Construction of a prognostic model for lung adenocarcinoma based on m6A/m5C/m1A genes.

BACKGROUND: Developing a prognostic model for lung adenocarcinoma (LUAD) that utilizes m6A/m5C/m1A genes holds immense importance in providing precise prognosis predictions for individuals. METHODS: This study mined m6A/m5C/m1A-related differential genes in LUAD based on public databases, identified LUAD tumor subtypes based on these genes, and further built a risk prognostic model grounded in differential genes between subtypes. The immune status between high- and low-risk groups was investigated, and the distribution of feature genes in tumor immune cells was analyzed using single-cell analysis. Based on the expression levels of feature genes, a projection of chemotherapeutic and targeted drugs was made for individuals identified as high-risk. Ultimately, cell experiments were further verified. RESULTS: The 6-gene risk prognosis model based on differential genes between tumor subtypes had good predictive performance. Individuals classified as low-risk exhibited a higher (P < 0.05) abundance of infiltrating immune cells. Feature genes were mainly distributed in tumor immune cells like CD4+T cells, CD8+T cells, and regulatory T cells. Four drugs with relatively low IC50 values were found in the high-risk group: Elesclomol, Pyrimethamine, Saracatinib, and Temsirolimus. In addition, four drugs with significant positive correlation (P < 0.001) between IC50 values and feature gene expression were found, including Alectinib, Estramustine, Brigatinib, and Elesclomol. The low expression of key gene NTSR1 reduced the IC50 value of irinotecan. CONCLUSION: Based on the m6A/m5C/m1A-related genes in LUAD, LUAD patients were divided into 2 subtypes, and a m6A/m5C/m1A-related LUAD prognostic model was constructed to provide a reference for the prognosis prediction of LUAD.

IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability.

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Early-stage patients have a 30-50% probability of metastatic recurrence after surgical treatment. Here, we propose a new computational framework, Interpretable Biological Pathway Graph Neural Networks (IBPGNET), based on pathway hierarchy relationships to predict LUAD recurrence and explore the internal regulatory mechanisms of LUAD. IBPGNET can integrate different omics data efficiently and provide global interpretability. In addition, our experimental results show that IBPGNET outperforms other classification methods in 5-fold cross-validation. IBPGNET identified PSMC1 and PSMD11 as genes associated with LUAD recurrence, and their expression levels were significantly higher in LUAD cells than in normal cells. The knockdown of PSMC1 and PSMD11 in LUAD cells increased their sensitivity to afatinib and decreased cell migration, invasion and proliferation. In addition, the cells showed significantly lower EGFR expression, indicating that PSMC1 and PSMD11 may mediate therapeutic sensitivity through EGFR expression.

C9orf10/Ossa regulates the bone metastasis of established lung adenocarcinoma cell subline H322L-BO4 in a mouse model.

Lung cancer frequently metastasizes to the bones. An in vivo model is urgently required to identify potential therapeutic targets for the prevention and treatment of lung cancer with bone metastasis. We established a lung adenocarcinoma cell subline (H322L-BO4) that specifically showed metastasis to the leg bones and adrenal glands. This was achieved by repeated isolation of metastatic cells from the leg bones of mice. The cells were intracardially injected into nude mice. Survival was prolonged for mice that received H322L-BO4 cells versus original cells (H322L). H322L-BO4 cells did not exhibit obvious changes in general in vitro properties associated with the metastatic potential (e.g., cell growth, migration, and invasion) compared with H322L cells. However, the phosphorylation of chromosome 9 open reading frame 10/oxidative stress-associated Src activator (C9orf10/Ossa) was increased in H322L-BO4 cells. This result confirmed the increased anchorage independence through C9orf10/Ossa-mediated activation of Src family tyrosine kinase. Reduction of C9orf10/Ossa by shRNA reduced cells' metastasis to the leg bone and prolonged survival in mice. These findings indicate that H322L-BO4 cells can be used to evaluate the effect of candidate therapeutic targets against bone metastatic lung cancer cells. Moreover, C9orf10/Ossa may be a useful target for treatment of lung cancer with bone metastasis.

The spatial landscape of T cells in the microenvironment of stage III lung adenocarcinoma.

