Formation of Inorganic Sulfate and Volatile Nonsulfated Products from Heterogeneous Hydroxyl Radical Oxidation of 2-Methyltetrol Sulfate Aerosols: Mechanisms and Atmospheric Implications.

Chemical transformation of 2-methyltetrol sulfates (2-MTS), key isoprene-derived secondary organic aerosol (SOA) constituents, through heterogeneous hydroxyl radical (•OH) oxidation can result in the formation of previously unidentified atmospheric organosulfates (OSs). However, detected OSs cannot fully account for the sulfur content released from reacted 2-MTS, indicating the existence of sulfur in forms other than OSs such as inorganic sulfates. This work investigated the formation of inorganic sulfates through heterogeneous •OH oxidation of 2-MTS aerosols. Remarkably, high yields of inorganic sulfates, defined as the moles of inorganic sulfates produced per mole of reacted 2-MTS, were observed in the range from 0.48 ± 0.07 to 0.68 ± 0.07. These could be explained by the production of sulfate (SO4 •-) and sulfite (SO3 •-) radicals through the cleavage of C-O(S) and (C)O-S bonds, followed by aerosol-phase reactions. Additionally, nonsulfated products resulting from bond cleavage were likely volatile and evaporated into the gas phase, as evidenced by the observed aerosol mass loss (≤25%) and concurrent size reduction upon oxidation. This investigation highlights the significant transformation of sulfur from its organic to inorganic forms during the heterogeneous oxidation of 2-MTS aerosols, potentially influencing the physicochemical properties and environmental impacts of isoprene-derived SOAs.

Exploring clinical factors to predict the survival for resectable non-small cell lung cancer patients with neoadjuvant immunotherapy.

OBJECTIVES: To explore clinical factors and build a predictive model for the disease-free and overall survival in non-small cell lung cancer patients receiving neoadjuvant chemotherapy combined with immune checkpoint inhibitors. METHODS: Inclusion criteria for patients in this multicentre study were: (1) patients were diagnosed with stage I-III non-small cell lung cancer diagnosed by bronchoscopy biopsy or puncture; (2) computed tomography/positron emission tomography-computed tomography was applied before treatment and surgery; (3) neoadjuvant chemotherapy combined with immune checkpoint inhibitors were applied for 2-6 cycles preoperatively; (4) peripheral blood indicators and tumour markers were assessed before treatment and surgery; (5) patients underwent radical lung cancer surgery after neoadjuvant therapy. Cases were divided into high- and low-risk groups according to 78 clinical indicators based on 10-fold LASSO selection. We employed Cox proportional hazards models in predicting disease-free and overall survival. Then, we used time-dependent area under the curve and decision curve analyses to examine the accuracy of the results. RESULTS: Data were collected continuously, and 212 and 85 cases were randomly assigned to training and testing sets, respectively. The area under curve for the prediction of disease-free survival (training-1-year, 0.83; 2-year, 0.81; 3-year, 0.83 vs testing-1-year, 0.65; 2-year, 0.66; 3-year, 0.70), overall survival (training-1-year, 0.86; 2-year, 0.85; 3-year, 0.86 vs testing-1-year, 0.66; 2-year, 0.57; 3-year, 0.70) were determined. The coefficient factors including pathological response, preoperative tumour maximum diameter, preoperative lymph shorter-diameter, preoperative tumour&lymph maximum standardized uptake value, change in tumour standardized uptake value preoperative, and blood related risk factors were favorably associated with prognosis (P < 0.001). CONCLUSIONS: Our prediction model integrating data from preoperative positron emission tomography-CT, preoperative blood parameters, and pathological response was able to make high accuracy predictions for disease-free and overall survival in non-small cell lung cancer patients receiving neoadjuvant immunity with chemical therapy.

Subxiphoid video-assisted thoracoscopic extend thymectomy with sternal suspension for thymoma.

