Akt kinase LANCL2 functions as a key driver in EGFR-mutant lung adenocarcinoma tumorigenesis

Nuclear transport of phosphorylated LanCL2 promotes invadopodia formation and tumor progression of glioblastoma by activating STAT3/Cortactin signaling

INTRODUCTION

Our previous study showed that the abscisic acid receptor lanthionine synthetase C-like 2 (LanCL2) is a significant prognostic factor for overall survival in young glioblastoma patients. However, the role of LanCL2 in glioblastoma remains unclear yet.

OBJECTIVES

This study aims to investigate the role of LanCL2 in regulating in-vitro cell invasion and in-vivo tumor progression of glioblastoma and its underlying mechanism.

METHODS

Tyrosine 198 or 295 residue of LanCL2 was mutated using site-directed mutagenesis to block its phosphorylation. The role of LanCL2 in glioblastoma was investigated using transwell or 3D invasion assay, matrix degradation assay and intracranial xenograft model.

RESULTS

This study showed that nuclear transport of LanCL2 was enhanced by overexpression of LanCL2 or its ligand abscisic acid in glioblastoma cells. Knockdown of LanCL2 suppressed migration, invasion and invadopodia formation of glioblastoma cells, whereas overexpression of wild-type LanCL2 enhanced them. Blocking of Tyr295 residue phosphorylation of LanCL2 impeded its nuclear transport, retarded glioblastoma cell motility and invadopodia formation, and deceased the phosphorylation of Cortactin and STAT3. c-Met was identified as the upstream tyrosine kinase of Tyr295 residue of LanCL2, and inhibition of c-Met markedly suppressed the nuclear transport of LanCL2. Moreover, overexpression of wild-type LanCL2 significantly promoted orthotopic tumor growth of glioblastoma in vivo and led to poor survival of mice with median survival time of 33.5 days, whereas Tyr295 mutation rescued it with median survival time of 49 days.

CONCLUSION

Our findings suggested that Tyr295 phosphorylation is crucial to the activation and nuclear transport of LanCL2, as well as invadopodia formation and tumor progression of glioblastoma, providing the evidence of a novel signaling axis c-Met/LanCL2/STAT3/Cortactin and the first observation of the importance of Tyr295 phosphorylation to LanCL2.

Screening anlotinib responders via blood-based proteomics in non-small cell lung cancer

Anlotinib has been demonstrated to be effective in advanced non-small cell lung cancer (NSCLC) patients. The response stratification of anlotinib remains unclear. In this study, plasma samples from 28 anlotinib-treated NSCLC patients (discovery cohort: 14 responders and 14 non-responders) were subjected to proteomic analysis, and plasma samples from 35 anlotinib-treated NSCLC patients (validation cohort) were subjected to validation analysis. Liquid chromatography-tandem mass spectrometry analysis was performed on samples with different time points, namely baseline (BL), best response (BR), and progression disease (PD). Bioinformatics analysis was performed to screen for the underlying differential proteins. Enzyme-linked immunosorbent assay was performed to detect plasma ARHGDIB, FN1, CDH1, and KNG1 levels respectively. The Kaplan-Meier survival analysis was used for biomarker-based responsive stratification. Our results indicated that differential proteins between responders and non-responders showed that proteomic technology potentially contributes to biomarker screening in plasma samples at BL. Furthermore, our results suggested that the detection of plasma ARHGDIB, FN1, CDH1, and KNG1 levels have potential predictive value for anlotinib response both in the discovery cohort and validation cohort. Collectively, this study offers novel insights into the value of plasma biomarker screening via proteomic examination and suggests that plasma ARHGDIB, FN1, CDH1, and KNG1 levels could be used as biomarkers for anlotinib stratification in NSCLC patients.