This study aimed to provide more information for prognostic stratification for patients through an analysis of the T-cell spatial landscape. It involved analyzing stained tissue sections of 80 patients with stage III lung adenocarcinoma (LUAD) using multiplex immunofluorescence and exploring the spatial landscape of T cells and their relationship with prognosis in the center of the tumor (CT) and invasive margin (IM). In this study, multivariate regression suggested that the relative clustering of CT CD4+ conventional T cell (Tconv) to inducible Treg (iTreg), natural regulatory T cell (nTreg) to Tconv, terminal CD8+ T cell (tCD8) to helper T cell (Th), and IM Treg to tCD8 and the relative dispersion of CT nTreg to iTreg, IM nTreg to nTreg were independent risk factors for DFS. Finally, we constructed a spatial immunological score named the GT score, which had stronger prognostic correlation than IMMUNOSCORE® based on CD3/CD8 cell densities. The spatial layout of T cells in the tumor microenvironment and the proposed GT score can reflect the prognosis of patients with stage III LUAD more effectively than T-cell density. The exploration of the T-cell spatial landscape may suggest potential cell-cell interactions and therapeutic targets and better guide clinical decision-making. © 2024 The Pathological Society of Great Britain and Ireland.

UBA5 inhibition restricts lung adenocarcinoma via blocking macrophage M2 polarization and cisplatin resistance.

UBA5, a ubiquitin-like activated enzyme involved in ufmylation and sumoylation, presents a viable target for pancreatic and breast cancer treatments, yet its role in lung adenocarcinoma (LUAD) remains underexplored. This study reveals UBA5's tumor-promoting effect in LUAD, as evidenced by its upregulation in patients and positive correlation with TNM stages. Elevated UBA5 levels predict poor outcomes for these patients. Pharmacological inhibition of UBA5 using DKM 2-93 significantly curtails the growth of A549, H1299, and cisplatin-resistant A549 (A549/DDP) LUAD cells in vitro. Additionally, UBA5 knockdown via shRNA lentivirus suppresses tumor growth both in vitro and in vivo. High UBA5 expression adversely alters the tumor immune microenvironment, affecting immunostimulators, MHC molecules, chemokines, receptors, and immune cell infiltration. Notably, UBA5 expression correlates positively with M2 macrophage infiltration, the predominant immune cells in LUAD. Co-culture experiments further demonstrate that UBA5 knockdown directly inhibits M2 macrophage polarization and lactate production in LUAD. Moreover, in vivo studies show reduced M2 macrophage infiltration following UBA5 knockdown. UBA5 expression is also associated with increased tumor heterogeneity, including tumor mutational burden, microsatellite instability, neoantigen presence, and homologous recombination deficiency. Experiments indicate that UBA5 overexpression promotes cisplatin resistance in vitro, whereas UBA5 inhibition enhances cisplatin sensitivity in both in vitro and in vivo settings. Overall, these findings suggest that targeting UBA5 inhibits LUAD by impeding cancer cell proliferation, M2 macrophage polarization, and cisplatin resistance.

TMEM158 functions as an oncogene and promotes lung adenocarcinoma progression through the PI3K/AKT pathway via interaction with TWIST1.

Lung adenocarcinoma (LUAD) is a common and deadly form of lung cancer, with high rates of metastasis and unsatisfactory clinical outcomes. Herein, we examined the influence of TMEM158 on the LUAD progression. A combination of bioinformatic analyses was used to assess the TMEM158 expression pattern, prognostic implications, and potential function in LUAD. The levels of TMEM158 and TWIST1 were evaluated in clinical samples from LUAD patients using Western blot analysis and qRT-PCR. To discover the function and underlying molecular pathways of TMEM158 in LUAD, we employed a combination of experimental approaches in vitro, such as flow cytometry analysis and colony formation, Co-IP, CCK-8, Transwell, and wound-healing assays. Elevated expression of TMEM158 in LUAD is associated with increased cancer aggressiveness and a poor prognosis. In vitro experiments demonstrated that high levels of TMEM158 promote cell proliferation, progression through the cell cycle, migration, and invasion while suppressing apoptosis. Knockdown of TMEM158 produced opposite effects. The underlying mechanism involves TMEM158 and TWIST1 directly interacting, stimulating the PI3K/AKT signaling pathway in LUAD cells. This investigation emphasizes the molecular functions of TMEM158 in LUAD progression and proposes targeting it as a promising treatment approach for managing LUAD.

Identification and immunological characteristics of anoikis-associated molecular clusters in lung adenocarcinoma.