BACKGROUND: Thymoma is a primary tumor of the thymus, commonly located in the anterior mediastinum. Most thymomas are benign or low-grade malignant, but they can invade surrounding organs or metastasize. The primary treatment for thymoma is surgical resection. Traditional methods involve open thoracotomy, but it is traumatic, with slow recovery and many complications. In recent years, with the development of thoracoscopic techniques, thoracoscopic total thymectomy has gradually become the preferred method for small size thymomas due to its minimally invasive, safe, and effective. METHODS: This paper introduces a thoracoscopic extend thymectomy technique, the subxiphoid video-assisted thoracoscopic extend thymectomy with sternal suspension. This method involves placing hooks at the upper and lower ends of the sternum to suspend the sternum upward, increasing the thoracic cavity space and facilitating thoracoscopic operations. This research reviews the clinical data of 59 patients with early-stage thymomas treated with this technique at our center since 2020 and analyzes the perioperative therapeutic efficacy and safety. It also compares the outcomes with those of 17 patients who underwent thoracoscopic approaches. RESULTS: The results show that subxiphoid video-assisted thoracoscopic total thymectomy with sternal suspension is an innovative and effective surgical method, achieving the same tumor eradication as other thoracic surgeries. The flexible switching of observation ports provides a more comprehensive surgical field, reduces surgical trauma and complications, and improves the surgical outcomes and quality of life for patients.

[Retracted] lncRNA­u50535 promotes the progression of lung cancer by activating CCL20/ERK signaling.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that certain of the western blotting data shown in Fig. 4B and C on p. 1952, and the Transwell invasion assay data in Fig. 2F and 4I, had already appeared in previously published articles written by different authors at different research institutes (a number of which have been retracted). Owing to the fact that the contentious data in the above article had already been published prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 42: 1946­1956, 2019; DOI: 10.3892/or.2019.7302].

Comprehensive Analysis of Immune Responses to Neoadjuvant Immunotherapy in Resectable Non-small Cell Lung Cancer.

BACKGROUND: Neoadjuvant immunotherapy using immune checkpoint inhibitors (ICIs) has revolutionized the treatment of early stage non-small cell lung cancer (NSCLC). However, little is known about which patients are likely to benefit most from neoadjuvant immunotherapy. In this study, we performed a multiplatform analysis on samples from resectable NSCLC treated with neoadjuvant immunotherapy to explore molecular characteristics related to immune responses. PATIENTS AND METHODS: A total of 17 patients with resectable stage IB-IIIA NSCLC treated with neoadjuvant immunotherapy were included. A multiplex cytokine assay, bulk TCR sequencing in peripheral blood, and multiplexed immunohistochemistry were performed. RESULTS: Low levels of stromal cell-derived factor (SDF)-1alpha at baseline were associated with unfavorable disease-free survival (DFS). Patients with major pathologic response (MPR) showed a decrease in HGF after one cycle of neoadjuvant immunotherapy. An increase in IDO and IP-10 was observed in patients who developed immune-related adverse events (irAEs) after neoadjuvant immunotherapy. There were no correlations between irAEs and MPR or DFS. The MPR group presented a significant decrease in white blood cells and neutrophil count after neoadjuvant immunotherapy. The high peripheral baseline TCR convergence was correlated with MPR and favorable DFS in lung squamous cell carcinoma (LUSC) receiving neoadjuvant immunotherapy. Neoadjuvant immunotherapy led to a significant increase in CD4+, CD8+, and CD8+CD39+ T-cell infiltration in tumor areas. CONCLUSIONS: This study suggests the potential roles of cytokines and TCR convergence for predicting ICIs response in resectable NSCLC and LUSC. CD8+CD39+T cells and CD4+ T cells could be involved in the action of neoadjuvant immunotherapy.

Exploring cellular diversity in lung adenocarcinoma epithelium: Advancing prognostic methods and immunotherapeutic strategies.

Immunotherapy has brought significant advancements in the treatment of lung adenocarcinoma (LUAD), but identifying suitable candidates remains challenging. In this study, we investigated tumour cell heterogeneity using extensive single-cell data and explored the impact of different tumour cell cluster abundances on immunotherapy in the POPLAR and OAK immunotherapy cohorts. Notably, we found a significant correlation between CKS1B+ tumour cell abundance and treatment response, as well as stemness potential. Leveraging marker genes from the CKS1B+ tumour cell cluster, we employed machine learning algorithms to establish a prognostic and immunotherapeutic signature (PIS) for LUAD. In multiple cohorts, PIS outperformed 144 previously published signatures in predicting LUAD prognosis. Importantly, PIS reliably predicted genomic alterations, chemotherapy sensitivity and immunotherapy responses. Immunohistochemistry validated lower expression of immune markers in the low-PIS group, while in vitro experiments underscored the role of the key gene PSMB7 in LUAD progression. In conclusion, PIS represents a novel biomarker facilitating the selection of suitable LUAD patients for immunotherapy, ultimately improving prognosis and guiding clinical decisions.

