Lung Cancer Invasion Research Articles

Long Non-coding RNAs: Potential Diagnostic and Treatment Targets for Non-small Cell Lung Cancer

Abstract: Lung cancer is the leading cause of cancer-related deaths globally, necessitating ongoing scientific research to understand its detection, treatment, and prevention. Long non-coding RNAs (lncRNAs) are a diverse group of non-coding RNAs that play crucial roles in regulating tumorigenic processes, such as cell proliferation, invasion, and metastasis in non-small cell lung cancer (NSCLC). Despite not encoding proteins, lncRNAs have significant impacts on the development and progression of NSCLC. Recent evidence suggests that lncRNAs may serve as valuable biomarkers for diagnosing and prognosticating NSCLC through tissue or blood analysis, and as potential therapeutic targets. This review provides a comprehensive overview of recent advancements in lncRNA research for NSCLC, offering new insights into their mechanisms of action and potential therapeutic applications. It also explores promising avenues for therapeutic development. By elucidating the complex roles of lncRNAs in NSCLC, this article aims to contribute to the development of innovative diagnostic and therapeutic strategies that can significantly enhance patient outcomes. Understanding the multifaceted functions of lncRNAs in lung cancer has the potential to lead to substantial progress in early disease detection, targeted treatments, and personalized medicine, ultimately improving the prognosis and quality of life for individuals affected by this devastating disease.

MA08.09 Predictive CT Features of Visceral Pleural Invasion in Lung Cancer with Ground Glass Opacity

MA08.09 Predictive CT Features of Visceral Pleural Invasion in Lung Cancer with Ground Glass Opacity

Activating Invasion and Metastasis in Small Cell Lung Cancer: Role of the Tumour Immune Microenvironmentand Mechanisms of Vasculogenesis, Epithelial-Mesenchymal Transition, Cell Migration, and Organ Tropism.

Small cell lung cancer (SCLC) harbours the most aggressive phenotype of all lung cancers to correlate with its bleak prognosis. The aggression of SCLC is partially attributable to its strong metastatic tendencies. The biological processes facilitating the metastasis in SCLC are still poorly understood and garnering a deeper understanding of these processes may enable the exploration of additional targets against this cancer hallmark in the treatment of SCLC. This narrative review will discuss the proposed molecular mechanisms by which the cancer hallmark of activating invasion and metastasis is featured in SCLC through important steps of the metastatic pathway, and address the various molecular targets that may be considered for therapeutic intervention. The tumour immune microenvironment plays an important role in facilitating immunotherapy resistance, whilst the poor infiltration of natural killer cells in particular fosters a pro-metastatic environment in SCLC. SCLC vasculogenesis is achieved through VEGF expression and vascular mimicry, and epithelial-mesenchymal transition is facilitated by the expression of the transcriptional repressors of E-cadherin, the suppression of the Notch signalling pathway and tumour heterogeneity. Nuclear factor I/B, selectin and B1 integrin hold important roles in SCLC migration, whilst various molecular markers are expressed by SCLC to assist organ-specific homing during metastasis. The review will also discuss a recent article observing miR-1 mRNA upregulation as a potential therapeutic option in targeting the metastatic activity of SCLC. Treatment of SCLC remains a clinical challenge due to its recalcitrant and aggressive nature. Amongst the many hallmarks used by SCLC to enable its aggressive behaviour, that of its ability to invade surrounding tissue and metastasise is particularly notable and understanding the molecular mechanisms in SCLC metastasis can identify therapeutic targets to attenuate SCLC aggression and improve mortality.

Overexpression of NOP58 Facilitates Proliferation, Migration, Invasion, and Stemness of Non-small Cell Lung Cancer by Stabilizing hsa_circ_0001550.

