Preoperative diagnosis of solitary pulmonary nodules with a novel hematological index model based on circulating tumor cells

ObjectivePreoperative noninvasive diagnosis of the benign or malignant solitary pulmonary nodule (SPN) is still important and difficult for clinical decisions and treatment. This study aimed to assist in the preoperative diagnosis of benign or malignant SPN using blood biomarkers.MethodsA total of 286 patients were recruited for this study. The serum FR+CTC, TK1, TP, TPS, ALB, Pre-ALB, ProGRP, CYFRA21-1, NSE, CA50, CA199, and CA242 were detected and analyzed.ResultsIn the univariate analysis, age, FR+CTC, TK1, CA50, CA19.9, CA242, ProGRP, NSE, CYFRA21-1, and TPS showed the statistical significance of a correlation with malignant SPNs (P <0.05). The highest performing biomarker is FR+CTC (odd ratio [OR], 4.47; 95% CI: 2.57–7.89; P <0.001). The multivariate analysis identified that age (OR, 2.69; 95% CI: 1.34–5.59, P = 0.006), FR+CTC (OR, 6.26; 95% CI: 3.09–13.37, P <0.001), TK1 (OR, 4.82; 95% CI: 2.4–10.27, P <0.001), and NSE (OR, 2.06; 95% CI: 1.07–4.06, P = 0.033) are independent predictors. A prediction model based on age, FR+CTC, TK1, CA50, CA242, ProGRP, NSE, and TPS was developed and presented as a nomogram, with a sensitivity of 71.1% and a specificity of 81.3%, and the AUC was 0.826 (95% CI: 0.768–0.884).ConclusionsThe novel prediction model based on FR+CTC showed much stronger performance than any single biomarker, and it can assist in predicting benign or malignant SPNs

Cost-effectiveness analysis of toripalimab plus chemotherapy as the first-line treatment in patients with advanced non-small cell lung cancer (NSCLC) without EGFR or ALK driver mutations from the Chinese perspective

Objectives: The results of a CHOICE-1 study demonstrated the superior efficacy of toripalimab (anti-PD-1 antibody) plus chemotherapy for patients with advanced non–small cell lung cancer (NSCLC), with a manageable safety profile. This study was performed to evaluate the economic value of this treatment for this patient population from the Chinese payer’s perspective.Materials and methods: Basic data were derived from the CHOICE-1 study. Markov models were developed to simulate the process of advanced NSCLC, including the progression-free survival (PFS), progressive disease (PD), and death in intention-to-treat (ITT) populations, as well as patients with squamous or non-squamous NSCLC. The cost was obtained from the local institution, and the value of utilities referred to previous studies. Monte Carlo simulations were performed to depict the probabilistic scatter plots of the incremental cost-effectiveness ratio (ICER) and acceptability curves, aiming to address the uncertainty of model inputs.Results: Compared with standard chemotherapy, toripalimab plus chemotherapy yields an ICER of $21,563 per quality-adjusted life year (QALY) in the ITT population. For patients with squamous NSCLC, comparing the combined therapy with chemotherapy led to an ICER of$18,369 per QALY, while the ICER was $24,754 per QALY in patients with non-squamous NSCLC. With the threshold of willingness to pay we set ($37,653 per QALY), toripalimab plus chemotherapy was cost-effective in these patient populations.Conclusion: For patients with advanced NSCLC, toripalimab plus chemotherapy was an optimal choice as first-line treatment, regardless of histology

Genomic landscape of lung adenocarcinomas in different races

BACKGROUND: Lung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood. METHODS: We analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes. RESULTS: Native Americans had significantly higher rates of insertions and deletions than other races (P\u3c0.001). Among patients with lung adenocarcinomas, EGFR and KRAS were the highest discrepancy genes in the different racial groups (P\u3c0.001). The EGFR exon 21 L858R point mutation was three times higher in Asians than in all other races (P\u3c0.001). Asians, Whites, and Blacks had 4.7%, 3.1%, and 1.8% ALK rearrangement, respectively (P\u3c0.001). White patients had the highest rates of reported KRAS G12C (15.51%) than other races (P\u3c0.001). Whites (17.2%), Blacks (15.1%), and Other (15.7%) had higher rates of STK11 mutation than Asians (3.94%) (P\u3c0.001). RET rearrangement and ERBB2 amplification were more common in Asian patients than in Other racial groups. Apart from point mutations, structural variations, and fusion genes, we identified a significant amount of copy number alterations in each race. CONCLUSIONS: The tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients

Charged Particle (Negative Ion)-Based Cloud Seeding and Rain Enhancement Trial Design and Implementation

China has been suffering from water shortage for a long time. Weather modification and rainfall enhancement via cloud seeding has been proved to be effective to alleviate the problem. Current cloud seeding methods mostly rely on solid carbon dioxide and chemicals such as silver iodide and hygroscopic salts, which may have negative impacts on the environment and are expensive to operate. Lab experiments have proved the efficiency of ion-based cloud seeding compared with traditional methods. Moreover, it is also more environmentally friendly and more economical to operate at a large scale. Thus, it is necessary to carry out a field experiment to further investigate the characteristics and feasibility of the method. This paper provides the design and implementation of the ion-based cloud seeding and rain enhancement trial currently running in Northwest China. It introduces the basic principle of the trial and the devices developed for it, as well as the installation of the bases and the evaluation method design for the trial

DataSheet1_Identification pyroptosis-related gene signature to predict prognosis and associated regulation axis in colon cancer.docx

Background: Pyroptosis is an important component of the tumor microenvironment and associated with the occurrence and progression of cancer. As the expression of pyroptosis-related genes and its impact on the prognosis of colon cancer (CC) remains unclear, we constructed and validated a pyroptosis-related genes signature to predict the prognosis of patients with CC.Methods: Microarray datasets and the follow-up clinical information of CC patients were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. Candidate genes were screened out for further analysis. Various methods were combined to construct a robust pyroptosis-related genes signature for predicting the prognosis of patients with CC. Based on the gene signature and clinical features, a decision tree and nomogram were developed to improve risk stratification and quantify risk assessment for individual patients.Results: The pyroptosis-related genes signature successfully discriminated CC patients with high-risk in the training cohorts. The prognostic value of this signature was further confirmed in independent validation cohort. Multivariable Cox regression and stratified survival analysis revealed this signature was an independent prognostic factor for CC patients. The decision tree identified risk subgroups powerfully, and the nomogram incorporating the gene signature and clinical risk factors performed well in the calibration plots.Conclusion: Pyroptosis-related genes signature was an independent prognostic factor, and can be used to predict the prognosis of patients with CC.</p

Image_2_Genomic landscape of lung adenocarcinomas in different races.jpeg

BackgroundLung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood.MethodsWe analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes.ResultsNative Americans had significantly higher rates of insertions and deletions than other races (PConclusionsThe tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients.</p

Image_4_Genomic landscape of lung adenocarcinomas in different races.jpeg

BackgroundLung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood.MethodsWe analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes.ResultsNative Americans had significantly higher rates of insertions and deletions than other races (PConclusionsThe tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients.</p

Image_1_Genomic landscape of lung adenocarcinomas in different races.jpeg

BackgroundLung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood.MethodsWe analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes.ResultsNative Americans had significantly higher rates of insertions and deletions than other races (PConclusionsThe tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients.</p