Prognosis Of Non-small Cell Lung Cancer Research Articles

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.

Soluble PD-L1 and Serum Vascular Endothelial Growth Factor-B May Independently Predict Prognosis in Patients with Advanced Non-Small Cell Lung Cancer Treated with Pembrolizumab

Background: Previous preclinical data have shown that the dynamic cross-talk between abnormal tumor vasculature and immune cell factors in the tumor microenvironment may exert a critical role in the progression and treatment resistance of non-small cell lung cancer (NSCLC). In the clinical setting, a variety of blood-based angiogenesis- and immune-related factors are being increasingly investigated as potential biomarkers of prognosis or treatment response in immunotherapy-treated NSCLC. We herein aimed to evaluate the clinical relevance of the peripheral blood levels of vascular endothelial growth factor-A and -B (VEGF-A and VEGF-B, respectively), soluble programmed cell death-1 (sPD-1), and programmed cell death-ligand 1 (sPD-L1) in patients with advanced NSCLC treated with immune checkpoint inhibitors (ICIs). Methods: Consecutive patients with advanced-stage, non-oncogene-addicted NSCLC, eligible to receive ICIs at the Oncology Unit of Sotiria Athens General Hospital, were prospectively recruited. A group of sex- and age-matched healthy controls was also enrolled for the evaluation of the potential diagnostic significance of the examined biomarkers. Serum levels of all biomarkers were measured using ELISA, both before and after treatment, and were correlated with standard clinicopathological features of patients, treatment response, progression-free survival (PFS), and overall survival (OS). Results: A total of 55 patients and 16 healthy controls were included in the final analysis. The mean age of patients and controls was 66.5 years (SD = 8.0 years) and 65.4 years (SD = 9.1 years), respectively. The majority of patients (65.5%) received pembrolizumab in combination with chemotherapy, while the remaining patients received pembrolizumab monotherapy. ROC curve analysis showed that VEGFB and sPD-1 were the only markers with a significant diagnostic value. Higher pre-treatment values of sPD-L1 (HR = 1.68; p = 0.040) and sPD-1 (HR = 10.96; p = 0.037) as well as higher post-treatment values of VEGF-B (HR = 2.99; p = 0.049) were all significantly associated with a reduced OS in univariate Cox regression analysis. The adverse prognostic significance of higher pre-treatment values of sPD-L1 (HR = 2.10; p = 0.014) and higher post-treatment values of VEGFB (HR = 3.37; p = 0.032) was further confirmed in multivariate analysis. Conclusions: Our study results suggest that serum levels of sPD-L1 and VEGF-B may independently predict prognosis in ICI-treated advanced-stage NSCLC.

Characterization of the genomic landscape in liver oligometastatic NSCLC

ObjectivesEmerging data have shown that local treatment could provide clinical benefit for non-small cell lung cancer (NSCLC) patients with oligometastasis. Liver metastases have the worst prognosis in advanced NSCLC, but the genomic characteristics of liver oligometastasis remain unclear. The aim of our study was to elucidate the molecular features of liver oligometastatic NSCLC.MethodsPaired liver metastatic tissue samples and peripheral blood from 32 liver oligometastatic NSCLC patients were concurrently collected for comprehensive genomic analysis using next-generation sequencing.ResultsA total of 206 mutated genes in 32 patients were detected, with a median of 4 mutations per sample. The most frequent alterations (> 10%) in liver oligometastasis were TP53 (72%), EGFR (50%), RB1 (19%) and SMARCA4 (12%). The co-occurrence rate of TP53 and RB1 in our cohort was significantly higher than that in the TCGA-LUAD cohort. Age, APOBEC, homologous recombination deficiency (HRD) and deficient mismatch repair (dMMR) established the mutational signature of liver oligometastatic NSCLC. The median tumor mutation burden (TMB) was 4.8 mutations/Mb. A total of 78.12% patients harbored at least one potentially actionable molecular alteration that may guide further targeted therapy according to the OncoKB evidence.ConclusionsOur study comprehensively delineated the genomic characteristics of liver oligometastatic NSCLC - such findings were helpful to better understand the distinct clinic-biological features of oligometastasis and optimize personalized treatment of this population.