NOP58 ribonucleoprotein (NOP58) is associated with the recurrence of lung adenocarcinoma. Few investigations concentrate on the role of NOP58 in non-small cell lung cancer (NSCLC), which is the focus of our current study. Following transfection, the proliferation, migration, and invasion of NSCLC cells were assessed by 5- ethynyl-2'-deoxyuridine (EdU), wound healing, and transwell assays. The percentage of CD9+ cells was evaluated by flow cytometry assay. Based on target genes and binding sites predicted through bioinformatics analysis, a dual-luciferase reporter assay was performed to verify the targeting relationship between hsa_circ_0001550 and NOP58. The effect of NOP58 overexpression on hsa_circ_0001550 stability was gauged using Actinomycin D. The hsa_circ_0001550 and NOP58 expression levels, as well as protein expressions of CD44, CD133, OCT4, and SOX2 in NSCLC cells were determined by quantitative real-time PCR and Western blot, respectively. Hsa_circ_0001550 was remarkably up-regulated in NSCLC cell lines A549 and PC9, silencing of which weakened cell abilities to proliferate, migrate and invade, decreased CD9+ cell ratio, and diminished protein expressions of CD44, CD133, OCT4, and SOX2. NOP58 could bind to hsa_circ_0001550 and stabilize its expression, and NOP58 overexpression partially abrogated hsa_circ_0001550 knockdown-inhibited NSCLC cell proliferation, migration, invasion and stemness. Overexpression of NOP58 facilitates proliferation, migration, invasion, and stemness of NSCLC cells by stabilizing hsa_circ_0001550, hinting that NOP58 is a novel molecular target for NSCLC therapy.

Prognosis evaluation and efficacy analysis of different treatment options for patients with visceral pleural invasion in stage IIA–IIB lung cancer

ObjectiveControversy surrounds the treatment of visceral pleural invasion in lung cancer, and no studies have compared the efficacy of its four main treatment options (i.e., surgery, chemotherapy, targeted therapy, and immunotherapy). This study aims to compare and analyze surgery, chemotherapy, targeted therapy, and immunotherapy outcomes and explore the optimal treatment of visceral pleural invasion in lung cancer.MethodsWe searched electronic databases (i.e., Pubmed, Embase, Cochrane Library, CNKI, and Chinese Biomedical Literature Database Search) for relevant studies of treatment options for patients with visceral pleural invasion in stage IIA–IIB lung cancer. Searches times were limited to studies published between January 1, 2000 and February 20, 2021. Meta analysis was performed using RevMan 5.3 software We also downloaded original RNA transcription data about lung cancer invasion in the GEO and TCGA tumor databases, and used R 4.0.3 software to perform differential expression and co-expression gene network analyses.ResultsWe included a total of 25 high-quality (i.e., Jadad score 4–7) studies. Meta-analysis found that surgical treatment was associated with a 3-year survival rate OR = 3.80 (95% CI 3.53, 4.09; P < 0.0001), 5-year survival rate OR = 4.10 (95% CI 3.72, 4.53; P < 0.0001), and median survival time OR = 2.71 (95% CI 2.53, 2.89; P < 0.0001). Chemotherapy was associated with a 3-year survival rate OR = 2.08 (95% CI 1.93, 2.25; P < 0.0001), 5-year survival rate OR = 1.68 (95% CI 1.49, 1.89; P < 0.0001), and median survival time OR = 1.84 (95% CI 1.66, 2.04; P < 0.0001). Targeted therapy was associated with a 3-year survival rate OR = 2.91 (95% CI 2.65, 3.19; P < 0.0001), 5-year survival rate OR = 1.83 (95% CI 1.39, 2.33; P < 0.0001), and median survival time OR = 1.76 (95% CI 1.59, 1.94; P < 0.0001). Finally, immunotherapy was associated with a 3-year survival rate OR = 1.89 (95% CI 1.73, 2.07; P < 0.0001), 5-year survival rate OR = 1.66 (95% CI 1.46, 1.88; P < 0.0001), and median survival time OR = 2.53 (95% CI 2.27, 2.82; P < 0.0001). After screening differential genes and co-expressed genes in tumor gene databases, we found that AC245595.1, ITGB1-DT and AL606489.1 may be involved in the process of lung cancer invasion, and macrophages M1 and M2, CD4+-Th1, CD8+-Th1 may participate in immune infiltration.ConclusionsIn patients with visceral pleural invasion of stage IIA-IIB lung cancer, chemotherapy has shown a significant effect on improving prognosis and enhancing efficacy. However, surgical treatment did not significantly improve the overall prognosis. Therefore, the individual situation of the patient and the comprehensive benefits of the treatment program should be fully considered when developing the treatment program.

