Lung Cancer Gene Research Articles

Exploring effective biomarkers and potential immune related gene in small cell lung cancer

Small cell lung cancer (SCLC) is well known as a highly malignant neuroendocrine tumor. Immunotherapy combined with chemotherapy has become a standard treatment for extensive SCLC. However, since most patients quickly develop resistance and relapse, finding new therapeutic targets for SCLC is important. We obtained four microarray datasets from the Gene Expression Omnibus database and screened differentially expressed genes by two methods: batch correction and “RobustRankAggregation”. After the establishment of a protein–protein interaction network through Cytoscape, seven hub genes (AURKB, BIRC5, TOP2A, TYMS, PCNA, UBE2C, and AURKA) with high expression in SCLC samples were obtained by eight CytoHubba algorithms. The Least Absolute Shrinkage and Selection Operator regression and the Wilcoxon test were used to analyze the differences in the immune cells’ infiltration between normal and SCLC samples. The contents of seven kinds of immune cells were considered to differ significantly between SCLC samples and normal samples. A negative association was found between BIRC5 and monocytes in the correlation analysis between immune cells and the seven hub genes. The subsequent in vitro validation of experimental results showed that downregulating the expression of BIRC5 by siRNA can promote apoptotic activity of SCLC cells and inhibit their vitality, migration, and invasion. The use of BIRC5 inhibitor inhibited the vitality of SCLC cells and increased their apoptotic activity. BIRC5 may be a novel therapeutic target option for SCLC.

[Chinese expert consensus on iruplinalkib for the treatment of locally advanced or metastatic ALK-positive non-small cell lung cancer (2024 edition)].

Anaplastic lymphoma kinase (ALK) fusion gene is one of the most common driver gene in non-small cell lung cancer (NSCLC). Epidemiological data showed that ALK gene fusion is detected in 9.06% of Chinese advanced NSCLC patients. ALK-tyrosine kinase inhibitors (TKIs) have become the standard treatment for advanced NSCLC patients with ALK gene fusion. Seven different ALK-TKIs have been approved by the National Medical Products Administration (NMPA) of China, including crizotinib, ceritinib, alectinib, ensartinib, brigatinib, lorlatinib, and iruplinalkib. Iruplinalkib is a novel new-generation ALK-TKI independently developed in China. On June 27, 2023, the NMPA approved iruplinalkib for the treatment of locally advanced or metastatic ALK-positive NSCLC patients whose disease has progressed after previous treatment with crizotinib or who are intolerant to crizotinib. On January 16, 2024, the NMPA approved iruplinalkib for the first-line treatment of locally advanced or metastatic ALK-positive NSCLC patients. In order to better understand the efficacy and safety of iruplinalkib, and facilitate more rationally clinical application of iruplinalkib, the Medical Oncology Branch of China International Exchange and Promotive Association for Medical and Health Care and the Chinese Association for Clinical Oncologists co-organized experts to compile the "Chinese expert consensus on iruplinalkib for the treatment of locally advanced or metastatic ALK-positive non-small cell lung cancer (2024 edition)".

Hexavalent chromium exposure activates the non-canonical nuclear factor kappa B pathway to promote immune checkpoint protein programmed death-ligand 1 expression and lung carcinogenesis

Lung cancer is the leading cause of cancer-related death worldwide; however, the mechanism of lung carcinogenesis has not been clearly defined. Chronic exposure to hexavalent chromium [Cr(VI)], a common environmental and occupational pollutant, causes lung cancer, representing an important lung cancer etiology factor. The mechanism of how chronic Cr(VI) exposure causes lung cancer remains largely unknown. By using cell culture and mouse models and bioinformatics analyses of human lung cancer gene expression profiles, this study investigated the mechanism of Cr(VI)-induced lung carcinogenesis. A new mouse model of Cr(VI)-induced lung carcinogenesis was developed as evidenced by the findings showing that a 16-week Cr(VI) exposure (CaCrO4, 100 μg per mouse once per week) via oropharyngeal aspiration induced lung adenocarcinomas in male and female A/J mice, whereas none of the sham-exposed control mice had lung tumors. Mechanistic studies revealed that chronic Cr(VI) exposure activated the non-canonical NFκB pathway through the long non-coding RNA (lncRNA) ABHD11-AS1/deubiquitinase USP15-mediated tumor necrosis factor receptor-associated factor 3 (TRAF3) down-regulation. The non-canonical NFκB pathway activation increased the interleukin 6 (IL-6)/Janus kinase (Jak)/signal transducer and activator of transcription 3 (Stat3) signaling. The activation of the IL-6/Jak signaling axis by Cr(VI) exposure not only promoted inflammation but also stabilized the immune checkpoint molecule programmed death-ligand 1 (PD-L1) protein in the lungs, reducing T lymphocyte infiltration to the lungs. Given the well-recognized critical role of PD-L1 in inhibiting anti-tumor immunity, these findings suggested that the lncRNA ABHD11-AS1-mediated non-canonical NFκB pathway activation and PD-L1 up-regulation may play important roles in Cr(VI)-induced lung carcinogenesis.

