Non-small cell lung cancer: Emerging molecular targeted and immunotherapeutic agents

Advances in pharmacological effects and mechanism of action of cinnamaldehyde

Cinnamaldehyde is extracted from Cinnamomum cassia and other species, providing diverse sources for varying chemical properties and therapeutic effects. Besides natural extraction, synthetic production and biotechnological methods like microbial fermentation offer scalable and sustainable alternatives. Cinnamaldehyd demonstrates a broad pharmacological range, impacting various diseases through detailed mechanisms. This review aims to encapsulate the diverse therapeutic effects of cinnamaldehyde, its molecular interactions, and its potential in clinical applications. Drawing on recent scientific studies and databases like Web of Science, PubMed, and ScienceDirect, this review outlines cinnamaldehyde's efficacy in treating inflammatory conditions, bacterial infections, cancer, diabetes, and cardiovascular and kidney diseases. It primarily operates by inhibiting the NF-κB pathway and modulating pro-inflammatory mediators, alongside disrupting bacterial cells and inducing apoptosis in cancer cells. The compound enhances metabolic health by improving glucose uptake and insulin sensitivity and offers cardiovascular protection through its anti-inflammatory and lipid-lowering effects. Additionally, it promotes autophagy in kidney disease management. Preclinical and clinical research supports its therapeutic potential, underscoring the need for further investigation into its mechanisms and safety to develop new drugs based on cinnamaldehyde.

Identifying an immunogenic cell death-related gene signature contributes to predicting prognosis, immunotherapy efficacy, and tumor microenvironment of lung adenocarcinoma

BACKGROUND

Immunogenic cell death (ICD) is a regulated form of cell death that triggers an adaptive immune response. The objective of this study was to investigate the correlation between ICD-related genes (ICDGs) and the prognosis and the immune microenvironment of patients with lung adenocarcinoma (LUAD).

METHODS

ICD-associated molecular subtypes were identified through consensus clustering. Subsequently, a prognostic risk model comprising 5 ICDGs was constructed using Lasso-Cox regression in the TCGA training cohort and further tested in the GEO cohort. Enriched pathways among the subtypes were analyzed using GO, KEGG, and GSVA. Furthermore, the immune microenvironment was assessed using ESTIMATE, CIBERSORT, and ssGSEA analyses.

RESULTS

Consensus clustering divided LUAD patients into three ICDG subtypes with significant differences in prognosis and the immune microenvironment. A prognostic risk model was constructed based on 5 ICDGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of tumor purity. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor. The five hub genes were verified by TCGA database, cell sublocalization immunofluorescence analysis, IHC images and qRT-PCR, which were consistent with bioinformatics analysis.

CONCLUSIONS

The molecular subtypes and a risk model based on ICDGs proposed in our study are both promising prognostic classifications in LUAD, which may provide novel insights for developing accurate targeted cancer therapies.

Molecular map of disulfidptosis-related genes in lung adenocarcinoma: the perspective toward immune microenvironment and prognosis

BACKGROUND

Disulfidptosis is a recently discovered form of programmed cell death that could impact cancer development. Nevertheless, the prognostic significance of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) requires further clarification.

METHODS

This study systematically explores the genetic and transcriptional variability, prognostic relevance, and expression profiles of DRGs. Clusters related to disulfidptosis were identified through consensus clustering. We used single-sample gene set enrichment analysis and ESTIMATE to assess the tumor microenvironment (TME) in different subgroups. We conducted a functional analysis of differentially expressed genes between subgroups, which involved gene ontology, the Kyoto encyclopedia of genes and genomes, and gene set variation analysis, in order to elucidate their functional status. Prognostic risk models were developed using univariate Cox regression and the least absolute shrinkage and selection operator regression. Additionally, single-cell clustering and cell communication analysis were conducted to enhance the understanding of the importance of signature genes. Lastly, qRT-PCR was employed to validate the prognostic model.

RESULTS

Two clearly defined DRG clusters were identified through a consensus-based, unsupervised clustering analysis. Observations were made concerning the correlation between changes in multilayer DRG and various clinical characteristics, prognosis, and the infiltration of TME cells. A well-executed risk assessment model, known as the DRG score, was developed to predict the prognosis of LUAD patients. A high DRG score indicates increased TME cell infiltration, a higher mutation burden, elevated TME scores, and a poorer prognosis. Additionally, the DRG score showed a significant correlation with the tumor mutation burden score and the tumor immune dysfunction and exclusion score. Subsequently, a nomogram was established for facilitating the clinical application of the DRG score, showing good predictive ability and calibration. Additionally, crucial DRGs were further validated by single-cell sequencing data. Finally, crucial DRGs were further validated by qRT-PCR and immunohistochemistry.

