Diagnosis Of Lung Cancer Patients Research Articles

An Effective Lung Cancer Diagnosis Model Using the CNN Algorithm

The disease known as lung cancer is a serious condition that may be deadly if it is not diagnosed at an early stage. The diagnosis of lung cancer has to be improved, and there is a need for a cost-effective and user-friendly system that leverages state-of-the-art data science technology. This would help simplify operations, save time and money, and improve diagnosis. This research suggests the use of a convolutional neural network (CNN) architecture for the purpose of categorizing three unique histopathological pictures, namely benign, adenocarcinoma, and squamous cell carcinoma. The purpose of this study is to apply the CNN model to properly classify these three kinds of cancers and to compare the accuracy of the CNN model to the accuracy of other techniques that have been employed in investigations that are comparable to this one. The CNN model was not used in any of the preceding research for the purpose of categorizing these particular histopathological pictures; hence, the relevance of this work cannot be overstated. It is possible to get more positive treatment results by correctly classifying malignant tumors as early as possible. In training, the CNN model obtained an accuracy of 96.11%, and in validation, it earned an accuracy of 97.2%. The suggested method has the potential to improve lung cancer diagnosis in patients by classifying them into subgroups according to the symptoms they exhibit. This approach to machine learning, which makes use of the random forest technique, has the potential to reduce the amount of time, resources, and labor required. Utilizing the CNN model to categorize histopathological pictures may, ultimately, improve the diagnostic accuracy of lung cancer and save lives by allowing early disease identification.

Gold Nanoprobes for Detection of a Crucial EGFR Deletion for Early Diagnosis of Non-Small-Cell Lung Cancer

Gold nanoparticles (AuNPs) exhibit improved optical and spectral properties compared to bulk materials, making them suitable for the detection of DNA, RNA, antigens, and antibodies. Here, we describe a simple, selective, and rapid non-cross linking detection assay, using approx. 35 nm spherical Au nanoprobes, for a common mutation occurring in exon 19 of the epidermal growth factor receptor (EGFR), associated with non-small-cell lung cancer cells. AuNPs were synthesized based on the seed-mediated growth method and functionalized with a specific 16 bp thiolated oligonucleotide using a pH-assisted method. Both AuNPs and Au nanoprobes proved to be highly stable and monodisperse through ultraviolet-visible spectrophotometry, dynamic light scattering (DLS), and electrophoretic light scattering (ELS). Our results indicate a detection limit of 1.5 µg mL−1 using a 0.15 nmol dm−3 Au nanoprobe concentration. In conclusion, this work presents an effective possibility for a straightforward, fast, and inexpensive alternative for the detection of DNA sequences related to lung cancer, leading to a potential platform for early diagnosis of lung cancer patients.

The Impact of the SARS-COV-2 Pandemic on the Diagnosis of Lung Cancer Patients

Abstract The SARS-COV-2 pandemic had an important impact on the diagnosis of all pathologies, including lung cancer. According to Global Cancer Observatory 2020, lung cancer is the leading cause of cancer death (18%). The study aims are the comparative evaluation of lung cancer diagnosis and optimal identification of the factors that influenced the establishment of this diagnosis in the pre-pandemic and SARS-COV-2 pandemic periods. This retrospective study included patients >18 years-old, diagnosed with lung carcinoma on surgical specimens in „Marius Nasta” Institute of Pneumophtisiology, grouped in two cohorts: pre-pandemic (March 01, 2019 - February 29, 2020, N=370) and pandemic (March 01, 2020 - February 28, 2021, N=177). Demographic, clinical, and paraclinical information have been collected from the Institute's database, and statistically analyzed (IBM SPSS Statistics 21). The number of newly diagnosed bronchopulmonary carcinoma decrease almost by half during the first year of the SARS-COV-2 pandemic. We noticed a significant increase in the number of patients with professional exposure (p=0.040), atypical resections (p≤0.001), and tumors that couldn't be completely resected (p=0.001), and an ascending trend of lung carcinoma diagnosis in women smokers, even though it wasn't statistically significant (p=0.098). The proportion of newly diagnosed women from rural medium significantly decreased, from 36.45% to 17.65% (p=0.023). The SARS-COV-2 pandemic debut determined a significant under-diagnosis of lung cancer, with an increase in advanced tumors at the time of diagnosis. It is important to further analyze the situation in our country, given the fact that the literature review reported different results, depending on the geographic area.