Abstract 5646: Altered intronic polyadenylation by mutant p53 impairs transcription of DNA repair genes in lung cancer

Abstract Introduction: Changes in alternative pre-mRNA processing have been found in many cancers. Aberrant intronic polyadenylation (IPA) causes a stop of normal transcription resulting in the production of truncated mRNA isoform or lncRNA. We sought to examine the role of mutant p53 in pre-mRNA processing, especially in IPA regulation in lung cancer. Methods: We established stable cell lines transfected with mutant p53 (R273H, R175H, H179Q, C238Y, and C242F) or vector control using the NSCLC cell line H1299 with a homozygous deletion of the endogenous p53. Total RNA was used to build libraries enriched in sequences near polyadenylation sites (PASs) using the 3’mRNA-Seq REV library kit (Lexogen; Greenland, NH). Sequencing reads were mapped to the human genome (GRCh37), and PASs with ≥2 supporting reads and ≥0.05 usage in any experiment were identified. Counts for each Intronic Polyadenylation (IPA) and total reads in the terminal exon were compiled into matrices for each condition. DEXseq was applied to detect changes in the relative abundance of each exon part normalized to all exons within the gene. Gene Ontology (GO) analysis was implemented using the enrichR package. Results: We identified 32,752 IPA sites in 5,718 genes, and 26,416 distal PASs (dPASs) in the 3’UTRs of 10,298 genes. Across all five cell lines, when compared individually to the vector control, a comprehensive shift in IPA events was observed, with a concurrent decrease in dPASs. Many of IPA isoforms exhibited consistent patterns of increased or decreased abundance changes. Upon closer examination of each individual cell line, such as the p53-R273H cell line (vs. vector), significant usage changes were identified for 2,389 IPA sites, of which 1,210 were increased and 1,128 terminal exons were altered, with 650 being suppressed. At the gene level, a total of 1,183 genes had at least one significantly increased IPA isoform, a significantly decreased distal isoform, or both. GO analysis showed that these genes were highly enriched in DNA repair-related functional terms such as DNA repair, double-strand break repair, and nucleotide excision repair. The observed IPA changes in DNA-repair genes were consistently observed across the other 4 mutant lines (vs. vector). This observation was further supported by analyzing data from patients with lung adenocarcinoma (LUAD) in the TCGA cohort, where we selected samples carrying nonsense/frameshift mutations, and/or a deep deletion as the p53-null control group, and those carrying missense mutations as the p53-mutant group. Conclusions: Our study illustrated a novel role of p53 mutants in the regulation of intronic polyadenylation processing that contributes to deficient DNA repair. These observations offer a fresh perspective on the multifaceted roles of p53 in cellular homeostasis. Acknowledgment: This work was supported by NCI Cancer Center Support Grant P30CA012197 and NIH/NCI grant R03CA256100. Citation Format: Liang Liu, Elizabeth Forbes, Wei Zhang. Altered intronic polyadenylation by mutant p53 impairs transcription of DNA repair genes in lung cancer [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 5646.

Abstract 2932: Computational discovery of paralog dependencies drives target identification in lung cancer

Abstract Lung cancer is the leading cause of cancer-related death in the United States, and worldwide, with the 5-year survival rate of non-small cell lung cancer at 24%. Treatment options are limited, and even in cancers that harbor druggable biomarkers, resistance is near-universal. Identifying novel treatment strategies is essential to improve the outcomes of patients with lung cancer and provide secondary strategies for those who acquire resistance to first-line therapeutics. Identifying targeted therapies based on the genotype or expression pattern of cancers is an ongoing endeavor. In lung cancer, treatment of patients that harbor activating mutations in EGFR with specific EGFR inhibitors has improved progression-free survival rates and extended the lifespan of patients diagnosed with this aggressive cancer, demonstrating the utility of targeted therapies based genetic-based vulnerabilities, or synthetic lethal interactions. A rich source of synthetic lethal genetic interactions are paralogous genes. Paralogs result from gene duplication events through evolutionary history, and many paralogs share both sequence homology and functional redundancy. Co-targeting of some paralogous genes induces a fitness defect that is synergistic compared to individual paralog loss alone. Nearly 70% of genes in the human genome are considered paralogs, and until recent efforts from the Berger lab and others, this buffering effect has caused them to be under-represented in lethality studies. Identifying frequently-inactivated paralog genes in lung cancer will provide a platform to identify new vulnerabilities in lung cancer and other cancer types that share mutational backgrounds. To identify patterns of mutation and expression of paralog genes in lung cancer, we have accessed publicly available data sets for both cell line and patient tumor samples. Using TCGA and CCLE data sources, and a set of 1030 paralog pairs identified previously by the Berger lab as potential drug targets, we have identified paralog genes that harbor high mutational frequencies in lung cancer. Using these candidates, we next asked whether genetic inactivation or transcriptional repression of one paralog influences the essentiality of its paired gene using CERES scores generated by the Cancer Dependency Map. Preliminary results identifies several paralog pairs with distinct dependency profiles in cell lines for which expression of one paralog is lost, including MAGOH/MAGOHB and TLK1/TLK2. Further work to characterize these dependencies in relevant cell line models is ongoing. Additionally, the druggability of these targets will be tested using targeted degradation using the dTAG system. This work will uncover a new set of paralog synthetic lethality targets, and further validate the utility of targeting known synthetic lethal paralogs for the treatment of highly lethal lung cancer. Citation Format: Siobhan O'Brien, Alice H. Berger. Computational discovery of paralog dependencies drives target identification in lung cancer [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 2932.

