Biomarker For Non-small Cell Lung Cancer Research Articles

CT based radiomics signature for phenotyping histopathological subtype in patients with non-small cell lung cancer.

e20599 Background: The determination of the histopathology of non-small cell lung cancer (NSCLC) is crucial for guiding the appropriate therapeutic strategy, affecting prognosis and recurrence rates. In addition, targetable oncologic mutations are highly correlated to histological subtypes. Conventional methods such as biopsy or surgical excision are the primary methods for histology determination but are invasive, costly, and have limitations such as sampling error. Computed tomography (CT) scans, widely used for NSCLC diagnosis and follow-up, offer a non-invasive alternative through radiomics-based models that provide comprehensive analysis of the entire tumor and surrounding tissue, improving patient selection and stratification in clinical trials and enhancing the development of molecularly targeted drugs. The goal of this study was to evaluate the ability of a CT-based radiomics model to predict the subtype histopathology of NSCLC patients. Methods: A total of 678 patients with advanced-stage NSCLC with at least one measurable lung lesion (≥10mm) were selected from multicenter institutions; 531 were used for training and 147 for independent testing. The test set originates from centers unique from the training cohort. Semi-automatic segmentation of the lung lesions was performed and the segmentations were retrospectively reviewed by an experienced radiologist with > 20 years of experience. A total of 1246 radiomics features were extracted using the Pyradiomics package. Ten Robust features were selected first by removing all features with variances near zero, then by applying Maximum Relevance — Minimum Redundancy to the remaining features. All selected features were standardized before modeling. A support vector machines classifier was trained using a five-fold cross-validation and Random Over-Sampling Examples to classify the histology of NSCLC patients (Squamous vs. Non-Squamous). Results: The model trained with the radiomics features achieved a mean area under the curve (AUC) of 0.80 (95% CI, ±0.05) on the cross-validation and an AUC of 0.77 (95% CI, ±0.05) on the test set. Conclusions: Results showed that the model was able to accurately classify the histology of NSCLC patients as squamous vs. non-squamous in a multicenter setting. It highlights the promise of CT-based radiomics in determining the histopathology or other molecular biomarkers of NSCLC, offering a more efficient, cost-effective, and less invasive alternative to traditional tissue analysis methods. Our findings suggest that this non-invasive method has the potential to improve patient selection and stratification and enhance the development of molecularly targeted drugs. These results underscore the importance of incorporating advanced imaging techniques and machine learning algorithms into oncology practice for better patient outcomes.

Hypoxia-mediated promotion of glucose metabolism in non-small cell lung cancer correlates with activation of the EZH2/FBXL7/PFKFB4 axis

F-box/LRR-repeat protein 7 (FBXL7) was predicted as a differentially expressed E3 ubiquitin ligase in non-small cell lung cancer (NSCLC), which has been suggested to influence cancer growth and metastasis. In this study, we aimed to decipher the function of FBXL7 in NSCLC and delineate the upstream and downstream mechanisms. FBXL7 expression was verified in NSCLC cell lines and GEPIA-based tissue samples, after which the upstream transcription factor of FBXL7 was bioinformatically identified. The substrate PFKFB4 of the FBXL7 was screened out by tandem affinity purification coupled with mass-spectrometry (TAP/MS). FBXL7 was downregulated in NSCLC cell lines and tissue samples. FBXL7 ubiquitinated and degraded PFKFB4, thus suppressing glucose metabolism and malignant phenotypes of NSCLC cells. Hypoxia-induced HIF-1α upregulation elevated EZH2 and inhibited FBXL7 transcription and reduced its expression, thus promoting PFKFB4 protein stability. By this mechanism, glucose metabolism and the malignant phenotype were enhanced. In addition, knockdown of EZH2 impeded tumor growth through the FBXL7/PFKFB4 axis. In conclusion, our work reveals that the EZH2/FBXL7/PFKFB4 axis plays a regulatory role in glucose metabolism and tumor growth of NSCLC, which is expected to be potential biomarkers for NSCLC.