Comprehensive analysis pinpoints CCNA2 as a prognostic and immunological biomarker in non-small cell lung cancer

BackgroundLung cancer is a leading cause of morbidity and mortality globally. Despite advances in targeted and immunotherapies, overall survival (OS) rates remain suboptimal. Cyclin-A2 (CCNA2), known for its upregulation in various tumors and role in tumorigenesis, has an undefined function in non-small cell lung cancer (NSCLC).MethodsWe analyzed three microarray datasets from the Gene Expression Omnibus (GEO) repository to identify differentially expressed genes. Using STRING, we constructed a protein-protein interaction (PPI) network to pinpoint hub genes. The expression and prognostic relevance of CCNA2 were validated using GEPIA and the Kaplan-Meier plotter. Clinicopathological correlations were assessed via the Human Protein Atlas (HPA) and UALCAN databases. qRT-PCR and immunohistochemistry (IHC) were performed to validate CCNA2 mRNA and protein levels. Loss-of-function assays in lung cancer cell lines evaluated the biological role of CCNA2. Immune infiltration and single-cell sequencing were also explored.ResultsAnalysis of GSE18842, GSE101929, and GSE116959 datasets identified 321 upregulated and 623 downregulated genes in NSCLC. CCNA2 was confirmed to be highly expressed in NSCLC through qRT-PCR and IHC, with overexpression correlating with advanced pathological stages and lymph node metastasis. The area under the curve (AUC) of CCNA2 indicating high diagnostic accuracy. Immune infiltration and single-cell sequencing revealed that CCNA2 expression was significantly associated with immune cell infiltration, particularly in Tprolif cells.ConclusionCCNA2 is upregulated in NSCLC and shows significant correlation with clinicopathological characteristics. Our findings suggest that CCNA2 may serve as a promising biomarker for both the prognosis and diagnosis of NSCLC.

Anti-Inflammatory and Anti-Migratory Effects of Morin on Non-Small-Cell Lung Cancer Metastasis via Inhibition of NLRP3/MAPK Signaling Pathway.

Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths globally, with a persistently low five-year survival rate of only 14-17%. High rates of metastasis contribute significantly to the poor prognosis of NSCLC, in which inflammation plays an important role by enhancing tumor growth, angiogenesis, and metastasis. Targeting inflammatory pathways within cancer cells may thus represent a promising strategy for inhibiting NSCLC metastasis. This study evaluated the anti-inflammatory and anti-metastatic properties of morin, a bioactive compound derived from a Thai medicinal herb, focusing on its effects on NLRP3 inflammasome-mediated pathways in an in vitro NSCLC model. The A549 and H1299 cell lines were stimulated with lipopolysaccharide (LPS) and adenosine triphosphate (ATP) to activate the NLRP3 pathway. The inhibition effects exhibited by morin in reducing pro-inflammatory secretion in LPS- and ATP-stimulated NSCLC cells were assessed by ELISA, while wound healing and trans-well invasion assays evaluated its impact on cell migration and invasion. RT-qPCR measurement quantified the expression of inflammatory genes, and zymography and Western blotting were used to examine changes in invasive protein levels, epithelial-to-mesenchymal transition (EMT) markers, and underlying molecular mechanisms. Our findings demonstrated the significant ability of morin to decrease the production of IL-1β, IL-18, and IL-6 in a dose-dependent manner (p < 0.05), as well as suppress NSCLC cell migration and invasion. Morin downregulated invasive proteins (MMP-2, MMP-9, u-PAR, u-PA, MT1-MMP) and EMT markers (fibronectin, N-cadherin, vimentin) (p < 0.01) while also reducing the mRNA levels of NLRP3, IL-1β, IL-18, and IL-6. Mechanistic investigations revealed that morin suppressed NLRP3 inflammasome activity and inactivated MAPK pathways. Specifically, it decreased the expression of NLRP3 and ASC proteins and reduced caspase-1 activity, while reducing the phosphorylation of ERK, JNK, and p38 proteins. Collectively, these findings suggest that morin's inactivation of the NLRP3 inflammasome pathway could offer a novel therapeutic strategy for counteracting pro-tumorigenic inflammation and metastatic progression in NSCLC.

