Sex steroid metabolism and actions in non-small cell lung carcinoma

Metabolomics for early-stage lung adenocarcinoma: diagnostic biomarker screening

Objective

This study aimed to identify specific metabolic markers in the blood that can diagnose early-stage lung adenocarcinoma.

Methods

An untargeted metabolomics study was performed, and the participants were divided into four groups: early-stage lung adenocarcinoma group (E-LUAD; n = 21), healthy control group (HC, n = 17), non-cancerous lung disease group (NCC; n = 17), and advanced lung adenocarcinoma group (A-LUAD; n = 25). Plasma metabolite levels that differed in the E-LUAD group compared to the other three groups were identified via liquid chromatography-mass spectrometry (LC-MS). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed at metaX for statistical analysis. A Venn diagram was constructed to identify overlapping differential metabolites of the class comparisons. The data were randomly divided into a training set and a validation set. Based on the overlapping differential metabolites, the diagnostic model was constructed. The discrimination of the model was evaluated using the area under the curve (AUC).

Results

A total of 527 metabolites were tentatively identified in positive ion mode and 286 metabolites in negative ion mode. Compared with the HC group, 121 differential metabolites were identified. Compared with the NCC group, 67 differential metabolites were identified. Compared with the A-LUAD group, 54 differential metabolites were identified. The Venn diagram showed that 29 metabolites can distinguish E-LUAD from HC and NCC and that four metabolites can distinguish E-LUAD from HC, NCC, and A-LUAD. The feature metabolites were selected to establish the diagnostic model for E-LUAD. The AUC value of the training set was 0.918, and it was 0.983 in the validation set.

Conclusion

Blood metabolomics has potential diagnostic value for E-LUAD. More medical studies are needed to verify whether the metabolic markers identified in the current research can be applied in clinical practice.

Androgen Receptor Promotes Lung Cancer Metastasis by Modifying the miR23a-3p/EPHB2 Pathway

OBJECTIVE

This study aimed to investigate the reasons behind the lower survival rates in male lung cancer patients than in female lung cancer patients.

METHODS

Through various techniques, such as Argonaute immunoprecipitation, luciferase assays, and ChIP, this study confirmed the positive effects of androgen receptor (AR) on lung cancer cell invasion across different in vitro cell lines and in vivo mouse models.

RESULTS

The findings suggest that AR enhanced the invasion of lung cancer cells by modifying EPHB2 signals at the protein expression level, which in turn required changes in miRNA-23a-3p. Restoring miRNA-23a-3p could counteract the intensified invasion of lung cancer cells mediated by AR.

CONCLUSION

This study revealed that AR may facilitate the lung cancer matastasis by modulating miRNA-23a-3p/EPHB2 signaling and that targeting this signaling pathway could provide new approaches to inhibit lung cancer metastasis.

Regulome-based characterization of drug activity across the human diseasome

Drugs are expected to recover the cell system away from the impaired state to normalcy through disease treatment. However, the understanding of gene regulatory machinery underlying drug activity or disease pathogenesis is far from complete. Here, we perform large-scale regulome analysis for various diseases in terms of gene regulatory machinery. Transcriptome signatures were converted into regulome signatures of transcription factors by integrating publicly available ChIP-seq data. Regulome-based correlations between diseases and their approved drugs were much clearer than the transcriptome-based correlations. For example, an inverse correlation was observed for cancers, whereas a positive correlation was observed for immune system diseases. After demonstrating the usefulness of the regulome-based drug discovery method in terms of accuracy and applicability, we predicted new drugs for nonsmall cell lung cancer and validated the anticancer activity in vitro. The proposed method is useful for understanding disease–disease relationships and drug discovery.

Preoperative Serum Triglyceride to High-Density Lipoprotein Cholesterol Ratio Can Predict Prognosis in Non-Small Cell Lung Cancer: A Multicenter Retrospective Cohort Study

