Pan-cancer analysis combined with experiments predicts NNMT as a therapeutic target for human cancers.

The identification of effective therapeutic targets plays a pivotal role in advancing cancer treatment outcomes. We employed a comprehensive pan-cancer analysis, complemented by experimental validation, to explore the potential of Nicotinamide N-methyltransferase (NNMT) as a promising therapeutic strategy for human cancers. By analyzing large-scale transcriptomic datasets across various cancer types, we consistently observed upregulated expression of NNMT. Furthermore, elevated NNMT expression correlated with inferior overall survival in multiple cancer cohorts, underscoring its significance as a prognostic biomarker. Additionally, we investigated the relationship between NNMT expression and the tumor immune microenvironment, which plays a crucial role in regulating anti-tumor immune responses. To confirm the malignant functions of NNMT in tumor cells, we conducted a series of cell-based experiments, revealing that NNMT promotes cancer cell proliferation and invasion, indicative of its oncogenic properties. The integration of computational analysis and experimental validation in our study firmly establishes NNMT as a potential therapeutic target for human cancers. Specifically, targeting NNMT holds promise for the development of innovative and effective cancer treatments. Further investigations into NNMT's role in cancer pathogenesis could potentially pave the way for groundbreaking advancements in cancer treatment.

Response of a Novel KANK1::ALK Fusion to Alectinib in an Advanced Lung Adenocarcinoma: A Case Report.

More than 90 distinct fusion partners of ALK rearrangement have been identified. Different ALK fusions may exhibit different sensitivities to ALK tyrosine kinase inhibitors. The emergence of rare fusions poses significant challenges to targeted therapies. This study aimed to investigate the response of KANK1::ALK fusion to alectinib in an advanced lung adenocarcinoma. A novel KANK1::ALK fusion was identified by next-generation sequencing (NGS) and Ventana immunohistochemistry assessments. A 73-year-old woman who had never smoked was admitted with hemoptysis in May 2020. PET/CT revealed a nodule in the left upper lobe, with bilateral pulmonary and multiple lymph node metastases. The upper lobe nodule of the left lung was diagnosed as adenocarcinoma through bronchofiberscopy biopsy, resulting in a clinical diagnosis of stage IVA (cT1c,N3,M1a). Because the biopsy tissue was insufficient for NGS analysis, a blood-based genetic analysis was performed, revealing the presence of KRAS p.Q61R mutations. The patient received carboplatin and pemetrexed with pembrolizumab as first-line therapy, followed by maintenance therapy of pembrolizumab monotherapy. Although the tumor initially showed significant shrinkage, it unfortunately progressed further after 11 months. Subsequently, the patient was given carboplatin and pemetrexed with pembrolizumab again, but the tumor progression continued. An NGS using a rebiopsy of the left upper lobe tumor suggested a KANK1::ALK fusion. Alectinib was prescribed in January 2022, and a durable partial response was observed after 18 months. ALK rearrangements were observed in the broader spectrum of lung cancers. This study provided a potential treatment option for patients with KANK1::ALK fusions. Further studies are needed to understand the function of these fusions.

Identification and Validation of a Hypoxia and Glycolysis Prognostic Signatures in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) represents a prevalent subtype of non-small cell lung cancer with a complex molecular landscape. Dysregulated cellular energetics, notably the interplay between hypoxia and glycolysis, has emerged as a hallmark feature of LUAD tumorigenesis and progression. In this study, we aimed to identify hypoxia and glycolysis related gene signatures and construct a prognostic model to enhance the clinical management of LUAD. Methods: A gene signature associated with hypoxia and glycolysis was established within the The Cancer Genome Atlas (TCGA) cohort and subsequently validated in the GSE31210 cohort. Additionally, a nomogram was formulated to aid in predictive modeling. Subsequently, an evaluation of the tumor microenvironment and immune checkpoints expression levels was conducted to discern disparities between low risk and high risk groups. Lastly, an exploration for drugs with potential effectiveness was carried out. Results: Our analyses revealed a distinct hypoxia and glycolysis related gene signature consisting of 6 genes significantly associated with LUAD patient survival. Integration of these genes into the prognostic model demonstrated superior predictive accuracy for patient outcomes. Furthermore, we developed a user-friendly nomogram that effectively translates the model's prognostic information into a practical tool for clinical decision-making. Conclusion: This study elucidates the critical role of hypoxia and glycolysis related genes in LUAD and offers a novel prognostic model with promising clinical utility. This model has the potential to refine risk stratification and guide personalized therapeutic interventions, ultimately improving the prognosis of LUAD patients.