Anoikis plays a crucial role in the progression, prognosis, and immune response of lung adenocarcinoma (LUAD). However, its specific impact on LUAD remains unclear. In this study, we investigated the intricate interplay of nesting apoptotic factors in LUAD. By analyzing nine key nesting apoptotic factors, we categorized LUAD patients into two distinct clusters. Further examination of immune cell profiles revealed that Cluster A exhibited greater infiltration of innate immune cells than did Cluster B. Additionally, we identified two genes closely associated with prognosis and developed a predictive model to differentiate patients based on molecular clusters. Our findings suggest that the loss of specific anoikis-related genes could significantly influence the prognosis, tumor microenvironment, and clinical features of LUAD patients. Furthermore, we validated the expression and functional roles of two pivotal prognostic genes, solute carrier family 2 member 1 (SLC2A1) and sphingosine kinase 1 (SPHK1), in regulating tumor cell viability, migration, apoptosis, and anoikis. These results offer valuable insights for future mechanistic investigations. In conclusion, this study provides new avenues for advancing our understanding of LUAD, improving prognostic assessments, and developing more effective immunotherapy strategies.

MAFF confers vulnerability to cisplatin-based and ionizing radiation treatments by modulating ferroptosis and cell cycle progression in lung adenocarcinoma.

AIMS: Lung cancer is the leading cause of cancer mortality and lung adenocarcinoma (LUAD) accounts for more than half of all lung cancer cases. Tumor elimination is mostly hindered by drug resistance and the mechanisms remain to be explored in LUAD. METHODS: CRISPR screens in cell and murine models and single-cell RNA sequencing were conducted, which identified MAF bZIP transcription factor F (MAFF) as a critical factor regulating tumor growth and treatment resistance in LUAD. RNA and ChIP sequencing analyses were performed for transcriptional target expression and specific binding sites of MAFF. Functions of MAFF in inhibiting tumor growth and promoting cisplatin or irradiation efficacy were investigated using cellular and xenograft models. RESULTS: Patients with lung adenocarcinoma and reduced MAFF expression had worse clinical outcomes. MAFF inhibited tumor cell proliferation by regulating the expression of SLC7A11, CDK6, and CDKN2C, promoting ferroptosis and preventing cell cycle progression from G1 to S. MAFF also conferred tumor cells vulnerable to cisplatin-based or ionizing radiation treatments. MAFF reduction was a final event in the acquisition of cisplatin resistance of LUAD cells. The intracellular cAMP/PKA/CREB1 pathway upregulated MAFF in response to cisplatin-based or ionizing radiation treatments. CONCLUSIONS: MAFF suppresses tumor growth, and pharmacological agonists targeting MAFF may improve cisplatin or irradiation therapies for lung adenocarcinoma patients.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma.

BACKGROUND: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). METHODS: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). RESULTS: This study identified TIME-related lncRNAs from integrated analysis of single­cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. CONCLUSIONS: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Olink Proteomics-Based Exploration of Immuno-Oncology-Related Biomarkers Leading to Lung Adenocarcinoma Progression.

INTRODUCTION: It is crucial to investigate the distinct proteins that contribute to the advancement of lung cancer. MATERIAL AND METHODS: We analyzed the expression levels of 92 immuno-oncology-related proteins in 96 pairs of lung adenocarcinoma tissue samples using Olink proteomics. The differentially expressed proteins (DEPs) were successively screened in tumor and paraneoplastic groups, early and intermediate-late groups by a nonparametric rank sum test, and the distribution and expression levels of DEPs were determined by volcano and heat maps, etc., and the area under the curve was calculated. RESULTS: A total of 24 DEPs were identified in comparisons between tumor and paracancerous tissues. Among them, interleukin-8 (IL8) and chemokine (C-C motif) ligand 20 (CCL20) as potential markers for distinguishing tumor tissues. Through further screening, it was found that interleukin-6 (IL6) and vascular endothelial growth factor A (VEGFA) may be able to lead to tumor progression through the JaK-STAT signaling pathway, Toll-like receptor signaling pathway and PI3K/AKT signaling pathway. Interestingly, our study revealed a down-regulation of IL6 and VEGFA in tumor tissues compared to paracancerous tissues. CONCLUSIONS: IL8 + CCL20 (AUC: 0.7056) have the potential to differentiate tumor tissue from paracancerous tissue; IL6 + VEGFA (AUC: 0.7531) are important protein markers potentially responsible for tumor progression.

Construction of a Lung Adenocarcinoma Prognostic Model Utilizing Serine and Glycine Metabolism-Related Genes.

