Non-Small-Cell Lung Cancer Signaling Pathways, Metabolism, and PD-1/PD-L1 Antibodies

Transcriptional regulation by LKB1 in lung adenocarcinomas: Exploring oxidative stress, neuroglial and amino acid signatures

Lung adenocarcinoma (LUAD) is one of the most prevalent cancer types worldwide and has one of the poorest survival rates. Understanding its developpment is crucial for improving diagnosis, prognosis, and treatment. A key factor in LUAD is the frequent loss-of-function mutations in LKB1/STK11, a kinase that regulates metabolism. These mutations are linked to increased metastasis and worse clinical outcomes. In this study, we analyzed gene expression data from LUAD patients to explore how LKB1 mutations affect cancer behavior. We found that LKB1 mutations in KRAS-driven LUAD lead to widespread gene downregulation. By integrating avalaible protein interaction data, mass spectrometry analysis of LKB1 nuclear partners, and co-immunoprecipitations experiments, we identified BRG1, a chromatin activator and subunit of the BAF complex, as a nuclear partner of LKB1. Further analysis suggested that LKB1 mutations may impair BRG1 activity, disrupting chromatin regulation and gene expression. Notably, LUAD patients with mutated LKB1 showed gene expression patterns indicative of oxidative stress, defective neuronal-glial and neuroinflammation programs, and altered amino acid homeostasis. These changes resemble the roles LKB1 plays in neural crest stem cells, suggesting that LKB1 may reduce tumor aggressiveness in LUAD by maintaining a developmental gene expression program.

Integrated radiomics and immune infiltration analysis to decipher immunotherapy efficacy in lung adenocarcinoma

Background

Research in recent years has witnessed unprecedented improvements in immunotherapy, especially immune checkpoint blockade (ICB) for the treatment of lung adenocarcinoma (LUAD) patients. Nevertheless, due to the heterogeneity of immunotherapy response, reliable biomarkers are urgently needed to guide precision cancer therapy. In this study, we aimed to identify immune subtypes in LUAD and develop a radiogenomic model to improve immunotherapy predictive accuracy.

Methods

In this study, clinical data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) databases, and immune subtypes were identified using the ConsensusClusterPlus package in R. Biological, genomic, and epigenomic distinctions were compared. The TCGA cohort and clinical cohort from the Third Xiangya Hospital were utilized to demonstrate no significant differences of survival probability between sexes. Feature extraction and definition were conducted from 103 computed tomography (CT) images from The Cancer Imaging Archive (TCIA) dataset via the "PyRadiomics" embedded in Python. A series of machine learning techniques were applied to build a radiogenomic model.

Results

Two LUAD subtypes with different molecular and immune characteristics were identified. Significant differences in biological, genomic, and epigenomic distinctions among the two subtypes were observed (P<0.05). The immune subtype A participated in pathways related to immune activation and displayed a higher tumor microenvironment (TME) score (P<0.001) with a better prognosis of LUAD [overall survival (OS), P=0.037; disease-specific survival (DSS), P=0.034]. Besides, the model appears to show better fit for females (P=0.015) than for males (P=0.641). Our constructed radiogenomic model incorporating 12 radiomics features displayed satisfactory potential to facilitate the predictive accuracy of immunotherapy in LUAD [test area under the curve (AUC) =0.89; train AUC =0.95].

Conclusions

Our study presented a promising avenue to harness the rich radiomics data to identify the specific immune subtype and integrate it into the existing clinical decision-making system to facilitate the predictive accuracy of immunotherapy in LUAD.

Monoclonal Antibodies in Clinical Trials for Breast Cancer Treatment

One of the most potent therapeutic and diagnostic agents in contemporary medicine is the monoclonal antibody (mAb). mAbs can perform a variety of tasks in breast cancer (BC), including identifying and delivering therapeutic medications to targets, preventing cell development, and suppressing immune system inhibitors including directly attacking cancer cells. mAbs are one of the most effective therapeutic options, particularly for HER2, but they have not been well studied for their use in treating other forms of BC, particularly triple negative breast tumors. Bispecific and trispecific mAbs have created new opportunities for more targeted specific efficacy, which has a positive impact on the viability of antigen specificity. They are more versatile and effective than other forms of treatment, emerging as most popular option for treating BC. However, mAbs have a limit in treatment due to certain adverse effects, including fever, shaking, exhaustion, headache, nausea, and vomiting, as well as rashes, bleeding, and difficulty breathing. To examine the current and prospective future capacities of mAbs with regard to the detection and treatment of BC, the present review highlights advantages and disadvantages of mAb approach.

Expression patterns of MCM8 in lung adenocarcinoma and its correlation with key biological processes

OBJECTIVE

Lung adenocarcinoma (LUAD) is one of the most common and lethal tumors. The identification of diagnostic and prognostic biomarkers is essential to improve patient prognosis and treatment outcomes.

METHODS

The expression of minichromosome maintenance complex component 8 (MCM8) in 33 cancer types was analyzed using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression. Tumor and normal tissues in LUAD were compared using TCGA data and validated against four datasets from the Gene Expression Omnibus. MCM8 expression was assessed by immunohistochemistry (IHC) using tissue microarrays. The diagnostic value of MCM8 was assessed by Receiver Operating Characteristic curve analysis, and its prognostic significance was determined by Kaplan-Meier analysis. The CIBERSORT method was used to examine immune infiltration. The association between MCM8 expression and m6A RNA methylation, glycolysis, and ferroptosis was assessed using the GEPIA online tool.

RESULTS

MCM8 is markedly overexpressed in many tumors including LUAD. MCM8 showed high accuracy for the diagnosis of LUAD, with an area under the curve of 0.849 in TCGA dataset. MCM8 overexpression in tumor tissues in LUAD was confirmed by IHC and shown to be associated with decreased overall survival and disease-specific survival. Analysis of immune cell infiltration showed that immune cell populations differed between high and low MCM8 expression groups. MCM8 expression correlated with that of genes associated with m6A RNA methylation, glycolysis, and ferroptosis.

CONCLUSIONS

MCM8 was identified as a promising diagnostic and prognostic marker in LUAD. The mechanism underlying the effect of MCM8 on cancer development and the immune response remains to be elucidated.

Prognostic and immunological implications of paraptosis-related genes in lung adenocarcinoma: Comprehensive analysis and functional verification of hub gene

BACKGROUND

Lung adenocarcinoma (LUAD) poses significant clinical challenges due to its inherent heterogeneity and variable response to treatment. Recent research has specifically focused on elucidating the role of Paraptosis-related genes (PRGs) in the progression of cancer and the prognosis of patients.

METHODS

We conducted a comprehensive analysis of the differential expression of PRGs in LUAD. Additionally, univariate Cox regression analysis was utilized to determine the prognostic significance of these genes. Furthermore, consensus clustering was employed to differentiate molecular subtypes within LUAD, while immune heterogeneity was assessed. To evaluate treatment outcomes, the expression of immune checkpoint inhibitors was examined, and the sensitivity of LUAD patients to chemotherapy drugs was assessed. Moreover, machine learning algorithms were employed to construct a Paraptosis-related risk score with prognostic and immunological indicators. Finally, to validate the findings, in vitro experiments were performed to verify the regulatory effect of key PRGs on Paraptosis.

RESULTS

Our analysis identified 24 PRGs that exhibited differential expression, with CDKN3, TP53, and PHB emerging as the most prominently upregulated genes in tumor tissues. Among these genes, seven were identified as prognostic markers, with HSPB8 being the sole protective factor. Notably, our analysis also revealed the existence of two distinct molecular subtypes within LUAD, each characterized by unique prognoses and immune responses. Specifically, Subtype B displayed a poorer prognosis but demonstrated increased sensitivity to both chemotherapy and immunotherapy. In addition, our development of a Paraptosis-Associated Risk Score yielded a significant prognostic value in predicting patient outcomes. Furthermore, we found regulatory effect of CDKN3 on Paraptosis in two cell lines.

CONCLUSIONS

Our study highlights the importance of PRGs in LUAD, particularly in prognosis and treatment response. The identified molecular subtypes and Paraptosis-Associated Risk Score offer valuable insights for personalized treatment strategies.

Significance of Ribonucleoside-diphosphate Reductase Subunit M2 in Lung Adenocarcinoma

INTRODUCTION

The Ribonucleoside-diphosphate Reductase subunit M2 (RRM2) is known to be overexpressed in various cancers, though its specific functional implications remain unclear. This aims to elucidate the role of RRM2 in the progression of Lung Adenocarcinoma (LUAD) by exploring its involvement and potential impact.

METHODS

RRM2 data were sourced from multiple databases to assess its diagnostic and prognostic significance in LUAD. We evaluated the association between RRM2 expression and immune cell infiltration, analyzed its function, and explored the effects of modulating RRM2 expression on LUAD cell characteristics through laboratory experiments.

RESULTS

RRM2 was significantly upregulated in LUAD tissues and cells compared to normal counterparts (p < 0.05), with rare genetic alterations noted (approximately 2%). This overexpression clearly distinguished LUAD from normal tissue (area under the curve (AUC): 0.963, 95% confidence intervals (CI): 0.946-0.981). Elevated RRM2 expression was significantly associated with adverse clinicopathological characteristics and poor prognosis in LUAD patients. Furthermore, a positive association was observed between RRM2 expression and immune cell infiltration. Pathway analysis revealed a critical connection between RRM2 and the cell cycle signaling pathway within LUAD. Targeting RRM2 inhibition effectively suppressed LUAD cell proliferation, migration, and invasion while promoting apoptosis. This intervention also modified the expression of several crucial proteins, including the downregulation of CDC25A, CDC25C, RAD1, Bcl-2, and PPM1D and the upregulation of TP53 and Bax (p < 0.05).

