BACKGROUND:Tumour associated autoantibody (TAAb) generated against cell membrane receptor proteins in lung cancer have attracted attention. Understanding the role of these autoantibodies in tumours may open up new therapeutic modalities. METHODS:Plasma samples from 1170 participants were used to detect TAAbs level by enzyme-linked immunosorbent assay (ELISA) for evaluating the diagnostic value of candidate TAAbs. 353 non-small cell lung cancer (NSCLC) cases were used to assess the prognostic value of anti-platelet-derived growth factor receptor alpha (PDGFRα) autoantibody. The impact and mechanisms of anti-PDGFRα autoantibody were explored through antibody absorption, CCK-8, transwell, wound healing, and angiogenesis assays in NCI-H1703 cell. RESULTS:Anti - PDGFRα autoantibody was overexpressed in NSCLC and had an AUC of 0.747 (95% CI: 0.701-0.794) for early diagnosis compared to normal individuals. Cox regression analysis showed that it could be served as an independent predictor of poor prognosis in NSCLC with a HR of 1.510 (95% CI: 1.094-2.098). In vitro results suggested a role of anti-PDGFRα in promoting proliferation, migration, and angiogenesis via PI3K/AKT/NF-κB pathway. CONCLUSIONS:Anti-PDGFRα autoantibody is a novel biomarker for early diagnosis and poor prognosis of NSCLC. The mechanisms exploration may provide the theoretical basis for the precision treatment of NSCLC targeting anti-PDGFRα autoantibody.

Autoantibodies against tumor-associated antigens (TAAs) in the plasma have demonstrated potential as biomarkers for cancer detection and prognosis. Copper transport proteins ATP7A and ATP7B (copper ATPase transporter alpha and beta peptides, respectively), identified as TAAs, are abnormally expressed in patients with non-small cell lung cancer (NSCLC) and represent potential diagnostic biomarkers. In this study, we aimed to evaluate the diagnostic and prognostic values of plasma autoantibodies targeting ATP7A/B in NSCLC. The expression levels of anti-ATP7A/B autoantibodies were detected in a verification group of 75 patients with NSCLC and 75 normal controls (NC) and confirmed in a validation group including 253 patients with NSCLC, 253 patients with benign pulmonary nodules (BPN), and 253 NC using the enzyme-linked immunosorbent assay method. The results showed that the expression levels of anti-ATP7A/B autoantibodies in patients with NSCLC were significantly higher than in those with BPN and in NC. The anti-ATP7A/B autoantibodies distinguished NSCLC from NC with AUC values of 0.785 (95 % CI: 0.746-0.824) and 0.849 (95 % CI: 0.816-0.882), respectively. Those autoantibodies distinguished NSCLC from BPN with AUC values of 0.772 (95 % CI: 0.731-0.812) and 0.777 (95 % CI: 0.736-0.817), respectively. Additionally, the combination of anti-ATP7A and anti-ATP7B autoantibodies improved the efficacy of NSCLC diagnosis with increased AUC values. The prognostic values of anti-ATP7A/B autoantibodies were analyzed in 356 patients with NSCLC. The anti-ATP7B autoantibody served as an independent prognostic predictor for NSCLC, as high expression levels predicted poor prognosis. In conclusion, this study demonstrated the potential benefits of anti-ATP7A/B autoantibodies as biomarkers for NSCLC detection and prognosis.