183P Improving timeliness of diagnosis of lung cancer patients through implementation of a web-based lung cancer referral pathway

183P Improving timeliness of diagnosis of lung cancer patients through implementation of a web-based lung cancer referral pathway

Prognostic Factors and Outcomes in Advanced Stage Lung Cancer Patients with COVID-19 Omicron Variant Infection.

We study the characteristics and outcomes in lung cancer patients with COVID-19 Omicron variant infection. Hospitalized lung cancer patients with advanced-stage disease and laboratory-confirmed COVID-19 Omicron infection were included. Pneumonitis involving at least 25% of lung parenchyma on CT scans, accompanied by symptoms and oxygen saturation below 93%, were criteria for enrollment. Pneumonitis severity was graded using CTCAE v5.0. Treatment included Paxlovid, prednisolone, anticoagulation, and ventilation. Initial data, radiographic findings, and outcomes were compared. Logistic regression was employed to determine risk factors for in-hospital mortality. Fifteen patients (median age: 65 years; 80.0% males) were included. 73.3% improved and were discharged, 20.0% died, and 6.7% remained intubated. Initial symptoms included cough (100.0%), fever (73.3%), and shortness of breath (53.3%). Symptoms resolved in discharged patients. Median fever duration was 3.5 days, and respiratory symptom recovery took 26 days. Three patients died due to respiratory failure from Omicron pneumonia. Lower oxygen saturation, reduced lymphocyte/neutrophil ratio on day 7, and diffuse bilateral lung lesions were poor prognostic factors. This study underscores the importance of prompt intervention and early diagnosis for lung cancer patients infected with the COVID-19 Omicron variant. Lower oxygen saturation, decreased lymphocyte/neutrophil ratio on day 7, and diffuse lung lesions on CT scans were associated with worse outcomes. Clinicians should prioritize timely and comprehensive management to improve survival rates in this population.

Diagnostic significance of CA-62 cancer antigen for early detection and differential diagnosis of non-small cell lung cancer: results of the blind clinical trials

