Characteristics Of Lung Cancer Patients Research Articles

Characteristics of Lung Cancer Patients With Asymptomatic or Undiagnosed SARS-CoV-2 Infections

IntroductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be spread by individuals unaware they are infected. Such dissemination has heightened ramifications in cancer patients, who may need to visit healthcare facilities frequently, be exposed to immune-compromising therapies, and face greater morbidity from coronavirus disease 2019 (COVID-19). We determined characteristics of (1) asymptomatic, clinically diagnosed, and (2) serologically documented but clinically undiagnosed SARS-CoV-2 infection among individuals with lung cancer. Patients and methodsIn a multicenter registry, individuals with lung cancer (regardless of prior SARS-CoV-2 vaccination or documented infection) underwent collection of clinical data and serial blood samples, which were tested for antinucleocapsid protein antibody (anti-N Ab) or IgG (N) levels. We used multivariable logistic regression models to investigate clinical characteristics associated with the presence or absence of symptoms and the presence or absence of a clinical diagnosis among patients with their first SARS-CoV-2 infection. ResultsAmong patients with serologic evidence or clinically documented SARS-CoV-2 infection, 80/142 (56%) had no reported symptoms at their first infection, and 61/149 (40%) were never diagnosed. Asymptomatic infection was more common among older individuals and earlier-stage lung cancer. In multivariable analysis, non-white individuals with SARS-CoV-2 serologic positivity were 70% less likely ever to be clinically diagnosed (P = .002). ConclusionsIn a multicenter lung cancer population, a substantial proportion of SARS-CoV-2 infections had no associated symptoms or were never clinically diagnosed. Because such cases appear to occur more frequently in populations that may face greater COVID-19-associated morbidity, measures to limit disease spread and severity remain critical.

Development and validation of a LASSO prediction model for cisplatin induced nephrotoxicity: a case-control study in China

BackgroundEarly identification of high-risk individuals with cisplatin-induced nephrotoxicity (CIN) is crucial for avoiding CIN and improving prognosis. In this study, we developed and validated a CIN prediction model based on general clinical data, laboratory indications, and genetic features of lung cancer patients before chemotherapy.MethodsWe retrospectively included 696 lung cancer patients using platinum chemotherapy regimens from June 2019 to June 2021 as the traing set to construct a predictive model using Absolute shrinkage and selection operator (LASSO) regression, cross validation, and Akaike’s information criterion (AIC) to select important variables. We prospectively selected 283 independent lung cancer patients from July 2021 to December 2022 as the test set to evaluate the model’s performance.ResultsThe prediction model showed good discrimination and calibration, with AUCs of 0.9217 and 0.8288, sensitivity of 79.89% and 45.07%, specificity of 94.48% and 94.81%, in the training and test sets respectively. Clinical decision curve analysis suggested that the model has value for clinical use when the risk threshold ranges between 0.1 and 0.9. Precision-Recall (PR) curve shown in recall interval from 0.5 to 0.75: precision gradually declines with increasing Recall, up to 0.9.ConclusionsPredictive models based on laboratory and demographic variables can serve as a beneficial complementary tool for identifying high-risk populations with CIN.

Characteristics of Lung Cancer Patients with Brain Metastases based on Baseline Head Computerized Tomography (CT)-scan in Arifin Achmad Hospital October 2022 - June 2023

Background: The majority of lung cancer cases are often discovered at a late stage because it frequently develops without symptoms in the early stages. Many lung cancer deaths are caused by metastases to other organs. The purpose of this study was to examine the features of lung cancer patients with brain metastases using baseline CT scan data. Method: Between October 2022 and June 2023, a cross-sectional study was conducted at the Arifin Achmad Hospital in Pekanbaru on all newly diagnosed lung cancer patients with brain metastases who also met the inclusion and exclusion criteria. Results: Eight subjects of lung cancer with brain metastasis were found from 49 patients. All subjects were male with age mostly in between 40 and 60 years. Three subjects (37.5%) were Squamous Cell Carcinoma (SCC), four subject (50%) were adenocarcinoma and 1 (12.5%) were SCLC. Conclusion: This study discovered that 16.3% of patients who met the inclusion criteria had lung cancer with brain metastases. Further research should be done on a cohort study and a preventive strategy for lung cancer with brain metastases.