Development and Validation of a 7-Gene Inflammatory Signature Forecasts Prognosis and Diverse Immune Landscape in Lung Adenocarcinoma

Background: Inflammatory responses are strongly linked with tumorigenesis and cancer development. This research aimed to construct and validate a novel inflammation response–related risk predictive signature for forecasting the prognosis of patients with LUAD.

Methods: Differential expression analysis, univariate Cox, LASSO, and multivariate Cox regression analyses of 200 inflammatory response–related genes (IRRG) were performed to establish a risk predictive model in the TCGA training cohort. The performance of the IRRG model was verified in eight GEO datasets. GSEA analysis, ESTIMATE algorithms, and ssGSEA analysis were applied to elucidate the possible mechanisms. Furthermore, the relationship analysis between risk score, model genes, and chemosensitivity was performed. Last, we verified the protein expression of seven model genes by immunohistochemical staining or Western blotting.

Results: We constructed a novel inflammatory response–related 7-gene signature (MMP14, BTG2, LAMP3, CCL20, TLR2, IL7R, and PCDH7). Patients in the high-risk group presented markedly decreased survival time in the TCGA cohort and eight GEO cohorts than the low-risk group. Interestingly, multiple pathways related to immune response were suppressed in high-risk groups. The low infiltration levels of B cell, dendritic cell, natural killer cell, and eosinophil can significantly affect the unsatisfactory prognosis of the high-risk group in LUAD. Moreover, the tumor cells’ sensitivity to anticancer drugs was markedly related to risk scores and model genes. The protein expression of seven model genes was consistent with the mRNA expression.

Conclusion: Our IRRG prognostic model can effectively forecast LUAD prognosis and is tightly related to immune infiltration.

Multi-Omics Signatures Identification for LUAD Prognosis Prediction Model Based on the Integrative Analysis of Immune and Hypoxia Signals

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer with heterogeneous outcomes and diverse therapeutic responses. However, the understanding of the potential mechanism behind LUAD initiation and progression remains limited. Increasing evidence shows the clinical significance of the interaction between immune and hypoxia in tumor microenvironment. To mine reliable prognostic signatures related to both immune and hypoxia and provide a more comprehensive landscape of the hypoxia-immune genome map, we investigated the hypoxia-immune-related alteration at the multi-omics level (gene expression, somatic mutation, and DNA methylation). Multiple strategies including lasso regression and multivariate Cox proportional hazards regression were used to screen the signatures with clinical significance and establish an incorporated prognosis prediction model with robust discriminative power on survival status on both the training and test datasets. Finally, combing all the samples, we constructed a robust model comprising 19 signatures for the prognosis prediction of LUAD patients. The results of our study provide a comprehensive landscape of hypoxia-immune related genetic alterations and provide a robust prognosis predictor for LUAD patients.

The centromere-associated protein CENPU promotes cell proliferation, migration, and invasiveness in lung adenocarcinoma

CENPU, encoding an important factor involved in kinetochore assembly during mitosis, is associated with shorter survival rates in lung adenocarcinoma (LUAD) patients. CENPU promotes growth rates and invasive behavior of LUAD cells; however, its mechanism of action in LUAD progression remains to be elucidated. CENPU mRNA and protein expression were elevated in LUAD tumors, and high CENPU gene expression was associated with inferior survival prognosis in LUAD patients. CENPU knockdown inhibited LUAD cell proliferation, clone formation, migration, invasion, and epithelial-mesenchymal transition (EMT) in addition to inducing cell cycle arrest and apoptosis in vitro and reduced LUAD xenograft tumor growth in vivo. Furthermore, we identified CENPU-regulated genes significantly enriched for proliferation and apoptosis pathways, and identified HSP Family Member C10 (DNAJC10) as putative effector of CENPU. CENPU knockdown produced DNAJC10 protein downregulation, and DNAJC10 overexpression partially rescued the phenotypic effects of CENPU knockdown in LUAD cells. Moreover, CENPU's coiled-coil domain was essential for CENPU's phenotypic effects in LUAD cells. In conclusion, the kinetochore component CENPU plays a critical role in LUAD cell proliferation and invasiveness. Targeting CENPU-DNAJC10 axis may inhibit LUAD tumor cell proliferation and metastasis.