The objective of this study was to construct a prognostic model by utilizing serine/glycine metabolism-related genes (SGMGs), thus establishing a risk score for lung adenocarcinoma (LUAD). Based on the TCGA-LUAD and SGMG data set, two subtypes with different SGMG expression levels were identified by clustering analysis. Thirteen differential expression genes were used to construct RiskScore by Cox regression. GSE72094 data set was used for validation. The survival characteristics, immune features, and potential benefits of chemotherapy drugs were analyzed for two risk groups. RiskScore was constructed based on the genes ABCC12, RIC3, CYP4B1, SFTPB, CACNA2D2, IGF2BP1, NTSR1, DKK1, CREG2, PITX3, RGS20, FETUB, and IGFBP1. Patients in the low-risk (LR) group exhibited a superior overall survival. In addition, aDCs, iDSs, mast cells, neutrophils, HLA, and type II IFN were more abundant in the LR group with higher IPS scores and lower TIDE scores. In contrast, NK cells, APC coinhibition, and MHC-I were more common in the high-risk (HR) group, which may be more sensitive to chemotherapy drugs such as cisplatin, oxaliplatin, and nilotinib. RiskScore was a promising biomarker that can be used to distinguish LUAD prognosis, immune features, and sensitivity to chemotherapy drugs.

Potential of Targeting TDO2 as the Lung Adenocarcinoma Treatment.

Tryptophan catabolism plays an important role in the metabolic reconnection in cancer cells to support special demands of tumor initiation and progression. The catabolic product of the tryptophan pathway, kynurenine, has the capability of suppressing the immune reactions of tumor cells. In this study, we conducted internal and external cohort studies to reveal the importance of tryptophan 2,3-dioxygenase (TDO) for lung adenocarcinoma (LUAD). Our study further demonstrated that the TDO2 expression was associated with the proliferation, survival, and invasion of LUAD cells, and targeting TDO2 for LUAD tumors could be a potential therapeutic strategy.

Defining the Soluble and Extracellular Vesicle Protein Compartments of Plasma Using In-Depth Mass Spectrometry-Based Proteomics.

Plasma-derived extracellular vesicles (pEVs) are a potential source of diseased biomarker proteins. However, characterizing the pEV proteome is challenging due to its relatively low abundance and difficulties in enrichment. This study presents a streamlined workflow to identify EV proteins from cancer patient plasma using minimal sample input. Starting with 400 µL of plasma, we generated a comprehensive pEV proteome using size exclusion chromatography (SEC) combined with HiRIEF prefractionation-based mass spectrometry (MS). First, we compared the performance of HiRIEF and long gradient MS workflows using control pEVs, quantifying 2076 proteins with HiRIEF. In a proof-of-concept study, we applied SEC-HiRIEF-MS to a small cohort (12) of metastatic lung adenocarcinoma (LUAD) and malignant melanoma (MM) patients. We also analyzed plasma samples from the same patients to study the relationship between plasma and pEV proteomes. We identified and quantified 1583 proteins in cancer pEVs and 1468 proteins in plasma across all samples. While there was substantial overlap, the pEV proteome included several unique EV markers and cancer-related proteins. Differential analysis revealed 30 DEPs in LUAD vs the MM group, highlighting the potential of pEVs as biomarkers. This work demonstrates the utility of a prefractionation-based MS for comprehensive pEV proteomics and EV biomarker discovery. Data are available via ProteomeXchange with the identifiers PXD039338 and PXD038528.

Integrated analysis highlights the significance role of ITGAL in lung adenocarcinoma.

Integrin alpha L (ITGAL), a member of the integrin family, is associated with carcinogenesis and immune regulation. However, the biological functions of ITGAL in lung adenocarcinoma (LUAD) remain poorly understood. In this study, we utilized the TCGA dataset to analyse ITGAL mRNA expression in LUAD and examined its correlation with clinical prognosis. Three-dimensional (3D) Matrigel culture, 5-bromodeoxyuridine (BrdU) ELISA, wound-healing migration and cell adherence assays were used to demonstrate the potential role of ITGAL in LUAD progression. Additionally, we analysed single-cell sequencing data of LUAD to determine the expression and biological function of ITGAL. Our research revealed that the expression of ITGAL in LUAD samples is an independent predictor of prognosis. Patients with high expression of ITGAL had significantly better overall survival (OS), progression-free survival (PFS) and disease-specific survival (DSS) compared to the low-expression group. Meanwhile, the expression of ITGAL suppressed malignant progression in LUAD cells. Functional enrichment analyses showed that ITGAL was significantly correlated with cell immune response and immune checkpoint, consistent with the analysis of single-cell sequencing in paired samples of normal and tumour. Furthermore, we confirmed that ITGAL expression affect the tumour microenvironment (TME) through regulation of the expression of cytokines in NK cells of LUAD. In summary, ITGAL is a prognostic biomarker for LUAD patients, and it repressed malignant progression in LUAD cells. Moreover, ITGAL expression also enhanced the effect of immunotherapy and may be an important target in LUAD therapy.

