Histological Types Of Lung Cancer Research Articles

T1 mapping-based radiomics in the identification of histological types of lung cancer: a reproducibility and feasibility study.

T1 mapping can quantify the longitudinal relaxation time of tissues. This study aimed to investigate the repeatability and reproducibility of T1 mapping radiomics features of lung cancer and the feasibility of T1 mapping-based radiomics model to predict its pathological types. The chest T1 mapping images and clinical characteristics of 112 lung cancer patients (54 with adenocarcinoma and 58 with other types of lung cancer) were collected retrospectively. 54 patients underwent twice short-term T1 mapping scans. Regions of interest were manually delineated on T1 mapping pseudo-color images to measure the mean native T1 values of lung cancer, and radiomics features were extracted using the semi-automatic segmentation method by two independent observers. The patients were randomly divided into training group (77 cases) and validation group (35 cases) with the ratio of 7:3. Interclass correlation coefficients (ICCs), Student's t-test or Mann-Whitney U tests and least absolute shrinkage and selection operator (LASSO) were used for feature selection. The optimum features were selected to establish a logistic regression (LR) radiomics model. Independent sample t-test, Mann Whitney U-test or chi square test were used to compare the differences of clinical characteristics and T1 values. Performance was compared by the area under the receiver operating characteristic (ROC) curve (AUC). In the training group, smoking history, lesion type and native T1 values were different between adenocarcinoma and non-adenocarcinoma patients (P = 0.004-0.038). There were 1035 (54.30%) radiomics features meet the intra-and inter-observer, and test-retest reproducibility with ICC > 0.80. After feature dimensionality reduction and model construction, the AUC of T1 mapping-based radiomics model for predicting the pathological types of lung cancer was 0.833 and 0.843, respectively, in the training and validation cohorts. The AUCs of T1 value and clinical model (including smoking history and lesion type) were 0.657 and 0.692 in the training group, and 0.722 and 0.686 in the validation group. Combined with T1 mapping radiomics, clinical model and T1 value to establish a combined model, the prediction efficiency was further improved to 0.895 and 0.915 in the training and validation groups. About 50% of the T1 mapping-based radiomics features displayed relatively poor repeatability and reproducibility. While T1 mapping-based radiomics model is valuable in identification of histological types of lung cancer despite the measurement variability. Combination of T1 mapping radiomics model, clinical characteristics and native T1 value can improve the predictive value of pathological types of lung cancer.

The association of combined GSTM1, GSTT1, and GSTP1 genetic polymorphisms with lung cancer risk in male Iraqi Waterpipe Tobacco (Nargila) smokers

Mutations in genes encoding proteins necessary for detoxifying oxidative stress products have been predicted to increase susceptibility to lung cancer (LC). Despite this, the association between waterpipe tobacco smoking (WP), genetic polymorphisms, and LC risk remains poorly understood. This is the first study to explore the relationship between WP tobacco smoking and these genetic factors. Previously, we investigated the association of GSTP1 SNPs (rs1695-A/G and rs1138272-C/T) with LC in Iraqi males who smoke WP. Here, we expanded our analysis to include GSTM1 (active/null) and GSTT1 (active/null) genotypes, both individually and in combination with GSTP1 SNPs. Multiplex PCR and RFLP-PCR assays were utilized to determine the genotypes of 123 cases and 129 controls. No significant association was observed between GSTM1-null or GSTT1-null genotypes and LC risk, either separately or in combination with variant genotypes of GSTP1 (rs1695 "AG+GG" and rs1138272 "CT+TT"). However, smoking WP and carrying null genotypes elevated the risk five-fold for GSTM1-null (OR 5.17, 95 % CI 2.02–13.24, P<0.001) and three-fold for GSTT1-null (OR 3.08, 95 % CI 1.55–6.13, P=0.001) compared to non-smokers carrying active genotypes. Conversely, genotype distribution analysis based on LC histological types did not indicate an increased risk of LC. Lung cancer is a complex multifactorial disease. WP smoking and GSTs genetic polymorphisms might be associated with an increased risk of developing LC. However, our data did not confirm an association between GST polymorphisms alone and the risk of LC.