Abstract 5826: Comprehensive analysis with single-cell RNA sequence and spatial transcriptomics unravels distinctive expression profile of apoptotic-related genes in EGFR-mutated lung cancer

Abstract Despite an initial marked response to targeted therapy with tyrosine kinase inhibitors (TKIs) in EGFR-mutated lung cancer, the duration of response is limited due to the inevitable development of acquired resistance. Anti- and pro-apoptotic genes play an important role in the survival of tumor cells. Currently, variations in these gene expression levels are not well characterized due to the complex interplay between the inducement of expression changes by EGFR-TKIs and the presence of inter- and intra-tumor heterogeneity. Here, a comprehensive analysis of apoptosis-related genes, including BCL-2 family members and the IAP family members, was conducted via single-cell RNA sequence (scRNA-seq) and spatial transcriptomics. scRNA-seq captured changes in apoptosis-related gene expression after EGFR-TKI treatment using different EGFR-mutated lung cancer cell lines. Notably, BCL2L1 expression increased, whereas MCL1 expression decreased after EGFR-TKI treatment. Other anti- and pro-apoptotic genes did not display consistent trends in the cell lines used. Additionally, scRNA-seq was carried out on samples collected from patients with EGFR-mutated lung cancer after the development of resistance to EGFR-TKIs in order to validate the results obtained from cell line data and to compare gene expression levels between tumor and non-tumor cells. BCL2L1 exhibited high expression specifically in tumor cells; in contrast, MCL1 expression was lower in tumor cells compared to non-tumor cells. Moreover, BAD and XIAP were highly expressed in a tumor-specific manner. To further corroborate the scRNA-seq findings and delineate the spatial heterogeneity in tumors, spatial transcriptomics was performed using EGFR-driven lung cancer transgenic mouse specimens in three conditions: prior to treatment, during therapeutic response after short-term treatment, and following acquired resistance to EGFR-TKIs. Spatial transcriptomics data demonstrated that an increased BCL2L1 expression was observed in tumor tissues and that MCL1 expression was significantly higher in tissue adjacent to tumors than in tumors. Finally, we demonstrated that genetic ablation of BCL2L1 and pharmacological inhibition of BCL2L1 overcame or delayed resistance to EGFR-TKIs in vitro and in vivo. Overall, BCL2L1 is particularly important for tumor cell survival during the emergence of drug tolerance and the development of acquired resistance to EGFR-TKIs. Citation Format: Motohiro Izumi, Masanori Fujii, Vivian Ho, Ikei S. Kobayashi, Susumu S. Kobayashi. Comprehensive analysis with single-cell RNA sequence and spatial transcriptomics unravels distinctive expression profile of apoptotic-related genes in EGFR-mutated lung cancer [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 5826.

Abstract 3747: Bronchial washing fluid sequencing is useful in the diagnosis of lung cancer with necrotic tumor

