Prognosis Of Non-small Cell Lung Cancer Research Articles

An integrated bioinformatics approach to early diagnosis, prognosis and therapeutics of non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the most deadly tumors characterized by poor survival rates. Advances in therapeutics and precise identification of biomarkers can potentially reduce the mortality rate. Thus, this study aimed to identify a set of common and stable gene biomarkers through integrated bioinformatics approaches that might be effective for NSCLC early diagnosis, prognosis, and therapies. Four gene expression profiles (GSE19804, GSE19188, GSE10072, and GSE32863) downloaded from the Gene Expression Omnibus database to identify common differential expressed genes (DEGs). A total of 213 overlapping DEGs (oDEGs) between NSCLC and healthy samples were identified by using statistical LIMMA method. Then 6 common top-ranked key genes (KGs) (CENPF, CAV1, ASPM, CCNB2, PRC1, and KIAA0101) were selected by using four network-measurer methods in the protein– protein interaction network. The GO functional and KEGG pathway enrichment analysis were performed to reveal some significant functions and pathways associated with NSCLC progression. Transcriptional and post-transcriptional factors of KGs were identified through the regulatory interaction network. The prognostic power and expression level of KGs were validated by using the independent data through the Kaplan–Meier and Box plots, respectively. Finally, 4 KGs–guided repositioning candidate drugs (ZSTK474, GSK2126458, Masitinib, and Trametinib) were proposed. The stability of three top-ranked drug-target interactions (CAV1 vs. ZSTK474, CAV1 vs. GSK2126458, and ASPM vs. Trametinib) were investigated by computing their binding free energies for 140 ns MD-simulation based on MM-PBSA approach. Therefore, the findings of this computational study may be useful for early prognosis, diagnosis and therapies of NSCLC.

Sinensetin inhibits the movement ability and tumor immune microenvironment of non-small cell lung cancer through the inactivation of AKT/β-catenin axis.

Although current treatment strategies have improved clinical outcomes of non-small cell lung cancer (NSCLC) patients, side effect and prognosis remain a hindrance. Thus, safer and more effective therapeutical drugs are needed for NSCLC. Sinensetin (Sin) is a flavonoid from citrus fruits, which exhibits antitumor effect on diverse cancers. However, the effect and mechanism of Sin on NSCLC remain unknown. In this study, NSCLC cell lines, and tumor-bearing mice were treated with Sin. The effect and mechanism of Sin were addressed using cell counting kit-8, transwell, enzyme-linked immunosorbent assay, hematoxylin and eosin, immunohistochemistry, and western blot analysis assays in both cell and animal models. Sin reduced the cell viability of A549 and H1299, with the IC50 of 81.46 µM and 93.15 µM, respectively. Sin decreased invaded cell numbers, the expression of N-cadherin and vascular endothelial growth factor A (VEGFA), while increased the E-cadherin level, the cytotoxicity of CD8+ T cells, and the concentration of interferon-γ (IFN-γ), interleukin-2 (IL-2), and tumor necrosis factor-α (TNF-α) in NSCLC cells. Mechanistically, Sin declined the expression of protein kinase B (AKT)/β-catenin pathway, which was restored with the application of SC79, an activator of AKT. The inhibitory role of Sin in NSCLC cell proliferation, invasion, epithelial-mesenchymal transition (EMT) and immune escape was reversed by the management of SC79. In vivo, Sin reduced tumor size and weight, and the expression of N-cadherin, VEGFA, and AKT/β-catenin pathway, but enhanced the level of E-cadherin and IFN-γ. Taken together, Sin suppressed cell growth, invasion, EMT and immune escape via AKT/β-catenin pathway in NSCLC.

Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC.