Artificial Intelligence Recognition Model Using Liquid-Based Cytology Images to Discriminate Malignancy and Histological Types of Non-Small-Cell Lung Cancer

Introduction: Artificial intelligence image recognition has applications in clinical practice. The purpose of this study was to develop an automated image classification model for lung cancer cytology using a deep learning convolutional neural network (DCNN). Methods: Liquid-based cytology samples from 8 normal parenchymal (N), 22 adenocarcinoma (ADC), and 15 squamous cell carcinoma (SQCC) surgical specimens were prepared, and 45 Papanicolaou-stained slides were scanned using whole-slide imaging. The final dataset of 9,141 patches consisted of 2,737 N, 4,756 ADC, and 1,648 SQCC samples. Densenet-121 was used as the DCNN to classify N versus malignant (ADC+SQCC) and ADC versus SQCC images. AdamW optimizer and 5-fold cross-validation were used in the training. Results: For malignancy prediction, the sensitivity, specificity, and accuracy were 0.97, 0.85, and 0.94, respectively, in the patch-level classification, and 0.92, 0.88, and 0.91, respectively, in the case-level classification. For SQCC prediction, the sensitivity, specificity, and accuracy were 0.86, 0.91, and 0.90, respectively, in the patch-level classification and 0.73, 0.82, and 0.78, respectively, in the case-level classification. Conclusion: The DCNN model performed excellently in predicting malignancy and histological types of lung cancer. This model may be useful for predicting cytopathological diagnosis in clinical situations by reinforcing training.

The relationship between lobar distribution and primary lung cancer histological types

Background: Lung cancer is the primary cause of cancer-related deaths globally. Accurate tumor location and subtype characterization are critical for optimizing treatment and predicting outcomes. This study aims to identify the relationship between lobar distribution and primary lung cancer histological types and describe the most recent patterns at the country-level origin. Methods: This cross-sectional study was conducted at a major tertiary care hospital in Bangladesh, including 165 patients recruited using purposive non-probability sampling. Data were collected using a semi-structured case record form and analyzed using SPSS version 28.0. Results: Tumors were most commonly found in the central area (58.2%). Squamous cell carcinoma was the most prevalent type (46.1%), followed by adenocarcinoma (38.8%), small cell carcinoma (13.9%), and large cell carcinoma (1.2%). The incidence of squamous cell carcinoma was significantly higher in the upper lobe of the right lung (55.9%) compared to other forms, particularly in the central region of the right lung (P &lt; 0.001). Squamous cell carcinoma was more common in the lower part of the left lung (42.9%), while adenocarcinoma was exclusively observed in the lingular portion of the left lung (100%). The major bronchus of the left lung primarily exhibited squamous cell carcinoma (60%), but this finding was not statistically significant (p=0.899). Conclusion: The study highlights the significant association between lobar distribution and histological types of primary lung cancer, emphasizing the need for precise tumor characterization for better treatment strategies and prognostic evaluation.

The role of circular RNAs (circRNAs) as a prognostic factor in lung cancer: a meta-analysis

BackgroundLung cancer is a leading cause of cancer-related death worldwide. Among various histological types of lung cancer, majority are non-small cell lung cancer (NSCLC) which account for > 80%. Circular RNAs (circRNAs) are widely expressed in various cancers including lung cancer and implicated in tumourigenesis and cancer progression. This study aimed to systematically evaluate the prognostic values of circRNAs in lung cancer.MethodsA systematic literature search was done in PubMed, Embase, and MEDLINE databases to select the eligible studies which reported the association between the expression of circRNAs and overall survival (OS) or disease-free survival (DFS) in histopathologically diagnosed lung cancer patients. The pooled hazard ratio (HR) and 95% confidence interval (CI) were assessed to determine the prognostic significance of circRNAs.ResultsA total of 43 studies were eligible for this meta-analysis (MA). 39 different types of circRNAs were reported: 28 showing upregulating and 11 showing downregulating action in lung cancer. High expression of circRNAs with upregulating action in lung cancer was associated with worse prognosis and poor OS (HR 1.93, 95% CI [1.61–2.33], p < 0.00001). High expression of circRNAs with downregulating action in lung cancer was associated with favorable OS and prognosis (HR 0.73, 95% CI [0.58–0.94], p = 0.01). However, there was no statistically significant association between high and low expression of both upregulating and downregulating circRNAs and DFS (HR 1.44, 95% CI [0.92–2.24], p = 0.11).ConclusionsThis MA confirmed the pivotal role of circRNAs as important prognostic biomarkers for lung cancer, especially NSCLC. High expression of upregulating circRNAs is associated with poor prognosis; however, high expression of downregulating circRNAs is associated with favorable prognosis. Therefore, downregulatory action of circRNAs should be considered a promising treatment in the management of lung cancer, especially NSCLC.

