Identification of potential target genes and crucial pathways in small cell lung cancer based on bioinformatic strategy and human samples

Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches

Lung cancer is one of the most common cancer and the leading cause of cancer-related death worldwide. Early detection of lung cancer can help reduce the death rate; therefore, the identification of potential biomarkers is crucial. Thus, this study aimed to identify potential biomarkers for lung cancer by integrating bioinformatics analysis and machine learning (ML)-based approaches. Data were normalized using the robust multiarray average method and batch effect were corrected using the ComBat method. Differentially expressed genes were identified by the LIMMA approach and carcinoma-associated genes were selected using Enrichr, based on the DisGeNET database. Protein-protein interaction (PPI) network analysis was performed using STRING, and the PPI network was visualized using Cytoscape. The core hub genes were identified by overlapping genes obtained from degree, betweenness, closeness, and MNC. Moreover, the MCODE plugin for Cytoscape was used to perform module analysis, and optimal modules were selected based on MCODE scores along with their associated genes. Subsequently, Boruta-based ML approach was utilized to identify the important genes. Consequently, the core genes were identified by the overlapping genes obtained from PPI networks, module analysis, and ML-based approach. The prognostic and discriminative power analysis of the core genes was assessed through survival and ROC analysis. We extracted five datasets from USA cohort and three datasets from Taiwan cohort and performed same experimental protocols to determine potential biomarkers. Four genes (LPL, CLDN18, EDNRB, MME) were identified from USA cohort, while three genes (DNRB, MME, ROBO4) were from Taiwan cohort. Finally, two biomarkers (EDNRB and MME) were identified by intersecting genes, obtained from USA and Taiwan cohorts. The proposed biomarkers can significantly improve patient outcomes by enabling earlier detection, precise diagnosis, and tailored treatment, ultimately contributing to better survival rates and quality of life for patients.

Increased SLC7A3 Expression Inhibits Tumor Cell Proliferation and Predicts a Favorable Prognosis in Breast Cancer

BACKGROUND

Arginine plays significant and contrasting roles in breast cancer growth and survival. However, the factors governing arginine balance remain poorly characterized.

OBJECTIVE

We aimed to identify the molecule that governs arginine metabolism in breast cancer and to elucidate its significance.

METHODS

We analyzed the correlation between the expression of solute carrier family 7 member 3 (SLC7A3), the major arginine transporter, and breast cancer survival in various databases, including GEPIA, UALCAN, Metascape, String, Oncomine, KM-plotter, CBioPortal and PrognoScan databases. Additionally, we validated our findings through bioinformatic analyses and experimental investigations, including colony formation, wound healing, transwell, and mammosphere formation assays.

RESULTS

Our analysis revealed a significant reduction in SLC7A3 expression in all breast cancer subtypes compared to adjacent breast tissues. Kaplan-Meier survival analyses demonstrated that high SLC7A3 expression was positively associated with decreased nodal metastasis (HR=0.70, 95% CI [0.55, 0.89]), ER positivity (HR=0.79, 95% CI [0.65, 0.95]), and HER2 negativity (HR=0.69, 95% CI [0.58, 0.82]), and increased recurrence-free survival. Moreover, low SLC7A3 expression predicted poor prognosis in breast cancer patients for overall survival. Additionally, the knockdown of SLC7A3 in MCF-7 and MDA-MB-231 cells resulted in increased cell proliferation and invasion in vitro.

CONCLUSION

Our findings indicate a downregulation of SLC7A3 expression in breast cancer tissues compared to adjacent breast tissues. High SLC7A3 expression could serve as a prognostic indicator for favorable outcomes in breast cancer patients due to its inhibitory effects on breast cancer cell proliferation and invasion.

Elucidating the prognostic and therapeutic significance of TOP2A in various malignancies

Topoisomerase IIα (TOP2A) is a crucial enzyme that plays a vital role in DNA replication and transcription mechanisms. Dysregulated expression of TOP2A has been associated with various malignancies, including hepatocellular carcinoma, prostate cancer, colon cancer, lung cancer and breast cancer. In this review, we summarized the prognostic relevances of TOP2A in various types of cancer. The increased expression of TOP2A has been linked to resistance to therapy and reduced survival rates. Therefore, evaluating TOP2A levels could assist in identifying patients who may derive advantages from molecular targeted therapy. The amplification of TOP2A has been linked to a positive response to chemotherapy regimens that contain anthracycline. Nevertheless, the overexpression of TOP2A also indicates a heightened likelihood of disease recurrence and unfavorable prognosis. The prognostic significance of TOP2A has been extensively studied in various types of cancer. The increased expression of TOP2A is associated with poor clinical outcomes, indicating its potential as a valuable biomarker for assessing risk and stratifying treatment in these malignancies. However, further investigation is needed to elucidate the underlying mechanisms by which TOP2A influences cancer progression and to explore its potential as a therapeutic target.

