IGFBP7 Drives Resistance to Epidermal Growth Factor Receptor Tyrosine Kinase Inhibition in Lung Cancer

Angiogenesis modulated by CD93 and its natural ligands IGFBP7 and MMRN2: a new target to facilitate solid tumor therapy by vasculature normalization

The tumor vasculature was different from the normal vasculature in both function and morphology, which caused hypoxia in the tumor microenvironment (TME). Previous anti-angiogenesis therapy had led to a modest improvement in cancer immunotherapy. However, antiangiogenic therapy only benefitted a few patients and caused many side effects. Therefore, there was still a need to develop a new approach to affect tumor vasculature formation. The CD93 receptor expressed on the surface of vascular endothelial cells (ECs) and its natural ligands, MMRN2 and IGFBP7, were now considered potential targets in the antiangiogenic treatment because recent studies had reported that anti-CD93 could normalize the tumor vasculature without impacting normal blood vessels. Here, we reviewed recent studies on the role of CD93, IGFBP7, and MMRN2 in angiogenesis. We focused on revealing the interaction between IGFBP7-CD93 and MMRN2-CD93 and the signaling cascaded impacted by CD93, IGFBP7, and MMRN2 during the angiogenesis process. We also reviewed retrospective studies on CD93, IGFBP7, and MMRN2 expression and their relationship with clinical factors. In conclusion, CD93 was a promising target for normalizing the tumor vasculature.

IGFBP-6 Network in Chronic Inflammatory Airway Diseases and Lung Tumor Progression

The lung is an accomplished organ for gas exchanges and directly faces the external environment, consequently exposing its large epithelial surface. It is also the putative determinant organ for inducing potent immune responses, holding both innate and adaptive immune cells. The maintenance of lung homeostasis requires a crucial balance between inflammation and anti-inflammation factors, and perturbations of this stability are frequently associated with progressive and fatal respiratory diseases. Several data demonstrate the involvement of the insulin-like growth factor (IGF) system and their binding proteins (IGFBPs) in pulmonary growth, as they are specifically expressed in different lung compartments. As we will discuss extensively in the text, IGFs and IGFBPs are implicated in normal pulmonary development but also in the pathogenesis of various airway diseases and lung tumors. Among the known IGFBPs, IGFBP-6 shows an emerging role as a mediator of airway inflammation and tumor-suppressing activity in different lung tumors. In this review, we assess the current state of IGFBP-6's multiple roles in respiratory diseases, focusing on its function in the inflammation and fibrosis in respiratory tissues, together with its role in controlling different types of lung cancer.

m7G-related gene NUDT4 as a novel biomarker promoting cancer cell proliferation in lung adenocarcinoma

Background

Lung cancer is the leading cause of mortality in cancer patients. N7-methylguanosine (m7G) modification as a translational regulation pattern has been reported to participate in multiple types of cancer progression, but little is known in lung cancer. This study attempts to explore the role of m7G-related proteins in genetic and epigenetic variations in lung adenocarcinoma, and its relationship with clinical prognosis, immune infiltration, and immunotherapy.

Methods

Sequencing data were obtained from the Genomic Data Commons (GDC) Data Portal and Gene Expression Omnibus (GEO) databases. Consensus clustering was utilized to distinguish m7G clusters, and responses to immunotherapy were also evaluated. Moreover, univariate and multivariate Cox and Least absolute shrinkage and selection operator LASSO Cox regression analyses were used to screen independent prognostic factors and generated risk scores for constructing a survival prediction model. Multiple cell types such as epithelial cells and immune cells were identified to verify the bulk RNA results. Short hairpin RNA (shRNA) Tet-on plasmids, Clustered Regularly Interspaced Short Palindromic Repeats CRISPR/Cas9 for knockout plasmids, and nucleoside diphosphate linked to moiety X-type motif 4 (NUDT4) overexpression plasmids were constructed to inhibit or promote tumor cell NUDT4 expression, then RT-qPCR, Cell Counting Kit-8 CCK8 proliferation assay, and Transwell assay were used to observe tumor cell biological functions.

