Lung Cancer-related Genes Research Articles

Preparing a Phytosome for Promoting Delivery Efficiency and Biological Activities of Methyl Jasmonate-Treated Dendropanax morbifera Adventitious Root Extract (DMARE).

(1) Background: Methyl jasmonate-treated D. morbifera adventitious root extract (MeJA-DMARE), enriched with phenolics, has enhanced bioactivities. However, phenolics possess low stability and bioavailability. Substantial evidence indicates that plant extract-phospholipid complex assemblies, known as phytosomes, represent an innovative drug delivery system. (2) Methods: The phytosome complex was created by combining MeJA-DMARE with Soy-L-α-phosphatidylcholine (PC) using three different ratios through two distinct methods (co-solvency method: A1, A2, and A3; thin-layer film method: B1, B2, and B3). (3) Results: Initial evaluation based on UV-Vis, entrapment efficiency (EE%), and loading content (LC%) indicated that B2 exhibited the highest EE% (79.98 ± 1.45) and LC% (69.17 ± 0.14). The phytosome displayed a spherical morphology with a particle size of 210 nm, a notably low polydispersity index of 0.16, and a superior zeta potential value at -25.19 mV. The synthesized phytosome exhibited superior anti-inflammatory activities by inhibiting NO and ROS production (reduced to 8.9% and 55.1% at 250 μg/mL) in RAW cells and adjusting the expression of related inflammatory cytokines; they also slowed lung tumor cell migration (only 2.3% of A549 cells migrated after treatment with phytosomes at 250 μg/mL), promoting ROS generation in A549 cell lines (123.7% compared to control) and stimulating apoptosis of lung cancer-related genes. (4) Conclusions: In conclusion, the MeJA-DMARE phytosome offers stable, economically efficient, and environmentally friendly nanoparticles with superior inflammation and lung tumor inhibition properties. Thus, the MeJA-DMARE phytosome holds promise as an applicable and favorable creation for drug delivery and lung cancer treatment.

Effect on Non-Small Cell Lung Cancer after Combination of Driver Gene Mutations and Anti-PD-1/PD-L1 Immunotherapy as Well as Chemotherapy.

We aimed to reveal the correlation between pathological indicators and PD-L1, between gene mutation status in lung cancer through clinico-pathological data and lung cancer-related gene mutation and PD-L1 expression analysis. The study was conducted in Jinhua Municipal Central Hospital, Zhejiang, China from 2017 to 2022. PD-L1 testing and targeted gene mutations detection were evaluated. The clinical characteristics of these non-small cell lung cancer (NSCLC) samples have been obtained. The groups (LUAD, n=142; LUSC, n=143) were grouped according to clinico-pathological features and PD-L1 expression (Yes/No or High/Low), and the clinico-pathological and genetic and molecular features and correlation with PD-L1 expression were compared across the above groups. Comparisons and analyses were made between different treatment schemes. Lung adenocarcinoma (LUAD, n=142) and lung squamous carcinoma (LUSC, n=143) samples were enrolled (median age: 64 years old). Pleural invasion and M staging were significantly different from PD-L1 alterations (P<0.05). The percentage of patients with PD-L1 tumor proportion score (TPS)≥50% was 36.24% and the percentage of patients with PD-L1 TPS<50% was 29.53%. The percentage of patients with PD-L1 high-expressed and treated by immunotherapy was 75.93% and 63.41% experienced Partial Response/Complete Response. The mutations ratio of EGFR, ALK, KRAS, MET, RET and TP53 were 28.86%, 1.34%, 6.04%, 0.67%, 1.34% and 0.67%, respectively. KRAS mutation was significantly different from PD-L1 alterations (P<0.01). There are individual differences in PD-L1 expression, which can also vary depending on the different clinical features. Specific molecular features correlate with differential PD-L1 expression and may influence the response to therapy.

Smoking and pathogenic germline variants in patients with lung cancer.

