Identification of hypoxia-related gene signatures based on multi-omics analysis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and one of the malignancies with the highest incidence rate and mortality worldwide. Hypoxia is a typical feature of tumour microenvironment (TME), which affects the progression of LUAD from multiple molecular levels. However, the underlying molecular mechanisms behind LUAD hypoxia are not fully understood. In this study, we estimated the level of hypoxia by calculating a score based on 15 hypoxia genes. The hypoxia scores were relatively high in LUAD patients with poor prognosis and were bound up with tumour node metastasis (TNM) stage, tumour size, lymph node, age and gender. By comparison of high hypoxia score group and low hypoxia score group, 1820 differentially expressed genes were identified, among which up-regulated genes were mainly about cell division and proliferation while down-regulated genes were primarily involved in cilium-related biological processes. Besides, LUAD patients with high hypoxia scores had higher frequencies of gene mutations, among which TP53, TTN and MUC16 had the highest mutation rates. As for DNA methylation, 1015 differentially methylated probes-related genes were found and may play potential roles in tumour-related neurobiological processes and cell signal transduction. Finally, a prognostic model with 25 multi-omics features was constructed and showed good predictive performance. The area under curve (AUC) values of 1-, 3- and 5-year survival reached 0.863, 0.826 and 0.846, respectively. Above all, our findings are helpful in understanding the impact and molecular mechanisms of hypoxia in LUAD.

A heterogeneous tumor immune microenvironment of uncommon epidermal growth factor receptor mutant non-small cell lung cancer.

Common epidermal growth factor receptor (EGFR) mutations are usually not considered for immunotherapy in non-small cell lung cancer (NSCLC) due to poor efficacy. However, whether uncommon EGFR mutations are suitable for immunotherapy has not been thoroughly studied. Thus, we explored the tumor immune microenvironment (TME) features in uncommon EGFR mutant NSCLC. In this study, a total of 41 patients with EGFR mutations were included, the majority (85.4%) of whom were stage I. Among them, 22 patients harbored common mutations, while 19 patients presented with uncommon mutations. Compared with common mutations, uncommon mutations exhibited more infiltrating T cells and fewer M2 macrophages, upregulated expression of antigen processing and a presentation pathway. Unsupervised clustering based on the mIF profile identified two classes with heterogeneous TME in uncommon mutations. Class 1 featured the absence of PD-1+ cytotoxic T cell infiltration, and class 2 displayed a hotter TME because of the downregulated expression of hypoxia (p < 0.001), oxidative phosphorylation (p = 0.009), and transforming growth factor beta signaling (p = 0.01) pathways as well as increased expression of CTLA4 (p = 0.001) and PDCD1 (p = 0.004). The association of CTLA4 and PDCD1 with TME profiles was validated in a TCGA lung adenocarcinoma cohort with uncommon EGFR mutations. Our study reveals the distinct and heterogeneous TME features in uncommon EGFR mutant NSCLC.

Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study.

Our aim was to validate and analyze the prognostic impact of the novel International Association for the Study of Lung Cancer (IASLC) Pathology Committee grading system for invasive pulmonary adenocarcinomas (IPAs) in Chinese patients and to evaluate its utility in predicting a survival benefit from adjuvant chemotherapy (ACT). In this multicenter, retrospective, cohort study, we included 926 Chinese patients with completely resected stage I IPAs and classified them into three groups (Grade 1, n = 119; Grade 2, n = 431; Grade 3, n = 376) according to the new grading system proposed by the IASLC. Recurrence-free survival (RFS) and overall survival (OS) were estimated by the Kaplan-Meier method, and prognostic factors were assessed using univariable and multivariable Cox proportional hazards models. All included cohorts were well stratified in terms of RFS and OS by the novel grading system. Furthermore, the proposed grading system was found to be independently associated with recurrence and death in the multivariable analysis. Among patients with stage IB IPA (N = 490), the proposed grading system identified patients who could benefit from ACT but who were undergraded by the adenocarcinoma (ADC) classification. The novel grading system not only demonstrated prognostic significance in stage I IPA in a multicenter Chinese cohort but also offered clinical value for directing therapeutic decisions regarding adjuvant chemotherapy.