Most patients with non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the disease, which complicates treatment due to a heightened risk of metastasis. Consequently, the timely identification of biomarkers associated with lymph node metastasis is essential for improving the clinical management of NSCLC patients. In this research, the WGCNA algorithm was utilized to pinpoint genes linked to lymph node metastasis in NSCLC. A cluster analysis was carried out to investigate how these genes correlate with the prognosis and the outcomes of immunotherapy for NSCLC patients. Following this, diagnostic and prognostic models were created and validated through various machine learning methodologies. The random forest technique highlighted the importance of ARHGAP11A, leading to an in-depth examination of its role in NSCLC. By analyzing 78 tissue chip samples from NSCLC patients, the study confirmed the association between ARHGAP11A expression, patient prognosis, and lymph node metastasis. Finally, the influence of ARHGAP11A on NSCLC cells was assessed through cell function experiments. This research utilized the WGCNA technique to identify 25 genes that are related to lymph node metastasis, clarifying their connections with tumor invasion, growth, and the activation of stemness pathways. Cluster analysis revealed significant associations between these genes and lymph node metastasis in NSCLC, especially concerning immunotherapy and targeted treatments. A diagnostic system that combines various machine learning approaches demonstrated strong efficacy in forecasting both the diagnosis and prognosis of NSCLC. Importantly, ARHGAP11A was identified as a key prognostic gene associated with lymph node metastasis in NSCLC. Molecular docking analyses suggested that ARHGAP11A has a strong affinity for targeted therapies within NSCLC. Additionally, immunohistochemical assessments confirmed that higher levels of ARHGAP11A expression correlate with unfavorable outcomes for NSCLC patients. Experiments on cells showed that reducing ARHGAP11A expression can hinder the proliferation, metastasis, and stemness traits of NSCLC cells. This investigation reveals the novel insight that ARHGAP11A may function as a potential biomarker connected to lymph node metastasis in NSCLC. Moreover, reducing the expression of ARHGAP11A has demonstrated the ability to diminish tumor stemness characteristics, presenting a promising opportunity for improving treatment strategies for this condition.

Unraveling the Core Components and Critical Targets of Houttuynia cordata Thunb. in Treating Non-small Cell Lung Cancer through Network Pharmacology and Multi-omics Analysis.

This study aimed to preliminary explore the molecular mechanisms of Houttuynia cordata Thunb. (H. cordata; Saururaceae) in treating non-small cell lung cancer (NSCLC), with the goal of screening drug potential targets for clinical drug development. This study employed a multi-omics and multi-source data integration approach to identify potential therapeutic targets of H. cordata against NSCLC from the TCMSP database, GEO database, BioGPS database, Metascape database, and others. Meanwhile, target localization was performed, and its possible mechanisms of action were predicted. Furthermore, dynamics simulations and molecular docking were used for verification. Multiomics analysis was used to confirm the selected key genes' efficacy in treating NSCLC. A total of 31 potential therapeutic targets, 8 key genes, and 5 core components of H. cordata against NSCLC were screened out. These potential therapeutic targets played a therapeutic role mainly by regulating lipid and atherosclerosis, the TNF signaling pathway, the IL-17 signaling pathway, and others. Molecular docking indicated a stable combination between MMP9 and quercetin. Finally, through multi-omics analysis, it was found that the expression of some key genes was closely related not only to the progression and prognosis of NSCLC but also to the level of immune infiltration. Through comprehensive network pharmacology and multi-omics analysis, this study predicts that the core components of H. cordata play a role in treating NSCLC by regulating lipid and atherosclerosis, as well as the TNF signaling pathway. Among them, the anti-NSCLC activity of isoramanone is reported for the first time.

Serum Exosomal MiR-874 as a Potential Biomarker for Nonsmall Cell Lung Cancer Diagnosis and Prognosis

AbstractLung cancer, primarily nonsmall cell lung cancer (NSCLC), is a leading cause of cancer-related fatalities globally. Due to late detection, the 5-year survival rate for NSCLC remains low. Therefore, the current research aimed to assess the diagnostic and prognostic value of serum exosomal miR-874 levels in NSCLC patients. This study involved 161 NSCLC patients and 80 control subjects. Blood samples were collected from all participants, and serum exosomal MiR-874 levels were quantified using quantitative reverse transcription-polymerase chain reaction. The study revealed a significant decrease in MiR-874 levels among NSCLC patients compared to controls. The receiver operating characteristic analysis demonstrated the diagnostic value of serum exosomal MiR-874 in effectively distinguishing NSCLC patients from controls.Furthermore, associations were observed between serum exosomal MiR-874 expression and adverse clinical factors such as young age, male sex, smoking, high tumor grade, squamous cell carcinoma histopathology, advanced tumor stage, and lymphatic involvement. Patients with high levels of MiR-874 had significantly longer overall and disease-free survival compared to those with lower levels. The study demonstrates that levels of serum exosomal miR-874 are considerably lower in NSCLC patients, indicating its potential as a diagnostic biomarker. The study's findings suggest that the expression of MiR-874 may predict the prognosis of NSCLC patients based on clinical features.