CONCLUSION

Our new DRG signature risk score can predict the immune landscape and prognosis of LUAD. It also serves as a reference for LUAD's immunotherapy and chemotherapy.

A Pluripotential Neutrophil-Mimic Nanovehicle Modulates Immune Microenvironment with Targeted Drug Delivery for Augmented Antitumor Chemotherapy

The limited therapeutic outcomes and severe systemic toxicity of chemotherapy remain major challenges to the current clinical antitumor therapeutic regimen. Tumor-targeted drug delivery that diminishes the undifferentiated systemic distribution is a practical solution to ameliorating systemic toxicity. However, the tumor adaptive immune microenvironment still poses a great threat that compromises the therapeutic efficacy of chemotherapy by promoting the tolerance of the tumor cells. Herein, a pluripotential neutrophil-mimic nanovehicle (Neutrosome(L)) composed of an activated neutrophil membrane-incorporated liposome is proposed to modulate the immune microenvironment and synergize antitumor chemotherapy. The prominent tumor targeting capability inherited from activated neutrophils and the improved tumor penetration ability of Neutrosome(L) enable considerable drug accumulation in tumor tissues (more than sixfold that of free drug). Importantly, Neutrosome(L) can modulate the immune microenvironment by restricting neutrophil infiltration in tumor tissue, which may be attributed to the neutralization of inflammatory cytokines, thus potentiating antitumor chemotherapy. As a consequence, the treatment of cisplatin-loaded Neutrosome(L) performs prominent tumor suppression effects, reduces systemic drug toxicity, and prolongs the survival period of tumor-bearing mice. The pluripotential neutrophil-mimic nanovehicle proposed in this study can not only enhance the tumor accumulation of chemotherapeutics but also modulate the immune microenvironment, providing a compendious strategy for augmented antitumor chemotherapy.

Integrative analysis of single-cell and bulk RNA-sequencing data revealed disulfidptosis genes-based molecular subtypes and a prognostic signature in lung adenocarcinoma

BACKGROUND

Disulfidoptosis is an unconventional form of programmed cell death that distinguishes itself from well-established cell death pathways like ferroptosis, pyroptosis, and necroptosis.

METHODS

Initially, we conducted a single-cell analysis of the GSE131907 dataset from the GEO database to identify disulfidoptosis-related genes (DRGs). We utilized differentially expressed DRGs to classify TCGA samples with an unsupervised clustering algorithm. Prognostic models were built using Cox regression and LASSO regression.

RESULTS

Two DRG-related clusters (C1 and C2) were identified based on the DEGs from single-cell sequencing data analysis. In comparison to C1, C2 exhibited significantly worse overall prognosis, along with lower expression levels of immune checkpoint genes (ICGs) and chemoradiotherapy sensitivity-related genes (CRSGs). Furthermore, C2 displayed a notable enrichment in metabolic pathways and cell cycle-associated mechanisms. C2 was also linked to the development and spread of tumors. We created a prognostic risk model known as the DRG score, which relies on the expression levels of five DRGs. Patients were categorized into high-risk and low-risk groups depending on their DRG score, with the former group being linked to a poorer prognosis and higher TMB score. Moreover, the DRG score displayed significant correlations with CRSGs, ICGs, the tumor immune dysfunction and exclusion (TIDE) score, and chemotherapeutic sensitivity. Subsequently, we identified a significant correlation between the DRG score and monocyte macrophages. Additionally, crucial DRGs were additionally validated using qRT-PCR.

CONCLUSIONS

Our new DRG score can predict the immune landscape and prognosis of LUAD, serving as a reference for immunotherapy and chemotherapy.

ALKBH5 regulates paclitaxel resistance in NSCLC via inhibiting CEMIP-mediated EMT