Genomic features of lung cancer patients in Indonesia’s national cancer center

IntroductionAdvances in molecular biology bring advantages to lung cancer management. Moreover, high-throughput molecular tests are currently useful for revealing genetic variations among lung cancer patients. We investigated the genomics profile of the lung cancer patients at the National Cancer Centre of Indonesia.MethodsA retrospective study enrolled 627 tissue biopsy samples using real time polymerase chain reaction (RT-PCR) and 80 circulating tumour DNA (ctDNA) liquid biopsy samples using next-generation sequencing (NGS) from lung cancer patients admitted to the Dharmais Cancer Hospital from January 2018 to December 2022. Data were obtained from medical records. Data statistically analysed with p < 0.05 is considered significant.ResultThe EGFR test results revealed by RT-PCR were wild type (51.5%), single variant (38.8%), double variant (8.3%), and triple variant (1.4%), with 18.66% L85R, 18.22% Ex19del, and 11.08% L861Q variant. Liquid biopsy ctDNA using NGS showed only 2.5% EGFR wild type, 62.5% single variant and 35% co-variant, with EGFR/TP53 and EGFR/PIK3CA as the highest.ConclusionEGFR variants are the most found in our centre. Liquid biopsy with ctDNA using NGS examination could detect broad variants and co-variants that will influence the treatment planning.

Pathological characteristics of lung tumors in Sri Lanka 2017-2021.

The prevalence of lung cancer is steadily increasing globally, and it is projected to become the second most prevalent cancer in men by 2030. Lung cancer is the leading cause of cancer-related deaths worldwide, accounting for approximately 3.61% of total fatalities. Despite its significant impact, many Asian countries, including Sri Lanka, lack precise data on the epidemiological patterns of lung tumors. This study pioneers a comprehensive exploration in Sri Lanka, delving into the demographic and clinicopathological characteristics of lung cancer patients. The study included 733 consecutive patients with lung tumors from 2017 to 2021, with a median age of 59 years. The most common site of tumors was the right lower lobe and left upper lobes. Adenocarcinoma was the most prevalent histopathological type of primary malignant lung tumors, while colorectal adenocarcinomas were the most common cause of metastatic deposits in the lungs. The most common benign tumor was hamartoma. Significantly, our findings unveiled associations between patient demographics and tumor types, underscoring the importance of factoring in age and gender in diagnostic assessments. Notably, the absence of a dedicated lung cancer screening program in Sri Lanka underscores the critical reliance on clinical suspicion and accurate diagnostic methods.

Association Between Patient Characteristics and Histopathological Features of Lung Cancer At RSUP Dr. Mohammad Hoesin Palembang

Introduction. Lung cancer is the uncontrolled growth of malignant cells by the body in lung tissue and is caused by genetic mutations and changes in protein synthesis in normal cells. Histopathological features of lung cancer include squamous cell carcinoma, adenocarcinoma, small cell carcinoma, and other types. Early detection, as well as prevention, needs to be done in high-risk communities with the aim of reducing the number of events. This study aims to determine the relationship between sociodemographic factors and histopathological features of lung cancer. Methods. This study is an analytic observational study with a cross-sectional design. The research sample is in the form of secondary data from the Department of Anatomical Pathology and Medical Record Installation for 2019-2021. The research was conducted at Dr. Mohammad Hoesin Palembang. The sampling technique was carried out by total sampling. Results. Most of the respondents were in the age group &gt;45 years (84.1%), male (78.3%), had no history of smoking (60.9%), the predominant main complaint was shortness of breath (63, 8%), the most common histopathological picture is adenocarcinoma. There was no significant relationship between age (p=0.998), gender (p=0.736), smoking history (p=0.572) and histopathological features of lung cancer patients. Conclusion. There was no significant relationship between age, sex and smoking status on the histopathological features of lung cancer.

