Biomarker For Lung Adenocarcinoma Research Articles

Circ_BBS9 as an early diagnostic biomarker for lung adenocarcinoma: direct interaction with IFIT3 in the modulation of tumor immune microenvironment

Circ_BBS9 as an early diagnostic biomarker for lung adenocarcinoma: direct interaction with IFIT3 in the modulation of tumor immune microenvironment

TICRR as a potential prognostic biomarker for lung adenocarcinoma: A comprehensive analysis using TCGA database.

To investigate the role of TopBP1-interacting checkpoint and replication regulator (TICRR) in the tumorigenesis and prognosis of lung adenocarcinoma (LUAD) patients. Wilcoxon signed-rank test and logistic regression were utilized to analyze the relationship between clinical characteristics and TICRR expression in LUAD from TCGA dataset. Kaplan-Meier plots and Cox regressions were used to assess the impact of TICRR impact on prognosis. ROC curves and nomograms were generated to further evaluate the relationship between TICRR expression and the risk of LUAD. Gene set enrichment analysis (GSEA) was conducted on TCGA dataset, and ssGSEA was employed to investigate the association between TICRR and immune infiltrates. The results showed that high TICRR expression was significantly associated with various clinical factors including gender, age, pathological stage, T stage, N stage, M stage, outcome of primary therapy and smoking status. ROC curves also demonstrated that TICRR was a promising biomarker for molecular pathology diagnosis in LUAD patients (AUC = 0.952). Further analysis using gene ontology (GO) term enrichment and GSEA revealed an abnormal correlation between TICRR expression and cell division. Interestingly, ssGSEA analysis showed that TICRR expression correlated with multiple immune cell types, such as Th2 cell, TFH cell, mast cell, iDC, eosinophils, and dendritic cell. Lastly, the KM-plotters indicated that LUAD patients with high TICRR expression obtained worse life expectancy (P < .001). TICRR has proven to be a valuable tool in predicting disease progression and prognosis in patients with LUAD, thereby establishing itself as a fitting biomarker for forecasting overall survival (OS) of LUAD patients.

Utility of liquid biopsy for predicting cancer type and informing treatment of carcinoma with unknown primary.

e13606 Background: The advent of next-generation sequencing has greatly facilitated physicians in recommending tailored treatments for cancer patients. Despite these advancements, the dependence on the primary tumor site remains crucial for accurate diagnoses, posing a substantial obstacle in cases of carcinomas of unknown primary (CUPs) and hindering optimal patient care. To address this challenge, we propose the implementation of a machine learning model capable of identifying the tissue of origin (TOO) across 16 cancer types. Current standards gravitate to the use of tumor tissue for identifying primary tumor site. Leveraging the advantages of cell-free DNA (cfDNA), our approach provides a non-invasive and highly sensitive alternative to traditional biopsy or radiography methods. Methods: Cell-free DNA was extracted from patients diagnosed with carcinoma of known origin. The model underwent training using a dataset comprising 2,793 cfDNA samples, while the validation set consisted of 1,863 samples. The training and validation cohorts exhibited comparable demographics in terms of sex, age, and cancer types. Employing low-coverage whole genome sequencing (WGS), samples were analyzed to capture cfDNA features, including DNA fragment size distribution, copy number variation, nucleosome coverage pattern, mutational signature, and hotspot regions associated with cancer-related mutations. The final prediction model's accuracy was evaluated based on top 1 and top 2 predictions in accordance with the true tumor site of origin. Results: Overall accuracy of TOO predictions in the training cohort is 80.20% (2240/2793) for top 1 site and 90.26% (2521/2793) for top 2 sites. Overall accuracy of TOO predictions in the validation cohort is 81.80% (1524/1863) for top 1 site and 90.07% (1678/1863) for top 2 sites. Accuracy of tumor site prediction in the validation cohort is highest for lung cancer (Top 1 = 95.9%; Top 2 = 98.0%) tumor sites and lowest for biliary system and kidney tumor types (Top 1 = 54.3% &amp; 57.4%; Top 2 = 71.6% &amp; 63.2%). In the clinical setting, TOO estimation of 12/16 patients with CUP were identified to be in concordance with majority pathological consensus. Of note, two patients with CUP were diagnosed as lung cancer patients through TOO estimation. Molecular biomarkers of lung adenocarcinoma were also identified through targeted sequencing which corroborated the diagnosis, and chemoradiotherapy was recommended to the patient. Conclusions: We developed an accurate predictor of TOO by leveraging machine learning algorithm and incorporating cfDNA mutational, fragmentomic, and epigenetic features. Our results demonstrate high concordance between model-predicted and actual tumor sites across all examined cancer types. This model shows promise in offering valuable insights for the identification of cancers with an unknown primary origin using non-invasive cell free DNA samples.