N6-methyladenosine (m6A) is the most prevalent mRNA modification, and it is verified to be closely correlated with cancer occurrence and progression. The m6A demethylase ALKBH5 (alkB homolog 5) is dysregulated in various cancers. However, the role and underlying mechanism of ALKBH5 in the pathogenesis and especially the chemo-resistance of non-small cell lung cancer (NSCLC) is poorly elucidated. The current study shows that ALKBH5 expression is reduced in paclitaxel (PTX) resistant NSCLC cells and down-regulation of ALKBH5 usually implies poor prognosis of NSCLC patients. Over-expression of ALKBH5 in PTX-resistant cells can suppress cell proliferation and enhance chemo-sensitivity, while knockdown of ALKBH5 exerts the opposite effect, which further supports the tumor suppressive role of ALKBH5. Over-expression of ALKBH5 can also reverse the epithelial-mesenchymal transition (EMT) process in PTX-resistant cancer cells. Mechanistically, data from RNA-seq, real-time PCR and western blotting indicate that CEMIP (cell migration inducing hyaluronidase 1), also known as KIAA1199, may be the downstream target of ALKBH5. Furthermore, ALKBH5 negatively regulates the CEMIP level by reducing the stability of CEMIP mRNA. Collectively, the current data demonstrate that the ALKBH5/CEMIP axis modulates the EMT process in NSCLC, which in turn regulates the chemo-sensitivity of cancer cells to PTX.

Pulmonary Adenocarcinoma Patient with Complex Mutations on EGFR Benefits from Furmonertinib after Acquiring Gefitinib Resistance: A Case Report

BACKGROUND

Although epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have been proven a long-lasting treatment effect in pulmonary adenocarcinoma, most patients still progressed within one year due to the acquired resistance. Complex mutations of rare rare sites after acquiring resistance are rarely reported in pulmonary adenocarcinoma.

CASE PRESENTATION

A 62-year-old woman was diagnosed with pulmonary adenocarcinoma with stage IV. Genetic testing at the initial treatment showed EGFR L858R positive. After being treated with gefitinib, persistent 2 years disease progression occurred due to drug resistance. The genetic testing showed that EGFR L858R was eliminated, while a rare rare complex mutation of L861Q/G719X appeared. After 160 mg furmonertinib was treated for 1 month, the primary tumor regressed and the intracranial lesions disappeared. The patient has achieved progression-free survival (PFS) for more than 20 months.

CONCLUSION

Pulmonary adenocarcinoma with rare rare complex mutations in EGFR induced by gefitinib resistance and disease progression might benefit from furmonertinib treatment.

Sclareol induces cell cycle arrest and ROS-mediated apoptosis and ferroptosis in lung adenocarcinoma cells

Sclareol (SC) has shown significant anticancer activity against breast and colon cancers among others. However, its ability to precipitate similar anticancer effects in lung cancer has yet to be investigated. To address this issue, SC-treated lung adenocarcinoma cells (A549) were assessed for viability and functional competence as well as the expression of genes related to apoptosis and cell cycling. Our results demonstrated that SC treatment inhibited A549 cell clonogenic features and reduced their migration and invasion potential in a dose-dependent manner. Mechanistically, SC treatment downregulated the expression of cyclin D1 and survivin and upregulated that of p21 and p16, which was associated with a significant increase in the percentage of SubG0 cells. SC treatment is also associated with the induction of both the extrinsic and intrinsic apoptotic pathways, as evidenced by the increased expression and splitting of PARP1 and procaspases 3 and 9 and the reduced expression of antiapoptotic proteins Bcl-2 and Bcl-xL. Increased cell death in SC-treated cells is likely to have resulted from the induction of ferroptosis as suggested by the reduced expression of FPN and the inhibition of the anti-ferroptosis regulator GPX4. In conclusion, the data presented here suggest that SC can reduce lung carcinoma cell growth and metastasis and promote cell death.

Advances and challenges in the treatment of lung cancer

Lung cancer accounts for a relatively high proportion of malignant tumors. As the most prevalent type of lung cancer, non-small cell lung cancer (NSCLC) is characterized by high morbidity and mortality. Presently, the arsenal of treatment strategies encompasses surgical resection, chemotherapy, targeted therapy and radiotherapy. However, despite these options, the prognosis remains distressingly poor with a low 5-year survival rate. Therefore, it is urgent to pursue a paradigm shift in treatment methodologies. In recent years, the advent of sophisticated biotechnologies and interdisciplinary integration has provided innovative approaches for the treatment of lung cancer. This article reviews the cutting-edge developments in the nano drug delivery system, molecular targeted treatment system, photothermal treatment strategy, and immunotherapy for lung cancer. Overall, by systematically summarizing and critically analyzing the latest progress and current challenges in these treatment strategies of lung cancer, we aim to provide a theoretical basis for the development of novel drugs for lung cancer treatment, and thus improve the therapeutic outcomes for lung cancer patients.