CONCLUSION

Our findings highlight the potential utility of RRM2 expression as a biomarker for diagnosing and predicting prognosis in LUAD, shedding new light on the role of RRM2 in this malignancy.

Identification of the molecular subtype and prognostic characteristics of lung adenocarcinoma based on CD8+ T cell-related gene signature

BackgroundLung adenocarcinoma (LUAD) stands as a major respiratory malignancy with high mortality. With the advent of immunotherapy, new therapeutic avenues have emerged in cancer treatment.ObjectiveOur focus aimed at developing a CD8+ T cell-based immune gene prognostic model (CDIGPM) for LUAD, shedding light on the immunological aspects and the potential advantages of immunotherapy in distinct CDIGPM-defined LUAD categories.MethodsData from LUAD patients were extracted from the TCGA and GEO databases (GSE11969). The differentially expressed genes (DEGs) were intersected with immune genes from ImmPort and InnateDB, yielding 89 significant immune genes related to CD8+ T cells (CDIGs). Univariate Cox regression and LASSO regression analyses were performed on 10 hub CDIGs (ADM, CAV1, CTSL, HLA-DMB, HLA-DQA1, IGHM, PLSCR1, PTGDS, S100A16, and WFDC2). Furthermore, the immunological attributes and the immunotherapy efficacy in CDIGPM-defined categories were explored. Moreover, to support the findings of the bioinformatics analysis, fifteen LUAD patients' tumor and adjacent tissues were collected for qRT-PCR detection of CDIGPM-related genes.ResultsKaplan-Meier analysis revealed that the high-CDIGPM group exhibited significantly poorer overall survival (OS) trajectories, whereas the low-CDIGPM group showed more favorable OS trajectories, indicating a better prognosis. Age, tumor stage, and CDIGPM score were identified as independent prognostic factors. The high-CDIGPM group was enriched in pathways related to the cell cycle, focal adhesion, and cancer, while the low-CDIGPM group was associated with immune response-related pathways. The CDIGPM model effectively differentiated clinical subtypes in patients with LUAD. QRT-PCR detection of Clinical LUAD samples also validated the differentially expression of CDIGPM model related genes.ConclusionsThe study highlights the prognostic importance of CDIGs in LUAD using the CDIGPM model, linking age, stage and CDIGPM score to poor outcomes. The identified genes and pathways provide potential therapeutic targets, deepening our understanding of LUAD's molecular landscape.

Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature

The prognosis of lung adenocarcinoma (LUAD) is generally poor. Immunotherapy has emerged as a promising therapeutic modality, demonstrating remarkable potential for substantially prolonging the overall survival of individuals afflicted with LUAD. However, there is currently a lack of reliable signatures for identifying patients who would benefit from immunotherapy. We conducted a comparative analysis of two immunotherapy cohorts (OAK and POPLAR) and utilized single-factor COX regression to identify genes that significantly impact the prognosis of LUAD. Based on the TCGA-LUAD dataset, we employed a combination of 101 machine learning algorithms to construct a model and selected the optimal model. The model was validated on five GEO datasets and compared with 144 previously published signatures to assess its performance. Subsequently, we explored the underlying biological mechanisms through tumor mutation burden analysis, enrichment analysis, and immune infiltration analysis. An immunotherapy prognostic prediction signature (IPPS) was constructed based on 13 genes, showing robust performance in the TCGA-LUAD dataset. IPPS exhibited consistent predictive accuracy in the validation cohorts. Compared to 144 previously published signatures, IPPS consistently ranked among the top in terms of C-index values. Further exploration revealed differences between high and low-IPPS groups in terms of tumor mutation burden, pathway enrichment, and immune infiltration. IPPS demonstrates strong predictive capabilities for the prognosis of LUAD patients, offering the potential to identify suitable candidates for immunotherapy and contribute to precision treatment strategies for LUAD.

Unraveling the immune landscape of lung adenocarcinoma: insights for tailoring therapeutic approaches

Lung adenocarcinoma (LUAD), a prevalent type of non-small cell lung cancer (NSCLC), was known for its diversity and intricate tumor microenvironment (TME). Comprehending the interaction among human immune-related genes (IRGs) and the TME is vital in the creation of accurate predictive models and specific treatments. We created a risk score based on IRGs and designed a nomogram to predict the prognosis of LUAD accurately. This involved a thorough examination of TME and the infiltration of immune cells in both high-risk and low-risk LUAD groups. Furthermore, the examination of the association between characteristic genes (BIRC5 and BMP5) and immune cells, along with immune checkpoints in the TME, was also conducted. The findings of our research unveiled unique immune profiles and interactions among individuals in the high- and low-risk categories, which contribute to variations in prognosis. LUAD demonstrated significant associations between BIRC5, BMP5, immune cells, and checkpoints, suggesting their involvement in disease advancement and resistance to medication. Furthermore, by correlating our findings with a multidrug database, we identified specific LUAD patient subsets that might benefit from tailored treatments. Our study establishes a groundbreaking prognostic model for LUAD, which not only underscores the importance of the immune context in LUAD but also paves the way for advancing precision medicine strategies in this complex malignancy.

PLEK2 activates the PI3K/AKT signaling pathway to drive lung adenocarcinoma progression by upregulating SPC25

Lung adenocarcinoma (LUAD) is the most common subtype of NSCLC, characterized by poor prognosis and frequently diagnosed at advanced. While previous studies have demonstrated pleckstrin-2 (PLEK2) as aberrantly expressed and implicated in tumorigenesis across various tumor types, including LUAD, the molecular mechanisms underlying PLEK2-mediated LUAD progression remain incompletely understood. In this study, we obtained data from The Cancer Genome Atlas (TCGA) database to assess PLEK2 expression in LUAD, a finding further confirmed through analysis of human tissue specimens. PLEK2-silenced LUAD cellular models were subsequently constructed to examine the functional role of PLEK2 both in vitro and in vivo. Our results showed elevated PLEK2 expression in LUAD, correlating with poor patients' prognosis. PLEK2 knockdown led to a significant suppression of LUAD cell proliferation and migration, accompanied by enhanced apoptosis. Moreover, tumor growth in mice injected with PLEK2-silencing LUAD cells was impaired. Gene expression profiling and Co-IP assays suggested direct interaction between PLEK2 and SPC25, with downregulation of SPC25 similarly impairing cell proliferation and migration. Additionally, we revealed phosphoinositide 3-kinase (PI3K)/AKT signaling activation as requisite for PLEK2-induced malignant phenotypes in LUAD. Collectively, our findings underscore PLEK2's oncogenic potential in LUAD, suggesting its utility as a prognostic indicator and therapeutic target for LUAD management.

Anoikis-related subtype and prognosis analyses based on bioinformatics, and an expression verification of ANGPTL4 based on experiments of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with high mortality. Anoikis resistance is an important mechanism of tumor cell proliferation and migration. Our research is devoted to exploring the role of anoikis in the diagnosis, classification, and prognosis of LUAD.

Methods

We downloaded the expression profile, mutation, and clinical data of LUAD from The Cancer Genome Atlas (TCGA) database. The "ConsensusClusterPlus" package was then used for the cluster analysis, and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were used to establish the prognostic model. We verified the reliability of the model using a Gene Expression Omnibus (GEO) data set. A gene set variation analysis (GSVA) was conducted to investigate the functional enrichment differences in the different clusters and risk groups. The CIBERSORT algorithm and a single-sample gene set enrichment analysis (ssGSEA) were used to analyze immune cell infiltration. The tumor mutation burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) scores were used to evaluate the patients' sensitivity to immunotherapy. Immunohistochemical staining of tissue microarrays was used to verify the correlation between ANGPTL4 expression and the clinicopathological characteristics and prognosis of LUAD patients.

Results

First, we screened 135 differentially expressed anoikis-related genes (ARGs) and 23 prognosis-related ARGs from TCGA-LUAD data set. Next, 494 LUAD samples were allocated to cluster A and cluster B based on the 23 prognosis-related ARGs. The Kaplan-Meier (K-M) analysis showed the overall survival (OS) of cluster B was better than that of cluster A. The clinicopathological characteristics and functional enrichment analyses revealed significant differences between clusters A and B. The tumor microenvironment (TME) analysis showed that cluster B had more immune cell infiltration and a higher TME score than cluster A. Subsequently, a LASSO Cox regression model of LUAD was constructed with ten ARGs. The K-M analysis showed that the low-risk patients had longer OS than the high-risk patients. The receiver operating characteristic curve, nomogram, and GEO data set verification results showed that the model had high accuracy and reliability. The level of immune cell infiltration and TME score were higher in the low-risk group than the high-risk group. The high-risk group had stronger sensitivity to immune checkpoint block therapy and weaker sensitivity to chemotherapy drugs than the low-risk group. ANGPTL4 expression was correlated with stage, tumor differentiation, tumor size, lymph node metastasis, and OS.

Conclusions

We discovered novel molecular subtypes and constructed a novel prognostic model of LUAD. Our findings provide important insights into subtype classification and the accurate survival prediction of LUAD. We also identified ANGPTL4 as a prognostic indicator of LUAD.

Maresin1 alleviates neuroinflammation by inhibiting caspase-3/ GSDME-mediated pyroptosis in mice cerebral ischemia-reperfusion model

OBJECTIVE

To explore the mechanism of Maresin1 in reducing cerebral ischemia-reperfusion injury.