Role and Therapeutic Potential of P2X7 Receptor in Lung Cancer Progression.

Lung cancer is the second malignant tumor in the world and is the most prevalent malignant tumor of the respiratory system. In lung cancer, the P2X7 receptor (P2X7R) is an important purinergic receptor. P2X7R is a class of ionotropic adenosine triphosphate (ATP)-gated receptors, which exists in many kinds of immune tissues and cells and is involved in tumorigenesis and progression. P2X7R is closely related to lung cancer and is expressed at higher levels in lung cancer than in normal lung tissue. P2X7R plays a critical regulatory function in lung cancer invasion and migration through multiple mechanisms of action and affects the proliferation and apoptosis of cancer cells in the lung. Antagonists of P2X7R can block its function, which in turn has a significant inhibitory effect on lung cancer cell development and progression. This paper details a comprehensive overview of the structure and function of P2X7R. It focuses on the impact and treatment potential of P2X7R in lung cancer invasion, migration, proliferation, and apoptosis, providing new ideas and a new basis for clinical lung cancer treatment and prognosis.

KIFC3 promotes the proliferation, migration and invasion of non-small cell lung cancer through the PI3K/AKT signaling pathway

KIFC3 is a member of the Kinesin superfamily proteins (KIFs). The role of KIFC3 in non-small cell lung cancer (NSCLC) is unknown. This study aimed to elucidate the function of KIFC3 in NSCLC and the underlying mechanism. Immunohistochemistry indicated that KIFC3 was highly expressed in NSCLC tissues and correlated with the degree of differentiation, tumor size, lymph node metastasis and TNM stage. MTT, colony formation and Transwell assays demonstrated that KIFC3 overexpression promoted the proliferation, migration and invasion of NSCLC cells in vitro, while KIFC3 knockdown led to the opposite results. The protein expression levels of PI3Kp85α and p-Akt were increased after KIFC3 overexpression, meanwhile the downstream protein expression levels such as cyclin D1, CDK4, CDK6, RhoA, RhoC and MMP2 were increased. This promotion effect could be inhibited by a specific inhibitor of the PI3K/Akt pathway, LY294002. Co-immunoprecipitation assays confirmed the interaction between endogenous/exogenous KIFC3 and PI3Kp85α. Tumor formation experiments in nude mice confirmed that KIFC3 overexpression promoted the proliferation, migration and invasion of NSCLC cells in vivo and performed its biological function through the PI3K/Akt signaling pathway.In conclusion, KIFC3 promotes the malignant behavior of NSCLC cells through the PI3K/Akt signaling pathway.

Effect of Pterostilbene on Regulating LncRNA-Linc00511 Targeting MiR-184 to Promote the Proliferation and Invasion of Non-Small Cell Lung Cancer Under Hypoxic Environment

Non-small cell lung cancer (NSCLC) is one of the most common lung cancers, accounting for more than 85% of lung cancer incidence rates and seriously endangering human health. Increasing evidence shows that some long non-coding RNAs (lncRNAs) act as tumor suppressors and some promote cancer. Pterostilbene-regulated lncRNA-linc00511 has been confirmed to be an oncogenic gene in a variety of tumors. This study aimed to determine the biological function of pterostilbene-regulated lncRNA-linc00511 (LINC00511) in non-small cell lung cancer and provide new diagnostic and therapeutic targets for it. Lung cancer A549 cells were randomly divided into control group and hypoxic group. siRNA knockdown and LINC00511 overexpression plasmid were constructed under hypoxic conditions. Pterostilbene was used to intervene with lncRNA-linc00511. Real time PCR was used to detect the expression changes of LINC00511 and MiR-184. Analyze and detect the effect on the proliferation and invasion of non-small cell lung cancer cells under hypoxic conditions. Real time PCR analysis was used to detect the expression changes of EMT molecules E-cadherin and Vimentin. Western blot detected changes in HIF-1α expression. The expression of LINC00511 increased and the expression of MiR-184 decreased in lung cancer A549 cells, and hypoxic environment led to more significant changes in both. After siRNA knocked down the expression of LINC00511 under hypoxic conditions, pterostilbene was used to intervene with lncRNA-linc00511. The results showed that it promoted the expression of MiR-184, inhibited the proliferation and invasion of lung cancer cells, upregulated the expression of EMT molecules E-cadherin, and increased the expression of Vimentin. The expression is reduced and the expression of HIF-1α is downregulated. Overexpression of LINC00511 can reverse the above changes. Under hypoxic conditions, pterostilbene was used to interfere with lncRNA-linc00511 to promote cell proliferation in non-small cell lung cancer cells. Pterostilbene’s intervention with lncRNA-linc00511 could target the expression of MiR-184 to promote the proliferation and invasion of non-small cell lung cancer. Knocking down the expression of LINC00511 can target down-regulate the expression of MiR-184, change the occurrence of EMT, and alleviate the occurrence and progression of non-small cell lung cancer.

