Biomarker For Lung Adenocarcinoma Research Articles

Identification of a methyltransferase-related long noncoding RNA signature as a novel prognosis biomarker for lung adenocarcinoma.

Lung adenocarcinoma (LUAD) accounts for a high proportion of tumor deaths globally, while methyltransferase-related lncRNAs in LUAD were poorly studied. In our study, we focused on two distinct cohorts, TCGA-LUAD and GSE3021, to establish a signature of methyltransferase-related long non-coding RNAs (MeRlncRNAs) in LUAD. We employed univariate Cox and LASSO regression analyses as our main analytical tools. The GSE30219 cohort served as the validation cohort for our findings. Furthermore, to explore the differential pathway enrichments between groups stratified by risk, we utilized Gene Set Enrichment Analysis (GSEA). Additionally, single-sample GSEA (ssGSEA) was conducted to assess the immune infiltration landscape within each sample. Reverse transcription quantitative PCR (RT-qPCR) was also performed to verify the expression of prognostic lncRNAs in both clinically normal and LUAD samples. In LUAD, we identified a set of 32 MeRlncRNAs. We further narrowed our focus to six prognostic lncRNAs to develop gene signatures. The TCGA-LUAD cohort and GSE30219 were utilized to validate the risk score model derived from these signatures. Our analysis showed that the risk score served as an independent prognostic factor, linked to immune-related pathways. Additionally, the analysis of immune infiltration revealed that the immune landscape in high-risk groups was suppressed, which could contribute to poorer prognoses. We also constructed a regulatory network comprising 6 prognostic lncRNAs, 19 miRNAs, and 21 mRNAs. Confirmatory RT-qPCR results aligned with public database findings, verifying the expression of these prognostic lncRNAs in the samples. The prognostic gene signature of LUAD associated with MeRlncRNAs that we provided, may offer us a comprehensive picture of the prognosis prediction for LUAD patients.

CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1’s potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD.

The expression characteristic and prognostic role of Siglec-15 in lung adenocarcinoma.

Sialic acid-binding immunoglobulin-like lectin-15 (Siglec-15) has been identified as an immune suppressor and a promising candidate for immunotherapy of cancer management. However, the association between Siglec-15 expression and clinicopathological features of lung adenocarcinoma (LUAD), especially the prognostic role, is not fully elucidated. In this present study, a serial of bioinformatics analyses in both tissue and cell levels were conducted to provide an overview of Siglec-15 expression. Real-time quantitative PCR (qPCR) test, western blotting assay, and immunohistochemistry (IHC) analyses were conducted to evaluate the expression of Siglec-15 in LUAD. Survival analysis and Kaplan-Meier curve were employed to describe the prognostic parameters of LUAD. The results of bioinformatics analyses demonstrated the up-regulation of Siglec-15 expression in LUAD. The data of qPCR, western blotting, and IHC analyses further proved that the expression of Siglec-15 in LUAD tissues was significantly increased than that in noncancerous tissues. Moreover, the expression level of Siglec-15 protein in LUAD was substantially associated with TNM stage. LUAD cases with up-regulated Siglec-15 expression, positive N status, and advance TNM stage suffered a critical unfavorable prognosis. In conclusion, Siglec-15 could be identified as a novel prognostic biomarker in LUAD and targeting Siglec-15 may provide a promising strategy for LUAD immunotherapy.

A novel microRNA miR-4433a-3p as a potential diagnostic biomarker for lung adenocarcinoma

