Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

Integrating bulk-RNA sequencing and single-cell sequencing analyses to characterize adenosine-enriched tumor microenvironment landscape and develop an adenosine-related prognostic signature predicting immunotherapy in lung adenocarcinoma.

The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.

CDC45 promotes the stemness and metastasis in lung adenocarcinoma by affecting the cell cycle.

OBJECTIVE: This study aimed to assess the functions of cell division cycle protein 45 (CDC45) in Non-small cell lung cancer (NSCLC) cancer and its effects on stemness and metastasis. METHODS: Firstly, differentially expressed genes related to lung cancer metastasis and stemness were screened by differential analysis and lasso regression. Then, in vitro, experiments such as colony formation assay, scratch assay, and transwell assay were conducted to evaluate the impact of CDC45 knockdown on the proliferation and migration abilities of lung cancer cells. Western blotting was used to measure the expression levels of related proteins and investigate the regulation of CDC45 on the cell cycle. Finally, in vivo model with subcutaneous injection of lung cancer cells was performed to verify the effect of CDC45 on tumor growth. RESULTS: This study identified CDC45 as a key gene potentially influencing tumor stemness and lymph node metastasis. Knockdown of CDC45 not only suppressed the proliferation and migration abilities of lung cancer cells but also caused cell cycle arrest at the G2/M phase. Further analysis revealed a negative correlation between CDC45 and cell cycle-related proteins, stemness-related markers, and tumor mutations. Mouse experiments confirmed that CDC45 knockdown inhibited tumor growth. CONCLUSION: As a novel regulator of stemness, CDC45 plays a role in regulating lung cancer cell proliferation, migration, and cell cycle. Therefore, CDC45 may serve as a potential target for lung cancer treatment and provide a reference for further mechanistic research and therapeutic development.

RACGAP1 promotes the progression and poor prognosis of lung adenocarcinoma through its effects on the cell cycle and tumor stemness.

OBJECTION: Investigating the key genes and mechanisms that influence stemness in lung adenocarcinoma. METHODS: First, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes. Then, machine learning methods were employed to screen and identify the key genes within these modules. Lastly, functional analysis of the key genes was conducted through cell scratch assays, colony formation assays, transwell migration assays, flow cytometry cell cycle analysis, and xenograft tumor models. RESULTS: First, two groups of patients with different stemness scores were obtained, where the high stemness score group exhibited poor prognosis and immunotherapy efficacy. Next, LASSO regression analysis and random forest regression were employed to identify genes (PBK, RACGAP1) associated with high stemness scores. RACGAP1 was significantly upregulated in the high stemness score group of lung adenocarcinoma and closely correlated with clinical pathological features, poor overall survival (OS), recurrence-free survival (RFS), and unfavorable prognosis in lung adenocarcinoma patients. Knockdown of RACGAP1 suppressed the migration, proliferation, and tumor growth of cancer cells. CONCLUSION: RACGAP1 not only indicates poor prognosis and limited immunotherapy benefits but also serves as a potential targeted biomarker influencing tumor stemness.

Research progress of N1-methyladenosine RNA modification in cancer.

N1-methyladenosine (m1A) is a post-transcriptionally modified RNA molecule that plays a pivotal role in the regulation of various biological functions and activities. Especially in cancer cell invasion, proliferation and cell cycle regulation. Over recent years, there has been a burgeoning interest in investigating the m1A modification of RNA. Most studies have focused on the regulation of m1A in cancer enrichment areas and different regions. This review provides a comprehensive overview of the methodologies employed for the detection of m1A modification. Furthermore, this review delves into the key players in m1A modification, known as the "writers," "erasers," and "readers." m1A modification is modified by the m1A methyltransferases, or writers, such as TRMT6, TRMT61A, TRMT61B, TRMT10C, NML, and, removed by the demethylases, or erasers, including FTO and ALKBH1, ALKBH3. It is recognized by m1A-binding proteins YTHDF1, TYHDF2, TYHDF3, and TYHDC1, also known as "readers". Additionally, we explore the intricate relationship between m1A modification and its regulators and their implications for the development and progression of specific types of cancer, we discuss how m1A modification can potentially facilitate the discovery of novel approaches for cancer diagnosis, treatment, and prognosis. Our summary of m1A methylated adenosine modification detection methods and regulatory mechanisms in various cancers provides useful insights for cancer diagnosis, treatment, and prognosis. Video Abstract.

Recent advances in the potential role of RNA N4-acetylcytidine in cancer progression.