Abstract Lung cancers identified with low-dose CT are typically early stage without endobronchial lesions, and most require a pathological diagnosis using invasive procedures. We conducted a study analyzing bronchial washing (BW) fluid using targeted panel sequencing to evaluate its diagnostic performance. And we aimed to elucidate the characteristics of patients group in which this method could be effectively applied. We prospectively enrolled patients with an incidental lung lesion suspected of early-stage lung cancer on chest CT and no visible endobronchial lesion on bronchoscopy from June 2017 to March 2018 at two independent hospitals. Lung cancer was histologically diagnosed using a diagnostic work-up including surgical lung biopsy, percutaneous needle biopsy, endobronchial ultrasound, and other biopsies. BW was performed on each patient in the subsegmental bronchus where the lung lesion was suspected to be located. Among shared genes between the panels for each cohort, we selected 8 genes that are frequently mutated known oncogenes/tumor suppressor genes in lung cancer not to consider passenger mutations for diagnosis. In addition, several filtering criteria were considered to differentiate cancer. Since criterion d considered definitive somatic mutations [known hotspot mutations or loss of function mutations with variant allele fraction (VAF) ≥ 2%] with criterion c (≥ 2 COSMIC11 variants with VAF ≥ 1%), the sensitivity was increased without loss of precision and the sensitivity of sequencing was higher than BW cytology. In total, 164 subjects (114 with lung cancer and 50 with benign) were enrolled. Of lung cancer patients, necrosis was observed on chest CT in 44 (38.6%) patients and malignant cells were identified upon BW cytological examination in 33 (28.9%) patients. Of total, 33 (20.1%) patients had complications related to invasive diagnostic test. By the panel with the criterion d, 42 patients (25.6%) were classified as cancer. The panel showed 100% of specificity, 100% of positive predictive value for diagnosing cancer whereas it had relatively low sensitivity. Twenty patients who were classified as cancer by sequencing despite of negative cytology. In the group with necrosis, the proportion of patients with positive for sequencing only was significantly higher than that of patients with positive for cytology only. In addition, the sensitivity of BW sequencing reached 75% in patients with necrotic tumors. The prevalence of necrotic tumors was significantly higher in SQC than in ADC. The significant proportion (66.7%) of primary tumors with positive for sequencing only and located in outer area had necrosis. This study demonstrated that BW sequencing could be applied for diagnosis in patients with necrotic lung lesion suspected of early-stage lung cancer in chest CT. It would be possible to reduce the frequency of unnecessary invasive procedures and subsequent complications. Citation Format: Jun Hyeok Lim, Hyun-Tae Shin, Sunmin Park, Woo Kyung Ryu, Lucia Kim, Kyung-Hee Lee, Sung Min Ko, Seung Jae Lee, Jung Soo Kim, Jeong-Seon Ryu. Bronchial washing fluid sequencing is useful in the diagnosis of lung cancer with necrotic tumor [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 3747.

Abstract 4759: Targeting slow-cycling persisters in EGFR mutant non-small cell lung cancer

Abstract Activating mutations in the epidermal growth factor receptor (EGFR) gene in non-small cell lung cancer (NSCLC) patients are associated with clinical benefit in the metastatic and adjuvant settings when treated with EGFR inhibitors, such as osimertinib. Despite its dramatic efficacy, most patients are partial responders and refractive disease leave limited treatment options. The objective was to dissect the mechanism of osimertinib resistance in EGFR mutant NSCLC models to identify a means of re-sensitization. Imaging mass cytometric analysis of 76 NSCLC patients demonstrated EGFR expression was inversely correlated to CD105 membrane expression. CD105 is a transforming growth factor beta (TGF-β) family co-receptor that promotes bone morphogenic protein (BMP) signaling and inhibits TGF-β signaling. Significant elevation in cell surface CD105 by osimertinib was furthered by EGFR knockdown in two NSCLC lines with EGFR activating mutations. These lines were subjected to a program of increasing osimertinib concentrations to generate isogenic resistant lines. Heterogeneous drug-tolerant persister cells had significantly higher mutational load, increased CD105 cell surface expression as well as greater expression of bypass signaling factors such as ERK, PI3K, and BMP ligands compared to their parental counterparts. Single cell RNA-seq analysis of parental NSCLC revealed a small population of cells that shared elevated endothelial and pyrimidine metabolism, with a slow-cycling signature that was enriched in the osimertinib-resistant cells. Combining osimertinib with a CD105 neutralizing antibody, carotuximab, reduced the slow-cycling population and restored osimertinib sensitivity in resistant cell lines. The knockdown of CD105 had a more pronounced decrease in cell viability when combined with osimertinib. The osimertinib-resistant lines demonstrated more condensed chromatin and glycolytic state compared to the respective parental lines by ATAC-seq and Single Cell ENergetIc metabolism profiling, respectively. The addition of carotuximab reversed the chromatin and metabolic reprograming of osimertinib resistance. Carotuximab was discovered to initiate CD105 interaction with EGFR and its dominant active variant, EGFRv3. Ultimately, combination therapy of carotuximab and osimertinib resulted in significantly reduced tumor expansion compared to mice treated with either drug alone. Paradoxically, the small tumors from combination therapy had greater mitosis compared to the larger tumors of the osimertinib single agent treated mice. Inhibition of CD105 with carotuximab can overcome resistance to osimertinib and inhibit NSCLC tumor progression. This is a first-in-class pre-clinical foundation for a novel synthetic lethality treatment strategy resulting from the observation of global changes in EGFR-antagonist resistance as opposed to individual mutations identified in tumor subpopulations. Citation Format: Manish Thiruvalluvan, Sandrine Billet, Zhenqiu Liu, Joseph Lownik, Gabrielle Gonzales, Hyoyoung Kim, Anton L. Villamejor, Larry Milshteyn, Kamya Sankar, Edwin M. Posadas, Jean Lopategui, Sungyong You, Karen Reckamp, Neil A. Bhowmick. Targeting slow-cycling persisters in EGFR mutant non-small cell lung cancer [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 4759.