Integration of liquid biopsy and immunotherapy: opening a new era in colorectal cancer treatment

Immunotherapy has revolutionized the conventional treatment approaches for colorectal cancer (CRC), offering new therapeutic prospects for patients. Liquid biopsy has shown significant potential in early screening, diagnosis, and postoperative monitoring by analyzing circulating tumor cells (CTC) and circulating tumor DNA (ctDNA). In the era of immunotherapy, liquid biopsy provides additional possibilities for guiding immune-based treatments. Emerging technologies such as mass spectrometry-based detection of neoantigens and flow cytometry-based T cell sorting offer new tools for liquid biopsy, aiming to optimize immune therapy strategies. The integration of liquid biopsy with immunotherapy holds promise for improving treatment outcomes in colorectal cancer patients, enabling breakthroughs in early diagnosis and treatment, and providing patients with more personalized, precise, and effective treatment strategies.

Gene set variation analysis-based aging and senescence score as a prognostic indicator and therapeutic guide in lung adenocarcinoma

Accumulating evidence suggests that aging and senescence play crucial roles in tumorigenesis, cancer progression, and treatment. However, the influence of aging and senescence-related genes (ASRGs) on clinical outcomes and treatment options in lung adenocarcinoma (LUAD) patients remains unknown. Here, we developed an aging and senescence-related scoring system, ASRS, by integrating bulk transcriptome data from 22 LUAD datasets. In 3,243 LUAD samples, higher ASRS scores were associated with poor tumor stage and pathological grade, as well as shorter overall survival, disease-free survival, and recurrence-free survival. Additionally, ASRS was associated with different immune patterns in the tumor microenvironment (TME). Importantly, ASRS was found to predict therapeutic efficacy, with patients having a low ASRS benefiting from immunotherapy and those with a high ASRS responding better to chemotherapy. Therefore, ASRS represents a previously overlooked characteristic of LUAD that can influence patient outcomes and treatment success.

LncRNA DGUOK-AS1 facilitates non-small cell lung cancer growth and metastasis through increasing TRPM7 stability via m6A modification

BACKGROUND

N6-methyladenosine (m6A) modification plays key roles in tumor progression. LncRNA deoxyguanosine kinase antisense RNA 1 (DGUOK-AS1) has been reported as a promoter in tumors, but its role and mechanism in non-small cell lung cancer (NSCLC) development remain uncertain.

METHODS

Cell proliferation, migration, invasion and angiogenesis were investigated via CCK-8, colony formation, transwell, and tube formation assays, respectively. The location of DGUOK-AS1 was detected via FISH assay. The interaction relationship among DGUOK-AS1, IGF2BP2 and TRPM7 was confirmed by RIP and MeRIP assays. The effects of DGUOK-AS1 on NSCLC growth and metastasis in vivo were investigated using xenograft and pulmonary metastatic models.

RESULTS

DGUOK-AS1 was upregulated in NSCLC. DGUOK-AS1 silencing inhibited NSCLC cell proliferation, migration, invasion and angiogenesis. DGUOK-AS1 was mostly expressed in cytoplasm, and positively regulated IGF2BP2. METTL3/IGF2BP2 axis could increase TRPM7 mRNA stability in m6A-dependent manner. TRPM7 overexpression reversed the inhibitive function of DGUOK-AS1 silencing on NSCLC development. DGUOK-AS1 knockdown suppressed NSCLC cell growth and metastasis in nude mice.

CONCLUSION

DGUOK-AS1 silencing restrains NSCLC cell growth and metastasis through decreasing TRPM7 stability via regulation of the METTL3/IGF2BP2-mediated m6A modification.

Budding uninhibited by benzimidazoles 1 overexpression is associated with poor prognosis and malignant phenotype: A promising therapeutic target for lung adenocarcinoma

BACKGROUND

The budding uninhibited by benzimidazoles (BUB) family is involved in the cell cycle process as mitotic checkpoint components. Abnormal proliferation is a vital process in the development of lung adenocarcinoma (LUAD). Nevertheless, the roles of BUB1 in LUAD remain unclear. In this study, we evaluated the prognostic value and biological functions of BUB1 in LUAD using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), clinical LUAD samples, and in vitro experiments.

METHODS

The expression, prognostic significance, functions, immune infiltration, and methylation of BUB1 in LUAD were comprehensively analyzed using TCGA, GEO, Gene Expression Profiling Interactive Analysis, Metascape, cBioPortal, MethSurv, and cancerSEA databases. Furthermore, we performed a battery of in vitro experiments and immunohistochemistry (IHC) to verify the bioinformatics results.