Background:Autoantibodies against tumor-associated antigens in plasma are valuable biomarkers for early cancer detection and prognostic stratification. Dihydrolipoamide acetyltransferase (DLAT) and lipoic acid synthetase (LIAS), two key cuproptosis regulators, are abnormally expressed in non-small cell lung cancer (NSCLC) and are potential biomarkers for clinical diagnosis. This study explored the significance of anti-DLAT and anti-LIAS autoantibodies in the clinical diagnosis and prognosis of NSCLC. Methods:Plasma levels of anti-DLAT and anti-LIAS autoantibodies were detected using Enzyme-Linked Immunosorbent Assay (ELISA). Their diagnostic value was evaluated in 340 cases with normal control (NC), 260 patients with benign pulmonary nodule (BPN) and 340 patients with NSCLC. Additionally, the prognostic value of these autoantibodies was analyzed in a separate independent cohort of 354 patients with NSCLC. Results:The expression levels of anti-DLAT and anti-LIAS autoantibodies were significantly elevated in NSCLC compared to those in BPN and NC. These autoantibodies distinguished NSCLC from NC with AUCs of 0.712 (95% CI [0.669-0.756]) and 0.668 (95% CI [0.623-0.714]), respectively. To enhance diagnostic efficacy, a multi-autoantibody signature (anti-DLAT/LIAS/FDX1/COPT1) was constructed, which significantly improved discrimination (NSCLC vs NC: AUC = 0.805; NSCLC vs BPN: AUC = 0.751). Prognostic analysis indicated that anti-LIAS autoantibody served as an independent predictor of outcome (HR = 1.42, 95% CI [1.01-1.99]). Conclusions:These findings demonstrate the clinical utility of an autoantibody signature targeting cuproptosis-related proteins for NSCLC diagnosis and prognosis.

Autoantibodies (AAbs) represent promising biomarkers in cancer. While most AAbs are elevated in cancer, a substantial subset is downregulated, and their diagnostic and prognostic potential remains largely unexplored. Here we used the HuProt protein microarray to identify downregulated AAbs in non-small cell lung cancer (NSCLC) serum. Indirect ELISA quantified serum levels in 781 samples. Ten machine learning algorithms were used to construct diagnostic models. An independent cohort of 353 NSCLC patients was used to assess prognostic value and develop a prognostic model. Six downregulated AAbs were identified, among which five AAbs (anti-HIST1H1B, anti-HIST1H1C, anti-DYDC2, anti-CAMKK2, and anti-GRPEL1) were significantly reduced in NSCLC. The gradient boosting machine (GBM) model showed the best performance for NSCLC and BPNs, with AUCs of 0.869 (95% CI: 0.833-0.905) in the training set and 0.813 (95% CI: 0.745-0.880) in the validation set. For early-stage NSCLC, the model achieved an AUC of 0.809 (95% CI: 0.729-0.890) in the validation set, with a sensitivity of 74.0% and specificity of 81.3%. Multivariate Cox regression identified four AAbs significantly associated with patient prognosis. A prognostic model integrating age and AAb levels demonstrated robust predictive performance for long-term survival (7-year AUC = 0.79). Bioinformatics analyses further supported the relevance of the corresponding genes/proteins of these AAbs to NSCLC outcomes. Overall, our findings demonstrate that downregulated AAbs possess significant diagnostic and prognostic value in NSCLC and may contribute to improved patient management and survival prediction.

BackgroundMacrophages play a crucial role in the progression of idiopathic pulmonary fibrosis (IPF). This study aims to identify a predictive signature based on macrophage-related genes to forecast patient prognosis and uncover potential therapeutic targets for IPF.MethodsWe analyzed single-cell transcriptomic and microarray data from the GEO database, exploring cellular variations in healthy controls, COPD, and IPF patients. CellChat and Monocle were utilized for analyzing cell interactions and pseudotime trajectories, respectively. Bioinformatics was used to identify differentially expressed genes, leading to the development of a gene signature via multivariate Cox regression, which was validated using ROC curves and an external dataset. The biological function of LGMN was investigated through in vivo and in vitro experiments.ResultsWe observed a significant increase in monocyte-derived macrophages (MDMs) in patients with IPF, which negatively correlated with lung function. In IPF patients, interactions between macrophages and fibroblasts, as well as myofibroblasts, were both more frequent and intense compared to those observed in controls. Notably, the TGF-β1 signaling pathway was significantly activated in IPF, particularly within MDMs and myofibroblasts, leading to increased extracellular matrix (ECM) activity. We developed a gene signature associated with MDMs, which serves as an independent prognostic tool for IPF patients. In vitro experiments demonstrated elevated levels of LGMN in M2 macrophages, co-localizing with CD206 in fibrotic lung tissue. Treatment with RR-11a, a LGMN inhibitor, reduced TGF-β1 secretion from M2 macrophages, thereby diminishing communication between macrophages and fibroblasts and alleviating bleomycin-induced pulmonary fibrosis in mice.ConclusionsOur research establishes a gene signature associated with MDMs, which may aid clinicians in the personalized management of IPF. Additionally, we identify LGMN as a promoter of interaction between M2 macrophages and fibroblasts, suggesting its potential as a therapeutic target for IPF treatment.