Designing a general method for predicting the regulatory relationships between long noncoding RNAs and protein-coding genes based on multi-omics characteristics.

MOTIVATION: Long noncoding RNA (lncRNA) has been verified to interact with other biomolecules especially protein-coding genes (PCGs), thus playing essential regulatory roles in life activities and disease development. However, the inner mechanisms of most lncRNA-PCG relationships are still unclear. Our study investigated the characteristics of true lncRNA-PCG relationships and constructed a novel predictor with machine learning algorithms. RESULTS: We obtained the 307 true lncRNA-PCG pairs from database and found that there are significant differences in multiple characteristics between true and random lncRNA-PCG sets. Besides, 3-fold cross-validation and prediction results on independent test sets show the great AUC values of LR, SVM and RF, among which RF has the best performance with average AUC 0.818 for cross-validation, 0.823 and 0.853 for two independent test sets, respectively. In case study, some candidate lncRNA-PCG relationships in colorectal cancer were found and HOTAIR-COMP interaction was specially exemplified. The proportion of the reported pairs in the predicted positive results was significantly higher than that in negative results (P < 0.05). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

LncRNA XIST Contributes to Cisplatin Resistance of Lung Cancer Cells by Promoting Cellular Glycolysis through Sponging miR-101-3p.

BACKGROUND: Non-small-cell lung carcinoma is one of the most frequently diagnosed cancers. Cisplatin (CDDP) is a currently applied standard anticancer agent for advanced lung cancers. Although effectively clinical response was achieved initially, a large fraction of lung cancer patients developed cisplatin resistance. Therefore, understanding the molecular mechanisms of chemoresistance is crucial for anti-lung cancer therapy. Long non-coding RNA (lncRNA)-X-inactive-specific transcript (XIST) has been reported to be positively associated with multiple cancers. Currently, the precise role and mechanism of XIST in cisplatin resistance of lung cancer have not been elucidated. METHODS: The expression levels of miR-101-3p and lncRNA XIST were detected by qRT-PCR. Cisplatin-resistant lung cancer cell line was established by selecting the survival cells under gradually increased cisplatin treatments. The cell proliferation was detected by MTT assay, and the cellular glucose metabolism rate was evaluated by Seahorse metabolic flux analysis and glucose uptake and lactate product assays. Glycolysis-related protein expression levels were detected by Western blot. Dual luciferase reporter was constructed to determine the lncRNA-miRNA interaction. RESULTS: Here, we report XIST is significantly upregulated in lung cancer tissues compared with normal lung tissues. In addition, cisplatin-resistant lung cancer cells displayed remarkably elevated XIST expression. We demonstrated that miR-101-3p functioned as a tumor suppressor in lung cancer and sensitized lung cancer cells to cisplatin. Bioinformatics analysis predicted miR-101-3p could be a potential target of XIST through direct binding with it as a competing endogenous RNA, which was further validated from lung tumor tissues and cell lines by luciferase assay. Intriguingly, XIST significantly promoted cellular glycolysis rate of lung cancer cells. The extracellular acidification rate, glucose uptake, and lactate product were elevated by XIST overexpression. On the contrary, miR-101-3p effectively suppressed glycolysis rate. Finally, we demonstrated silencing XIST significantly recovered miR-101-3p expression and downregulated expression of glycolysis key enzymes, a phenotype could be further overridden by miR-101-3p inhibition. CONCLUSIONS: This study reveals a new molecular mechanism for the lncRNA-XIST-promoted cisplatin resistance via sponging miR-101-3p, leading to de-repression of cellular glycolysis. Moreover, these findings warrant further in vivo investigations to study XIST as a potential target to overcome cisplatin resistance.

Knockdown of lncRNA ZFAS1-suppressed non-small cell lung cancer progression via targeting the miR-150-5p/HMGA2 signaling.