SLC12A8 promotes the migration and invasion of non-small cell lung cancer (NSCLC) cells.

This study aims to investigate the impacts of SLC12A8 on the invasion, migration, and epithelial-mesenchymal transition (EMT) of non-small cell lung cancer (NSCLC) cells. GEPIA database was employed to examine SLC12A8 expression pattern in lung cancer cells. Subsequently, qRT-PCR and Western blot analyses were conducted to assess SLC12A8 expression in NSCLC tissues and cell lines. The overall prognosis of NSCLC patients was evaluated using Kaplan-Meier plot and univariate and multivariate COX regression curves. The knockdown of SLC12A8 was established using lentivirus-mediated shRNA in A549 and H1299 cells. Cell proliferation, invasion, migration, and apoptosis were evaluated using CCK-8 assay, transwell, and flow cytometry techniques, respectively. Western blot analysis was performed to measure the expression levels of EMT-related proteins (E-cadherin and vimentin). The expression level of SLC12A8 was found to be significantly higher in both NSCLC cell lines and tissues. High SLC12A8 expression was correlated with a poor prognosis in NSCLC patients. Knocking down SLC12A8 led to a significant decrease in proliferation, migration, and invasion abilities, while promoting apoptosis in NSCLC cells. Additionally, SLC12A8 knockdown resulted in decreased levels of N-cadherin and vimentin, along with increased E-cadherin expression. The results indicate that reducing SLC12A8 expression may suppress the malignant phenotype of NSCLC cells, as well as the EMT. SLC12A8 may serve as a target for the clinical management of NSCLC progression.

LVI-PathNet: Segmentation-classification pipeline for detection of lymphovascular invasion in whole slide images of lung adenocarcinoma

Lymphovascular invasion (LVI) in lung cancer is a significant prognostic factor that influences treatment and outcomes, yet its reliable detection is challenging due to interobserver variability. This study aims to develop a deep learning model for LVI detection using whole slide images (WSIs) and evaluate its effectiveness within a pathologist's information system. Experienced pathologists annotated blood vessels and invading tumor cells in 162 WSIs of non-mucinous lung adenocarcinoma sourced from two external and one internal datasets. Two models were trained to segment vessels and identify images with LVI features. DeepLabV3+ model achieved an Intersection-over-Union of 0.8840 and an area under the receiver operating characteristic curve (AUC-ROC) of 0.9869 in vessel segmentation. For LVI classification, the ensemble model achieved a F1-score of 0.9683 and an AUC-ROC of 0.9987. The model demonstrated robustness and was unaffected by variations in staining and image quality. The pilot study showed that pathologists' evaluation time for LVI detecting decreased by an average of 16.95%, and by 21.5% in “hard cases”. The model facilitated consistent diagnostic assessments, suggesting potential for broader applications in detecting pathological changes in blood vessels and other lung pathologies.

A Comprehensive Review of Protein Biomarkers for Invasive Lung Cancer.