RESULTS

Multivariate analysis revealed that BUB1 overexpression was an independent prognostic factor (hazard ratio = 1.499, p = 0.013). Functional enrichment analysis showed that BUB1 was correlated with cell cycle, proliferation, DNA repair, DNA damage, and invasion (p < 0.05). Finally, in vitro experiments showed that downregulation of BUB1 inhibited the proliferation, migration, and invasion of LUAD cells and promoted LUAD cell apoptosis. IHC also showed that BUB1 was overexpressed in LUAD (p < 0.001) and was significantly associated with poor prognosis (p < 0.001).

CONCLUSIONS

Our bioinformatics and IHC analyses revealed that BUB1 overexpression was an adverse prognostic factor in LUAD. In vitro experiments demonstrated that BUB1 promoted tumor cell proliferation, migration, and invasion in LUAD. These results indicated that BUB1 was a promising biomarker and potential therapeutic target in LUAD.

CircCCDC66: Emerging roles and potential clinical values in malignant tumors

Circular RNAs (circRNAs) are endogenous non-coding RNAs (ncRNAs) with a closed-loop structure. In recent years, circRNAs have become the focus of much research into RNA. CircCCDC66 has been identified as a novel oncogenic circRNA and is up-regulated in a variety of malignant tumors including thyroid cancer, non-small cell carcinoma, gastric cancer, colorectal cancer, renal cancer, cervical cancer, glioma, and osteosarcoma. It mediates cancer progression by regulating epigenetic modifications, variable splicing, transcription, and protein translation. The oncogenicity of circCCDC66 suppresses or promotes the expression of related genes mainly through direct or indirect pathways. This finding suggests that circCCDC66 is a biomarker for cancer diagnosis, prognosis assessment and treatment. However, there is no review on the relationship between circCCDC66 and cancers. Thus, the expression, biological functions, and regulatory mechanisms of circCCDC66 in malignant tumor and non-tumor diseases are summarized. The clinical value and prognostic significance of circCCDC66 are also evaluated, which can provide insights helpful to those exploring new strategies for the early diagnosis and targeted treatment of malignancies.

Circ_0007534 as new emerging target in cancer: Biological functions and molecular interactions

Circular RNA (circRNAs), an important member of the non-coding RNA (ncRNA) family, are widely expressed in a variety of biological cells. Owing to their stable structures, sequence conservations, and cell- or tissue-specific expressions, these RNA have become a popular subject of scientific research. With the development of sequencing methods, it has been revealed that circRNAs exert their biological function by sponging microRNAs (miRNAs), regulating transcription, or binding to proteins. Humans have historically been significantly impacted by various types of cancer. Studies have shown that circRNAs are abnormally expressed in various cancers and are involved in the occurrence and development of malignant tumors, such as tumor cell proliferation, migration, and invasion. As one of its star molecules, circ_0007534 is upregulated in colorectal, cervical, and pancreatic cancers; is closely related to the occurrence, development, and prognosis of tumors; and is expected to become a novel tumor marker and therapeutic target. This article briefly reviews the expression and mechanism of circ_0007534 in malignant tumors based on the domestic and foreign literature.

Integrative Analysis of Bioinformatics and Machine Learning Algorithms Identifies a Novel Diagnostic Model Based on Costimulatory Molecule for Predicting Immune Microenvironment Status in Lung Adenocarcinoma

Costimulatory molecules are an indispensable signal for activating immune cells. However, the features of many costimulatory molecule genes (CMGs) in lung adenocarcinoma (LUAD) are poorly understood. This study systematically explored expression patterns of CMGs in the tumor immune microenvironment (TIME) status of patients with LUAD. Their expression profiles were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Two robust TIME subtypes ("hot" and "cold") were classified by K-means clustering and estimation of stromal and immune cells in malignant tumor tissues using expression data. The "hot" subtype presented higher infiltration in activated immune cells and enrichments in the immune cell receptor signaling pathway and adaptive immune response. Three CMGs (CD80, LTB, and TNFSF8) were screened as final diagnostic markers by means of Least Absolute Shrinkage Selection Operator and Support Vector Machine-Recursive Feature Elimination algorithms. Accordingly, the diagnostic nomogram for predicting individualized TIME status showed satisfactory diagnostic accuracy in The Cancer Genome Atlas training cohort as well as GSE31210 and GSE180347 validation cohorts. Immunohistochemistry staining of 16 specimens revealed an apparently positive correlation between the expression of CMG biomarkers and pathologic response to immunotherapy. Thus, this diagnostic nomogram provided individualized predictions in TIME status of LUAD patients with good predictive accuracy, which could serve as a potential tool for identifying ideal candidates for immunotherapy.

Evolutions in the management of non-small cell lung cancer: A bibliometric study from the 100 most impactful articles in the field

Objective

The study was designed to explore the evolution of non-small cell lung cancer (NSCLC) management in the last 20 years.

