNK-induced ectopic miRNA expression in NNK-induced lung injury both in vitro and in vivo. Either lncRNA XIST silencing or miR-328-3p overexpression exerted opposing effects in lung normal and cancer cells regarding cell migration. LncRNA XIST down-regulated miR-328-3p levels as a miRNA sponge, and miR-328-3p targeted the 3'-UTR of FZD7 mRNA, which is ectopically overexpressed in lung cancer patients. Both in vivo lncRNA XIST silencing and miR-328 overexpression could rescue NNK-induced lung injury and aberrant overexpression of the lung cancer biomarker CK19 in NNK-treated A/J mice. Our results highlight the promotive effect of lncRNA XIST in NNK-induced lung injury and elucidate its post-transcriptional mechanisms, indicating that targeting lncRNA XIST/miR-328-3p could be a potential therapeutic strategy to prevent tobacco carcinogen-induced lung injury in vivo.

PBMCs as Tool for Identification of Novel Immunotherapy Biomarkers in Lung Cancer.

Lung cancer (LC), including both non-small (NSCLC) and small (SCLC) subtypes, is currently treated with a combination of chemo- and immunotherapy. However, predictive biomarkers to identify high-risk patients are needed. Here, we explore the role of peripheral blood mononuclear cells (PBMCs) as a tool for novel biomarkers searching. We analyzed the expression of the cGAS-STING pathway, a key DNA sensor that activates during chemotherapy, in PBMCs from LC patients divided into best responders (BR), responders (R) and non-responders (NR). The PBMCs were whole exome sequenced (WES). PBMCs from BR and R patients of LC cohorts showed the highest levels of STING (p < 0.0001) and CXCL10 (p < 0.0001). From WES, each subject had at least 1 germline/somatic alteration in a DDR gene and the presence of more DDR gene mutations correlated with clinical responses, suggesting novel biomarker implications. Thus, we tested the effect of the pharmacological DDR inhibitor (DDRi) in PBMCs and in three-dimensional spheroid co-culture of PBMCs and LC cell lines; we found that DDRi strongly increased cGAS-STING expression and tumor infiltration ability of immune cells in NR and R patients. Furthermore, we performed FACS analysis of PBMCs derived from LC patients from the BR, R and NR cohorts and we found that cytotoxic T cell subpopulations displayed the highest STING expression. cGAS-STING signaling activation in PBMCs may be a novel potential predictive biomarker for the response to immunotherapy and high levels are correlated with a better response to treatment along with an overall increased antitumor immune injury.

Circulating miR-16-5p, miR-92a-3p and miR-451a are biomarkers of lung cancer in Tunisian patients

Lung cancer is one of the most common type of cancer and, despite significant advances in screening and diagnosis approaches, a large proportion of patients at diagnosis still present advanced stages of the disease with distant metastasis and bad prognosis. Finding and validating biomarkers of lung cancer is therefore essential. Such studies are often conducted on European, American and Asian populations and the relevance of these biomarkers in other populations remains less clear. In that prospect, we investigated the expression level of seven microRNAs, chosen from the medical literature (miR-16-5p, miR-92a-3p, miR-103a-3p, miR-375-3p, miR-451a, miR-520-3p and miR-let-7e-5p), in the blood of Tunisian lung cancer patients, treated or not by chemotherapy, and healthy control individuals. We found that high expression levels of circulating miR-16-5p, miR-92a-3p and miR-451a in the plasma of untreated patients discriminate them from healthy control individuals. In addition, miR-16-5p and miR-451a expression levels are significantly reduced in the plasma of chemotherapy-treated patients compared to untreated patients. Our results confirmed previous work in other populations worldwide and provide further evidence that circulating miR-16-5p, miR-92a-3p and miR-451a potentially regulate key pathways involved in the initiation and progression of cancer. 

Identification and validation of PCDHGA12 and PRRX1 methylation for detecting lung cancer in bronchial washing sample.