Construction of lncRNA prognostic model related to disulfidptosis in lung adenocarcinoma

BackgroundLung cancer is one of the malignant tumors with the highest rates of morbidity and mortality worldwide. One of the most common histological types of lung cancer is lung adenocarcinoma (LUAD). Despite the fact that development in medicine has significantly improved some patients’ prognoses, the overall survival (OS) rate is still very low. In glucose-deficient SLC7A11-overexpressed cancer cells, the accumulation of disulfide molecules leads to abnormal disulfide bonding between actin cytoskeletal proteins, interferes with their tissues, and eventually leads to actin network collapse and cell death. This mode of cell death is called disulfidptosis. Studies have shown that disulfidptosis may be a new target for cancer treatment. However, the role of disulfidptosis in LUAD is still unknown. MethodsLUAD transcriptome and clinical information from The Cancer Genome Atlas (TCGA) was downloaded. The co-expression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Cox regression analysis was performed to screen the disulfidptosis-related lncRNAs (DRLs) and build the prognostic model. Kaplan-Meier curve, Cox regression analysis, and receiver operating characteristic (ROC) curve was used to validate the model. Then a nomogram is made to predict the prognosis of LUAD patients. Finally, fresh-collected clinical samples were used to verify the expression of DRLs in LUAD. ResultsThe prognostic model with six DRLs was developed to predict the prognosis of LUAD, with superior prognosis value compared to other clinical variables. The Cox regression analysis revealed that T stage, N stage and the risk score were identified as independent variables that affected LUAD prognosis. ROC curve revealed that the model has a moderate diagnostic value, with an AUC of 1-year 0.684, 3-year 0.664, and 5-year 0.588. Moreover, nine medications connected to LUAD treatment were acquired through drug sensitivity analysis. LUAD tissue validation showed that AC012073.1, AC012615.1, EMSLR, and SNHG12 were highly expressed, while AL606834.1 and AL365181.2 with low expression. ConclusionSix DRLs were screened and verified to construct the prognostic model, which can accurately predict the LUAD prognosis. It establishes a basis for further exploration into the molecular mechanisms underlying LUAD and identification of potential biomarkers for diagnosis, prognosis, and therapeutic targets.

Lung Cancer Subtyping: A Short Review.

As of 2022, lung cancer is the most commonly diagnosed cancer worldwide, with the highest mortality rate. There are three main histological types of lung cancer, and it is more important than ever to accurately identify the subtypes since the development of personalized, type-specific targeted therapies that have improved mortality rates. Traditionally, the gold standard for the confirmation of histological subtyping is tissue biopsy and histopathology. This, however, comes with its own challenges, which call for newer sampling techniques and adjunctive tools to assist in and improve upon the existing diagnostic workflow. This review aims to list and describe studies from the last decade (n = 47) that investigate three such potential omics techniques-namely (1) transcriptomics, (2) proteomics, and (3) metabolomics, as well as immunohistochemistry, a tool that has already been adopted as a diagnostic adjunct. The novelty of this review compared to similar comprehensive studies lies with its detailed description of each adjunctive technique exclusively in the context of lung cancer subtyping. Similarities between studies evaluating individual techniques and markers are drawn, and any discrepancies are addressed. The findings of this study indicate that there is promising evidence that supports the successful use of omics methods as adjuncts to the subtyping of lung cancer, thereby directing clinician practice in an economical and less invasive manner.

The prognostic value of immune escape-related genes in lung adenocarcinoma.