Multiregional transcriptomic profiling provides improved prognostic insight in localized non-small cell lung cancer

Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

Food Aversion, Systemic Inflammation and Intramuscular Adipose Tissue are Mortality Predictors in Advanced Lung Cancer Patients

ABSTRACTBackgroundCancer cachexia, systemic inflammation and muscle wasting are associated with poor survival in non–small cell lung cancer (NSCLC) patients (pts). We hypothesized whether neutrophil‐to‐lymphocyte ratio (NLR) and intramuscular adipose tissue/skeletal muscle index (IMAT/SMI) would predict prognosis in metastatic NSCLC (mNSCLC). In addition, we verified the role of a cancer cachexia questionnaire (EORTC‐QLQ‐CAX24) in the survival prediction.MethodsWe analysed a prospective cohort of 128 treatment‐naive mNSCLC pts (April 2017 to May 2020). We evaluated QoL using the EORTC‐QLQ‐C30 and EORTC‐QLQ‐CAX24 scales. We used the baseline NLR as a surrogate of systemic inflammation. We did evaluate IMAT/SMI using baseline plain computed tomography imaging. Cox multivariate regression, including age, sex, ECOG‐PS and histology as covariates, was performed.ResultsElevated NLR (hazard ratio [HR] 1.26, 95% confidence interval [CI]: 1.01–1.59, p = 0.038), IMAT/SMI ratio (HR 1.37, 95% CI: 1.03–1.84, p = 0.032) and high CAX24 scores for food aversion (HR 1.52, 95% CI: 1.13–2.03, p = 0.006) were associated with worse prognosis in mNSCLC. Indeed, higher ECOG‐PS (Spearman rho = 0.208, p = 0.027), CAX24 scores for food aversion (Spearman rho = 0.197, p = 0.036), loss of control (Spearman rho = 0.212, p = 0.024) and eating and weight loss worry domains (Spearman rho = 0.219, p = 0.020) were associated with elevated NLR levels.ConclusionsElevated NLR, IMAT/SMI ratio and CAX24 score for food aversion are independently associated with worse survival in mNSCLC. These data underscored the importance of cachexia features as negative prognostic factors in mNSCLC and revealed the EORTC‐QLQ‐CAX24 questionnaire as a new tool for helping clinical decision‐making.Trial Registration: ClinicalTrials.gov identifier: NCT03960034 and NCT04306094

The time-to-surgery interval and its effect on pathological response after neoadjuvant chemoimmunotherapy in non-small cell lung cancer: a retrospective cohort study.