Background. The combination of several diagnostic methods is used to predict treatment outcomes, assess overall survival, and increase the positive predictive value of detecting malignant lung and bronchial tumors.
 Aim. To evaluate the diagnostic value of the CLIA-СА-62 chemiluminescence immunoassay reagent kit for the detection of early (IaIIb) and advanced (IIIac) stages of lung cancer (LC) in a double-blind clinical study and to assess the use of the CA-62 cancer antigen as a supportive decision-making tool in LC diagnosis in patients with suspicious changes on the tomogram or as a tool for pre-screening of LC prior to computed tomography (CT) to increase diagnostic sensitivity in the detection of early (I and II) stages of LC.
 Materials and methods. A blinded clinical study was conducted on 304 clinically verified serum samples, including 141 samples from patients with non-small cell LC (NSCLC), 133 healthy volunteers, and 30 chronic obstructive pulmonary disease patients. Quantification of other well-known tumor markers used in the diagnosis of LC (CEA, CA-125, CA 15-3, CA 19-9, CYFRА 21-1, NSE, and SCC), as well as the CA-62 marker in all serum samples was performed using electrochemiluminescent immunoassay Elecsys CA-125, ELECSYS CA 19-9, ELECSYS CYFRА 21-1 and ELECSYS SCC (COBAS, Roche Diagnostics GmbH, Germany, EU), enzyme-linked immunoassay CA 15-3-ELISA-BEST, CEA-ELISA-BEST, NSE-ELISA-BEST (AO Vector-Best, Russia) and chemiluminescent immunoassay CLIA-СА-62 (JVS Diagnostics, Skolkovo, Moscow, Russia).
 Results. CA-62 glycoprotein showed the highest level of expression at stage I NSCLC (12 745 U/mL) compared to other tumor markers studied and remained very high at the later stages of cancer: stage II (11 261 U/mL) and stage III (10 220 U/mL). A comparative analysis of the ROC curves of the most promising tumor markers CEA, CYFRA 21-1, SCC, and CA-62 for the entire NSCLC cohort versus all healthy volunteers and patients with chronic obstructive pulmonary disease showed a significant difference in the area under the curve between CA-62 (AUC 0.981) and other markers: CEA (AUC 0.84) CYFRA 21-1 (AUC 0.753)SCC (AUC 0.682). When detecting early stages (I and II) of NSCLC, a comparison of the sensitivity of the studied tumor markers showed the following pattern: CA-62 (92%)CEA (37%)CYFRA 21-1 (9%) and SCC (9%)NSE (4.5%)CA-125 (3%)CA 15-3 (1.5%)CA 199 (1%). In contrast to the CEA, CA 15-3, CA-125, NSE, CA 19-9, CYFRA 21-1, and SCC tumor markers, which are expressed proportionally to tumor growth, the epithelial carcinoma marker CA-62 showed the highest diagnostic indicators in the detection of LC early stages (III): sensitivity 92.5%, specificity 96.3%, positive predictive value 91.2%, NPV 97%, with 95% accuracy of LC detection with biopsy.
 Conclusion. The study results showed that in order to increase the specificity of computed tomography in diagnosing LC in patients with suspicious lesion on the CT scan on the tomogram, the use of the carcinoma-specific marker CA-62 can improve the interpretation of the localized focus visualized and increase the accuracy of differential diagnosis at the early stages of LC to 96%, thus contributing to an increase of the overall survival among patients with lung cancer. Of the entire panel of markers, only glycoprotein CA-62 showed a strong correlation with histology (kappa 0.91) in identifying the malignant process with inconclusive results of low-dose CT (LDCT). In the future, introducing the CA-62 marker to the current system for assessing the LC risk as a pre-screening for LDCT can improve the detection of early LC by reducing false-positive results. Once introduced into existing screening programs, it can help significantly reduce the number of patients who need LDCT, decreasing the workload of LDCT and reducing radiation exposure.

Delays in the diagnosis of lung cancer patients in Poland

Introduction. Lung cancer is the most common cause of death from malignant tumors in the world, with more than 2 million patients diagnosed every year. The most common symptoms of lung cancer are cough and shortness of breath. However, they appear late when the cancer is at an advanced stage. The standard measure of the correct diagnostic path in cancer patients is the time from the first symptoms of the disease to the final diagnosis. The aim of the study is to identify reasons for late diagnosis of patients with symptoms of lung cancer in Poland. Material and methods. We performed an analysis of a survey conducted among 149 patients with lung cancer from the Department of Pneumonology, Oncology and Allergology at the Medical University of Lublin. The SPSS software was used to perform the analysis of these data. Males accounted for 56.4% of the patients, and the median age of the patients was 66.8 ± 7.2 years. The mean time from the first symptoms to the first appointment with a doctor was 5.3 weeks and from the first symptoms to diagnosis was 14.7 weeks. Results. The time from the onset of symptoms and treatment initiation was significantly (p = 0.04) longer in patients living at a greater distance from cancer centers (24.1 weeks) than in patients living nearby (18.3 weeks). In patients who were treated with antibiotics before diagnosis, the time from the onset of the symptoms to the start of treatment was significantly longer (p = 0.003) than in patients who did not use antibiotics (26.8 weeks vs. 18.1 weeks). Conclusions. The results of our study showed that Polish patients with suspected lung cancer are diagnosed too late, which has an impact on the stage at which the tumor is diagnosed.

Clinical symptoms and conditions leading to metastatic non–small cell lung cancer diagnosis in patients with and without targeted mutations.