Development of a QCM-based biosensor for the detection of non-small cell lung cancer biomarkers in liquid biopsies

Lung cancer is the main malignant cancer reported worldwide, with one of the lowest survival rates. Deletions in the Epidermal Growth Factor Receptor (EGFR) gene are often associated with non-small cell lung cancer (NSCLC), a common subtype of lung cancer. The detection of such mutations provides key information for the diagnosis and treatment of the disease; therefore, the early screening of such biomarkers is of vital importance. The need for fast, reliable, and early detection means applied to NSCLC has led to the development of highly sensitive devices that can detect cancer-associated mutations. Such devices, known as biosensors, are a promising alternative to more conventional detection methods and can potentially alter the way cancer is diagnosed and treated. In this study, we report the development of a DNA-based biosensor, namely a quartz crystal microbalance (QCM), applied to the detection of NSCLC, from liquid biopsies samples. The detection, as is the case of most DNA biosensors, is based on the hybridization between the NSCLC-specific probe and the sample DNA (containing specific mutations associated with NSCLC). The surface functionalization was performed with a blocking agent (dithiothreitol) and thiolated-ssDNA strands. The biosensor was able to detect specific DNA sequences in both synthetic and real samples. Aspects such as reutilization and regeneration of the QCM electrode were also studied.

Extracellular RNA profiles in non-small cell lung cancer plasma.

Non-small cell lung cancer (NSCLC) has a high mortality rate and poor prognosis. The early detection of high-risk patients is essential to improve patient prognosis. Thus, the identification of a non-invasive, non-radiative, convenient, and fast diagnostic approach should be a top priority in NSCLC research. Circulating extracellular RNAs (exRNAs) in the plasma are potential biomarkers for NSCLC. We used RNA-sequencing (RNA-seq) technology to explore the NSCLC-related RNAs, especially the circular RNAs (circRNAs). The circRNA-targeted micro RNAs (miRNAs) were predicted using 3 circRNA databases [i.e., the Cancer-Specific CircRNA Database (CSCD), circBank, and Circular RNA Interactome]. The circRNA-miRNA-messenger RNA (mRNA) network was constructed using Cytoscape V3.8.0 (Cytoscape Consortium, San Diego, CA, USA). The expression levels of some differentially expressed genes were validated by a quantitative real-time polymerase chain reaction (qRT-PCR) analysis. The results showed that the RNA biotypes of the mitochondrial ribosomal RNAs (mt-rRNAs) and mitochondrial transfer RNAs (mt-tRNAs) were upregulated in the NSCLC plasma. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms of the differentially expressed transcripts of NSCLC included oxidative phosphorylation, proton transmembrane transport, and the response to oxidative stress. Additionally, the qRT-PCR validation indicated that hsa_circ_0000722 had significantly higher expression in the NSCLC plasma than the control plasma, but hsa_circ_0006156 did not differ between the NSCLC plasma and the control plasma. The expression levels of miR-324-5p and miR-326 were higher in the NSCLC plasma than the control plasma. In this study, an exRNA-sequencing strategy was used to identify the expression of NSCLC-specific transcription factors in clinical plasma samples, and hsa_circ_0000722 and hsa-miR-324-5p were identified as potential biomarkers in NSCLC.

GPX2 promotes EMT and metastasis in non-small cell lung cancer by activating PI3K/AKT/mTOR/Snail signaling axis.

Lung cancer, with non-small cell lung cancer (NSCLC) being the main subtype, is the leading cause of cancer death worldwide, which is mainly due to the cancer metastasis. Glutathione peroxidase 2 (GPX2), anantioxidant enzyme, is involved in tumor progression and metastasis. Nevertheless, the role of GPX2 in NSCLC metastasis has not been clarified. In this study, we found that GPX2 expression was elevated in NSCLC tissues and high GPX2 expression was correlated with poor prognosis in patients with NSCLC. In addtion, GPX2 expression was related to the patient's clinicopathological features, including lymph node metastasis, tumor size, and TNM stage. Overexpression of GPX2 promoted epithelial-mesenchymal transition (EMT), migration, and invasion of NSCLC cells in vitro. Knockdown of GPX2 showed the opposite effects in vitro and inhibited the metastasis of NSCLC cells in nude mice. Furthermore, GPX2 reduced reactive oxygen species (ROS) accumulation and activated the PI3K/AKT/mTOR/Snail signaling axis. Therefore, our results indicate that GPX2 promotes EMT and metastasis of NSCLC cells by activating the PI3K/AKT/mTOR/Snail signaling axis via the removal of ROS. GPX2 may be an effective diagnostic and prognostic biomarker for NSCLC.