MATERIALS AND METHODS

Male C57BL/6 mice were randomly divided (n = 5 in each group), and focal middle cerebral artery occlusion (MCAO) model was used to simulate cerebral ischemia/reperfusion injury. TTC and the Longa score were used to detect the degree of neurological deficits. Western blot was used to detect the expression levels of GSDME, GSDME-N, caspase-3 and cleaved caspase-3 in cerebral ischemic penumbra tissue, and immunofluorescence was used to detect the expression levels of GSDME-N. The mRNA expression levels of GSDME and pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) were detected by RT-PCR.

RESULTS

Compared with sham group, GSDME mRNA levels in MCAO group were significantly increased at 12 h and 24 h after reperfusion, and GSDME and GSDME-N significantly increased at 6-48 h after reperfusion. Compared with sham group, the percentage of infarct size, the Longa score, the mRNA expression levels of IL-1β, IL-6 and TNF-α, and GSDME, GSDME-N, caspase-3 and cleaved caspase-3 in MCAO group was significantly increased. Then, the percentage of infarct size and the Longa score significantly decreased after MaR1 administration, the mRNA expression levels of IL-1β and IL-6 downregulated, and GSDME, GSDME-N, caspase-3 and cleaved caspase-3 were also reduced. After administration of Z-DEVD-FMK(ZDF), the expression of caspase-3, cleaved caspase-3 and GSDME-N was decreased, which in MCAO+MaR1+ZDF group was not statistically significant compared with MCAO+ ZDF group.

CONCLUSION

Maresin1 alleviates cerebral ischemia/reperfusion injury by inhibiting pyroptosis mediated by caspase-3/GSDME pathway and alleviating neuroinflammation.

First-line immunotherapy efficacy in advanced squamous non-small cell lung cancer with PD-L1 expression ≥50%: a network meta-analysis of randomized controlled trials

Objective

The optimal first-line immunotherapy regimen for patients with PD-L1 expression ≥50% in squamous non-small cell lung cancer (Sq-NSCLC) remains uncertain. This study utilized net-work meta-analysis (NMA) to indirectly compare the efficacy of various first-line immuno-therapy regimens in this patient subset.

Methods

Systematic searches were conducted across PubMed, the Cochrane Library, Web of Science, and Embase databases for randomized controlled trials reporting overall survival (OS) and progression-free survival (PFS) outcomes. The search spanned from database inception to November 3, 2023. Bayesian network meta-analysis was employed for a comprehen-sive analysis. To ensure scientific rigor and transparency, this study is registered in the Interna-tional Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD42022349712.

Results

The NMA encompassed 9 randomized controlled trials (RCTs), involving 2170 patients and investigating 9 distinct immunotherapy regimens. For OS, the combination of camrelizumab and chemotherapy demonstrated the highest probability (36.68%) of efficacy, fol-lowed by cemiplimab (33.86%) and atezolizumab plus chemotherapy (23.87%). Regarding PFS, the camrelizumab and chemotherapy combination had the highest probability (39.70%) of efficacy, followed by pembrolizumab (22.88%) and pembrolizumab plus chemotherapy (17.69%). Compared to chemotherapy, first-line treatment with immune checkpoint inhibitors (ICIs) in Sq-NSCLC pa-tients exhibited significant improvements in OS (HR 0.59, 95% CI 0.47-0.75) and PFS (HR 0.44, 95% CI 0.37-0.52).

Conclusion

This study suggests that, for Sq-NSCLC patients with PD-L1 expression ≥50%, the first-line immunotherapy regimen of camrelizumab plus chemotherapy provides superior OS and PFS outcomes. Furthermore, ICIs demonstrate enhanced efficacy compared to chemotherapy in this patient population.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD 42022349712.

SLC7A11 inhibits ferroptosis and downregulates PD-L1 levels in lung adenocarcinoma

Introduction

Lung adenocarcinoma (LUAD) is a prevalent form of lung cancer originating from lung glandular cells with low survival rates despite recent therapeutic advances due to its diverse and complex nature. Recent evidence suggests a link between ferroptosis and the effectiveness of anti-PD-L1 therapy, with potential synergistic effects.

Methods

Our study comprehensively analyzed the expression patterns of ferroptosis regulators in LUAD and their association with prognosis and PD-L1 expression. Furthermore, we identified two distinct subtypes of LUAD through consensus clustering of ferroptosis regulators, revealing significant tumor heterogeneity, divergent PD-L1 expression, and varying prognoses between the subtypes.

Results

Among the selected ferroptosis regulators, SLC7A11 emerged as an independent prognostic marker for LUAD patients and exhibited a negative correlation with PD-L1 expression. Subsequent investigations revealed high expression of SLC7A11 in the LUAD population. In vitro experiments demonstrated that overexpression of SLC7A11 led to reduced PD-L1 expression and inhibited ferroptosis in A549 cells, underscoring the significant role of SLC7A11 in LUAD. Additionally, pan-cancer analyses indicated an association between SLC7A11 and the expression of immune checkpoint genes across multiple cancer types with poor prognoses.

Discussion

From a clinical standpoint, these findings offer a foundation for identifying and optimizing potential combination strategies to enhance the therapeutic effectiveness of immune checkpoint inhibitors and improve the prognosis of patients with LUAD.

Deterministic reprogramming and signaling activation following targeted therapy in non-small cell lung cancer driven by mutations or oncogenic fusions

INTRODUCTION

Targeted therapy is used to treat lung adenocarcinoma caused by epidermal growth factor receptor (EGFR) mutations in the tyrosine kinase domain and rare subtypes (<5%) of non-small cell lung cancer. These subtypes include fusion oncoproteins like anaplastic lymphoma kinase (ALK), ROS1, rearranged during transfection (RET), and other receptor tyrosine kinases (RTKs). The use of diverse selective oral inhibitors, including those targeting rat sarcoma viral oncogene homolog (KRAS) mutations, has significantly improved clinical responses, extending progression-free and overall survival.

AREAS COVERED

Resistance remains a critical issue in lung adenocarcinoma, notably in EGFR mutant, echinoderm microtubule associated protein-like 4 (EML4)-ALK fusion, and KRAS mutant tumors, often associated with epithelial-to-mesenchymal transition (EMT).

EXPERT OPINION

Despite advancements in next generation EGFR inhibitors and EML4-ALK therapies with enhanced brain penetrance and identifying resistance mutations, overcoming resistance has not been abated. Various strategies are being explored to overcome this issue to achieve prolonged cancer remission and delay resistance. Targeting yes-associated protein (YAP) and the mechanisms associated with YAP activation through Hippo-dependent or independent pathways, is desirable. Additionally, the exploration of liquid-liquid phase separation in fusion oncoproteins forming condensates in the cytoplasm for oncogenic signaling is a promising field for the development of new treatments.

Discovery of lung adenocarcinoma tumor antigens and ferroptosis subtypes for developing mRNA vaccines

mRNA vaccines are becoming a feasible alternative for treating cancer. To develop mRNA vaccines against LUAD, potential antigens were identified and LUAD ferroptosis subtypes distinguished for selecting appropriate patients. The genome expression omnibus, cancer genome atlas (TCGA) and FerrDB were used to collect gene expression profiles, clinical information, and the genes involved in ferroptosis, respectively. cBioPortal was used to visualize and compare genetic alterations, GEPIA2 to calculate prognostic factors of the selected antigens, and TIMER to visualize the relationship between potential antigens and tumor immune cell infiltration. Consensus clustering analysis was utilized to identify ferroptosis subtypes and their prognostic value assessed by Log-rank and cox regression tests. The modules of ferroptosis-related gene screening were conducted by weight gene co-expression network analysis. The LUAD ferroptosis landscape was visualized through dimensionality reduction and graph learning. Six tumor antigens had obvious LUAD-mutations, positively correlated with different antigen-presenting cells, and might induce tumor cell ferroptosis. LUAD patients were stratified into three ferroptosis subtypes (FS1, FS2, and FS3) according to diverse molecular, cellular, and clinical characteristics. FS3 showed the highest tumor mutation burden and the most somatic mutations, deemed potential indicators of mRNA vaccine effectiveness. Moreover, different ferroptosis subtypes expressed distinct immune checkpoints and immunogenic cell death modulators. AGPS, NRAS, MTDH, PANX1, NOX4, and PPARD are potentially suitable for mRNA vaccinations against LUAD, specifically in patients with FS3 tumors. This study defines vaccination candidates and establishes a theoretical basis for LUAD mRNA vaccinations.

Canakinumab as Adjuvant Therapy in Patients With Completely Resected Non-Small-Cell Lung Cancer: Results From the CANOPY-A Double-Blind, Randomized Clinical Trial

PURPOSE

Effective treatments for resectable non-small-cell lung cancer (NSCLC) are limited and relapse rates are high. The interleukin (IL)-1β pathway has been linked with tumor development and progression, including in the Canakinumab Anti-Inflammatory Thrombosis Outcomes cardiovascular study in which IL-1β pathway inhibition with canakinumab reduced lung cancer incidence and mortality in an exploratory analysis.

METHODS

CANOPY-A (ClinicalTrials.gov identifier: NCT03447769) is a phase III, randomized, double-blind, multicenter study of canakinumab versus placebo for adult patients with stage II-IIIA or IIIB (T >5 cm, N2-positives II-IIIB; American Joint Committee on Cancer/Union for International Cancer Control version 8), completely resected NSCLC who had received adjuvant cisplatin-based chemotherapy. The primary end point was disease-free survival (DFS) and the key secondary end point was overall survival (OS).