Lung cancer is one of the most common cancers in humans, and lung adenocarcinoma (LUAD) has become the most common histological type of lung cancer. Immune escape promotes progression of LUAD from the early to metastatic late stages and is one of the main obstacles to improving clinical outcomes for immunotherapy targeting immune detection points. Our study aims to explore the immune escape related genes that are abnormally expressed in lung adenocarcinoma, providing assistance in predicting the prognosis of lung adenocarcinoma and targeted. RNA data and related clinical details of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Through weighted gene coexpression network analysis (WGCNA), 3112 key genes were screened and intersected with 182 immune escape genes obtained from a previous study to identify the immune escape-related genes (IERGs). The role of IERGs in LUAD was systematically explored through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses, which were used to enrich the relevant pathways of IERGs. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis were used to identify the key prognostic genes, and a prognostic risk model was constructed. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) and microenvironment cell populations (MCP) counter methods (which can accurately assess the amount of eight immune cell populations and two stromal cell groups) were used to analyze the tumor immune status of the high and low risk subgroups. The protein expression level of the differentially expressed genes in lung cancer samples was determined by using the Human Protein Atlas (HPA) database. A nomogram was constructed, and the prognostic risk model was verified via the Gene Expression Omnibus (GEO) datasets GSE72094 and GSE30219. Twenty differentially expressed IERGs were obtained. GO analysis of these 20 IERGs revealed that they were mainly associated with the regulation of immune system processes, immune responses, and interferon-γ enrichment in mediating signaling pathways and apoptotic signaling pathways; meanwhile, KEGG analysis revealed that IERGs were associated with necroptosis, antigen processing and presentation, programmed cell death ligand 1 (PD-L1) expression and programmed cell death 1 (PD-1) pathway in tumors, cytokine-cytokine receptor interactions, T helper cell 1 (Th1) and Th2 differentiation, and tumor necrosis factor signaling pathways. Using LASSO and Cox regression analysis, we constructed a four-gene model that could predict the prognosis of patients with LUAD, and the model was validated with a validation cohort. The immunohistochemical results of the HPA database showed that AHSA1 and CEP55 had low expression in normal lung tissue but high expression in lung cancer tissue. We constructed an IERG-based model for predicting the prognosis of LUAD. Among the genes identified, CEP55 and AHSA1 may be potential prognostic and therapeutic targets, and reducing their expression may represent a novel approach in the treatment of LUAD.

High-throughput characterization of functional variants highlights heterogeneity and polygenicity underlying lung cancer susceptibility

Genome-wide association studies (GWASs) have identified numerous lung cancer risk-associated loci. However, decoding molecular mechanisms of these associations is challenging since most of these genetic variants are non-protein-coding with unknown function. Here, we implemented massively parallel reporter assays (MPRAs) to simultaneously measure the allelic transcriptional activity of risk-associated variants. We tested 2,245 variants at 42 loci from 3 recent GWASs in East Asian and European populations in the context of two major lung cancer histological types and exposure to benzo(a)pyrene. This MPRA approach identified one or more variants (median 11 variants) with significant effects on transcriptional activity at 88% of GWAS loci. Multimodal integration of lung-specific epigenomic data demonstrated that 63% of the loci harbored multiple potentially functional variants in linkage disequilibrium. While 22% of the significant variants showed allelic effects in both A549 (adenocarcinoma) and H520 (squamous cell carcinoma) cell lines, a subset of the functional variants displayed a significant cell-type interaction. Transcription factor analyses nominated potential regulators of the functional variants, including those with cell-type-specific expression and those predicted to bind multiple potentially functional variants across the GWAS loci. Linking functional variants to target genes based on four complementary approaches identified candidate susceptibility genes, including those affecting lung cancer cell growth. CRISPR interference of the top functional variant at 20q13.33 validated variant-to-gene connections, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive functional analysis of lung cancer GWAS loci and help elucidate the molecular basis of heterogeneity and polygenicity underlying lung cancer susceptibility.

Long Noncoding RNA MSL3P1 Regulates CUL3 mRNA Cytoplasmic Transport and Stability and Promotes Lung Adenocarcinoma Metastasis.

Lung adenocarcinoma (LUAD) is the most prevalent histological type of lung cancer. Previous studies have reported that specific long noncoding RNAs (lncRNA) are involved in cancer development and progression. The phenotype and mechanism of ENST00000440028, named MSL3P1, an lncRNA referred to as a cancer-testis gene with potential roles in tumorigenesis and progression, have not been reported. MSL3P1 is overexpressed in LUAD tumor tissues, which is significantly associated with clinical characteristics, metastasis, and poor clinical prognosis. MSL3P1 promotes the metastasis of LUAD in vitro and in vivo. The enhancer reprogramming in LUAD tumor tissue is the major driver of the aberrant expression of MSL3P1. Mechanistically, owing to the competitive binding to CUL3 mRNA with ZFC3H1 protein (a protein involved in targeting polyadenylated RNA to exosomes and promoting the degradation of target mRNA), MSL3P1 can prevent the ZFC3H1-mediated RNA degradation of CUL3 mRNA and transport it to the cytoplasm. This activates the downstream epithelial-to-mesenchymal transition signaling pathway and promotes tumor invasion and metastasis. Implications: This study indicates that lncRNA MSL3P1 regulates CUL3 mRNA stability and promotes metastasis and holds potential as a prognostic biomarker and therapeutic target in LUAD.