Invasion and metastasis are important hallmarks of lung cancer, and affect patients' survival. Early diagnostics of metastatic potential are important for treatment management. Recent findings suggest that the transition to an invasive phenotype causes changes in the expression of 700-800 genes. In this context, the biomarkers restricted to the specific type of cancer, like lung cancer, are often overlooked. Some well-known protein biomarkers correlate with the progression of the disease and the immunogenicity of the tumor. Most of these biomarkers are not exclusive to lung cancer because of their significant role in tumorigenesis. The dysregulation of others does not necessarily indicate cell invasiveness, as they play an active role in cell division. Clinical studies of lung cancer use protein biomarkers to assess the invasiveness of cancer cells for therapeutic purposes. However, there is still a need to discover new biomarkers for lung cancer. In the future, minimally invasive techniques, such as blood or saliva analyses, may be sufficient for this purpose. Many researchers suggest unconventional biomarkers, like circulating nucleic acids, exosomal proteins, and autoantibodies. This review paper aims to discuss the advantages and limitations of protein biomarkers of invasiveness in lung cancer, to assess their prognostic value, and propose novel biomarker candidates.

Cancer-associated fibroblast-derived circFARP1 modulates non-small cell lung cancer invasion and metastasis through the circFARP1/miR-338-3p/SOX4 axis.

The pleiotropic effect of cancer-associated fibroblasts (CAFs) on tumour progression depends on the environment. circFARP1 is critical for CAFs-induced gemcitabine (GEM) resistance in pancreatic cancer. Its specific role and mechanism in non-small cell lung cancer (NSCLC) have not been reported yet. We prepared a cancer-associated fibroblasts-conditioned medium (CAF-CM) to incubate the A549 cells. Quantitative real-time polymerase chain reaction was used to detect RNA levels. We detected protein expression by immunohistochemistry, immunocytochemistry, western blot and immunofluorescence. We also detected the targeting impact between circFARP1, miR-338-3p and SRY-box transcription factor 4 (SOX4) by using dual-luciferase reporter and RNA pull-down assays. We determined cell proliferation, migration and invasion capabilities through Cell Counting Kit-8 and transwell assays. In addition, we measured tumour volume and weight in vivo by establishing a xenograft tumour model. CircFARP1 levels were remarkably high in the CAFs. The transfection experiments found that circFARP1 downregulation in CAFs caused migration, proliferation and invasion inhibition of CAFs and A549 cells, whereas inhibiting miR-38-3p or overexpressing SOX4 in CAFs could significantly reverse the inhibition. In vivo study in nude mice confirmed that CAFs could promote NSCLC tumour growth and knockdown of circFARP1 could inhibit tumour growth of NSCLC, whereas miR-38-3p downregulation or SOX4 overexpression could significantly reverse the inhibition. circFARP1 promotes NSCLC development by stimulating miR-338-3p/SOX4 signalling axis to regulate CAFs.

XRCC2 driven homologous recombination subtypes and therapeutic targeting in lung adenocarcinoma metastasis

Lung adenocarcinoma (LUAD) is a leading cause of cancer mortality, with many patients facing poor prognosis, particularly those with metastatic or drug-resistant tumors. Homologous recombination genes (HRGs) are crucial in tumor progression and therapy resistance, but their clinical significance in LUAD is not well understood. In this study, we systematically characterize key HRGs in LUAD patients, identifying two distinct HR subtypes associated with different outcomes and biological functions. We establish a 5-gene scoring system (XRCC2, RAD51, BRCA1, FANCA, and CHEK1) that reliably predicts patient outcomes and immunotherapy responses in LUAD. Bioinformatics analysis and clinical validation highlight XRCC2 as a crucial biomarker in LUAD. Functional investigations through in vivo and in vitro experiments reveal the role of XRCC2 in promoting lung cancer migration and invasion. Mechanistically, XRCC2 stabilizes vimentin (VIM) protein expression through deubiquitylation. We predict c-MYC as a potential regulator of XRCC2 and demonstrate that inhibiting c-MYC with compound 10058-F4 reduces XRCC2 and VIM expression. Preclinical studies show the synergistic inhibition of metastasis in vivo when combining 10058-F4 with doxorubicin (Dox). Our findings present a potential personalized predictive tool for LUAD prognosis, identifying XRCC2 as a critical biomarker. The c-Myc-XRCC2-VIM axis emerges as a promising therapeutic target for overcoming lung metastasis. This study provides valuable insights into LUAD, proposing a prognostic tool for further clinical validation and unveiling a potential therapeutic strategy for combating lung metastasis by targeting c-Myc-XRCC2-VIM.

MiR-21-5p knockdown inhibits epithelial to mesenchymal transition in A549 lung adenocarcinoma cells by upregulating RhoB.