401 Background: This study compares patient characteristics, clinical conditions, the prevalence and timing of lung cancer symptoms, and diagnostic procedures from onset to mNCSLC diagnosis for patients with and without targetable mutations. Methods: This was a retrospective claims analysis of Medicare Advantage and commercially insured adult mNSCLC patients (11/01/2012 - 01/31/2020) with continuous health plan enrollment (24 months pre-index and ≥2 months post-index) around the index date (mNSCLC diagnosis). Patients on targeted therapy post-diagnosis were assigned to the targeted group (TG); non-targeted group (NTG) otherwise. Twenty pre-specified lung cancer related symptoms, baseline comorbidities, and diagnostic procedures were examined in the pre-index period. Results: The study comprised 2,940 patients (TG: 390; NTG: 2,550); TG had lower mean age (65.8yrs vs 69.2yrs; p < 0.001), more females (59.5% vs 50.6%; p = 0.001), and lower tobacco use (55.9% vs 92.5%; p < 0.001). Mean TG Charlson score was 1.37 in the TG vs 1.93 in the NTG; p < 0.001. There were no significant differences in prevalence of any lung cancer related symptoms (TG 81.8% vs NTG 83.5%; p = 0.4). When comparing the 20 individual, pre-specified lung cancer related symptoms (cough, dyspnea, hemoptysis, etc.), there were also no significant differences between the study cohorts. For patients with symptoms, the mean times from the first symptom to mNSCLC diagnosis were similar (TG: 339.3 days; NTG: 363.1 days; p = 0.13)(Table). There were significant differences in the proportion of patients with comorbidities between study cohorts (TG 64.4% vs NTG 73.5%; p < 0.001). Among patients within TG, there was higher prevalence of pleural effusion (22.1% vs 12.6%; p < 0.001) and lower prevalence of COPD (17.7% vs 50.8%; p < 0.001). For diagnostic procedures, patients in TG had fewer imaging procedures than NTG (Chest x-ray 67.7% vs. 74.1%; p = 0.008, CT scan 57.2% vs 63.5%; p = 0.016, PET scan 19.0% vs 27.1%; p < 0.001); and a longer mean time from first symptom to first imaging procedure (TG: 220 days; NTG: 184 days; p = 0.015)(Table). Conclusions: Patients with and without targetable mutations may differ by some patient characteristics, but they may not differ by presentation and type of lung cancer related symptoms leading up to diagnosis.[Table: see text]

P11.29.B Risk factors associated with the presence of brain metastasis at the moment of diagnosis in non-small cell lung cancer patients. Retrospective case series

Abstract Background Lung cancer is the second most frequent neoplasm worldwide and the leading cause of cancer death in both sexes. Furthermore, it is the most common origin of brain metastases. The aim of this study is to identify clinical, histological, and molecular variables associated with a higher risk of presenting brain metastases at the moment of diagnosis in patients with lung cancer. Material and Methods A single-center retrospective case series analysis of patients with a new diagnosis of lung cancer (from January 2015 to December 2018) was performed. A total of 723 total patients with a new diagnosis of non-small cell lung cancer (NSCLC) were identified. Only patients with a brain imaging study at the time of diagnosis were included in the analysis. Non-parametric statistical tests were used to compare patients with or without metastases at the moment of diagnosis. A uni- and multivariate analysis were performed to identify risk factors associated with the presence of brain metastases at NSCLC diagnosis. Statistical significance was considered when p<0.05. Results We included 135 patients with a new diagnosis of lung cancer and with brain imaging study at the time of diagnosis (mean age at diagnosis of 64.69 years [SD= 10.34]; 71.9% men). The most common histology was adenocarcinoma (67.1%) followed by squamous carcinoma (25.2%). Brain metastases were present in 40% of patients at diagnosis. No significant differences in clinical, histological and molecular variables was identified between patients with or without brain metastases. In any case, as expected, the survival analysis showed that brain metastasis at diagnosis was associated with a worse overall survival (Log-Rank test, p<0.01).The univariate analysis showed that presenting neurological symptoms (OR=19.5, p<0.0001 CI [7.895-47.65]), histology of adenocarcinoma (OR= 2.113, p<0.014 CI [1.160-3.849]) and the presence of visceral metastases (OR= 14.444, p<0.0001 CI [6.161-33.86]) were associated to the presence of brain metastases at diagnosis. The presence of metastases limited to the thorax (OR= 0.019, p<0.001 CI [0.003-0.146] was associated to be free of brain metastasis at NSCLC diagnosis. However, only neurological symptoms (OR= 20.290, p<0.0001 CI [4.953-83.118]), presenting visceral metastases (OR= 4.451, p<0.010 CI [1.458-13.777]) and/or metastases limited to the thorax (OR= 0.066, p<0.024 CI [0.006-0.010]) reached statistical significance in the multivariate analysis. Conclusion Neurological symptoms and the presence of visceral metastases are independent predictors or presenting brain metastasis at the moment of diagnosis in lung cancer patients. On the other hand, the presence of lung cancer disease confined in the thoracic cavity is associated with a lower risk to present brain metastasis

Clinical Value of Cytokine Assay in Diagnosis and Severity Assessment of Lung Cancer.