Abstract 5836: Non-invasive quantification of fibroblast activation protein (FAP) cleaved type III collagen in serum reflects FAP activity and has biomarker potential in non-small cell lung cancer

Abstract Introduction: Fibroblast activation protein (FAP) is an established cancer associated fibroblast (CAF) marker. FAP is highly expressed in the cancer stroma and is a predictor of poor survival for patients with non-small cell lung cancer (NSCLC). For this reason, it is being explored as a potential drug target. FAP has broad proteolytic activity and can directly promote multiple aspects of tumor progression. The aim of this study was to develop a tool to non-invasively measure FAP activity and validate its potential as a non-invasive biomarker in NSCLC. Methods: An ELISA, named C3F, was developed to reflect proteolytic activity of FAP by quantifying FAP-mediated cleavage of type III collagen in serum. To confirm that C3F reflects proteolytic activity of FAP, type III collagen was assayed after incubation with and without FAP. C3F was measured in serum samples from healthy controls (n = 26) and patients with NSCLC: adenocarcinoma (AD) (n = 26) and squamous cell carcinoma (SCC) (n = 14). An ELISA quantifying matrix metalloprotease degraded type III collagen (C3M) was used for measuring the same serum samples and compared to C3F using spearman correlation test and area under receiver operating characteristic curves (AUROCs). Results: A C3F signal only appeared after FAP cleavage of type III collagen, supporting that C3F reflects FAP proteolytic activity. Compared to healthy controls, C3F was significantly elevated in serum from patients with SCC (p = 0.0004, AUROC = 0.86), but not AD (p = 0.21, AUROC = 0.66). C3F was also significantly elevated in SCC compared to AD (p = 0.030, AUROC = 0.77). In comparison, C3M was significantly elevated in serum from both SCC and AD compared to healthy controls (p < 0.0001, AUROC = 0.93 and p < 0.0001, AUROC = 0.92, respectively), but no difference was seen between SSC and AD (p > 0.99, AUROC = 0.56). Only a moderate correlation was seen between C3M and C3F (r = 0.58, p < 0.0001). Conclusion: FAP activity can be non-invasively quantified in serum by assaying FAP cleaved type III collagen (C3F). C3F shows promise as a cancer biomarker in NSCLC with potential for discriminating between NSCLC subtypes. As C3F reflects FAP activity, it is potentially a more suitable (or complementary) biomarker for anti-FAP drug development and prediction of anti-FAP treatment response compared to methods that asses the presence of FAP. Citation Format: Rasmus Sund Pedersen, Jeppe Thorlacius-Ussing, Nicholas Willumsen, Morten A. Karsdal. Non-invasive quantification of fibroblast activation protein (FAP) cleaved type III collagen in serum reflects FAP activity and has biomarker potential in non-small cell lung cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5836.

Down-regulation and Clinic-pathological Correlation of SIK-1 and SIK-1-LNC in Non-small Cell Lung Cancer Patients

Non-small-cell lung cancer (NSCLC) is currently the leading cause of mortality cancer. Introducing noninvasive approaches to diagnose NSCLC, especially at an early phase, might improve the disease's prognosis. Long noncoding RNAs (lncRNAs), which are important regulators of the expression genes inside the cells, have been linked to a range of biological processes, such as cancer progression and metastasis, including NSCLC. The present work aims to determine the potential involvement of SIK-1-LNC and SIK-1 in NSCLC pathogenesis and the possible use of these molecules as novel biomarkers or therapeutic targets. In this work, the expression levels of SIK-1-LNC and SIK-1 in 50 pairs of NSCLC tumor and tumor marginal tissues were evaluated. So, after total RNA extraction and complementary DNA synthesis, the SIK-1-LNC and SIK-1 expression levels were evaluated by real-time PCR. In the study groups, clinical and pathological characteristics of the NSCLC patients were also examined. Our findings showed that tumor samples had much lower levels of SIK-1 and SIK-1-LNC expression than tumor margin samples. SIK-1-LNC expression was correlated with SIK-1 levels in NSCLC samples. Interestingly, both stage and lymph node metastasis features of the tumor were associated significantly with SIK-1 and SIK-1-LNC expression levels. A ROC curve analysis indicated a biomarker index of 0.69 and 0.74 for SIK-1 and SIK-1-LNC, respectively. Collectively, our study emphasized the role of SIK-1-LNC and SIK-1 downregulation in NSCLC oncogenesis. Additionally, SIK-1 and SIK-1-LNC, particularly the latter, have shown remarkable potential to be utilized as new NSCLC biomarkers and therapeutic targets.