A population level study on smoking and radon induced adenocarcinoma and small-cell carcinoma among males and females in Canada

ObjectiveTo assess if there is a relationship between residential radon exposure and two lung cancer histological types, small-cell carcinoma (diagnosed in people with a smoking history) and adenocarcinoma (the most commonly diagnosed histologic type in people who have never smoked) among males and females in Canada. MethodsWith survey data of long-term radon measurements in residential homes, long-term averaged tobacco consumption rates in the units of cigarettes per day per person and long-term averaged age-standardized lung cancer incidence rates at provincial level, simple linear fitting (ANOVA linear regression) was applied in this study to determine the effect on lung cancer induction by smoking and exposure to indoor radon, and to assess if there is a relationship between residential radon exposure and lung cancer histological types. ResultsLung cancer incidence rates correlate very well with the tobacco consumption rates (P ​< ​0.05). However, females appear to be more likely than males to develop lung cancer at a given amount of cigarette consumption. For both small-cell carcinoma and adenocarcinoma, a statistically significant correlation between incidence rate and mean radon concentration was observed for females, the correlation was much stronger for adenocarcinoma (P ​= ​0.0057) than small-cell carcinoma (P ​= ​0.0483). However, there was no such correlation for males. ConclusionIt is possible that female non-smokers are more susceptible to radon-induced lung cancer, and the joint effect of radon exposure and tobacco smoking may be worse in female smokers compared to males, such that higher incidence rate of adenocarcinoma among females compared to males were observed in recent decades, even though females never smoked more than males.

Treating lung cancer in resource limited setting: Retrospective study from Armenia.

e20055 Background: Lung cancer (LC) is second most common cancer by incidence in Armenia. Every year approximately 800-900 new cases are diagnosed, from all cases 55.5% are in the 4th stage. Methods: We have collected data from three oncology centers in Armenia: Yeolyan Hematology and Oncology Center, Mikaelyan Institute of Surgery, and Muratsan Hospital Complex of Yerevan State Medical University. In this retrospective hospital-based study the data of patients with LC who were treated at these three centers during the 01 Oct 2009 - 31 Dec 2023 period was collected․ Results: Four hundred and eighty-nine LC patients were involved in the final analysis. Male to female ratio was 6:1. From the all patients 10.6% were diagnosed at age ≤ 50, 79,6% of patients 50-70, and 9.6% ≥ 70 years. In 71.6% of all cases, LC was diagnosed in current or former smokers. Only 3% of patients were diagnosed in stage I, 9.8% in stage II, 44.8% in stage III, 41.1% in stage IV, and for 1.2% of patients' stage was unknown. From all cases 74% of patients had non small cell lung cancer (NSCLC), 22.7% small cell lung cancer (SCLC) and 3.3% had other histological types of lung cancer. Of all patients 63% are dead. The median overall survival (mOS) for all stages was 21 months for the entire cohort. Median OS was not reached for stage I ( &gt; 100 months), was 61 months for stage II, 23 months for stage III, and 13 months for stage IV (p &lt; 0,001). ALK mutation was checked in 22.7%, EGFR in 22%,ROS in 14.1%, KRAS in 11.2%, BRAF in 9.8% and of all patients. From all checked AKL was positive in 1.8%, EGFR in 19.4%, ROS in 2.8%, KRAS in 21.8%, BRAF in 8,3% and of cases. For patients with stage IV lung cancer (41.1%), we found a significant difference in mOS in those who received first line immunotherapy in combination with chemotherapy (19,4%) compared to those who received only chemotherapy (74.1%) (mOS: 24 months vs 11 months accordingly, p = 0.014). For stage I-III LC patients, those who received systematic therapy with cisplatin showed better overall survival than those who received systemic therapy with carboplatin (mOS 31 vs 25 months, p = 0.01), but for stage IV LC patients survival difference was not found (mOS 15 vs 12 months, p = 0.24). Conclusions: In Armenia, lung cancer is mostly diagnosed in the advanced stage where overall survival is approximately one year. In our study population, those who received immunotherapy in combination with chemotherapy showed doubled mOS, compared with only chemotherapy. In the nonmetastatic group, chemotherapy with cisplatin showed a significant increase in mOS compared with carboplatin.

NCI 159456 PERK Inhibitor as a Targeted Therapy for Lung Cancer: An In Vitro Study.