Non-small cell lung cancer (NSCLC) is the main type of lung malignancy. Early diagnosis and treatments for NSCLC are far from satisfactory due to the limited knowledge of the molecular mechanisms regarding NSCLC progression. Long noncoding RNA (lncRNA) ZNFX1 antisense RNA1 (ZFAS1) has been implicated for its functional role in the progression of malignant tumors. This study aimed to determine the ZFAS1 expression from lung cancer clinical samples and to explore the molecular mechanisms underlying ZFAS1-modulated NSCLC progression. Experimental assays revealed that clinical samples and cell lines of lung malignant tumors showed an upregulation of ZFSA1. ZFAS1 expression was markedly upregulated in the lung tissues from patients with advanced stage of this malignancy. The loss-of-function assays showed that knockdown of ZFAS1-suppressed NSCLC cell proliferative, as well as invasive potentials, increased NSCLC cell apoptotic rates in vitro and also attenuated tumor growth of NSCLC cells in the nude mice. Further experimental evidence showed that ZFAS1 inversely affected miR-150-5p expression and positively affected high-mobility group AT-hook 2 (HMGA2) expression in NSCLC cell lines. MiR-150-5p inhibition or HMGA2 overexpression counteracted the effects of ZFAS1 knockdown on NSCLC cell proliferative, invasive potentials and apoptotic rates. In light of examining the clinical lung cancer samples, miR-150-5p expression was downregulated and the HMGA2 expression was highly expressed in the lung cancer tissues compared with normal ones; the ZFAS1 expression showed a negative correlation with miR-150-5p expression but a positive correlation with HMGA2 expression in lung cancer tissues. To summarize, we, for the first time, demonstrated the inhibitory effects of ZFAS1 knockdown on NSCLC cell progression, and the results from mechanistic studies indicated that ZFAS1-mediated NSCLC progression cells via targeting miR-150-5p/HMGA2 signaling.

LncRNA FOXD3-AS1 promoted chemo-resistance of NSCLC cells via directly acting on miR-127-3p/MDM2 axis.

BACKGROUND: This study aims to investigate the mechanism underlying the high level of long non-coding RNA FOXD3-AS1 in cisplatin-resistant NSCLC cells. METHODS: Cisplatin-resistant cells were generated from A549 cells. CCK-8 were used to evaluate cell proliferation. The FOXD3-AS1, miR-127-3p, MDM2 and MRP1 mRNA expression levels were confirmed by qRT-PCR. Protein levels of MDM2 and MRP1 were determined by western blot assay. Luciferase reporter and RNA pull-down assays were evaluated the relationship between miR-127-3p and FOXD3-AS1/MDM2. In vivo tumor growth was evaluated in a xenograft nude mice model. RESULTS: FOXD3-AS1 was up-regulated in cisplatin-resistant NSCLC cells (A549/DDP and H1299/DDP cells) in comparison with their parental cell lines. Overexpression of FOXD3-AS1 promoted cisplatin-resistance in A549 and H1299 cells; while FOXD3-AS1 knockdown sensitized A549/DDP and H1299/DDP cells to cisplatin treatment. FOXD3-AS1 regulated miR-127-3p expression by acting as a competing endogenous RNA, and miR-127-3p repressed MDM2 expression via targeting the 3'UTR. MiR-127-3p overexpression and MDM2 knockdown both increased the chemo-sensitivity in A549/DDP cells; while miR-127-3p knockdown and MDM2 overexpression both promoted chemoresistance in A549 cells. Further rescue experiments revealed that miR-127-3p knockdown or MDM2 overexpression counteracted the suppressive effects of FOXD3-AS1 knockdown on chemo-resistance and MRP1 expression in A549/DDP cells. In vivo studies showed that FOXD3-AS1 knockdown potentiated the antitumor effects of cisplatin treatment. Inspection of clinical samples showed the upregulation of FOXD3-AS1 and MDM2, and down-regulation of miR-127-3p in NSCLC tissues compared to normal adjacent tissues. CONCLUSION: In conclusion, our results suggest that LncRNA FOXD3-AS1 promotes chemo-resistance of NSCLC cells via directly acting on miR-127-3p/MDM2 axis. Our findings may provide novel perspectives for the treatment of NSCLC in patients resistant to chemotherapy.