Identification of nomogram associated with durable clinical benefit gene for advanced non-small cell lung cancer with sensitivity to responsive to immunotherapy

BackgroundImmunotherapy has become the standard treatment for advanced non-small cell lung cancer (NSCLC). However, a subset of the most advanced NSCLC patients fails to respond adequately to Immune checkpoint inhibitors (ICIs). Developing new nomograms and integrating prognostic factors are crucial for improving the clinical predictability of NSCLC patients undergoing ICIs. MethodsClinical information and genomic data of NSCLC patients undergoing ICIs were retrieved from cBioPortal. Gene alterations associated with durable clinical benefit (DCB) were compared to those linked to no durable benefit (NDB). The Kaplan-Meier plot method was employed for survival analysis, and a novel nomogram was formulated by selecting pertinent clinical variables. ResultsFor the NSCLC patients receiving immunotherapy, three subgroups were identified based on the treatment regimen, including anti-PD-1 monotherapy, anti-PD-1 combination with anti–CTLA–4, and first-line treatment. The mutation status of TP53, PGR, PTPRT, RELN, MUC19, LRP1B, and FAT3 was found to be associated with progression-free survival (PFS). Using the clinicopathological parameters and genomic data of the patients, we developed three novel nomograms to predict the prognosis of ICI treatment in different subgroups. ConclusionOur study revealed that PGR, PTPRD, RELN, MUC19, LRP1B, and FAT3 mutation could serve as predictive biomarkers. Our systematic nomograms demonstrate significant potential in predicting the prognosis for NSCLC patients with sensitivity to different ICI treatment strategies.

Bioinformatics analysis and validation of CSRNP1 as a key prognostic gene in non-small cell lung cancer

Cysteine and serine-rich nuclear protein 1 (CSRNP1) has shown prognostic significance in various cancers, but its role in non-small cell lung cancer (NSCLC) remains elusive. We investigated CSRNP1 expression in NSCLC cases using bioinformatics tools from the GEO public repository and validated our findings through RT-qPCR in tumor and adjacent normal tissues. KEGG and GO enrichment analyses were employed to unveil the significant deregulation in signaling pathways. Additionally, clinical significance of CSRNP1 in NSCLC was determined through receiver operating curve (ROC) analysis, and its impact on survival was assessed using Kaplan-Meier analysis. To explore the functional impact of CSRNP1, we silenced its expression in NSCLC cells and assessed the effects on cell viability, migration, and invasion using MTT, Transwell, and wound-healing assays, respectively. Additionally, we investigated the influence of CSRNP1 silencing on the phosphorylation patterns of critical signaling proteins such as p53, p-Akt, and p-MDM2. Our results demonstrated significantly lower CSRNP1 expression in NSCLC tumor tissues (P < 0.01). ROC analysis indicated that NSCLC patients with high CSRNP1 expression exhibited extended overall survival and disease-free survival. Furthermore, CSRNP1 silencing promoted NSCLC cells viability, migration, and invasion (P < 0.05). Mechanistically, CSRNP1 silencing led to increased phosphorylation of AKT and MDM2, along with a concurrent reduction in p53 protein expression, suggesting its impact on NSCLC through deregulated cell cycle processes. In conclusion, our study underscores the significance of CSRNP1 in NSCLC pathogenesis, offering insights for targeted therapeutic interventions of NSCLC.

Particulate matters 2.5 induce tumor progression in lung cancer by increasing the activity of hnRNPA2B1 resulting in retarding mRNA decay of oxidative phosphorylation.

Particulate matter 2.5 (PM2.5) has been implicated in lung injury and various cancers, yet its precise mechanistic role remains elusive. To elucidate the key signaling pathways underpinning PM2.5-induced lung cancer progression, we embarked on a study examining the impact of PM2.5 both in vitro and in vivo. Lung cancer cell lines, A549 and H157, were employed for the in vitro investigations. Overexpression or knockdown techniques targeting the hnRNPA2B1 protein were implemented. Lung cancer cells were treated with a medium containing PM2.5 and subsequently prepared for in vitro evaluations. Cell growth, invasion, and migration were gauged using transwell and CCK-8 assays. Apoptosis was ascertained through flow cytometry and western blotting of pertinent proteins. Seahorse analyses probed the influence of PM2.5 on lung cancer energy metabolism. The RNA stability assay was employed to discern the impact of PM2.5 on the stability of oxidative phosphorylation-related genes in lung cancer. Our findings revealed that PM2.5 augmented cell proliferation, migration, and invasion rates. Similarly, a diminished apoptosis rate was observed in PM2.5-treated cells. Elevated expression of hnRNPA2B1 was detected in lung cancer cells exposed to PM2.5. Moreover, in cells treated with PM2.5, hnRNPA2B1 knockdown markedly curtailed cell proliferation by inducing G1-S cell cycle arrest and bolstered lung cancer cell apoptosis in vitro; it also curbed xenograft tumor growth. Mechanistically, our data suggest that PM2.5 undermines the stability of mRNA transcripts associated with oxidative phosphorylation (OXPHOS) and augments the formation of processing bodies (P-bodies), leading to an upsurge in OXPHOS levels. In conclusion, PM2.5 appears to drive lung cancer progression and migration by modulating the energy metabolism of lung cancer in a hnRNPA2B1-dependent manner.