BackgroundProteinase 3 (PRTN3) has been recognized as a crucial target for anti-neutrophil cytoplasmic autoantibody. However, the relationship between anti-PRTN3 autoantibody and cancer remains largely unexplored.MethodsImmunohistochemistry was used to detect the level of PRTN3 in lung adenocarcinoma (LUAD) tissue array. Enzyme-linked immunosorbent assay was conducted to measure anti-PRTN3 IgG and IgM autoantibodies in plasma from patients with early- and advanced-stage LUAD, benign pulmonary nodules (BPN) and normal control (NC). Western blotting and immunofluorescence staining were performed to confirm the presence of plasma immune response to PRTN3.ResultsPRTN3 protein was highly expressed in LUAD tissues. Elevated plasma levels of anti-PRTN3 IgG and IgM autoantibodies were also detected in LUAD, especially in early LUAD. The AUC of anti-PRTN3 IgG autoantibodies in the diagnosis of early LUAD from NC was 0.782, and from BPN was 0.761. When CEA and anti-PRTN3 autoantibodies were combined, the AUC for the diagnosis of early LUAD was significantly higher than that of CEA alone. The presence of a plasma immune response to PRTN3 in LUAD was also confirmed.ConclusionAnti-PRTN3 IgG and IgM autoantibodies maybe early biomarkers to differentiate LUAD from NC and BPN.

AbstractBackground: Autoantibodies can be readily identified prior to biopsy and may serve as valuable biomarkers for cancer detection. Ferredoxin 1 (FDX1) is a key regulator in the process of cuproptosis and affects the prognosis of lung cancer. In this study, we investigated whether the anti-FDX1 autoantibody could serve as a novel biomarker for the detection of non–small cell lung cancer (NSCLC). Methods: A total of 1,155 plasma samples were divided into the verification and validation groups. The expression levels of the anti-FDX1 autoantibody in 414 patients with NSCLC, 327 patients with benign pulmonary nodules (BPN), and 414 normal controls (NC) were detected using ELISA. Western blotting and immunofluorescence analyses were performed to confirm the ELISA results. Results: Plasma anti-FDX1 autoantibody levels were significantly higher in patients with NSCLC than in patients with BPN and NCs in the verification and validation groups. The ELISA results were confirmed by Western blotting and immunofluorescence. The anti-FDX1 autoantibody distinguished NSCLC from NC and BPN with an AUC (95% confidence interval) of 0.806 (0.772–0.839) and 0.627 (0.584–0.670), respectively. Conclusions: Our study demonstrated the potential benefits of the anti-FDX1 autoantibody as a novel biomarker for NSCLC detection. Impact: These findings suggested that the anti-FDX1 autoantibody may facilitate the detection of NSCLC.

Supplementary Table S2 shows the combination analysis of anti–FDX1 autoantibody and CEA to distinguish NSCLC.

Supplementary Figure S4 shows the mRNA expression level of FDX1 in LUAD and LUSC patients based on GEPIA database.

