Subtype Of Lung Cancer Research Articles

Optimization of treatment strategies for elderly patients with advanced non-small cell lung cancer.

Lung cancer stands as a malignant neoplasm bearing the highest burden of morbidity and mortality within the elderly population on a global scale. Among the lung cancer subtypes, non-small cell lung cancer (NSCLC) prevails as the most prevalent. As age advances, elderly patients often present with an increased prevalence of comorbidities, diminished organ reserve function, and alterations in drug pharmacokinetics, including absorption, distribution, metabolism, and clearance. These factors collectively contribute to a reduction in their capacity to tolerate therapeutic interventions. Regrettably, there exists a paucity of research data and evidence regarding the management of elderly patients afflicted by advanced lung cancer. This article endeavors to compile and elucidate strategies for the enhancement of treatment approaches, with the aim of aiding clinical decision-making. Prior to the selection of clinical treatment modalities for elderly patients with advanced NSCLC, a comprehensive assessment should be conducted, taking into account various facets, including tumor characteristics, patient age, physiological status, and the presence of comorbidities. The treatment strategy should be implemented in a tiered fashion, thereby affording the opportunity for the tailoring of individualized therapeutic approaches for elderly patients afflicted by advanced NSCLC. The demographic of elderly patients confronting advanced NSCLC presents a complex landscape marked by intricate underlying conditions, necessitating the imperative optimization of treatment strategies.

Subclassification of lung adenocarcinoma through comprehensive multi-omics data to benefit survival outcomes

ObjectivesLung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Understanding the molecular mechanisms underlying tumor progression is of great clinical significance. This study aims to identify novel molecular markers associated with LUAD subtypes, with the goal of improving the precision of LUAD subtype classification. Additionally, optimization efforts are directed towards enhancing insights from the perspective of patient survival analysis. Materials and methodsWe propose an innovative feature-selection approach that focuses on LUAD classification, which is comprehensive and robust. The proposed method integrates multi-omics data from The Cancer Genome Atlas (TCGA) and leverages a synergistic combination of max-relevance and min-redundancy, least absolute shrinkage and selection operator, and Boruta algorithms. These selected features were deployed in six machine-learning classifiers: logistic regression, random forest, support vector machine, naive Bayes, k-Nearest Neighbor, and XGBoost. ResultsThe proposed approach achieved an area under the receiver operating characteristic curve (AUC) of 0.9958 for LR. Notably, the accuracy and AUC of a composite model incorporating copy number, methylation, as well as RNA- sequencing data for expression of exons, genes, and miRNA mature strands surpassed the accuracy and AUC metrics of models with single-omics data or other multi-omics combinations. Survival analyses, revealed the SVM classifier to elicit optimal classification, outperforming that achieved by TCGA. To enhance model interpretability, SHapley Additive exPlanations (SHAP) values were utilized to elucidate the impact of each feature on the predictions. Gene Ontology (GO) enrichment analysis identified significant biological processes, molecular functions, and cellular components associated with LUAD subtypes. ConclusionIn summary, our feature selection process, based on TCGA multi-omics data and combined with multiple machine learning classifiers, proficiently identifies molecular subtypes of lung adenocarcinoma and their corresponding significant genes. Our method could enhance the early detection and diagnosis of LUAD, expedite the development of targeted therapies and, ultimately, lengthen patient survival.

Histological trends and molecular genetic features of non-small cell lung cancer in the Khanty-Mansiysk autonomous district – Ugra