HOXD9 contributes to the Warburg effect and tumor metastasis in non-small cell lung cancer via transcriptional activation of PFKFB3

Warburg effect is associated with the progression of various tumors, leading to the development of drugs targeting the phenomenon. PFKFB3 is an isoform of 6-phosphofructo-2-kinase (PFK2) that modulates the Warburg effect and has been implicated in most common types of cancer, including non-small cell lung cancer (NSCLC). However, the mechanisms underlying the upstream regulation of PFKFB3 in NSCLC remain poorly understood. This study reported that the transcription factor HOXD9 is upregulated in NSCLC patient samples relative to adjacent normal tissue. Elevated HOXD9 levels are primarily associated with poor prognosis in patients with NSCLC. Functionally, HOXD9 knockdown impaired the metastatic capacity of NSCLC cells, whereas its over-expression accelerated the metastasis and invasion of NSCLC cells in an orthotopic tumor mouse model. In addition, HOXD9 promoted metastasis by increasing cellular glycolysis. Further mechanistic studies revealed that HOXD9 directly binds to the promoter region of PFKFB3 to enhance its transcription. The recovery assay confirmed that the capability of HOXD9 to promote NSCLC cells metastasis was significantly weakened upon PFKFB3 inhibition. These data suggest that HOXD9 may exert as a novel biomarker in NSCLC, indicating that blocking the HOXD9/PFKFB3 axis may be a potential therapeutic strategy for NSCLC treatment.

Quantitative Image Analysis of Fibrillar Collagens Reveals Novel Diagnostic and Prognostic Biomarkers and Histotype-Dependent Aberrant Mechanobiology in Lung Cancer

Fibrillar collagens are the most abundant extracellular matrix components in non–small cell lung cancer (NSCLC). However, the potential of collagen fiber descriptors as a source of clinically relevant biomarkers in NSCLC is largely unknown. Similarly, our understanding of the aberrant collagen organization and associated tumor-promoting effects is very scarce. To address these limitations, we identified a digital pathology approach that can be easily implemented in pathology units based on CT-FIRE software (version 2; https://loci.wisc.edu/software/ctfire) analysis of Picrosirius red (PSR) stains of fibrillar collagens imaged with polarized light (PL). CT-FIRE settings were pre-optimized to assess a panel of collagen fiber descriptors in PSR-PL images of tissue microarrays from surgical NSCLC patients (106 adenocarcinomas [ADC] and 89 squamous cell carcinomas [SCC]). Using this approach, we identified straightness as the single high-accuracy diagnostic collagen fiber descriptor (average area under the curve = 0.92) and fiber density as the single descriptor consistently associated with a poor prognosis in both ADC and SCC independently of the gold standard based on the TNM staging (hazard ratio, 2.69; 95% CI, 1.55-4.66; P < .001). Moreover, we found that collagen fibers were markedly straighter, longer, and more aligned in tumor samples compared to paired samples from uninvolved pulmonary tissue, particularly in ADC, which is indicative of increased tumor stiffening. Consistently, we observed an increase in a panel of stiffness-associated processes in the high collagen fiber density patient group selectively in ADC, including venous/lymphatic invasion, fibroblast activation (α-smooth muscle actin), and immune evasion (programmed death-ligand 1). Similarly, a transcriptional correlation analysis supported the potential involvement of the major YAP/TAZ pathway in ADC. Our results provide a proof-of-principle to use CT-FIRE analysis of PSR-PL images to assess new collagen fiber–based diagnostic and prognostic biomarkers in pathology units, which may improve the clinical management of patients with surgical NSCLC. Our findings also unveil an aberrant stiff microenvironment in lung ADC that may foster immune evasion and dissemination, encouraging future work to identify therapeutic opportunities.

Effective voltammetric tool for simultaneous detection of MMP-1, MMP-2, and MMP-9; important non-small cell lung cancer biomarkers

Simultaneous detection of multiple biomarkers can allow to reduce the costs of medical diagnostics, and thus improve the accuracy and effectiveness of disease diagnosis and prognosis. Here, for the first time, we present a low-cost, simple, and rapid method for simultaneous detection of three matrix metalloproteinases (MMP-1, MMP-2, and MMP-9) that play important roles in the progression of lung cancer. The sensor matrix was constructed using a G2 polyamidoamine dendrimer (PAMAM) containing amino, carboxyl, and sulfhydryl groups. The recognition process was based on specific enzymatic cleavage of the Gly-Ile peptide bond by MMP-1, Gly-Leu bond by MMP-2, and Gly-Met bond by MMP-9, and monitoring was done by square wave voltammetry. The activity of metalloproteinases was detected based on the change of current signals of redox receptors (dipeptides labeled with electroactive compounds) covalently anchored onto the electrode surface. The conditions of the biosensor construction, including the concentration of receptors on the sensor surface and the time of interaction of the receptor with the analyte, were carefully optimized. Under optimal conditions, the linear response of the developed method ranged from 1.0⋅10−8 to 1.0 mg⋅L−1, and the limit of detection for MMP-1, MMP-2, and MMP-9 was 0.35, 0.62, and 1.10 fg⋅mL−1, respectively. The constructed biosensor enabled us to efficiently profile the levels of active forms of MMP-1, MMP-2, and MMP-9 in tissue samples (plasma and lung and tumor extracts). Thus, the developed biosensor can aid in the early detection and diagnosis of lung cancer.