RESULTS

In total, 1,382 patients were randomized to 200 mg canakinumab (n = 693) or placebo (n = 689) once every 3 weeks for 18 cycles. Grade ≥3 adverse events (AEs) were reported in 20.8% and 19.6% of patients receiving canakinumab and placebo, respectively; AEs led to discontinuation in 4.3% and 4.1% of patients in these groups, respectively. This study did not meet its primary end point. Median DFS was 35.0 months (canakinumab arm) and 29.7 months (placebo arm; hazard ratio, 0.94; 95% CI, 0.78 to 1.14; one-sided P = .258). DFS subgroup analyses did not show any meaningful differences between arms. As expected, because of canakinumab-driven IL-1β pathway inhibition, C-reactive protein and IL-6 levels decreased in the canakinumab arm versus placebo arm, but had no correlation with differential clinical outcomes. OS was not formally tested as DFS was not statistically significant.

CONCLUSION

CANOPY-A did not show a DFS benefit of adding canakinumab after surgery and adjuvant cisplatin-based chemotherapy in patients with resected, stage II-III NSCLC. No new safety signals were identified with canakinumab.

Prognostic gene HLA-DMA associated with cell cycle and immune infiltrates in LUAD

BACKGROUND

The dominant subclass of non-small-cell lung cancer (NSCLC) is lung adenocarcinoma (LUAD). The tumor microenvironment (TME) is a crucial feature of carcinogenesis and progression in LUAD. Furthermore, immune and stromal components of TME are crucial factors to investigating and curing LUAD. Thus, the study assessed the value of TME-related genes for LUAD prognosis and immune infiltration.

METHODS

All data were downloaded from TCGA and GEO databases. The immune and stromal scores were downloaded from ESTIMATE, and the association between the scores and prognosis was explored by Kaplan-Meier survival analysis. Protein-protein interaction (PPI) network and univariate Cox regression were used to find TME-related differentially expressed genes (DEGs), and HLA-DMA was regarded as a prognostic hub gene. Western blot analyses, qRT-PCR, and immunofluorescence were applied to verify HLA-DMA expression in clinical samples. NSCLC cell lines were used to verify the effect of HLA-DMA on cell proliferation and cell cycle distribution. At last, the alteration of immunotherapy response and TME transition caused by HLA-DMA different expression were further studied.

RESULTS

The immune score was positively correlated with survival. The functional analyses suggested that TME-related DEGs may be involved in the immune response. The expression level of HLA-DMA was decreased in LUAD. In addition, HLA-DMA expression was associated with several clinical features and was positively associated with survival. Furthermore, HLA-DMA may suspend cell proliferation by regulating cell cycle. HLA-DMA expression was closely associated with immune infiltration and positively correlated with TMB, indicating that patients with high HLA-DMA level were more suitable for immunotherapy.

CONCLUSION

These results reveal that HLA-DMA might act as a biomarker for immune infiltration and immunotherapy response.

Mathematical Modeling of Non-Small-Cell Lung Cancer Biology through the Experimental Data on Cell Composition and Growth of Patient-Derived Organoids

Mathematical models of non-small-cell lung cancer are powerful tools that use clinical and experimental data to describe various aspects of tumorigenesis. The developed algorithms capture phenotypic changes in the tumor and predict changes in tumor behavior, drug resistance, and clinical outcomes of anti-cancer therapy. The aim of this study was to propose a mathematical model that predicts the changes in the cellular composition of patient-derived tumor organoids over time with a perspective of translation of these results to the parental tumor, and therefore to possible clinical course and outcomes for the patient. Using the data on specific biomarkers of cancer cells (PD-L1), tumor-associated macrophages (CD206), natural killer cells (CD8), and fibroblasts (αSMA) as input, we proposed a model that accurately predicts the cellular composition of patient-derived tumor organoids at a desired time point. Combining the obtained results with "omics" approaches will improve our understanding of the nature of non-small-cell lung cancer. Moreover, their implementation into clinical practice will facilitate a decision-making process on treatment strategy and develop a new personalized approach in anti-cancer therapy.

Inflammatory Cytokine Elaboration Following Secondhand Smoke (SHS) Exposure Is Mediated in Part by RAGE Signaling

The receptor for advanced glycation end products (RAGE) is a key contributor to immune and inflammatory responses in myriad diseases. RAGE is a transmembrane pattern recognition receptor with a special interest in pulmonary anomalies due to its naturally abundant pulmonary expression. Our previous studies demonstrated an inflammatory role for RAGE following acute 30-day exposure to secondhand smoke (SHS), wherein immune cell diapedesis and cytokine/chemokine secretion were accentuated in part via RAGE signaling. However, the chronic inflammatory mechanisms associated with RAGE have yet to be fully elucidated. In this study, we address the impact of long-term SHS exposure on RAGE signaling. RAGE knockout (RKO) and wild-type (WT) mice were exposed to SHS using a nose-only delivery system (Scireq Scientific, Montreal, Canada) for six months. SHS-exposed animals were compared to mice exposed to room air (RA) only. Immunoblotting was used to assess the phospho-AKT and phospho-ERK activation data, and colorimetric high-throughput assays were used to measure NF-kB. Ras activation was measured via ELISAs. Bronchoalveolar lavage fluid (BALF) cellularity was quantified, and a mouse cytokine antibody array was used to screen the secreted cytokines. The phospho-AKT level was decreased, while those of phospho-ERK, NF-kB, and Ras were elevated in both groups of SHS-exposed mice, with the RKO + SHS-exposed mice demonstrating significantly decreased levels of each intermediate compared to those of the WT + SHS-exposed mice. The BALF contained increased levels of diverse pro-inflammatory cytokines in the SHS-exposed WT mice, and diminished secretion was detected in the SHS-exposed RKO mice. These results validate the role for RAGE in the mediation of chronic pulmonary inflammatory responses and suggest ERK signaling as a likely pathway that perpetuates RAGE-dependent inflammation. Additional characterization of RAGE-mediated pulmonary responses to prolonged exposure will provide a valuable insight into the cellular mechanisms of lung diseases such as chronic obstructive pulmonary disease.

TRIM11 promotes cell proliferation of non-small cell lung cancer through the inhibition of ferroptosis by AMPK

Lung cancer is one of the leading causes of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) being the most prevalent type. This study investigates the role of TRIM11 gene in NSCLC and its underlying mechanism. NSCLC patients were recruited from our hospital and showed upregulated TRIM11 mRNA and protein expressions. Patients with high TRIM11 expression had lower survival rates. TRIM11 gene was found to promote cell proliferation and reduce ROS-induced ferroptosis in NSCLC. Additionally, TRIM11 gene induced AMPK expression and its regulation affected TRIM11's effects on cell proliferation and ferroptosis in NSCLC. IP analysis revealed that TRIM11 protein interacted with AMPK protein in NSCLC. These data confirmed that TRIM11 promotes cell proliferation and reduces ROS-induced ferroptosis in NSCLC through AMPK. Hence, TRIM11 is a potential target for the treatment of NSCLC and other cancers.

Biological insights in non-small cell lung cancer

Lung oncogenesis relies on intracellular cysteine to overcome oxidative stress. Several tumor types, including non-small cell lung cancer (NSCLC), upregulate the system xc- cystine/glutamate antiporter (xCT) through overexpression of the cystine transporter SLC7A11, thus sustaining intracellular cysteine levels to support glutathione synthesis. Nuclear factor erythroid 2-related factor 2 (NRF2) serves as a master regulator of oxidative stress resistance by regulating SLC7A11, whereas Kelch-like ECH-associated protein (KEAP1) acts as a cytoplasmic repressor of the oxidative responsive transcription factor NRF2. Mutations in KEAP1/NRF2 and p53 induce SLC7A11 activation in NSCLC. Extracellular cystine is crucial in supplying the intracellular cysteine levels necessary to combat oxidative stress. Disruptions in cystine availability lead to iron-dependent lipid peroxidation, thus resulting in a type of cell death called ferroptosis. Pharmacologic inhibitors of xCT (either SLC7A11 or GPX4) induce ferroptosis of NSCLC cells and other tumor types. When cystine uptake is impaired, the intracellular cysteine pool can be sustained by the transsulfuration pathway, which is catalyzed by cystathionine-B-synthase (CBS) and cystathionine g-lyase (CSE). The involvement of exogenous cysteine/cystine and the transsulfuration pathway in the cysteine pool and downstream metabolites results in compromised CD8+ T cell function and evasion of immunotherapy, diminishing immune response and potentially reducing the effectiveness of immunotherapeutic interventions. Pyroptosis is a previously unrecognized form of regulated cell death. In NSCLCs driven by EGFR, ALK, or KRAS, selective inhibitors induce pyroptotic cell death as well as apoptosis. After targeted therapy, the mitochondrial intrinsic apoptotic pathway is activated, thus leading to the cleavage and activation of caspase-3. Consequently, gasdermin E is activated, thus leading to permeabilization of the cytoplasmic membrane and cell-lytic pyroptosis (indicated by characteristic cell membrane ballooning). Breakthroughs in KRAS G12C allele-specific inhibitors and potential mechanisms of resistance are also discussed herein.