Results

Fifteen m7G-related genes were highly expressed in tumor samples, and 12 genes were associated with poor prognosis. m7G cluster-B had lower immune infiltration level, worse survival, and samples that predicted poor responses to immunotherapy. The multivariate Cox model showed that NUDT4 and WDR4 (WD repeat domain 4) were independent risk factors. Single-cell m7G gene set variation analysis (GSVA) scores also had a negative correlation tendency with immune infiltration level and T-cell Programmed Death-1 PD-1 expression, but the statistics were not significant. Knocking down and knocking out the NUDT4 expression significantly inhibited cell proliferation capability in A549 and H1299 cells. In contrast, overexpressing NUDT4 promoted tumor cell proliferation. However, there was no difference in migration capability in the knockdown, knockout, or overexpression groups.

Conclusions

Our study revealed that m7G modification-related proteins are closely related to the tumor microenvironment, immune cell infiltration, responses to immunotherapy, and patients' prognosis in lung adenocarcinoma and could be useful biomarkers for the identification of patients who could benefit from immunotherapy. The m7G modification protein NUDT4 may be a novel biomarker in promoting the progression of lung cancer.

Development and Validation of a Prognostic Nomogram for Lung Adenocarcinoma: A Population-Based Study

PURPOSE

To establish an effective and accurate prognostic nomogram for lung adenocarcinoma (LUAD). Patients and Methods. 62,355 LUAD patients from 1975 to 2016 enrolled in the Surveillance, Epidemiology, and End Results (SEER) database were randomly and equally divided into the training cohort (n = 31,179) and the validation cohort (n = 31,176). Univariate and multivariate Cox regression analyses screened the predictive effects of each variable on survival. The concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were used to examine and validate the predictive accuracy of the nomogram. Kaplan-Meier curves were used to estimate overall survival (OS).

RESULTS

10 prognostic factors associated with OS were identified, including age, sex, race, marital status, American Joint Committee on Cancer (AJCC) TNM stage, tumor size, grade, and primary site. A nomogram was established based on these results. C-indexes of the nomogram model reached 0.777 (95% confidence interval (CI), 0.773 to 0.781) and 0.779 (95% CI, 0.775 to 0.783) in the training and validation cohorts, respectively. The calibration curves were well-fitted for both cohorts. The AUC for the 3- and 5-year OS presented great prognostic accuracy in the training cohort (AUC = 0.832 and 0.827, respectively) and validation cohort (AUC = 0.835 and 0.828, respectively). The Kaplan-Meier curves presented significant differences in OS among the groups.

CONCLUSION

The nomogram allows accurate and comprehensive prognostic prediction for patients with LUAD.

Evolutionary analysis and functional characterization reveal the role of the insulin-like growth factor system in a diversified selection of chickens (Gallus gallus)