The time to surgery (TTS) after the completion of the final cycle of neoadjuvant chemoimmunotherapy in patients with non-small cell lung cancer (NSCLC) is inconsistent. Pathological complete response (pCR) and major pathological response (MPR) are associated with enhanced survival in those with NSCLC. The optimal TTS interval remains to be determined, some studies indicated that TTS ≤6 weeks has a vital role in NSCLC prognosis. Therefore, this study aimed to determine whether TTS is correlated with pathological outcomes and to identify the factors associated with TTS. We retrospectively analyzed 82 individuals who had surgery after neoadjuvant chemoimmunotherapy for NSCLC between January 2020 and December 2023. Fifty participants were included in this study after inclusion and exclusion criteria. Participants were categorized into two groups: TTS ≤4 weeks and TTS >4 to 6 weeks. Univariate and multivariate regression analyses were employed to determine the impact of TTS on pathological response and to identify the variables associated with TTS. Variables that showed their P value <0.2 in univariate analyses were included in the multivariate analysis. Kaplan-Meier analysis was used to analyze disease-free survival (DFS). Our study evaluating 50 patients revealed that patients in the TTS ≤4 weeks group achieved pCR or MPR compared to patients in the >4 to 6 weeks group (P=0.01). In univariate analyses, TTS ≤4 weeks was more correlated with achieving pCR or MPR than TTS >4 to 6 weeks [odds ratio (OR) =0.211; 95% confidence interval (CI): 0.062-0.711; P=0.01] The multivariate analysis showed that cT1 stage (compared to cT4), and cN1 stage (compared to cN0) showed statistical correlation with achieving pCR or MPR. cN1 stage was independent predictor of achieving pCR or MPR (OR =27.817; 95% CI: 1.536-503.88; P=0.02). Concerning to the DFS, TTS ≤4 weeks group and TTS >4 to 6 weeks group showed no statistical differences (2-year DFS rate were 70.6% and 72.6%, respectively). Regarding the tendency of being patients' TTS ≤4 weeks, patients with ventilatory impairment (OR =0.203; 95% CI: 0.04-0.98; P=0.047) were more tending to prolong the TTS to >4 to 6 weeks. TTS ≤4 weeks was associated with a significant improvement of pathological response. Therefore, patients with NSCLC should undergo surgery within 4 weeks after the last cycle of neoadjuvant chemoimmunotherapy.

POSTN promotes the progression of NSCLC via regulating TNFAIP6 expression

Aberrant upregulation of Periostin (POSTN) expression has been implicated in various disease-related pathological cascades, notably inflammatory responses, fibrotic processes and tumor progression, including non-small cell lung cancer (NSCLC). The present study aimed to elucidate the functional role and underlying mechanisms of POSTN in NSCLC. Immunohistochemical and Western blot analysis consistently revealed elevated POSTN levels in NSCLC tissues and cell lines. POSTN expression negatively correlated with patient prognosis. Functional experiments utilizing POSTN-targeting siRNAs demonstrated a significant suppression of NSCLC cell proliferation, migration and invasion, whereas POSTN overexpression via plasmid transfection enhanced these oncogenic properties. Mechanistically, RNA sequencing analysis and subsequent validation studies revealed that POSTN positively modulates the transcriptional expression of tumor necrosis factor alpha-induced protein 6 (TNFAIP6) in NSCLC. Notably, a positive correlation was observed between POSTN and TNFAIP6 expression levels, and their overexpression positively correlated with NSCLC progression. Furthermore, TNFAIP6 overexpression rescued the inhibitory effects of POSTN knockdown on NSCLC malignant phenotypes. Collectively, our findings indicate that POSTN promotes NSCLC malignancy through TNFAIP6 upregulation, positioning POSTN as a promising biomarker and potential therapeutic target for NSCLC prognosis and treatment strategies in clinical settings.

Prognostic value of circulating proteins at diagnosis among patients with lung cancer: a comprehensive analysis by smoking status.

Improved prediction of prognosis among lung cancer patients could facilitate better clinical management. We aimed to study the prognostic significance of circulating proteins at the time of lung cancer diagnosis, among patients with and without smoking history. We measured 91 proteins using the Olink Immune-Oncology panel in plasma samples that were collected at diagnosis from 244 never smoking and 742 ever smoking patients with stage I-IIIA non-small cell lung cancer (NSCLC). Patients were recruited from nine centres in Russian Federation, Poland, Serbia, Czechia, and Romania, between 2007-2016 and were prospectively followed through 2020. We used multivariable Survey-weighted Cox models to assess the relationship between overall survival and levels of proteins by adjusting for smoking, age at diagnosis, sex, education, alcohol intake, histology, and stage. The 5-year survival rate was higher among never than ever smoking patients (63.1% vs. 46.6%, P<0.001). In age- and sex-adjusted survival analysis, 23 proteins were nominally associated with overall survival, but after adjustment for potential confounders and correcting for multiple testing, none of the proteins showed a significant association with overall survival. In stratified analysis by smoking status, IL8 [hazard ratio (HR) per standard deviation (SD): 1.40, 95% confidence interval (CI): 1.18-1.65, P=1×10-4] and hepatocyte growth factor (HGF) (HR: 1.45, 95% CI: 1.18-1.79, P=5×10-4) were associated with survival among never smokers, but no protein was found associated with survival among ever smokers. Integrating proteins into the models with clinical risk factors did not improve the predictive performance of NSCLC prognosis [C-index of 0.63 (clinical) vs. 0.64 (clinical + proteins) for ever smokers, P=0.20; C-index of 0.68 (clinical) vs. 0.72 (clinical + proteins) for never smokers, P=0.28]. We found limited evidence of a potential for circulating immune- and cancer-related protein markers in lung cancer prognosis. Whereas some specific proteins appear to be uniquely associated with lung cancer survival in never smokers.