Emerging Molecular Dependencies of Mutant EGFR-Driven Non-Small Cell Lung Cancer

Epidermal growth factor receptor (EGFR) mutations are the molecular driver of a subset of non-small cell lung cancers (NSCLC); tumors that harbor these mutations are often dependent on sustained oncogene signaling for survival, a concept known as “oncogene addiction”. Inhibiting EGFR with tyrosine kinase inhibitors has improved clinical outcomes for patients; however, successive generations of inhibitors have failed to prevent the eventual emergence of resistance to targeted agents. Although these tumors have a well-established dependency on EGFR signaling, there remain questions about the underlying genetic mechanisms necessary for EGFR-driven oncogenesis and the factors that allow tumor cells to escape EGFR dependence. In this review, we highlight the latest findings on mutant EGFR dependencies, co-operative drivers, and molecular mechanisms that underlie sensitivity to EGFR inhibitors. Additionally, we offer perspective on how these discoveries may inform novel combination therapies tailored to EGFR mutant NSCLC.

TP53 Mutation Status and Biopsy Lesion Type Determine the Immunotherapeutic Stratification in Non-Small-Cell Lung Cancer

Immunotherapy, a chemotherapy-free process, has emerged as a promising therapeutic strategy to prolong the overall survival (OS) of patients with non-small-cell lung cancer (NSCLC). However, effective stratification factors for immunotherapy remain unclear. The purpose of this study was to discuss the potential stratification factors of NSCLC immunotherapy using immune checkpoint inhibitors (ICIs) by integrating genomic profiling and tumor lesion–type information. In this study, 344 patients with NSCLC, whose clinical and tissue (including metastatic and primary lesions) mutation information was available, were included. The potential gene mutation status for predicting the outcomes of immunotherapy was screened by comparing the difference in mutation frequency between responders and non-responders. Our results indicated that the potential predictors of immunotherapy were significantly different, especially between patients with TP53(+) (including metastatic and primary lesions) and TP53(−) (including metastatic and primary lesions). According to this classification, patients with NSCLC who suggested immunotherapy had a higher OS than those who did not (25 months vs. 7 months, P < 0.0001, hazard ratio = 0.39). Collectively, this study provides a new perspective for screening immunotherapy predictors in NSCLC, suggesting that the TP53 mutation status and source of biopsy tissue should be considered during the development of immunotherapy biomarkers.

ctDNA-Profiling-Based UBL Biological Process Mutation Status as a Predictor of Atezolizumab Response Among TP53-Negative NSCLC Patients

Atezolizumab, an immune checkpoint inhibitor, has been approved for use in clinical practice in non-small cell lung cancer (NSCLC) patients, but potential biomarkers for response stratification still need further screening. In the present study, a total of 399 patients with high-quality ctDNA profiling results were included. The mutation status of ubiquitin-like conjugation (UBL) biological process genes (including ABL1, APC, LRP6, FUBP1, KEAP1, and TOP2A) and clinical information were further integrated. The results suggested that the patients with the clinical characteristics of male or history of smoking had a higher frequency of UBL mutation positivity [UBL (+)]; the patients who were UBL (+) had shorter progression-free survival (PFS) (1.69 vs. 3.22 months, p = 0.0007) and overall survival (8.61 vs. 16.10 months, p < 0.0001) than those patients with UBL mutation negativity [UBL (–)]; and more promising predictive values were shown in the smoker subgroup and ≤ 3 metastasis subgroup. More interestingly, we found the predictor has more performance in TP53-negative cohorts [training in an independent POPLAR and OAK cohorts (n = 200), and validation in an independent MSKCC cohort (n = 127)]. Overall, this study provides a predictor, UBL biological process gene mutation status, not only for identifying NSCLC patients who may respond to atezolizumab therapy but also for screening out the potential NSCLC responders who received other immune checkpoint inhibitors.