The insulin-like growth factor (IGF) system plays an indispensable role in embryonic and postnatal development in mammals. However, the effects of the system on growth, carcass, and egg-laying traits, and diversified selection have not been systematically studied in chickens. In the present study, firstly the composition and gene structures of the chicken IGF system were investigated using phylogenetic tree and conserved synteny analysis. Then the effects of the genetic variations in the IGF system genes on breeding of specialized varieties were explored by principal component analysis. In addition, the spatiotemporal expression properties of the genes in this system were analyzed by RT-qPCR and the functions of the genes in egg production performance and growth were explored by association study. Moreover, the effects of IGF-binding proteins 3 (IGFBP3) on skeletal muscle development in chicken were investigated by cell cycle analysis, 5-ethynyl-2'-deoxyuridine (EdU) and Cell Counting Kit-8 (CCK-8) assays. The results showed that the chicken IGF system included 13 members which could be classified into 3 groups based on their amino acid sequences: IGF binding proteins 1 to 5 and 7 (IGFBP1-5 and 7) belonged to the first group; IGF 1 and 2 (IGF1 and IGF2), and IGF 1 and 2 receptor (IGF1R and IGF2R) belonged to the second group; and IGF2 binding proteins 1-3 (IGF2BP1-3) belonged to the third group. The IGF2BP1 and 3, and IGFBP2, 3, and 7 genes likely contributed more to the formation of both the specialized meat-type and egg-type lines, whereas IGFBP1 and 5 likely contributed more to the formation of the egg-type lines. The SNPs in the IGF2BP3 and IGFBP2 and 5 genes were significantly associated with egg number, and SNPs in the IGFBP3 promoter region were significantly associated with body weight, breast muscle weight and leg muscle weight. The IGFBP3 inhibited proliferation but promoted differentiation of chicken primary myoblasts (CPMs). These results provide insights into the roles of the IGF system in the diversified selection of chickens. The SNPs associated with egg-laying performance, growth, and carcass traits could be used as genetic markers for breeding selection of chickens in the future.

Identification of a novel gene signature of lung adenocarcinoma based on epidermal growth factor receptor-tyrosine kinase inhibitor resistance

INTRODUCTION

Tyrosine kinase inhibitors (TKIs) that target epidermal growth factor receptor (EGFR) mutations are commonly administered to EGFR-positive lung cancer patients. However, resistance to EGFR-TKIs (mostly gefitinib and erlotinib) is presently a significant problem. Limited studies have focused on an EGFR-TKI resistance-related gene signature (ERS) in lung adenocarcinoma (LUAD).

METHODS

Gefitinib and erlotinib resistance-related genes were obtained through the differential analyses of three Gene Expression Omnibus datasets. These genes were investigated further in LUAD patients from The Cancer Genome Atlas (TCGA). Patients in the TCGA-LUAD cohort were split into two groups: one for training and one for testing. The training cohort was used to build the ERS, and the testing cohort was used to test it. GO and KEGG analyses were explored for the enriched pathways between the high-risk and low-risk groups. Various software, mainly CIBERSORT and ssGSEA, were used for immune infiltration profiles. Somatic mutation and drug sensitivity analyses were also explored.

RESULTS

An ERS based on five genes (FGD3, PCDH7, DEPDC1B, SATB2, and S100P) was constructed and validated using the TCGA-LUAD cohort, resulting in the significant stratification of LUAD patients into high-risk and low-risk groups. Multivariable Cox analyses confirmed that ERS had an independent prognostic value in LUAD. The pathway enrichment analyses showed that most of the genes that were different between the two risk groups were related to the immune system. Further immune infiltration results revealed that a lower immune infiltration score was observed in high-risk patients, and that various leukocytes were significantly related to the ERS. Importantly, samples from the high-risk group showed lower levels of PD-1, PD-L1, and CTLA-4, which are important biomarkers for immunotherapy responses. Patients in the high-risk group also had more gene mutation changes and were more sensitive to chemotherapy drugs like docetaxel and sorafenib. The ERS was also validated in the GSE30219, GSE11969 and GSE72094, and showed a favorable prognostic value for LUAD patients.

DISCUSSION

The ERS established during this study was able to predict a poor prognosis for LUAD patients and had great potential for predicting drug responses.

Construction of the model for predicting prognosis by key genes regulating EGFR-TKI resistance