LncRNA HAR1A inhibits non-small cell lung cancer growth by downregulating c-MYC transcripts and facilitating its proteasomal degradation

Non-small cell lung cancer (NSCLC) is a primary cause of cancer-related mortality on a global scale. Research increasingly shows that long non-coding RNAs (lncRNAs) play crucial regulatory roles and serve as biomarkers for diagnosis, prognosis, therapy monitoring, and druggable targets in NSCLC. We previously identified HAR1A as a tumor-suppressing lncRNA in NSCLC, with its loss also observed in oral and hepatocellular carcinoma. This study aimed to expand the understanding of the functional role of HAR1A in NSCLC and uncover its underlying mechanisms. Our results demonstrated that elevating HAR1A levels impeded NSCLC cell proliferation and migration but promoted apoptosis, thereby boosting their susceptibility to cisplatin. Subsequently, we discovered that HAR1A enhanced cisplatin’s cytotoxicity in NSCLC cells by curbing adaptive autophagy through the downregulation of MYC. Further analysis revealed that HAR1A suppresses MYC by both lowering its transcript levels and promoting protein ubiquitination and degradation, thereby restricting tumor cell proliferation, migration, and adaptive autophagy. In exploring MYC’s targets, we observed that MYC upregulated the transcription of heat shock protein 90 alpha family class B member 1 (HSP90AB1/HSP90β) gene. Rescue experiments verified that HAR1A mitigated NSCLC cell proliferation and migration and induced apoptosis through the MYC/HSP90β axis. Finally, we confirmed that HAR1A overexpression increased cisplatin efficacy in nude mouse NSCLC xenograft models.In conclusion, the findings suggest that HAR1A could be a promising therapeutic target in treating NSCLC and biomarkers for predicting chemotherapy outcomes. This study provides new insights into the molecular mechanisms of chemoresistance in NSCLC and underscores the potential of lncRNA-based strategies in cancer therapy.

FBXO11 Mediates Ubiquitination of ZEB1 and Modulates Epithelial-to-Mesenchymal Transition in Lung Cancer Cells.

Epithelial-to-mesenchymal transition (EMT) affects the invasion and migration of cancer cells. Here, we show that FBXO11 recognizes and promotes ubiquitin-mediated degradation of ZEB1. There is a strong association between FBXO11 and ZEB1 in non-small cell lung cancer (NSLC) in a clinical database. FBXO11 interacts with ZEB1, a core inducer of EMT. FBXO11 leads to increased ubiquitination and proteasomal degradation of ZEB1. Depletion of endogenous FBXO11 causes ZEB1 protein accumulation and EMT in A549 and H1299 cells, while overexpression of FBXO11 reduces ZEB1 protein abundance and cellular invasiveness. Importantly, the depletion of ZEB1 suppresses the increased migration and invasion of A549 and H1299 cells promoted by the depletion of FBXO11. The same results are shown in xenograft tumors. High FBXO11 expression is associated with a favorable prognosis in NSLC. Collectively, our study demonstrates that FBXO11 modulates EMT by mediating the stability of ZEB1 in lung cancer cells.