Network analysis of KLF5 targets showing the potential oncogenic role of SNHG12 in colorectal cancer.

BACKGROUND: KLF5 is a member of the Kruppel-like factor, subfamily of zinc finger proteins that are involved in cancers. KLF5 functions as a transcription factor and regulates the diverse protein-coding genes (PCGs) in colorectal cancer (CRC). However, the long non-coding RNAs (lncRNAs) regulated by KLF5 in CRC are currently unknown. METHODS: In this study, we first designed a computational pipeline to determine the PCG and lncRNA targets of KLF5 in CRC. Then we analyzed the motif pattern of the binding regions for the lncRNA targets. The regulatory co-factors of KLF5 were then searched for through bioinformatics analysis. We also constructed a regulatory network for KLF5 and annotated its functions. Finally, one of the KLF5 lncRNA targets, SNHG12, was selected to further explore its expression pattern and functions in CRC. RESULTS: We were able to identify 19 lncRNA targets of KLF5 and found that the motifs of the lncRNA binding sites were GC-enriched. Next, we pinpointed the transcription factors AR and HSF1 as the regulatory co-factors of KLF5 through bioinformatics analysis. Then, through the analysis of the regulatory network, we found that KLF5 may be involved in DNA replication, DNA repair, and the cell cycle. Furthermore, in the cell cycle module, the SNHG12 up-regulating expression pattern was verified in the CRC cell lines and tissues, associating it to CRC invasion and distal metastasis. This indicates that SNHG12 may play a critical part in CRC tumorigenesis and progression. Additionally, expression of SNHG12 was found to be down-regulated in CRC cell lines when KLF5 expression was knocked-down by siRNA; and a strong correlation was observed between the expression levels of SNHG12 and KLF5, further alluding to their regulatory relationship. CONCLUSIONS: In conclusion, the network analysis of KLF5 targets indicates that SNHG12 may be a significant lncRNA in CRC.

Cholesterol-lowering drug pitavastatin targets lung cancer and angiogenesis via suppressing prenylation-dependent Ras/Raf/MEK and PI3K/Akt/mTOR signaling.

Therapeutic agents that target both tumor cell and vascular endothelial cell may achieve additional anti-tumor efficacy, particularly in lung cancer due to the critical roles of angiogenesis during lung cancer progression and metastasis. In this work, we showed that pitavastatin, a novel cholesterol-lowering drug, potently inhibited lung cancer cells and angiogenesis. This was achieved by the induction of apoptosis and inhibition of proliferation of lung cancer cells and human lung tumor-associated endothelial cell. Pitavastatin was not only effective to chemo-sensitive but also chemo-resistant lung cancer cells. This was also consistent with the finding that pitavastatin significantly enhanced cisplatin's efficacy in lung cancer xenograft model without causing toxicity in mice. We further showed that pitavastatin inhibited lung tumor angiogenesis in vitro and in vivo through suppressing human lung tumor-associated endothelial cell migration and morphogenesis without affecting adhesion. Mechanistically, we showed that pitavastatin acted on lung cancer cells and human lung tumor-associated endothelial cell through suppressing prenylation-dependent Ras/Raf/MEK and PI3K/Akt/mTOR signaling. Our work is the first to demonstrate the inhibitory effects of pitavastatin on Ras-mediated signaling. Our findings provide pre-clinical evidence to repurpose pitavastatin for the treatment of lung cancer.

Genome-wide identification of WRKY transcription factor family members in Miscanthus sinensis (Miscanthus sinensis Anderss).