A machine learning decision support system for determining the primary factors impacting cancer survival and their temporal effect

It is critical for healthcare providers to accurately determine lung cancer patients' prognostics and develop customized treatment plans. However, lung cancer has proven to be a complex disease, and every patient responds differently to treatment options, making survivability predictions highly challenging. This study proposes a holistic machine learning model that can assist healthcare providers in predicting the temporal effects of lung cancer-related factors on one-, five-, and ten-year survival rates. Variable selection algorithms such as genetic algorithm (GA) and Baruta are employed along with data balancing methods to achieve parsimonious models for survival prediction. Classification results are obtained through logistic regression and extreme gradient boosting algorithms followed by an information fusion technique to combine the classification results and identify the temporal effects of lung cancer variables over time. Results demonstrate that the prediction power of the classification models improved as the survival period increased. The models trained using the GA and intersection variable sets generated better average prediction scores. The study contributes to the cancer literature by analyzing the varying temporal impacts of lung cancer variables over varying time periods. Medical professionals can use these findings to understand better the longitudinal characteristics of lung cancer patients’ survival indicators.

Genomic alterations as independent prognostic factors to predict the type of lung cancer recurrence

Introduction33–70% of lung cancer (LC) patients develop recurrence after radical treatment. Previous studies have shown the importance of clinical-pathological characteristics for the risk of recurrence. The role of molecular mechanisms remains unclear. The aim was analyzing genomic features in LC patients with local (LR) versus distant recurrence (DR) to predict the risk and type of recurrence. Materials and methodsPatients previously curatively treated with LC recurrences from 2015 to 2017 were retrospectively enrolled. Histological specimens collected at the time of LC diagnosis were sent for whole exome sequencing (WES). Genomic data was analyzed for single nucleotide polymorphisms (SNPs) and insertion-deletion mutations (INDELs). Results191 patients were included. 33% of patients had LR and 67% DR, with median recurrence-free survival (RFS) 15.4 versus 11.2 months (p = 0.20) and overall survival (OS) after recurrence 12.9 versus 8.5 months (p = 0.007), respectively. Of various laboratory parameters studied, lymphocytes were significantly decreased at recurrence (p < 0.0001) in the DR group.In genetic analysis, significantly enriched INDEL mutations were found in 38 and 98 genes and SNP mutations in 63 and 179 genes in DR and LR groups, respectively. DMXL2 and ABCC9 gene mutations caused by INDELs appeared exclusively in the DR group. Enrichment analysis detected genes, like KNTC1, CLASP1, CLASP2 and CENPE, responsible of microtubule disturbance in the DR group. Furthermore, genes related to cytosolic Ca2+ such as STIM1, ITPR3 and RYR3, were significantly enriched in DR group whereas in LR group enrichment of pathways related to endoplasmic/sarcoplasmic reticulum Ca2+ was observed. ConclusionOur findings indicate distinct genomic signatures in the LR and DR cohorts, with microtubule disturbance and calcium regulation playing a crucial role in invasiveness in DR of LC. Understanding molecular mechanisms of LC recurrence may lead to the discovery of novel drug targets that could potentially stop spread of cancer cells.

NOX4 Upregulation in Lung Cancer: A Potential Therapeutic Target Associated with Immune Infiltration

Lung cancer is a common and highly lethal tumor worldwide. Research indicates that NOX4 plays a crucial role in apoptosis resistance and sustained proliferation of cancer cells in various types of tumors. In this study, NOX4 expression in lung cancer tissues was analyzed using the Wilcoxon rank sum test, while the Kruskal-Wallis Test was employed to explore the relationship between NOX4 expression and clinical characteristics in lung cancer patients. Prognostic evaluation was conducted using Kaplan-Meier plotter analysis, Cox regression, and receiver operating characteristic (ROC) curve construction. Gene set enrichment analysis (GSEA) was performed to investigate the correlation between NOX4 and immune infiltration. Results showed significantly higher NOX4 expression in lung cancer patients compared to normal tissues. High NOX4 expression was associated with shorter overall survival (OS) in lung cancer patients, as confirmed by Cox analysis. Furthermore, other clinicopathological factors predicted poor prognosis in lung adenocarcinoma (LUAD), and NOX4 demonstrated diagnostic value according to ROC analysis. Additionally, NOX4 overexpression correlated with macrophages and Th1 cells based on SsGSEA analysis. In summary, NOX4 serves as an independent prognostic biomarker and is associated with immune infiltration in lung cancer.