BackgroundLung adenocarcinoma is one of the leading causes of cancer-related deaths because of the lack of early specific clinical indicators. MicroRNAs (miRNAs) have become the focus in lung cancer diagnosis. Further studies are required to explore miRNA expression in the serum of lung adenocarcinoma patients and their correlation with therapy and analyse specific messenger RNA targets to improve the specificity and sensitivity of early diagnosis. MethodsThe Toray 3D-Gene miRNA array was used to compare the expression levels of various miRNAs in the sera of patients with lung adenocarcinoma and healthy volunteers. Highly expressed miRNAs were selected for further analysis. To verify the screening results, serum and pleural fluid samples were analysed using qRT-PCR. Serum levels of the miRNAs and their correlation with the clinical information of patients with lung adenocarcinoma were analysed. The functions of miRNAs were further analysed using the Kyoto Encyclopedia of Gene and Genomes and Gene Ontology databases. ResultsMicroarray analysis identified 60 and 50 miRNAs with upregulated and downregulated expressions, respectively, in the serum of patients with lung adenocarcinoma compared to those in healthy individuals. Using qRT-qPCR to detection of miRNAs expression in the serum or pleural effusion of patients with early and advanced lung adenocarcinoma, we found that miR-4433a-3p could be used as a diagnostic marker and therapeutic evaluation indicator for lung adenocarcinoma. Serum of miR-4433a-3p levels significantly correlated with the clinical stage. miR-4433a-3p may be more suitable than other tumour markers for the early diagnosis and evaluation of therapeutic effects in lung adenocarcinoma. miR-4433a-3p may affect tumour growth and metastasis by acting on target genes (PIK3CD, UBE2J2, ICMT, PRDM16 and others) and regulating tumour-related signalling pathways (MAPK signal pathway, Ras signalling pathway and others). ConclusionmiR-4433a-3p may serve as a biomarker for the early diagnosis of lung adenocarcinoma and monitoring of therapeutic effects.

IL1R2 is a Novel Prognostic Biomarker for Lung Adenocarcinoma.

The aim of this study is to figure out the role of IL1R2 in LUAD (lung adenocarcinoma). IL1R2, a special member of IL-1 receptor family, binds to IL-1 and plays an important role in inhibiting IL-1 pathway, which seems to be involved in tumorigenesis. Emerging studies demonstrated higher IL1R2 expression levels in several malignancies. In the present study, we assessed the expression of IL1R2 in LUAD tissues with immunohistochemistry and explored various databases to determine whether it could be a potential prognostic biomarker and therapeutic target. The expression level of IL1R2 in lung adenocarcinoma was analyzed by Immunohistochemistry and UALCAN database. The correlation between IL1R2 expression and the patient prognosis was identified by Kaplan-Meier plotter. The correlation of IL1R2 expression with immune infiltrates was clarified by TIMER database. The protein-protein interaction network and gene functional enrichment analysis were constructed and performed by STRING and Metascape database. Immunohistochemistry showed that the expression of IL1R2 was higher in tumor tissues of LUAD patients and that patients with lower IL1R2 level have a better prognosis than their counterparts. We validated our findings in several online databases and found that IL1R2 gene was also positively correlated with B cells and neutrophils and biomarkers of CD8+T cells and exhausted T cells. PPI network and gene enrichment analyses showed that expression of IL1R2 was also associated with complex functionspecific networks involving IL-1 signal, NF-KappaB transcription factors. According to these findings, we demonstrated that IL1R2 was involved in the progression and prognosis of LUAD and the underlying mechanism needs further investigation.

Prognostic value and immunological function of cuproptosis-related genes in lung adenocarcinoma

BackgroundLung cancer is one of the malignant tumors with the highest morbidity and fatality rates worldwide. The overall survival (OS) of lung adenocarcinoma (LUAD) is poor. Cuproptosis is a copper-triggered modality of mitochondrial cell death, however, its contribution to the emergence of lung cancer is unknown. The clinical implication and immunological function of cuproptosis-related genes (CRGs) in LUAD has yet to be established. MethodsTCGA, HPA, GEPIA, Kaplan-Meier, TIMER and CancerSEA database were used to explore the prognostic value and biological function of CRGs in LUAD. ResultsCRGs are primarily involved in copper ion transport, the citrate cycle (TCA cycle) and central carbon metabolism in LUAD. The mRNA expression of COA6, UBE2D1, DLAT, SLC25A3, and DBH was significantly increased. The expression of COA6, DLAT, SLC25A3, DBH, and LOXL2 were all strongly associated with the clinicopathological stages in LUAD. Moreover, high expression of COA6, UBE2D1, DLAT, SLC25A3 and LOXL2 was related to poor OS. The expression of SLC25A3 and LOXL2 showed different association with immune cell infiltration. The single cell sequencing demonstrated that CRGs play important roles in the regulation of DNA damage response, inflammation and metastasis in LUAD. ConclusionsIn summary, this study comprehensively uncovered that CRGs could be identified as potential prognostic and immunological biomarkers in LUAD. Our current research could provide a solid theoretical basis for LUAD survival research and clinical decision-making.

