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Background Prognostic biomarkers are promising targets for cancer prevention and treatment. Objective We try to filtrate survival-related genes for non-small cell lung cancer (NSCLC) via transcriptome analysis. Methods Transcriptome data and clinical information of Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), mainly subtypes of NSCLC, were obtained from The Cancer Genome Atlas (TCGA) program. Differentially expressed genes (DEGs) analyzed by DESeq2 package were regarded as candidate genes. For survival analysis, univariate and multivariate Cox regression were applied to select biomarkers for overall survival (OS) and progression-free survival (PFS), where univariate analysis was for preliminary filtration and multivariate analysis considering age, gender, TNM parameters and clinical stage was for ultimate determination. Gene ontology (GO) analysis and pathway enrichment were used for biological annotation. Results We ultimately acquired a series of genes closely related to prognosis. For LUAD, we determined 314 OS-related genes and 275 PFS-related genes, while 54 OS-related genes and 78 PFS-related genes were chosen for LUSC. The final biological analysis indicated important function of proliferative signaling in LUAD but for LUSC, only cornification process had statistical meaning. Conclusions We strictly determined prognostic genes of NSCLC, which would contribute to its carcinogenesis investigation and therapeutic methods improvement.

Immunotherapy has been used as a first-line treatment for a variety of advanced tumors, allowing remarkable progress to be made in cancer treatment. Nonetheless, only a small number of patients can benefit from immune checkpoint inhibitor monotherapy. To improve the effect of immunotherapy, the underlying mechanism of combination therapy was investigated in the context of an intact human tumor immune microenvironment using mice with a human immune system (HIS) bearing human tumors. Herein, we summarize and discuss strategies for the development and use of HIS mice models in tumor immunotherapies. Most importantly, this review proposes a method of t11umor identification and classification in HIS mice based on the tumor-infiltrating lymphocytes and PD-L1 expression, and according to this classification, we propose different combination treatment strategies that can be utilized to enhance the effect of immunotherapy. Thus, we provide effective experimental schemes for tumor immunotherapy in HIS mice models.

Transcription factor AP-2α (TFAP2A) was previously regarded as a critical regulator during embryonic development, and its mediation in carcinogenesis has received intensive attention recently. However, its role in lung adenocarcinoma (LUAD) has not been fully elucidated. Here, we tried to investigate TFAP2A expression profiling, clinical significance, biological function and molecular underpinnings in LUAD. We proved LUAD possessed universal TFAP2A high expression, indicating a pervasively poorer prognosis in multiple independent datasets. Then we found TFAP2A was not indispensable for LUAD proliferation, and exogenous overexpression even caused repression. However, we found TFAP2A could potently promote LUAD metastasis possibly by triggering epithelial–mesenchymal transition (EMT) in vitro and in vivo. Furthermore, we demonstrated TFAP2A could transactivate Pregnancy-specific glycoprotein 9 (PSG9) to enhance transforming growth factor β (TGF-β)-triggering EMT in LUAD. Meanwhile, we discovered suppressed post-transcriptional silencing of miR-16 family upon TFAP2A partly contributed to TFAP2A upregulation in LUAD. In clinical specimens, we also validated cancer-regulating effect of miR-16 family/TFAP2A/PSG9 axis, especially for lymph node metastasis of LUAD. In conclusion, we demonstrated that TFAP2A could pivotally facilitate LUAD progression, possibly through a novel pro-metastasis signaling pathway (miR-16 family/TFAP2A/PSG9/ TGF-β).

Immunotherapy is a curable treatment for certain cancers, but it is still only effective in a small subset of patients, partly because of the lack of sufficient immune cells in the tumor. It is reported that targeted lactate dehydrogenase (LDH) to reduce lactic acid production can promote the infiltration and activity of immune cells and turn tumors into hot tumors. Therefore, we constructed a humanized mouse model to evaluate the efficacy of using classical LDH inhibitor oxamate and pembrolizumab alone or in combination in non-small cell lung cancer (NSCLC). We found that both oxamate and pembrolizumab monotherapy significantly delayed tumor growth; moreover, combination therapy showed better results. Immunofluorescence analysis showed that oxamate treatment increased the infiltration of activated CD8+ T cells in the tumor, which might have enhanced the therapeutic effects of pembrolizumab. Treatment of the humanized mice with anti-CD8 abrogated the therapeutic effects of oxamate, indicating CD8+ T cells as the main force mediating the effect of oxamate. In conclusion, Our preclinical findings position that oxamate not only inhibits tumor growth at a high safe dose but also enhances the efficacy of pembrolizumab in Hu-PBMC-CDX mice. Our study also provides a preclinical model for exploring the efficacy of other immune-based combination therapies for NSCLC.

Background: Immunotherapy has dramatically changed the treatment landscape of cancer. Immunotherapies targeting the programmed death 1/programmed death ligand 1 pathway have been shown to lead to durable responses in patients with a variety of cancers. However, combination approaches are required to extend this benefit beyond a subset of patients. Studies have suggested that anti-angiogenic therapy can elicit or enhance tumor immunity response.Therefore, we hypothesised that combining immunotherapy with anti-angiogenic treatment may have a synergistic effect and may enhance the efficacy of both treatments.Methods: We evaluated the combination of bevacizumab (anti-vascular endothelial growth factor monoclonal antibody) and pembrolizumab (anti-programmed death 1 monoclonal antibody) in two mouse models of human non-small cell lung cancer cell lines (H1299 and A549). We monitored tumour growth and examined changes in the tumour vasculature, along with the frequency and phenotype of tumour-infiltrating lymphocytes.Results: The combination of bevacizumab and pembrolizumab synergistically inhibited tumour growth in vivo without overt toxicity in both cell lines. Combination therapy reprogrammed the immune microenvironment by increasing CD8+ cytotoxic T cell infiltration, thereby turning tumours with different phenotypes into inflamed (‘hot’) tumours. This is potentially mediated by vascular normalisation and endothelial cell activation, as demonstrated by a reduction in the number of microvessels and an increase in adhesion molecules.Conclusions: Taken together, our preclinical studies demonstrate that the combination of bevacizumab and pembrolizumab had a synergistic anti-tumour effect and provides a theoretical basis for translating basic research into clinical applications.