Bronchoscopy is a frequently used initial diagnostic procedure for patients with suspected lung cancer (LC). Cytological examinations of bronchial washing (BW) samples obtained during bronchoscopy often yield inconclusive results regarding LC diagnosis. The present study aimed to identify molecular biomarkers as a non-invasive method for LC diagnosis. Aberrant DNA methylation is used as a useful biomarker for LC. Therefore, microarray-based methylation profiling analyses on 13 patient-matched tumor tissues at stages I-III vs. non-tumor tissues were performed, and a group of highly differentially methylated genes was identified. A subsequent analysis using bisulfite-pyrosequencing with additional tissues and cell lines revealed six methylated genes [ADAM metallopeptidase with thrombospondin type 1 motif 20, forkhead box C2 (mesenchyme forkhead 1), NK2 transcription factor related, locus 5 (Drosophila), oligodendrocyte transcription factor 3, protocadherin γ subfamily A 12 (PCDHGA12) and paired related homeobox 1 (PRRX1)] associated with LC. Next, a highly sensitive and accurate detection method, linear target enrichment-quantitative methylation-specific PCR in a single closed tube, was applied for clinical validation using BW samples from patients with LC (n=68) and individuals with benign diseases (n=33). PCDHGA12 and PRRX1 methylation were identified as the best-performing biomarkers to detect LC. The two-marker combination showed a sensitivity of 82.4% and a specificity of 87.9%, with an area under the curve of 0.891. Notably, the sensitivity for small cell LC was 100%. The two-marker combination had a positive predictive value of 93.3% and a negative predictive value of 70.7%. The sensitivity was higher than that of cytology, which only had a sensitivity of 50%. The methylation status of the two-marker combination showed no association with sex, age or stage, but was associated with tumor location and histology. In conclusion, the present study showed that the regulatory regions of PCDHGA12 and PRRX1 are highly methylated in LC and can be used to detect LC in BW specimens as a diagnostic adjunct to cytology in clinical practice.

Highly sensitive “off-on” sensor based on MXene and magnetic microspheres for simultaneous detection of lung cancer biomarkers - Neuron specific enolase and carcinoembryonic antigen

In this work, a highly sensitive lung cancer biomarkers detection probe was developed based on Ag and MXene co-functionalized magnetic microspheres. By using carboxyl magnetic microspheres as carrier, MXene was coated repeatedly by Poly (allylamine hydrochloride) (PAH) as interlayer adhesive, and silver particles grown on the surface of MXene in situ can efficiently improve the sensitivity of the probe. The detection of neuron specific enolase (NSE) is mainly through the formation of a specific complex between NSE antigen and antibody, and the release of antibody labeled with amino carbon quantum dots (CQDs) from the surface of Ag nanoparticles (AgNPs), so that the fluorescence is restored and "OFF-ON" is formed. The biosensor exhibits excellently wide linear range (0.0001–1500 ng/mL) and the limit of detection (LOD) is up to 0.03 pg/mL, which is superior to most tumor marker probes based on fluorescence mechanism. Furthermore, we constructed dual detection strategy for NSE and carcinoembryonic antigen (CEA) simultaneously.

Dynamic mutation late acceptance hill climbing aided red fox optimization for metabolomic biomarkers selection from lung cancer patient sera

The accurate selection of serum metabolomic biomarkers for early lung cancer screening remains a significant challenge in the clinical context. Consequently, this study introduces the Red Fox Optimization (RFO) that integrates Dynamic Mutation Late Acceptance Hill Climbing (DM-LAHC), with the aim of selecting a panel of serum metabolomic biomarkers suitable for distinguishing between benign and malignant pulmonary nodules. The key innovation is the dynamic adjustment of the mutation probability in the Late Acceptance Hill Climbing algorithm, which greatly enhances the local search capabilities. And the RFO's reproduction mechanism has been improved through the utilization of a more efficient interpolation form. The biomarker selection model employs a multi-objective fitness function that takes into account both accuracy and quantity. After this, the optimal model yielded a biomarker panel, including Inosine, Hippuric acid, Alanine, and other metabolites. This model demonstrates outstanding performance on an independent test dataset, achieving a fitness value of 0.9136, an AUC (Area Under the Curve) of 0.9926, a sensitivity of 0.9643, and a specificity of 0.9412. Furthermore, the clinical net benefit is highlighted across various risk thresholds by decision curve analysis. These results underscore the significance of DM-LAHC aided RFO in the selection of serum metabolomic biomarkers for lung cancer. The supporting source codes of this work can be found at: https://github.com/zzl2022/DM-LAHC-aided-RFO.