Estrogen, estrogen receptor and the tumor microenvironment of NSCLC

AbstractLung cancer remains the foremost cause of cancer‐related mortality worldwide. Clinical observations reveal a notable increase in both the proportion and mortality rate among female non‐small cell lung cancer (NSCLC) patients compared to males, a trend that continues to escalate. Extensive preclinical research underscores the pivotal role of estrogen in the initiation, progression, prognosis, and treatment response of NSCLC. Estrogen receptors are widely expressed in stromal and immune cells, influencing cellular activities across innate and adaptive immune systems. Immune evasion mechanisms significantly impact tumor development and outcomes, with immunotherapy offering promise in NSCLC by targeting these mechanisms. The intriguing gender disparities in immunotherapy responses prompt an exploration into the data on NSCLC occurrence, progression, and gender‐specific immunotherapy. Evidence highlights estrogen's contribution to a tumor‐permissive microenvironment, influencing various cells including cancer‐associated fibroblasts, macrophages, neutrophils, dendritic cells, natural killer cells, B cells, and T cells. Gender‐specific variations in NSCLC occurrence, development, prognosis, and treatment efficacy likely stem from interactions between estrogen, lung cancer cells, and these estrogen‐responsive cells, shaping a microenvironment conducive to tumor progression. Clarifying estrogen's role and its signaling pathways in NSCLC may unveil novel therapeutic strategies to modify the tumor microenvironment or enhance immunotherapy efficacy.

The Role of Pentacyclic Triterpenoids in Non-Small Cell Lung Cancer: The Mechanisms of Action and Therapeutic Potential.

Lung cancer remains a major global health problem because of its high cancer-related mortality rate despite advances in therapeutic approaches. Non-small cell lung cancer (NSCLC), a major subtype of lung cancer, is more amenable to surgical intervention in its early stages. However, the prognosis for advanced NSCLC remains poor, owing to limited treatment options. This underscores the growing need for novel therapeutic strategies to complement existing treatments and improve patient outcomes. In recent years, pentacyclic triterpenoids, a group of natural compounds, have emerged as promising candidates for cancer therapy due to their anticancer properties. Pentacyclic triterpenoids, such as lupeol, betulinic acid, betulin, oleanolic acid, ursolic acid, glycyrrhetinic acid, glycyrrhizin, and asiatic acid, have demonstrated the ability to inhibit cell proliferation and angiogenesis, induce apoptosis, suppress metastasis, and modulate inflammatory and immune pathways in NSCLC cell line models. These compounds exert their effects by modulating important signaling pathways such as NF-κB, PI3K/Akt, and MAPK. Furthermore, advances in drug delivery technologies such as nanocarriers and targeted delivery systems have improved the bioavailability and therapeutic efficacy of triterpenoids. However, despite promising preclinical data, rigorous clinical trials are needed to verify their safety and efficacy. This review explores the role of triterpenoids in NSCLC and therapeutic potential in preclinical models, focusing on their molecular mechanisms of action.

Circulating TERT serves as the novel diagnostic and prognostic biomarker for the resectable NSCLC

BackgroundTelomerase reverse transcriptase (TERT) is a catalytic subunit of telomerase and required for cancer development. This study aims to reveal its clinical utility for diagnosis and prognosis of resectable NSCLC.MethodsTERT was quantitatively evaluated by the enzyme-linked immunosorbent assay (ELISA) from 69 patients before and after the surgery. The prognostic value was evaluated by disease-free survival (DFS) and overall survival (OS).ResultsCirculating TERT in NSCLC patients were significantly higher than that in the healthy group, possessing the AUC of 0.90. Importantly, TERT change between pre- and post- operation was significantly correlated with OS and DFS (p = 0.022, p = 0.046 respectively), acted as the independent prognostic factors for DFS and OS, indicating it can serve as the promising diagnostic and prognostic biomarker for resectable non-small cell lung cancer (NSCLC).ConclusionsTERT change between pre- and post- resection can serve as the promising biomarker for prognosis of resectable NSCLC.