Objective: to study the histological structure of lung cancer, as well as molecular-genetic, gender, demographic and anamnestic characteristics of patients with non-small cell lung cancer in Khanty-Mansiysk Autonomous district – Ugra. Material and Methods. Material for the study consisted of 6725 cases of lung cancer for the period 2001–2020 and 266 cases diagnosed with non-small cell lung cancer for the period 2020–2023. Nonparametric Fisher’s criterion and χ2 test were used to analyze statistical factors. The relative risk of an event in the main group compared to the control group was calculated. Results. Squamous cell carcinoma remained the most common histological form among lung cancers detected for the periods 2001–2010 and 2011–2020 (40.2 and 38.3 %, respectively). During the second decade of the study period, the proportion of lung adenocarcinoma increased by 9.6%, approaching the rates of squamous cell lung carcinoma. It should be noted that in the structure of all histologic subtypes of non-small cell lung cancer, genetic aberrations occurred more frequently in adenocarcinoma than in other histologic forms of lung cancer (33 vs 6 %, respectively). The results of the analysis showed that the relative risk of developing genetic aberrations in EGFR, KRAS, ALK oncogenes was respectively 21.08; 9.04 and 10.84 times higher in lung adenocarcinoma and 15.87; 2.18 and 10.2 times higher among never smokers than in the control groups. The incidence of mutations in the EGFR gene was statistically more frequent in women (p<0.001), and the incidence of translocation in the AL K gene was predominantly diagnosed at age ≥48 years (p=0.002) regardless of gender. The specificity of PD-L1 expression levels (low – 63.2 %, medium – 16.2 %, high – 4.5 %) is consistent with other recent studies. Conclusion. The study of molecular-genetic changes observed in patients with non-small-cell lung cancer in Ugra allows the development of organizational and methodological approaches to diagnosis and treatment of these patients.

Predictors of lung cancer subtypes and lymph node status in non-small-cell lung cancer: intravoxel incoherent motion parameters and extracellular volume fraction

ObjectiveTo determine the performance of intravoxel incoherent motion (IVIM) parameters and the extracellular volume fraction (ECV) in distinguishing between different subtypes of lung cancer and predicting lymph node metastasis (LNM) status in patients with non-small-cell lung cancer (NSCLC).MethodsOne hundred sixteen patients with lung cancer were prospectively recruited. IVIM, native, and postcontrast T1 mapping examinations were performed, and the T1 values were measured to calculate the ECV. The differences in IVIM parameters and ECV were compared between NSCLC and small-cell lung cancer (SCLC), adenocarcinoma (Adeno-Ca) and squamous cell carcinoma (SCC), and NSCLC without and with LNM. The assessment of each parameter’s diagnostic performance was based on the area under the receiver operating characteristic curve (AUC).ResultsThe apparent diffusion coefficient (ADC), true diffusion coefficient (D), and ECV values in SCLC were considerably lower compared with NSCLC (all p < 0.001, AUC > 0.887). The D value in SCC was substantially lower compared with Adeno-Ca (p < 0.001, AUC = 0.735). The perfusion fraction (f) and ECV values in LNM patients were markedly higher compared with those without LNM patients (p < 0.01, < 0.001, AUC > 0.708).ConclusionIVIM parameters and ECV can serve as non-invasive biomarkers for assisting in the pathological classification and LNM status assessment of lung cancer patients.Critical relevance statementIVIM parameters and ECV demonstrated remarkable potential in distinguishing pulmonary carcinoma subtypes and predicting LNM status in NSCLC.Key PointsLung cancer is prevalent and differentiating subtype and invasiveness determine the treatment course.True diffusion coefficient and ECV showed promise for subtyping and determining lymph node status.These parameters could serve as non-invasive biomarkers to help determine personalized treatment strategies.Graphical

Knockdown of miR-1293 attenuates lung adenocarcinoma angiogenesis via Spry4 upregulation–mediated ERK1/2 signaling inhibition