N4-acetylcytidine (ac4C) is a highly conserved chemical modification widely found in eukaryotic and prokaryotic RNA, such as tRNA, rRNA, and mRNA. This modification is significantly associated with various human diseases, especially cancer, and its formation depends on the catalytic activity of N-acetyltransferase 10 (NAT10), the only known protein that produces ac4C. This review discusses the detection techniques and regulatory mechanisms of ac4C and summarizes ac4C correlation with tumor occurrence, development, prognosis, and drug therapy. It also comments on a new biomarker for early tumor diagnosis and prognosis prediction and a new target for tumor therapy. Video Abstract.

MiR-31-5p alleviates septic cardiomyopathy by targeting BAP1 to inhibit SLC7A11 deubiquitination and ferroptosis.

Septic cardiomyopathy is one of the most severe and common complications in patients with sepsis and poses a great threat to their prognosis. However, the potential mechanisms and effective therapeutic drugs need to be explored. The control of cardiac cell death by miRNAs has emerged as a prominent area of scientific interest in the diagnosis and treatment of heart disorders in recent times. In the present investigation, we discovered that overexpression of miR-31-5p prevented LPS-induced damage to H9C2 cells and that miR-31-5p could inhibit BAP1 production by binding to its 3'-UTR. BRCA1-Associated Protein 1 (BAP1) is a ubiquitin carboxy-terminal hydrolase. BAP1 upregulation blocked effect of miR-31-5p on H9C2 cell injury. Moreover, BAP1 inhibited the expression of solute carrier family 7 member 11 (SLC7A11) by deubiquitinating histone 2 A (H2Aub) on the promoter of SLC7A11. Furthermore, overexpression of miR-31-5p and downregulation of BAP1 inhibited SLC7A11 mediated ferroptosis. In addition, the downregulation of SLC7A11 reversed the inhibitory effect of miR-31-5p on the expression of myocardial injury and inflammatory factors, and cell apoptosis was reversed. In conclusion, these results indicate that miR-31-5p alleviates malignant development of LPS-induced H9C2 cell injury by targeting BAP1 and regulating SLC7A11 deubiquitination-mediated ferroptosis, which confirmed the protective effect of miR-31-5p on H9C2 cell injury and revealed potential mechanisms that may provide new targets for treatment of septic cardiomyopathy.

Association of parathyroid hormone with risk of hypertension and type 2 diabetes: a dose-response meta-analysis.

BACKGROUND: Despite an increase in parathyroid hormone (PTH) has been reported to be associated with a higher risk of hypertension and type 2 diabetes (T2D), the comprehensive evaluation of the dose-response relationship between PTH and hypertension and T2D remains ambiguous. Therefore, a dose-response meta-analysis was performed to quantitatively investigate this association. METHODS: PubMed, Web of Science, and Embase were systematically searched up to May 2023. Random-effect models were used to estimate the summary odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic splines were used to model the dose-response association. RESULTS: Ten articles (including 13 studies) were identified, with a total of 11,878 cases and 51,234 participants in the meta-analysis. Of these studies, eight (five cohort and three cross-sectional) studies investigated the association of PTH with hypertension; five (two cohort and three cross-sectional) studies assessed the association of PTH with T2D. The results showed a positive relationship between PTH and the risk of hypertension (OR,1.24, 95% CI: 1.16-1.33). We found a linear association between PTH and hypertension (Pnon-linearity= 0.222). In the dose-response analysis, the risk of hypertension increased 5% for every 10 pg/ml increase in PTH (OR,1.05, 95% CI: 1.02-1.08). The pooled OR of T2D risk for a 10 pg/ml increase in PTH was 1.00 (95% CI: 0.98-1.02). CONCLUSIONS: Elevated PTH is associated with an increased risk of hypertension. However, the evidence of the association between PTH and T2D is limited, and more well-designed studies need to be explored.

Human health risks of heavy metal(loid)s mediated through crop ingestion in a coal mining area in Eastern China.