MicroRNA-651-5p affects the proliferation, migration, and invasion of lung cancer cells by regulating Calmodulin 2 expression.

Lung cancer is prevalent worldwide and a leading contributor to tumor death. This research intends to explore the molecular mechanism of the microRNA-651-5p (miR-651-5p)/Calmodulin 2 (CALM2) axis in the proliferation, migration, and invasion of lung cancer cells. Lung cancer tissues and para-cancerous tissues were collected. The expression levels of miR-651-5p and CALM2 in lung cancer tissues and cells were tested, and the connection between miR-651-5p expression and clinicopathological characteristics of lung cancer patients was further analyzed. The binding sites between miR-651-5p and CALM2 were analyzed and validated. Lung cancer cell proliferation, migration, invasion, and apoptosis were examined. miR-651-5p was lowly expressed in lung cancer tissues and cells. miR-651-5p expression had no correlation with patients' age and gender but had a correlation with patients' tumor size, TNM stage, and lymph node metastasis. Overexpression of miR-651-5p repressed proliferative, migratory, and invasive behaviors of lung cancer cells. miR-651-5p targeted and negatively regulated CALM2 expression, and CALM2 reversed the inhibiting effects of miR-651-5p on lung cancer cell malignant behaviors, including proliferation, migration, and invasion. This study expounds that miR-651-5p affects the proliferation, migration, and invasion of lung cancer cells by regulating CALM2 expression.

Clinical predictors and outcomes of non-expandable lung following percutaneous catheter drainage in lung cancer patients with malignant pleural effusion.

Non-expandable lung (NEL) often occurs during pleural fluid drainage in patients with malignant pleural effusion (MPE). However, data regarding the predictors and prognostic impact of NEL on primary lung cancer patients with MPE receiving pleural fluid drainage, compared to malignant pleural mesothelioma (MPM), are limited. This study was aimed to investigate the clinical characteristics of lung cancer patients with MPE developing NEL following ultrasonography (USG)-guided percutaneous catheter drainage (PCD) and compare the clinical outcomes between those with and without NEL. Clinical, laboratory, pleural fluid, and radiologic data and survival outcomes of lung cancer patients with MPE undergoing USG-guided PCD were retrospectively reviewed and compared between those with and without NEL. Among 121 primary lung cancer patients with MPE undergoing PCD, NEL occurred in 25 (21%). Higher pleural fluid lactate dehydrogenase (LDH) levels and presence of endobronchial lesions were associated with development of NEL. The median time to catheter removal was significantly extended in those with NEL compared to those without (P = .014). NEL was significantly associated with poor survival outcome in lung cancer patients with MPE undergoing PCD, along with poor Eastern Cooperative Oncology Group (ECOG) performance status (PS), the presence of distant metastasis, higher serum C-reactive protein (CRP) levels, and not receiving chemotherapy. NEL developed in one-fifth of lung cancer patients undergoing PCD for MPE and was associated with high pleural fluid LDH levels and the presence of endobronchial lesions. NEL may negatively affect overall survival in lung cancer patients with MPE receiving PCD.

Characteristics of Lung Cancer Patients at Dr. Soedarso Hospital Pontianak from 2017 to 2019

Background: Lung cancer is the second most commonly diagnosed malignancy and the leading cause of death in 2020. Preliminary studies from 2014 to 2019 at Dr. Soedarso Hospital Pontianak showed there was an increase in lung cancer cases. This study aimed to determine the clinical profile of patients with lung cancer in Dr. Soedarso HospitalMethods: This epidemiological study used medical records from patients diagnosed with lung cancer at Dr. Soedarso Hospital Pontianak from 2017 to 2019. It was a cross-sectional study, and 81 samples met the criteria. The inclusion criteria are the completeness of data and the results of cytopathology laboratory examinations. The data were processed using Microsoft Excel.Results: In this study, based on the characteristics of patients diagnosed with lung cancer in Dr. Soedarso Hospital, 82.7% are male with an average diagnosed age of 54.8 years, and 72.8% of patients do not have a smoking history. The common symptoms of patients are shortness of breath (77.8%), chest pain (55.6%), and weight loss (30.9%). The most common type is Non-Small Cell Lung Carcinoma (NSCLC) specifically Adenocarcinoma (76.5%).Conclusion: This study shows that lung cancer incidence in males was higher than in females, and most patients diagnosed did not have a smoking history. The most common symptom of patients is shortness of breath with the most common type of cytopathology results being adenocarcinoma.