Non-small cell lung cancer (NSCLC) represents the most common histological type of lung cancer, characterized by a five-year survival rate of 15% and poor prognosis. Accumulating evidence indicates a prominent role of endoplasmic reticulum (ER) stress and the protein kinase RNA-like ER kinase (PERK)-dependent pathway of the unfolded protein response (UPR) in the pathogenesis of NSCLC. Increased expression of downstream targets of PERK was observed in various subtypes of NSCLC, and it was associated with a more aggressive phenotype, high risk of recurrence, and poor prognosis. Therefore, the present study aimed to investigate the biological effect of the selective PERK inhibitor NCI 159456 on A549 NSCLC cells and Human Pulmonary Fibroblasts (HPF) in vitro. Treatment of both normal and ER-stressed A549 cells with NCI 159456 resulted in a significant increase in the mRNA expression level of pro-apoptotic genes like activating transcription factor 4 (ATF4), DNA damage inducible transcript 3 (DDIT3), and BCL2 Associated X, Apoptosis Regulator (BAX) as well as a decreased level of the anti-apoptotic gene B-cell lymphoma 2 (Bcl-2). Cytotoxicity and genotoxicity analyses revealed that NCI 159456 significantly decreased viability and increased DNA damage in A549 cells under normal and ER stress conditions. Caspase-3 and reactive oxygen species (ROS) detection assays demonstrated that NCI 159456 significantly induced apoptosis and increased the ROS level in normal and ER-stressed A549 cells. Importantly, treatment with the inhibitor did not affect substantially normal HPF cells at any used concentration. The results indicate that PERK inhibitors could potentially be applied as a targeted therapy for NSCLC.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with lower survival rates. Recent advancements in targeted therapies and immunotherapies targeting immune checkpoints have achieved remarkable success, there is still a large percentage of LUAD that lacks available therapeutic options. Due to tumor heterogeneity, the diagnosis and treatment of LUAD are challenging. Exploring the biology of LUAD and identifying new biomarker and therapeutic targets options are essential. We performed single-cell RNA sequencing (scRNA-seq) of 6 paired primary and adjacent LUAD tissues, and integrative omics analysis of the scRNA-seq, bulk RNA-seq and whole-exome sequencing data revealed molecular subtype characteristics. Our experimental results confirm that CDC25C gene can serve as a potential marker for poor prognosis in LUAD. We investigated aberrant gene expression in diverse cell types in LUAD via the scRNA-seq data. Moreover, multi-omics clustering revealed four subgroups defined by transcriptional profile and molecular subtype 4 (MS4) with poor survival probability, and immune cell infiltration signatures revealed that MS4 tended to be the immunosuppressive subtype. Our study revealed that the CDC25C gene can be a distinct prognostic biomarker that indicates immune infiltration levels and response to immunotherapy in LUAD patients. Our experimental results concluded that CDC25C expression affects lung cancer cell invasion and migration, might play a key role in regulating Epithelial-Mesenchymal Transition (EMT) pathways. Our multi-omics result revealed a comprehensive set of molecular attributes associated with prognosis-related genes in LUAD at the cellular and tissue level. Identification of a subtype of immunosuppressive TME and prognostic signature for LUAD. We identified the cell cycle regulation gene CDC25C affects lung cancer cell invasion and migration, which can be used as a potential biomarker for LUAD.

Composition of the sputum bacterial microbiome of patients with different pathomorphological forms of non-small-cell lung cancer.