8040 Background: Few studies have investigated the correlation of smoking history with pathogenic germline variants (PGVs) in patients diagnosed with lung cancer. With emerging opportunities for PGVs in DNA damage-repair (DDR) genes to inform precision therapies, we investigated the prevalence of PGVs in patients with lung cancer, stratified by smoking status. Methods: Germline genetic testing (GGT) (Invitae Corp.) and insurance claims (Komodo Healthcare MapTM) data were reviewed for 14,317 patients with an ICD code for lung cancer from 2015-2023 and hereditary cancer GGT of ≥ 10 genes. PGV rates were assessed overall, in DDR genes and in lung cancer related genes. Smoking history was defined by ICD codes. Number of genes tested varied per ordering clinician preference. Clinically actionable PGVs were defined as those associated with clinical management recommendations or trial eligibility per current standard of care guidelines. Chi-square tests were used with significance set to p &lt; 0.05. Results: The cohort was predominantly female (70.9%), white (65.7%), and over half had a history of smoking (57.1%). PGVs in 73 known cancer-risk genes were identified in 1,804/14,317 (12.6%) patients. Frequencies of PGV were 12.6% (1,026/8,175) in patients with smoking history compared to 12.7% (778/6,142) in those with no reported smoking history. There was no statistically significant difference in DDR gene, TP53, or EGFR PGV rates for patients with or without smoking history (p &gt; 0.05). Mean (SD) age of lung cancer diagnosis was significantly younger for patients with a history of smoking and DDR PGVs (61 (11)) compared to those with negative results (62 (12), p = 0.005). There was no significant difference in age of diagnosis between patients with no smoking history and DDR PGVs (60 (12)) and those with negative results (59 (13), p = 0.888). PGV rates by clinician-reported ancestry: Black/African-American, 9%; Asian or Pacific Islander, 11%; Hispanic, 12%; White, 13%. Among genes with &gt; 1,000 patients tested, PGVs were most common in BRCA2 (2.2%), CHEK2 (2.0%), ATM (1.6%), SPINK1 (1.6%), and BRCA1 (1.2%). Conclusions: In 14,317 patients with lung cancer, 12.6% had PGVs. There was no significant difference in enrichment of PGVs in DDR genes when patients were stratified by reported smoking history, suggesting the enrichment of these genes is independently associated with lung cancer. The age of onset for patients with DDR gene PGVs varied with smoking history, suggesting that risk conferred by these PGVs could be additive to smoking risk. These data reinforce prior studies supporting consideration of GGT for all patients with lung cancer, independent of age or reported smoking history.

Germline NQO1c.559C&gt;T as a biomarker of genetic susceptibility to immune checkpoint blockade resistance.

8537 Background: Tobacco is the main risk factor for developing lung cancer. Yet, some heavy smokers do not develop cancer while others do at young ages. The study of cancer immunology has led to the surge of immune checkpoint blockade (ICB), which transformed the treatment landscape of cancer pts. NQO1 has been associated with extreme phenotypes of high risk for the development of tobacco-induced NSCLC and with poor survival outcomes for xerographs. Development of biomarkers for ICB has been mainly focused on tumor-related factors while genetic susceptibility of the host has been poorly explored to date and some evidence suggests that genetic dysregulation may enables immune escape. Methods: From June 2016 to January 2023, 326 NSCLC pts from two main University Hospitals of Malaga (Spain) receiving ICB were prospectively enrolled, blood samples were gathered. We selected a representative set of 60 consecutive pts for exome sequencing to characterize the germline contribution to resistance (progression within the first 6 months of treatment). PBMC DNA was extracted and prepared for exome sequencing. Raw sequencing data was processed and aligned to a reference genome using BWA. Base recalibration, germline variant calling and variant filtering was performed through GATK. Survival probabilities were estimated with the Kaplan-Meier method and compared using the log-rank test. We explored the lung cancer related genes among our results. Results: Median age at diagnosis of 64 (54-85). 76,6% were men. 44/60 (73,3%) were adenocarcinoma (ADC), PD-L1≥1% in 55% of patients, 22% shown PD-L≥50%. 78% had advanced disease at diagnosis. 65% received ICB in combination with chemotherapy. We found NQO1c.559C&gt;T in 46,6% of pts (28/60). The variation was not associated with survival outcomes in the multivariant analysis (p&gt;0.05) but with poor OS for non-ADC histology (19.7m vs 6m for mutated and WT, respectively; p&lt;0.01). In addition, we found 26 germline variants associated with OS and PFS, and 52 variants with response to ICB. The variants were missense or involved a stop gain/loss. Conclusions: Exome sequencing analysis of germline variants could be a suitable methodology to identify subrogated biomarkers of immune resistance in NSCLC patients. NQO1c.559C&gt;T might help to identify poor prognosis non-ADC pts in the ICB setting.

Clinically relevant immune subtypes based on alternative splicing landscape of immune-related genes for lung cancer advanced PPPM approach.