Comprehensive analysis of the prognostic and immunological role of cavins in non-small cell lung cancer

Caveolae, specialized and dynamic subdomains of the plasma membrane, have a crucial role in diverse cellular functions encompassing endocytosis, signal transduction, mechanosensation, lipid storage, and metabolism. Cavin family proteins are indispensable for caveolar formation and function. An increasing number of studies have found that cavins are involved in tumor growth, invasion, metastasis, and angiogenesis and may have dual roles in the regulation of cancer. However, the expression and prognostic value of cavins in non-small cell lung cancer (NSCLC) remain unexplored. In this study, the expression, survival data, immune infiltration, and functional enrichment of cavins in patients with NSCLC were investigated using multiple databases. Furthermore, different subtypes of cavin-binding proteins were identified through protein-protein interaction networks and k-means clustering. The results showed that the expression of Cavin-1–3 in NSCLC tissues was significantly lower than that in normal tissues, and that Cavin-2 is the major subtype of cavin that inhibits NSCLC progression. It regulates downstream signaling pathways, modulates the infiltration of immune cells and influences the prognosis of NSCLC. Related experiments also confirmed that Cavin-2 promotes the proliferation and metastasis of NSCLC cells. These findings suggest that cavins and their binding proteins may be novel biomarkers for NSCLC prognosis and immunotherapy, providing new treatment options for NSCLC.

Construction of a prognostic model based on cuproptosis-related genes and exploration of the value of DLAT and DLST in the metastasis for non-small cell lung cancer.

To reveal the clinical value of cuproptosis-related genes on prognosis and metastasis in non-small cell lung cancer. Gene expression profiles and clinical information of non-small cell lung cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The data were grouped into training set, internal testing set, and external testing set. A risk prognostic model was constructed by Lasso-Cox regression analysis. Hub genes were identified and evaluated using immunohistochemistry and the transwell migration assay in 50 clinical patients. A total of 17/19 cuproptosis-related genes were differentially expressed in tumors, 8 were significantly associated with prognosis, and 4 were markedly associated with metastasis. A risk model based on 2 cuproptosis-related genes was constructed and validated for predicting overall survival. The risk score was proven to be an independent risk factor for the prognosis of non-small cell lung cancer. Dihydrolipoamide S-acetyltransferase and dihydrolipoamide S-succinyltransferase, key genes in cuproptosis, were proven to be associated with non-small cell lung cancer prognosis and metastasis. Immunohistochemistry showed that their expression significantly predicted metastasis but failed to predict prognosis in non-small cell lung cancer patients. The transwell migration assay further increased the cellular reliability of our findings. The cuproptosis-related genes prognostic model effectively predicted the prognosis of non-small cell lung cancer. Dihydrolipoamide S-acetyltransferase and dihydrolipoamide S-succinyltransferase may serve as predictive markers for metastasis in non-small cell lung cancer.

Identification of gene signatures relevant to the efficacy of immune checkpoint inhibitors in non-small cell lung cancer.

Despite significant advancements in the treatment of non-small cell lung cancer (NSCLC) through immunotherapy, many patients still exhibit resistance to this approach. This study aims to identify the characteristics of individuals who can benefit from immunotherapy, especially immune checkpoint inhibitors (ICIs), and to investigate optimal strategies for patients who experience resistance to it. Data on gene expression patterns and clinical information from NSCLC patients who underwent immunotherapy were obtained from the Gene Expression Omnibus databases. A predictive signature for immunotherapy prognosis was developed using a training dataset and validated with validation datasets. Immune landscape and immunotherapy responsiveness analyses were conducted to assess the risk signature. Additionally, data from a study on immunotherapy were used to evaluate the correlation between MNX1 mutation and the effectiveness of ICIs, including clinical data and whole exome sequencing data. We identified 7 genes in NSCLC using RNA-seq data that were significantly associated with the efficacy of immunotherapy. Based on these genes, a risk signature was created to predict the efficacy of ICIs. Patients in the low-risk group had better outcomes compared to those in the high-risk group after receiving ICIs. Additionally, our analysis of the immune landscape revealed a significant association between the high-risk signature and an immunosuppressive state. We also discovered an unexpected role of tumor-specific MNX1 and HOXD1 in suppressing the immune response against cancer. Notably, NSCLC patients with MNX1 mutations experienced prolonged progression-free survival. Furthermore, we identified several medications that exhibited increased sensitivity in patients with high MNX1 expression, with topoisomerase inhibitors showing the highest level of sensitivity. This could be a potential strategy to improve the efficacy of ICIs. The risk signature has demonstrated its effectiveness in forecasting the prognosis of NSCLC treated with ICIs, enabling better patient stratification and more accurate prediction of immunotherapy response. Moreover, MNX1 and HOXD1 have been identified as key molecules related to immunotherapy resistance. Inhibition of these molecules, combined with current ICIs, offers novel strategies for the management of NSCLC patients.