Background: Previous studies have suggested that patients with lung adenocarcinoma (LUAD) will significantly benefit from epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI). However, many LUAD patients will develop resistance to EGFR-TKI. Thus, our study aims to develop models to predict EGFR-TKI resistance and the LUAD prognosis. Methods: Two Gene Expression Omnibus (GEO) datasets (GSE31625 and GSE34228) were used as the discovery datasets to find the common differentially expressed genes (DEGs) in EGFR-TKI resistant LUAD profiles. The association of these common DEGs with LUAD prognosis was investigated in The Cancer Genome Atlas (TCGA) database. Moreover, we constructed the risk score for prognosis prediction of LUAD by LASSO analysis. The performance of the risk score for predicting LUAD prognosis was calculated using an independent dataset (GSE37745). A random forest model by risk score genes was trained in the training dataset, and the diagnostic ability for distinguishing sensitive and EGFR-TKI resistant samples was validated in the internal testing dataset and external testing datasets (GSE122005, GSE80344, and GSE123066). Results: From the discovery datasets, 267 common upregulated genes and 374 common downregulated genes were identified. Among these common DEGs, there were 59 genes negatively associated with prognosis, while 21 genes exhibited positive correlations with prognosis. Eight genes (ABCC2, ARL2BP, DKK1, FUT1, LRFN4, PYGL, SMNDC1, and SNAI2) were selected to construct the risk score signature. In both the discovery and independent validation datasets, LUAD patients with the higher risk score had a poorer prognosis. The nomogram based on risk score showed good performance in prognosis prediction with a C-index of 0.77. The expression levels of ABCC2, ARL2BP, DKK1, LRFN4, PYGL, SMNDC1, and SNAI2 were positively related to the resistance of EGFR-TKI. However, the expression level of FUT1 was favorably correlated with EGFR-TKI responsiveness. The RF model worked wonderfully for distinguishing sensitive and resistant EGFR-TKI samples in the internal and external testing datasets, with predictive area under the curves (AUC) of 0.973 and 0.817, respectively. Conclusion: Our investigation revealed eight genes associated with EGFR-TKI resistance and provided models for EGFR-TKI resistance and prognosis prediction in LUAD patients.

Different roles of the insulin-like growth factor (IGF) axis in non-small cell lung cancer

Abstract:

Non-small cell lung cancer (NSCLC) remains one of the deadliest malignant diseases, with high incidence and mortality worldwide. The insulin-like growth factor (IGF) axis, consisting of IGF-1, IGF-2, related receptors (IGF-1R, -2R), and high-affinity binding proteins (IGFBP 1–6), is associated with promoting fetal development, tissue growth, and metabolism. Emerging studies have also identified the role of the IGF axis in NSCLC, including cancer growth, invasion, and metastasis. Upregulation of IGE-1 and IGF-2, overexpression of IGF-1R, and dysregulation of downstream signaling molecules involved in the PI-3K/Akt and MAPK pathways jointly increase the risk of cancer growth and migration in NSCLC. At the genetic level, some noncoding RNAs could influence the proliferation and differentiation of tumor cells through the IGF signaling pathway. The resistance to some promising drugs might be partially attributed to the IGF axis. Therapeutic strategies targeting the IGF axis have been evaluated, and some have shown promising efficacy. In this review, we summarize the biological roles of the IGF axis in NSCLC, including the expression and prognostic significance of the related components, noncoding RNA regulation, involvement in drug resistance, and therapeutic application. This review offers comprehensive understanding of NSCLC and provides insightful ideas for future research.

The Multi-Omics Analysis of Key Genes Regulating EGFR-TKI Resistance, Immune Infiltration, SCLC Transformation in EGFR-Mutant NSCLC

Background

Lung cancer is a high-risk malignancy worldwide. The harboring of epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) makes EGFR-tyrosine kinase inhibitor (EGFR-TKI) an attractive therapeutic option. However, patients usually suffer the primary and secondary resistance to EGFR-TKI. And the molecular alteration is still not fully clear and needs further study.

Methods

The GEO database was utilized to find the differentially expressed genes (DEGs) in NSCLC profiles resistant to the 1st or 2nd generation EGFR-TKI. We analyzed the expression and pathway enrichment of hub genes, and the prognosis of EGFR mutant/wild-type lung adenocarcinoma (LUAD). Moreover, small cell lung cancer (SCLC) and TKI-resistant profiles were used to find common DEGs, and construct miRNA regulatory network. Analysis was performed of hub genes' related immune infiltration, drug sensitivity, and methylation. Further, we analyzed hub gene expression in EGFR-mutant LUAD and paracancerous tissue by qRT-PCR.