Prognostic effect of TCF1+ CD8+ T cell and TOX+ CD8+ T cell infiltration in lung adenocarcinoma.

Recent studies have highlighted the pivotal roles of T cell transcription factors TCF-1 and TOX in modulating the immune response in cancer, with TCF-1 maintaining CD8+ T cell stemness and TOX promoting T cell exhaustion. The prognostic significance of these factors in lung adenocarcinoma (LUAD) remains a critical area of investigation. The retrospective study included 191 patients with LUAD who underwent surgery, of whom 83% were in stages II and III. These patients were divided into exploratory (n = 135) and validation (n = 56) groups based on the time of diagnosis. Multiplex fluorescence immunohistochemistry was used to examine the infiltration levels of CD8+ T cells, TCF1+ CD8+ T cells, and TOX+ CD8+ T cells. The percentage of CD8+ T cells in tumor was markedly lower than that in stroma (p < 0.05). In tumor-draining lymph nodes (TDLNs) invaded by tumor, the proportion of stem-like TCF1+ CD8+ T cells was significantly decreased (p < 0.01). Importantly, higher infiltration levels of CD8+ T cells and TCF1+ CD8+ T cells were associated with improved disease-free survival (DFS) (p = 0.009 and p = 0.006, respectively) and overall survival (OS) (p = 0.018 and p = 0.010, respectively). This study underscores the potential of TCF1+ CD8+ T cells as prognostic biomarkers in LUAD, providing insights into the tumor immune microenvironment and guiding future therapeutic strategies.

2 The role of cellular pathology departments in the improvement of turnaround times for lung adenocarcinoma biomarker testing

2 The role of cellular pathology departments in the improvement of turnaround times for lung adenocarcinoma biomarker testing

Cancer testis antigen MAGEA3 in serum and serum-derived exosomes serves as a promising biomarker in lung adenocarcinoma

Cancer testis antigen (CTA) Melanoma Antigen Gene A3 (MAGEA3) were overexpressed in multiple tumor types, but the expression pattern of MAGEA3 in the serum of lung adenocarcinoma (LUAD) remains unclear. Clinically derived serum and serum exosome samples were used to assess the mRNA expression of MAGEA3 and MAGEA4 by qRT-PCR, and serum MAGEA3 and MAGEA4 protein expression were evaluated by ELISA in total 133 healthy volunteers’ and 289 LUAD patients’ serum samples. An analysis of the relationship of the mRNA and protein expression of MAGEA3 and MAGEA4 with clinicopathologic parameters was performed and the diagnostic value of MAGEA3 and MAGEA4 was plotted on an ROC curve. In addition, the correlation of MAGEA3 mRNA with infiltrating immune cells was investigated through TIMER, the CIBERSORT algorithm and the TISIDB database. Expression of serum and serum exosome MAGEA3 and MAGEA4 mRNA were significantly higher in LUAD patients than in healthy donors. MAGEA3 mRNA associated with tumor diameter, TMN stage, and NSE in LUAD serum samples, and MAGEA3 mRNA correlated with N stage in serum-derived exosomes, possessing areas under the curve (AUC) of 0.721 and 0.832, respectively. Besides, serum MAGEA3 protein levels were elevated in LUAD patients, and were closely related to stage and NSE levels, possessing AUC of 0.781. Further analysis signified that the expression of MAGEA3 mRNA was positive correlation with neutrophil, macrophages M2, dendritic cells resting, and eosinophilic, but negatively correlated with B cells, plasma cells, CD8 + T cells, CD4 + T cells, Th17 cells, macrophages and dendritic cells. Collectively, our results suggested that the MAGEA3 expression in mRNA and protein were upregulated in LUAD, and MAGEA3 could be used as a diagnostic biomarker and immunotherapy target for LUAD patients.