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Angiogenesis plays a pivotal role in LUAD progression via supplying oxygen and nutrients for cancer cells. Non-coding miR-1293, a significantly up-regulated miRNA in LUAD tissues, can be potentially used as a novel biomarker for predicting the prognosis of LUAD patients. However, little information is available about the function of miR-1293 in LUAD progression especially cancer-induced angiogenesis. Herein, we found that miR-1293 knockdown could obviously attenuate LUAD-induced angiogenesis in vitro and down-regulate two most important pro-angiogenic cytokines VEGF-A and bFGF expression and secretion. Indeed, miR-1293 abrogation inactivated the angiogenesis-promoting ERK1/2 signaling characterized by decreased ERK1/2 phosphorylation and translocation from nucleus to cytoplasm. Next we found that miR-1293 knockdown reactivated the endogenous ERK1/2 pathway inhibitor Spry4 expression and Spry4 perturbance with specific siRNA transfection abolished the inhibition of ERK1/2 pathway and LUAD-induced angiogenesis by miR-1293 knockdown. Finally, with in vivo assay, we found obvious Spry4 up-regulation and VEGF-A, bFGF, ERK1/2 phosphorylation, micro-vessel density marker CD31 expression down-regulation in vivo, respectively. Collectively, these results indicated that miR-1293 knockdown could significantly attenuate LUAD angiogenesis via Spry4-mediated ERK1/2 signaling inhibition, which might be helpful for uncovering more functions of miR-1293 in LUAD and providing experimental basis for possible LUAD therapeutic strategy targeting miR-1293.

Therapeutic effect of induction therapy including nab-paclitaxel followed by surgical resection for the patients with locally advanced non-small-cell lung cancer

BackgroundLung cancer is associated with a high mortality rate worldwide. Non-small-cell lung cancer (NSCLC) is a major subtype of lung cancer. Carboplatin (CBDCA) plus nab-paclitaxel (PTX) has become a standard treatment for advanced unresectable NSCLC. However, treatment with nab-PTX has not been established as a standard therapy for resectable locally advanced (LA)-NSCLC.MethodsWe conducted a comprehensive study involving consecutive patients with locally advanced NSCLC who underwent induction therapy including nab-PTX followed by surgical resection. Fifteen patients with locally advanced NSCLC underwent induction therapy including nab-PTX followed by surgical resection. Concurrent chemoradiotherapy (CRT) consisted of weekly administration of nab-PTX (50 mg/m2) plus CBDCA (area under the plasma concentration time curve (AUC) 2) and thoracic radiotherapy (50 Gy/25 fractions).ResultsThe clinical stages were as follows: IIB (n =1), IIIA (n =12), and IIIC (n =2). Downstaging was observed in 73% (11/15) of patients on comparison with the clinical stage before concurrent CRT. Adverse drug reactions were observed in seven patients. Complete resection was performed in all patients. The re-evaluated pathological stage after pretreatment was diagnosed as stage 0 in three patients, stage IA1 in six, stage IA2 in one, and stage IIIA in five. The pathological effects of previous therapy were as follows: Ef3 (n =3), Ef2 (n =9), and Ef1a (n =3).ConclusionThe therapeutic effect of induction therapy including nab-PTX was promising. Induction CRT, including nab-PTX, followed by resection, may be a viable alternative treatment option for locally advanced NSCLC.

Single-cell analysis of treatment-resistant prostate cancer: Implications of cell state changes for cell surface antigen–targeted therapies

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)-a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single-cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to current and future antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types.

Noninvasive Lung Cancer Subtype Classification Using Tumor-Derived Signatures and cfDNA Methylome.

This study explores the use of cfDNA methylomes for the classification of lung cancer subtypes, vital for effective treatment. By identifying specific methylation markers in tumor tissues, we developed a robust classification model achieving high accuracy for noninvasive subtype detection. This cfDNA methylome approach offers promising avenues for early detection and monitoring.