Alternative splicing (AS) occurs in the process of gene post-transcriptional process, which is very important for the correct synthesis and function of protein. The change of AS pattern may lead to the change of expression level or function of lung cancer-related genes, and then affect the occurrence and development of lung cancers. The specific AS pattern might be used as a biomarker for early warning and prognostic assessment of a cancer in the framework of predictive, preventive, and personalized medicine (PPPM; 3PM). AS events of immune-related genes (IRGs) were closely associated with tumor progression and immunotherapy. We hypothesize that IRG-AS events are significantly different in lung adenocarcinomas (LUADs) vs. controls or in lung squamous cell carcinomas (LUSCs) vs. controls. IRG-AS alteration profiling was identified to construct IRG-differentially expressed AS (IRG-DEAS) signature models. Study on the selective AS events of specific IRGs in lung cancer patients might be of great significance for further exploring the pathogenesis of lung cancer, realizing early detection and effective monitoring of lung cancer, finding new therapeutic targets, overcoming drug resistance, and developing more effective therapeutic strategies, and better used for the prediction, diagnosis, prevention, and personalized medicine of lung cancer. The transcriptomic, clinical, and AS data of LUADs and LUSCs were downloaded from TCGA and its SpliceSeq databases. IRG-DEAS events were identified in LUAD and LUSC, followed by their functional characteristics, and overall survival (OS) analyses. OS-related IRG-DEAS prognostic models were constructed for LUAD and LUSC with Lasso regression, which were used to classify LUADs and LUSCs into low- and high-risk score groups. Furthermore, the immune cell distribution, immune-related scores, drug sensitivity, mutation status, and GSEA/GSVA status were analyzed between low- and high-risk score groups. Also, low- and high-immunity clusters and AS factor (SF)-OS-related-AS co-expression network and verification of cell function of CELF6 were analyzed in LUAD and LUSC. Comprehensive analysis of transcriptomic, clinical, and AS data of LUADs and LUSCs identified IRG-AS events in LUAD (n = 1607) and LUSC (n = 1656), including OS-related IRG-AS events in LUAD (n = 127) and LUSC (n = 105). A total of 66 IRG-DEAS events in LUAD and 89 IRG-DEAS events in LUSC were identified compared to controls. The overlapping analysis between IRG-DEASs and OS-related IRG-AS events revealed 14 OS-related IRG-DEAS events for LUAD and 16 OS-related IRG-DEAS events for LUSC, which were used to identify and optimize a 12-OS-related-IRG-DEAS signature prognostic model for LUAD and an 11-OS-related-IRG-DEAS signature prognostic model for LUSC. These two prognostic models effectively divided LUAD or LUSC samples into low- and high-risk score groups that were closely associated with OS, clinical characteristics, and tumor immune microenvironment, with significant gene sets and pathways enriched in the two groups. Moreover, weighted gene co-expression network (WGCNA) and nonnegative matrix factorization method (NMF) analyses identified four OS-relevant subtypes of LUAD and six OS-relevant subtypes of LUSC, and ssGSEA identified five immunity-relevant subtypes of LUAD and five immunity-relevant subtypes of LUSC. Interestingly, splicing factors-OS-related-AS network revealed hub molecule CELF6 was significantly related to the malignant phenotype in lung cancer cells. This study established two reliable IRG-DEAS signature prognostic models and constructed interesting splicing factor-splicing event networks in LUAD and LUSC, which can be used to construct clinically relevant immune subtypes, patient stratification, prognostic prediction, and personalized medical services in the PPPM practice. The online version contains supplementary material available at 10.1007/s13167-024-00366-4.

Abstract 748: Impact of oral supplementation of sulforaphane for 12 months on lung cancer-related gene expression in former smokers at high risk for lung cancer: Results from a randomized placebo-controlled phase II clinical trial

Abstract Introduction: Higher consumption of dietary sulforaphane (SFN), a phytochemical found in many cruciferous vegetables, has been shown to be associated with lower risk of lung cancer (LC). SF activates the NRF2-pathway, which initiates cellular detoxification, antioxidant, and anti-inflammatory responses. To date, no chemoprevention trial for LC has examined the impact of SFN on LC-related gene expression (GE) as an endpoint in nasal and bronchial tissue. The objective of our study was to examine whether oral intake of SF for 12 months impacts the GE of previously identified LC- and premalignant lesions (PML)-related genes in bronchial and nasal brushing samples. Methods: A randomized, placebo-controlled clinical trial (NCT03232138) was conducted in former smokers with ≥ 30 pack-years and quitting smoking for 1-10 years in Western Pennsylvania, USA. Forty-three subjects were randomly assigned to the SFN treatment (n = 21) or placebo group (n = 22) in 2018-2022. Each participant was instructed to take 4 Avmacol® or identical placebo capsules BID for 12 months. Each Avmacol® capsule contained 15 mg of glucoraphanin, which yielded a daily internal dose of 120 μmol SFN. Nasal swabs and bronchial brushings were obtained at baseline and after 12 months. Among the 37 participants who completed the study, RNA was extracted from their nasal swabs and bronchial brushings. We constructed single sample gene signature scores (GSS) using the GSVA algorithm for the following: 1) the NRF2-pathway, 2) genes associated with LC risk in bronchial biopsies, and 3) genes associated with PML. The genes in these sets were stratified by their up- or down-regulation in LC or PML. We evaluated the association between the interaction of SFN supplementation over time (pre-/post-treatment) on GSS using linear mixed models, adjusted for the fixed effects of age at baseline, RNA integrity number (RIN), packyears of smoking, and random effect of participant. Results: GE data was available for 31 participant pairs with bronchial and/or nasal samples. Within nasal tissue, SFN treatment increased both the GSSs of the NRF2-pathway (p=0.0089) and the downregulated LC-risk genes (p=0.0047), and decreased the upregulated LC-risk genes (p=0.012) over time, whereas SFN had no significant impact on GSSs of the NRF2-pathway and LC-risk genes in the bronchial tissue. No association between SFN treatment over time and the PML-related GSS was observed in nasal or bronchial tissue. Conclusion: Our initial analysis indicates that SFN treatment over 12 months impacted LC-associated GE in nasal tissue but not in bronchial tissue from former smokers. The discrepancy results may be due to small sample size and additional studies are warranted to confirm if SFN has direct impact on LC-risk related genes in bronchial tissue (NIH grant No. R01CA213123). Citation Format: Kathryn Demanelis, Avrum Spira, Yohana Kefella, Renwei Wang, Jennifer Adams-Haduch, Thomas W. Kensler, Jennifer E. Beane, David O. Wilson, Jian-Min Yuan. Impact of oral supplementation of sulforaphane for 12 months on lung cancer-related gene expression in former smokers at high risk for lung cancer: Results from a randomized placebo-controlled phase II clinical trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 748.