The heavy metal(loid)s (HMs) in soils can be accumulated by crops grown, which is accompanied by crop ingestion into the human body and then causes harm to human health. Hence, the health risks posed by HMs in three crops for different populations were assessed using Health risk assessment (HRA) model coupled with Monte Carlo simulation. Results revealed that Zn had the highest concentration among three crops; while Ni was the main polluting element in maize and soybean, and As in rice. Non-carcinogenic risk for all populations through rice ingestion was at an "unacceptable" level, and teenagers suffered higher risk than adults and children. All populations through ingestion of three crops might suffer Carcinogenic risk, with the similar order of Total carcinogenic risk (TCR): TCRAdults > TCRTeenagers > TCRChildren. As and Ni were identified as priority control HMs in this study area due to their high contribution rates to health risks. According to the HRA results, the human health risk was associated with crop varieties, HM species, and age groups. Our findings suggest that only limiting the Maximum allowable intake rate is not sufficient to prevent health risks caused by crop HMs, thus more risk precautions are needed.

Adaptive Super-Twisting Sliding Mode Control for Robot Manipulators with Input Saturation.

The paper investigates a modified adaptive super-twisting sliding mode control (ASTSMC) for robotic manipulators with input saturation. To avoid singular perturbation while increasing the convergence rate, a modified sliding mode surface (SMS) is developed in this method. Using the proposed SMS, an ASTSMC is developed for robot manipulators, which not only achieves strong robustness but also ensures finite-time convergence. The boundary of lumped uncertainties cannot be easily obtained. A modified adaptive law is developed such that the boundaries of time-varying disturbance and its derivative are not required. Considering input saturation in practical cases, an ASTSMC with saturation compensation is proposed to reduce the effect of input saturation on tracking performances of robot manipulators. The finite-time convergence of the proposed scheme is analyzed. Through comparative simulations against two other sliding mode control schemes, the proposed method has been validated to possess strong adaptability, effectively adjusting control gains; simultaneously, it demonstrates robustness against disturbances and uncertainties.

Hypoxia-inducible factor 1α activates the NLRP3 inflammasome to regulate epithelial differentiation in chronic rhinosinusitis.

BACKGROUND: Chronic rhinosinusitis (CRS) is an upper airway inflammation disease associated with hypoxia-mediated inflammation. The effect of hypoxia-inducible factor 1α (HIF-1α) on NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome activation in the pathogenesis of sinonasal mucosa is unclear. OBJECTIVE: We investigated the effect and mechanism of HIF-1α on NLRP3 inflammasome activation in the primary human nasal epithelial cells (hNECs). METHODS: We measured the expression levels of HIF-1α and the NLRP3 inflammasome in nasal biopsy samples and hNECs derived from negative controls (healthy) and patients with CRS with and without nasal polyps, then further analyzed the specific mechanism of HIF-1α regulation of the NLRP3 inflammasome and its effect on hNEC differentiation. RESULTS: Increased mRNA and protein expression levels of HIF-1α and the NLRP3 inflammasome were found in all CRS biopsy samples. HIF-1α enhanced expression of phosphorylated NLRP3 (S295) in both HEK293T cells and hNECs; it also promoted recruitment of caspase-1 and apoptotic speck-like protein containing caspase recruitment domain (aka ASC) by NLRP3. HIF-1α also improved NLRP3's stability by preventing NLRP3 degradation caused by hypoxia-mediated inflammation. In addition, HIF-1α could also increase expression of Mucin5AC and decrease expression of α-tubulin by promoting activation of the NLRP3 inflammasome in hNECs. In addition, HIF-1α could also directly promote P63 expression in hNECs. CONCLUSION: HIF-1α could potentially induce cilia loss and enhance the proliferation of goblet cells, possibly mediated by the regulation of NLRP3 phosphorylation in CRS inflammation.

Celastrol Pyrazine Derivative Alleviates Silicosis Progression via Inducing ROS-Mediated Apoptosis in Activated Fibroblasts.

Silicosis is a complex occupational disease without recognized effective treatment. Celastrol, a natural product, has shown antioxidant, anti-inflammatory, and anti-fibrotic activities, but the narrow therapeutic window and high toxicity severely limit its clinical application. Through structural optimization, we have identified a highly efficient and low-toxicity celastrol derivative, CEL-07. In this study, we systematically investigated the therapeutic potential and underlying mechanisms of CEL-07 in silicosis fibrosis. By constructing a silicosis mouse model and analyzing with HE, Masson, Sirius Red, and immunohistochemical staining, CEL-07 significantly prevented the progress of inflammation and fibrosis, and it effectively improved the lung respiratory function of silicosis mice. Additionally, CEL-07 markedly suppressed the expression of inflammatory factors (IL-6, IL-1α, TNF-α, and TNF-ß) and fibrotic factors (α-SMA, collagen I, and collagen III), and promoted apoptosis of fibroblasts by increasing ROS accumulation. Moreover, bioinformatics analysis combined with experimental validation revealed that CEL-07 inhibited the pathways associated with inflammation (PI3K-AKT and JAK2-STAT3) and the expression of apoptosis-related proteins. Overall, these results suggest that CEL-07 may serve as a potential candidate for the treatment of silicosis.