Purpose To investigate the clinical value of interleukin 2 (IL-2), interleukin 4 (IL-4), interleukin 6 (IL-6), interleukin 10 (IL-10), tumor necrosis factor α (TNF-α), and interferon-γ (IFN-γ) in diagnosis and severity assessment of lung cancer. Methods In this observational study, 50 physical examination healthy subjects were included in the control group and 100 lung cancer patients were included in the study group. In the study group, 53 cases with pleural effusion were subgrouped to the pleural effusion group (n = 53), while 47 patients were assigned to the nonpleural effusion group (n = 47). Plasma cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores of all eligible subjects were collected and compared. Results The study group showed significantly higher levels of plasma cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ versus healthy subjects (P < 0.05). Deterioration of lung cancer was associated with increased plasma cytokine levels and APACHE II scores. The combination assay of the above plasma cytokines showed significantly better diagnostic efficacy for lung cancer versus the single assay of the cytokines. Dead patients had higher plasma cytokine levels versus survived patients. The accuracy of plasma IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ levels in the severity assessment of lung cancer was comparable with that of the APACHE II scale. Conclusion The plasma cytokines IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ are effective markers for the diagnosis of lung cancer. The combined assay contributes to the early diagnosis of lung cancer patients, and the persistent elevation of cytokines suggests an increased risk of death in lung cancer patients, so the detection of cytokine levels facilitates the severity assessment of lung cancer.

GMFG (glia maturation factor gamma) inhibits lung cancer growth by activating p53 signaling pathway

ABSTRACT The tumor-promoting or tumor-suppressing functions of Glia maturation factor gamma (GMFG) were described in several cancers. However, how GMFG regulates lung cancer progression is elusive. Bioinformatics analysis was employed to analyze GMFG expression in lung adenocarcinoma (LUAD) and lung squamous cancer (LUSC) as well as its significance in prognosis prediction and diagnosis in lung cancer patients. CCK8 and colony formation assays were adopted to evaluate the impact of GMFG overexpressing and depleting on lung cancer cell proliferation. And in vivo experiments were implemented. Luciferase reporter assays were used to disclose the signaling pathway mediated by GMFG in lung cancer. GMFG expression was lower in LUSC and LUAD tissues compared with normal lung tissues based on TCGA and GTEx databases. Low GMFG expression was associated with lower overall survival and shorter disease specific survival compared high GMFG expression. In vitro loss and gain functions assays demonstrated that ectopically GMFG expression dampened the lung cancer cell proliferation while GMFG knockout escalated the cell proliferation. The promoting effect of GMFG knockout on lung cancer tumorgenesis was also observed in vivo. More interesting, GMFG overexpression reinforced the p53 signaling pathway in lung cancer cells, conversely GMFG deficiency disrupted p53 signaling pathway. In conclusion, we revealed that GMFG is fundamental to p53 signaling pathway to inhibit lung cancer progression, highlighting the importance of GMFG as a p53 inducer for lung cancer patient’s diagnosis and therapy.

Immunohistochemical and Electron Microscopy Evolution in the Diagnosis of Lung Cancer in Iraq.

Lung cancer is considered themost commonly diagnosed cancer that kills over 1.76 million people yearlyaround the world. This study aimed to investigate how electron microscopy (EM) and immunohistochemistry (IHC)worked together. In the current study, a total of50 tissue blocks were used which wereembedded in paraffin wax from 20 healthy controls and30 lung cancer patients (19 males and 11 females) to conduct a histopathological examination, which included hematoxylin and eosin stain, IHC detection regarding theprotein expression in P53, and EM for lung cancer diagnosis. The findings indicated that the mean age of thepatients was 51.84±15.70 years, and there was no correlation between the age of patients and the disease stage. P53 expression was measured using an immunohistochemical technique, while thepositive rate showed a highly significant difference between healthy controls and patients(PP≤0.05). The association of P53 expression with age and gender was not significant, although it showed a significant correlation with stage and grade. Furthermore, a correlation was found between P53 IHC and EM (P≤0.05). In conclusion, the detection of an immunohistochemical method of lung cancer patients has been (gold standard) useful in detecting the subsets of patients in addition to a good method of EM in the diagnosis of lung cancer patients.