MiR-21-5p is a highly expressed microRNA that plays an important role in various cancer-promoting processes, including anchorage-independent growth, invasion, migration metastasis, and drug resistance in lung cancer. Studies indicate that miR-21-5p may contribute to these processes by promoting epithelial-mesenchymal transition (EMT). Ras homolog gene family member B (RhoB), a gene downregulated by miR-21-5p, has also been linked to EMT in lung cancer. However, the role of the miR-21-5p/RhoB axis in EMT regulation in lung adenocarcinoma remains unclear. In this study, we aimed to investigate the regulatory role of the miR-21-5p/RhoB axis in EMT and related in vitro functional characteristics such as migration, invasion, cisplatin resistance, and the formation of tumor spheroids. A549 cells were transfected with the miR-21-5p inhibitor, RhoB siRNA, and their corresponding negative controls. Wound healing, transwell invasion, Methyl thiazole tetrazolium (MTT), and sphere formation assays were also performed to evaluate the migration, invasion, cisplatin resistance, and anchorage-independent growth of A549 cells. RT-qPCR was used to determine the mRNA expression levels of EMT markers. MiR-21-5p knockdown inhibited migration, invasion, cisplatin resistance, and sphere formation while upregulating E-cadherin and downregulating Slug. Furthermore, RhoB silencing restored EMT and related in vitro functional characteristics in A549 cells. Knockdown of miR-21-5p inhibits EMT and related in vitro functional characteristics by upregulating RhoB, suggesting that miR-21-5p may promote EMT through downregulation of RhoB.

Combined expert-in-the-loop—random forest multiclass segmentation U-net based artificial intelligence model: evaluation of non-small cell lung cancer in fibrotic and non-fibrotic microenvironments

BackgroundThe tumor microenvironment (TME) plays a key role in lung cancer initiation, proliferation, invasion, and metastasis. Artificial intelligence (AI) methods could potentially accelerate TME analysis. The aims of this study were to (1) assess the feasibility of using hematoxylin and eosin (H&E)-stained whole slide images (WSI) to develop an AI model for evaluating the TME and (2) to characterize the TME of adenocarcinoma (ADCA) and squamous cell carcinoma (SCCA) in fibrotic and non-fibrotic lung.MethodsThe cohort was derived from chest CT scans of patients presenting with lung neoplasms, with and without background fibrosis. WSI images were generated from slides of all 76 available pathology cases with ADCA (n = 53) or SCCA (n = 23) in fibrotic (n = 47) or non-fibrotic (n = 29) lung. Detailed ground-truth annotations, including of stroma (i.e., fibrosis, vessels, inflammation), necrosis and background, were performed on WSI and optimized via an expert-in-the-loop (EITL) iterative procedure using a lightweight [random forest (RF)] classifier. A convolution neural network (CNN)-based model was used to achieve tissue-level multiclass segmentation. The model was trained on 25 annotated WSI from 13 cases of ADCA and SCCA within and without fibrosis and then applied to the 76-case cohort. The TME analysis included tumor stroma ratio (TSR), tumor fibrosis ratio (TFR), tumor inflammation ratio (TIR), tumor vessel ratio (TVR), tumor necrosis ratio (TNR), and tumor background ratio (TBR).ResultsThe model’s overall classification for precision, sensitivity, and F1-score were 94%, 90%, and 91%, respectively. Statistically significant differences were noted in TSR (p = 0.041) and TFR (p = 0.001) between fibrotic and non-fibrotic ADCA. Within fibrotic lung, statistically significant differences were present in TFR (p = 0.039), TIR (p = 0.003), TVR (p = 0.041), TNR (p = 0.0003), and TBR (p = 0.020) between ADCA and SCCA.ConclusionThe combined EITL—RF CNN model using only H&E WSI can facilitate multiclass evaluation and quantification of the TME. There are significant differences in the TME of ADCA and SCCA present within or without background fibrosis. Future studies are needed to determine the significance of TME on prognosis and treatment.

TNNT1 accelerates migration, invasion and EMT progression in lung cancer cells.