Abstract 2413: Mutated TP53 prevalence in EGFR-mutated advanced non-small cell lung cancer patients with brain metastases

Abstract Introduction: Approximately 50% of patients with EGFR-mutated advanced non-small cell lung cancer (NSCLC) develops brain metastases (BM), which is associated with a poor prognosis. Mutations in TP53 are associated with earlier development of resistance to EGFR tyrosine kinase inhibitors, but it is unclear whether patients who develops BM have a higher prevalence of TP53 mutations. Analyses of circulating tumor DNA (ctDNA) in blood have been established as a good alternative to tissue biopsies to assess the genomic landscape of NSCLC. In this study, we aim to analyze ctDNA from patients with advanced EGFR-mutated NSCLC to investigate the prevalence of TP53 mutations in patients with BM, and to explore whether patients with BM exhibit a distinct ctDNA profile compared to patients without. Materials and Methods: Plasma samples collected before treatment commenced from 97 of the 100 patients with EGFR-mutated advanced NSCLC enrolled in the First-line Treatment With Osimertinib in EGFR-mutated Non-small Cell Lung Cancer study (The FIOL study: NCT03804580) were analyzed. Patients were split into cohorts with (n=44) and without BM (n=53) at baseline. The cell-free DNA was isolated and sequenced with targeted next-generation sequencing with the AVENIO ctDNA Surveillance Panel (Roche) containing 197 lung cancer-related genes. Results: Mutations in ctDNA were found in 83 patients (85.6%), with 6 patients with BM having no ctDNA mutations and 8 patients without BM having no ctDNA mutations. Besides EGFR mutations, TP53 was the most frequently mutated gene, with 42 patients (43.3%) harboring TP53 mutations. There was no significant difference in the prevalence of TP53 mutations between the cohort with BM (n=23) and the cohort without (n=19), (p=0.15). There was no difference in the number of identified mutations in the two cohorts (BM: median: 2 (range: 0-6), without BM: median: 2 (range: 0-11), p=0.71). Patients with BM had a numerically lower ctDNA level (median: 45.5 mutant molecules/mL), than patients without BM (median: 75.9 mutant molecules/mL), though the difference was not statistically significant (p=0.68). Conclusion: Prevalence of TP53 mutations in plasma collected before osimertinib treatment initiation in advanced EGFR-mutated NSCLC was similar between patients with and without BM at baseline. Furthermore, there was no difference in the ctDNA profile between these two cohorts. Future experiments will clarify the impact of TP53 mutations in patients with or without BM. Citation Format: Simone Stensgaard, Inger Johanne Z. Eide, Elin Marie Stensland, Åslaug Helland, Simon Ekman, Karin H. Hansen, Saulius Cicenas, Bjørn Henning Grønberg, Peter Meldgaard, Boe S. Sørensen, Odd Terje Brustugun. Mutated TP53 prevalence in EGFR-mutated advanced non-small cell lung cancer patients with brain metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2413.

Utility of Circulating Tumor DNA Assay in Identifying Mutations and Guiding Matched Targeted Therapy in Lung Cancers.