Transcriptome profiling and metabolic pathway analysis towards reliable biomarker discovery in early-stage lung cancer.

Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-IIIrespectively. Topological analysis of the protein-protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70months were identified for hub genes during the Kaplan-Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.

Persistent Homology Identifies Pathways Associated with Hepatocellular Carcinoma from Peripheral Blood Samples

Topological data analysis (TDA) methods have recently emerged as powerful tools for uncovering intricate patterns and relationships in complex biological data, demonstrating their effectiveness in identifying key genes in breast, lung, and blood cancer. In this study, we applied a TDA technique, specifically persistent homology (PH), to identify key pathways for early detection of hepatocellular carcinoma (HCC). Recognizing the limitations of current strategies for this purpose, we meticulously used PH to analyze RNA sequencing (RNA-seq) data from peripheral blood of both HCC patients and normal controls. This approach enabled us to gain nuanced insights by detecting significant differences between control and disease sample classes. By leveraging topological descriptors crucial for capturing subtle changes between these classes, our study identified 23 noteworthy pathways, including the apelin signaling pathway, the IL-17 signaling pathway, and the p53 signaling pathway. Subsequently, we performed a comparative analysis with a classical enrichment-based pathway analysis method which revealed both shared and unique findings. Notably, while the IL-17 signaling pathway was identified by both methods, the HCC-related apelin signaling and p53 signaling pathways emerged exclusively through our topological approach. In summary, our study underscores the potential of PH to complement traditional pathway analysis approaches, potentially providing additional knowledge for the development of innovative early detection strategies of HCC from blood samples.

Emerging trends in the coexistence of primary lung Cancer and hematologic malignancy: a comprehensive analysis of clinicopathological features and genetic abnormalities

BackgroundThe incidence of multiple primary cancers (MPC), especially involving primary lung cancer (PLC) and primary hematologic malignancies (PHM), is rising. This study aims to analyze clinicopathological features, gene abnormalities, and prognostic outcomes in individuals diagnosed with PLC-PHM MPC.MethodsA retrospective analysis included 89 patients diagnosed with PLC-PHM MPC at the Respiratory or Hematology Departments of Ruijin Hospital from 2003 to 2022 (a total of 842,047 people). Next-generation sequencing (NGS) assessed lung cancer specimens, while Polymerase Chain Reaction (PCR) and NGS were used for hematologic malignancy specimens. Statistical analysis involved survival analysis and Cox regression.ResultsPLC-PHM MPC incidence surged from 1.67 per year (2011–2013) to 16.3 per year (2020–2022). The primary demographic for PLC-PHM MPC consists predominantly of elderly (average age 66 years) males (59.6%), with a high prevalence of metachronous MPC (89.9%). The prevailing histological types were lung adenocarcinoma (70.8%) in lung cancer (LC) and mature B-cell lymphomas (50.6%) in hematologic malignancies (HM). Notably, in a molecular testing cohort of 38 LC patients, 84.2% of lung cancer cases exhibited driver mutations, in which EGFR mutations frequence prevalent was 74.2%. In total group of 85 cases achieved a median overall survival (mOS) of 46.2 months, with a 5-year survival rate of 37.9% and advanced LC patients with LC gene mutations achieved a mOS was 52.6 months, with a 5-year OS rate of 30.6%. The median progression-free survival (PFS) following first-line treatment of 11 advanced patients with lung cancer-associated driver gene mutations is 26.6 months. Multivariate Cox regression revealed a favorable OS associated with surgery for LC, favorable PS score, adenocarcinoma pathology of LC, and the presence of genetic abnormalities associated with HM.ConclusionPLC-PHM MPC incidence is rising, characterized by a significant proportion of lung adenocarcinoma and a high prevalence of positive driver genes, especially in EGFR. Despite suffering from two primary tumors, the PLC-PHM MPC patients had superior data of both PFS and OS, suggesting an inherently intricate background of genetic abnormalities between the two kinds of tumors.

The integration of multi-omics analysis and machine learning for the identification of prognostic assessment and immunotherapy efficacy through aging-associated genes in lung cancer.