Methods

The top 100 most-cited papers on NSCLC treatment were retrieved from the Web of Science Core Collection database. R and VOSviewer were used to extract bibliographic information, including the year of publication, countries/regions, institutions, authors, journals, keywords, impact factor, and total citations. The topic and type of papers were checked independently by authors. Bibliometric analysis was conducted and visualized with R, CiteSpace, Excel and VOSviewer to identify output dynamics, research forces, topics, hotspots, and frontiers in the field.

Results

The average citation of each retrieved top 100 most-cited NSCLC management papers was 1,725 (range: 615-7,340). Fifty-seven corresponding authors were from the United States. This country contributed the most papers (n=76), followed by Germany (n=34), France (n=33), and South Korea (n=32). The top contributors were Paz-Ares L. (n=12) and Reck M. (n=12). The Memorial Sloan Kettering Cancer Center published the largest number of papers (n=20). There were two significant citation paths, indicating publications in medicine/medical/clinical journals primarily cited journals in molecular/biology/genetics fields, partly cited health/nursing/medicine fields. Top-cited papers mainly came from the New England Journal of Medicine (n=33, citations=80,427), followed closely by the Journal of Clinical Oncology (n=28, citations=32,408). “Chemotherapy” (n=36) was the keyword with the greatest frequency of co-occurrence. “Open-label” was the keyword with the strongest burst strength (=4.01), followed by “nivolumab” (=3.85), “blockade” (=2.86), and “efficacy” (=2.85).

Conclusions

The United States as a nation and the Memorial Sloan Kettering Cancer Center as an institute contributed the most to this field. The New England Journal of Medicine is the most eye-catching journal. Hotspots of NSCLC management have almost undergone an evolution from chemotherapy and radiotherapy to targeted therapy to immunotherapy. Molecular/biological/genetic fields become the main research base for NSCLC treatment. Immunotherapy and combination therapy are research frontiers.

Significant metabolic alterations in non-small cell lung cancer patients by epidermal growth factor receptor-targeted therapy and PD-1/PD-L1 immunotherapy

Background: Cancer-related deaths are primarily attributable to lung cancer, of which non-small cell lung cancer (NSCLC) is the most common type. Molecular targeting therapy and antitumor immunotherapy have both made great strides in the treatment of NSCLC, but their underlying mechanisms remain unclear, especially from a metabolic perspective.

Methods: Herein, we used a nontargeted metabolomics approach based on liquid chromatography-mass spectrometry to analyze the metabolic response of NSCLC patients to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) or PD-1/PD-L1 inhibitors. Multiple analyses, including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA) and pathway analysis, were used for metabolic data analysis. Additionally, differential metabolites were analysed and identified by publically available and integrated databases.

Results: After treatment with EGFR-TKIs or PD-1/PD-L1 inhibitors, glutamate/glutamine, phenylalanine, n-acetyl-l-leucine, n-acetyl-d-tryptophan, D-n-valine, arachidonic acid, and linoleic acid levels were significantly increased in patients with NSCLC, whereas carnitine, stearyl carnitine, palmitoyl carnitine, linoleic carnitine, and palmitic acid levels were markedly decreased. Compared with newly diagnosed, untreated patients, there were three shared metabolic pathways (phenylalanine metabolism, glycerophospholipid metabolism, and D-glutamine and D-glutamate metabolism) in the EGFR-TKIs or PD-1/PD-L1 inhibitor-treated groups, all of which were related to lipid and amino acid metabolism. Moreover, there were significant differences in lipid metabolism (glycerophospholipid metabolism and phosphatidylinositol signaling) and amino acid metabolism (tryptophan metabolism) between the EGFR-TKI and PD-1/PD-L1 inhibitor groups.

Conclusion: Our results show that EGFR-TKIs and PD-1/PD-L1 inhibitors induce changes in carnitine, amino acids, fatty acids, and lipids and alter related metabolic pathways in NSCLC patients. Endogenous metabolism changes occur due to drug action and might be indicative of antitumor therapeutic effect. These findings will provide new clues for identifying the antitumor mechanism of these two treatments from the perspective of metabolism.