Establishment of a prognostic signature for patients with advanced lung squamous cell carcinoma based on tumor-infiltrating immune cells.

Background: With the advancements in the fields of science, technology, and medical therapy, there is an increasing awareness among the general public regarding tumor-infiltrating immune cells. These immune cells have a close association with the prognosis of clinical patients with lung cancer. Methods: The research used a comprehensive analysis and assessed tumor-infiltrating immune cells in advanced lung squamous cell carcinoma (LUSC) using The Cancer Genome Atlas (TCGA) database and the CIBERSORT algorithm. The research examined 22 types of tumor-infiltrating immune cells and observed notable differences in the infiltration patterns of immune cells between normal tissue and advanced LUSC. Results: Univariate Cox regression analyses revealed a positive correlation between macrophages M2 and patient prognoses, as well as potential influences on patient prognosis by natural killer (NK) cells resting, monocytes, and activated mast cells. Multivariate Cox regression models were developed, incorporating three types of immune cells. The efficacy of the model was evaluated using a receiver operating characteristic (ROC) curve. Furthermore, the research constructed a nomogram model to individually predict the mortality risk in patients with advanced LUSC. This prediction model serves as a valuable tool for clinicians, enabling them to provide effective guidance based on tumor-infiltrating immune cells for advanced LUSC patients. Conclusions: The research comprehensively analyzed and evaluated 22 types of tumor-infiltrating immune cells from advanced LUSC, revealing the correlation between immune cell infiltration and overall survival (OS) in clinical patients. Based on the nomogram of NK cells resting, monocytes, and macrophages M2, it can make specific prognostic predictions for advanced LUSC patients.

Exploring the Association Between PRC2 Genes Variants and Lung Cancer Risk in Chinese Han Population.

Background: Genetic susceptibilities play a large role in the pathogenesis of lung cancer (LC). The polycomb repressive complex 2 (PRC2) is a conserved chromatin-associated complex that represses gene expression and is crucial for proper organismal development and gene expression patterns. Despite PRC2 dysregulation has been observed in various human cancers, the relationship between PRC2 genes variants and lung cancer risk remains largely unexplored. Methods: To investigate the association between single nucleotide polymorphisms (SNPs) in PRC2 genes and the risk of developing LC, we genotyped blood genomic DNA from 270 LC patients and 452 healthy individuals of Chinese Han ethnicity using the TaqMan™ genotyping technique. Results: We found that rs17171119T>G(adjusted odds ratio (OR) = 0.662, 95% CI: 0.467-0.938, P < 0.05), rs10898459 T>C(adjusted OR = 0.615, 95% CI: 0.4-0.947, P < 0.05), and rs1136258 C>T(adjusted OR = 0.273, 95% CI: 0.186-0.401, P < 0.001) were significantly associated with a reduced risk of LC. Stratified analysis revealed a protective effect of rs17171119 in both male and female patients, specifically those with lung adenocarcinoma (LUAD). Additionally, rs1391221 showed a protective effect in both the LUAD and lung squamous cell carcinoma (LUSC) groups, while rs1136258 exhibited a protective effect in both females and males, as well as in both LUAD and LUSC groups. Furthermore, analysis of The Cancer Genome Atlas (TCGA) dataset revealed expression levels of EED and RBBP4 in both LUAD and LUSC. Conclusion: This study provides evidence that allelic variants in EZH2, EED, and RBBP4 may act as protective factors against LC development and could serve as genetic markers associated with susceptibility to LC.

LINC01798/miR-17-5p axis regulates ITGA8 and causes changes in tumor microenvironment and stemness in lung adenocarcinoma.

Integrins are closely related to the occurrence and development of tumors. ITGA8 encodes the alpha 8 subunit of the heterodimeric integrin alpha8beta1. Studies on the role of this gene in the occurrence and development of lung cancer are scarce. The examination of public databases revealed that ITGA8 expression was significantly lower in tumor tissue than that in normal tissue, especially in lung cancer, renal carcinoma, and prostate cancer. Survival analysis of patients with lung adenocarcinoma revealed that higher ITGA8 expression had better prognosis. ITGA8 was positively related to immune checkpoints and immunomodulators, whereas B cell, CD4+ T cell, CD8+ T cell, neutrophil, macrophage, and dendritic cell infiltration had the same correlation. Moreover, ITGA8 was negatively related to cancer stemness. We used an online database to predict the miRNAs and lncRNAs that regulate ITGA8 and obtained the regulatory network of ITGA8 through correlation analysis and Kaplan-Meier survival analysis. Quantitative real-time PCR and western blot analyses showed that LINC01798 regulates ITGA8 expression through miR-17-5p. Therefore, the regulatory network of ITGA8 may serve as a new therapeutic target to improve the prognosis of patients with lung cancer.