While polysomnography (PSG) is the gold standard for diagnosing obstructive sleep apnea (OSA), its limited availability means that many patients remain undiagnosed. This study seeks to evaluate whether CHI3L1-Ab could serve as a diagnostic biomarker for OSA. A total of 366 individuals, including 333 OSA patients and 33 healthy controls, were recruited for this study, all of whom underwent polysomnography. Enzyme-linked immunosorbent assay (ELISA) was used to measure CHI3L1-Ab levels, and clinical factors were analyzed to assess their relationship with CHI3L1-Ab expression. OSA patients exhibited significantly higher CHI3L1-Ab levels compared to healthy controls (P < 0.05), with an area under the curve (AUC) of 0.721. Subgroup analysis revealed the highest AUC of 0.735 (95% CI 0.637-0.832) in patients with severe OSA. Logistic regression analysis, which incorporated age, BMI and CHI3L1-Ab levels, demonstrated strong predictive performance with an AUC of 0.846 (95% CI 0.815-0.942). The corresponding nomogram allowed individualized risk estimation based on these predictors. The combination of CHI3L1-Ab levels, age and BMI demonstrated strong predictive accuracy in distinguishing OSA from healthy individuals. These findings also suggest that elevated CHI3L1-Ab levels could serve as an independent diagnostic biomarker for OSA.

BACKGROUND:DNA methylation alteration in peripheral blood provides a promising approach for the diagnosis of cancers. We aimed to investigate the association between blood-based methylation of F2RL3 and lung adenocarcinoma (LUAD). METHODS:A total of 970 LUAD patients, 333 benign pulmonary nodes (BPNs), and 2413 normal controls (NCs) were included. The methylation levels of blood F2RL3 were measured by mass spectrometry. The gender-associated heterogeneity of blood F2RL3 methylation in LUAD was investigated. The blood F2RL3 methylation associations with male LUAD were assessed by logistic regression. The relations of blood F2RL3 hypomethylation to tumor size and lymph node involvement in male LUAD were also evaluated. Mann-Whitney and Kruskal-Wallis tests were conducted for the comparisons. Tissue F2RL3 methylation and expression in LUAD were investigated via UALCAN database analysis. RESULTS:Blood-based F2RL3 methylation presented significant difference between male and female LUAD patients. While, blood F2RL3 methylation in LUAD patients were significantly lower than in BPN cases and NCs in male population. Through logistic regression analysis, the independent associations of blood F2RL3 hypomethylation with male LUAD was identified. In addition, blood F2RL3 methylation was correlated with tumor size and lymph nodes involvement in male LUAD patients. CONCLUSIONS:In conclusion, blood-based F2RL3 methylation might be a potential biomarker for male LUAD early detection.

BACKGROUND:Autoantibodies can be readily identified prior to biopsy and may serve as valuable biomarkers for cancer detection. Ferredoxin 1 (FDX1) is a key regulator in the process of cuproptosis and affects the prognosis of lung cancer. In this study, we investigated whether the anti-FDX1 autoantibody could serve as a novel biomarker for the detection of non-small cell lung cancer (NSCLC). METHODS:A total of 1,155 plasma samples were divided into the verification and validation groups. The expression levels of the anti-FDX1 autoantibody in 414 patients with NSCLC, 327 patients with benign pulmonary nodules (BPN), and 414 normal controls (NC) were detected using ELISA. Western blotting and immunofluorescence analyses were performed to confirm the ELISA results. RESULTS:Plasma anti-FDX1 autoantibody levels were significantly higher in patients with NSCLC than in patients with BPN and NCs in the verification and validation groups. The ELISA results were confirmed by Western blotting and immunofluorescence. The anti-FDX1 autoantibody distinguished NSCLC from NC and BPN with an AUC (95% confidence interval) of 0.806 (0.772-0.839) and 0.627 (0.584-0.670), respectively. CONCLUSIONS:Our study demonstrated the potential benefits of the anti-FDX1 autoantibody as a novel biomarker for NSCLC detection. IMPACT:These findings suggested that the anti-FDX1 autoantibody may facilitate the detection of NSCLC.