Clinically, most patients with lung cancer (LC) die from tumor spread and metastasis. Specific metastasis-related molecules can provide reference for clinical prediction of efficacy, evaluation of prognosis, and search for the best treatment plan. Troponin T1 (TNNT1) is highly expressed in various cancer tissues, which affects malignant behavior of tumor cells and is related to patients' survival and prognosis. However, the role and molecular mechanism of TNNT1 in LC invasion and metastasis have not yet been investigated. Gene expression profiling interactive analysis (GEPIA) online analysis was used to analyze TNNT1 expression in LC tissues. Quantitative real-time-polymerase chain reaction (qRT-PCR) or western blot were performed to measure TNNT1 or epithelial-to-mesenchymal transition (EMT)-related and Wnt/β-catenin pathway-related protein expression in LC cells. After TNNT1 knockdown, cell scratch healing and transwell assays were introduced to assess cell migration and invasion, respectively. TNNT1 expression in LC tissues and cells was increased. TNNT1 knockdown notably impaired LC cell migration, invasion and EMT. TNNT1 knockdown inhibited Wnt/β-catenin pathway of LC cells. Lithium chloride (LiCl) addition partially restored the inhibition of TNNT1 knockdown on migration, invasion, EMT and Wnt/β-catenin of LC cells. TNNT1 knockdown attenuated LC migration, invasion and EMT, possibly through Wnt/β-catenin signaling.

CBX8 Promotes Epithelial-mesenchymal Transition, Migration, and Invasion of Lung Cancer through Wnt/β-catenin Signaling Pathway.

Lung cancer (LC) is primarily responsible for cancer-related deaths worldwide. Epithelial-mesenchymal transition (EMT) is a process in which epithelial cells acquire mesenchymal features and is associated with the development of tumors. CBX8, a member of the PcG protein family, plays a critical role in various cancers, containing LC. However, specific regulatory mechanisms of CBX8 in LC progression are not fully understood. This study aimed to investigate the regulatory role of CBX8 in LC progression. Bioinformatics was used to analyze the relationship between CBX8 level and tumor and the enrichment pathway of CBX8 enrichment. qRT-PCR was used to detect the differential expression of CBX8 in LC cells and normal lung epithelial cells. The effects of knockdown or overexpression of CBX8 on the proliferation, migration and invasion of LC cells were evaluated by CCK- -8 assay and Transwell assay, and the levels of proteins associated with the EMT pathway and Wnt/ β-catenin signaling pathway were detected by western blot. Bioinformatics analysis revealed that CBX8 was highly expressed in LC and enriched on the Wnt/β-catenin signaling pathway. The expression level of CBX8 was significantly elevated in LC cells. Knockdown of CBX8 significantly inhibited cell proliferation, migration and invasion, and decreased the expression levels of EMT-related proteins and Wnt/β-catenin pathway-related proteins. Conversely, overexpression of CBX8 promoted cell proliferation, migration and invasion, and increased the expression levels of EMT-related proteins and Wnt/β-catenin pathway-related proteins. The Wnt inhibitor IWP-4 alleviated the effects produced by overexpression of CBX8. Collectively, these data demonstrated that CBX8 induced EMT through Wnt/β-- catenin signaling, driving migration and invasion of LC cells.

Remodelin delays non-small cell lung cancer progression by inhibiting NAT10 via the EMT pathway.