Recent years revealed key molecules in lung cancer research, yet their exact roles in disease onset and progression remain uncertain. Lung cancer's heterogeneity complicates prognosis prediction. This study integrates pivotal molecules to evaluate patient prognosis and immunotherapy efficacy. The WGCNA algorithm identified module genes linked to immunity. The Lasso-Cox method built a prognostic model for outcome prediction. GO and KEGG analyses explored gene pathways. ssGSEA quantified immune cell types and functions. The riskScore predicts the effectiveness of immunotherapy based on its correlation with DNA repair and immune checkpoint genes. Single-cell sequencing examined key gene expression across cell types. Using WGCNA, we identified the MEbrown module related to immunity. Lasso-Cox selected "BLK," "ITGB4," "PRKCH," and "SNAI1" for the prognostic model. MF analysis revealed enriched functions including antigen binding, GTPase regulator activity. In terms of BP, processes like immune signaling and mitotic division were enriched. CC enrichment included immunoglobulin complexes and chromosomal regions. Enriched pathways encompassed Cell cycle, Focal adhesion, Cellular senescence, and p53 signaling. ssGSEA evaluated immune cell abundance. RiskScore correlated with CTLA4 and PD1 through MMR and immune checkpoint analysis. Single-cell analysis indicated gene expression across cell types for BLK, ITGB4, PRKCH, and SNAI1. In summary, our developed prognostic model utilizing age-related genes effectively predicts lung cancer prognosis and the efficacy of immune therapy.

Prognostic, immunity, stemness, and anticancer drug sensitivity characterization of pyroptosis related genes in non-small cell lung cancer.

Pyroptosis plays a pivotal role in the tumor immune microenvironment (TME) dynamics, particularly in non-small cell lung cancer (NSCLC). The aim of our study was to explore its effects on tumor progression, TME patterns, and the efficacy of therapeutic interventions in NSCLC. Our investigation encompassed a thorough analysis of pyroptosis-related genes (PRGs), integrating immunohistochemistry (IHC) data, TME characteristics, stemness indices, and anticancer drug sensitivities. We aimed to analyze mRNA expression profiles across various cancers, constructing benchmark datasets to assess the clinical significance of PRGs in NSCLC. This included evaluating their association with clinical responses and efficacy. Notably, both our and HPA IHC data demonstrated significantly elevated GSDMD-N protein levels in lung squamous cell carcinoma (LUSC) tissues. The expression of PRGs differed significantly between tumor and normal tissues across various cancers, as validated by IHC data, and was correlated with prognosis (p < 0.05). Moreover, our investigation revealed significant differences (p < 0.05) in the expression of the PRGs among distinct TME subtypes categorized as C1 (wound healing), C3 (inflammatory), C2 (IFN-gamma dominant), C5 (immunological quiet), C4 (lymphocyte deficient), and C6 (TGF-beta dominant). Additionally, our research on anticancer drug sensitivity uncovered compelling connections between specific anticancer medications and the expression of PRGs, including GSDMD, ELANE, IL18, and CHMP4A (p < 0.05). Our study provided valuable insights into the critical role of PRGs in TME modulation, tumor stemness, and anticancer drug sensitivity across diverse cancers. Our findings illuminate the intricate relationship between pyroptosis and the TME, offering new perspectives for enhancing NSCLC treatment and prognosis.

Mutation Analysis of Epidermal Growth Factor Receptor Gene in Non-Small Cell Lung Cancer for Selection of Patients Eligible for Tyrosine Kinase Inhibitor Therapy

Introduction: Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor therapy is effective as a first-line treatment of advanced non-small-cell lung cancer (NSCLC). This research study investigated the distribution of EGFR mutations in patients diagnosed with NSCLC to assist in selecting patients who could benefit from tyrosine kinase inhibitor therapy. Materials and Methods: This cross-sectional study was conducted between July 2017 and November 2022. A real-time multiplex ​Polymerase Chain Reaction (PCR) assay supplied by Roche Diagnostics was used to examine DNA obtained from 682 tumor biopsies collected from NSCLC patients. DNA amplification was performed in a Cobas z 480 instrument for mutation analysis. The PCR assay was designed using specific primers and probes to detect 43 different mutations targeting exons 18-21. Results: Among the 682 samples, 466 (68.3%) were males, and 216 were females. The male-to-female ratio was 2.1. Twenty per cent of the male and 37% of the female samples were positive for EGFR mutations. The most common mutations were the in-frame deletion of exon 19, followed by L858R in exon 21, exon 20 insertion and S769I, exon 18 G719X. In addition, three mutations, namely del exon 19, T790M and exon 20 insertions were also detected in a patient, suggesting an actively progressive disease. Conclusions: This study showed that EGFR mutations are more common in Pakistani female patients than males. Secondly, in-frame deletion of exon 19 and exon 21 mutation L858R are prevalent in most of the NSCLC patients. The prevalence of common and rare EGFR mutations in Pakistani patients provides an opportunity for a subset of patients' chance of therapy.