Nanomaterials in tumor immunotherapy: new strategies and challenges

Tumor immunotherapy exerts its anti-tumor effects by stimulating and enhancing immune responses of the body. It has become another important modality of anti-tumor therapy with significant clinical efficacy and advantages compared to chemotherapy, radiotherapy and targeted therapy. Although various kinds of tumor immunotherapeutic drugs have emerged, the challenges faced in the delivery of these drugs, such as poor tumor permeability and low tumor cell uptake rate, had prevented their widespread application. Recently, nanomaterials had emerged as a means for treatment of different diseases due to their targeting properties, biocompatibility and functionalities. Moreover, nanomaterials possess various characteristics that overcome the defects of traditional tumor immunotherapy, such as large drug loading capacity, precise tumor targeting and easy modification, thus leading to their wide application in tumor immunotherapy. There are two main classes of novel nanoparticles mentioned in this review: organic (polymeric nanomaterials, liposomes and lipid nanoparticles) and inorganic (non-metallic nanomaterials and metallic nanomaterials). Besides, the fabrication method for nanoparticles, Nanoemulsions, was also introduced. In summary, this review article mainly discussed the research progress of tumor immunotherapy based on nanomaterials in the past few years and offers a theoretical basis for exploring novel tumor immunotherapy strategies in the future.

Role and therapeutic targeting of glutamine metabolism in non‑small cell lung cancer (Review)

The Warburg effect indicates that cancer cells survive through glycolysis under aerobic conditions; as such, the topic of cancer metabolism has aroused interest. It is requisite to further explore cancer metabolism, as it helps to simultaneously explain the process of carcinogenesis and guide therapy. The flexible metabolism of cancer cells, which is the result of metabolic reprogramming, can meet the basic needs of cells, even in a nutrition-deficient environment. Glutamine is the most abundant non-essential amino acid in the circulation, and along with glucose, comprise the two basic nutrients of cancer cell metabolism. Glutamine is crucial in non-small cell lung cancer (NSCLC) cells and serves an important role in supporting cell growth, activating signal transduction and maintaining redox homeostasis. In this perspective, the present review aims to provide a new therapeutic strategy of NSCLC through inhibiting the metabolism of glutamine. This review not only summarizes the significance of glutamine metabolism in NSCLC cells, but also enumerates traditional glutamine inhibitors along with new targets. It also puts forward the concept of combination therapy and patient stratification with the aim of comprehensively showing the effect and prospect of targeted glutamine metabolism in NSCLC therapy. This review was completed by searching for keywords including 'glutamine', 'NSCLC' and 'therapy' on PubMed, and screening out articles.

Generation of a Perfusable 3D Lung Cancer Model by Digital Light Processing

Lung cancer still has one of the highest morbidity and mortality rates among all types of cancer. Its incidence continues to increase, especially in developing countries. Although the medical field has witnessed the development of targeted therapies, new treatment options need to be developed urgently. For the discovery of new drugs, human cancer models are required to study drug efficiency in a relevant setting. Here, we report the generation of a non-small cell lung cancer model with a perfusion system. The bioprinted model was produced by digital light processing (DLP). This technique has the advantage of including simulated human blood vessels, and its simple assembly and maintenance allow for easy testing of drug candidates. In a proof-of-concept study, we applied gemcitabine and determined the IC₅₀ values in the 3D models and 2D monolayer cultures and compared the response of the model under static and dynamic cultivation by perfusion. As the drug must penetrate the hydrogel to reach the cells, the IC₅₀ value was three orders of magnitude higher for bioprinted constructs than for 2D cell cultures. Compared to static cultivation, the viability of cells in the bioprinted 3D model was significantly increased by approximately 60% in the perfusion system. Dynamic cultivation also enhanced the cytotoxicity of the tested drug, and the drug-mediated apoptosis was increased with a fourfold higher fraction of cells with a signal for the apoptosis marker caspase-3 and a sixfold higher fraction of cells positive for PARP-1. Altogether, this easily reproducible cancer model can be used for initial testing of the cytotoxicity of new anticancer substances. For subsequent in-depth characterization of candidate drugs, further improvements will be necessary, such as the generation of a multi-cell type lung cancer model and the lining of vascular structures with endothelial cells.

Targeted therapies for KRAS-mutant non-small cell lung cancer: from preclinical studies to clinical development-a narrative review

Background and Objective

Non-small cell lung cancer (NSCLC) with Kirsten rat sarcoma viral oncogene homolog (KRAS) driver alterations harbors a poor prognosis with standard therapies, including chemotherapy and/or immunotherapy with anti-programmed cell death protein 1 (anti-PD-1) or anti-programmed death ligand-1 (anti-PD-L1) antibodies. Selective KRAS G12C inhibitors have been shown to provide significant clinical benefit in pretreated NSCLC patients with KRAS G12C mutation.

Methods

In this review, we describe KRAS and the biology of KRAS-mutant tumors and review data from preclinical studies and clinical trials on KRAS-targeted therapies in NSCLC patients with KRAS G12C mutation.

Key Content and Findings

KRAS is the most frequently mutated oncogene in human cancer. The G12C is the most common KRAS mutation found in NSCLC. Sotorasib is the first, selective KRAS G12C inhibitor to receive approval based on demonstration of significant clinical benefit and tolerable safety profile in previously treated, KRAS G12C-mutated NSCLC. Adagrasib, a highly selective covalent inhibitor of KRAS G12C, has also shown efficacy in pretreated patients and other novel KRAS inhibitors are being under evaluation in early-phase studies. Similarly to other oncogene-directed therapies, mechanisms of intrinsic and acquired resistance limiting the activity of these agents have been described.

Conclusions

The discovery of selective KRAS G12C inhibitors has changed the therapeutic scenario of KRAS G12C-mutant NSCLC. Various studies testing KRAS inhibitors in different settings of disease, as single-agent or in combination with targeted agents for synthetic lethality and immunotherapy, are currently ongoing in this molecularly-defined subgroup of patients to further improve clinical outcomes.

Comprehensively Analyze the Prognosis Significance and Immune Implication of PTPRO in Lung Adenocarcinoma

Immunotherapy for lung adenocarcinoma (LUAD) is considered to be a promising treatment option, but only a minority of patients benefit from it. Therefore, it is essential to clarify the regulation mechanism of the tumor immune microenvironment (TIM) of the LUAD. Receptor-type protein tyrosine phosphatase (PTPRO) has been shown to be a tumor suppressor in a variety of tumor; however, its role in LUAD has never been reported. In this study, we first found that PTPRO was lowly expressed in LUAD and positively correlated with patient prognosis. Next, we investigated the relationship between PTPRO and clinical characteristics, and the results showed that gender, age, T, and stage were closely related to the expression level of PTPRO. Moreover, we performed univariate and multivariate analyses, and the results revealed that PTPRO was a protective factor for LUAD. By constructing a nomogram based on the expression level of PTPRO and various clinical characteristics, it was proved that the nomogram has a good predictive capacity. Furthermore, we analyzed the coexpression network of PTPRO through multiple databases and performed GO and KEGG enrichment analyses. The results demonstrated that PTPRO was involved in the regulation of multiple immune pathways. In addition, we analyzed whether PTPRO expression of LUAD regulate immune cell infiltration and the results demonstrated that PTPRO was closely related to the infiltration of various immune cells. Finally, we predicted LUAD sensitivity to chemotherapeutics and response to immunotherapy by PTPRO expression levels. The results showed that PTPRO expression level affect the sensitivity of various chemotherapeutic drugs and may be involved in the efficacy of immunotherapy. These results we obtained suggested that PTPRO is closely related to the prognosis and TIM of LUAD, which may be a potential immunotherapeutic target for LUAD.

High Expression of DLGAP5 Indicates Poor Prognosis and Immunotherapy in Lung Adenocarcinoma and Promotes Proliferation through Regulation of the Cell Cycle

Background

Lung adenocarcinoma (LUAD) is one of the most common types of cancer in the respiratory system, with a high mortality and recurrence rate. The role of disc large-associated protein 5 (DLGAP5) in LUAD progression and tumor microenvironment (TME) remains unclear. This study is aimed at revealing the functional role of DLGAP5 in LUAD based on bioinformatics analysis and experimental validation.

Methods

Differential expression analysis, protein-protein interaction (PPI) network, and Cox regression analysis were applied to screen potential prognostic biomarkers. The mRNA and protein levels of DLGAP5 were analyzed using The Cancer Genome Atlas (TCGA) and the Human Protein Atlas (HPA) databases. The CCK-8 and colony formation assays were performed to assess the effect of DLGAP5 on cell proliferation. RNA sequencing (RNA-seq) and enrichment analyses were utilized to explore the biological functions of DLGAP5. Furthermore, flow cytometry was used to explore the role of DLGAP5 on the cell cycle. The ssGSEA algorithm in the R package "GSVA" was applied to quantify immune infiltrating cells, and the tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict the efficacy of immunotherapy. Moreover, analyses using the cBioPortal and MethSurv databases were performed to evaluate the mutation and methylation of DLGAP5, respectively. Finally, the prognostic value of DLGAP5 was estimated using the TCGA and the Gene Expression Omnibus (GEO) databases. The nomogram model was constructed using the TCGA-LUAD cohort and evaluated by adopting calibration curves, time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).

Results

DLGAP5 mRNA and protein abundance were significantly elevated in LUAD, and knockdown of DLGAP5 remarkably suppressed lung cancer cell proliferation through induction of cell cycle G1 arrest. In addition, DLGAP5 expression was positively correlated with Th2 cells and negatively correlated with B cells, T follicular helper cells, and mast cells. LUAD patients with high DLGAP5 expression may be resistant to immunotherapy. Hypermethylation levels of the cg23678254 site of DLGAP5 or its enhanced expression were unfavorable for the survival of LUAD patients. Meanwhile, DLGAP5 expression was associated with TNM stages, tumor status, and therapy outcome. Notably, the prognostic model constructed based on DLGAP5 expression exhibited great predictive capability, which was promising for clinical applications.