SPOCK1, as a potential prognostic and therapeutic biomarker for lung adenocarcinoma, is associated with epithelial-mesenchymal transition and immune evasion.

BACKGROUND: The occurrence of epithelial-mesenchymal transition (EMT) and immune evasion is considered to contribute to poor prognosis in lung adenocarcinoma (LUAD). Therefore, this study aims to explore the key oncogenes that promote EMT and immune evasion and reveal the expression patterns, prognostic value, and potential biological functions. METHODS: Firstly, we identified gene modules associated with EMT and Tumor Immune Dysfunction and Exclusion (TIDE) through weighted gene co-expression network analysis (WGCNA). Next, we utilized differential analysis and machine learning to identify the key genes and validate them. Moreover, we analyzed the correlation between key genes and tumor microenvironment remodeling, drug sensitivity, as well as mutation frequency. Furthermore, we explored and validated their malignant biological characteristics through in vitro experiments and clinical samples. Finally, potential drugs for LUAD were screened based on CMap and validated through experiments. RESULTS: Firstly, WGCNA analysis revealed that red and green modules were highly correlated with EMT and TIDE. Among them, upregulated expression of SPOCK1 was observed in lung adenocarcinoma tissues and was associated with poor prognosis. Additionally, patients in the high SPOCK1 group showed more activation of malignant oncogenic pathways, higher infiltration of immunosuppressive components, and a higher frequency of mutations. The knockdown of SPOCK1 suppressed invasion and metastasis capabilities of lung adenocarcinoma cells, and the high expression of SPOCK1 was associated with low infiltration of CD8+ T cells. Therapeutic aspects, SPOCK1 can be a candidate indicator for drug sensitivity and CMap showed that VER-155008 was the drug candidate with the largest perturbation effect on the SPOCK1 expression profile. In vitro and in vivo experiments validated the cancer-inhibitory effect of VER-155008 in LUAD. CONCLUSION: This study revealed through comprehensive bioinformatics analysis and experimental analysis that SPOCK1 can promote EMT and immune escape in LUAD, and it may serve as a promising candidate prognostic biomarker and therapeutic target for LUAD.

Construction and Validation of a Novel Immune-Related Gene Pairs-Based Prognostic Model in Lung Adenocarcinoma.

OBJECT: Focus on immune-related gene pairs (IRGPs) and develop a prognostic model to predict the prognosis of patients with lung adenocarcinoma (LUAD). METHODS: First, the LUAD patient dataset was downloaded from The Cancer Genome Atlas database, and paired analysis of immune-related genes was subsequently conducted. Then, LASSO regression was used to screen prognostic IRGPs for building a risk prediction model. Meanwhile, the Gene Expression Omnibus database was used for external validation of the model. Next, the clinical predictive power of IRGPs features was assessed by uni-multivariate Cox regression analysis, the infiltration of key immune cells in high and low IRGPs risk groups was analyzed with CIBERSORT, quanTIseq, and Timer, and the key pathways enriched for IRGPs were assessed using the Kyoto Encyclopedia of Genes and Genomes. Finally, the expression and related functions of key immune cells and genes were verified by immunofluorescence and cell experiments of tissue samples. RESULTS: It was revealed that the risk score of 19 IRGPs could be used as accurate indicators to evaluate the prognosis of LUAD patients, and the risk score was mainly related to T cell infiltration based on CIBERSORT analysis. Two genes of IRGPs, IL6, and CCL2, were found to be closely associated with the expression of PD-1/PD-L1 and the function of T-cells. Depending on the results of tissue immunofluorescence, IL6, CCL2, and T cells were highly expressed in the LUAD tissues of patients. Furthermore, IL6 and CCL2 were positively correlated with the expression of T cells. Besides, qRT-PCR assay in four different LUAD cells proved that IL6 and CCL2 were positively correlated with the expression of PD-L1 (P < .001). CONCLUSIONS: Based on 19 IRGPs, an effective prognosis model was established to predict the prognosis of LUAD patients. In addition, IL6 and CCL2 are closely related to the function of T-cells.

IKKε protects against starvation-induced NLRP3 inflammasome and pyroptosis in H9c2 cells by alleviating mitochondrial injury.