Comparative analysis of malnutrition diagnosis methods in lung cancer patients using a Bayesian latent class model.

There are no consensus criteria for malnutrition diagnosis in clinical settings, the Global Leadership Initiative on Malnutrition (GLIM) criteria were developed to facilitate global comparisons of malnutrition prevalence, interventions and outcomes. Validation to assess usefulness in clinical practice is essential, however, the imperfect nature of reference standards used in concurrent validation may result in biased estimates of diagnostic accuracy. The Bayesian latent class model (BLCM) can assess the diagnostic performance when a "gold standard" is absent. This study's objective was to assess the diagnostic performance of the GLIM criteria in comparison with the Nutritional Risk Screening 2002 (NRS-2002) and the Patient Generated Subjective Global Assessment (PG-SGA) in lung cancer patients using a BLCM. We hypothesized that the GLIM criteria are more sensitive and specific for malnutrition diagnosis in lung cancer patients. 1,384 patient records retrospectively obtained from the "Investigation on Nutrition Status and its clinical outcome of common Cancers" (INSCOC) study were used to determine the prevalence of malnutrition, sensitivity (Se) and specificity (Sp) by applying a BLCM. The prevalence of malnutrition was 0.56. The sensitivity and specificity of the GLIM criteria were Se: 0.85 and Sp: 0.88; Se: 0.74 and Sp: 0.85 for NRS-2002 and Se: 0.96 and Sp: 0.89 for PG-SGA. Although the GLIM criteria were acceptable for malnutrition diagnosis, PG-SGA is superior for determining cancer-associated malnutrition. Because of its fair sensitivity, NRS-2002 was best equipped to screen out patients not at nutritional risk.

Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics

Background and objectiveTo study the diagnostic effect of 64-slice spiral CT and MRI high-resolution images based on deep convolutional neural networks(CNN) in lung cancer. MethodsIn this paper, we Select 74 patients with highly suspected lung cancer who were treated in our hospital from January 2017 to January 2021 as the research objects. The enhanced 64-slice spiral CT and MRI were used to detect and diagnose respectively, and the images and accuracy of CT diagnosis and MRI diagnosis were retrospectively analyzed. ResultsThe accuracy of CT diagnosis is 94.6% (70/74), and the accuracy of MRI diagnosis is 89.2% (66/74). CT examination has the advantages of non-invasive, convenient operation and fast examination. MRI is showing there are advantages in the relationship between the chest wall and the mediastinum, and the relationship between the lesion and the large blood vessels. ConclusionEnhanced CT and MRI examinations based on convolutional neural networks(CNN) to improve image clarity have high application value in the diagnosis of lung cancer patients, but the focus of performance is different.

Chest Computerized Tomography Images under Iterative Model Reconstruction Algorithm in Patients with Lung Cancer