Background: Previously, research has reported associations of lipid and lipoprotein imbalances with carcinogenesis and cancer progression, so they have been considered as promising prognostic biomarkers for cancer in recent years. However, the correlation of preoperative serum triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) with non-small cell lung carcinoma (NSCLC) prognosis remains under exploration. Here, the study investigated the prognostic function of TG/HDL-C for NSCLC. Methods: The total combined group of this retrospective study enrolled 479 NSCLC patients from two tertiary referral hospitals, of which 223 patients were defined as the training group (Nanchang) and the remaining 256 were defined as the validation group (Wuhan). The cut-off of preoperative TG/HDL-C was determined through ROC curve in the training group and verified in the validation and combined groups subsequently. With one Cox proportional hazards model and K-M survival curves, a survival analysis was conducted. Results: In the training group, the optimal cut-off of TG/HDL-C was 1.02. Furthermore, the data based on the training group revealed a greater, shorter, overall survival (OS) in patients having a high TG/HDL-C (>1.02) than those having low TG/HDL-C (≤1.02). Meanwhile, in univariate and multivariate analysis, for prognostic OS among NSCLC patients, TG/HDL-C acted as one independent factor. All the results above were confirmed in the validation and combined groups. Conclusion: NSCLC patients with a comparatively low preoperative serum TG/HDL-C level had a correlation with well OS. TG/HDL-C possibly acted as one novel, effective prognostic biomarker for NSCLC patients.

Concurrent Androgen Deprivation Therapy for Prostate Cancer Improves Survival for Synchronous or Metachronous Non-Small Cell Lung Cancer: A SEER-Medicare Database Analysis

Introduction: The crosstalk between receptor kinase signaling, such as EGFR and androgen receptor signaling, suggests a potential interaction between androgen deprivation therapy (ADT) and lung cancer outcome. Methods: We employed the SEER−Medicare data of lung cancer patients diagnosed between 1988 and 2005 to test for an association between ADT for prostate cancer and lung cancer outcome. We employed the Kaplan−Meier method and Cox proportional hazard with log-rank test model to assess any significant impact of ADT on survival. Results: We included data from 367,750 lung cancer patients; 17.4%, 2.9%, 33.6% and 46.1% with stages I, II, III and IV, respectively; 84.5% were >65 years; 57.2% males; 84.2% Caucasians and 9.3% Blacks. There were 11,061 patients (3%) with an initial prostate cancer diagnosis followed by lung cancer (P-L group); 3017 (0.8%) with an initial diagnosis of lung cancer and subsequent prostate cancer diagnosis (L-P group); the remainder had only lung cancer (L group). Stage I lung cancer was most common in the L-P group compared to the L and P-L groups—54% vs. 17.13% vs. 17.92%, p < 0.0001 for L-P, L and P-L, respectively. The median OS for lung cancer diagnosis was 93 months versus 10 and 9 months, respectively, for the L-P, L and P-L subgroups. ADT was associated with improved survival on multivariate analysis, especially in Caucasian patients (HR of death: 0.86; 95% CI: 0.76−0.97; p = 0.012). Conclusion: ADT was associated with improved outcome for NSCLC, in line with the hypothesis of a role for the androgen receptor in lung cancer. Our findings support a systematic evaluation of the potential benefit of ADT as a therapy for lung cancer.

Selective Estrogen Receptor Modulators (SERMs) Synergize with Cisplatin, Induce Apoptosis and Suppress Cellular Migration and Colony Formation of Lung Cancer Cells

Background:

Lung cancer remains the leading cause of cancer-related deaths worldwide. Hence, novel therapeutic approaches targeting crucial pathways are needed to improve its treatment. Previous studies have verified the involvement of the estrogen pathway, mediated through estrogen receptor β (ERβ), in the development and progression of lung carcinogenesis. Selective estrogen receptor modulators (SERMs) are a group of estrogen receptor agonists/antagonists that have tissue selective effects. Many of the available SERMs are used for the management of breast cancer. However, their role in lung cancer is still under investigation.

Objectives:

The aim of this research is to investigate the anti-tumorigenic activity of the selective estrogen receptor modulators, tamoxifen, raloxifene, and toremifene, against different lung cancer cell lines.

Methods:

The anti-proliferative and combined effects of SERMs with standard chemotherapy were evaluated by MTT assay. Cell migration was assessed using a wound-healing assay. The mechanism of cell death was determined using the Annexin V-FITC/ propidium iodide staining flow cytometry method. Cells’ capability to form colonies was evaluated by soft agar colony formation assay. Estrogen receptors expression was determined using real-time PCR.

Results:

Our results have demonstrated the presence of ERβ in A549, H1299, and H661 lung cancer cells. Cellular proliferation assay suggested that SERMs have significantly reduced lung cancer cells proliferation in a time and concentration- dependent manner. Additionally, SERMs exhibited a synergistic effect against A549 cells when combined with cisplatin. SERMs treatment have increased cell apoptosis and resulted in concentration-dependent inhibition of cell migration and colony formation of A549 cells.