The deprivation of myocardial nutrition causes cardiomyocyte death and disturbance of energy metabolism. IKKε plays an important regulatory role in many biological events such as inflammation, redox reaction, cell death, etc. However, the more in-depth mechanism by which IKKε contributes to cardiomyocytes death in nutrition deprivation remains poorly understood. IKKε expression was knocked down by siRNA in H9c2 cells, and cells were cultured under starvation conditions to simulate ischemic conditions. Starvation triggered greater NLRP3 activation, accompanied by more IL-1ß, IL-18 and caspase-1 release in the siIKKε H9c2 cells compared with the control H9c2 cells. Western blot and immunofluorescence showed that the IKKε konckdown promoted NLRP3 expressions and ROS release under starvation conditions. Furthermore, electron micrography and JC-1 analysis revealed that IKKε konckdown resulted in aggravated mitochondrial damage and more mitochondrial ROS (mtROS) released in vitro. Notably, Western blot analysis showed that IKKε deficiency activated the TBK1 and IRF3 signaling pathways to promote pyroptosis in vitro. Collectively, our results indicate that IKKε protects against cardiomyocyte injury by reducing mitochondrial damage and NLRP3 expression following nutrition deprivation via regulation of the TBK1/IRF3 signaling pathway. This study further revealed the mechanism of IKKε in inflammation and myocardial nutrition deprivation.

Stomatin-like protein-2 attenuates macrophage pyroptosis and H9c2 cells apoptosis by protecting mitochondrial function.

Myocytes undergoing hypoxia condition can recruit macrophages and cause pro-inflammation initiation around the injury area. Mitochondrial dysfunction is related to macrophage pyroptosis. Stomatin-like protein-2 (SLP-2) can regulate mitochondrial biogenesis and function. Whether SLP-2 could affect macrophage pyroptosis remains unclear. In this study, bone marrow derived macrophages (BMDMs) were extracted from WT and SLP-2 knocked out mice, then stimulated by LPS/Nigericin. Western blot showed that SLP-2-/- promoted the expression of NLRP3, GSDMD-N, caspase-11 in macrophages, which means the deficiency of SLP-2 augments macrophage pyroptosis. Higher fluorescence intensity of dihydroethidium and TUNEL represented the increased ROS releasing and macrophage programmed death in SLP-2 deficiency groups. The immunofluorescence intensity of MtioTracker Red decreased and that of mitochondrial ROS (mtROS) increased in SLP-2 deletion groups with LPS/Nigericin stimulation, representing the increased mitochondrial damage. The expression level of HIF-1α increased in SLP-2 deletion macrophages with LPS and Nigericin stimulation. The level of Parkin and the ratio of LC3II/I decreased in SLP-2 deficiency macrophages after stimulated by LPS/Nigericin, compared with untreated macrophages. H9c2 cells were cultured in hypoxia condition before being cocultured with macrophage supernatant. The cocultured H9c2 cells were injured due to the serious pyroptosis of SLP-2 deficiency macrophages. According to these results, we suggest that SLP-2 can reduce macrophage pyroptosis and relieve hypoxia H9c2 cells injury through protecting mitochondrial function.

Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database.

BACKGROUND: To determine the populations who suitable for surgical treatment in elderly patients (age ≥ 75 y) with IA stage. METHODS: The clinical data of NSCLC patients diagnosed from 2010 to 2015 were collected from the SEER database and divided into surgery group (SG) and no-surgery groups (NSG). The confounders were balanced and differences in survival were compared between groups using PSM (Propensity score matching, PSM). Cox regression analysis was used to screen the independent factors that affect the Cancer-specific survival (CSS). The surgery group was defined as the patients who surgery-benefit and surgery-no benefit according to the median CSS of the no-surgery group, and then randomly divided into training and validation groups. A surgical benefit prediction model was constructed in the training and validation group. Finally, the model is evaluated using a variety of methods. RESULTS: A total of 7297 patients were included. Before PSM (SG: n = 3630; NSG: n = 3665) and after PSM (SG: n = 1725, NSG: n = 1725) confirmed that the CSS of the surgery group was longer than the no-surgery group (before PSM: 82 vs. 31 months, P < .0001; after PSM: 55 vs. 39 months, P < .0001). Independent prognostic factors included age, gender, race, marrital, tumor grade, histology, and surgery. In the surgery cohort after PSM, 1005 patients (58.27%) who survived for more than 39 months were defined as surgery beneficiaries, and the 720 patients (41.73%) were defined surgery-no beneficiaries. The surgery group was divided into training group 1207 (70%) and validation group 518 (30%). Independent prognostic factors were used to construct a prediction model. In training group (AUC = .678) and validation group (AUC = .622). Calibration curve and decision curve prove that the model has better performance. CONCLUSIONS: This predictive model can well identify elderly patients with stage IA NSCLC who would benefit from surgery, thus providing a basis for clinical treatment decisions.