To explore the effect of the full iterative model reconstruction algorithm (IMR) on chest CT image processing and its adoption value in the clinical diagnosis of lung cancer patients, multislice spiral CT (MSCT) scans were performed on 96 patients with pulmonary nodules. Reconstruction was performed by hybrid iterative reconstruction (iDose4) and IMR2 algorithms. Then, the image contrast, spatial resolution, density resolution, image uniformity, and noise of the CT reconstructed image were recorded. The benign and malignant pulmonary nodules of patients were collected and classified into malignant pulmonary nodule group and benign pulmonary nodule group, and the differences in chest CT imaging characteristics between the two groups were compared. The subject’s receiver operating characteristic (ROC) curve was used to analyze the diagnostic sensitivity, specificity, and area under the curve (AUC) of CT for benign and malignant pulmonary nodules. It was found that the spatial resolution, density resolution, image uniformity, and contrast of the CT image reconstructed by the IMR2 algorithm were remarkably greater than those of the iDose4 algorithm, and the noise was considerably less than that of the iDose4 algorithm ( P &lt; 0.05 ). Among 96 patients with pulmonary nodules, 65 were malignant nodules, including 15 squamous cell carcinoma, 31 adenocarcinoma, and 19 small cell carcinomas. There were 31 cases of benign nodules, including 14 cases of hamartoma, 10 cases of tuberculous granuloma, 2 cases of sclerosing hemangioma, and 5 cases of diffuse lymphocyte proliferation. The pulmonary nodule malignant group and the pulmonary nodule benign group had statistical differences in pulmonary nodule size, nodule morphology, burr sign, lobular sign, vascular sign, bronchial sign, and pleural depression sign ( P &lt; 0.05 ). The sensitivity, specificity, and area under the curve (AUC) of IMR2 algorithm processing chest CT images for liver cancer diagnosis were 85.7%, 82.3%, and 0.815, respectively, which were significantly higher than the original CT images ( P &lt; 0.05 ). In short, chest MSCT based on the IMR2 algorithm can greatly improve the diagnosis efficiency of lung cancer and had practical significance for the timely detection of early lung cancer.

Upregulation of SPP1 Is a Marker for Poor Lung Cancer Prognosis and Contributes to Cancer Progression and Cisplatin Resistance.

The chemoresistance of lung cancer is a significant contributor to its high mortality and morbidity rate. There is an urgent need to identify differentially expressed genes in lung cancer patients with a poor prognosis to develop effective means to overcome drug resistance in subsequent treatment. In this study, we identified the secreted phosphoprotein 1 (SPP1) as a potential gene associated with a poor diagnosis of lung cancer patients using the Cancer Genome Atlas analysis, which suggested that the expression of SPP1 in tumor tissues was significantly higher than normal tissues. The high expression of SPP1 was also correlated with tumor grade and poor clinical prognosis. To understand the roles of SPP1 and the DNA methyltransferase 1 (DNMT1), which regulated SPP1 expression, in affecting cell viability, migration and invasion, SPP1 and DNMT1 were overexpressed in the human lung cancer A549 and NCI-446 cells, followed by analyzing cell viability, migration and invasion. We showed that SPP1 promoted the proliferation, migration and invasion of lung cancer cells, and increased the resistance of lung cancer to the chemotherapeutic drug cisplatin. Knocking down SPP1 in cells restored sensitivity to cisplatin. Further, A549 cells without SPP1 overexpression demonstrated lower tumor growth rate than SPP1 overexpression cells using the xenograft tumor mouse model. High expression of SPP1 in lung cancer tumor tissue was caused by the reduced methylation level of its promoter region mediated by DNMT1. Our data suggested that SPP1 can be used as a marker for highly malignant lung cancer and targeting SPP1 may be a potential lung cancer treatment strategy.

Expression and analysis of PD-L1 in peripheral blood circulating tumor cells of lung cancer.

Aim: PD-L1is an important immune intervention target for lung cancer treatment;however, its clinical significance andbiological function in circulating tumor cells (CTCs) of lung cancer need to be explored in depth. Materials & methods: In this study, the CanPatrolmethod was used to detect three types of CTCs and PD-L1 in 271 lung cancer patients from December2015 to October2019. Results: Smoking index, pathological diagnosisand clinical stage are independent influencing factors of PD-L1 expression. The methods that affect the count of CTCs are first-line chemotherapy and targeted therapy; however, there is no difference in the expression of PD-L1 with different treatments. Conclusions: The detection of CTCs and PD-L1 in peripheral blood is helpful for the diagnosis of lung cancer patients.