PP01.19 Comparison of A.I. Models in Lung Cancer Staging and Subtyping

PP01.19 Comparison of A.I. Models in Lung Cancer Staging and Subtyping

Machine learning-based integration of CD8 T cell-related gene signatures for comprehensive prognostic assessment in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) stands as the most prevalent histological subtype of lung cancer, exhibiting heterogeneity in outcomes and diverse responses to therapy. CD8 T cells are consistently present throughout all stages of tumor development and play a pivotal role within the tumor microenvironment (TME). Our objective was to investigate the expression profiles of CD8 T cell marker genes, establish a prognostic risk model based on these genes in LUAD, and explore its relationship with immunotherapy response. By leveraging the expression data and clinical records from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, we identified 23 consensus prognostic genes. Employing ten machine-learning algorithms, we generated 101 combinations, ultimately selecting the optimal algorithm to construct an artificial intelligence-derived prognostic signature named riskScore. This selection was based on the average concordance index (C-index) across three testing cohorts. RiskScore emerged as an independent risk factor for overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS) in LUAD. Notably, riskScore exhibited notably superior predictive accuracy compared to traditional clinical variables. Furthermore, we observed a positive correlation between the high-risk riskScore group and tumor-promoting biological functions, lower tumor mutational burden (TMB), lower neoantigen (NEO) load, and lower microsatellite instability (MSI) scores, as well as reduced immune cell infiltration and an increased probability of immune evasion within the TME. Of significance, the immunophenoscore (IPS) score displayed significant differences among risk subgroups, and riskScore effectively stratified patients in the IMvigor210 and GSE135222 immunotherapy cohort based on their survival outcomes. Additionally, we identified potential drugs that could target specific risk subgroups. In summary, riskScore demonstrates its potential as a robust and promising tool for guiding clinical management and tailoring individualized treatments for LUAD patients.

The causal effect of atopic dermatitis on lung cancer: A Mendelian randomization study.

Growing evidence has shown that atopic dermatitis (AD) may decrease lung cancer (LC) risk. However, the causality between the two diseases is inconsistent and controversial. Therefore, we explored the causal relationship between AD and different histological subtypes of LC by using the Mendelian randomization (MR) method. We conducted the MR study based on summary statistics from the genome-wide association studies (GWAS) of AD (10,788 cases and 30,047 controls) and LC (29,266 cases and 56,450 controls). Instrumental variables (IVs) were obtained after removing SNPs associated with potential confounders. We employed inverse-variance weighted (IVW), MR-Egger, and weighted median methods to pool estimates, and performed a comprehensive sensitivity analysis. The results of the IVW method suggested that AD may decrease the risk of developing lung adenocarcinoma (LUAD) (OR=0.91, 95% CI: 0.85-0.97, P=0.007). Moreover, no causality was identified between AD and overall LC (OR=0.96, 95% CI: 0.91-1.01, P=0.101), lung squamous cell carcinoma (LUSC) (OR=1.04, 95% CI: 0.96-1.036, P=0.324), and small cell lung carcinoma (SCLC) (OR=0.95, 95% CI: 0.82-1.10, P=0.512). A comprehensive sensitivity test showed the robustness of our results. The present study indicates that AD may decrease the risk of LUAD in the European population, which needs additional investigations to identify the potential molecular mechanisms.

Pathological and imaging features of pulmonary invasive mucinous adenocarcinoma-a retrospective cohort study.

Pulmonary invasive mucinous adenocarcinoma (IMA) is a rare subtype of lung cancer which is easily misdiagnosed as inflammatory nodules, tuberculosis, pulmonary diffuse lesions, or hamartomas due to the lack of clinical specificity. This study aims to identify the pathological and imaging characteristics of IMA, which will favor to improve the diagnostic and therapeutic efficacy. A retrospective study was conducted by enrolling patients histopathologically diagnosed with pulmonary IMA in the current study between January 2014 and December 2021. The clinical pathological and radiological data were collected for analysis to evaluate the radiological patterns and pathological and molecular characteristics of IMA. A total of 136 patients were included in the study, of whom 58 were male and 78 were female. The patients had an average age of 63.0±9.7 years. The tumors were classified into the following three pathological types: pure mucinous (76 cases) featured by only mucinous cells observed under the microscope; mixed mucinous (23 cases) featured as an attached-wall, papillary, acinar, and solid tumor cells with more than 10% mucinous cells.; and mucinous-absent (29 cases) featured with the absence of mucous cells, but still can detect more than 10% of mucin expresses. In terms of the morphological classification based on the CT scans, 88 (64.7%) cases were identified as the nodular type, 31 (22.8%) as the inflammatory type, 15 (11.1%) as the mass-like type, and two (1.5%) as the diffuse type. For the molecular features, patients afflicted with IMA showed much lower levels of thyroid transcription factor-1 (15%) than those with usual adenocarcinoma (over 80%). However, cytokeratin 20 was more common in IMA (50%) than the usual adenocarcinoma (about 5%). The K-RAS mutation was prevalent in 75% of IMA, which contrasted sharply to its occurrence in a mere 15% of the usual adenocarcinoma. Epidermal growth factor receptor mutations were rarer in IMA (less than 5%) than the usual adenocarcinoma (about 50%). The pathological and imaging features enrich our understanding of the disease's heterogeneity, which will contribute to more personalized diagnostic and therapeutic strategies.