Daidzein Inhibits Non-small Cell Lung Cancer Growth by Pyroptosis.

Non-Small-Cell Lung Cancer (NSCLC) represents the leading cause of cancer deaths in the world. We previously found that daidzein, one of the key bioactivators in soy isoflavone, can inhibit NSCLC cell proliferation and migration, while the molecular mechanisms of daidzein in NSCLC remain unclear. We developed an NSCLC nude mouse model using H1299 cells and treated the mice with daidzein (30 mg/kg/day). Mass spectrometry analysis of tumor tissues from daidzein-treated mice identified 601 differentially expressed proteins (DEPs) compared to the vehicle-treated group. Gene enrichment analysis revealed that these DEPs were primarily associated with immune regulatory functions, including B cell receptor and chemokine pathways, as well as natural killer cell-mediated cytotoxicity. Notably, the NOD-like receptor signaling pathway, which is closely linked to pyroptosis, was significantly enriched. Further analysis of key pyroptosis-related molecules, such as ASC, CASP1, GSDMD, and IL-1β, revealed differential expression in NSCLC versus normal tissues. High levels of ASC and CASP1 were associated with a favorable prognosis in NSCLC, suggesting that they may be critical effectors of daidzein's action. In NSCLC-bearing mice treated with daidzein, RT-qPCR and Western blot analyses showed elevated mRNA and protein levels of ASC, CASP1, and IL-1β but not GSDMD, which was consistent with the proteomic data. In summary, this study demonstrated that daidzein inhibits NSCLC growth by inducing pyroptosis. Key pathway modulators ASC, CASP1, and IL-1β were identified as primary targets of daidzein. These findings offer insights into the molecular mechanisms underlying the anti-NSCLC effects of daidzein and could offer dietary recommendations for managing NSCLC.

The Clinical Significance and Prognostic Value of ALDH1 Expression in Non-small Cell Lung Cancer: A Systematic Review and Meta-analysis.

The results of the association between aldehyde dehydrogenase 1 (ALDH1) expression and prognosis of non-small cell lung cancer (NSCLC) are contradictory. We conducted this meta-analysis to investigate the clinical significance and prognostic value of ALDH1 in NSCLC. The databases PubMed, Web of Science, EMBASE, the Cochrane Library, Wanfang, and CNKI were systematically queried to identify eligible studies. The retrieval time was from database establishment to August 2023. We evaluated the correlation between ALDH1 expression and clinical features of NSCLC by employing odds ratios (ORs) and 95% confidence intervals (95% CIs). In addition, we used hazard ratios (HRs) and 95% CIs to evaluate the role of ALDH1 expression in the prognosis of NSCLC. Our study included 21 literatures involving 2721 patients. The expression of ALDH1 in NSCLC was higher than that in normal tissues (OR = 6.04, 95% CI: 1.25-29.27, P = 0.026). The expression of ALDH1 was related to TNM stage (OR = 1.81, 95% CI: 1.06-3.09, P = 0.029), tumor grade (OR = 0.29, 95% CI: 0.17-0.48, P < 0.0001), lymph node metastasis (OR = 2.60, 95% CI: 1.52-4.45, P = 0001) and histological subtype (OR = 0.67, 95% CI: 0.52-0.86, P = 0.002). In patients with NSCLC, we found that the over-expression of ALDH1 was significantly associated with poor overall survival (OS) (HR = 1.44, 95% CI: 1.15-1.81, P = 0.002) and disease-free survival (DFS) (HR = 1.74, 95% CI: 1.45-2.10, P < 0.0001). The expression of ALDH1 is closely associated with the clinicopathologic characteristics and prognosis of NSCLC. ALDH1 may serve as a valuable clinical assessment tool and prognostic predictor in NSCLC.