Fatty acid metabolism is a key driver of tumor progression, yet its dysregulation in lung adenocarcinoma (LUAD) remains incompletely characterized. Here, we identify apolipoprotein C3 (APOC3)—previously linked to cardiovascular disease—as a novel suppressor of triglyceride (TG) hydrolysis and fatty acid oxidation, ultimately restraining LUAD growth and metastasis. Proteomic and tissue microarray analyses revealed that APOC3 expression was significantly downregulated in LUAD tissues compared with adjacent normal tissues, and low APOC3 levels correlated with poor prognosis in metastatic patients. Furthermore, plasma levels of APOC3 and TG showed a positive correlation in LUAD patients. Functionally, APOC3 overexpression suppressed TG hydrolysis, fatty acid oxidation, and the proliferation and metastasis of LUAD cells both in vitro and in vivo. Mechanistically, APOC3 attenuated the cAMP/PKA signaling pathway, leading to reduced expression of hormone-sensitive lipase (HSL), a key enzyme in TG hydrolysis, and PGC-1α, a master regulator of fatty acid oxidation. The inhibitory effects of APOC3 on TG hydrolysis and fatty acid oxidation were reversed by cAMP activators or knockdown of HSL or PGC-1α. Additionally, APOC3 was found to interact with GNAI3, a critical inhibitory regulator of the cAMP/PKA pathway. In summary, our study uncovers an APOC3-mediated pathway that constrains TG hydrolysis and fatty acid oxidation, the dysregulation of which contributes to LUAD progression, highlighting APOC3 as a potential therapeutic target in LUAD.

BackgroundEarly diagnosis of lung cancer is crucial for improving patient outcomes. Autoantibodies against tumor-associated antigens (TAAs) found in the plasma can serve as biomarkers for lung cancer detection. Copper transporter 1 (COPT1) is abnormally expressed in several cancers including lung cancer. The purpose of this study is to explore the significance of anti-COPT1 autoantibodies in the clinical diagnosis of non-small cell lung cancer (NSCLC).MethodsThe expression level of COPT1 in NSCLC and normal tissues was analyzed based on TCGA and the Human Protein Atlas (HPA) database. Through enzyme-linked immunosorbent assay (ELISA), the expression levels of anti-COPT1 autoantibodies in plasma samples from normal controls (NC), patients with benign pulmonary nodules (BPN), and patients with NSCLC were detected in the discovery (89 NC and 89 NSCLC) and verification (321 NC, 321 BPN and 321 NSCLC) groups. The ELISA results were verified by western blotting and indirect immunofluorescence experiments.ResultsBased on HPA and TCGA databases, the mRNA and protein levels of COPT1 were higher in NSCLC tissues than in normal tissues. The levels of anti-COPT1-IgG and anti-COPT1-IgM autoantibodies were significantly higher in patients with NSCLC (P<0.05). Anti-COPT1-IgG and anti-COPT1-IgM could discriminate NSCLC from NC with area under the curve (AUC) values of 0.733 (95% CI: 0.694-0.771) and 0.679 (95% CI: 0.638-0.720), respectively. Additionally, the combination of anti-COPT1-IgG, anti-COPT1-IgM, and carcinoembryonic antigen (CEA) could enhance the efficacy of NSCLC diagnosis from BPN with increased AUC values.ConclusionsOur study indicated the potential significance of anti-COPT1-IgG and anti-COPT1-IgM autoantibodies as novel biomarkers for the detection of NSCLC. Furthermore, the combination of anti-COPT1-IgG and anti-COPT1-IgM improved the diagnostic value.

Supplementary Figure S2 shows the ROC curve analysis of anti-FDX1 autoantibody in different clinical subgroups of NSCLC versus NC.

Background: Approximately 60% of Asian populations with non-small cell lung cancer (NSCLC) harbor epidermal growth factor receptor (EGFR) gene mutations, marking it as a pivotal target for genotype-directed therapies. Currently, determining EGFR mutation status relies on DNA sequencing of histological or cytological specimens. This study presents a predictive model integrating clinical parameters, computed tomography (CT) characteristics, and serum tumor markers to forecast EGFR mutation status in NSCLC patients. Methods: Retrospective data collection was conducted on NSCLC patients diagnosed between January 2018 and June 2019 at the First Affiliated Hospital of Zhengzhou University, with available molecular pathology results. Clinical information, CT imaging features, and serum tumor marker levels were compiled. Four distinct models were employed in constructing the diagnostic model. Model diagnostic efficacy was assessed through receiver operating characteristic (ROC) area under the curve (AUC) values and calibration curves. DeLong's test was administered to validate model robustness. Results: Our study encompassed 748 participants. Logistic regression modeling, trained with the aforementioned variables, demonstrated remarkable predictive capability, achieving an AUC of 0.805 (95% confidence interval (CI) [0.766-0.844]) in the primary cohort and 0.753 (95% CI [0.687-0.818]) in the validation cohort. Calibration plots suggested a favorable fi t of the model to the data. Conclusions: The developed logistic regression model emerges as a promising tool for forecasting EGFR mutation status. It holds potential to aid clinicians in more precisely identifying patients likely to benefit from EGFR molecular testing and facilitating targeted therapy decision-making, particularly in scenarios where molecular testing is impractical or inaccessible.