SFXN1-mediated immune cell infiltration and tumorigenesis in lung adenocarcinoma: A potential therapeutic target

BackgroundSideroflexin 1 (SFXN1), a mitochondrial serine transporter implicated in one-carbon metabolism, is a prognostic biomarker in lung adenocarcinoma (LUAD). However, its role in LUAD progression remains elusive. This study aimed to investigate the functional significance of SFXN1 in LUAD and evaluate its potential as a therapeutic target. MethodsWe analyzed SFXN1 expression and its diagnostic and prognostic value in LUAD using the Pan-cancer TCGA dataset. In vitro assays (CCK-8, cell cycle, EDU, wound-healing, and transwell) were employed to assess the role of SFXN1, complemented by in vivo experiments. RNA sequencing elucidated SFXN1-mediated cellular functions and potential mechanisms. Bulk RNA-seq and scRNA-seq data from TCGA and GEO were used to investigate the correlation between SFXN1 and the tumor immune microenvironment. RT-qPCR, Western blot, and IHC assays validated SFXN1 expression and its impact on the immune microenvironment in LUAD. ResultsSFXN1 was upregulated in LUAD tissues and associated with poor prognosis. RNA-seq and scRNA-seq analyses revealed increased SFXN1 expression in tumor cells, accompanied by decreased infiltration of NK and cytotoxic T cells. SFXN1 knockdown significantly reduced cell proliferation and migration, and the inhibition of ERK phosphorylation and CCL20 expression may be the molecular mechanism involved. In vivo, targeting SFXN1 decreased Tregs infiltration and inhibited tumor growth. ConclusionsOur findings suggest that SFXN1 may be a potential therapeutic target for LUAD treatment.

SH3GL2 and MMP17 as lung adenocarcinoma biomarkers: a machine-learning based approach

ObjectiveUsing bioinformatics machine learning methods, our research aims to identify the potential key genes associated with Lung adenocarcinoma (LUAD). MethodsWe obtained two gene expression profiling microarrays (GSE68571 and GSE74706) from the public Gene Expression Omnibus (GEO) database at the National Centre for Biotechnology Information (NCBI). The purpose was to identify Differentially Expressed Genes (DEGs) between the lung adenocarcinoma group and the healthy control group. The limma R package in R was utilized for this analysis. For the differential gene diagnosis of lung adenocarcinoma, we employed the least absolute shrinkage and selection operator (LASSO) regression and SVM-RFE screening crossover. To evaluate the performance, ROC curves were plotted. We performed immuno-infiltration analysis using CIBERSORT. Finally, we validated the key genes through qRT-PCR and Western-blot verification, then downregulated MMP17 gene expression, upregulated SH3GL2 gene expression, and performed CCK8 experiments. ResultsA total of 32 Differentially Expressed Genes (DEGs) were identified. Two diagnostic marker genes, SH3GL2 and MMP17, were selected by employing LASSO and SVM-RFE machine learning methods. In Lung adenocarcinoma cells, the expression of MMP17 was observed to be elevated compared to normal lung epithelial cells in the control group (P < 0.05). In contrast, a down-regulation of SH3GL2 was found in Lung adenocarcinoma cells (P < 0.05). Finally, we downregulated MMP17 and upregulated SH3GL2 gene expression, then the CCK8 showed that the proliferation of both lung cancer cells was inhibited. ConclusionSH3GL2 and MMP17 are expected to be potential biomarkers for Lung adenocarcinoma.

Abstract 7269: Karyopherin α-2, a nuclear export protein, promotes cancer progression in lung adenocarcinoma