Deciphering the prognostic role of endoplasmic reticulum stress in lung adenocarcinoma: integrating prognostic prediction and immunotherapy strategies.

Endoplasmic reticulum stress (ERS) is a critical factor influencing lung adenocarcinoma (LUAD) progression and patient outcomes. In this study, we analyzed gene expression data from LUAD samples sourced from The Cancer Genomic Atlas and Gene Expression Omnibus databases. Utilizing advanced statistical methods including LASSO and Cox regression, we developed a ERS-associated signature (ERAS) based on ten ERS-related genes. This model stratified patients into high- and low-risk groups, with the high-risk group exhibiting decreased survival rates, elevated tumor mutational burden, and heightened chemotherapy sensitivity. Additionally, we observed lower immune and ESTIMATE scores in the high-ERAS group, indicating a potentially compromised immune response. Experimental validation through quantitative real-time polymerase chain reaction confirmed the utility of our model. Furthermore, we constructed a nomogram to predict 1-, 3-, and 5-year survival rates, providing clinicians with a valuable tool for personalized patient management. In conclusion, our study demonstrates the efficacy of the ERAS in identifying high-ERAS LUAD patients, offering promising implications for improved prognostication and treatment strategies.

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

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

Decreases in Epoxide-Driven Secondary Organic Aerosol Production under Highly Acidic Conditions: The Importance of Acid-Base Equilibria.

Isoprene has the highest atmospheric emissions of any nonmethane hydrocarbon, and isoprene epoxydiols (IEPOX) are well-established oxidation products and the primary contributors forming isoprene-derived secondary organic aerosol (SOA). Highly acidic particles (pH 0-3) widespread across the lower troposphere enable acid-driven multiphase chemistry of IEPOX, such as epoxide ring-opening reactions forming methyltetrol sulfates through nucleophilic attack of sulfate (SO42-). Herein, we systematically demonstrate an unexpected decrease in SOA formation from IEPOX on highly acidic particles (pH < 1). While IEPOX-SOA formation is commonly assumed to increase at low pH when more [H+] is available to protonate epoxides, we observe maximum SOA formation at pH 1 and less SOA formation at pH 0.0 and 0.4. This is attributed to limited availability of SO42- at pH values below the acid dissociation constant (pKa) of SO42- and bisulfate (HSO4-). The nucleophilicity of HSO4- is 100× lower than SO42-, decreasing SOA formation and shifting particulate products from low-volatility organosulfates to higher-volatility polyols. Current model parameterizations predicting SOA yields for IEPOX-SOA do not properly account for the SO42-/HSO4- equilibrium, leading to overpredictions of SOA formation at low pH. Accounting for this underexplored acidity-dependent behavior is critical for accurately predicting SOA concentrations and resolving SOA impacts on air quality.

Applying a Phase-Separation Parameterization in Modeling Secondary Organic Aerosol Formation from Acid-Driven Reactive Uptake of Isoprene Epoxydiols under Humid Conditions.

Secondary organic aerosol (SOA) from acid-driven reactive uptake of isoprene epoxydiols (IEPOX) contributes up to 40% of organic aerosol (OA) mass in fine particulate matter. Previous work showed that IEPOX substantially converts particulate inorganic sulfates to surface-active organosulfates (OSs). This decreases aerosol acidity and creates a viscous organic-rich shell that poses as a diffusion barrier, inhibiting additional reactive uptake of IEPOX. To account for this "self-limiting" effect, we developed a phase-separation box model to evaluate parameterizations of IEPOX reactive uptake against time-resolved chamber measurements of IEPOX-SOA tracers, including 2-methyltetrols (2-MT) and methyltetrol sulfates (MTS), at ~ 50% relative humidity. The phase-separation model was most sensitive to the mass accommodation coefficient, IEPOX diffusivity in the organic shell, and ratio of the third-order reaction rate constants forming 2-MT and MTS ( k M T / k M T S ). In particular, k M T / k M T S had to be lower than 0.1 to bring model predictions of 2-MT and MTS in closer agreement with chamber measurements; prior studies reported values larger than 0.71. The model-derived rate constants favor more particulate MTS formation due to 2-MT likely off-gassing at ambient-relevant OA loadings. Incorporating this parametrization into chemical transport models is expected to predict lower IEPOX-SOA mass and volatility due to the predominance of OSs.

Neoadjuvant SHR-1701 with or without chemotherapy in unresectable stage III non-small-cell lung cancer: A proof-of-concept, phase 2 trial.