Conclusion

DLGAP5 promotes lung cancer cell proliferation through regulation of the cell cycle and is associated with multiple immune infiltrating cells. Furthermore, DLGAP5 predicts poor prognosis and response to immunotherapy in lung adenocarcinoma.

Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas

Background

Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent studies have identified 33 positive regulators of T cell functions (TPRs) that play a critical role in promoting the proliferation, activity, and functions of multiple immunocytes. However, their role in the TME of LGG has not been investigated. This study aimed to construct a risk model based on these TPRs and to detect the significance of immunotypes in predicting LGG prognosis and immunotherapy efficacy.

Methods

A total of 688 LGGs and 202 normal brain tissues were extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases. The NMF R package was used to identify TRP-related subtypes. The TPR prognostic model was established using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival of LGG samples.

Results

The Subtype 2 patients had worse survival outcomes, suppressed immune function, and higher immune cell infiltration. A risk regression model consisting of 14 TPRs was established, and its performance was validated in CGGA325 cohorts. The low-risk group exhibited better overall survival, immune microenvironment, and immunotherapy response, as determined via the TIDE algorithm, indicating that increasing the level of immune infiltration can effectively improve the response to immunotherapy in the low-risk group. The risk score was determined to be an independent hazard factor (p<0.001) although other clinical features (age, sex, grade, IDH status, 1p19q codel status, MGMT status, and accepted radiotherapy) were considered. Lastly, high-risk groups in both cohorts revealed optimal drug responses to rapamycin, paclitaxel, JW-7-52-1, and bortezomib.

Conclusions

Our study identified two distinct TPR subtypes and built a TPR signature to elucidate the characteristics of T cell proliferation in LGG and its association with immune status and prognosis. These findings shed light on possible immunotherapeutic strategies for LGGs.

STK24 Promotes Progression of LUAD and Modulates the Immune Microenvironment

Objective

Recent studies have shown that serine/threonine-protein kinase 24 (STK24) plays an important role in cancer development. However, the significance of STK24 in lung adenocarcinoma (LUAD) remains to be determined. This study is aimed at investigating the significance of STK24 in LUAD.

Methods

STK24 was silenced and overexpressed by siRNAs and lentivirus, respectively. Cellular function was assessed by CCK8, colony formation, transwell, apoptosis, and cell cycle. mRNA and protein abundance was checked by qRT-PCR and WB assay, respectively. Luciferase reporter activity was evaluated to examine the regulation of KLF5 on STK24. Various public databases and tools were applied to investigate the immune function and clinical significance of STK24 in LUAD.

Results

We found that STK24 was overexpressed in lung adenocarcinoma (LUAD) tissues. High expression of STK24 predicted poor survival of LUAD patients. In vitro, STK24 enhanced the proliferation and colony growth ability of A549 and H1299 cells. STK24 knockdown induced apoptosis and cell cycle arrest at G0/G1 phase. Furthermore, Krüppel-like factor 5 (KLF5) activated STK24 in lung cancer cells and tissues. Enhanced lung cancer cell growth and migration triggered by KLF5 could be reversed by silencing of STK24. Finally, the bioinformatics results showed that STK24 may be involved in the regulation of the immunoregulatory process of LUAD.

Conclusion

KLF5 upregulation of STK24 contributes to cell proliferation and migration in LUAD. Moreover, STK24 may participate in the immunomodulatory process of LUAD. Targeting KLF5/STK24 axis may be a potential therapeutic strategy for LUAD.

Prognostic necroptosis-related gene signature aids immunotherapy in lung adenocarcinoma

Background: Necroptosis is a phenomenon of cellular necrosis resulting from cell membrane rupture by the corresponding activation of Receptor Interacting Protein Kinase 3 (RIPK3) and Mixed Lineage Kinase domain-Like protein (MLKL) under programmed regulation. It is reported that necroptosis is closely related to the development of tumors, but the prognostic role and biological function of necroptosis in lung adenocarcinoma (LUAD), the most important cause of cancer-related deaths, is still obscure. Methods: In this study, we constructed a prognostic Necroptosis-related gene signature based on the RNA transcription data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as well as the corresponding clinical information. Kaplan-Meier analysis, receiver operating characteristic (ROC), and Cox regression were made to validate and evaluate the model. We analyzed the immune landscape in LUAD and the relationship between the signature and immunotherapy regimens. Results: Five genes (RIPK3, MLKL, TLR2, TNFRSF1A, and ALDH2) were used to construct the prognostic signature, and patients were divided into high and low-risk groups in line with the risk score. Cox regression showed that risk score was an independent prognostic factor. Nomogram was created for predicting the survival rate of LUAD patients. Patients in high and low-risk groups have different tumor purity, tumor immunogenicity, and different sensitivity to common antitumor drugs. Conclusion: Our results highlight the association of necroptosis with LUAD and its potential use in guiding immunotherapy.

Identification and Application of a Novel Immune-Related lncRNA Signature on the Prognosis and Immunotherapy for Lung Adenocarcinoma

Background: Long non-coding RNA (lncRNA) participates in the immune regulation of lung cancer. However, limited studies showed the potential roles of immune-related lncRNAs (IRLs) in predicting survival and immunotherapy response of lung adenocarcinoma (LUAD). Methods: Based on The Cancer Genome Atlas (TCGA) and ImmLnc databases, IRLs were identified through weighted gene coexpression network analysis (WGCNA), Cox regression, and Lasso regression analyses. The predictive ability was validated by Kaplan−Meier (KM) and receiver operating characteristic (ROC) curves in the internal dataset, external dataset, and clinical study. The immunophenoscore (IPS)-PD1/PD-L1 blocker and IPS-CTLA4 blocker data of LUAD were obtained in TCIA to predict the response to immune checkpoint inhibitors (ICIs). The expression levels of immune checkpoint molecules and markers for hyperprogressive disease were analyzed. Results: A six-IRL signature was identified, and patients were stratified into high- and low-risk groups. The low-risk had improved survival outcome (p = 0.006 in the training dataset, p = 0.010 in the testing dataset, p < 0.001 in the entire dataset), a stronger response to ICI (p < 0.001 in response to anti-PD-1/PD-L1, p < 0.001 in response to anti-CTLA4), and higher expression levels of immune checkpoint molecules (p < 0.001 in PD-1, p < 0.001 in PD-L1, p < 0.001 in CTLA4) but expressed more biomarkers of hyperprogression in immunotherapy (p = 0.002 in MDM2, p < 0.001 in MDM4). Conclusion: The six-IRL signature exhibits a promising prediction value of clinical prognosis and ICI efficacy in LUAD. Patients with low risk might gain benefits from ICI, although some have a risk of hyperprogressive disease.

Single-cell sequencing analysis and transcriptome analysis constructed the macrophage related gene-related signature in lung adenocarcinoma and verified by an independent cohort

BACKGROUND

Recent studies have emphasized the close relationship between macrophages and tumor immunity, and the prognosis of lung adenocarcinoma (LUAD) patients is intimately linked to this. Nonetheless, the prognostic signature and classification of different immune patterns in LUAD patients based on the macrophages is largely unexplored.

METHODS

Two sc-RNAseq datasets of LUAD patients were collected and reprocessed. The differentially expressed genes (DEGs) related to macrophages between LUAD tissues and normal lung tissues were then identified. Based upon the above genes, three distinct immune patterns in the TCGA-LUAD cohort were identified. The ssGSEA and CIBERSORT were applied for immune profiling and characterization of different subtypes. A four-gene prognostic signature for LUAD patients was established based on the DEGs between the subtypes using stepwise multi-Cox regression. TCGA-LUAD cohort was used as training set. Five GEO-LUAD datasets and an independent cohort containing 112 LUAD samples were used for validation. TIDE (tumor immune dysfunction and exclusion) and drug sensitivity analyses were also performed.

RESULTS

Macrophage-related differentially expressed genes were found out using the publicly available scRNA-seq data of LUAD. Three different immune patterns which were proved to have distinct immune infiltration characteristics in the TCGA-LUAD cohort were recognized based on the above macrophage-related genes. Thereafter, 174 DEGs among the above three different immune patterns were figured out; on the basis of this, a four-gene prognostic signature was constructed. This signature distinguished the prognosis of LUAD patients well in various GSE datasets as well as our independent cohort. Further analyses revealed that patients which had a higher risk score also accompanied with a lower immune infiltration level and a worse response to several immunotherapy biomarkers.

CONCLUSION

This study highlighted that macrophage were significantly associated with TME diversity and complexity. The four-gene prognostic signature could be used for predicting outcomes and immune landscapes for patients with LUAD.

Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Background: Immunotherapy has been a promising approach option for lung cancer.

Method: All the open-accessed data was obtained from the Cancer Genome Atlas (TCGA) database. All the analysis was conducted using the R software analysis.