Cratoxylumxanthone C, a natural xanthone, inhibits lung cancer proliferation and metastasis by regulating STAT3 and FAK signal pathways

To discover phytochemicals as lead compounds for cancer treatment, cratoxylumxanthone C, a natural xanthone, was obtained from Cratoxylum cochinchinense (Lour.) Bl., for which there have been no reports on the biological effects against cancer. Our study revealed that cratoxylumxanthone C had significant anti-tumor activity by inducing apoptosis, augmenting cellular reactive oxygen species (ROS), and arresting cell circle. The mechanistic examination showed the inhibition of A549 cell proliferation and metastasis by cratoxylumxanthone C was coupled with the signal transducer and activator of transcription 3 (STAT3) and focal adhesion kinase (FAK) signaling pathways. Furthermore, the zebrafish models confirmed its significant in vivo anti-tumor activity, in which cratoxylumxanthone C inhibited tumor proliferation and metastasis and suppressed the angiogenesis. Comprehensively, these cellular and zebrafish experiments implied that cratoxylumxanthone C may have the potential to become an anti-tumor agent for lung cancer, especially non-small cell lung cancer (NSCLC).

Identification of an Exosome-Related Signature for Predicting Prognosis, Immunotherapy Efficacy, and Tumor Microenvironment in Lung Adenocarcinoma

Accumulating evidence suggests that exosomes can affect lung adenocarcinoma (LUAD) progression. However, there is still a lack of understanding of the global influence of exosome-related genes (ERGs) on prognostic relevance, tumor microenvironment features, and immunotherapy responsiveness in patients with LUAD. In the TCGA dataset, differential analysis of 490 LUAD samples and 59 normal samples yielded 30 ERGs with differential expression. We have created a predictive signature based on 10 overall survival (OS)-related ERGs and confirmed it in two external cohorts (GSE72094 and GSE68465) via the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis in the TCGA dataset. The new signature revealed superior robustness and prognostic capacity for overall patient survival. Univariate and multivariate Cox regression analyses indicated that this signature was an independent risk factor for survival in patients with LUAD. In addition, for predicting the 1-year, 3-year, and 5-year OS of LUAD patients, we developed a nomogram and confirmed its predictive ability via the C-index and calibration curve. In addition, patients categorized by risk score exhibited distinct immunological states, stemness index, immune subtypes, and immunotherapy response. In conclusion, we created a risk signature for LUAD that was tightly associated with the immune landscape and therapeutic response. Also, such a risk signature effectively promotes the ability of the clinicians in making more precise and individualized treatment recommendations for patients with LUAD.

Prediction of EGFR Mutation Status in Non–Small Cell Lung Cancer Based on Ensemble Learning

Objectives: We aimed to identify whether ensemble learning can improve the performance of the epidermal growth factor receptor (EGFR) mutation status predicting model.

Methods: We retrospectively collected 168 patients with non–small cell lung cancer (NSCLC), who underwent both computed tomography (CT) examination and EGFR test. Using the radiomics features extracted from the CT images, an ensemble model was established with four individual classifiers: logistic regression (LR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost). The synthetic minority oversampling technique (SMOTE) was also used to decrease the influence of data imbalance. The performances of the predicting model were evaluated using the area under the curve (AUC).

Results: Based on the 26 radiomics features after feature selection, the SVM performed best (AUCs of 0.8634 and 0.7885 on the training and test sets, respectively) among four individual classifiers. The ensemble model of RF, XGBoost, and LR achieved the best performance (AUCs of 0.8465 and 0.8654 on the training and test sets, respectively).

Conclusion: Ensemble learning can improve the model performance in predicting the EGFR mutation status of patients with NSCLC, showing potential value in clinical practice.

Salvianolic Acid B Suppresses Non-Small-Cell Lung Cancer Metastasis through PKM2-Independent Metabolic Reprogramming

Objective

Salvianolic acid B (Sal B) has been demonstrated to be a potential chemoprevention agent for several cancers. Herein, we investigated the pharmacological function of Sal B on non-small-cell lung cancer (NSCLC) metastasis.

Methods

Two NSCLC cell lines (NCI-H2030 and NCI-H1650) were disposed of by 200 μM Sal B or 10 μM PKM2 agonist TEPP-46. Wound healing and transwell experiments were implemented for analyzing migratory and invasive capacities. Epithelial-to-mesenchymal transition (EMT) markers β-catenin and E-cadherin were measured via western blotting. Cellular bioenergetics were evaluated with glucose uptake, lactate production, enolase activity, cellular ATP levels, as well as seahorse-based oxygen consumption rate (OCR), extracellular acidification rate (ECAR) analysis. Metabolic reprogramming markers PKM2, LDHA, and GLUT1 were detected via western blotting and immunofluorescence.