Miscanthus is an emerging sustainable bioenergy crop whose growing environment is subject to many abiotic and biological stresses. WRKY transcription factors play an important role in stress response and growth of biotic and abiotic. To clarify the distribution and expression of the WRKY genes in Miscanthus, it is necessary to classify and phylogenetically analyze the WRKY genes in Miscanthus. The v7.1 genome assembly of Miscanthus was analyzed by constructing an evolutionary tree. In Miscanthus, there are 179 WRKY genes were identified. The 179 MsWRKYs were classified into three groups with conserved gene structure and motif composition. The tissue expression profile of the WRKY genes showed that MsWRKY genes played an essential role in all growth stages of plants. At the early stage of plant development, the MsWRKY gene is mainly expressed in the rhizome of plants. In the middle stage, it is mainly expressed in the leaf. At the end stage, mainly in the stem. According to the results, it showed significant differences in the expression of the MsWRKY in different stages of Miscanthus sinensis. The results of the study contribute to a better understanding of the role of the MsWRKY gene in the growth and development of Miscanthus.

MDM2 provides TOP2 poison resistance by promoting proteolysis of TOP2ßcc in a p53-independent manner.

DNA topoisomerase II (TOP2) is an enzyme that performs a critical function in manipulating DNA topology during replication, transcription, and chromosomal compaction by forming a vital intermediate known as the TOP2-DNA cleavage complex (TOP2cc). Although the TOP2cc is often transient, stabilization can be achieved by TOP2 poisons, a family of anti-cancer chemotherapeutic agents targeting TOP2, such as etoposide (VP-16), and then induce double-strand breaks (DSBs) in cellular DNA. TOP2cc first needs to be proteolyzed before it can be processed by TDP2 for the removal of these protein adducts and to produce clean DNA ends necessary for proper repair. However, the mechanism by which TOP2ßcc is proteolyzed has not been thoroughly studied. In this study, we report that after exposure to VP-16, MDM2, a RING-type E3 ubiquitin ligase, attaches to TOP2ß and initiates polyubiquitination and proteasomal degradation. Mechanistically, during exposure to VP-16, TOP2ß binds to DNA to form TOP2ßcc, which promotes MDM2 binding and subsequent TOP2ß ubiquitination and degradation, and results in a decrease in TOP2ßcc levels. Biologically, MDM2 inactivation abrogates TOP2ß degradation, stabilizes TOP2ßcc, and subsequently increases the number of TOP2ß-concealed DSBs, resulting in the rapid death of cancer cells via the apoptotic process. Furthermore, we demonstrate the combination activity of VP-16 and RG7112, an MDM2 inhibitor, in the xenograft tumor model and in situ lung cancer mouse model. Taken together, the results of our research reveal an underlying mechanism by which MDM2 promotes cancer cell survival in the presence of TOP2 poisons by activating proteolysis of TOP2ßcc in a p53-independent manner, and provides a rationale for the combination of MDM2 inhibitors with TOP2 poisons for cancer therapy.

Global, regional, and national burden of trachea, bronchus, and lung cancer among women of reproductive age, 1990-2019.

BACKGROUND: Trachea, bronchus, and lung (TBL) cancer has demonstrated a discernible feminization and a tendency towards younger onset in recent decades. Therefore, our objective is to examine the most recent patterns in the worldwide prevalence of TBL among women of reproductive age on a global, regional, and national scale. METHODS: To assess the prevalence trends of TBL in women of reproductive age, we calculated the estimated annual percentage change (EAPC), age-standardized incidence rate (ASIR), age-standardized death rate (ASDR), and disability-adjusted life years (DALYs) for 204 countries and territories from 1990 to 2019. These calculations were based on the Global Burden of Disease (GBD) 2019 database. RESULTS: From 1990 to 2019, there was a global increase in the absolute number of incidence cases, deaths, and DALYs of TBL in women of reproductive age. However, the ASIR, ASDR, and age-standardized DALY rates were decreasing over this period, with EAPC of -0.77 (95 % confidence interval [CI]: -1.03 to -0.51), -1.08 (95 % CI: -1.34 to -0.82), and -1.10 (95 % CI: -1.36 to -0.84), respectively. This trend was observed even in regions with higher Socio-Demographic Index (SDI). East Asia consistently had the highest ASIR, ASDR, and age-standardized DALY rate, but there was a decreasing trend. Conversely, Eastern Sub-Saharan Africa displayed an increasing burden pattern. When examining countries individually, Monaco, Greenland, and Palau had the highest ASIR. Moreover, in most countries, the ASIR for TBL increased with age, particularly among women aged 35-49 years. CONCLUSIONS: Despite a global decline in ASIR, ASDR, and age-standardized DALY rates for TBL in women of reproductive age over the past three decades, there is still a troubling increase observed in low- and low-middle SDI regions. It is crucial to implement effective preventive and curative measures in these regions in order to address this concerning trend.