Conclusion:

Selective estrogen receptor modulators may possess potential therapeutic utility for the treatment of lung cancer as monotherapy or in combination with standard chemotherapy.

Untargeted metabolomics profiling in a mouse model of lung cancer treated with thermal ablation

Thermal ablation is widely used in the treatment of lung cancer and is beneficial for the overall survival of patients in clinic. However, there is barely a priority in which ablation system should be chosen under different periods of tumor progression in lung cancer. The present study investigated different modes of thermal ablation systems in mice with transplanted Lewis lung carcinoma tumors and their various biological effects in local regions using untargeted metabolomics. The results showed that thermal ablation could significantly suppress tumor growth and the differentially expressed metabolites of tumors after ablation relative to untreated tumors concentrated on organic compounds, organic acids and derivatives, nucleosides, nucleotides, and lipids. The upregulated metabolites indicated an inflammatory reaction in the ablation groups at an early stage after ablation. Steroid hormone and tryptophan metabolism, which are associated with immune responses, were modulated after both cryoablation and hyperthermal ablation. Characteristically, the results also indicated that cryoablation suppressed glucose oxidation and carbohydrate metabolism of tumor, while hyperthermal ablation suppressed lipid metabolism of tumor. In conclusion, thermal ablation could inhibit tumor growth under either freezing or heating modes with characteristic different biological effects on tumors.

Antibody Validation for Estrogen Receptor Beta

Antibodies can cross-react with proteins other than their intended targets, and antibody-based applications can, if not properly validated, lead to flawed interpretations. When evaluating 13 anti-estrogen receptor beta (ERβ) antibodies in 2017, we concluded that only one of them was specific. Applying this antibody in immunohistochemistry of over 44 different normal human tissues and 20 types of cancers revealed ERβ expression in only a few selected tissues. This aligned with mRNA evidence but contradicted a large set of published literature. ERβ protein expression continues to be reported in tissues without clear support by mRNA expression. In this chapter, we describe how ERβ antibodies can be thoroughly validated and discuss selection of well-characterized positive and negative controls. The validation scheme presented is applicable for immunohistochemistry and Western blotting. The protocol includes evaluation of mRNA evidence, use of public databases, assessment of on- and off-target binding, and an optional step for corroboration with immunoprecipitation and mass spectrometry.

Identification of a six-gene metabolic signature predicting overall survival for patients with lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.

Methods

The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan-Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.

Results

The six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.

Conclusions

Our study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.

The Association Between RAPSN Methylation in Peripheral Blood and Early Stage Lung Cancer Detected in Case-Control Cohort

Background

Early detection is essential to improve the survival and life quality of lung cancer (LC) patients. Changes of peripheral blood DNA methylation could be associated with malignancy but were mostly studied in Caucasians.

Methods

Here, in a Chinese population, we performed mass spectrometry assays to investigate the association between very early stage LC and methylation levels of RAPSN in the peripheral blood by a case–control cohort using of 221 LC patients (93.2% LC at stage I) and 285 unrelated cancer free control individuals.

Results

The odds ratios (ORs) of all CpG sites were evaluated for their risk to LC using inter-quartile analyses by logistic regression. In general, we observed an association between very early LC and decreased methylation of RAPSN_CpG_1.15 and RAPSN_CpG_3.4 (referring to Q4, OR range from 1.64 to 1.81, p<0.05). Stratified by gender, while hypomethylation of RAPSN_CpG_1.15, RAPSN_CpG_3.4 and RAPSN_CpG_7.14 were associated with LC in males (referring to Q4, ORs range from 1.94 to 2.31, p<0.05), RAPSN_CpG_2 and RAPSN_CpG_5 showed significantly lower methylation in female LC patients comparing to controls (referring to Q4, ORs range from 2.49 to 3.60, p<0.05). The risk of RAPSN hypomethylation to LC was enhanced by aging, and typically for people older than 55 years (referring to Q4, ORs range from 2.17 to 3.61 in six out of all 10 analyzed CpG groups, p<0.05).

Conclusion

Our study reveals an association between RAPSN hypomethylation in peripheral blood and LC and suggests the occurrence of altered blood-based methylation at the early stage of cancer.