Results

The results showed that Sal B disposal weakened the migration and invasion of NCI-H2030 and NCI-H1650 cells and inactivated the EMT process according to downregulation of β-catenin and upregulation of E-cadherin. Sal B-treated NSCLC cells displayed decreased glucose uptake, lactate production, enolase activity, cellular ATP levels, OCR, and ECAR, indicating a reduction in metabolic reprogramming. Additionally, Sal B downregulated the expression of PKM2, LDHA, and GLUT1. TEPP-46 may reverse the inhibitory effect of Sal B on metastasis as well as metabolic reprogramming.

Conclusion

Our findings provide evidence that Sal B enables to weaken NSCLC metastasis through PKM2-independent metabolic reprogramming, which sheds light on the promising therapeutic usage of Sal B in treating NSCLC.

Liquid biopsy in lung cancer: significance in diagnostics, prediction, and treatment monitoring

Primary lung cancer is one of the most common malignant tumors in China. Approximately 60% of lung cancer patients have distant metastasis at the initial diagnosis, so it is necessary to find new tumor markers for early diagnosis and individualized treatment. Tumor markers contribute to the early diagnosis of lung cancer and play important roles in early detection and treatment, as well as in precision medicine, efficacy monitoring, and prognosis prediction. The pathological diagnosis of lung cancer in small biopsy specimens determines whether there are tumor cells in the biopsy and tumor type. Because biopsy is traumatic and the compliance of patients with multiple biopsies is poor, liquid biopsy has become a hot research direction. Liquid biopsies are advantageous because they are nontraumatic, easy to obtain, reflect the overall state of the tumor, and allow for real-time monitoring. At present, liquid biopsies mainly include circulating tumor cells, circulating tumor DNA, exosomes, microRNA, circulating RNA, tumor platelets, and tumor endothelial cells. This review introduces the research progress and clinical application prospect of liquid biopsy technology for lung cancer.

A novel diagnostic model for predicting immune microenvironment subclass based on costimulatory molecules in lung squamous carcinoma

There is still no ideal predictive biomarker for immunotherapy response among patients with non-small cell lung cancer. Costimulatory molecules play a role in anti-tumor immune response. Hence, they can be a potential biomarker for immunotherapy response. The current study comprehensively investigated the expression of costimulatory molecules in lung squamous carcinoma (LUSC) and identified diagnostic biomarkers for immunotherapy response. The costimulatory molecule gene expression profiles of 627 patients were obtained from the The Cancer Genome Atlas, GSE73403, and GSE37745 datasets. Patients were divided into different clusters using the k-means clustering method and were further classified into two discrepant tumor microenvironment (TIME) subclasses (hot and cold tumors) according to the immune score of the ESTIMATE algorithm. A high proportion of activated immune cells, including activated memory CD4 T cells, CD8 T cells, and M1 macrophages. Five CMGs (FAS, TNFRSF14, TNFRSF17, TNFRSF1B, and TNFSF13B) were considered as diagnostic markers using the Least Absolute Shrinkage and Selection Operator and the Support Vector Machine-Recursive Feature Elimination machine learning algorithms. Based on the five CMGs, a diagnostic nomogram for predicting individual tumor immune microenvironment subclasses in the TCGA dataset was developed, and its predictive performance was validated using GSE73403 and GSE37745 datasets. The predictive accuracy of the diagnostic nomogram was satisfactory in all three datasets. Therefore, it can be used to identify patients who may benefit more from immunotherapy.

CHEK1: a hub gene related to poor prognosis for lung adenocarcinoma

Aim: The study aims to pinpoint hub genes and investigate their functions in order to gain insightful understandings of lung adenocarcinoma (LUAD). Methods: Bioinformatic approaches were adopted to investigate genes in databases including Gene Expression Omnibus, WebGestalt, STRING and Cytoscape, GEPIA2, Oncomine, Human Protein Atlas, TIMER2.0, UALCAN, cBioPortal, TargetScanHuman, OncomiR, ENCORI, Kaplan-Meier plotter, UCSC Xena, European Molecular Biology Laboratory - European Bioinformatics Institute Single Cell Expression Atlas and CancerSEA. Results: Five hub genes were ascertained. CHEK1 was overexpressed in a range of cancers, including LUAD. Promoter methylation, amplification and miRNA regulation might trigger CHEK1 upregulation, signaling poor prognosis. CHEK1 with its coexpressed genes were enriched in the cell cycle pathway. Intratumor heterogeneity of CHEK1 expression could be observed. Cell clusters with CHEK1 expression were more prone to metastasis and epithelial-to-mesenchymal transition. Conclusion: CHEK1 might potentially act as a prognostic biomarker for LUAD.