Predicting the risk of lung cancer using machine learning: A large study based on UK Biobank.

In response to the high incidence and poor prognosis of lung cancer, this study tends to develop a generalizable lung-cancer prediction model by using machine learning to define high-risk groups and realize the early identification and prevention of lung cancer. We included 467,888 participants from UK Biobank, using lung cancer incidence as an outcome variable, including 49 previously known high-risk factors and less studied or unstudied predictors. We developed multivariate prediction models using multiple machine learning models, namely logistic regression, naïve Bayes, random forest, and extreme gradient boosting models. The performance of the models was evaluated by calculating the areas under their receiver operating characteristic curves, Brier loss, log loss, precision, recall, and F1 scores. The Shapley additive explanations interpreter was used to visualize the models. Three were ultimately 4299 cases of lung cancer that were diagnosed in our sample. The model containing all the predictors had good predictive power, and the extreme gradient boosting model had the best performance with an area under curve of 0.998. New important predictive factors for lung cancer were also identified, namely hip circumference, waist circumference, number of cigarettes previously smoked daily, neuroticism score, age, and forced expiratory volume in 1 second. The predictive model established by incorporating novel predictive factors can be of value in the early identification of lung cancer. It may be helpful in stratifying individuals and selecting those at higher risk for inclusion in screening programs.

Identification of novel gene signature for lung adenocarcinoma by machine learning to predict immunotherapy and prognosis.

Background: Lung adenocarcinoma (LUAD) as a frequent type of lung cancer has a 5-year overall survival rate of lower than 20% among patients with advanced lung cancer. This study aims to construct a risk model to guide immunotherapy in LUAD patients effectively. Materials and methods: LUAD Bulk RNA-seq data for the construction of a model, single-cell RNA sequencing (scRNA-seq) data (GSE203360) for cell cluster analysis, and microarray data (GSE31210) for validation were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We used the Seurat R package to filter and process scRNA-seq data. Sample clustering was performed in the ConsensusClusterPlus R package. Differentially expressed genes (DEGs) between two groups were mined by the Limma R package. MCP-counter, CIBERSORT, ssGSEA, and ESTIMATE were employed to evaluate immune characteristics. Stepwise multivariate analysis, Univariate Cox analysis, and Lasso regression analysis were conducted to identify key prognostic genes and were used to construct the risk model. Key prognostic gene expressions were explored by RT-qPCR and Western blot assay. Results: A total of 27 immune cell marker genes associated with prognosis were identified for subtyping LUAD samples into clusters C3, C2, and C1. C1 had the longest overall survival and highest immune infiltration among them, followed by C2 and C3. Oncogenic pathways such as VEGF, EFGR, and MAPK were more activated in C3 compared to the other two clusters. Based on the DEGs among clusters, we confirmed seven key prognostic genes including CPA3, S100P, PTTG1, LOXL2, MELTF, PKP2, and TMPRSS11E. Two risk groups defined by the seven-gene risk model presented distinct responses to immunotherapy and chemotherapy, immune infiltration, and prognosis. The mRNA and protein level of CPA3 was decreased, while the remaining six gene levels were increased in clinical tumor tissues. Conclusion: Immune cell markers are effective in clustering LUAD samples into different subtypes, and they play important roles in regulating the immune microenvironment and cancer development. In addition, the seven-gene risk model may serve as a guide for assisting in personalized treatment in LUAD patients.