Inhibition of IL1β by Canakinumab May Be Effective against Diverse Molecular Subtypes of Lung Cancer: An Exploratory Analysis of the CANTOS Trial

In the Canakinumab Anti-inflammatory Thrombosis Outcomes Study (CANTOS), inhibition of the IL1β inflammatory pathway by canakinumab has been shown to significantly reduce lung cancer incidence and mortality. Here we performed molecular characterization of CANTOS patients who developed lung cancer during the study, including circulating tumor DNA (ctDNA) and soluble inflammatory biomarker analysis. Catalogue of Somatic Mutations in Cancer (COSMIC) database ctDNA mutations were detected in 65% (46/71) of the CANTOS patients with lung cancer, with 51% (36/71) having detectable ctDNA at the time point closest to lung cancer diagnosis and 43% (29/67) having detectable ctDNA at trial randomization. Mutations commonly found in lung cancer were observed with no evidence of enrichment in any mutation following canakinumab treatment. Median time to lung cancer diagnosis in patients with (n = 29) versus without (n = 38) detectable COSMIC ctDNA mutations at baseline was 407 days versus 837 days (P = 0.011). For serum inflammatory biomarker analysis, circulating levels of C-reactive protein (CRP), IL6, IL18, IL1 receptor antagonist, TNFα, leptin, adiponectin, fibrinogen, and plasminogen activator inhibitor-1 were determined. Patients with the highest level of baseline CRP or IL6, both downstream of IL1β signaling, trended toward a shorter time to lung cancer diagnosis. Other inflammation markers outside of the IL1β pathway at baseline did not trend with time to lung cancer diagnosis. These results provide further evidence for the importance of IL1β-mediated protumor inflammation in lung cancer and suggest canakinumab's effect may be mediated in part by delaying disease progression of diverse molecular subtypes of lung cancer. SIGNIFICANCE: These findings suggest that targeting the IL1β inflammatory pathway might be critical in reducing tumor-promoting inflammation and lung cancer incidence.

Intraoperative diagnosis of lymph node metastasis during segmentectomy for non-small cell lung cancer by rapid immunohistochemistry using noncontact alternating current electric field mixing.

BackgroundAlthough lobectomy is considered the standard surgery for any non‐small cell lung cancer (NSCLC), recent evidence indicates that for early NSCLCs segmentectomy may be equally effective. For segmentectomy to be oncologically safe, however, adequate intraoperative lymph node staging is essential. The aim of this study was to compare the results of a new rapid‐IHC system to the HE analysis for intraoperative nodal diagnosis in lung cancer patients considered for segmentectomy.MethodsThis retrospective study analyzed the pathological reports from NSCLC resections over a six‐year period between 2014 and 2020. Using a new device for rapid‐IHC, we applied a high‐voltage, low‐frequency alternating current (AC) field, which mixes the antipancytokeratin antibody as the voltage is switched on/off. Rapid‐IHC can provide a nodal diagnosis within 20 minutes.ResultsFrozen sections from 106 resected lymph nodes from 70 patients were intraoperatively evaluated for metastasis. Of those, five nodes were deemed positive based on both HE staining and rapid‐IHC. In addition, rapid‐IHC alone detected isolated tumor cells in one hilar lymph node. Three cStage IA patients with nodal metastasis detected with HE staining and rapid‐IHC received complete lobectomies. Five‐year relapse‐free survival and overall survival among patients receiving segmentectomy with rapid‐IHC were 88.77% and 88.79%, respectively.ConclusionsRapid‐IHC driven by AC mixing is simple, highly accurate, and preserves nodal tissue for subsequent tests. This system can be used effectively for intraoperative nodal diagnosis.Rapid immunohistochemistry based on alternating‐current field mixing (completed within 20 minutes) is simple and highly accurate. This system will assist clinicians when making intraoperative diagnoses of lymph node metastasis and deciding upon the appropriate surgical procedure in segmentectomy for lung cancer.Key pointsSignificant findings of the studyRapid immunohistochemistry driven by alternating‐current field mixing (completed within 20 minutes intraoperatively) is simple, highly accurate, and preserves lymph node tissue for subsequent pathological examination, including molecular assessments.What this study addsSegmentectomy for lung cancer is oncologically safe, but only when there is adequate intraoperative node staging. Rapid immunohistochemistry will assist clinicians when making intraoperative nodal diagnoses.

Role of LDH, 17-ß-hydroxysteroid dehydrogenase and Myloperoxidase Enzymes in early diagnosis for Lung Cancer patients

Role of LDH, 17-ß-hydroxysteroid dehydrogenase and Myloperoxidase Enzymes in early diagnosis for Lung Cancer patients