The Tumorigenic Effect of lncRNA AFAP1-AS1 is Mediated by Translated Peptide ATMLP Under the Control of m6 A Methylation.

Long noncoding RNAs (lncRNAs) in eukaryotic transcripts have long been believed to regulate various aspects of cellular processes, including carcinogenesis. Herein, it is found that lncRNA AFAP1-AS1 encodes a conserved 90-amino acid peptide located on mitochondria, named lncRNA AFAP1-AS1 translated mitochondrial-localized peptide (ATMLP), and it is not the lncRNA but the peptide that promotes the malignancy of nonsmall cell lung cancer (NSCLC). As the tumor progresses, the serum level of ATMLP increases. NSCLC patients with high levels of ATMLP display poorer prognosis. Translation of ATMLP is controlled by m6 A methylation at the 1313 adenine locus of AFAP1-AS1. Mechanistically, ATMLP binds to the 4-nitrophenylphosphatase domain and non-neuronal SNAP25-like protein homolog 1 (NIPSNAP1) and inhibits its transport from the inner to the outer mitochondrial membrane, which antagonizes the NIPSNAP1-mediated regulation of cell autolysosome formation. The findings uncover a complex regulatory mechanism of NSCLC malignancy orchestrated by a peptide encoded by a lncRNA. A comprehensive judgment of the application prospects of ATMLP as an early diagnostic biomarker for NSCLC is also made.

Increased TIM-3 expression in tumor-associated macrophages predicts a poorer prognosis in non-small cell lung cancer: a retrospective cohort study.

T-cell immunoglobulin and mucin domain-containing molecule 3 (TIM-3) is considered a key negative regulator in T-cell-mediated response. However, few studies have been reported on the relationship between TIM-3 expression in tumor-associated macrophages (TAMs) and clinicopathological characteristics of patients. This study evaluated the correlation between the expression of TIM-3 on the surface of TAMs macrophages in tumor matrix and the clinical outcome of patients with non-small cell lung cancer (NSCLC). The expression of CD68, CD163 and TIM-3 in 248 NSCLC patients who underwent surgery in Zhoushan Hospital from January 2010 to January 2013 was detected by immunohistochemistry (IHC). From the date of operation to the date of death, overall survival (OS) was measured to analyze the relationship between the expression of Tim-3 and the prognosis of NSCLC patients. The study assessed 248 patients with NSCLC. TIM-3 expression in TAMs was more frequently identified in patients with higher carcinoembryonic antigen (CEA) levels, lymph node metastasis, higher grade, high CD68 expression, and high CD163 expression (P<0.05). The OS of the high TIM-3 expression groups was shorter than that of the low TIM-3 expression groups (P=0.01). Patients with high TIM-3 and CD68/CD163 expressions had the worst prognosis, whereas patients with low expressions of both TIM-3 and CD68/CD163 had the best prognosis (P<0.05). In NSCLC, the OS of the high TIM-3 expression groups was shorter than that of the low TIM-3 expression groups (P=0.01). In lung adenocarcinoma, the OS of the high TIM-3 expression groups was shorter than that of the low TIM-3 expression groups(P=0.03). TIM-3 expression in TAMs may be a promising prognostic biomarker for NSCLC or adenocarcinoma. Our results demonstrated that high TIM-3 expression in TAMs was an independent predictor of worse prognosis in patients.

Lnc-TMEM132D-AS1 overexpression reduces sensitivity of non-small cell lung cancer cells to osimertinib