A risk score based on polyamine metabolism and chemotherapy-related genes predicts prognosis and immune cells infiltration of lung adenocarcinoma.

We aimed to explore whether the genes associated with both platinum-based therapy and polyamine metabolism could predict the prognosis of LUAD. We searched for the differential expression genes (DEGs) associated with platinum-based therapy, then we interacted them with polyamine metabolism-related genes to obtain hub genes. Subsequently, we analysed the main immune cell populations in LUAD using the scRNA-seq data, and evaluated the activity of polyamine metabolism of different cell subpopulations. The DEGs between high and low activity groups were screened to identify key DEGs to establish prognostic risk score model. We further elucidated the landscape of immune cells, mutation and drug sensitivity analysis in different risk groups. Finally, we got 10 hub genes associated with both platinum-based chemotherapy and polyamine metabolism, and found that these hub genes mainly affected signalling transduction pathways. B cells and mast cells with highest polyamine metabolism activity, while NK cells were found with lowest polyamine metabolism activity based on scRNA-seq data. DEGs between high and low polyamine metabolism activity groups were identified, then 6 key genes were screened out to build risk score, which showed a good predictive power. The risk score showed a universal negative correlation with immunotherapy checkpoint genes and the cytotoxic T cells infiltration. The mutation rates of EGFR in low-risk group was significantly higher than that of high-risk group. In conclusion, we developed a risk score based on key genes associated with platinum-based therapy and polyamine metabolism, which provide a new perspective for prognosis prediction of LUAD.

Study of the mechanism by which Xiaoyan decoction combined with E7449 regulates tumorigenesis in lung adenocarcinoma.

TNKS is a new target for the treatment of lung adenocarcinoma, the synergistic effects of the TCM compound Xiaoyan decoction and the TNKS inhibitor E7449 in the intervention on TNKS were investigated, and the possible underlying mechanisms involved were clarified. Immunohistochemistry was used to analyse TNKS expression in tumour tissues. The impact of targeting TNKS on cell growth, invasion, apoptosis, key genes and signalling pathways was investigated in tumour cells by Western blotting, rescue experiments, colony formation assays, flow cytometry and label-free experiments. Tumour xenografts with A549 cells were then transplanted for in vivo study. We found that TNKS high expression was closely related to the advanced tumour stage and tumour size in lung adenocarcinom. After TNKS was knocked down in vitro, the growth, proliferation, migration and invasion were markedly reduced in A549 and H1975 cells. We subsequently applied the Xiaoyan decoction and TNKS inhibitors to intervene in lung adenocarcinoma. Xiaoyan decoction and E7449 suppressed TNKS expression and inhibited adenocarcinoma cell proliferation, migration, invasion and apoptosis in vitro. Proteomic analysis revealed that E7449 treatment may be most closely associated with the classic Wnt/ß-catenin pathway, whereas Xiaoyan decoction treatment may be related to the WNT/PLAN pathway. Xenograft studies confirmed that E7449 or Xiaoyan decoction inhibited lung tumour growth in vivo and attenuated the Wnt signalling pathway in adenocarcinoma. These findings suggest that TNKS is a novel therapeutic target. TCM preparations and small molecule inhibitors are expected to constitute an effective combination strategy.

Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers.

The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cell datasets and using inferCNV, we identified and analysed tumour cell clusters to explore their heterogeneity and changes in abundance throughout LUAD progression. We applied gene set variation analysis (GSVA), pseudotime analysis, scMetabolism, and Cytotrace scores to study biological functions, metabolic profiles and stemness traits. A predictive model for prognosis, based on key cluster marker genes, was developed using CoxBoost and plsRcox (CPM), and validated across multiple cohorts for its prognostic prediction capabilities, tumour microenvironment characterization, mutation landscape and immunotherapy response. We identified nine distinct tumour cell clusters, with Cluster 6 indicating an early developmental stage, high stemness and proliferative potential. The abundance of Clusters 0 and 6 increased from AAH to IAC, correlating with prognosis. The CPM model effectively distinguished prognosis in immunotherapy cohorts and predicted genomic alterations, chemotherapy drug sensitivity, and immunotherapy responsiveness. Key gene S100A16 in the CPM model was validated as an oncogene, enhancing LUAD cell proliferation, invasion and migration. The CPM model emerges as a novel biomarker for predicting prognosis and immunotherapy response in LUAD patients, with S100A16 identified as a potential therapeutic target.