We conducted a proof-of-concept, phase 2 trial to assess neoadjuvant SHR-1701 with or without chemotherapy, followed by surgery or radiotherapy, and then consolidation SHR-1701 in unresectable stage III non-small-cell lung cancer (NSCLC). In the primary cohort of patients receiving neoadjuvant combination therapy (n = 97), both primary endpoints were met, with a post-induction objective response rate of 58% (95% confidence interval [CI] 47-68) and an 18-month event-free survival (EFS) rate of 56.6% (95% CI 45.2-66.5). Overall, 27 (25%) patients underwent surgery; all achieved R0 resection. Among them, 12 (44%) major pathological responses and seven (26%) pathological complete responses were recorded. The 18-month EFS rate was 74.1% (95% CI 53.2-86.7) in surgical patients and 57.3% (43.0-69.3) in radiotherapy-treated patients. Neoadjuvant SHR-1701 with chemotherapy, followed by surgery or radiotherapy, showed promising efficacy with a tolerable safety profile in unresectable stage III NSCLC. Surgical conversion was feasible in a notable proportion of patients and associated with better survival outcomes.

Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature.

We employed single-cell analysis techniques, specifically the inferCNV method, to dissect the complex progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) through minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). This approach enabled the identification of Cluster 6, which was significantly associated with LUAD progression. Our comprehensive analysis included intercellular interaction, transcription factor regulatory networks, trajectory analysis, and gene set variation analysis (GSVA), leading to the development of the lung progression associated signature (LPAS). Interestingly, we discovered that the LPAS not only accurately predicts the prognosis of LUAD patients but also forecasts genomic alterations, distinguishes between 'cold' and 'hot' tumours, and identifies potential candidates suitable for immunotherapy. PSMB1, identified within Cluster 6, was experimentally shown to significantly enhance cancer cell invasion and migration, highlighting the clinical relevance of LPAS in predicting LUAD progression and providing a potential target for therapeutic intervention. Our findings suggest that LPAS offers a novel biomarker for LUAD patient stratification, with significant implications for improving prognostic accuracy and guiding treatment decisions.

Injectable hydrogel with doxorubicin-loaded ZIF-8 nanoparticles for tumor postoperative treatments and wound repair.

The need for tumor postoperative treatments aimed at recurrence prevention and tissue regeneration have raised wide considerations in the context of the design and functionalization of implants. Herein, an injectable hydrogel system encapsulated with anti-tumor, anti-oxidant dual functional nanoparticles has been developed in order to prevent tumor relapse after surgery and promote wound repair. The utilization of biocompatible gelatin methacryloyl (GelMA) was geared towards localized therapeutic intervention. Zeolitic imidazolate framework-8@ceric oxide (ZIF-8@CeO2, ZC) nanoparticles (NPs) were purposefully devised for their proficiency as reactive oxygen species (ROS) scavengers. Furthermore, injectable GelMA hydrogels loaded with ZC NPs carrying doxorubicin (ZC-DOX@GEL) were tailored as multifunctional postoperative implants, ensuring the efficacious eradication of residual tumor cells and alleviation of oxidative stress. In vitro and in vivo experiments were conducted to substantiate the efficacy in cancer cell elimination and the prevention of tumor recurrence through the synergistic chemotherapy approach employed with ZC-DOX@GEL. The acceleration of tissue regeneration and in vitro ROS scavenging attributes of ZC@GEL were corroborated using rat models of wound healing. The results underscore the potential of the multifaceted hydrogels presented herein for their promising application in tumor postoperative treatments.

GAPDH inhibition mediated by thiol oxidation in human airway epithelial cells exposed to an environmental peroxide.

Intracellular redox homeostasis in the airway epithelium is closely regulated through adaptive signaling and metabolic pathways. However, inhalational exposure to xenobiotic stressors such as secondary organic aerosols (SOA) can alter intracellular redox homeostasis. Isoprene hydroxy hydroperoxide (ISOPOOH), a ubiquitous volatile organic compound derived from the atmospheric photooxidation of biogenic isoprene, is a major contributor to SOA. We have previously demonstrated that exposure of human airway epithelial cells (HAEC) to ISOPOOH induces oxidative stress through multiple mechanisms including lipid peroxidation, glutathione oxidation, and alterations of glycolytic metabolism. Using dimedone-based reagents and copper catalyzed azo-alkynyl cycloaddition to tag intracellular protein thiol oxidation, we demonstrate that exposure of HAEC to micromolar levels of ISOPOOH induces reversible oxidation of cysteinyl thiols in multiple intracellular proteins, including GAPDH, that was accompanied by a dose-dependent loss of GAPDH enzymatic activity. These results demonstrate that ISOPOOH induces an oxidative modification of intracellular proteins that results in loss of GAPDH activity, which ultimately impacts the dynamic regulation of the intracellular redox homeostatic landscape in HAEC.