COX-2 in lung cancer: Mechanisms, development, and targeted therapies.

Lung cancer (LC) is the leading cause of cancer-related death worldwide, with non-small cell lung cancer (NSCLC) comprising 85% of all cases. COX-2, an enzyme induced significantly under stress conditions, catalyzes the conversion of free arachidonic acid into prostaglandins. It exhibits high expression in various tumors and is closely linked to LC progression. COX-2 functions as a pivotal driver in cancer pathogenesis by promoting prostaglandin E2synthesis and facilitating tumor cell occurrence and development. Furthermore, COX-2 holds potential as a predictive marker for early-stage NSCLC, guiding targeted therapy in patients with early COX-2 overexpression. Additionally, combining COX-2 inhibitors with diverse treatment modalities enhances tumor therapeutic efficacy, minimizes adverse effects on healthy tissues, and improves overall patient survival rates posttreatment. In conclusion, combined therapy targeting COX-2 presents a promising novel strategy for NSCLC treatment, offering avenues for improving prognosis and effective tumor treatment. This review provides novel insights and ideas for developing new treatment strategies to improve the prognosis of NSCLC.

Construction of a cuproptosis-tricarboxylic acid cycle-associated lncRNA model to predict the prognosis of non-small cell lung cancer.

In cuproptosis, excess copper ions induce cell death via fatty acylation in the tricarboxylic acid (TCA) cycle. However, the effects of cuproptosis-TCA-related long non-coding RNAs (lncRNAs) on the clinical prognosis of non-small cell lung cancer (NSCLC) and the associated tumor microenvironment remain unclear. The purpose of this study is to use cuproptosis-TCA related lncRNAs to predict the prognosis of NSCLC. Molecular signature databases and cuproptosis-related publications were made use of identifying cuproptosis-TCA-related genes. They were identified based on Pearson correlation analysis. The prognostic features associated with these lncRNAs were evaluated using the absolute contraction and selection operator and a receiver operating characteristic curve analysis. Additionally, downstream functional enrichment and immunoinfiltration were analyzed to examine the immunotherapeutic responses of patients with NSCLC. Eleven cuproptosis-TCA-associated lncRNAs were identified. A high-risk group was compared with a low-risk group based on risk scores, and the high-risk group had a significantly lower overall survival (OS). We established a prognostic risk profile, and based on these characteristics and clinical staging, a nomogram was constructed. An analysis of functional enrichment revealed the involvement of pathways associated with cellular and humoral immunity and fatty acylation. Risk scores differed significantly based on immune cells and pathways (antigen-presenting cell co-stimulation). Moreover, TP53, TTN, and MUC16 mutation status were strongly associated with risk scores, with patients identified as having a higher risk of NSCLC being more responsive to immunotherapy. Eleven cuproptosis-TCA-associated lncRNAs can be used to predict the prognosis of NSCLC patients, thereby providing a new theoretical basis for immunotherapy.

Construction and validation of a prognostic model based on oxidative stress-related genes in non-small cell lung cancer (NSCLC): predicting patient outcomes and therapy responses.

Non-small cell lung cancer (NSCLC) is a significant health concern. The prognostic value of oxidative stress (OS)-related genes in NSCLC remains unclear. The study aimed to explore the prognostic significance of OS-genes in NSCLC using extensive datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The research used the expression data and clinical information of NSCLC patients to develop a risk-score model. A total of 74 OS-related differentially expressed genes (DEGs) were identified by comparing NSCLC and control samples. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were employed to identify the prognostic biomarkers. A risk-score model was constructed and validated with receiver operating characteristic (ROC) curves in TCGA and GSE72094 datasets. The model's accuracy was further verified by univariate and multivariate Cox regression. The identified biomarkers, including lactate dehydrogenase A (LDHA), protein tyrosine phosphatase receptor type N (PTPRN), and transient receptor potential cation channel subfamily A (TRPA1) demonstrated prognostic significance in NSCLC. The risk-score model showed good predictive accuracy, with 1-year area under the curves (AUC) of 0.661, 3-year AUC of 0.648, and 5-year AUC of 0.634 in the TCGA dataset, and 1-year AUC of 0.643, 3-year AUC of 0.648, and 5-year AUC of 0.662 in the GSE72094 dataset. A nomogram integrating risk score and tumor node metastasis (TNM) stage was developed. The signature effectively distinguished between patient responses to immunotherapy. High-risk groups were characterized by an immunosuppressive microenvironment and an increased tumor mutational burden (TMB), marked by a higher incidence of mutations in genes such as TP53, DCP1B, ELN, and MAGI2. Organoid drug sensitivity testing revealed that NSCLC patients with a low-risk score responded better to chemotherapy. This study successfully developed a robust model for predicting patient prognosis in NSCLC, highlighting the critical prognostic value of OS-genes. These findings hold significant potential to refine treatment strategies, and enhance survival outcomes for NSCLC patients. By enabling a personalized therapeutic approach tailored to individual risk scores, this model may facilitate more precise decisions concerning immunotherapy and chemotherapy, thereby optimizing patient management and treatment efficacy.