Chronic obstructive pulmonary disease alters the genetic landscape and tumor immune microenvironment in lung cancer patients.

Chronic obstructive pulmonary disease (COPD) and lung cancer are leading causes of morbidity and mortality worldwide. Studies have reported molecular alterations in patients with lung cancer and in patients with COPD. However, few investigation has been conducted on the molecular characteristics of lung cancer patients with COPD. We performed a retrospective cohort study that included 435 patients with pathologically confirmed lung cancer at the Ruijin Hospital. For patients with documented spirometry, Global Initiative for Chronic Obstructive Lung Disease criteria were used to define COPD. For patients without documented spirometry, chest computed tomography and other clinical information were used to define COPD. Tumor tissue DNA was extracted from formalin-fixed paraffin-embedded samples. DNA mutation analysis, multiplex immunohistochemistry (mIHC), calculation of tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and predication of neoantigens were performed. Although SNV mutations in lung cancer patients with COPD (G1 group) were generally higher than those in lung cancer patients without COPD (G2 group), the difference in the number of mutations was insignificant between the two groups. Of the 35 mutated genes, the number of them was higher in G1 than in G2, except that of EGFR. PI3K-Akt signaling pathway was enriched from significantly different genes. While TMB and MATH levels were not significantly different, the tumor neoantigen burdenwas markedly higher in G1 than that in G2. The level of CD68+ macrophages was significant higher in the stroma and total areas in the G1 group than in G2 group. The level of CD8+ lymphocytes was markedly higher in the stroma and showed a clear tendency forhigher expression in the G1 group than inthe G2 group. No significant differences were observed for the level of programmed death-ligand 1+ (PD-L1+), programmed death 1+ (PD-1+), and CD68PD-L1 in the stroma, tumor and total areas. Our study revealed different genetic aberrations and pathways, higher neoantigen burden, and higher level of CD68+ macrophages and CD8+ T lymphocytes in lung cancer patients with COPD. Our investigation implies that the existence of COPD should be considered and immunotherapy is a potential choice when treating lung cancer patients with COPD.

Real-world data on survival outcomes and characteristics of lung cancer patients in northern serbia.

e22528 Background: Serbia is the one of the countries with the highest incidence and mortality of lung cancer in Europe and survival rates are very low. Despite that fact, there is no recent data published on the incidence, mortality, survival time or the most significant patient characteristics for the Northern Serbian Province of Vojvodina. Methods: For the purpose of this retrospective study data for the period 2010 to 2022 were collected from Institute for Pulmonary Diseases of Vojvodina Hospital Information System and the Lung Cancer Registry. Also, we collected data from seven Public Health Institutes, one for each district to analyze incidence and mortality rates. The primary objective of the study was to determine the impact of demographic and clinical pathological characteristics of patients on overall survival. The secondary objective was to analyze the incidence and mortality of lung cancer in the region of Vojvodina. Incidence and mortality rates were directly age-standardized to the World and Europe Standard Population. Results: A total of 15072 patients were eligible for the analysis, 10413 (69.1%) males and 4659 (30.9%) females. The most of the patients were current smokers (62.9% males vs 63.3% females), stage IV (47.7% males vs 46.9% females), ECOG performance status 1 (78.5% males vs 79.0% females). One-year survival rate for the patients with stage IV squamous carcinoma was 20.5% males vs 27.2% females, adenocarcinoma 18.0% males vs 22.9% females and small-cell carcinoma 10.6% males vs 17.8% females. Three-year survival rate for all stages of squamous carcinoma was 12.7%, adenocarcinoma 11.8% and small-cell carcinoma 2.9%. Five-year survival rate for all stages of squamous carcinoma was 7.4%, adenocarcinoma 6.8% and small-cell carcinoma 1.9%. There was statistically significant difference in survival time by gender in subtypes of adenocarcinoma (p = 0.000), squamous cell carcinoma (p = 0.000) and small-cell carcinoma (p = 0.001). Analysis showed significant difference in survival by age (p = 0.000), cancer type (p = 0.000), stage of the disease (p = 0.000), ECOG performance status (p = 0.000) and smoking status (p = 0.001). Incidence (ASR-W) was 65.4/100000 for males and 21.7/100000 for females. Mortality (ASR-W) was 67.8/100000 for males and 20.9/100000 for females. Conclusions: Northern Serbian Province of Vojvodina is one of the regions with the highest incidence and mortality of lung cancer and overall survival is low. Determining the impact of the most important demographic and tumor characteristics on lung cancer patients’ survival, as well as incidence and mortality rates define the parameters necessary for adequate planning of activities and strategies for improving the prevention, diagnosis and treatment of patients in Vojvodina.