Tumor genomic profiling has a significant impact on the selection of targeted therapy. Circulating tumor DNA (ctDNA) has emerged as a noninvasive, and reproducible assay compared with tissue biopsy. We aimed to evaluate its utility in identifying mutations and guiding targeted therapy for lung cancer. A total of 173 lung cancer patients underwent next-generation sequencing (NGS) using a targeted enrichment panel covering 20 lung cancer-related genes. The performance of the ctDNA NGS assay in identifying genetic mutations or alterations was compared with tissue biopsy and droplet digital PCR (ddPCR). The treatment response to epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapies based on the ctDNA assay results was also assessed. The ctDNA was detected in 61.85% of patients. Tissue mutations were detected in paired ctDNA in 38.57% of cases, while ctDNA mutations were detected in paired tissues in 89.1% of cases. The ctDNA increased the number of advanced non-small cell lung cancer (NSCLC) patients who received NCCN-recommended genetic testing by 12%. The concordance between ddPCR and ctDNA was relatively high reaching 99.43%. EGFR T790M/C797S c.G2390C and EGFR T790M/C797S c.T2389A were detected in tissue and ctDNA, respectively, in patient 01015. Moreover, ctDNA assay identified the EGFR T790M mutation, which was missed by tissue biopsy in patient 01149, who developed drug resistance after 1 year of EGFR-TKI therapy. Of the 17 patients who received EGFR-TKI targeted therapies based on the ctDNA NGS results, 12 patients achieved a partial response and two patients had stable disease. The results demonstrated that the ctDNA assay could partially overcome tumor heterogeneity in detecting mutations and provide complementary information on tumor genomic profiles. Moreover, the presence of EGFR mutations in ctDNA could offer valuable guidance for selecting appropriate EGFR-TKI treatment for advanced lung cancer patients. However, it is important to note that the ctDNA NGS assay has certain limitations in fully identifying all genomic alterations present in the tumor.

Different gene alterations in patients with non-small-cell lung cancer between the eastern and southern China

Geographical differences are conspicuous in lung cancer, and the distinct molecular features of lung tumor between Western patients and Asian patients have been demonstrated. However, the etiology of non-small-cell lung cancer (NSCLC) and the distribution of associated molecular aberrations in China have not been fully elucidated. The mutational profiles of 12 lung cancer-related genes were investigated in 85 patients from eastern China and 88 patients from southern China who had been histologically confirmed NSCLC. Overall, 93.6% (162/173) of tumor samples harbored at least one somatic alteration. The most frequently mutated genes were TP53 (56.1%), EGFR (50.3%), and KRAS (14.5%). We found that EGFR mutated much more frequently (60.0% vs 40.9%, P = 0.012) and TP53 mutations had significantly lower incidence (47.1% vs 64.8%, P = 0.019) in eastern cohort than that in southern cohort. Mutational signature analysis revealed a region-related mutagenesis mechanism characterized by a high prevalence of C to T transitions mainly occurring at CpG dinucleotides in southern patients. This study reveals the difference in the mutational features between NSCLC patients in eastern and southern China. The distinct patterns of gene mutation could provide clues for the mechanism of carcinogenesis of lung cancer, offering opportunities to stratify patients into optimal treatment plans based on genomic profiles.

High-Throughput Microfluidic Production of Droplets and Hydrogel Microspheres through Monolithically Integrated Microchannel Plates.

In this paper, we present a highly effective microfluidic emulsion system using an integrated microchannel plate (MCP), a porous glass membrane that is readily available and densely packs millions of through-microchannels, for high-throughput production of monodisperse droplets. The physical controls of droplet formation, including viscosity, flow rate, and pore size, have been extensively explored for optimum emulsification conditions. The performance of the device has been validated where monodisperse droplets with a narrow coefficient of variance (<5%) can be achieved at a dispersed phase flux of 3 mL h-1 from a piece of 4 × 4 mm2 MCP. The average droplet size is two times the nominal membrane pore diameter and thus can be easily controlled by choosing the appropriate membrane type. The preparation of hydrogel microspheres has also been demonstrated with a high throughput of 1.5 × 106 particles min-1. These microspheres with a uniform size range and rough surface morphology provide suitable bioenvironments and serve as ideal carriers for cell culture. Mouse fibroblasts are shown to be cultured on these 3D scaffolds with an average cell viability of over 96%. The cell attachment rate can reach up to 112 ± 7% in 24 h and the proliferation ability increases with the number of culture days. Furthermore, the device has been applied in the droplet digital polymerase chain reaction for absolute quantification of lung cancer-related PLAU genes. The detection limit achieved was noted to be 0.5 copies/μL with a dynamic range of 105 ranging from 1 × 102 to 1 × 106 copies/μL. Given the easy fabrication, robust performance, and simple operation, the emulsion system sets the stage for the laboratory's droplet-based assays and applications in tissue engineering.