A novel PIBF1-RET gene fusion identified from a stage IA lung adenocarcinoma: A case report.

INTRODUCTION: Rearranged during transfection (RET) gene fusions occur in 0.7% to 2% in lung cancer and 1% to 2% in non-small cell lung cancer. Systemic therapies for RET fusion-positive non-small cell lung cancer consist mostly of targeted therapy with RET inhibitors such as selpercatinib and pralsetinib. To date, approximately 40 fusion partners have been reported. Herein, we report a novel progesterone immunomodulatory binding factor 1 (PIBF1)-RET gene fusion identified from a stage IA lung adenocarcinoma and was further validated by RNA sequencing analysis. PATIENT CONCERNS: A 55-year-old male smoker was found by chest computed tomography to have a solid nodule in the right lower lobe of the lung and enlarged mediastinal lymph nodes. DIAGNOSES: The patient was then diagnosed with stage IA lung adenocarcinoma (T1N0M0). INTERVENTION: The patient then underwent thoracoscopic lobectomy of the right lower lobe and mediastinal lymph node dissection. Molecular testing with a targeted panel of 8 lung cancer-associated driver genes detected a novel PIBF1-RET (P16:R12) fusion, which putatively encodes a gene in which the first 16 exons of PIBF1 was concatenated to RET exon 13 and its downstream sequence, retaining the RET kinase domain. The genomic translocation was further validated by RNA sequencing with a panel of 115 cancer-associated genes, which found no other aberrations. OUTCOMES: The patient was discharged 3 days after surgery. CONCLUSION: We report a novel PIBF1-RET fusion in early-stage lung adenocarcinoma. This finding expands the spectrum of RET fusion partners and warrants further studies in characterizing the oncogenic role of this genomic aberration and response to RET-targeted therapies.

ATM inhibitor KU60019 synergistically sensitizes lung cancer cells to topoisomerase II poisons by multiple mechanisms.

Type II topoisomerases (TOP2) poisons represent one class of the most successful and widely prescribed chemotherapeutics, which is frontline therapy for a myriad of systemic cancers and solid tumors, including lymphomas, leukemias, and lung cancer. Despite this, treatment with this class of drugs induces unwanted side effects (including cardiovascular morbidity and secondary malignancies). Additionally, the emergence of drug resistance also greatly compromises the clinical use of these drugs. To enhance therapeutic efficiency while lowering unwanted side effects, new insights into effective combination therapy are required. In this study we found that KU60019, a novel, and highly specific ATM kinase inhibitor interferes with the association of ATM with TOP2ß and stabilizes TOP2ß-DNA cleavage complex, thereby impairing the repair of TOP2 poison-induced DSBs and contributes to genome stability, leading to accelerated cell death. In H1299 as well as in A549 lung cancer cell lines, biologically, KU60019 combined with VP-16 (one of the TOP2 poisons) synergistically suppressed the growth of cells and survival and triggered a much higher apoptosis rate. In summary, we provide a proof-of-concept strategy that ATM inhibitors combined with TOP2 poison would synergistically suppresses lung cancer cell survival as well as reduce DNA damage responses, thus may lowering the possibility of cardiotoxicity and secondary malignancy linked to therapy.

Identification of EGFR mutation status in male patients with non-small-cell lung cancer: role of 18F-FDG PET/CT and serum tumor markers CYFRA21-1 and SCC-Ag.