Identification of PRODH as a mitochondria- and angiogenesis-related biomarker for lung adenocarcinoma.

Proline dehydrogenase (PRODH) encodes a mitochondrial protein that catalyzes the first step of proline degradation and is related to angiogenesis. Angiogenesis is a critical process in the development and progression of tumors, including lung adenocarcinoma (LUAD), as tumor growth and metastasis are dependent on angiogenesis. The mitochondria and their associated genes thus play a vital role in tumor therapy. However, the specific mechanism of action of PRODH in LUAD is not yet clear. The aim of this study was thus to clarify the specific mechanism of PRODH as a mitochondrial gene in LUAD. This study identified genes related to mitochondria and angiogenesis in LUAD. Based on the high and low expression of the genes in LUAD, we grouped them and conducted relevant bioinformatics analysis on the differentially expressed genes. We screened genes related to mitochondria and angiogenesis in the differential genes of LUAD, and identified PRODH as a gene of interest. The expression of PRODH was associated with the survival outcome of patients with LUAD. Additionally, PRODH was found to be associated with immune cell infiltration and tumor mutations. Mitochondrial metabolism and angiogenesis may have significant therapeutic ramifications for patients with LUAD. We identified PRODH, a gene exerts a dual role in cancer. PRODH may be a prospective therapeutic target in LUAD and a possible diagnostic and prognostic biomarker associated with immune infiltration and tumor mutational burden.

Factors correlating the expression of PD-L1

ObjectivePD-L1 was an important biomarker in lung adenocarcinoma. The study was to confirm the most important factor affecting the expression of PD-L1 remains undetermined.MethodsThe clinical records of 1045 lung adenocarcinoma patients were retrospectively reviewed. The High-Resolution Computed Tomography (HRCT) scanning images of all the participants were analyzed, and based on the CT characteristics, the adenocarcinomas were categorized according to CT textures. Furthermore, PD-L1 expression and Ki67 index were detected by immunohistochemistry. All patients underwent EGFR mutation detection.ResultsMultivariate logistic regression analysis revealed that smoking (OR: 1.73, 95% CI: 1.04–2.89, p = 0.004), EGFR wild (OR: 1.52, 95% CI: 1.11–2.07, p = 0.009), micropapillary subtypes (OR: 2.05, 95% CI: 1.46–2.89, p < 0.0001), and high expression of Ki67 (OR: 2.02, 95% CI: 1.44–2.82, p < 0.0001) were independent factors which influence PD-L1 expression. In univariate analysis, tumor size > 3 cm and CT textures of pSD showed a correlation with high expression of PD-L1. Further analysis revealed that smoking, micropapillary subtype, and EGFR wild type were also associated with high Ki67 expression. Moreover, high Ki67 expression was observed more frequently in tumors of size > 3 cm than in tumors with ≤ 3 cm size as well as in CT texture of pSD than lesions with GGO components. In addition, multivariate logistic regression analysis revealed that only lesions with micropapillary components correlated with pSD (OR: 3.96, 95% CI: 2.52–5.37, p < 0.0001).ConclusionThis study revealed that in lung adenocarcinoma high Ki67 expression significantly influenced PD-L1 expression, an important biomarker for immune checkpoint treatment.

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.