Neutrophil infiltration associated genes on the prognosis and tumor immune microenvironment of lung adenocarcinoma.

The neutrophils exhibit both anti-tumor and pro-tumor effects in cancers. The correlation between neutrophils and tumor development in lung adenocarcinoma (LUAD) is still uncertain, possibly due to a lack of specific neutrophil infiltration evaluation methods. In this study, we identified 30 hub genes that were significantly associated with neutrophil infiltration in LUAD through data mining, survival analysis, and multiple tumor-infiltrating immune cells (TICs) analysis, including TIMER, CIBERSORT, QUANTISEQ, XCELL, and MCPCOUNTER. Consensus clustering analysis showed that these 30 hub genes were correlated with clinical features in LUAD. We further developed a neutrophil scoring system based on these hub genes. The neutrophil score was significantly correlated with prognosis and tumor immune microenvironment (TIME) in LUAD. It was also positively associated with PD-L1 expression and negatively associated with tumor mutational burden (TMB). When combined with the neutrophil score, the predictive capacity of PD-L1 and TMB for prognosis was significantly improved. Thus, the 30 hub genes might play an essential role in the interaction of neutrophils and LUAD, and the neutrophil scoring system might effectually assess the infiltration of neutrophils. Furthermore, we verified the expression of these 30 genes in the LUAD tumor tissues collected from our department. We further found that overexpressed TNFAIP6 and TLR6 and downregulated P2RY13, SCARF1, DPEP2, PRAM1, CYP27A1, CFP, GPX3, and NCF1 in LUAD tissue might be potentially associated with neutrophils pro-tumor effects. The following in vitro experiments demonstrated that TNFAIP6 and TLR6 were significantly overexpressed, and P2RY13 and CYP27A1 were significantly downregulated in LUAD cell lines, compared to BEAS-2B cells. Knocking down TNFAIP6 in A549 and PC9 resulted in the upregulation of FAS, CCL3, and ICAM-1, and the downregulation of CCL2, CXCR4, and VEGF-A in neutrophils when co-culturing with the conditioned medium (CM) from LUAD cells. Knocking down TNFAIP6 in LUAD also led to an elevated early apoptosis rate of neutrophils. Therefore, overexpressed TNFAIP6 in LUAD cancer cells might lead to neutrophils "N2" polarization, which exhibited pro-tumor effects. Further research based on the genes identified in this pilot study might shed light on neutrophils' effects on LUAD in the future.

Systematic pan-cancer analysis showed that RAD51AP1 was associated with immune microenvironment, tumor stemness, and prognosis.

Although RAD51 associated protein 1 (RAD51AP1) is crucial in genome stability maintenance, it also promotes cancer development with an unclear mechanism. In this study, we collected intact expression data of RAD51AP1 from the public database, and verified it was significantly over-expressed in 33 cancer types and correlated with poor prognosis in 13 cancer types, including glioma, adrenocortical carcinoma, lung adenocarcinoma. We further authenticated that RAD51AP1 is up-regulated in several typical cancer cell lines and promotes cancer cell proliferation in vitro. Moreover, we also demonstrated that RAD51AP1 was significantly positively related to cancer stemness score mRNAsi in 27 cancer types and broadly correlated to tumor-infiltrating immune cells in various cancers in a diverse manner. It was also negatively associated with immunophenoscore (IPS) and Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) scores and positively correlated with mutant-allele tumor heterogeneity (MATH), tumor mutational burden (TMB), microsatellite instability (MSI), and PD-L1 expression in multiple cancers. The tumor stemness enhancing and tumor immune microenvironment affecting functions of RAD51AP1 might compose its carcinogenesis mechanism. Further investigations beyond the bioinformatics level should confirm these findings in each specific cancer.

Genomic analysis of TNF-related genes with prognosis and characterization of the tumor immune microenvironment in lung adenocarcinoma.