Mutational differences between primary cancer tissue and circulating tumor cells in early-stage non-small cell lung cancer.

Early-stage non-small cell lung cancer (NSCLC) has a high recurrence rate despite proper management, including curative surgery. Circulating tumor cells (CTCs) are believed to play a key role in the distant metastasis of lung cancer. Immunofluorescence imaging studies of CTCs have revealed that they are associated with the prognosis of NSCLC. However, the mutational profiling of CTCs from early-stage NSCLC has not been extensively explored. We hypothesized that CTCs could be detected by mutational analysis using panel sequencing and would have distinct mutations associated with distant metastasis compared to those of primary cancer tissue in early-stage NSCLC. Thus, this study examined the DNA from CTCs using targeted panel sequencing to identify mutations and compared them with mutations found in primary cancer tissue in patients with resectable early-stage NSCLC. Overall, 45 patients with resectable NSCLC were prospectively enrolled from September to December 2023. Matched whole blood samples and primary cancer tissues were collected during curative surgery. Then, 405-gene targeted panel sequencing was performed on DNA from primary cancer tissues and CTCs. In this study, 37 patients (82%) had adenocarcinoma, and 30 (67%) were classified as having pathologic stage 1 disease. Mutated genes were detected in all (100%) and 31 patients (69%) for primary cancer tissue and CTCs from panel sequencing, respectively. The partial concordance rate of mutations between primary cancer tissue and CTCs was 17.8%, with the top 10 mutated genes differing significantly. Among primary cancer tissue samples, mutated genes differed by stage and histologic type; these findings were not observed in CTCs. CTCs predominantly displayed mutations in tumor suppressor genes, whereas primary cancer tissues exhibited mutations in both oncogenes and tumor suppressor genes. CTCs exhibited unique mutations, showing low concordance with mutations found in primary cancer tissue. CTCs may possess specific mutations independent from those of primary cancer tissue in early-stage NSCLC.

Postexercise downregulation of NUP155 in regulating non-small cell lung cancer progression via the PTEN/AKT signaling pathway.

Research interest into regulation of gene expression by physical activity and its effect on cancer prognosis has intensified. This study investigated the role of an exercise-related gene, NUP155, in the progression of non-small cell lung cancer (NSCLC) and its potential as therapy target. Using the GSE41914 dataset, which includes data related to exercise, and the Cancer Genome Atlas (TCGA)-NSCLC dataset, we identified differentially expressed genes (DEGs) and selected NUP155 as a hub gene for further analysis. NUP155 expression levels were measured in NSCLC cell lines and normal lung cells using in vitro assays. The functional roles of NUP155 were investigated through small interfering RNA (siRNA) knockdown experiments, assessing effects on migration, cell proliferation, invasion, and apoptosis. The involvement of the PTEN/AKT signaling pathway was examined using the PTEN inhibitor SF1670. NUP155 was downregulated in postexercise samples and upregulated in NSCLC samples, indicating its association with poor prognosis in NSCLC. Knockdown of NUP155 in NSCLC cell lines resulted in reduced cell viability, migration, and invasion, alongside increased apoptosis. Western blotting revealed that NUP155 knockdown upregulated PTEN levels and downregulated phosphorylated AKT (p-AKT), without altering total AKT levels. The addition of SF1670 partially reversed the effects of NUP155 knockdown, indicating the involvement of the signaling pathway PTEN/AKT in NUP155-mediated tumorigenesis. NUP155 is upregulated in NSCLC, which promotes cell invasion and migration via the PTEN/AKT signaling pathway. Targeting NUP155, potentially influenced by exercise, could be a promising therapy. Combining exercise with targeted treatments may enhance patient outcomes.