Results: Firstly, the genes differentially expressed in lung cancer immunotherapy responders and non-responders were identified. Then, the lung adenocarcinoma immunotherapy-related genes were determined by LASSO logistic regression and SVM-RFE, respectively. A total of 18 immunotherapy response-related genes were included in our investigation. Subsequently, we constructed the logistics score model. Patients with high logistics score had a better clinical effect on immunotherapy, with 63.2% of patients responding to immunotherapy, while only 12.1% of patients in the low logistics score group responded to immunotherapy. Moreover, we found that pathways related to immunotherapy were mainly enriched in metabolic pathways such as fatty acid metabolism, bile acid metabolism, oxidative phosphorylation, and carcinogenic pathways such as KRAS signaling. Logistics score was positively correlated with NK cells activated, Mast cells resting, Monocytes, Macrophages M2, dendritic cells resting, dendritic cells activated and eosinophils, while was negatively related to Tregs, macrophages M0, macrophages M1, and mast cells activated. In addition, ERVH48-1 was screened for single-cell exploration. The expression of ERVH48-1 increased in patients with distant metastasis, and ERVH48-1 was associated with pathways such as pancreas beta cells, spermatogenesis, G2M checkpoints and KRAS signaling. The result of quantitative real-time PCR showed that ERVH48-1 was upregulated in lung cancer cells.

Conclusion: Our study developed an effective signature to predict the immunotherapy response of lung cancer patients.

Identification of a novel m5C/m6A-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer (NSCLC) and is associated with high mortality rates. However, effective methods to guide clinical therapeutic strategies for LUAD are still lacking. The goals of this study were to analyze the relationship between an m5C/m6A-related signature and LUAD and construct a novel model for evaluating prognosis and predicting drug resistance and immunotherapy efficacy. We obtained data from LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Based on the differentially expressed m5C/m6A-related genes, we identified distinct m5C/m6A-related modification subtypes in LUAD by unsupervised clustering and compared the differences in functions and pathways between different clusters. In addition, a risk model was constructed using multivariate Cox regression analysis based on prognostic m5C/m6A-related genes to predict prognosis and immunotherapy response. We showed the landscape of 36 m5C/m6A regulators in TCGA-LUAD samples and identified 29 differentially expressed m5C/m6A regulators between the normal and LUAD groups. Two m5C/m6A-related subtypes were identified in 29 genes. Compared to cluster 2, cluster 1 had lower m5C/m6A regulator expression, higher OS (overall survival), higher immune activity, and an abundance of infiltrating immune cells. Four m5C/m6A-related gene signatures consisting of HNRNPA2B1, IGF2BP2, NSUN4, and ALYREF were used to construct a prognostic risk model, and the high-risk group had a worse prognosis, higher immune checkpoint expression, and tumor mutational burden (TMB). In patients treated with immunotherapy, samples with high-risk scores had higher expression of immune checkpoint genes and better immunotherapeutic efficacy than those with low-risk scores. We concluded that the m5C/m6A regulator-related risk model could serve as an effective prognostic biomarker and predict the therapeutic sensitivity of chemotherapy and immunotherapy.

Comprehensive analysis of somatic mutator-derived and immune infiltrates related lncRNA signatures of genome instability reveals potential prognostic biomarkers involved in non-small cell lung cancer

Background: The function and features of long non-coding RNAs (lncRNAs) are already attracting attention and extensive research on their role as biomarkers of prediction in lung cancer. However, the signatures that are both related to genomic instability (GI) and tumor immune microenvironment (TIME) have not yet been fully explored in previous studies of non-small cell lung cancer (NSCLC). Method: The clinical characteristics, RNA expression profiles, and somatic mutation information of patients in this study came from The Cancer Genome Atlas (TCGA) database. Cox proportional hazards regression analysis was performed to construct genomic instability-related lncRNA signature (GIrLncSig). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the potential functions of lncRNAs. CIBERSORT was used to calculate the proportion of immune cells in NSCLC. Result: Eleven genomic instability-related lncRNAs in NSCLC were identified, then we established a prognostic model with the GIrLncSig ground on the 11 lncRNAs. Through the computed GIrLncSig risk score, patients were divided into high-risk and low-risk groups. By plotting ROC curves, we found that patients in the low-risk group in the test set and TCGA set had longer overall survival than those in the high-risk group, thus validating the survival predictive power of GIrLncSig. By stratified analysis, there was still a significant difference in overall survival between high and low risk groups of patients after adjusting for other clinical characteristics, suggesting the prognostic significance of GIrLncSig is independent. In addition, combining GIrLncSig with TP53 could better predict clinical outcomes. Besides, the immune microenvironment differed significantly between the high-risk and the low-risk groups, patients with low risk scores tend to have upregulation of immune checkpoints and chemokines. Finally, we found that high-risk scores were associated with increased sensitivity to chemotherapy. Conclusion: we provided a new perspective on lncRNAs related to GI and TIME and revealed the worth of them in immune infiltration and immunotherapeutic response. Besides, we found that the expression of AC027288.1 is associated with PD-1 expression, which may be a potential prognostic marker in immune checkpoint inhibitor response to improve the prediction of clinical survival in NSCLC patients.

Prognostic Modeling of Lung Adenocarcinoma Based on Hypoxia and Ferroptosis-Related Genes

Background. It is well known that hypoxia and ferroptosis are intimately connected with tumor development. The purpose of this investigation was to identify whether they have a prognostic signature. To this end, genes related to hypoxia and ferroptosis scores were investigated using bioinformatics analysis to stratify the risk of lung adenocarcinoma. Methods. Hypoxia and ferroptosis scores were estimated using The Cancer Genome Atlas (TCGA) database-derived cohort transcriptome profiles via the single sample gene set enrichment analysis (ssGSEA) algorithm. The candidate genes associated with hypoxia and ferroptosis scores were identified using weighted correlation network analysis (WGCNA) and differential expression analysis. The prognostic genes in this study were discovered using the Cox regression (CR) model in conjunction with the LASSO method, which was then utilized to create a prognostic signature. The efficacy, accuracy, and clinical value of the prognostic model were evaluated using an independent validation cohort, Receiver Operator Characteristic (ROC) curve, and nomogram. The analysis of function and immune cell infiltration was also carried out. Results. Here, we appraised 152 candidate genes expressed not the same, which were related to hypoxia and ferroptosis for prognostic modeling in The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) cohort, and these genes were further validated in the GSE31210 cohort. We found that the 14-gene-based prognostic model, utilizing MAPK4, TNS4, WFDC2, FSTL3, ITGA2, KLK11, PHLDB2, VGLL3, SNX30, KCNQ3, SMAD9, ANGPTL4, LAMA3, and STK32A, performed well in predicting the prognosis in lung adenocarcinoma. ROC and nomogram analyses showed that risk scores based on prognostic signatures provided desirable predictive accuracy and clinical utility. Moreover, gene set variance analysis showed differential enrichment of 33 hallmark gene sets between different risk groups. Additionally, our results indicated that a higher risk score will lead to more fibroblasts and activated CD4 T  cells but fewer myeloid dendritic cells, endothelial cells, eosinophils, immature dendritic cells, and neutrophils. Conclusion. Our research found a 14-gene signature and established a nomogram that accurately predicted the prognosis in patients with lung adenocarcinoma. Clinical decision-making and therapeutic customization may benefit from these results, which may serve as a valuable reference in the future.

Study of PD-1 Customization and Autoimmune T Cells for Advanced Colorectal Cancer with High MSI Expression

Objective

To evaluate the significance of PD-1 customization and autoimmune T-cell therapy for advanced colorectal cancer with high MSI expression.

Methods

One hundred and eight patients with advanced colorectal cancer with high MSI expression admitted to our hospital between August 2019 and January 2022 were divided into control and study groups, and PD-1 customization and autoimmune T-cell therapy were administered to the two groups, respectively. Trends in immune indexes, PD-1 exposure, and survival rates were studied in both groups.

Results

The treatment efficiency of the study group was 90.74%, which was higher than that of the control group (61.11%) (P < 0. 05); after treatment, the presence of CDl07a, perforin, and GranB cells was significantly higher in both groups compared with that before treatment, but the expression of PD-1 was more pronounced in the study group (P < 0. 05); that is, the expression of PD-1 in peripheral T lymphocytes in the study group compared with that of the control group was higher in patients with grade III-IV, and peripheral T lymphocytes were also higher in patients with grade III-IV compared with patients with grade I-II (P < 0. 05).

Conclusion

PD-1 customization combined with autoimmune T-cell therapy is a novel therapeutic modality that can substantially improve.

The RIPK family: expression profile and prognostic value in lung adenocarcinoma

Receptor interacting protein kinases (RIPKs) are a family of serine/threonine kinases which are supposed to regulate tumor generation and progression. Rare study illustrates the roles and functions of RIPKs family in lung adenocarcinoma (LUAD) comprehensively. Our results indicated that the expression of RIPK2 higher in LUAD patients while RIPK5 (encoded by gene DSTYK) expression was lower. Only RIPK2 had a strong correlation with pathological stage in LUAD patients. Kaplan-Meier plotter revealed that LUAD patients with low RIPK2 or RIPK3 level showed better overall survival (OS), but worse when LUAD patients with high RIPK5. Further, lower expression of RIPK2 and higher expression of RIPK1, RIPK4 and RIPK5 prompted a longer disease free survival (DFS). Genetic alterations based on cBioPortal revealing 16% alteration rates of RIPK2, as well as RIPK5. We also found that the functions of RIPKs family were linked to cellular senescence, protein serine/threonine kinase activity, apoptosis process et al. TIMER database indicated that the RIPKs family members had distinct relationships with the infiltration of six types of immune cells (macrophages, neutrophils, CD8+ T-cells, B-cells, CD4+ T-cells and dendritic cells). Moreover, RIPK2 could be observed as an independent prognostic factor with Cox proportional hazard model analysis. DiseaseMeth databases revealed that the global methylation levels of RIPK2 increased in LUAD patients. Thus, the findings above will enhance the understanding of RIPKs family in LUAD pathology and progression, providing novel insights into RIPKs-core therapy for LUAD patients.