NPM1 Is a Prognostic Biomarker Involved in Immune Infiltration of Lung Adenocarcinoma and Associated With m6A Modification and Glycolysis

Background

Overexpression of NPM1 can promote the growth and proliferation of various tumor cells. However, there are few studies on the comprehensive analysis of NPM1 in lung adenocarcinoma (LUAD).

Methods

TCGA and GEO data sets were used to analyze the expression of NPM1 in LUAD and clinicopathological analysis. The GO/KEGG enrichment analysis of NPM1 co-expression and gene set enrichment analysis (GSEA) were performed using R software package. The relationship between NPM1 expression and LUAD immune infiltration was analyzed using TIMER, GEPIA database and TCGA data sets, and the relationship between NPM1 expression level and LUAD m6A modification and glycolysis was analyzed using TCGA and GEO data sets.

Results

NPM1 was overexpressed in a variety of tumors including LUAD, and the ROC curve showed that NPM1 had a certain accuracy in predicting the outcome of tumors and normal samples. The expression level of NPM1 in LUAD is significantly related to tumor stage and prognosis. The GO/KEGG enrichment analysis indicated that NPM1 was closely related to translational initiation, ribosome, structural constituent of ribosome, ribosome, Parkinson disease, and RNA transport. GSEA showed that the main enrichment pathway of NPM1-related differential genes was mainly related to mTORC1 mediated signaling, p53 hypoxia pathway, signaling by EGFR in cancer, antigen activates B cell receptor BCR leading to generation of second messengers, aerobic glycolysis and methylation pathways. The analysis of TIMER, GEPIA database and TCGA data sets showed that the expression level of NPM1 was negatively correlated with B cells and NK cells. The TCGA and GEO data sets analysis indicated that the NPM1 expression was significantly correlated with one m6A modifier related gene (HNRNPC) and five glycolysis related genes (ENO1, HK2, LDHA, LDHB and SLC2A1).

Conclusion

NPM1 is a prognostic biomarker involved in immune infiltration of LUAD and associated with m6A modification and glycolysis. NPM1 can be used as an effective target for diagnosis and treatment of LUAD.

A Novel circRNA-miRNA-mRNA Hub Regulatory Network in Lung Adenocarcinoma

The growing evidence suggests that circular RNAs (circRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of circRNAs in lung adenocarcinoma (LUAD) remains unclear. This study clarified the potentially regulatory network and functional mechanism of circRNAs in LUAD. The expression data of circRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were obtained from the Gene Expression Omnibus (GEO) database. Relying on GSE101586, GSE101684, and GSE112214, we identified differentially expressed circRNAs (DEcircRNAs). Depending on GSE135918 and GSE32863, we screened out differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs), respectively. Then, a novel competing endogenous RNA (ceRNA) regulatory network related to LUAD was constructed. We also revealed biological processes and signal pathways regulated by these DEcircRNAs. Based on gene expression data and survival information of LUAD patients in The Cancer Genome Atlas (TCGA) and GEO, we implemented survival analysis to select DEmRNAs related to prognosis and build a novel circRNA-miRNA-mRNA hub regulatory network. Meanwhile, quantitative real-time PCR (qRT-PCR) was utilized to validate DEcircRNAs in the ceRNA hub regulatory network. As a result, a total of 8 DEcircRNAs, 19 DEmiRNAs, and 85 DEmRNAs were identified. The novel ceRNA regulatory network included 5 circRNAs, 8 miRNAs, and 22 mRNAs. The final ceRNA hub regulatory network contained two circRNAs, two miRNAs, and two mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the five DEcircRNAs may affect LUAD onset and progression through Wnt signaling pathway and Hippo signaling pathway. All in all, this study revealed the regulatory network and functional mechanism of circRNA-related ceRNAs in LUAD.