Overview on Therapeutic Options in Uncommon EGFR Mutant Non-Small Cell Lung Cancer (NSCLC): New Lights for an Unmet Medical Need.

The majority of epidermal growth factor receptor (EGFR) mutations (85-90%) are exon 19 deletions and L858R point mutations of exon 21, characterized by high sensitivity to EGFR-tyrosine kinase inhibitors (TKIs). Less is known about uncommon mutations (10-15% of EGFR mutations). The predominant mutation types in this category include exon 18 point mutations, exon 21 L861X, exon 20 insertions, and exon 20 S768I. This group shows a heterogeneous prevalence, partly due to different testing methods and to the presence of compound mutations, which in some cases can lead to shorter overall survival and different sensitivity to different TKIs compared to simple mutations. Additionally, EGFR-TKI sensitivity may also vary depending on the specific mutation and the tertiary structure of the protein. The best strategy remains uncertain, and the data of EGFR-TKIs efficacy are based on few prospective and some retrospective series. Newer investigational agents are still under study, and there are no other approved specific treatments targeting uncommon EGFR mutations. Defining the best treatment option for this patient population remains an unmet medical need. The objective of this review is to evaluate existing data on the outcomes, epidemiology, and clinical characteristics of lung cancer patients with rare EGFR mutations, with a focus on intracranial activity and response to immunotherapy.

Risk factors of SARS-CoV-2 infection and complications from COVID-19 in lungcancer patients.

Identifying lung cancer patients at an increased risk of getting SARS-CoV-2-related complications will facilitate tailored therapy to maximize the benefit of anti-cancer therapy, while decreasing the likelihood of COVID-19 complications. This analysis aimed to identify the characteristics of lung cancer patients that predict for increased risk of death or serious SARS-CoV-2 infection. This was a retrospective cohort study of patients with lung cancer diagnosed October 1, 2015, and December 1, 2020, and a diagnosis of COVID-19 between February 2, 2020, and December 1, 2020, within the Veterans Health Administration. Serious SARS-CoV-2 infection was defined as hospitalization, ICU admission, or mechanical ventilation or intubation within 2weeks of COVID-19 diagnosis. For categorical variables, differences were assessed using Χ2 tests, while Kruskal-Wallis rank-sum test was used for continuous variables. Multivariable logistic regression models were fit relative to onset of serious SARS-CoV-2 infection and death from SARS-CoV-2 infection. COVID-19 infection was diagnosed in 352 lung cancer patients. Of these, 61 patients (17.3%) died within four weeks of diagnosis with COVID-19, and 42 others (11.9%) experienced a severe infection. Patients who had fatal or severe infection were older and had lower hemoglobin levels than those with mild or moderate infection. Factors associated with death from SARS-CoV-2 infection included increasing age, immune checkpoint inhibitor therapy and low hemoglobin level. The mortality of lung cancer patients from COVID-19 disease in the present cohort was less than previously reported in the literature. The identification of risk factors associated with severe or fatal outcomes informs management of patients with lung cancer who develop COVID-19 disease.