Identification of volatile biomarkers for lung cancer from different histological sources: A comprehensive study

The identification of noninvasive volatile biomarkers for lung cancer is a significant clinical challenge. Through in vitro studies, the recognition of altered metabolism in cell volatile organic compound (VOC) emitting profile, along with the occurrence of oncogenesis, provides insight into the biochemical pathways involved in the production and metabolism of lung cancer volatile biomarkers. In this research, for the first time, a comprehensive comparative analysis of the volatile metabolites in NSCLS cells (A549), SCLC cells (H446), lung normal cells (BEAS-2B), as well as metabolites in both the oxidative stress (OS) group and control group. Specifically, the combination of eleven VOCs, including n-dodecane, acetaldehyde, isopropylbenzene, p-ethyltoluene and cis-1,3-dichloropropene, exhibited potential as volatile biomarkers for lung cancer originating from two different histological sources. Furthermore, the screening process in A549 cell lines resulted in the identification of three exclusive biomarkers, isopropylbenzene, formaldehyde and bromoform. Similarly, the exclusive biomarkers 1,2,4-trimethylbenzene, p-ethyltoluene, and cis-1,3-dichloropropene were present in the H446 cell line. Additionally, significant changes in trans-2-pentene, acetaldehyde, 1,2,4-trimethylbenzene, and bromoform were observed, indicating a strong association with OS. These findings highlight the potential of volatile biomarkers profiling as a means of noninvasive identification for lung cancer diagnosis.

Dynamic Changes of the Gut Microbiota and Its Functional Metagenomic Potential during the Development of Non-Small Cell Lung Cancer.

The gut microbiota plays a significant role in tumor pathogenesis by regulating the host metabolism and immune response, and there are few studies focused on tracking changes in the gut microbiota from the onset of lung cancer. Therefore, the aim of our study is combining preclinical and clinical research to thoroughly analyze the signatures of fecal microbiota in lung cancer, which will be useful for early diagnosis and predicting the therapeutic efficacy of lung cancer. The first part of this study analyzed the fecal metagenomic differences between patients with non-small cell lung cancer and healthy subjects, and the second part of this work constructed a murine lung cancer model to monitor changes in mouse fecal metagenomics and T cell immunology during lung cancer progression. We found that the fecal microbiota was altered in both humans and mice with lung cancer, characterized by a significantly reduced microbial diversity and number of beneficial microbes, with increases in potential pathogens. The fecal level of Akkermansia muciniphila and the gut metabolic module of the secondary bile acid metabolism were diminished in both humans and mice with lung cancer compared with healthy subjects. Splenomegaly was observed in the lung cancer mice. Flow cytometer analysis of the splenocytes revealed substantial alterations in the proportions of T cell subsets in the lung cancer mice, characterized by significant increases in CD4+Foxp3+CD25+ T regulatory cells (p < 0.05) while significant decreases in CD3+ T cells (p < 0.001), CD4+ T cells (p < 0.001), and the CD4+/CD8+ ratio (p < 0.01). Vertical and longitudinal analyses of the fecal microbiota of the two mouse groups identified some lung cancer biomarkers (including Acutalibacter timonensis, Lachnospiraceae bacterium NSJ-38 sp014337195, etc.). The fecal microbiota of the lung cancer mice had a reduced metagenomic potential for neurotransmitters (melatonin, γ-aminobutyric acid, and histamine) compared with healthy mice. In summary, this study found that the diversity, structure, and composition of gut microbiota vary between cancer and healthy conditions, ultimately leading to changes in the potential for functional metagenomics.