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

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

Single-cell and bulk RNA-sequencing reveal SPP1 and CXCL12 as cell-to-cell communication markers to predict prognosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) generally presents as an immunosuppressive microenvironment. The characteristics of cell-to-cell communication in the LUAD microenvironment has been unclear. In this study, the LUAD bulk RNA-seq data and single-cell RNA-seq data were retrieved from public dataset. Differential expression genes (DEGs) between LUAD tumor and adjacent non-tumor tissues were calculated by limma algorithm, and then detected by PPI, KEGG, and GO analysis. Cell-cell interactions were explored using the single-cell RNA-seq data. Finally, the first 15 CytoHubba genes were used to establish related pathways and these pathways were used to characterize the immune-related ligands and their receptors in LUAD. Our analyses showed that monocytes or macrophages interact with tissue stem cells and NK cells via SPP1 signaling pathway and tissue stem cells interact with T and B cells via CXCL signaling pathway in different states. Hub genes of SPP1 participated in SPP1 signaling pathway, which was negatively correlated with CD4+ T cell and CD8+ T cell. The expression of SPP1 in LUAD tumor tissues was negatively correlated with the prognosis. While CXCL12 participated in CXCL signaling pathway, which was positively correlated with CD4+ T cell and CD8+ T cell. The role of CXCL12 in LUAD tumor tissues exhibits an opposite effect to that of SPP1. This study reveals that tumor-associated monocytes or macrophages may affect tumor progression. Moreover, the SPP1 and CXCL12 may be the critic genes of cell-to-cell communication in LUAD, and targeting these pathways may provide a new molecular mechanism for the treatment of LUAD.

Purine metabolism in lung adenocarcinoma: A single-cell analysis revealing prognostic and immunotherapeutic insights.

Lung adenocarcinoma (LUAD) is a prevalent subtype of lung cancer, yet the contribution of purine metabolism (PM) to its pathogenesis remains poorly elucidated. PM, a critical component of intracellular nucleotide synthesis and energy metabolism, is hypothesized to exert a significant influence on LUAD development. Herein, we employed single-cell analysis to investigate the role of PM within the tumour microenvironment (TME) of LUAD. PM scoring (PMS) across distinct cell types was determined using AUCell, UCell, singscore and AddModuleScore algorithms. Subsequently, we explored communication networks among cells within high- and low-PMS groups, establishing a robust PM-associated signature (PAS) utilizing a comprehensive dataset comprising LUAD samples from TCGA and five GEO datasets. Our findings revealed that the high-PMS group exhibited intensified cell interactions, while the PAS, constructed using PM-related genes, demonstrated precise prognostic predictive capability. Notably, analysis across the TCGA dataset and five GEO datasets indicated that low-PAS patients exhibited a superior prognosis. Furthermore, the low-PAS group displayed increased immune cell infiltration and elevated CD8A expression, coupled with reduced PD-L1 expression. Moreover, data from eight publicly available immunotherapy cohorts suggested enhanced immunotherapy outcomes in the low-PAS group. These results underscore a close association between PAS and tumour immunity, offering predictive insights into genomic alterations, chemotherapy drug sensitivity and immunotherapy responses in LUAD. The newly established PAS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.

Unraveling the role of low-density lipoprotein-related genes in lung adenocarcinoma: Insights into tumor microenvironment and clinical prognosis.