Results

A total of 107 DEGs were found related to TKI resistance. Eleven hub genes were obtained after visualization, of which 5 hub genes were co-expressed in SCLC with common miRNAs. Lower expression of SPP1 (hub gene) was associated with better survival in NSCLC. The immune infiltration analysis showed more CD4+ T cells in the resistant group with high expression of SPP1. SPP1 and CD44 promoters’ methylations were independent prognostic factors of LUAD. And the expression level of SPP1 related to the sensitivity of EGFR-TKIs in multiple cancer cell lines. qRT-PCR validated the higher expression of SPP1 in EGFR-mutant LUAD than in normal tissue.

Conclusion

Our study suggested that the upregulation of SPP1 might induce resistance to the 1st and 2nd generation EGFR-TKI, and influence tumor immune infiltration, resulting in poor survival. ZEB1, SPP1, MUC1, CD44, and ESRP1 might be molecular drivers of SCLC transformation of TKI resistance.

IGFBP7 overexpression promotes acquired resistance to AZD9291 in non-small cell lung cancer

AZD9291 (osimertinib) is the third-generation EGFR-TKI treat for EGFR mutated NSCLC patients. Despite its encouraging efficacy in clinical, acquired resistance is still inevitable. The mechanism of drug resistance needs to be further explored. In a previous study, we established an AZD9291-resistant cell strain named HCC827/AZDR. We found that insulin-like growth factor binding protein 7 (IGFBP7) expression was markedly increased in HCC827/AZDR cells and AZD9291-resistant patients by RNA sequencing and immunohistochemical analysis, respectively. Reduced IGFBP7 in HCC827/AZDR cells by si-RNA interference recovered the sensitivity to AZD9291 partially and increased AZD9291-induced cell apoptosis. Enhancing IGFBP7 expression in EGFR-mutated non-small cell lung cancer (NSCLC) cells using lentiviruses infection reduced their sensitivity to AZD9291. This study is the first to discover that high IGFBP7 expression could occur following treatment with AZD9291. This might be one of the mechanisms underlying AZD9291 resistance and a potential therapeutic target following AZD9291 resistance.

Identification of Key Genes and Pathways in Gefitinib-Resistant Lung Adenocarcinoma using Bioinformatics Analysis

Gefitinib resistance is a serious threat in the treatment of patients with non-small cell lung cancer (NSCLC). Elucidating the underlying mechanisms and developing effective therapies to overcome gefitinib resistance is urgently needed. The differentially expressed genes (DEGs) were screened from the gene expression profile GSE122005 between gefitinib-sensitive and resistant samples. GO and KEGG analyses were performed with DAVID. The protein-protein interaction (PPI) network was established to visualize DEGs and screen hub genes. The functional roles of CCL20 in lung adenocarcinoma (LUAD) were examined using gene set enrichment analysis (GSEA). Functional analysis revealed that the DEGs were mainly concentrated in inflammatory, cell chemotaxis, and PI3K signal regulation. Ten hub genes were identified based on the PPI network. The survival analysis of the hub genes showed that CCL20 had a significant effect on the prognosis of LUAD patients. GSEA analysis showed that CCL20 high expression group was mainly enriched in cytokine-related signaling pathways. In conclusion, our analysis suggests that changes in inflammation and cytokine-related signaling pathways are closely related to gefitinib resistance in patients with lung cancer. The CCL20 gene may promote the formation of gefitinib resistance, which may serve as a new biomarker for predicting gefitinib resistance in patients with lung cancer.