Abstract 2448: Field cancerization proteomic analysis provides a novel class of functional risk biomarkers for non small cell lung cancer

Abstract Lung cancer carcinogenesis is the outcome of a field of premalignant changes that occur in the bronchial tree leading to the overt emergence of the malignant lung cancer (field cancerization). A tissue or blood proteomic signature of these premalignant changes represent a novel concept of risk biomarkers that can predict the probability of future emergence of Lung Cancer. In this study, we analyzed two independent cohorts of non-small cell lung cancer (NSCLC) patients. One cohort consisted of 18 patients who donated blood before and after tumor resection surgery and matched tissue samples (UAMS Medical Center). The second set derived from a longitudinal case-control study of plasma sample collected during the physician health study that were donated at different times prior to the diagnosis of Non-Small Cell Lung Cancer (N=272). We used affinity-enriched mass spectrometry analysis and statistical learning techniques to identify a set of common markers that discriminated plasma cases and controls and were conserved in different bronchial tissue compartments including tumor and adjacent tissue. The tumor microenvironment adjacent to and surrounding cancer cells undergoes to progressive stages of carcinogenesis during field cancerization. We identified 22 proteins involved in cell adhesion, protein folding, immune response, angiogenesis, and cancer proliferation. This is a novel class of functional risk biomarkers to determine the probability of NSCLC onset. In conclusion, our findings shed light on a new class of functional biomarkers that underly tumor pathogenesis mechanisms and can provide hints for new strategies of tumor prevention therapy or lifestyle modification. Citation Format: Rayan Ibrahim Alhammad, Ngoc Bao Vuong, Weidong Zhou, Donald J Johann Jr, Barbara Birkaya, Lance Liotta, Alessandra Luchini. Field cancerization proteomic analysis provides a novel class of functional risk biomarkers for non small cell 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 2448.

Abstract 1068: Plasma metabolite biomarkers for EGFR-mutated non-small cell lung cancer (NSCLC)

Abstract Background: Lung cancer is the leading cause of cancer death. More than half of the patients are diagnosed in the advanced stage for which the 5-year survival is below 10%. Lung cancer screening using low-dose CT scan reduced lung cancer mortality among heavy smokers. However, no standard screening method exists for non-smokers. Up to 35% and 90% of male and female lung cancer patients in Southeast Asia, respectively, do not smoke. Half of NSCLC patients in this region harbor EGFR mutations, which is common in women and non-smokers. Thus, we sought to explore novel biomarkers that help to identify lung cancer patients and those who have EGFR mutation. Metabolic reprogramming is one of the hallmarks of cancer. It leads to changes in metabolite levels in the blood. Hence, we conducted plasma metabolomic analysis to identify potential metabolite biomarkers in lung cancer patients. Methods: Plasma samples were collected from 69 lung cancer patients at Siriraj hospital and 10 healthy individuals during 2018-2022. Plasma metabolites from 29 treatment-naïve EGFR-mutated NSCLC patients, 30 treatment-naïve EGFR-wild-type NSCLC patients, 10 treatment-resistant EGFR T790M-mutated NSCLC patients, and 10 healthy individuals were profiled using GC-MS and untargeted LC-MS with Metlin database matching. EGFR mutation was detected from plasma ctDNA using real-time PCR. Negative plasma EGFR mutation results were confirmed with corresponding tumor tissues. Metabolomics data were processed by the metabox R package. Results: Among 114 candidate metabolites that passed the variable importance in projection (VIP) cutoff of 1.5, the top ten metabolites that differentiate NSCLC patients with EGFR mutation from those without were shown in Table 1. Many of them can also separate between NSCLC patients and healthy individuals. Table 1. ROC curve analysis Discriminant metabolites (Mutated EGFR vs Wild-type EGFR NSCLC) AUC Accuracy Sensitivity Specificity PG(a-13:0/i-12:0) 0.8000 0.7833 0.8333 0.7333 Nervonic ceramide 0.7736 0.6772 0.7259 0.6333 Valine 0.7678 0.7298 0.7259 0.7333 L-Histidinol 0.7644 0.7281 0.7222 0.7333 Leucine 0.7563 0.7632 0.7259 0.8000 Tryptophan 0.7425 0.6289 0.5593 0.7000 8-methylcaffeine 0.6793 0.6096 0.6222 0.6000 Formic acid 0.6759 0.6447 0.5889 0.7000 PC(20:0/24:0) 0.6506 0.6614 0.8259 0.5000 Sucrose 0.6471 0.6596 0.7593 0.5667 Discriminant metabolites (NSCLC patients vs Healthy individuals) AUC Accuracy Sensitivity Specificity Tryptophan 0.9986 0.9867 1.0000 0.9848 PC(20:0/24:0) 0.8609 0.9505 0.6111 1.0000 L-Histidinol 0.8572 0.9625 0.7778 0.9861 Formic acid 0.6696 0.9262 0.6667 0.9704 Conclusions: Plasma L-Histidinol, tryptophan, PC(20:0/24:0), and formic acid are potential metabolite biomarkers for NSCLC patients harboring EGFR mutation. Citation Format: Lucksamon Thamlikitkul, Siriphan Manocheewa, Suphitcha Limjiasahapong, Kwanjeera Wanichthanarak, Atikorn Panya, Naravat Poungvarin, Yotsawat Pomyen, Sakda Khoomrung. Plasma metabolite biomarkers for EGFR-mutated non-small cell lung cancer (NSCLC) [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 1068.