Detection of serum SNHG22 and its correlation with prognosis of non-small cell lung cancer

BackgroundLung cancer accounts for a significant proportion of cancer-related deaths in China, with the majority of the cases being classified as non-small cell lung cancer (NSCLC). The study aimed to investigate the expression of serum SNHG22 in patients with NSCLC, and its molecular mechanism and prognostic potential in NSCLC.MethodsAdmitted 125 NSCLC patients were selected for the study, along with 125 healthy individuals in the same period. The levels of SNHG22 and miR-128-3p were quantified via RT-qPCR. Correlations between the SNHG22 level and the pathological characteristics of the NSCLC patients were investigated through the application of the chi-square test. The targeting relationship between SNHG22 and miR-128-3p was predicted by online database and confirmed by luciferase activity. The prognostic ability of SNHG22 in NSCLC was assessed by Kaplan-Meier curves and multivariate Cox analysis.ResultsSNHG22 was upregulated in NSCLC and directly targeted miR-128-3p. The rate of overall survival is lower in patients with high-SNHG22 group compared to those with low-SNHG22 group. Silencing SNHG22 impaired the functionality of cells, which was restored by miR-128-3p inhibitor. SNHG22 stands as an independent predictor of poor prognosis in NSCLC patients.ConclusionThe overexpression of SNHG22 in NSCLC is related to lymph node metastasis, TNM stage and patient survival, which is expected to be a prognostic predictor of NSCLC patients.

Peripheral Inflammation Featuring Eosinophilia or Neutrophilia Is Associated with the Survival and Infiltration of Eosinophils within the Tumor among Various Histological Subgroups of Patients with NSCLC.

Immune activation status determines non-small cell lung cancer (NSCLC) prognosis, with reported positive/negative associations for T helper type 2 (TH2) responses, including allergen-specific IgE and eosinophils. Our study seeks to explore the potential impact of these comorbid immune responses on the survival rates of patients with NSCLC. Our retrospective study used data from the Data Warehouse of the German Center for Lung Research (DZL) and Lung Biobank at Thoraxklinik Heidelberg. We estimated the association of blood eosinophilia and neutrophilia on survival rates in an inflammatory cohort of 3143 patients with NSCLC. We also tested sensitization to food and inhalants and high-sensitivity C-reactive protein (hs-CRP) in a comorbidity cohort of 212 patients with NSCLC. Finally, we estimated the infiltration of immune-relevant cells including eosinophils, T-cells, and mast cells in a tissue inflammatory sub-cohort of 60 patients with NSCLC. Sensitization to at least one food or inhalant (sIgE) was higher in patients with adenocarcinoma (adeno-LC) than the non-adenocarcinoma (non-adeno-LC). Furthermore, hs-CRP was higher in non-adeno-LC compared with adeno-LC. Peripheral inflammation, particularly eosinophilia and neutrophilia, was associated with poor survival outcomes in NSCLC with a clear difference between histological subgroups. Finally, blood eosinophilia was paralleled by significant eosinophil infiltration into the peritumoral tissue in the lung. This study provides novel perspectives on the crucial role of peripheral inflammation, featuring eosinophilia and neutrophilia, with overall survival, underscoring distinctions between NSCLC subgroups (adeno-LC vs. non-adeno-LC). Peripheral eosinophilia enhances eosinophil infiltration into tumors. This sheds light on the complex interplay between inflammation, eosinophil infiltration, and NSCLC prognosis among various histological subtypes. Further studies are required to underscore the role of eosinophils in NSCLC among different histological subgroups and their role in shaping the tumor microenvironment.

Current status and quality of prognosis prediction models of non-small cell lung cancer constructed using computed tomography (CT)-based radiomics: a systematic review and radiomics quality score 2.0 assessment.

Radiomics extracts specific quantitative data from medical images and explores the characteristics of tumors by analyzing these representations and making predictions. The purpose of this paper is to review computed tomography (CT)-based radiomics articles related to prognostic outcomes in non-small cell lung cancer (NSCLC), assess their scientificity and quality by the latest radiomics quality score (RQS) 2.0 scoring criteria, and provide references for subsequent related studies. CT-based radiomics studies on NSCLC prognosis published from 1 November 2012 to 30 November 2022 in English were screened through the databases of the Cochrane Library, Embase, and PubMed. By excluding criteria such as non-original studies, small sample sizes studies, positron emission tomography (PET)/CT only, and methodological studies only, 17 studies in English were included. The RQS proposed in 2017 is a quality evaluation index specific to radiomics following the PRISMA guidelines, and the latest update of RQS 2.0 has improved the scientificity and completeness of the score. Each checkpoint either belongs to handcrafted radiomics (HCR), deep learning, or both. The 17 included studies covered most treatments for NSCLC, including radiotherapy, chemotherapy, surgery, radiofrequency ablation, immunotherapy, and targeted therapy, and predicted outcomes such as overall survival (OS), progression-free survival (PFS), distant metastases, and disease-free survival (DFS). The median score rate for the included studies was 28%, with a range of 12% to 44%. The quality of studies in HCR is not high, and only 4 studies have been validated with independent cohorts. The value of radiomics studies needs to be increased, such that clinical application will be possible, and the field of radiomics still has much room for growth. To make prediction models more reliable and stable in forecasting the prognosis of NSCLC and advancing the individualized treatment of NSCLC patients, more clinicians must participate in their development and clinical testing.