Recent studies have shown that the bacterial microbiome of the respiratory tract influences the development of lung cancer. Changes in the composition of the microbiome are observed in patients with chronic inflammatory processes. Such microbiome changes may include the occurrence of bacteria that cause oxidative stress and that are capable of causing genome damage in the cells of the host organism directly and indirectly. To date, the composition of the respiratory microbiome in patients with various histological variants of lung cancer has not been studied. In the present study, we determined the taxonomic composition of the sputum microbiome of 52 patients with squamous cell carcinoma of the lung, 52 patients with lung adenocarcinoma and 52 healthy control donors, using next-generation sequencing (NGS) on the V3-V4 region of the bacterial gene encoding 16S rRNA. The sputum microbiomes of patients with different histological types of lung cancer and controls did not show significant differences in terms of the species richness index (Shannon); however, the patients differed from the controls in terms of evenness index (Pielou). The structures of bacterial communities (beta diversity) in the adenocarcinoma and squamous cell carcinoma groups were also similar; however, when analyzed according to the matrix constructed by the Bray-Curtis method, there were differences between patients with squamous cell carcinoma and healthy subjects, but not between those with adenocarcinoma and controls. Using the LEFse method it was possible to identify an increase in the content of Bacillota (Streptococcus and Bacillus) and Actinomycetota (Rothia) in the sputum of patients with squamous cell carcinoma when compared with samples from patients with adenocarcinoma. There were no differences in the content of bacteria between the samples of patients with adenocarcinoma and the control ones. The content of representatives of the genera Streptococcus, Bacillus, Peptostreptococcus (phylum Bacillota), Prevotella, Macellibacteroides (phylum Bacteroidota), Rothia (phylum Actinomycetota) and Actinobacillus (phylum Pseudomonadota) was increased in the microbiome of sputum samples from patients with squamous cell carcinoma, compared with the control. Thus, the sputum bacterial microbiome of patients with different histological types of non-small-cell lung cancer has significant differences. Further research should be devoted to the search for microbiome biomarkers of lung cancer at the level of bacterial species using whole-genome sequencing.

CT Imaging Patterns in Major Histological Types of Lung Cancer.

Lung cancer ranks as the second most prevalent cancer globally and is the primary contributor to neoplastic-related deaths. The approach to its treatment relies on both tumour staging and histological type determination. Data indicate that the prognosis of lung cancer is strongly linked to its clinical stage, underscoring the importance of early diagnosis in enhancing patient outcomes. Consequently, the choice of an appropriate diagnostic method holds significant importance in elevating both the early detection rate and prognosis of lung cancer. This paper aims to assess computer tomography features specific to the most common lung cancer types (adenocarcinoma, squamous cell carcinomas and small cell lung cancer). Data were collected retrospectively from CT scans of 58 patients pathologically diagnosed with lung cancer. The following CT features were evaluated and recorded for each case: location, margins, structure, lymph node involvement, cavitation, vascular bundle-thickening, bronchial obstruction, and pleural involvement. Squamous cell carcinoma (SQCC) and small cell lung cancer (SCLC) showed a higher incidence of central location, while adenocarcinoma (ADC) showed a significant predilection for a peripheral location. Internal cavitation was mostly observed in SQCC, and a solid structure was observed in almost all cases of ADC. These features can provide information about the prognosis of the patient, considering that NSCLCs are more frequent but tend to demonstrate positive results for targetable driver mutations, such as EGFR, thereby increasing the overall survival. In addition, SCLC presents with early distant spreads, which limits the opportunity to investigate the evolution of tumorigenesis and gene alterations at early stages but can have a rapidly positively response to chemotherapy. The location of the lung cancer exhibits distinct forecasts, with several studies suggesting that peripheral lung tumours offer a more favourable prognosis. Cavity formation appears correlate with a poorer prognosis. Histopathological analysis is the gold standard for diagnosing the type of lung cancer; however, using CT scanning for the purpose of a rough, but fast, preliminary diagnosis has the potential to shorten the waiting time for treatment by helping clinicians and patients to know more about the diagnosis and prognosis.

Lung cancer tumor markers in serous effusions and other body fluids.

From its onset and during its progression, lung cancer may affect various extrapulmonary structures. These include the serous membranes, the pleura and pericardium, and less frequently the central nervous system, with leptomeningeal involvement. In these cases, fluid accumulates in the serous membranes which may contain substances secreted by the tumor. Measuring the concentrations of these substances can provide useful information for elucidating the origin of the fluid accumulation, either in pleural and pericardial effusions or in cerebrospinal fluid. This paper describes the histological types of lung cancer that most frequently affect the serosa and leptomeninges. It also reviews the literature on tumor markers in different fluids and makes recommendations for their interpretation.

The International Association for the Study of Lung Cancer (IASLC) Staging Project for Lung Cancer: Recommendation to Introduce Spread Through Air Spaces as a Histologic Descriptor in the Ninth Edition of the TNM Classification of Lung Cancer. Analysis of 4061 Pathologic Stage I NSCLC