Abstract Introduction: Karyopherin α-2 (KPNA2), a nucleocytoplasmic transport protein, regulates the nuclear import of macromolecules and contributes to carcinogenesis. Actually, KPNA2 is upregulated in various types of cancer tissues and serum from cancer patients. In particular, it is associated with cancer invasiveness and poor prognosis in patient. Here, we tried to present the molecular mechanism and clinical significance of KPNA2 in lung cancer progression and metastasis. Method: First, we retrospectively analyzed the data extracted from EMR for patients with non-small cell lung cancer receiving curative surgical resection in Uijeongbu and Bucheon St. Mary’s Hospitals (n=165). Immunohistochemistry staining was performed on the tumor microarray samples using antibodies against KPNA2. The functional assay and gene silencing was conducted. Result: The clinical and pathological information of the experimental group is as follows. Based on the TMA staining, mean KPNA2 score was 36.5 [0-240] and median value was 10. Based on the TMA staining, patients with high KPNA2 expression were related to lymphatic invasion (p = 0.00782), advanced stage (p = 0.0202), and current smoker (p = 0.0074). KPNA2 expression was higher in squamous cell carcinoma than in adenocarcinoma histotype. Patients with high KPNA2 expression showed shorter survival than those with low KPNA2 (median OS (months), 72.8 vs 42.2, P &amp;lt; 0.0001; median RFS (months), 72.8 vs 32.1, P &amp;lt; 0.0011) and relevant to high recurrence (recurrence rate (%), 24.7 vs 44.7, p = 0.007). Further, high KPNA2 expression was associated with poor survival outcomes. Knockdown of KPNA2 in lung cancer cells suppressed the invasion and migration of lung cancer cells and inhibited metastasis in a mouse model of lung cancer. Inversely, KPNA2 overexpression promoted cancer cell growth, invasion, and migration. Moreover, ectopic expression of KPNA2 made lung cancer cells less sensitive to anticancer drugs, Talazoparib and Olaparib, indicating that KPNA2 enhances drug resistance in lung cancer cells. Conclusion: Collectively, this study suggest that KPNA2 promotes invasiveness and metastasis and is associated with poor patient outcomes; therefore, KPNA2 will be a good therapeutic target or a biomarker in lung adenocarcinoma. Citation Format: Inyoung Cheon, Seoree Kim, Sengran Cho, Heejin Lee, Jung-Sook Yoon, Ji Hyun Lee, Sang Hoon Chun, Hye Sung Won, Soon Auck Hong, Yoon Ho Ko, Young-Ho Ahn. Karyopherin α-2, a nuclear export protein, promotes cancer progression in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7269.

Retracted: Identification of Cigarette Smoking-Related Novel Biomarkers in Lung Adenocarcinoma.

[This retracts the article DOI: 10.1155/2022/9170722.].

Crosstalk among disulfidptosis-related lncRNAs in lung adenocarcinoma reveals a correlation with immune profile and clinical prognosis

Disulfidptosis refers to a specific programmed cell death process characterized by the accumulation of disulfides. It has recently been reported in several cancers. However, the impact of disulfidptosis-related long non-coding RNAs (lncRNAs) on malignant tumors has remained largely unknown. In the present work, we screened prognostic disulfidptosis-related lncRNAs and studied their effects on lung adenocarcinoma. Relevant clinical data of lung adenocarcinoma cases were retrieved from The Cancer Genome Atlas (TCGA) database. RNA sequencing was used to identify differentially expressed disulfidptosis-related lncRNAs within lung adenocarcinoma. In addition, prognostic disulfidptosis-related lncRNAs were obtained through univariate Cox regression analysis. LASSO-COX was used to construct new disulfidptosis-related lncRNA signatures. Different statistical approaches were used to validate the practicability and accuracy of the disulfidptosis-related lncRNAs signatures. Furthermore, several bioinformatic approaches were used to study relevant heterogeneities in biological processes and pathways of diverse risk groups. Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was conducted to analyze the expression of disulfidptosis-related lncRNAs. Finally, seven disulfidptosis-related lncRNA signatures were identified in lung adenocarcinoma cells. The prognosis prediction model constructed efficiently predicted patient survival. Subgroup analysis revealed significant differences in immune cell proportion, including T follicular helper cells and M0 macrophages. In addition, in vitro experimental results demonstrated significant differences in disulfidptosis-related lncRNAs. Altogether, the six disulfidptosis-related lncRNA signatures could serve as a potential prognostic biomarker for lung adenocarcinoma. Furthermore, these can be used as a prediction model in individualized immunotherapy for lung adenocarcinoma.

The Diagnostic Value of ACSL1, ACSL4, and ACSL5 and the Clinical Potential of an ACSL Inhibitor in Non-Small-Cell Lung Cancer.