To screen the differentially expressed long non-coding RNAs (lncRNAs) in non-small cell lung cancer (NSCLC) cells with acquired resistance to osimertinib and explore their roles in drug resistance of the cells. The cell lines H1975_OR and HCC827_OR with acquired osimertinib resistance were derived from their osimertinib-sensitive parental NSCLC cell lines H1975 and HCC827, respectively, and their sensitivity to osimertinib was assessed with CCK-8 assay, clone formation assay and flow cytometry. RNA sequencing (RNA-seq) and real-time quantitative PCR (qPCR) were used to screen the differentially expressed lncRNAs in osimertinib-resistant cells. The role of the identified lncRNA in osimertinib resistance was explored using CCK-8, clone formation and Transwell assays, and its subcellular localization and downstream targets were analyzed by nucleoplasmic separation, bioinformatics analysis and qPCR. The resistance index of H1975_OR and HCC827_OR cells to osimertinib was 598.70 and 428.82, respectively (P < 0.001), and the two cell lines showed significantly increased proliferation and colony-forming abilities with decreased apoptosis (P < 0.01). RNA-seq identified 34 differentially expressed lncRNAs in osimertinib-resistant cells, and among them lnc-TMEM132D-AS1 showed the highest increase of expression after acquired osimertinib resistance (P < 0.01). Analysis of the TCGA database suggested that the level of lnc-TMEM132D-AS1 was significantly higher in NSCLC than in adjacent tissues (P < 0.001), and its high expression was associated with a poor prognosis of the patients. In osimertinib-sensitive cells, overexpression of Lnc-TMEM132D-AS1 obviously promoted cell proliferation, colony formation and migration (P < 0.05), while Lnc-TMEM132D-AS1 knockdown partially restored osimertinib sensitivity of the resistant cells (P < 0.01). Lnc-TMEM132D-AS1 was localized mainly in the cytoplasm, and bioinformatics analysis suggested that hsa-miR-766-5p was its candidate target, and their expression levels were inversely correlated. The target mRNAs of hsa-miR-766-5p were mainly enriched in the Ras signaling pathway. The expression of lnc-TMEM132D-AS1 is significantly upregulated in NSCLC cells with acquired osimertinib resistance, and may serve as a potential biomarker and therapeutic target for osimertinibresistant NSCLC.

Circular RNA circFBXO7 attenuates non-small cell lung cancer tumorigenesis by sponging miR-296-3p to facilitate KLF15-mediated transcriptional activation of CDKN1A

BackgroundAccumulating evidence indicates that circular RNAs (circRNAs) play important roles in various cancers. Hsa_circ_0008832 (circFBXO7) is a circRNA generated from the second exon of the human F-box only protein 7 (FBXO7). Mouse circFbxo7 is a circRNA generated from the second exon of mouse F-box only protein 7 (Fbxo7). The role of human circFBXO7 and mouse circFbxo7 in non-small cell lung cancer (NSCLC) has not been reported. MethodsThe expression of circFBXO7 was measured by quantitative real-time PCR. Survival analysis was performed to explore the association between the expression of circFBXO7 and the prognosis of patients with NSCLC. Lung cancer cell lines were transfected with plasmids. Cell proliferation, cell cycle, and tumorigenesis were evaluated to assess the effects of circFBXO7. Fluorescence in situ hybridization assay was used to identify the location of circFBXO7 and circFbxo7 in human and mouse lung cancer cells. Luciferase reporter assay was conducted to confirm the relationship between circFBXO7 and microRNA. ResultsIn this study, we found that circFBXO7 was downregulated in NSCLC tissues and cell lines. NSCLC patients with high circFBXO7 expression had prolonged overall survival. Overexpression of circFBXO7 inhibited cell proliferation both in vitro and in vivo. Mechanistically, we demonstrated that circFBXO7 upregulated the expression of miR-296-3p target gene Krüppel-like factor 15 (KLF15) and KLF15 transactivated the expression of CDKN1A. ConclusionsCircFBXO7 acts as a tumor suppressor by a novel circFBXO7/miR-296-3p/KLF15/CDKN1A axis, which may serve as a potential biomarker and therapeutic target for NSCLC.

Postoperative ctDNA detection predicts relapse but has limited effects in guiding adjuvant therapy in resectable stage I NSCLC.