BACKGROUND: The high incidence of epidermal growth factor receptor (EGFR) mutations is usually found in female patients with lung adenocarcinoma who have never-smoked. However, reports concerning male patients are scarce. Thus, this study aimed to explore a novel approach based on 18F-fluoro-2-deoxy-2-deoxyglucose (18F-FDG) PET/CT and serum tumor markers (STMs) to determine EGFR mutation status in male patients with non-small-cell lung cancer (NSCLC). METHODS: A total of 121 male patients with NSCLC were analyzed between October 2019 and March 2022. All patients underwent 18F-FDG PET/CT scan before treatment and monitored 8 STMs (cytokeratin 19 fragment [CYFRA21-1], squamous cell carcinoma-related antigen [SCC-Ag], carcinoembryonic antigen [CEA], neuron-specific enolase [NSE], carbohydrate antigen [CA] 50, CA125, CA72-4, and ferritin). A comparison was done between EGFR mutant and wild-type patients in terms of the maximum standardized uptake value of primary tumors (pSUVmax) and 8 STMs. We performed receiver operating characteristic (ROC) curve and multiple logistic regression analyses to determine predictors for EGFR mutation status. RESULTS: EGFR mutations were detected in 39 patients (32.2%). Compared with patients with EGFR wild-type, EGFR-mutant patients had lower concentrations of serum CYRFA21-1 (2.65 vs. 4.01, P = 0.002) and SCC-Ag (0.67 vs. 1.05, P = 0.006). No significant differences of CEA, NSE, CA 50, CA125, CA72-4 and ferritin were found between the two groups. The presence of EGFR mutations was significantly associated with low pSUVmax (< 8.75), low serum SCC-Ag (< 0.79 ng/mL) and CYFRA21-1 (< 2.91 ng/mL) concentrations. The area under ROC curve values were 0.679, 0.655, 0.685 and 0.754, respectively, for low CYFRA21-1, SCC-Ag, pSUVmax and the combination of these three factors. CONCLUSIONS: We demonstrated that low concentrations of CYFRA21-1 and SCC-Ag, as well as low pSUVmax, were associated with EGFR mutations, and that the combination of these factors resulted in a higher differentiation of EGFR mutation status in male patients with NSCLC.

Cellular Senescence in Non-Small Cell Lung Cancer.

Lung cancer has the highest mortality rate amongst all malignancies worldwide, and is the second-highest incidence of cancer in women. Non-small cell lung cancer (NSCLC) is responsible for approximately 80% of lung cancer cases. Recent studies indicate that cellular senescence may be a promising cancer biomarker. However, the regulation of cellular senescence and its underlying mechanisms in NSCLC are not yet fully understood. Here, we present a comprehensive analysis of the genes linked to cellular senescence in NSCLC. We also describe the secretory phenotype associated with NSCLC and examine its immune profile and prognostic potential. Our findings offer novel insights into the development of effective NSCLC treatments.

Penetrating chest trauma caused by a falling metallic bar: a case report.

Background: Impaling injuries to the chest are relatively rare and often lethal. Initial evaluation, resuscitation, and surgical planning can be challenging for emergency physicians and surgeons. Chest trauma can be classified as either closed or penetrating, depending on whether or not the pleural cavity is open. Penetrating objects entering chest cavity frequently make an entrance and exit and are often accompanied by visceral/vascular damage. Open thoracotomy or video-assisted thoracic surgery (VATS) are considered the first-line approaches for severe penetrating chest trauma. Case Description: A 63-year-old male patient sustained a penetrating chest trauma caused by a T-shaped metallic bar falling from a height of 16 meters above the ground. After laboratory and imaging tests, as well as pre-operative preparation, the object was pulled out from the entry site after disinfection with surgical standby. Closed chest tube drainage was promptly performed, with chest tubes inserted through the entry and exit sites. The patient was discharged on postoperative day 14 in a good condition. Regular telephone follow-ups over 3 years showed that the patient recovered well after discharge. Conclusions: For penetrating non-cardiac chest trauma patients in stable condition, it is necessary to complete an exhaustive imaging evaluation to determine the specific position of the foreign body and identify any injuries to major vessels and organs. If the condition permits, direct removal of foreign bodies is allowed, ideally under VATS control. Surgeons should evaluate the best option for each case based on the available resources.