Abnormal expression of ACSL members 1, 3, 4, 5, and 6 is frequently seen in human cancer; however, their clinical relevance is unclear. In this study, we analyzed the expression of ACSLs and investigated the effects of the ACSL inhibitor Triacsin C (TC) in lung cancer. We found that, compared to normal human bronchial epithelial (NHBE) cells, ACSL1, ACSL4, and ACSL6 were highly expressed, while ACSL3 and ACSL5 were lost in the majority of lung cancer cell lines. ACSL activity was associated with the expression levels of the ACSLs. In primary lung tumors, a higher expression of ACSL1, ACSL4, and ACSL5 was significantly correlated with adenocarcinoma (ADC). Moreover, ACSL5 was significantly reversely related to the proliferation marker Ki67 in low-grade tumors, while ACSL3 was positively associated with Ki67 in high-grade tumors. Combination therapy with TC and Gemcitabine enhanced the growth-inhibitory effect in EGFR wild-type cells, while TC combined with EGFR-TKIs sensitized the EGFR-mutant cells to EGFR-TKI treatment. Taken together, the data suggest that ACSL1 may be a biomarker for lung ADC, and ACSL1, ACSL4, and ACSL5 may be involved in lung cancer differentiation, and TC, in combination with chemotherapy or EGFR-TKIs, may help patients overcome drug resistance.

Long noncoding RNA LINC00921 serves as a predictive biomarker for lung adenocarcinoma: An observational study.

Lung adenocarcinoma (LUAD) is usually diagnosed at advanced stages. Hence, there is an urgent need to seek an effective biomarker to predict LUAD status. Long noncoding RNAs (lncRNAs) play key roles in the development of tumors. However, the relationship between LINC00921 and LUAD remains unclear. The gene expression data of LUAD were downloaded from the Cancer Genome Atlas database to investigate the expression level of LINC00921 in LUAD. Diagnostic ability analysis, survival analysis, tumor mutational burden analysis, and immune cell infiltration analysis of LINC00921 in LUAD patients were performed simultaneously. According to the median expression value of LINC00921, patients were divided into LINC00921 high- and low-expression groups. The function of LINC00921 in LUAD was identified through difference analysis and enrichment analysis. Moreover, drugs that may be relevant to LUAD treatment were screened. Finally, blood samples were collected for real-time polymerase chain reaction. LINC00921 was significantly lower in LUAD tumor tissues. Notably, patients with low expression of LINC00921 had a shorter median survival time. Decreased immune cell infiltration in the tumor microenvironment in the low LINC00921 expression group may contribute to poorer patient outcomes. Tumor mutational burden was significantly different in survival between the LINC00921 high- and low-expression groups. In addition, LINC00921 may exert an influence on cancer development through its regulation of target genes transcription. Glyceraldehyde-3-phosphate dehydrogenase-related drugs may be more likely to be therapeutically effective in LUAD. LINC00921 was able to be used as the potential diagnostic indicator for LUAD.

Non-targeted metabolomics analysis of indoleamine 2,3-dioxygenase inhibitor treatment in a mouse model of early-stage lung adenocarcinoma.

Lung adenocarcinoma is a common malignant tumor, and its early diagnosis and treatment are key to improving patient survival rates. However, due to the non-specific early symptoms, many patients are already at an advanced stage when diagnosed. Non-targeted metabolomics analysis, as a method for comprehensive analysis of metabolites in the body, has been shown to have potential in the early diagnosis of cancer. This study aims to identify early-stage lung adenocarcinoma-specific biomarkers using non-targeted metabolomics analysis in an established mouse model. The intervention mechanism of indoleamine 2,3-dioxygenase (IDO) inhibitor in early-stage lung adenocarcinoma is explored to provide evidence for clinical disease treatment. Twenty specific-pathogen-free-grade female Kunming mice were divided into control group, experimental group, Epacadostatlow group, and Epacadostathigh group. After modeling, immune therapy intervention (epacadostat) was administered to the mice, and plasma and urine samples were collected from all mice on day 7 and day 28. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) analysis was performed to identify potential biomarkers for diagnosing early-stage lung adenocarcinoma. Cluster analysis and correlation analysis were used to explore the differential expression patterns of metabolites in different samples. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to identify enriched pathways of differentially expressed metabolites. A total of 348 metabolites were identified after merging the positive and negative ion modes. Among them, organic acids and derivatives (16.954%) and lipids and lipid-like molecules (15.517%) were the two major classes of metabolites in the early-stage lung adenocarcinoma mice. Anthranilic acid (vitamin L1), 1-methylhistidine, 12(R)-HETE, and hippuric acid were the major differentially expressed metabolites on both day 7 and day 28, and they showed correlations with each other. Metabolic pathway analysis revealed multiple dysregulated pathways in lung adenocarcinoma mice. UPLC-QTOF-MS analysis is a feasible method for identifying biomarkers of lung adenocarcinoma. Epacadostat, a novel and promising IDO inhibitor, may exert its therapeutic effect by modulating 1-methylhistidine and anthranilic acid (vitamin L1).