Incidentally Diagnosed With Pulmonary Embolism in Lung Cancer Patients: Comparison of Clinical Characteristics and Mortality With Symptomatic Pulmonary Embolism.

The purpose of this work was to compare the clinical characteristics, rate of recurrent venous thromboembolism (VTE), bleeding complications and mortality of incidental and symptomatic pulmonary embolism (PE) detected on computed tomography in patients with lung cancer. Clinical data of lung cancer patients with PE were obtained from the Department of Respiratory and Critical Care Medicine of Ningbo First affiliated hospital of Ningbo University during January 2016 and June 2021 and were reviewed retrospectively. We compared clinical and radiological characteristics in lung cancer patients with incidental PE (IPE) and symptomatic PE (SPE) and identified variables associated with the 1-year survival on multivariate Cox analysis. All patients were followed up for 1 year to compare the risks of recurrent VTE, bleeding complications, and mortality. Survival analysis was performed by use of Kaplan-Meier. A total of 223 lung cancer patients with PE were enrolled over the period. Of these, 117 (52%) patients had symptomatic whereas 106 (48%) patients had incidental PE. Those with IPE were more likely to have adenocarcinoma, VTE history, chronic respiratory disease and chemotherapy within 30 days prior to PE, while SPE was more frequently observed in patients with squamous cancer, concomitant VTE, performance status 0-1, chronic heart disease and major surgery within 30 days prior to PE. During 1 year of follow-up, recurrent VTE was diagnosed in 10 patients (9.3%) in lung cancer patients with IPE and 13 patients (11.2%) with SPE. The 12-month cumulative recurrent VTE incidence was 9.6% for patients with incidental and 11.4% for patients with symptomatic PE (P = .61). The 12-month cumulative incidences of major bleeding complications were also comparable in the 2 groups (8.1% for incidental patients and 9.8% for symptomatic patients; P = .62). However, the respective 12-month mortality risks were 34.6% and 30.2% in lung cancer patients with IPE and SPE respectively (P = .03). On multivariate Cox analysis, we found that IPE occurrence was an independent risk factor associated with 1-year mortality in lung cancer patients complicated with PE after adjusting for age and sex (HR 1.517; 95% CI: 1.366-1.684; P = .027). Our findings suggest that lung cancer patients diagnosed with and treated for incidental PE had a similar rate of recurrent VTE, and incidence of hemorrhagic complications, but a significantly higher 1-year cumulative mortality rate after PE compared to those with symptomatic PE. IPE may be a marker of poor prognosis.

MiR-202-3p inhibits the proliferation and metastasis of lung adenocarcinoma cells by targeting RRM2.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer, and its pathogenesis is still unclear. The present study aimed to investigate the role of miR-202-3p and its downstream target gene, ribonucleotide reductase regulatory subunit M2 (RRM2), in the occurrence and development of LUAD and elucidate the correlation between RRM2 and the clinicopathological stage and prognosis of LUAD. The expression of miR-202-3p was analyzed using the CancerMIRNome database and quantitative polymerase chain reaction (qPCR). The effects of miR-202-3p and RRM2 on the proliferation, migration, and invasion of A549 cells were analyzed. A dual luciferase reporter assay was used to verify the targeting of miR-202-3p and RRM2. Additionally, the correlation between RRM2 expression and clinicopathology was analyzed. (I) MiR-202-3p was lowly expressed in LUAD and the LUAD cell lines. qPCR confirmed that microRNA (miRNA) transfection was effective and sufficient for subsequent experiments. (II) MiR-202-3p inhibited the proliferation, invasion, and migration of LUAD cells. (III) There was a targeting relationship between miR-202-3p and RRM2, and miR-202-3p affected the expression of the RRM2 protein. RRM2 was highly expressed in lung cancer tissue. (IV) RRM2 was associated with the clinicopathological staging of lung cancer. The prognosis of patients with low RRM2 expression was better, and the prognostic sensitivity of RRM2 to lung cancer was high. RRM2 may exert its effects via the Notch pathway. (V) Si-RRM2 inhibited the expression of the RRM2 protein. RRM2 promoted the proliferation, migration, and invasion of LUAD cells. A miR-202-3p inhibitor restored the inhibitory effect of si-RRM2 on LUAD cells. MiR-202-3p was lowly expressed in lung cancer tissue. MiR-202-3p overexpression inhibited the proliferation and metastasis of lung cancer cells. RRM2 was highly expressed in lung cancer tissue and promoted the proliferation and metastasis of lung cancer cells. MiR-202-3p targeted and inhibited RRM2, thereby reducing the proliferation and metastasis of LUAD cells. LUAD patients with low RRM2 expression had a better prognosis, and the expression level of RRM2 was correlated with the clinical characteristics of lung cancer patients.