P53 Genetics and Biology in Lung Carcinomas: Insights, Implications and Clinical Applications.

The TP53 gene is renowned as a tumor suppressor, playing a pivotal role in overseeing the cell cycle, apoptosis, and maintaining genomic stability. Dysregulation of p53 often contributes to the initiation and progression of various cancers, including lung cancer (LC) subtypes. The review explores the intricate relationship between p53 and its role in the development and progression of LC. p53, a crucial tumor suppressor protein, exists in various isoforms, and understanding their distinct functions in LC is essential for advancing our knowledge of this deadly disease. This review aims to provide a comprehensive literature overview of p53, its relevance to LC, and potential clinical applications.

Identification of subgroups and development of prognostic risk models along the glycolysis–cholesterol synthesis axis in lung adenocarcinoma

Lung cancer is one of the most dangerous malignant tumors affecting human health. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Both glycolytic and cholesterogenic pathways play critical roles in metabolic adaptation to cancer. A dataset of 585 LUAD samples was downloaded from The Cancer Genome Atlas database. We obtained co-expressed glycolysis and cholesterogenesis genes by selecting and clustering genes from Molecular Signatures Database v7.5. We compared the prognosis of different subtypes and identified differentially expressed genes between subtypes. Predictive outcome events were modeled using machine learning, and the top 9 most important prognostic genes were selected by Shapley additive explanation analysis. A risk score model was built based on multivariate Cox analysis. LUAD patients were categorized into four metabolic subgroups: cholesterogenic, glycolytic, quiescent, and mixed. The worst prognosis was the mixed subtype. The prognostic model had great predictive performance in the test set. Patients with LUAD were effectively typed by glycolytic and cholesterogenic genes and were identified as having the worst prognosis in the glycolytic and cholesterogenic enriched gene groups. The prognostic model can provide an essential basis for clinicians to predict clinical outcomes for patients. The model was robust on the training and test datasets and had a great predictive performance.

Rare Carcinomas of Lung - A Case Series and Rreview of Literature

Lung cancer remains a leading cause of mortality and morbidity related to cancers. Apart from common subtypes of lung cancer like Non-small cell carcinoma (NSCLC) and Small cell lung carcinoma (SCLC), there are clinical entities that are very rare in occurrence and differ in diagnostic workup, treatment, and prognosis. The symptoms or clinical presentation of such rare tumors may be similar to the commoner varieties. However, their diagnosis is a clinical challenge in common practice. Hence, early suspicion, and prompt diagnosis by histopathological, immunohistochemical analysis, and imaging studies are of paramount importance. Here we present a trilogy of rare carcinomas of the lung.

AMPK activation reduces cancer cell aggressiveness via inhibition of monoamine oxidase A (MAO-A) expression/activity