Dual peptides-modified cationic liposomes for enhanced Lung cancer gene therapy by a gap junction regulating strategy

BackgroundGene therapy for lung cancer has emerged as a novel tumor-combating strategy for its superior tumor specificity, low systematical toxicity and huge clinical translation potential. Especially, the applications of microRNA shed led on effective tumor ablation by directly interfering with the crucial gene expression, making it one of the most promising gene therapy agents. However, for lung cancer therapy, the microRNA treatment confronted three bottlenecks, the poor tumor tissue penetration effect, the insufficient lung drug accumulation and unsatisfied gene transfection efficiency. To address these issues, an inhalable RGD-TAT dual peptides-modified cationic liposomes loaded with microRNA miR-34a and gap junction (GJ) regulation agent all-trans retinoic acid (ATRA) was proposed, which was further engineered into dry powder inhalers (DPIs).ResultsEquipped with a rough particle surface and appropriate aerodynamic size, the proposed RGD-TAT-CLPs/ARTA@miR-34a DPIs were expected to deposit into the deep lung and reach lung tumor lesions guided by targeting peptide RGD. Assisted by cellular transmembrane peptides TAT, the RGD-TAT-CLPs/ARTA@miR-34a was proven to be effectively internalized by cancer cells, enhancing gene transfection efficiency. Then, the GJ between tumor cells was upregulated by ARTA, facilitating the intercellular transport of miR-34a and boosting the gene expression in the deep tumor.ConclusionOverall, the proposed RGD-TAT-CLPs/ARTA@miR-34a DPIs could enhance tumor tissue penetration, elevate lung drug accumulation and boost gene transfection efficiency, breaking the three bottlenecks to enhancing tumor elimination in vitro and in vivo. We believe that the proposed RGD-TAT-CLPs/ARTA@miR-34a DPIs could serve as a promising pulmonary gene delivery platform for multiple lung local disease treatments.

A novel feature selection algorithm for identifying hub genes in lung cancer

Lung cancer, a life-threatening disease primarily affecting lung tissue, remains a significant contributor to mortality in both developed and developing nations. Accurate biomarker identification is imperative for effective cancer diagnosis and therapeutic strategies. This study introduces the Voting-Based Enhanced Binary Ebola Optimization Search Algorithm (VBEOSA), an innovative ensemble-based approach combining binary optimization and the Ebola optimization search algorithm. VBEOSA harnesses the collective power of the state-of-the-art classification models through soft voting. Moreover, our research applies VBEOSA to an extensive lung cancer gene expression dataset obtained from TCGA, following essential preprocessing steps including outlier detection and removal, data normalization, and filtration. VBEOSA aids in feature selection, leading to the discovery of key hub genes closely associated with lung cancer, validated through comprehensive protein–protein interaction analysis. Notably, our investigation reveals ten significant hub genes—ADRB2, ACTB, ARRB2, GNGT2, ADRB1, ACTG1, ACACA, ATP5A1, ADCY9, and ADRA1B—each demonstrating substantial involvement in the domain of lung cancer. Furthermore, our pathway analysis sheds light on the prominence of strategic pathways such as salivary secretion and the calcium signaling pathway, providing invaluable insights into the intricate molecular mechanisms underpinning lung cancer. We also utilize the weighted gene co-expression network analysis (WGCNA) method to identify gene modules exhibiting strong correlations with clinical attributes associated with lung cancer. Our findings underscore the efficacy of VBEOSA in feature selection and offer profound insights into the multifaceted molecular landscape of lung cancer. Finally, we are confident that this research has the potential to improve diagnostic capabilities and further enrich our understanding of the disease, thus setting the stage for future advancements in the clinical management of lung cancer. The VBEOSA source codes is publicly available at https://github.com/TEHNAN/VBEOSA-A-Novel-Feature-Selection-Algorithm-for-Identifying-hub-Genes-in-Lung-Cancer.

Integrative analyses of N6-methyladenosine-associated single-nucleotide polymorphisms (m6A-SNPs) identify tumor suppressor gene AK9 in lung cancer.

N6 -methyladenosine (m6 A) modification has been identified as one of the most important epigenetic regulation mechanisms in the development of human cancers. However, the association between m6 A-associated single-nucleotide polymorphisms (m6 A-SNPs) and lung cancer risk remains largely unknown. Here, we identified m6 A-SNPs and examined the association of these m6 A-SNPs with lung cancer risk in 13,793 lung cancer cases and 14,027 controls. In silico functional annotation was used to identify causal m6 A-SNPs and target genes. Furthermore, methylated RNA immunoprecipitation and quantitative real-time polymerase chain reaction (MeRIP-qPCR) assay was performed to assess the m6 A modification level of different genotypes of the causal SNP. In vitro assays were performed to validate the potential role of the target gene in lung cancer. A total of 8794 m6 A-SNPs were detected, among which 397 SNPs in nine susceptibility loci were associated with lung cancer risk, including six novel loci. Bioinformatics analyses indicated that rs1321328 in 6q21 was located around the m6 A modification site of AK9 and significantly reduced AK9 expression (β = -0.15, p = 2.78 × 10-8 ). Moreover, AK9 was significantly downregulated in lung cancer tissues than that in adjacent normal tissues of samples from the Cancer Genome Atlas and Nanjing Lung Cancer Cohort. MeRIP-qPCR assay suggested that C allele of rs1321328 could significantly decrease the m6 A modification level of AK9 compared with G allele. In vitro assays verified the tumor-suppressing role of AK9 in lung cancer. These findings shed light on the pathogenic mechanism of lung cancer susceptibility loci linked with m6 A modification.