Relationship Between Neutrophil-To-Lymphocyte Ratio and Brain Metastasis in Non-Small Cell Lung Cancer Patients.

OBJECTIVE: To investigate the relationship between the neutrophil-to-lymphocyte ratio (NLR) of patients with non-small cell lung cancer (NSCLC) and their risk of developing brain metastases after adjusting for confounding factors. METHODS: A retrospective observational study of the general data of patients with NSCLC diagnosed from January 2016 to December 2020. Multivariate logistic regression was used to calculate the dominance ratio (OR) with 95% confidence interval (CI) for NLR and NSCLC brain metastases with subgroup analysis. Generalized summation models and smoothed curve fitting were used to identify whether there was a nonlinear relationship between them. RESULTS: In all 3 models, NLR levels were positively correlated with NSCLC brain metastasis (model 1: OR: 1.12, 95% CI: 1.01-1.23, P = .025; model 2: OR: 1.16, 95% CI: 1.04-1.29, P = .007; model 3: OR: 1.20, 95% CI: 1.05-1.37, P = .006). Stratified analysis showed that this positive correlation was present in patients with adenocarcinoma (LUAD) and female patients (LUAD: OR: 1.30, 95% CI: 1.10-1.54, P = .002; female: OR: 1.52, 95% CI: 1.05-2.20, P = .026), while there was no significant correlation in patients with squamous carcinoma (LUSC) and male patients (LUSC: OR:0.76,95% CI:0.38- 1.53, P = .443; male: OR:1.13, 95% CI:0.95-1.33, P = .159). CONCLUSION: This study showed that elevated levels of NLR were independently associated with an increased risk of developing brain metastases in patients with NSCLC, and that this correlation varied by TYPE and SEX, with a significant correlation in female patients and patients with LUAD.

Development and Validation of Machine Learning Models to Predict Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer: A Multi-Center Retrospective Radiomics Study.

OBJECTIVE: To develop and validate a generalized prediction model that can classify epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer patients. METHODS: A total of 346 patients (296 in the training cohort and 50 in the validation cohort) from four centers were included in this retrospective study. First, 1085 features were extracted using IBEX from the computed tomography images. The features were screened using the intraclass correlation coefficient, hypothesis tests and least absolute shrinkage and selection operator. Logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM) were used to build a radiomics model for classification. The models were evaluated using the following metrics: area under the curve (AUC), calibration curve (CAL), decision curve analysis (DCA), concordance index (C-index), and Brier score. RESULTS: Sixteen features were selected, and models were built using LR, DT, RF, and SVM. In the training cohort, the AUCs was .723, .842, .995, and .883; In the validation cohort, the AUCs were .658, 0567, .88, and .765. RF model with the best AUC, its CAL, C-index (training cohort=.998; validation cohort=.883), and Brier score (training cohort=.007; validation cohort=0.137) showed a satisfactory predictive accuracy; DCA indicated that the RF model has better clinical application value. CONCLUSION: Machine learning models based on computed tomography images can be used to evaluate EGFR status in patients with non-small cell lung cancer, and the RF model outperformed LR, DT, and SVM.

Seasonal Variation and Contamination Risk Assessment of Heavy Metals in Surface Sediment of an Estuary Alluvial Island in Eastern China.

The heavy metal pollution of estuary wetlands caused by industrial and agricultural production activities has aroused widespread concern. The Hakanson Pollution index, Geo-accumulation index (Igeo) and Redundancy analysis were used to explore the seasonal variation and contamination risk of heavy metals in surface sediments. Results showed that the heavy metal concentrations were ranked in descending order: Cd > Cu > Zn > Pb > Cr. The analysis result of HPI and Igeo showed that there was a low level of heavy metal contamination both in summer and winter. Redundancy analysis showed that the correlation between heavy metals and physicochemical properties of sediment was significantly different in winter and summer. Our findings provide scientific support for the prevention of heavy metal pollution in estuary wetlands.