AimAMPK can be considered as an important target molecule for cancer for its unique ability to directly recognize cellular energy status. The main aim of this study is to explore the role of different AMPK activators in managing cancer cell aggressiveness and to understand the mechanistic details behind the process. Main methodsFirst, we explored the AMPK expression pattern and its significance in different subtypes of lung cancer by accessing the TCGA data sets for LUNG, LUAD and LUSC patients and then established the correlation between AMPK expression pattern and overall survival of lung cancer patients using Kaplan-Meire plot. We further carried out several cell-based assays by employing different wet lab techniques including RT-PCR, Western Blot, proliferation, migration and invasion assays to fulfil the aim of the study. Key findings•Expression of AMPK is correlated with survival and prognosis of lung cancer patients.•AMPK activators like Metformin and Phenformin downregulate A549 and HCT-116 cell proliferation and migration via repression of p38MAPK activity, subsequent augmentation of R1 repressor and corresponding downregulation of MAO-A expression/activity resulting reduction in the intracellular ROS.•SRT-1720 directly activates AMPK in LKB1 mutant A549 cells either alone or in combination with Metformin resulting regulation of cancer cell aggressiveness. SignificanceThis study identifies the importance of AMPK activators as a repurposing agent for combating lung and colon cancer cell aggressiveness. It also suggests SRT-1720 as a potent repurposing agent for cancer treatment especially in NSCLC patients where a point mutation is present in LKB1.

Causal association between immune cells and lung cancer risk: a two-sample bidirectional Mendelian randomization analysis.

Previous studies have highlighted the crucial role of immune cells in lung cancer development; however, the direct link between immunophenotypes and lung cancer remains underexplored. We applied two-sample Mendelian randomization (MR) analysis, using genetic variants as instruments to determine the causal influence of exposures on outcomes. This method, unlike traditional randomized controlled trials (RCTs), leverages genetic variants inherited randomly at conception, thus reducing confounding and preventing reverse causation. Our analysis involved three genome-wide association studies to assess the causal impact of 731 immune cell signatures on lung cancer using genetic instrumental variables (IVs). We initially used the standard inverse variance weighted (IVW) method and further validated our findings with three supplementary MR techniques (MR-Egger, weighted median, and MR-PRESSO) to ensure robustness. We also conducted MR-Egger intercept and Cochran's Q tests to assess heterogeneity and pleiotropy. Additionally, reverse MR analysis was performed to explore potential causality between lung cancer subtypes and identified immunophenotypes, using R software for all statistical calculations. Our MR analysis identified 106 immune signatures significantly associated with lung cancer. Notably, we found five suggestive associations across all sensitivity tests (P<0.05): CD25 on IgD- CD24- cells in small cell lung carcinoma (ORIVW =0.885; 95% CI: 0.798-0.983; P IVW =0.022); CD27 on IgD+ CD24+ cells in lung squamous cell carcinoma (ORIVW =1.054; 95% CI: 1.010-1.100; P IVW =0.015); CCR2 on monocyte cells in lung squamous cell carcinoma (ORIVW =0.941; 95% CI: 0.898-0.987; P IVW =0.012); CD123 on CD62L+ plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) as well as on plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) in lung squamous cell carcinoma. This study establishes a significant genomic link between immune cells and lung cancer, providing a robust basis for future clinical research aimed at lung cancer management.

Additional impact of genetic ancestry over race/ethnicity to prevalence of KRAS mutations and allele-specific subtypes in non-small cell lung cancer

KRAS mutation is the most common oncogenic driver in patients with non-small cell lung cancer (NSCLC). However, the detailed understanding of how self-reported race and/or ethnicity (SIRE), genetically inferred ancestry (GIA), and their interaction affect KRAS mutation is largely unknown. Here, we investigated the associations between SIRE, quantitative GIA, and KRAS mutation and its allele-specific subtypes in a multi-ethnic cohort of 3918 patients from the Boston Lung Cancer Survival cohort and the Chinese OrigiMed cohort with an independent validation cohort of 1450 patients with NSCLC. This comprehensive analysis included detailed covariates including age at diagnosis, sex, clinical stage, cancer histology, and smoking status. We report that SIRE is significantly associated with KRAS mutations, modified by sex, with SIRE-Asian patients showing lower rates of KRAS mutation, transversion substitution, and the allele-specific subtype KRASG12C compared to SIRE-White patients, after adjusting for potential confounders. Moreover, GIA was found to correlate with KRAS mutations, where patients with a higher proportion of European ancestry had an increased risk of KRAS mutations, especially more transition substitutions and KRASG12D. Notably, among SIRE-White patients, an increase in European ancestry was linked to a higher likelihood of KRAS mutations, whereas an increase in Admixed American ancestry was associated with a reduced likelihood, suggesting that quantitative GIA offers additional information beyond SIRE. The association of SIRE, GIA, and their interplay with KRAS driver mutations in NSCLC highlights the importance of incorporating both into population-based cancer research, aiming to refine clinical decision-making processes and mitigate health disparities.