Background FBXW7 m6A modification plays an important role in lung adenocarcinoma (LUAD) progression; however, the underlying mechanisms remain unclear. Methods The correlation between FBXW7 and various genes related to m6A modification was analyzed using The Cancer Genome Atlas database. The regulatory effects of METTL3 on FBXW7 mRNA m6A modification were examined in a cell model, and the underlying mechanism was determined by methylated RNA immunoprecipitation, RNA immunoprecipitation, luciferase reporter, and mutagenesis assays. In vitro experiments were performed to further explore the biological effects of METTL3-mediated FBXW7 m6A modification on LUAD development. Results Decreased FBXW7 expression was accompanied by downregulated METTL3 expression in human LUAD tissues and was associated with a worse prognosis for LUAD in The Cancer Genome Atlas database. m6A was highly enriched in METTL3-mediated FBXW7 transcripts, and increased m6A modification in the coding sequence region increased its translation. Functionally, METTL3 overexpression or knockdown affected the apoptosis and proliferation phenotype of LUAD cells by regulating FBXW7 m6A modification and expression. Furthermore, FBXW7 overexpression in METTL3-depleted cells partially restored LUAD cell suppression in vitro and in vivo. Conclusions Our findings reveal that METTL3 positively regulates FBXW7 expression and confirm the tumor-suppressive role of m6A-modified FBXW7, thus providing insight into its epigenetic regulatory mechanisms in LUAD initiation and development.

Background Lung adenocarcinoma (LUAD) remains a crucial factor endangering human health. Gene-based clinical predictions could be of great help for cancer intervention strategies. Here, we tried to build a gene-based survival score (SS) for LUAD via analyzing multiple transcriptional datasets. Methods We first acquired differentially expressed genes between tumors and normal tissues from intersections of four LUAD datasets. Next, survival-related genes were preliminarily unscrambled by univariate Cox regression and further filtrated by LASSO regression. Then, we applied PCA to establish a comprehensive SS based on survival-related genes. Subsequently, we applied four independent LUAD datasets to evaluate prognostic prediction of SS. Moreover, we explored associations between SS and clinicopathological features. Furthermore, we assessed independent predictive value of SS by multivariate Cox analysis and then built prognostic models based on clinical stage and SS. Finally, we performed pathway enrichments analysis and investigated immune checkpoints expression underlying SS in four datasets. Results We established a 13 gene-based SS, which could precisely predict OS and PFS of LUAD. Close relations were elicited between SS and canonical malignant indictors. Furthermore, SS could serve as an independent risk factor for OS and PFS. Besides, the predictive efficacies of prognostic models were also reasonable (C-indexes: OS, 0.7; PFS, 0.7). Finally, we demonstrated enhanced cell proliferation and immune escape might account for high clinical risk of SS. Conclusions We built a 13 gene-based SS for prognostic prediction of LUAD, which exhibited wide applicability and could contribute to LUAD management.

Mining disease-related genes contributes momentously to handling lung adenocarcinoma (LUAD). But genetic complexity and tumor heterogeneity severely get in the way. Fortunately, new light has been shed by dramatic progress of bioinformatic technology in the past decades. In this research, we investigated relationships between gene expression and clinical features of LUAD via integrative bioinformatic analysis. First, we applied limma and DESeq2 packages to analyze differentially expressed genes (DEGs) of LUAD from GEO database and TCGA project (tumor tissues versus normal tissues), and acquired 180 down-regulated DEGs and 52 up-regulated DEGs. Then, we investigated genetic and biological assignment of theses DEGs by Bioconductor packages and STRING database. We found these DEGs were distributed dispersedly among chromosomes, enriched observably in extracellular matrix-related processes, and weighted hierarchically in interaction network. Finally, we established DEGs-based statistical models for evaluating TNM stage and survival status of LUAD. And these models (logistic regression models for TNM parameter and Cox regression models for survival probability) all possessed fine predictive efficacy (C-indexes: T, 0.740; N, 0.687; M, 0.823; overall survival, 0.678; progression-free survival, 0.611). In summary, we have successfully established gene expression-based models for assessing clinical characteristics of LUAD, which will assist its pathogenesis investigation and clinical intervention.

Elevated glycolysis remains a universal and primary character of cancer metabolism, which deeply depends on dysregulated metabolic enzymes. Lactate dehydrogenase A (LDHA) facilitates glycolytic process by converting pyruvate to lactate. Numerous researches demonstrate LDHA has an aberrantly high expression in multiple cancers, which is associated with malignant progression. In this review, we summarized LDHA function in cancer research. First, we gave an introduction of structure, location, and basic function of LDHA. Following, we discussed the transcription and activation mode of LDHA. Further, we focused on the function of LDHA in cancer bio‐characteristics. Later, we discussed the clinical practice of LDHA in cancer prevention and treatment. What we discussed gives a precise insight into LDHA especially in cancer research, which will contribute to exploring cancer pathogenesis and its handling measures.