BUB1 Inhibition Overcomes Radio- and Chemoradiation Resistance in Lung Cancer

Background: Despite advances in targeted therapies and immunotherapies, traditional treatments like microtubule stabilizers (paclitaxel, docetaxel), DNA-intercalating platinum drugs (cisplatin), and radiation therapy remain essential for managing locally advanced and metastatic lung cancer. Identifying novel molecular targets could enhance the efficacy of these treatments. Hypothesis: We hypothesize that BUB1 (Ser/Thr kinase) is overexpressed in lung cancers and its inhibition will sensitize lung cancers to chemoradiation. Methods: BUB1 inhibitor (BAY1816032) was combined with cisplatin, paclitaxel, a PARP inhibitor olaparib, and radiation in cell proliferation and radiation-sensitization assays. Biochemical and molecular assays evaluated the impact on DNA damage signaling and cell death. Results: Immunostaining of lung tumor microarrays (TMAs) confirmed higher BUB1 expression in non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) compared to normal tissues. In NSCLC, BUB1 overexpression correlated directly with the expression of TP53 mutations and poorer overall survival in NSCLC and SCLC patients. BAY1816032 synergistically sensitized lung cancer cell lines to paclitaxel and olaparib and enhanced cell killing by radiation in both NSCLC and SCLC. Molecular analysis indicated a shift towards pro-apoptotic and anti-proliferative states, evidenced by altered BAX, BCL2, PCNA, and Caspases-9 and -3 expressions. Conclusions: Elevated BUB1 expression is associated with poorer survival in lung cancer. Inhibiting BUB1 sensitizes NSCLC and SCLC to chemotherapies (cisplatin, paclitaxel), targeted therapy (olaparib), and radiation. Furthermore, we present the novel finding that BUB1 inhibition sensitized both NSCLC and SCLC to radiotherapy and chemoradiation. Our results demonstrate BUB1 inhibition as a promising strategy to sensitize lung cancers to radiation and chemoradiation therapies.

BUB1 inhibition sensitizes lung cancer cell lines to radiotherapy and chemoradiotherapy

Background

Lung cancer is a major public health concern, with high incidence and mortality. Despite advances in targeted therapy and immunotherapy, microtubule stabilizers (paclitaxel, docetaxel), DNA intercalating platinum drugs (cisplatin) and radiation therapy continue to play a critical role in the management of locally advanced and metastatic lung cancer. Novel molecular targets would provide opportunities for improving the efficacies of radiotherapy and chemotherapy.

Hypothesis

We hypothesize that BUB1 (Ser/Thr kinase) is over-expressed in lung cancers and that its inhibition will sensitize lung cancers to chemoradiation.

Methods

BUB1 inhibitor (BAY1816032) was combined with platinum (cisplatin), microtubule poison (paclitaxel), a PARP inhibitor (olaparib) and radiation in cell proliferation and radiation sensitization assays. Biochemical and molecular assays were used to evaluate their impact on DNA damage signaling and cell death mechanisms.

Results

BUB1 expression assessed by immunostaining of lung tumor microarrays (TMAs) confirmed higher BUB1 expression in NSCLC and SCLC compared to that of normal tissues. BUB1 overexpression in lung cancer tissues correlated directly with expression of TP53 mutations in non-small cell lung cancer (NSCLC). Elevated BUB1 levels correlated with poorer overall survival in NSCLC and small cell lung cancer (SCLC) patients. A BUB1 inhibitor (BAY1816032) synergistically sensitized lung cancer cell lines to paclitaxel and olaparib. Additionally, BAY1816032 enhanced cell killing by radiation in both NSCLC and SCLC. Molecular changes following BUB1 inhibition suggest a shift towards pro-apoptotic and anti-proliferative states, indicated by altered expression of BAX, BCL2, PCNA, and Caspases 9 and 3.

Conclusion

A direct correlation between BUB1 protein expression and overall survival was shown. BUB1 inhibition sensitized both NSCLC and SCLC to various chemotherapies (cisplatin, paclitaxel) and targeted therapy (PARPi). Furthermore, we present the novel finding that BUB1 inhibition sensitized both NSCLC and SCLC to radiotherapy and chemoradiation. Our results demonstrate BUB1 inhibition as a promising strategy to sensitize lung cancers to radiation and chemoradiation therapies.