Background Non-small cell lung cancer (NSCLC) accounts for the vast majority of lung cancers. Early detection is crucial to reduce lung cancer-related mortality. Aberrant DNA methylation occurs early during carcinogenesis and can be detected in blood. It is essential to investigate the dysregulated blood methylation markers for early diagnosis of NSCLC. Methods NSCLC-associated methylation gene folate receptor gamma ( FOLR3 ) was selected from an Illumina 850K array analysis of peripheral blood samples. Mass spectrometry was used for validation in two independent case–control studies (validation I: n = 2548; validation II: n = 3866). Patients with lung squamous carcinoma (LUSC) or lung adenocarcinoma (LUAD), normal controls (NCs) and benign pulmonary nodule (BPN) cases were included. FOLR3 methylations were compared among different populations. Their associations with NSCLC clinical features were investigated. Receiver operating characteristic analyses, Kruskal–Wallis test, Wilcoxon test, logistics regression analysis and nomogram analysis were performed. Results Two CpG sites (CpG_1 and CpG_2) of FOLR3 was significantly lower methylated in NSCLC patients than NCs in the discovery round. In the two validations, both LUSC and LUAD patients presented significant FOLR3 hypomethylations. LUSC patients were highlighted to have significantly lower methylation levels of CpG_1 and CpG_2 than BPN cases and LUAD patients. Both in the two validations, CpG_1 methylation and CpG_2 methylation could discriminate LUSC from NCs well, with areas under the curve (AUCs) of 0.818 and 0.832 in validation I, and 0.789 and 0.780 in validation II. They could also differentiate LUAD from NCs, but with lower efficiency. CpG_1 and CpG_2 methylations could also discriminate LUSC from BPNs well individually in the two validations. With the combined dataset of two validations, the independent associations of age, gender, and FOLR3 methylation with LUSC and LUAD risk were shown and the age-gender-CpG_1 signature could discriminate LUSC and LUAD from NCs and BPNs, with higher efficiency for LUSC. Conclusions Blood-based FOLR3 hypomethylation was shown in LUSC and LUAD. FOLR3 methylation heterogeneity between LUSC and LUAD highlighted its stronger associations with LUSC. FOLR3 methylation and the age-gender-CpG_1 signature might be novel diagnostic markers for the early detection of NSCLC, especially for LUSC.

Background Anti-programmed cell death 1 (PD-1) antibody combined with chemotherapy simultaneously is regarded as the standard treatment for patients with advanced non-small cell lung cancer (NSCLC) by current clinical guidelines. Different immune statuses induced by chemotherapy considerably affect the synergistic effects of the chemo-anti-PD-1 combination. Therefore, it is necessary to determine the optimal timing of combination treatment administration.Methods The dynamic immune status induced by chemotherapy was observed in paired peripheral blood samples of patients with NSCLC using flow cytometry and RNA sequencing. Ex vivo studies and metastatic lung carcinoma mouse models were used to evaluate immune activity and explore the optimal combination timing. A multicenter prospective clinical study of 170 patients with advanced NSCLC was performed to assess clinical responses, and systemic immunity was assessed using omics approaches.Results PD-1 expression on CD8+ T cells was downregulated on day 1 (D1) and D2, but recovered on D3 after chemotherapy administration, which is regulated by the calcium influx-P65 signaling pathway. Programmed cell death 1 ligand 1 expression in myeloid-derived suppressor cells was markedly reduced on D3. RNA sequencing analysis showed that T-cell function began to gradually recover on D3 rather than on D1. In addition, ex vivo and in vivo studies have shown that anti-PD-1 treatment on D3 after chemotherapy may enhance the antitumor response and considerably inhibit tumor growth. Finally, in clinical practice, a 3-day-delay sequential combination enhanced the objective response rate (ORR, 68%) and disease control rate (DCR, 98%) compared with the simultaneous combination (ORR=37%; DCR=81%), and prolonged progression-free survival to a greater extent than the simultaneous combination. The new T-cell receptor clones were effectively expanded, and CD8+ T-cell activity was similarly recovered.Conclusions A 3-day-delay sequential combination might increase antitumor responses and clinical benefits compared with the simultaneous combination.