IntroductionSpread through air spaces (STAS) consists of lung cancer tumor cells that are identified beyond the edge of the main tumor in the surrounding alveolar parenchyma. It has been reported by meta-analyses to be an independent prognostic factor in the major histologic types of lung cancer, but its role in lung cancer staging is not established. MethodsTo assess the clinical importance of STAS in lung cancer staging, we evaluated 4061 surgically resected pathologic stage I R0 NSCLC collected from around the world in the International Association for the Study of Lung Cancer database. We focused on whether STAS could be a useful additional histologic descriptor to supplement the existing ones of visceral pleural invasion (VPI) and lymphovascular invasion (LVI). ResultsSTAS was found in 930 of 4061 of the pathologic stage I NSCLC (22.9%). Patients with tumors exhibiting STAS had a significantly worse recurrence-free and overall survival in both univariate and multivariable analyses involving cohorts consisting of all NSCLC, specific histologic types (adenocarcinoma and other NSCLC), and extent of resection (lobar and sublobar). Interestingly, STAS was independent of VPI in all of these analyses. ConclusionsThese data support our recommendation to include STAS as a histologic descriptor for the Ninth Edition of the TNM Classification of Lung Cancer. Hopefully, gathering these data in the coming years will facilitate a thorough analysis to better understand the relative impact of STAS, LVI, and VPI on lung cancer staging for the Tenth Edition TNM Stage Classification.

Construction and validation of a prognostic model for stemness-related genes in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with poor overall prognosis. Early identification of high-risk patients and individualized treatment can help extend the survival time of patients. This study aimed to construct and validate a prognostic prediction least absolute shrinkage and selection operator (LASSO) model for stemness-related genes in LUAD. Firstly, LUAD RNA-sequencing data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. The tumor stemness index based on mRNA expression (mRNAsi) was calculated, and the relationship between mRNAsi and the survival prognosis as well as clinical features of LUAD patients was analyzed. Then, the weighted gene co-expression network analysis (WGCNA) method was used to screen for gene modules highly correlated with mRNAsi, and functional annotation [Gene Ontology (GO) analysis] and pathway enrichment analysis [Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis] were performed for the selected stemness-related gene module. Furthermore, prognosis-associated genes were determined from the stemness-related genes through univariate Cox analysis, and a prognostic model was constructed using LASSO analysis. Finally, a series of validations including survival curve analysis, receiver operating characteristic (ROC) curve analysis, and risk analysis were conducted for the prognostic model, and nomogram based on the risk model and various clinicopathological features were constructed. LUAD patients with high mRNAsi had a higher mortality rate than those with low mRNAsi. GO analysis showed that stemness-related genes were mainly involved in mRNA processing and extracellular matrix organization, while KEGG analysis revealed their involvement in cell cycle and PI3K-Akt signaling pathways. A prognostic model based on 12 stemness-related genes was constructed using LASSO regression. Validation of the prognostic model demonstrated its good accuracy in predicting the prognosis of LUAD patients. mRNAsi plays an important role in the occurrence and development of LUAD. This study successfully constructed a prognostic prediction LASSO model for stemness-related genes in LUAD, which can serve as a novel prognostic indicator for LUAD and may be an effective complement to the current Tumor Node Metastasis (TNM) clinical staging of LUAD.

Anoikis-related gene signature is associated with immune infiltration and predicts the prognosis of non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most common histological type of lung cancer. With the in-depth exploration of cell death manners, numerous studies found that anoikis is an important mechanism that associated with treatment. Therefore, we aimed to explore the prognostic value and treatment guidance of anoikis in NSCLC patients. In the current study, we first constructed a prognostic model based on the anoikis-related genes based on bulk RNA-sequencing and single-cell RNA-sequencing (scRNA-seq) dataset. Then, immuno-correlations of anoikis-related risk scores (ARGRS) were analyzed. In addition, HMGA1, a risky gene in ARGRS, was further explored to define its expression and immuno-correlation. Results showed that patients with higher ARGRS had worse clinical outcomes. Moreover, the five genes in the prognostic model were all highly expressed on tumor cells. Moreover, further analysis found that the ARGRS was negatively correlated with ImmuneScore, but positively with tumor purity. Besides, patients in the ARGRS-high group had lower levels of immunological characteristics, such as the immune-related signaling pathways and subpopulations. Additionally, in the immunotherapy cohorts, patients with the ARGRS-high phenotype were more resistant to immunotherapy and tended to not achieve remission after treatment. Last, HMGA1 was chosen as the representative biomarker, and analysis of the in-house cohort showed that HMGA1 was highly expressed in tumor tissues and correlated with decreased T cell infiltration. To sum up, ARGRS was correlated with a desert tumor microenvironment and identified immune-cold tumors, which can be a novel biomarker for the recognition of immunological characteristics and an immunotherapeutic response in NSCLC.