Identification of oxidative stress signatures of lung adenocarcinoma and prediction of patient prognosis or treatment response with single-cell RNA sequencing and bulk RNA sequencing data

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer globally, has seen improved prognosis with advancements in diagnostic, surgical, radiotherapy, and molecular therapy techniques, while its 5-year survival rate remains low. Molecular biomarkers provide prognostic value. Oxidative stress factors, such as reactive nitrogen species and ROS, are crucial in various stages of tumor progression, influencing cell transformation, proliferation, angiogenesis, and metastasis. ROS demonstrate dual roles, affecting tumor cells, hypoxia sensitivity, and the microenvironment. Comprehensive analysis of oxidative stress in LUAD has not been conducted to date. Therefore, we systematically investigated the regulatory patterns of oxidative stress in LUAD based on oxidative stress-related genes and correlated these patterns with cellular infiltration characteristics of the tumor immune microenvironment. The model utilizes single-factor Cox analysis to screen key differential genes with prognostic value and employs least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct a prognostic-related prediction model. Ten candidate genes were selected based on this model. The risk score was constructed using the coefficients and expression levels of these ten genes. Furthermore, the impact of this risk score on overall survival (OS) was determined. Two genes with the most significant differential expression, SFTPB and S100P, were selected through qRT-PCR. Cell experiments including CCK-8, Edu, transwell assays confirmed their effects on lung cancer cells growth, consistent with the results of bioinformatics analysis. These findings suggested that this model held potential clinical value for evaluating the prognosis of lung adenocarcinoma.

Investigating causal associations between pneumonia and lung cancer using a bidirectional mendelian randomization framework

BackgroundPneumonia and lung cancer are both major respiratory diseases, and observational studies have explored the association between their susceptibility. However, due to the presence of potential confounders and reverse causality, the comprehensive causal relationships between pneumonia and lung cancer require further exploration.MethodsGenome-wide association study (GWAS) summary-level data were obtained from the hitherto latest FinnGen database, COVID-19 Host Genetics Initiative resource, and International Lung Cancer Consortium. We implemented a bidirectional Mendelian randomization (MR) framework to evaluate the causal relationships between several specific types of pneumonia and lung cancer. The causal estimates were mainly calculated by inverse-variance weighted (IVW) approach. Additionally, sensitivity analyses were also conducted to validate the robustness of the causalty.ResultsIn the MR analyses, overall pneumonia demonstrated a suggestive but modest association with overall lung cancer risk (Odds ratio [OR]: 1.21, 95% confidence interval [CI]: 1.01 − 1.44, P = 0.037). The correlations between specific pneumonia types and overall lung cancer were not as significant, including bacterial pneumonia (OR: 1.07, 95% CI: 0.91 − 1.26, P = 0.386), viral pneumonia (OR: 1.00, 95% CI: 0.95 − 1.06, P = 0.891), asthma-related pneumonia (OR: 1.18, 95% CI: 0.92 − 1.52, P = 0.181), and COVID-19 (OR: 1.01, 95% CI: 0.78 − 1.30, P = 0.952). Reversely, with lung cancer as the exposure, we observed that overall lung cancer had statistically crucial associations with bacterial pneumonia (OR: 1.08, 95% CI: 1.03 − 1.13, P = 0.001) and viral pneumonia (OR: 1.09, 95% CI: 1.01 − 1.19, P = 0.037). Sensitivity analysis also confirmed the robustness of these findings.ConclusionThis study has presented a systematic investigation into the causal relationships between pneumonia and lung cancer subtypes. Further prospective study is warranted to verify these findings.