EGFR co-mutation is associated with the risk of recurrence in invasive lung adenocarcinoma with the micropapillary component

BackgroundInvasive lung adenocarcinoma (LUAD) patients with the micropapillary (MPP) component tend to have extremely poor prognosis. To optimize clinical outcomes, a better understanding of specific concurrent gene alterations and their impact on the prognosis of patients with the MPP component is necessary. MethodA total of 621 Chinese patients with surgically resected invasive LUAD who underwent genetic testing for lung cancer were enrolled in this retrospective study. The genomic profiling of major lung cancer-related genes based on next-generation sequencing (NGS) was carried out on formalin-fixed paraffin-embedded tumor samples. ResultAmong 621 patients with invasive LUAD, 154 (24.8%, 154/621) had the MPP component. We found that PIK3CA (4.5% vs 1.3%), KRAS (9.1% vs 4.7%), and ROS1 (2.6% vs 0.4%) were more frequent in patients with the MPP component than those without the MPP component (P < 0.05). The co-mutation occurred in 66 patients (10.6%, 66/621), of which 19 patients with the MPP component. Most of them were EGFR co-mutations (89.5%, 17/19), including EGFR and PIK3CA, EGFR and ERBB2, and other types. Patients with the MPP component who harbored EGFR co-mutations showed significantly worse recurrence-free survival (RFS) than single EGFR mutation (median RFS 20.1 vs 30.5 months; hazard ratio [HR]: 8.008; 95% confidence interval [CI]: 1.322–48.508). ConclusionsPatients with the MPP component harbored the co-mutation of driver genes had a higher risk of recurrence after surgery, especially in patients with EGFR co-mutation. EGFR co-mutation was a significant prognostic factor for RFS in patients with the MPP component.

Miniature Optical Fiber DNA Hybridization Sensor With Temperature Compensation Using a Gold Nanofilm-Coated Optical Fiber

DNA hybridization method is one of the most important techniques for detecting new disease genes. However, temperature cross-sensitivity is ubiquitously found in the DNA hybridization process, which may cause DNA damage and even produce false positives. An optical DNA hybridization sensor with temperature compensation based on dual surface plasmon resonance (SPR) effect by using a gold nanofilm coating optical fiber was proposed and demonstrated. Two parameters of DNA and temperature detection were realized by different functional modifications of the gold nanofilm. And a matrix equation was employed to analyze the relationship between two variables. Lung cancer-related genes exon-20 gene fragment was successfully detected in our work. From the theoretical and experimental results, the DNA detection limit was 9 nmol/L, and the temperature sensitivity reaches -1.74 nm/°C. The designed sensor could detect DNA with low concentration and measure temperature at the same time. The proposed sensor has the potential to be applied in disease marker gene detection with temperature compensation.

Identification of thioredoxin-1 as a biomarker of lung cancer and evaluation of its prognostic value based on bioinformatics analysis.

Thioredoxin-1 (TXN), a redox balance factor, plays an essential role in oxidative stress and has been shown to act as a potential contributor to various cancers. This study evaluated the role of TXN in lung cancer by bioinformatics analyses. Genes differentially expressed in lung cancer and oxidative stress related genes were obtained from The Cancer Genome Atlas, Gene Expression Omnibus and GeneCards databases. Following identification of TXN as an optimal differentially expressed gene by bioinformatics, the prognostic value of TXN in lung cancer was evaluated by univariate/multivariate Cox regression and Kaplan-Meier survival analyses, with validation by receiver operation characteristic curve analysis. The association between TXN expression and lung cancer was verified by immunohistochemical analysis of the Human Protein Atlas database, as well as by western blotting and qPCR. Cell proliferation was determined by cell counting kit-8 after changing TXN expression using lentiviral transfection. Twenty differentially expressed oxidative stress genes were identified. Differential expression analysis identified five genes (CASP3, CAT, TXN, GSR, and HSPA4) and Kaplan-Meier survival analysis identified four genes (IL-6, CYCS, TXN, and BCL2) that differed significantly in lung cancer and normal lung tissue, indicating that TXN was an optimal differentially expressed gene. Multivariate Cox regression analysis showed that T stage (T3/T4), N stage (N2/N3), curative effect (progressive diseases) and high TXN expression were associated with poor survival, although high TXN expression was poorly predictive of overall survival. TXN was highly expressed in lung cancer tissues and cells. Knockdown of TXN suppressed cell proliferation, while overexpression of TXN enhanced cell proliferation. High expression of TXN plays an important role in lung cancer development and prognosis. Because it is a prospective prognostic factor, targeting TXN may have clinical benefits in the treatment of lung cancer.