Single-cell transcriptome analysis demonstrates inter-patient and intra-tumor heterogeneity in primary and metastatic lung adenocarcinoma

In this study, we performed single-cell transcriptome data analysis of fifty primary and metastatic lung adenocarcinoma (LUAD) samples from the GSE123902 and GSE131907 datasets to determine the landscape of inter-patient and intra-tumoral heterogeneity. The gene expression profiles and copy number variations (CNV) showed significant heterogeneity in the primary and metastatic LUAD samples. We observed upregulation of pathways related to translational initiation, endoplasmic reticulum stress, exosomes, and unfolded protein response in the brain metastasis samples as compared to the primary tumor samples. Pathways related to exosomes, cell adhesion and metabolism were upregulated and the epithelial-to-mesenchymal-transition (EMT) pathway was downregulated in brain metastasis samples from chemotherapy-treated LUAD patients as compared to those from the untreated LUAD patients. Tumor cell subgroups in the brain metastasis samples showed differential expression of genes related to type II alveolar cells, chemoresistance, glycolysis and oxidative phosphorylation (metabolic reprogramming), and EMT. Thus, single-cell transcriptome analysis demonstrated intra-patient and intra-tumor heterogeneity in the regulation of pathways related to tumor progression, chemoresistance and metabolism in the primary and metastatic LUAD tissues. Moreover, our study demonstrates that single cell transcriptome analysis is a potentially useful tool for accurate diagnosis and personalized targeted treatment of LUAD patients.

Clinical study of serum IGFBP7 in predicting lymphatic metastasis in patients with lung adenocarcinoma

PURPOSE

To find serum tumor markers for predicting the presence of lymphatic metastasis in patients with lung adenocarcinoma, and to explore the diagnostic value of IGFBP7 in predicting if lymphatic metastasis occurs in lung adenocarcinoma.

METHODS

The concentration of IGFBP7 in the peripheral blood of 90 serum samples, including 30 patients with lung adenocarcinoma in situ, 30 patients with lung adenocarcinoma metastasis, and 30 normal controls were detected by ELISA. The data were analyzed statistically.

RESULTS

The concentration of IGFBP7 and D-dimer in the metastatic lung adenocarcinoma group was significantly higher than that in the lung adenocarcinoma in situ group (P < 0.05). The expression level of IGFBP7 in serum of patients with lung adenocarcinoma was associated with the clinical stage (P < 0.05) and lymphatic metastasis (P < 0.05). Using the receiver operating characteristic (ROC) curve, the area under the ROC curve of IGFBP7 was 0.901 (95% Confidence Interval was 0.806 to 0.996), and 0.5 was outside the 95% confidence interval (P < 0.05). The difference was statistically significant.

CONCLUSIONS

IGFBP7 can predict if the lung adenocarcinoma has lymphatic metastasis, which is helpful to improve the treatment of lung adenocarcinoma, and can be used as a new tumor marker to predict whether the lung adenocarcinoma has lymphatic metastasis or not.

Repositioning Aspirin to Treat Lung and Breast Cancers and Overcome Acquired Resistance to Targeted Therapy

Background: The major limitation of targeted cancer therapy is development of acquired resistance. Intratumoral heterogeneity and coexist of multiple resistance mechanisms make combination therapies targeting one specific mechanism inefficient.

Methods: Transcriptional signature obtained from GEO was used to reposition FDA-approved drugs to treat lung and breast cancers as well as overcome acquired resistance to EGFR TKIs in lung cancer and to tamoxifen in breast cancer via CMap. In vitro and in vivo models were used to examine candidate drugs for their anti-cancer and anti-resistance efficacy and underlying mechanisms.

Results: We found that aspirin, the most commonly used drug, not only inhibited proliferation and promoted apoptosis of cancer cells, but also delayed and overcame acquired resistance to targeted therapy using in vitro and in vivo models. The underlying mechanism could be attributed to enhanced cancer stemness and activated NF-κB signaling in acquired resistant tumors, both of which were suppressed by aspirin and rendered resistant tumors more sensitive to aspirin.

Conclusions: Our data identify aspirin as a potential candidate for combination therapy for lung and breast cancers.