CYFRA 21-1 predicts efficacy of combined chemoimmunotherapy in patients with advanced non-small cell lung cancer: a prospective observational study.

Tumor markers such as serum carcinoembryonic antigen (CEA) and cytokeratin fragment 19 (CYFRA 21-1) are utilized for assessing the effectiveness of chemotherapy in non-small cell lung cancer (NSCLC) patients. Yet, it remains uncertain whether these markers can reliably forecast responses to combined chemoimmunotherapy. Our study aimed to examine the significance and effectiveness of these markers in predicting responses among NSCLC patients undergoing combined chemoimmunotherapy. This two-part observational study involved patients with NSCLC who were treated with combined chemoimmunotherapy in Japanese hospitals. An initial retrospective study of these patients, with serum CEA and CYFRA 21-1 as prognostic factors for combined chemoimmunotherapy outcomes, served as a discovery cohort. Patients in a subsequent prospective study served as a validation cohort, where we assessed the prognostic accuracy of CEA and CYFRA 21-1 cut-off points determined by the discovery cohort. In total, 121 patients treated with combined chemoimmunotherapy were included, with 44 and 77 patients in the discovery and validation cohorts, respectively. Serum CYFRA 21-1 levels >3.0 ng/mL were significantly associated with progression-free survival (PFS) in both the discovery and validation cohorts (P=0.01, P=0.04, respectively). PFS did not differ significantly by CEA levels (P=0.21). After combined chemoimmunotherapy treatment, serum CYFRA 21-1 stands out as a potentially valuable biomarker for predicting the prognosis of NSCLC.

Organomics: A Concept Reflecting the Importance of PET/CT Healthy Organ Radiomics in Non-Small Cell Lung Cancer Prognosis Prediction Using Machine Learning.

Non-small cell lung cancer is the most common subtype of lung cancer. Patient survival prediction using machine learning (ML) and radiomics analysis proved to provide promising outcomes. However, most studies reported in the literature focused on information extracted from malignant lesions. This study aims to explore the relevance and additional value of information extracted from healthy organs in addition to tumoral tissue using ML algorithms. This study included PET/CT images of 154 patients collected from available online databases. The gross tumor volume and 33 volumes of interest defined on healthy organs were segmented using nnU-Net deep learning-based segmentation. Subsequently, 107 radiomic features were extracted from PET and CT images (Organomics). Clinical information was combined with PET and CT radiomics from organs and gross tumor volumes considering 19 different combinations of inputs. Finally, different feature selection (FS; 5 methods) and ML (6 algorithms) algorithms were tested in a 3-fold data split cross-validation scheme. The performance of the models was quantified in terms of the concordance index (C-index) metric. For an input combination of all radiomics information, most of the selected features belonged to PET Organomics and CT Organomics. The highest C-index (0.68) was achieved using univariate C-index FS method and random survival forest ML model using CT Organomics + PET Organomics as input as well as minimum depth FS method and CoxPH ML model using PET Organomics as input. Considering all 17 combinations with C-index higher than 0.65, Organomics from PET or CT images were used as input in 16 of them. The selected features and C-indices demonstrated that the additional information extracted from healthy organs of both PET and CT imaging modalities improved the ML performance. Organomics could be a step toward exploiting the whole information available from multimodality medical images, contributing to the emerging field of digital twins in health care.