Mapping Multi-factor-mediated Chromatin Interactions to Assess Dysregulation of Lung Cancer-related Genes

Studies on the lung cancer genome are indispensable for developing a cure for lung cancer. Whole-genome resequencing, genome-wide association studies, and transcriptome sequencing have greatly improved our understanding of the cancer genome. However, dysregulation of long-range chromatin interactions in lung cancer remains poorly described. To better understand the three-dimensional (3D) genomic interaction features of the lung cancer genome, we used the A549 cell line as a model system and generated high-resolution chromatin interactions associated with RNA polymerase II (RNAPII), CCCTC-binding factor (CTCF), enhancer of zeste homolog 2 (EZH2), and histone 3 lysine 27 trimethylation (H3K27me3) using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). Analysis showed that EZH2/H3K27me3-mediated interactions further repressed target genes, either through loops or domains, and their distributions along the genome were distinct from and complementary to those associated with RNAPII. Cancer-related genes were highly enriched with chromatin interactions, and chromatin interactions specific to the A549 cell line were associated with oncogenes and tumor suppressor genes, such as additional repressive interactions on FOXO4 and promoter–promoter interactions between NF1 and RNF135. Knockout of an anchor associated with chromatin interactions reversed the dysregulation of cancer-related genes, suggesting that chromatin interactions are essential for proper expression of lung cancer-related genes. These findings demonstrate the 3D landscape and gene regulatory relationships of the lung cancer genome.

Bioinformatics analysis identifies key genes of prognostic value in lung cancer

Lung cancer is the most common human malignancy worldwide and can be divided into different types of carcinomas depending on their pathological features. Advances in medical science and technology have led to the identification of some lung cancer-related marker genes, including EGFR (epidermal growth factor receptor), BRAF (B-Raf proto-oncogene), RAS (RAS proto-oncogene, GTPase) and HER2 (human epidermal growth factor receptor 2). However, the underlying biomarker and key genes associated with different types of lung cancer are still poorly understood. In this study, we analyzed a GEO (Gene Expression Omnibus) dataset and identified 28 upregulated intersection DEGs (different expression genes) and 125 downregulated intersection DEGs among AC (adenocarcinoma), PTC (primary typical carcinoid), PLCC (primary large cell carcinoma), PLCNC (primary large cell lung carcinoma) and PSCLC (primary small cell lung carcinoma). Through PPI (protein-protein interaction) network analysis, we identified 14 genes among the DEGs, namely MFAP4 (microfibril-associated protein 4), PDZD2 (PDZ domain containing 2), FBLN1 (fibulin 1), FBLN5 (fibulin 5), EFEMP1 (EGF containing fibulin extracellular matrix protein 1), KDR (kinase insert domain receptor), S1PR1 (sphingosine-1-phosphate receptor 1), CAV1 (caveolin 1), GRK5 (G protein-coupled receptor kinase 5), EDNRA (endothelin receptor type A), EDNRB (endothelin receptor type B), CALCRL (calcitonin receptor-like receptor), PTGER4 (prostaglandin E receptor 4), and ADRB1 (adrenoceptor beta 1), which were found to be downregulated in different subtypes of lung cancer and associated with poor survival outcomes. In addition, most of the screened DEGs demonstrated good predictive ability in LUAD (lung adenocarcinoma) and LUSC (lung squamous cell carcinoma). Among them, MFAP4 was found to promote cell proliferation while also suppressing cell migration and angiogenesis. In summary, we propose MFAP4, PDZD2, FBLN1, FBLN5, EFEMP1, KDR, S1PR1, CAV1, GRK5, EDNRA, EDNRB, CALCRL, PTGER4 and ADRB1 as potential prognostic markers in lung cancer patients.

Detection of gene mutation related to non-small cell lung cancer using next-generation sequencing

To date, lung cancer is one of the most well-understood cancers in terms of molecular mechanisms, with high incidence and mortality rates in the population. Detecting lung cancer-related gene mutations plays a vital role in offering targeted therapy, thereby improving the progression-free survival and overall survival rates of patients. This study aims to identify some clinical features and factors related to non-small cell lung cancer and detect some types of gene mutations related to non-small cell lung cancer by new-generation sequencing techniques on biopsy tissue samples of patients. 40 patients with non-small cell lung cancer who were tested to detect gene mutations in biopsy tissue samples by next-generation sequencing. Results showed the majority of patients were male (70%), over 60 years old (65%), in the late stage (100%), and have not received any treatment (85%). 26/40 patients have detected mutations, in which mutations are most frequently in EGFR (27.5%) and KRAS (20.0%), followed by ALK (12.5%), BRAF (5.0%), did not detect mutations on NRAS, ROS1, and PIK3CA. The rate of mutations related to the target drug susceptibility was quite high, no resistant mutants were detected.

Predicting non-small cell lung cancer-related genes by a new network-based machine learning method.