Background: The tumor necrosis factor (TNF) family plays a role in modulating cellular functions that regulate cellular differentiation, survival, apoptosis, and especially cellular immune functions. The TNF family members also play important roles in oncogenesis and progression. However, the potential role of the TNF family members in lung adenocarcinoma (LUAD) is yet to be explored. Methods: The expression of TNF-related genes (TNFRGs) in 1,093 LUAD samples was investigated using The Cancer Genome Atlas and Gene Expression Omnibus datasets. The characteristic patterns of TNFRGs in LUAD were systematically probed and three distinct molecular subtypes were identified. Furthermore, a correlation was found between the different subtypes and their clinical characteristics. A TNF scoring system was created to predict overall survival (OS) and therapeutic responses in patients with LUAD. Subsequently, the predictive accuracy of the score was verified and a nomogram was used to optimize the clinical applicability range of the TNF score. Results: A high TNF score, involving the immune and stromal scores, indicated negative odds of OS. Moreover, the TNF score was associated with immune checkpoints and chemotherapeutic drug sensitivity. Collectively, our comprehensive TNFRGs analysis of patients with LUAD revealed that TNF could be involved in forming the diverse and complex tumor microenvironment, its clinicopathological features, and its prognosis. Conclusions: A TNF-related prognostic model was constructed, and a TNF score was developed. These findings are expected to improve our knowledge regarding the function of TNFRGs in LUAD, pave a new path for assessing the disease prognosis, and assist in developing personalized therapeutic strategies for patients with LUAD.

[Association of CDH1, FANCB and APC Gene Polymorphisms 
with Lung Cancer Susceptibility in Chinese Population].

BACKGROUND: Lung cancer is the main cause of cancer-related death globally. Single nucleotide polymorphism (SNP) is one of the important factors leading to the occurrence of lung cancer, but its mechanism has not been elucidated. This study intends to investigate the relationship between SNPs of CDH1, FANCB, APC genes and lung cancer genetic susceptibility. METHODS: The case-control study design was used. We collected blood samples from 270 lung cancer cases in the Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, as well as blood samples from 445 healthy volunteers as controls, and extracted genomic DNA for genotyping using the Taqman® SNP genotyping kit. The distribution of three SNP loci of CDH1 gene rs201141645, FANCB gene rs754552650 and APC gene rs149353082 in Chinese population was analyzed. Chi-square test and Logistic regression were used to analyze the relationship between different genotypes and the risk of lung cancer. RESULTS: The distribution frequencies of AA, A/G and GG genotypes at rs754552650 of FANCB gene in the control group were 27.2%, 52.6% and 20.2%, respectively. The distribution frequencies of AA and A/G genotypes were 93.7% and 6.3% in the case group, respectively, and no GG genotype was detected. The A/G genotype of the rs754552650 locus of the FANCB gene was significantly different between the case group and the control group. Compared with the carriers of AA genotype, the individuals with FANCB rs754552650 A/G genotype had a lower risk of lung cancer (OR=0.035, 95%CI: 0.020-0.062, P<0.001). CDH1 gene rs201141645 A/C and CC genotypes only existed in the control group. In addition, only 1 sample was found to have APC rs149353082 genotype in the case group. CONCLUSIONS: In the Chinese population, the lung cancer risk of the individuals with FANCB rs754552650 A/G genotype was significantly decreased.

Necroptosis-related lncRNA in lung adenocarcinoma: A comprehensive analysis based on a prognosis model and a competing endogenous RNA network.

Background: Necroptosis, an innovative type of programmed cell death, involves the formation of necrosomes and eventually mediates necrosis. Multiple lines of evidence suggest that necroptosis plays a major role in the development of human cancer. However, the role of necroptosis in lung adenocarcinoma (LUAD) remains unclear. In this study, we aimed to construct an NRL-related prognostic model and comprehensively analyze the role of NRL in LUAD. Methods: A necroptosis-related lncRNA (NRL) signature was constructed in the training cohort and verified in the validation and all cohorts based on The Cancer Genome Atlas database. In addition, a nomogram was developed. The tumor microenvironment (TME), checkpoint, human leukocyte antigen, and m6A methylation levels were compared between low-risk and high-risk groups. Then, we identified five truly prognostic lncRNAs (AC107021.2, AC027117.1, FAM30A, FAM83A-AS1, and MED4-AS1) and constructed a ceRNA network, and four hub genes of downstream genes were identified and analyzed using immune, pan-cancer, and survival analyses. Results: The NRL signature could accurately predict the prognosis of patients with LUAD, and patients with low risk scores were identified with an obvious "hot" immune infiltration level, which was strongly associated with better prognosis. Based on the ceRNA network, we postulated that NRLs regulated the TME of patients with LUAD via cyclin-dependent kinase (CDK) family proteins. Conclusion: We constructed an NRL signature and a ceRNA network in LUAD and found that NRLs may modulate the immune microenvironment of LUAD via CDK family proteins.