BACKGROUND: The hypothesized link between low-density lipoprotein (LDL) and oncogenesis has garnered significant interest, yet its explicit impact on lung adenocarcinoma (LUAD) remains to be elucidated. This investigation aims to demystify the function of LDL-related genes (LRGs) within LUAD, endeavoring to shed light on the complex interplay between LDL and carcinogenesis. METHODS: Leveraging single-cell transcriptomics, we examined the role of LRGs within the tumor microenvironment (TME). The expression patterns of LRGs across diverse cellular phenotypes were delineated using an array of computational methodologies, including AUCell, UCell, singscore, ssGSEA, and AddModuleScore. CellChat facilitated the exploration of distinct cellular interactions within LDL_low and LDL_high groups. The findmarker utility, coupled with Pearson correlation analysis, facilitated the identification of pivotal genes correlated with LDL indices. An integrative approach to transcriptomic data analysis was adopted, utilizing a machine learning framework to devise an LDL-associated signature (LAS). This enabled the delineation of genomic disparities, pathway enrichments, immune cell dynamics, and pharmacological sensitivities between LAS stratifications. RESULTS: Enhanced cellular crosstalk was observed in the LDL_high group, with the CoxBoost+Ridge algorithm achieving the apex c-index for LAS formulation. Benchmarking against 144 extant LUAD models underscored the superior prognostic acuity of LAS. Elevated LAS indices were synonymous with adverse outcomes, diminished immune surveillance, and an upsurge in pathways conducive to neoplastic proliferation. Notably, a pronounced susceptibility to paclitaxel and gemcitabine was discerned within the high-LAS cohort, delineating prospective therapeutic corridors. CONCLUSION: This study elucidates the significance of LRGs within the TME and introduces an LAS for prognostication in LUAD patients. Our findings accentuate putative therapeutic targets and elucidate the clinical ramifications of LAS deployment.

USP3 promotes cisplatin resistance in non-small cell lung cancer cells by suppressing ACOT7-regulated ferroptosis.

This study aims to investigate the role and mechanism of ubiquitin-specific protease 3 (USP3) in cisplatin (DDP) in non-small cell lung cancer (NSCLC). USP3 expression in NSCLC cells was detected using reverse transcription quantitative PCR and Western blot. DDP-resistant cells were constructed and cell counting kit-8 assay determined the IC 50 of cells to DDP. USP3 expression was silenced in DDP-resistant cells, followed by detection of cell proliferation by clone formation assay, iron ion contents, ROS, MDA, and GSH levels by kits, GPX4 and ACSL4 protein expressions by Western blot. The binding between USP3 and ACOT7 was analyzed using Co-IP, and the ubiquitination level of ACOT7 was measured. USP3 and ACOT7 were highly expressed in NSCLC cells and further increased in drug-resistant cells. USP3 silencing reduced the IC 50 of cells to DDP and diminished the number of cell clones. Moreover, USP3 silencing suppressed GSH and GPX4 levels, upregulated iron ion contents, ROS, MDA, and ACSL4 levels, and facilitated ferroptosis. Mechanistically, USP3 upregulated ACOT7 protein expression through deubiquitination. ACOT7 overexpression alleviated the promoting effect of USP7 silencing on ferroptosis in NSCLC cells and enhanced DDP resistance. To conclude, USP3 upregulated ACOT7 protein expression through deubiquitination, thereby repressing ferroptosis in NSCLC cells and enhancing DDP resistance.

Clinical prognostication and immunotherapy response prediction in esophageal squamous cell carcinoma using the DNA damage repair-associated signature.

BACKGROUND: The relationship between DNA damage repair (DDR) and cancer is intricately intertwined; however, its specific role in esophageal squamous cell carcinoma (ESCC) remains enigmatic. METHODS: Employing single-cell analysis, we delineated the functionality of DDR-related genes within the tumor microenvironment (TME). A diverse array of scoring mechanisms, including AUCell, UCell, singscore, ssgsea, and AddModuleScore, were harnessed to scrutinize the activity of DDR-related genes across different cell types. Differential pathway alterations between high-and low-DDR activity cell clusters were compared. Furthermore, leveraging multiple RNA-seq datasets, we constructed a robust DDR-associated signature (DAS), and through integrative multiomics analysis, we explored differences in prognosis, pathways, mutational landscapes, and immunotherapy predictions among distinct DAS groups. RESULTS: Notably, high-DDR activity cell subpopulations exhibited markedly enhanced cellular communication. The DAS demonstrated uniformity across multiple datasets. The low-DAS group exhibited improved prognoses, accompanied by heightened immune infiltration and elevated immune checkpoint expression. SubMap analysis of multiple immunotherapy datasets suggested that low-DAS group may experience enhanced immunotherapy responses. The "oncopredict" R package analyzed and screened sensitive drugs for different DAS groups. CONCLUSION: Through the integration of single-cell and bulk RNA-seq data, we have developed a DAS associated with prognosis and immunotherapy response. This signature holds promise for the future stratification and personalized treatment of ESCC patients in clinical settings.