E2F7 serves as a potential prognostic biomarker for lung adenocarcinoma.

E2F transcription factors (E2Fs) are a family of transcription factors critical regulators of the cell cycle, apoptosis, and differentiation, thus influencing tumorigenesis. However, the specific roles of E2Fs in lung adenocarcinoma (LUAD) remain unclear. Data from The Cancer Genome Atlas (TCGA) were used. R version. 4.0.3 and multiple databases (TIMER, cBioportal, gene expression profile interaction analysis [GEPIA], LinkedOmics, and CancerSEA) were utilized to investigate mRNA expression, mutational analysis, prognosis, clinical correlations, co-expressed gene, pathway and network, and single-cell analyses. Immunohistochemistry (IHC) confirmed that E2F transcription factor 7 (E2F7) correlated with LUAD. Among the E2Fs, E2F7 was identified by constructing a prognostic model most significantly associated with overall survival (OS) in LUAD patients. The univariate and multivariate Cox regression analyses showed that E2F7, p-T stage, and p-TNM stage were closely related to OS and progression-free survival (PFS) (P < .05) in LUAD. E2F 7/8 were also identified as significantly associated with tumor stage in the GEPIA database. Compared with paracancerous tissues, E2F7 was up-regulated in LUAD by IHC, and E2F7 might be positively correlated with larger tumors and higher TNM stages. E2F7 may primarily regulate DNA repair, damage, and cell cycle processes and thus affect LUAD tumorigenesis, invasion, and metastasis by LinkedOmics and CancerSEA. E2F7 serves as a potential prognostic biomarker for LUAD.

Comprehensive analysis the prognostic and immune characteristics of mitochondrial transport-related gene SFXN1 in lung adenocarcinoma

BackgroundMitochondria, which serve as the fundamental organelle for cellular energy and metabolism, are closely linked to the growth and survival of cancer cells. This study aims to identify and assess Sideroflexin1 (SFXN1), an unprecedented mitochondrial gene, as a potential prognostic biomarker for lung adenocarcinoma (LUAD).MethodsThe mRNA and protein levels of SFXN1 were investigated based on the Cancer Genome Atlas (TCGA) LUAD dataset, and then validated by real-time quantitative PCR, Western Blotting and immunohistochemistry from our clinical samples. The clinical correlation and prognostic value were evaluated by the TCGA cohort and verified via our clinical dataset (n = 90). The somatic mutation, drug sensitivity data, immune cell infiltration and single-cell RNA sequencing data of SFXN1 were analyzed through public databases.ResultsSFXN1 was markedly upregulated at both mRNA and protein levels in LUAD, and high expression of SFXN1 were correlated with larger tumor size, positive lymph node metastasis, and advanced clinical stage. Furthermore, SFXN1 upregulation was significantly associated with poor clinical prognosis. SFXN1 co-expressed genes were also analyzed, which were mainly involved in the cell cycle, central carbon metabolism, DNA repair, and the HIF-1α signaling pathway. Additionally, SFXN1 expression correlated with the expression of multiple immunomodulators, which act to regulate the tumor immune microenvironment. Results also demonstrated an association between SFXN1 expression and increased immune cell infiltration, such as activated CD8 + T cells, natural killer cells (NKs), activated dendritic cells (DCs), and macrophages. LUAD patients with high SFXN1 expression exhibited heightened sensitivity to multiple chemotherapies and targeted drugs and predicted a poor response to immunotherapy. SFXN1 represented an independent prognostic marker for LUAD patients with an improved prognostic value for overall survival when combined with clinical stage information.ConclusionsSFXN1 is frequently upregulated in LUAD and has a significant impact on the tumor immune environment. Our study uncovers the potential of SFXN1 as a prognostic biomarker and as a novel target for intervention in LUAD.

Identification of Biomarker in Lung Adenocarcinoma Using Machine Learning and Neural Network

Identification of Biomarker in Lung Adenocarcinoma Using Machine Learning and Neural Network