Lung cancer remains the foremost reason of cancer-related mortality, with invasion and metastasis profoundly influencing patient prognosis. N-acetyltransferase 10 (NAT10) catalyzes the exclusive N (4)-acetylcytidine (ac4C) modification in eukaryotic RNA. NAT10 dysregulation is linked to various diseases, yet its role in non-small cell lung cancer (NSCLC) invasion and metastasis remains unclear. Our study delves into the clinical significance and functional aspects of NAT10 in NSCLC. We investigated NAT10's clinical relevance using The Cancer Genome Atlas (TCGA) and a group of 98 NSCLC patients. Employing WB, qRT-PCR, and IHC analyses, we assessed NAT10 expression in NSCLC tissues, bronchial epithelial cells (BECs), NSCLC cell lines, and mouse xenografts. Further, knockdown and overexpression techniques (siRNA, shRNA, and plasmid) were employed to evaluate NAT10's effects. A series of assays were carried out, including CCK-8, colony formation, wound healing, and transwell assays, to elucidate NAT10's role in proliferation, invasion, and metastasis. Additionally, we utilized lung cancer patient-derived 3D organoids, mouse xenograft models, and Remodelin (NAT10 inhibitor) to corroborate these findings. Our investigations revealed high NAT10 expression in NSCLC tissues, cell lines and mouse xenograft models. High NAT10 level correlated with advanced T stage, lymph node metastasis and poor overall survive. NAT10 knockdown curtailed proliferation, invasion, and migration, whereas NAT10 overexpression yielded contrary effects. Furthermore, diminished NAT10 levels correlated with increased E-cadherin level whereas decreased N-cadherin and vimentin expressions, while heightened NAT10 expression displayed contrasting results. Notably, Remodelin efficiently attenuated NSCLC proliferation, invasion, and migration by inhibiting NAT10 through the epithelial-mesenchymal transition (EMT) pathway. Our data underscore NAT10 as a potential therapeutic target for NSCLC, presenting avenues for targeted intervention against lung cancer through NAT10 inhibition.

Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology.

This study aimed to assess the efficiency of artificial intelligence (AI) in the detection of visceral pleural invasion (VPI) of lung cancer using high-resolution computed tomography (HRCT) images, which is challenging for experts because of its significance in T-classification and lymph node metastasis prediction. This retrospective analysis was conducted on preoperative HRCT images of 472 patients with stage I non-small cell lung cancer (NSCLC), focusing on lesions adjacent to the pleura to predict VPI. YOLOv4.0 was utilized for tumor localization, and EfficientNetv2 was applied for VPI prediction with HRCT images meticulously annotated for AI model training and validation. Of the 472 lung cancer cases (500 CT images) studied, the AI algorithm successfully identified tumors, with YOLOv4.0 accurately localizing tumors in 98% of the test images. In the EfficientNet v2-M analysis, the receiver operating characteristic curve exhibited an area under the curve of 0.78. It demonstrated powerful diagnostic performance with a sensitivity, specificity, and precision of 76.4% in VPI prediction. AI is a promising tool for improving the diagnostic accuracy of VPI for NSCLC. Furthermore, incorporating AI into the diagnostic workflow is advocated because of its potential to improve the accuracy of preoperative diagnosis and patient outcomes in NSCLC.

An exosomes-related lncRNA prognostic model correlates with the immune microenvironment and therapy response in lung adenocarcinoma

Recent research highlights the significance of exosomes and long noncoding RNAs (lncRNAs) in cancer progression and drug resistance, but their role in lung adenocarcinoma (LUAD) is not fully understood. We analyzed 121 exosome-related (ER) mRNAs from the ExoBCD database, along with mRNA and lncRNA expression profiles of TCGA-LUAD using “DESeq2”, “survival,” “ConsensusClusterPlus,” “GSVA,” “estimate,” “glmnet,” “clusterProfiler,” “rms,” and “pRRophetic” R packages. This comprehensive approach included univariate cox regression, unsupervised consensus clustering, GSEA, functional enrichment analysis, and prognostic model construction. Our study identified 134 differentially expressed ER-lncRNAs, with 19 linked to LUAD prognosis. These ER-lncRNAs delineated two patient subtypes, one with poorer outcomes. Additionally, 286 differentially expressed genes were related to these ER-lncRNAs, 261 of which also correlated with LUAD prognosis. We constructed an ER-lncRNA-related prognostic model and calculated an ER-lncRNA-related risk score (ERS), revealing that a higher ERS correlates with poor overall survival in both the Meta cohort and two validation cohorts. The ERS potentially serves as an independent prognostic factor, and the prognostic model demonstrates superior predictive power. Notably, significant differences in the immune landscape were observed between the high- and low-ERS groups. Drug sensitivity analysis indicated varying responses to common chemotherapy drugs based on ERS stratification, with the high-ERS group showing greater sensitivity, except to rapamycin and erlotinib. Experimental validation confirmed that thymidine kinase 1 enhances lung cancer invasion, metastasis, and cell cycle progression. Our study pioneers an ER-lncRNA-related prognostic model for LUAD, proposing that ERS-based risk stratification could inform personalized treatment strategies to improve patient outcomes.