Upregulation of POC1A in lung adenocarcinoma promotes tumour progression and predicts poor prognosis.

Lung adenocarcinoma (LUAD) is characterized by a high incidence rate and mortality. Recently, POC1 centriolar protein A (POC1A) has emerged as a potential biomarker for various cancers, contributing to cancer onset and development. However, the association between POC1A and LUAD remains unexplored. We extracted The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) data sets to analyse the differential expression of POC1A and its relationship with clinical stage. Additionally, we performed diagnostic receiver operator characteristic (ROC) curve analysis and Kaplan-Meier (KM) survival analysis to assess the diagnostic and prognostic value of POC1A in LUAD. Furthermore, we investigated the correlation between POC1A expression and immune infiltration, tumour mutation burden (TMB), immune checkpoint expression and drug sensitivity. Finally, we verified POC1A expression using real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Cell experiments were conducted to validate the effect of POC1A expression on the proliferation, migration and invasion of lung cancer cells. POC1A exhibited overexpression in most tumour tissues, and its overexpression in LUAD was significantly correlated with late-stage presentation and poor prognosis. The high POC1A expression group showed lower levels of immune infiltration but higher levels of immune checkpoint expression and TMB. Moreover, the high POC1A expression group demonstrated sensitivity to multiple drugs. In vitro experiments confirmed that POC1A knockdown led to decreased proliferation, migration, and invasion of lung cancer cells. Our findings suggest that POC1A may contribute to tumour development by modulating the cell cycle and immune cell infiltration. It also represents a potential therapeutic target and marker for the diagnosis and prognosis of LUAD.

MRPS16 promotes lung adenocarcinoma growth via the PI3K/AKT/Frataxin signalling axis.

Although MRPS16 is involved in cancer development, its mechanisms in developing LAUD remain unclear. Herein, qRT-PCR, WB and IHC were utilized for evaluating MRPS16 expression levels, while functional assays besides animal experiments were performed to measure MRPS16 effect on LAUD progression. Using WB, the MRPS16 effect on PI3K/AKT/Frataxin signalling pathway was tested. According to our study, MRPS16 was upregulated in LAUD and was correlated to the advanced TNM stage as well as poor clinical outcomes, which represent an independent prognostic factor. Based on functional assays, MRPS16 is involved in promoting LAUD growth, migration and invasion, which was validated further in subsequent analyses through PI3K/AKT/Frataxin pathway activation. Moreover, MRPS16-knockdown-mediated Frataxin overexpression was shown to restore the reduction in tumour cells proliferation, migration and invasion. Our results revealed that MRPS16 caused an aggressive phenotype to LAUD and was a poor prognosticator; thus, targeting MRPS16 may be effectual in LAUD treatment.

Molecular mechanism of radiation tolerance in lung adenocarcinoma cells using single-cell RNA sequencing.

The efficacy of radiotherapy, a cornerstone in the treatment of lung adenocarcinoma (LUAD), is profoundly undermined by radiotolerance. This resistance not only poses a significant clinical challenge but also compromises patient survival rates. Therefore, it is important to explore this mechanism for the treatment of LUAD. Multiple public databases were used for single-cell RNA sequencing (scRNA-seq) data. We filtered, normalized and downscaled scRNA-seq data based on the Seurat package to obtain different cell subpopulations. Subsequently, the ssGSEA algorithm was used to assess the enrichment scores of the different cell subpopulations, and thus screen the cell subpopulations that are most relevant to radiotherapy tolerance based on the Pearson method. Finally, pseudotime analysis was performed, and a preliminary exploration of gene mutations in different cell subpopulations was performed. We identified HIST1H1D+ A549 and PIF1+ A549 as the cell subpopulations related to radiotolerance. The expression levels of cell cycle-related genes and pathway enrichment scores of these two cell subpopulations increased gradually with the extension of radiation treatment time. Finally, we found that the proportion of TP53 mutations in patients who had received radiotherapy was significantly higher than that in patients who had not received radiotherapy. We identified two cellular subpopulations associated with radiotherapy tolerance, which may shed light on the molecular mechanisms of radiotherapy tolerance in LUAD and provide new clinical perspectives.