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation

Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

A 15-Gene-Based Risk Signature for Predicting Overall Survival in SCLC Patients Who Have Undergone Surgical Resection

Small cell lung cancer (SCLC) is a malignancy with a poor prognosis whose treatment has not progressed for decades. The survival benefit of surgery and the selection of surgical candidates are still controversial in SCLC. This study is the first report to identify transcriptomic alterations associated with prognosis and propose a gene expression-based risk signature that can be used to predict overall survival (OS) in SCLC patients who have undergone potentially curative surgery. An integrative transcriptome analysis of three gene expression datasets (GSE30219, GSE43346, and GSE149507) revealed 1734 up-regulated and 2907 down-regulated genes. Cox-Mantel test, Cox regression, and Lasso regression analyses were used to identify genes to be included in the risk signature. EGAD00001001244 and GSE60052-cohorts were used for internal and external validation, respectively. Overall survival was significantly poorer in patients with high-risk scores compared to the low-risk group. The discriminatory performance of the risk signature was superior to other parameters. Multivariate analysis showed that the risk signature has the potential to be an independent predictor of prognosis. The prognostic genes were enriched in pathways including regulation of transcription, cell cycle, cell metabolism, and angiogenesis. Determining the roles of the identified prognostic genes in the pathogenesis of SCLC may contribute to the development of new treatment strategies. The risk signature needs to be validated in a larger cohort of patients to test its usefulness in clinical decision-making.

Analysis of two-gene signatures and related drugs in small-cell lung cancer by bioinformatics

Small-cell lung cancer (SCLC) has a poor prognosis and can be diagnosed with systemic metastases. Nevertheless, the molecular mechanisms underlying the development of SCLC are unclear, requiring further investigation. The current research aims to identify relevant biomarkers and available drugs to treat SCLC. The bioinformatics analysis comprised three Gene Expression Omnibus datasets (including GSE2149507, GSE6044, and GSE30219). Using the limma R package, we discovered differentially expressed genes (DEGs) in the current work. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were made by adopting the DAVID website. The DEG protein-protein interaction network was built based on the Search Tool for the Retrieval of Interacting Genes/Proteins website and visualized using the CytoHubba plugin in Cytoscape, aiming to screen the top ten hub genes. Quantitative real-time polymerase chain reaction was adopted for verifying the level of the top ten hub genes. Finally, the potential drugs were screened and identified using the QuartataWeb database. Totally 195 upregulated and 167 downregulated DEGs were determined. The ten hub genes were NCAPG, BUB1B, TOP2A, CCNA2, NUSAP1, UBE2C, AURKB, RRM2, CDK1, and KIF11. Ten FDA-approved drugs were screened. Finally, two genes and related drugs screened could be the prospective drug targets for SCLC treatment.

UPS: Opportunities and challenges for gastric cancer treatment

Gastric cancer remains the fourth most frequently diagnosed malignancy and the fifth leading cause of cancer-related mortality worldwide owning to the lack of efficient drugs and targets for therapy. Accumulating evidence indicates that UPS, which consists of E1, E2, and E3 enzymes and proteasome, plays an important role in the GC tumorigenesis. The imbalance of UPS impairs the protein homeostasis network during development of GC. Therefore, modulating these enzymes and proteasome may be a promising strategy for GC target therapy. Besides, PROTAC, a strategy using UPS to degrade the target protein, is an emerging tool for drug development. Thus far, more and more PROTAC drugs enter clinical trials for cancer therapy. Here, we will analyze the abnormal expression enzymes in UPS and summarize the E3 enzymes which can be developed in PROTAC so that it can contribute to the development of UPS modulator and PROTAC technology for GC therapy.

The Bidirectional Relationship between Pulmonary Tuberculosis and Lung Cancer

Lung cancer and pulmonary tuberculosis are two significant public health problems that continue to take millions of lives each year. They may have similar symptoms and, in some cases, are diagnosed simultaneously or may have a causal relationship. In tuberculosis disease, the chronic inflammation, different produced molecules, genomic changes, and fibrosis are believed to be important factors that may promote carcinogenesis. As a reverse reaction, the development of carcinogenesis and the treatment may induce the reactivation of latent tuberculosis infection. Moreover, the recently used checkpoint inhibitors are a debatable subject since they help treat lung cancer but may lead to the reactivation of pulmonary tuberculosis and checkpoint-induced pneumonitis. Pulmonary rehabilitation is an effective intervention in post-tuberculosis patients and lung cancer patients and should be recommended to improve outcomes in these pathologies.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

BACKGROUND

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

METHODS

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

RESULTS

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

CONCLUSION

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.