Construction of a circular RNA-microRNA-messenger RNA regulatory network of hsa_circ_0043256 in lung cancer by integrated analysis.

BACKGROUND: Patients with non-small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5-year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease. METHODS: Differentially expressed genes (DEGs) were identified from three profiles of GSE101586, GSE101684 and GSE112214 using Venn diagrams. hsa_circ_0043256 were validated using quantitative real-time polymerase chain reaction (RT-qPCR). The circular RNA-microRNA-messenger RNA (circRNA-miRNA-mRNA) regulatory network was constructed with Cytoscape 3.7.0. Hub genes were identified with protein interaction (PPI) and validated with the Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) databases, and immunohistochemistry. Survival analyses were also performed using a Kaplan-Meier (KM) plotter. The effects of hsa_circ_0043256 on cell proliferation and cell cycles were evaluated by EdU staining and flow cytometry, respectively. RESULTS: hsa_circ_0043256, hsa_circ_0029426 and hsa_circ_0049271 were obtained. Following RT-qPCR validation, hsa_circ_0043256 was selected for further analysis. In addition, functional experiment results indicated that hsa_circ_0043256 could inhibit cell proliferation and cell-cycle progression of NSCLC cells in vitro. Prediction by three online databases and combining with DEGs identified from The Cancer Genome Atlas (TCGA), a network containing one circRNAs, three miRNAs, and 209 mRNAs was developed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated DEGs might be associated with lung cancer onset and progression. A PPI network based on the 209 genes was established, and five hub genes (BIRC5, SHCBP1, CCNA2, SKA3, and GINS1) were determined. Following verification of five hub genes using GEPIA database, HPA database, and immunohistochemistry. High expression of all five hub genes led to poor overall survival. CONCLUSION: Our study constructed a circRNA-miRNA-mRNA network of hsa_circ_0043256. hsa_circ_0043256 may be a potential therapeutic target for lung cancer.

Prediction Model for Lung Cancer in High-Risk Nodules Being Considered for Resection: Development and Validation in a Chinese Population.

BACKGROUND: Determining benign and malignant nodules before surgery is very difficult when managing patients with pulmonary nodules, which further makes it difficult to choose an appropriate treatment. This study aimed to develop a lung cancer risk prediction model for predicting the nature of the nodule in patients' lungs and deciding whether to perform a surgical intervention. METHODS: This retrospective study included patients with pulmonary nodules who underwent lobectomy or sublobectomy at Tianjin Medical University General Hospital between 2017 and 2020. All subjects were further divided into training and validation sets. Multivariable logistic regression models with backward selection based on the Akaike information criterion were used to identify independent predictors and develop prediction models. RESULTS: To build and validate the model, 503 and 260 malignant and benign nodules were used. Covariates predicting lung cancer in the current model included female sex, age, smoking history, nodule type (pure ground-glass and part-solid), nodule diameter, lobulation, margin (smooth, or spiculated), calcification, intranodular vascularity, pleural indentation, and carcinoembryonic antigen. The final model of this study showed excellent discrimination and calibration with a concordance index (C-index) of 0.914 (0.890-0.939). In an independent sample used for validation, the C-index for the current model was 0.876 (0.825-0.927) compared with 0.644 (0.559-0.728) and 0.681 (0.605-0.757) for the Mayo and Brock models. The decision curve analysis showed that the current model had higher discriminatory power for malignancy than the Mayo and the Brock models. CONCLUSIONS: The current model can be used in estimating the probability of lung cancer in nodules requiring surgical intervention. It may reduce unnecessary procedures for benign nodules and prompt diagnosis and treatment of malignant nodules.

Clinicopathological characteristics and molecular analysis of primary pulmonary mucoepidermoid carcinoma: Case report and literature review.

Primary pulmonary mucoepidermoid carcinoma (PMEC) is extremely rare. Herein, we report a case of a 71-year-old male patient with high-grade PMEC involving the right upper lobe that was successfully resected via lobectomy. As a result of invasion into the pleural and paratracheal lymph nodes, four cycles of adjuvant chemotherapy with paclitaxel and carboplatin were administered. There were no signs of relapse during 10 months of follow-up. Furthermore, we reviewed the literature and summarized the surgical approaches, prognostic factors, and underlying genetic mechanisms of PMEC, which will benefit clinical treatment.