Abstract 7501: Gene expression profiling of rare cells captured from liquid biopsy using the genesis cell isolation system

Abstract Background: Targeting rare cell types such as circulating tumor cells (CTCs), considered to be metastatic precursors in cancer progression, may provide long-term clinical benefits by enhancing patient outcomes. The study of CTCs comes with technical challenges due to their heterogeneity and low cell numbers, leading to difficulties in genomic characterization. This study aims to overcome these technical challenges by developing a comprehensive gene expression profiling workflow using qPCR and RNA sequencing (RNA-Seq) on rare cells enriched with Genesis System with Celselect SlidesTM. Methods: To mimic CTCs in blood, we created a rare cell model sample by spiking A549 non-small cell lung cancer cells at concentrations of 50, 100, 500 and 1000 cells/ml in whole blood from healthy donors. The Genesis System, which can capture rare cells of 8µm-30µm, isolated 83.73% of spiked A549 cells in whole blood. Using the same blood samples without A549 spiked in, we enriched cells using the Genesis and it was used as a baseline for gene expression controls. High quality RNA was extracted from each of the enriched samples and used for both qPCR and RNA-Seq to detect the gene expression signature of the non-small cell lung cancer cells. Results: Our analyses revealed significant differential expression of cancer-related genes (p &amp;lt; 0.05) in all A549-spiked samples when compared to the blood-only controls. Notably, in the 50 cells/ml dilution, RNA-Seq analysis identified over 3,000 differentially expressed genes, encompassing protein-coding genes, long non-coding RNAs, and small non-coding RNAs. Among these, 759 genes were consistently present across all enriched samples, suggesting a common expression pattern. To investigate the potential utility of these genes as non-small cell lung cancer biomarkers, we constructed a custom qPCR array comprising 38 of these genes and pre-amplified their targets using 50pg of RNA from the enriched cell samples. Notably, six genes from this panel (MET, TOP2A, NF1, SPP1, GAPDH, and ANXA5) exhibited significant differential expression (+/- 4-fold, p&amp;lt;0.05) in the enriched samples. MET and TOP2A, in particular, are well-known biomarkers for non-small cell lung cancer. Conclusion: Our liquid biopsy workflow demonstrates the recovery of high-quality RNA from enriched rare cells, including CTCs. It enables comprehensive profiling of the tumor transcriptome, encompassing RNAs of various sizes, including miRNAs. Our approach has the potential to facilitate the identification of patient-specific biomarkers, enabling swift monitoring using preamplification and qPCR in advancement of targeted oncology therapy and research. Citation Format: Srikanth Perike, Angelica Olcott, Cissy Jiang, Nish Kumar, Nathan Knapp, Jennifer Placek, Candice Cox, Yoon-Tae Kang, Linda Lingelbach, Elizabeth Dreskin. Gene expression profiling of rare cells captured from liquid biopsy using the genesis cell isolation system [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 7501.