Lung cancer is the leading cause of cancer death globally, killing 1.8 million people yearly. Over 85% of lung cancer cases are non-small cell lung cancer (NSCLC). Lung cancer running in families has shown that some genes are linked to lung cancer. Genes associated with NSCLC have been found by next-generation sequencing (NGS) and genome-wide association studies (GWAS). Many papers, however, neglected the complex information about interactions between gene pairs. Along with its high cost, GWAS analysis has an obvious drawback of false-positive results. Based on the above problem, computational techniques are used to offer researchers alternative and complementary low-cost disease–gene association findings. To help find NSCLC-related genes, we proposed a new network-based machine learning method, named deepRW, to predict genes linked to NSCLC. We first constructed a gene interaction network consisting of genes that are related and irrelevant to NSCLC disease and used deep walk and graph convolutional network (GCN) method to learn gene–disease interactions. Finally, deep neural network (DNN) was utilized as the prediction module to decide which genes are related to NSCLC. To evaluate the performance of deepRW, we ran tests with 10-fold cross-validation. The experimental results showed that our method greatly exceeded the existing methods. In addition, the effectiveness of each module in deepRW was demonstrated in comparative experiments.

Deep-LC: A Novel Deep Learning Method of Identifying Non-Small Cell Lung Cancer-Related Genes

According to statistics, lung cancer kills 1.8 million people each year and is the main cause of cancer mortality worldwide. Non-small cell lung cancer (NSCLC) accounts for over 85% of all lung cancers. Lung cancer has a strong genetic predisposition, demonstrating that the susceptibility and survival of lung cancer are related to specific genes. Genome-wide association studies (GWASs) and next-generation sequencing have been used to discover genes related to NSCLC. However, many studies ignored the intricate interaction information between gene pairs. In the paper, we proposed a novel deep learning method named Deep-LC for predicting NSCLC-related genes. First, we built a gene interaction network and used graph convolutional networks (GCNs) to extract features of genes and interactions between gene pairs. Then a simple convolutional neural network (CNN) module is used as the decoder to decide whether the gene is related to the disease. Deep-LC is an end-to-end method, and from the evaluation results, we can conclude that Deep-LC performs well in mining potential NSCLC-related genes and performs better than existing state-of-the-art methods.

Looking for the Genes Related to Lung Cancer From Nasal Epithelial Cells by Network and Pathway Analysis.

Previous studies have indicated that the airway epithelia of lung cancer-associated injury can extend to the nose and it was associated with abnormal gene expression. The aim of this study was to find the possible lung cancer-related genes from the nasal epithelium as bio-markers for lung cancer detection. WGCNA was performed to calculate the module–trait correlations of lung cancer based on the public microarray dataset, and their data were processed by statistics of RMA and t-test. Four specific modules associated with clinical features of lung cancer were constructed, including blue, brown, yellow, and light blue. Of which blue or brown module showed strong connection to genetic connectivity. From the brown module, it was found that HCK, NCF1, TLR8, EMR3, CSF2RB, and DYSF are the hub genes, and from the blue module, it was found that SPEF2, ANKFN1, HYDIN, DNAH5, C12orf55, and CCDC113 are the pivotal genes corresponding to the grade. These genes can be taken as the bio-markers to develop a noninvasive method of diagnosing early lung cancer.

To study the mechanism of Scutellariae Radix and Astragaloside in the treatment of lung cancer based on network pharmacology.

The aim of the study wasto explore the target and potential mechanism of Scutellariae Radix and Astragaloside in the treatment of lung cancer infection by network pharmacology.The target information of baicalein and flavonin was mined from CTD database and Swiss database. Genecards database, DRUGBANK database, and OMIM database were used to search for lung cancer related genes. The target protein network map (PPI) was drawn by using the STRING database analysis and Cytoscape3.7.1 software. With the help of Perl language, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene function analysis (GO) enrichment analysis were carried out by using the biological program package of R language.In total, 347 biological targets of Astragaloside and Scutellariae Radix were identified through the collection and analysis of multiple databases. In total, 1526 lung cancer targets were obtained from a multi-disease database. The “component-target” network of Astragaloside and Scutellariae Radix was constructed, and the protein interaction network (PPI) of the overlapping targets was analyzed to identify the key targets of drug-influenced diseases. In addition, KEGG pathway analysis and GO enrichment analysis were performed on the overlapping targets to explore the mechanism of Scutellariae Radix and Astragaloside in the treatment of lung cancer.Scutellariae Radix and Astragaloside have the characteristics of multi-component, multi-target and multi-pathway in the treatment of lung cancer, which provides a new idea and scientific basis for further research on the molecular mechanism of the antilung cancer effect of Scutellariae Radix and Astragaloside.