Comprehensive analysis of Epha10 as a predictor of clinical prognosis and immune checkpoint therapy efficacy in non-small cell lung cancer

The EphA family belongs to a large group of membrane receptor tyrosine kinases. Emerging evidence indicates that the EphA family participates in tumour occurrence and progression. Nonetheless, the expression patterns and prognostic values of the nine EphAs in non-small cell lung cancer (NSCLC) have rarely been studied before. In the current study, we comprehensively analysed the expression and prognostic role of EphA family members by different means. The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis databases were used to investigate the expression of EphAs in NSCLC. The cBioPortal database was applied to analyse the prognostic values and genetic mutations of EphAs.We discovered that the expression of EphA10 was significantly higher in NSCLC tissues than in adjacent noncancerous tissues, and survival analyses showed that a higher level of EphA10 predicted poor prognosis. Further exploration into the role of EphA10 by ESTIMATE, CIBERSORT, and ssGSEA analysis found that it was also related to immune infiltration and higher expression of targets of ICI targets. In conclusion, this study revealed that among the EphA family members, EphA10 played an oncogenic role and was a promising biomarker for poor prognosis and better immunotherapy response in NSCLC.

Research Progress of Circular RNA CircHIPK3 in Non-small Cell Lung Cancer

Lung cancer ranks among the most prevalent and deadliest malignancies worldwide. Despite significant strides in targeted therapies and immunotherapy for lung cancer, curing the disease remains a highly prioritized issue. Circular RNAs (circRNAs), recently discovered RNA molecules characterized by covalently closed loop structures, possess features such as structural stability, sequence conservation, and disease-specific expression. Cutting-edge medical research has linked circRNA dysregulation to the progression of various cancers. Among these, circular RNA HIPK3 (circHIPK3), an oncogenic gene primarily derived from the second exon of the HIPK3 gene, has emerged as a focal point of investigation. Increasing evidences suggest that circHIPK3 is involved in the development of non-small cell lung cancer (NSCLC) and other malignancies. Aberrant expression of circHIPK3 is closely associated with the disease mechanisms, diagnosis, treatment, and prognosis of NSCLC. This review discusses the latest research advancements on circHIPK3 in NSCLC, aiming to promote precise diagnosis and treatment of lung cancer. .

METTL3/IGF2BP1 influences the development of non-small-cell lung cancer by mediating m6A methylation modification of TRPV1.

Methyltransferase 3 (METTL3) accelerates N6-methyladenosine (m6A) modifications and affects cancer progression, including non-small-cell lung cancer (NSCLC). In this study, we aimed to explore the regulatory mechanisms of METTL3 underling NSCLC. Immunohistochemical assay, quantitative real-time polymerase chain reaction (qRT-PCR)assay, and western blot assay were conducted for gene expression. MTT assay and colony formation assay were performed to explore cell proliferation capacity. Cell apoptosis and THP-1 cell polarization were estimated by flow cytometry analysis. Cell migration and invasion capacities were evaluated by transwell assay. Methylated RNA immunoprecipitation assay, dual-luciferase reporter assay, actinomycin D treatment and RIP assay were performed to analyze the relationships of METTL3, insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1), and transient receptor potential cation channel subfamily V member 1 (TRPV1). The functions of METTL3 and TRPV1 in vivo were investigated through establishing the murine xenograft model. TRPV1 expression was upregulated in NSCLC and related poor prognosis. TRPV1 silencing inhibited NSCLC cell growth and metastasis, induced NSCLC cell apoptosis, and repressed M2 macrophage polarization. The results showed that METTL3 and IGF2BP1 could regulate TRPV1 expression through m6A methylation modification. Moreover, METTL3 deficiency inhibited NSCLC cell growth, metastasis, and M2 macrophage polarization and facilitated NSCLC cell apoptosis, while TRPV1 overexpression restored the impacts. In addition, METTL3 knockdown restrained tumor growth in vivo via regulating TRPV1 expression. METTL3 bound to IGF2BP1 and enhanced IGF2BP1's m6A recognition of TRPV1 mRNA, thereby promoting NSCLC cell growth and metastasis, and inhibiting M2 macrophage polarization.