Cisplatin-based chemotherapy is the current standard care for lung cancer patients; however, drug resistance frequently develops during treatment, thereby limiting therapeutic efficacy.The molecular mechanisms underlying cisplatin resistance remain elusive. In this study, we conducted an analysis of microarray data from the Gene Expression Omnibus (GEO) database under the accession numbers GSE21656,which encompassed expression profiling of cisplatin-resistant H460(DDP-H460)and the parental cells(H460). Subsequently, we calculated the differentially expressed genes (DEGs) between DDP-H460 and H460. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs demonstrated significant impact on the the Rap1, PI3K/AKT and MAPK signaling pathways. Moreover, protein and protein interaction (PPI) network analysis identified PRKCA, DET1, and UBE2N as hub genes that potentially contribute predominantly to cisplatin resistance. Ultimately, PRKCA was selected for validation due to its significant prognostic effect, which predicts unfavorable overall survival and disease-free survival in patients with lung cancer. Network analysis conducted on The Cancer Genome Atlas (TCGA) database revealed a strong gene-level correlation between PRKCA and TP53, CDKN2A, BYR2, TTN, KRAS, and PIK3CA; whereas at the protein level, it exhibited a high correlation with EGFR, Lck, Bcl2, and Syk. The in vitro experiments revealed that PRKCA was upregulated in the cisplatin-resistant A549 cells(DDP-A549), while knockdown of PRKCA increased DDP-A549 apoptosis upon cisplatin treatment. Moreover, we observed that PRKCA knockdown attenuated DDP-A549 proliferation, migration and invasion ability. Western blot analysis demonstrated that PRKCA knockdown downregulated phosphorylation of PI3K expression while upregulated the genes involved in ferroptosis signaling. In summary, our results elucidate the role of PRKCA in acquiring resistance to cisplatin and underscore its potential as a therapeutic target for cisplatin-resistant lung cancer.

The detection of autoantibodies (AAbs) with low-cost and noninvasiveness advantages has emerged as a promising technique for the diagnosis of early-stage lung cancer (LC). However, the specificity and sensitivity are frequently restricted to the characteristics of the antigens and the detection systems such as an enzyme-linked immunosorbent assay. Here, a highly sensitive and specific gold nanocluster-based capture-detection platform was developed to detect anti-PDL1 AAb as the biomarker of LC, for the diagnosis of early-stage LC. The nano capture-detection platform was composed of streptavidin magnetic beads conjugated PDL1 peptide (MB-peptide), serving as the capture probe, and goat-anti-human-IgG conjugated horseradish peroxidase-coated gold nanoclusters (anti-IgG-HRP-AuNCs) as the detection nanoprobe. Notably, the nanoplatform exhibited strikingly sensitive and specific detection of anti-PDL1 AAb, owing to the integration of the MB-peptide's precision recognition capabilities with the excellent peroxidase activity and profound affinity for IgG displayed by the anti-IgG-HRP-AuNCs. Furthermore, the innovative nanoplatform harnessing optical detection technology significantly boosted detection efficiency and dramatically reduced the analysis time from the traditional 12 h process to a mere 50 min. Additionally, this advanced system demonstrated significantly enhanced sensitivity and specificity in diagnosing early-stage LC, substantiating the tremendous potential of the AuNCs-based capture-detection platform for clinical applications in the early detection of LC in the future.