RNA binding protein RBM22 suppresses non-small cell lung cancer tumorigenesis by stabilizing LATS1 mRNA.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related mortality worldwide. Despite advancements in diagnostics and therapeutics, the prognosis for NSCLC remains poor, highlighting the urgent need for novel treatment options. RNA binding proteins, particularly RBM22, have emerged as significant contributors to cancer progression by influencing RNA splicing and gene expression. This study investigates the role of RBM22 in NSCLC and its potential as a therapeutic target. We focus on the effects of RBM22 on cell proliferation, invasion, stemness, and its interaction with LATS1 mRNA. RBM22 expression was assessed in samples and cell lines of NSCLC through techniques such as real-time PCR and western blot analysis. To modify RBM22 levels, overexpression and knockdown methods were employed utilizing vectors and siRNAs. We conducted assays for cell proliferation, invasion, and stemness to evaluate the effects of altering RBM22. The interaction between RBM22 and LATS1 mRNA was investigated using RNA immunoprecipitation. In addition, in vivo studies involving subdermal tumor and lung metastasis models in athymic mice were carried out to evaluate how changes in RBM22 influence the tumorigenic and metastatic characteristics of NSCLC. Our analysis revealed a significant underexpression of RBM22 in NSCLC tissues compared to adjacent healthy tissues. Increasing RBM22 expression in NSCLC cell lines led to a marked decrease in cellular proliferation, invasiveness, and stemness, while silencing RBM22 produced opposing effects. Further investigations confirmed that RBM22 directly interacts with LATS1 mRNA, thereby stabilizing and enhancing its expression. In vivo studies validated that elevated RBM22 expression substantially reduced tumor formation and pulmonary metastases, as evidenced by decreased tumor size, mass, and Ki-67 proliferation marker expression, along with a significant reduction in the number of metastatic nodules in the lungs. Our study demonstrates that RBM22 suppresses NSCLC by stabilizing LATS1 mRNA, which in turn reduces tumor growth and metastasis. Consequently, RBM22 emerges as a valuable therapeutic target for NSCLC, offering new strategies for addressing this challenging condition.

Constructing and identifying an eighteen-gene tumor microenvironment prognostic model for non-small cell lung cancer

BackgroundThe tumor microenvironment (TME) plays a crucial role in tumorigenesis and tumor progression. This study aimed to identify novel TME-related biomarkers and develop a prognostic model for patients with non-small-cell lung cancer (NSCLC).MethodsAfter downloading and preprocessing data from The Cancer Genome Atlas (TCGA) data portal and Gene Expression Omnibus (GEO) datasets, we classified the molecular subtypes using the “NMF” R package. We performed survival analysis and quantified immune scores between clusters. A Cox proportional hazards model was then constructed, and its formula was produced. We assessed model performance and clinical utility. A prediction nomogram was also constructed and validated. Additionally, we explored the potential regulatory mechanisms of our TME gene signature using Gene Set Enrichment Analysis (GSEA).ResultsFrom data processing and univariate Cox regression analysis, 57 TME-related prognostic genes were identified, and two significantly distinct clusters were established. Using Cox regression and Lasso regression, an 18-gene TME-related prognostic model was developed. Patients were stratified into high- and low-risk groups based on the risk score, with survival analysis showing that the low-risk group had significantly better outcomes than the high-risk group (P < 0.01). ROC curve analysis demonstrated strong predictive performance, with 1-year, 3-year, and 5-year AUC values ranging from 0.654 to 0.702 across different cohorts. The model accurately predicted survival outcomes across subgroups with varying clinical features, and its predictive accuracy was validated through a nomogram.ConclusionsWe developed a prognostic model based on TME-related genes in NSCLC. Our 18-gene TME signature can effectively predict the prognosis of NSCLC with high accuracy.