To date, identifying resectable stage I non-small cell lung cancer (NSCLC) patients likely to benefit from adjuvant therapy (ADT) remains a major challenge. Previous studies suggest that circulating tumor DNA (ctDNA) is emerging as a promising biomarker for NSCLC. However, the effectiveness of ctDNA detection in guiding ADT for resectable stage I NSCLC patients remains elusive. This study aimed to elucidate the role of ctDNA detection in estimating prognosis and guiding ADT for resectable stage I NSCLC patients. Individual patient data and ctDNA results data were collected from 270 patients across four independent cohorts. The detection of ctDNA was conducted at 3 days to 1 month after surgery. The endpoint for this study was relapse-free survival (RFS) and overall survival (OS). Of the 270 resectable stage I NSCLC patients, 9 patients with ctDNA-positive and 261 patients with ctDNA-negative. We found that the risk of recurrence was significantly lower in the ctDNA-negative group compared to the ctDNA-positive group(HR=0.11, p<0.0001). However, there is no difference in the risk of death between the two groups (p =0.39). In the ctDNA-positive group, there were no significant differences in RFS between patients who received ADT and patients who did not receive ADT (p =0.58). In the ctDNA-negative group, those who received ADT had a worse RFS in comparison with those who did not receive ADT (HR=2.36, p =0.029). No difference in OS was seen between patients who received ADT and patients who did not receive ADT in both the ctDNA-positive group and the ctDNA-negative group (All p values>0.05). Furthermore, there was no difference in RFS and OS between patients who received chemotherapy-based or tyrosine kinase inhibitor-based ADT and patients who did not receive ADT in both the ctDNA-positive group and the ctDNA-negative group (All p values>0.05). Postoperative ctDNA detection can be a prognostic marker to predict recurrence but has limited effects in guiding ADT for resectable stage I NSCLC. Future prospective investigations are needed to verify these results.

STRIP2 motivates non-small cell lung cancer progression by modulating the TMBIM6 stability through IGF2BP3 dependent

BackgroundStriatin interacting protein 2 (STRIP2) is a core component of the striatin-interacting phosphatase and kinase (STRIPAK) complexes, which is involved in tumor initiation and progression via the regulation of cell contractile and metastasis. However, the underlying molecular mechanisms of STRIP2 in non-small cell lung cancer (NSCLC) progression remain largely unknown.MethodsThe expressions of STRIP2 and IGF2BP3 in human NSCLC specimens and NSCLC cell lines were detected using quantitative RT-PCR, western blotting, and immunohistochemistry (IHC) analyses. The roles and molecular mechanisms of STRIP2 in promoting NSCLC progression were investigated in vitro and in vivo.ResultsHere, we found that STRIP2 expression was significantly elevated in NSCLC tissues and high STRIP2 expression was associated with a poor prognosis. Knockdown of STRIP2 suppressed tumor growth and metastasis in vitro and in vivo, while STRIP2 overexpression obtained the opposite effect. Mechanistically, P300/CBP-mediated H3K27 acetylation activation in the promoter of STRIP2 induced STRIP2 transcription, which interacted with insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) and upregulated IGF2BP3 transcription. In addition, STRIP2-IGF2BP3 axis stimulated m6A modification of TMBIM6 mRNA and enhanced TMBIM6 stability. Consequently, TMBIM6 involved NSCLC cell proliferation, migration and invasion dependent on STRIP2 and IGF2BP3. In NSCLC patients, high co-expression of STRIP2, IGF2BP3 and TMBIM6 was associated with poor outcomes.ConclusionsOur findings indicate that STRIP2 interacts with IGF2BP3 to regulate TMBIM6 mRNA stability in an m6A-dependent manner and may represent a potential prognostic biomarker and therapeutic target for NSCLC.

An explainable AI-driven biomarker discovery framework for Non-Small Cell Lung Cancer classification

Non-Small Cell Lung Cancer (NSCLC) exhibits intrinsic heterogeneity at the molecular level that aids in distinguishing between its two prominent subtypes — Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC). This paper proposes a novel explainable AI (XAI)-based deep learning framework to discover a small set of NSCLC biomarkers. The proposed framework comprises three modules — an autoencoder to shrink the input feature space, a feed-forward neural network to classify NSCLC instances into LUAD and LUSC, and a biomarker discovery module that leverages the combined network comprising the autoencoder and the feed-forward neural network. In the biomarker discovery module, XAI methods uncovered a set of 52 relevant biomarkers for NSCLC subtype classification. To evaluate the classification performance of the discovered biomarkers, multiple machine-learning models are constructed using these biomarkers. Using 10-Fold cross-validation, Multilayer Perceptron achieved an accuracy of 95.74% (±1.27) at 95% confidence interval. Further, using Drug-Gene Interaction Database, we observe that 14 of the discovered biomarkers are druggable. In addition, 28 biomarkers aid the prediction of the survivability of the patients. Out of 52 discovered biomarkers, we find that 45 biomarkers have been reported in previous studies on distinguishing between the two NSCLC subtypes. To the best of our knowledge, the remaining seven biomarkers have not yet been reported for NSCLC subtyping and could be further explored for their contribution to targeted therapy of lung cancer.

Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showed that resting NK cells, activated dendritic cells, and Tregs may be involved in the pathogenesis of NSCLC. Meanwhile, GDF10, NCKAP5, and RTKN2 were negatively correlated with Tregs and naïve B cells but were positively correlated with activated dendritic cells and resting NK cells. Immunohistochemical staining showed that the expression of GDF10, NCKAP5, and RTKN2 in the lung tissue of patients with NSCLC was lower than that of normal lung tissue. qRT-PCR also confirmed that the mRNA expression of three biomarkers in NSCLC cell lines A549 and H1975 were significantly lower than those in human normal lung epithelial cells BEAS-2B. An MTT assay showed that GDF10, NCKAP5, and RTKN2 knockdown significantly promoted the proliferation of A549 and H1975 cells. The in vitro experiments showed that GDF10, NCKAP5, and RTKN2 played the inhibitory effects on NSCLC cell lines proliferation. Hence, GDF10, NCKAP5, and RTKN2 can be used as diagnostic biomarkers for NSCLC.

MiR-124-3p impedes the metastasis of non-small cell lung cancer via extracellular exosome transport and intracellular PI3K/AKT signaling

BackgroundMetastasis is a significant factor that affects the survival of patients with non-small cell lung cancer (NSCLC). Nevertheless, the molecular regulatory mechanism underlying the metastasis is currently not fully understood. This study aims to identify the important role of miR-124-3p in metastasis of NSCLC, thereby providing a potential therapeutic intervention.MethodsExosome secretion was determined by Nanoparticle Tracking Analysis (NTA) and the uptake was measured by fluorescence inverted microscope. The binding mechanism between miR-124-3p and its upstream or downstream target genes was validated experimentally by Luciferase reporter. Cells migration was evaluated by transwell assays. Transcriptome sequencing on A549 was carried out to verify the potential signaling pathway underlying miR-124-3p regulation. Western blotting analysis was used to assess the level of AKT, p-AKT, PI3K, and p-PI3K protein expression in NSCLC cell lines. The role of miR-124-3p to suppress the tumor metastasis was verified in NSCLC xenograft model.ResultsExosomes were more abundant in serum from patients with advanced lung cancer (n = 24 patients) than in these from patients with early-stage lung cancer (n = 30 patients), which suggested the potential correlation between amount of exosome secretion and the metastasis of NSCLC. Interestingly, the exosome release, uptake and the migration of NSCLC cells were notably inhibited by miR-124-3p. LINC00511 suppressed the expression of miR-124-3p to facilitate exosome transport due to its role as the competitive endogenous RNA for miR-124-3p. The miR-124-3p could directly target the 3′-UTR of Rab27a in NSCLC cells to inhibit exosome secretion and thereby prevent cell migration and invasion. Aside from the inhibition of exosome transport, miR-124-3p inhibited the activation of PI3K/AKT signaling in the intracellular environment. Finally, by measuring subcutaneous tumor weight and volume and lung metastasis, we also demonstrated that miR-124-3p inhibited tumor growth in vivo.ConclusionIn NSCLC, miR-124-3p significantly suppressed metastasis through extracellular exosome transport and intracellular PI3K/AKT signaling. These findings provide new insights toward a better understanding of the NSCLC metastasis and suggest a potential treatment biomarker for NSCLC.

Investigation of miR221 and miR222 as Biomarkers in Non-small Cell Lung Cancer.

MicroRNAs (miRNA) are a class of small non-coding RNAs of 18-25 nucleotides, which regulate gene expression at the post-transcriptional level by disrupting or blocking translation of messenger RNA targets. Non-small cell lung cancer (NSCLC) represents approximately 85% of all lung cancers. Early and accurate diagnosis of the disease affects the probability of success of treatment. The purpose of this study was to investigate the expression levels of serum specific miRNA221 and miRNA222 as a biomarker in NSCLC. Thirty-two NSCLC cases and 30 healthy control cases that were diagnosed at Istanbul Yedikule Chest Diseases and Thoracic Surgery Training Hospital were included in this study. miRNAs were detected using miRNA-specific quantitative real-time-PCR. The relative expression of miRNAs was calculated using the 2-ΔΔCt method. miR221 and miR222 showed 1.46 and 1.63-fold higher expression in the samples from patients with NSCLC compared to controls, and the difference of expression was statistically significant for miR221 (p=0.000095) but not for miR222 (p=0.084470). In the presence of metastasis in NSCLC patients, miR221 levels were 2.33-fold higher compared to non-metastatic cases (p=0.014), and those of miR221 and miR222 were expressed 1.44 and 1.52-fold higher, respectively, in advanced stage compared to early stage (p=0.000387, p=0.000302). The levels of miR221 and miR222 in the serum of patients could be used as biomarkers for the diagnosis, treatment, and prognosis of NSCLC.