Transcription factor SP1 and oncoprotein PPP1R13L regulate nicotine-induced epithelial-mesenchymal transition in lung adenocarcinoma via a feedback loop

Tobacco remains the most common environmental carcinogen leading to the occurrence and development of lung cancer. Nicotine, a tumor promoter in cigarette smoke, has been shown to induce epithelial-mesenchymal transition (EMT), a cellular program required for the invasion and metastasis in tumor cells. Specificity Protein 1 (SP1) is a well-characterized transcription factor that can regulate the EMT process via transcriptionally activating E-cadherin expression. Protein Phosphatase 1 Regulatory Subunit 13 Like (PPP1R13L) is a newly identified oncoprotein previously reported to inhibit the transcriptional activity of SP1 via a direct protein–protein interaction. To reveal the underlying implication of the interconnections between PPP1R13L and SP1 in the nicotine-induced EMT process, the present study established an EMT cell model of lung cancer using 1 μM of nicotine, a dose close to human exposure, in which an alternate fluctuation in the expression of PPP1R13L and SP1 was captured. Subsequently, the direct inhibition of SP1 by PPP1R13L was demonstrated to be a critical mechanism underlying the involvement of PPP1R13L in the nicotine-induced EMT process. More interestingly, SP1 was further shown to transcriptionally activate PPP1R13L expression in a feedback manner. In addition, PPP1R13L and SP1 expression was found to be closely associated with the clinicopathological characteristics of lung cancer patients. Here we proposed a novel feedback regulation mechanism, in which SP1 may transcriptionally activate the PPP1R13L gene expression in the early stage of lung cancer to promote tumor growth, while the accumulation of PPP1R13L drives tumor invasion and metastasis by direct repression of SP1. Thus, this unique feedback loop between PPP1R13L and SP1 may play a vital role in chemical carcinogenesis and serve as a potential intervention target for lung cancer progression attributable to cigarette smoking.

Predicting the prevalence of lung cancer using feature transformation techniques

Healthcare sector is one of the most important sectors of any country as a big part of the country’s economy is associated with it. The research is about to contribute to the health sector by minimizing the expenses of a lung cancer diagnosis. The study tries to devise an efficient method for initial screening of the patients with symptoms through their demographic and clinical data. The study seeks appropriate feature transformation techniques from dimensionality reduction techniques in combination with an apposite regression model that can perform this task robustly using the lung cancer dataset for early carcinoma diagnosis. To equip the health sector with state-of-the-art technology and for the betterment of humankind, the most beneficial tool of today is machine learning. Lungs play a vivacious role in the human body, oxygen is circulated in the body, and the air is taken from the atmosphere and sends it into the bloodstream. Several people decease every year because of lung carcinoma as lung cancer is normally identified at the latter phase due to lack of awareness. It stays unidentified because people have pneumonia often, which converts into lung cancer later. The projected research seeks to enable health professionals to the rationalization of primary diagnosis and treatment of lung carcinoma in developing countries. The proposed methodology has selected the optimized combination of regression-based machine learning technique and feature transformation technique for the available patterns based on demographic and clinical features of lung cancer patients. Based on the gathered results during training (RMSE = 0.1324, R2-Score = 0.7428) and testing (RMSE = 0.1273, R2-Score = 0.7405) it can be concluded that the fast independent component analysis and elastic net regression technique provided optimized results and outperform the other aspirant techniques.