Necroptosis Identifies Novel Molecular Phenotypes and Influences Tumor Immune Microenvironment of Lung Adenocarcinoma

This study aims to investigate the immune and epigenetic mutational landscape of necroptosis in lung adenocarcinoma (LUAD), identify novel molecular phenotypes, and develop a prognostic scoring system based on necroptosis regulatory molecules for a better understanding of the tumor immune microenvironment (TIME) in LUAD. Based on the Cancer Genome Atlas and Gene Expression Omnibus database, a total of 29 overlapped necroptosis-related genes were enrolled to classify patients into different necroptosis phenotypes using unsupervised consensus clustering. We systematically correlated the phenotypes with clinical features, immunocyte infiltrating levels, and epigenetic mutation characteristics. A novel scoring system was then constructed, termed NecroScore, to quantify necroptosis of LUAD by principal component analysis. Three distinct necroptosis phenotypes were confirmed. Two clusters with high expression of necroptosis-related regulators were “hot tumors”, while another phenotype with low expression was a “cold tumor”. Molecular characteristics, including mutational frequency and types, copy number variation, and regulon activity differed significantly among the subtypes. The NecroScore, as an independent prognostic factor (HR=1.086, 95%CI=1.040-1.133, p<0.001), was able to predict the survival outcomes and show that patients with higher scores experienced a poorer prognosis. It could also evaluate the responses to immunotherapy and chemotherapeutic efficiency.

In conclusion, necroptosis-related molecules are correlated with genome diversity in pan-cancer, playing a significant role in forming the TIME of LUAD. Necroptosis phenotypes can distinguish different TIME and molecular features, and the NecroScore is a promising biomarker for predicting prognosis, as well as immuno- and chemotherapeutic benefits in LUAD.

Deglycosylation of pathological specimens alters performance of diagnostic PDL1 antibodies

Immunohistochemical (IHC) predictive quantitation of PDL1 expression is obligatory in many cancer entities with improved response to immune checkpoint inhibition in PDL1-positive subgroups. With recent demonstration of increased positivity rates after enzymatic deglycosylation in breast cancer specimens, a comparative analysis with two different antibodies and extended controls was performed in a cohort of head and neck squamous cell cancer samples (HNSCC).Formalin-fixed paraffin-embedded tissue from HNSCC specimens was used for initial on-slide method optimization based on the PNGase F assay. SDS-PAGE and immunoblotting with the PDL1 antibody 28-8 was performed to evaluate deglycosylation efficiency. A tissue micro array of n = 527 tissue cores of 181 patients with HNSCC was used to determine the effects of deglycosylation on staining pattern and intensity with PDL1 antibodies 28-8 and E1L3N.Successful on-slide deglycosylation with PNGase F was confirmed by immunoblot but varied across replicates. Using E1L3N (intracellular binding domain, most probably not glycosylated), mean signal intensity as well as the fraction of PDL1 positive cells was increased by deglycosylation. Opposite effects were observed with 28-8 (extracellular binding domain, glycosylated).Deglycosylation reduces diagnostic performance of the PDL1 antibody 28-8. In contrast, effects for E1L3N are complex and probably involve reduction of off-target binding leading to specifically improved signal intensity. However, enzymatic deglycosylation adds further variance to IHC.

Bone Marrow Mesenchymal Stem Cells (BMSCs)-Triggered Up-Regulation of miR-1297/NLR Family Pyrin Domain Containing 3 (NLRP3) Facilitates the Aggressive Proliferation of Lung Cancer Cells via Inducing Inflammatory Factor Release

miR-1297 derived from BMSC-originated exosomes participates in modulating multiple malignancies. Our study aims to clarify the effect of miR-1297 derived from BMSC-originated exosomes on the oxidative stress and inflammatory damage of lung cancer cells. miR-1297 and NLRP3 level was measured in lung cancer tissues and para-cancerous tissues, as well as in lung cancer cell lines and pulmonary epithelial cells. After miR-1297-mimics transfection or BMSC co-cultivation, cell viability was assessed by MTT and cytokines were evaluated by ELISA along with analysis of SOD activity and cell apoptosis. miR-1297 and NLRP3 were significantly elevated in lung cancer tissues and cell lines. Overexpression of miR-1297 enhanced oxidative stress and inflammatory response, along with increased cell viability and decreased apoptosis. Additionally, co-culture with BMSC protect the viability of lung cancer cells by facilitating miR-1297/NLRP3. In conclusion, a significant elevation of miR-1297 is found in lung cancer tissues and cells. Its overexpression induced the release of inflammatory factors, thereby protecting the proliferating activity of lung cancer cells and restraining apoptosis, indicating that miR-1297 may serve a promising target for early diagnosis of lung cancers.

PD-L1 Regulates Platelet Activation and Thrombosis via Caspase-3/GSDME Pathway

Platelets play a central role in hemostasis and thrombosis, regulating the occurrence and development of thrombotic diseases, including ischemic stroke. Programmed death ligand 1 (PD-L1) has recently been detected in platelet, while the function of PD-L1 in platelets remain elusive. Our data reveal a novel mechanism for the role of PD-L1 on platelet activation and arterial thrombosis. PD-L1 knockout does not affect platelet morphology, count, and mean volume under homeostasis and without risk of bleeding, which inhibits platelet activation by suppressing outside-in-activation of integrin by downregulating the Caspase-3/GSDME pathway. Platelet adoptive transfer experiments demonstrate that PD-L1 knockout inhibits thrombosis. And the absence of PD-L1 improves ischemic stroke severity and increases mice survival. Immunohistochemical staining of the internal structure of the thrombus proves that PD-L1 enhances the seriousness of the thrombus by inhibiting platelet activation. This work reveals a regulatory role of PD-L1 on platelet activation and thrombosis while providing novel platelet intervention strategies to prevent thrombosis.

SNCA correlates with immune infiltration and serves as a prognostic biomarker in lung adenocarcinoma

BACKGROUND

The SNCA gene is a critical gene in Parkinson's disease (PD) pathology. Accumulating evidence indicates that SNCA is involved in tumorigenesis; however, the role of SNCA in lung adenocarcinoma (LUAD) remains unclear. This study aimed to explore the potential value of SNCA as a prognostic and diagnostic molecular marker in LUAD.

METHODS

In this study, we explored the expression pattern, prognostic value, and promoter methylation status of SNCA in LUAD based on Oncomine, UALCAN, and Kaplan-Meier Plotter. Then, using TIMER, we investigated the correlation between SNCA expression and immune infiltration. And cBioPortal were used to analysis the correlation between SNCA expression and immune checkpoint. The transcriptome data of A549 cells overexpressing SNCA were used to further study the potential immune role of SNCA in LUAD. The effect of SNCA on proliferation of A549 cells were evaluated by CCK-8, EdU and colony formation. Finally, LUAD cell lines treated with 5-aza-dC were used to explore the correlation between increased promoter methylation and downregulated mRNA expression of SNCA.

RESULTS

In general, the expression level of SNCA in LUAD tissue was lower than that in normal tissue, and high expression of SNCA was related to better prognosis. There were significant positive correlations between SNCA expression and immune infiltrations, including CD8+ T cells, macrophages, neutrophils, dendritic cells, B cells, and CD4+ T cells, and immune checkpoints, suggesting that immune infiltration was one of the reasons for the influence of SNCA on prognosis in LUAD. The transcriptome data of A549 cells overexpressing SNCA were further used to screen the relevant immune-related genes regulated by SNCA. Enrichment analysis confirmed that SNCA participates in the PI3K-AKT signaling pathway and other key tumor signaling pathways and regulates the expression of MAPK3, SRC, PLCG1, and SHC1. Cellular proliferation assay showed that SNCA could inhabit the growth of A549 cells via inhibiting activity of PI3K/AKT/ mTOR pathway. Finally, analysis of the methylation level of SNCA promoter showed that the promoter methylation negatively correlated with mRNA level. The expression of SNCA in LUAD cell lines was significantly upregulated by treatment with 5-aza-dC.

CONCLUSION

High methylation of SNCA promoter in LUAD is one of the reasons for the downregulation of SNCA mRNA level. Given that SNCA could inhibit the proliferation of A549 cells and correlates with immune infiltrates, it may serve as a prognostic biomarker in LUAD.

circ_0004140 promotes LUAD tumor progression and immune resistance through circ_0004140/miR-1184/CCL22 axis

Lung adenocarcinoma (LUAD) is a highly prevalent cancer with high mortality. Immune resistance and tumor metastasis are the pivotal factors for the promotion of LUAD. CircRNAs have been revealed a crucial pre-clinical diagnostic and therapeutic potentials in LUAD. Herein, we identify a novel circRNA (circ_0004140), derived from the oncogene YAP1, which is up-regulated in LUAD. The high expression of circ_0004140 is correlated with poor prognosis and CTL cells dysfunction in LUAD patients. Knockdown of circ_0004140 regulated LUAD cells proliferation, migration, and apoptosis. Mechanistically, circ_0004140 served as a sponge of miR-1184 targeting C-C motif chemokine ligand 22(CCL22). Overexpression of CCL22 reversed the inhibitory effect induced by si-circ_0004140 on cells proliferation and migration. Moreover, we also revealed that elevated circ_ooo4140 was related to cytotoxic lymphocyte exhaustion, and a combination therapy of C-021 (CCL22/CCR4 axis inhibitor) and anti-PD-1 attenuated LUAD promotion and immune resistance. In conclusion, circ_0004140 may drive resistance to anti-PD-1 immunotherapy, providing a novel potential therapeutic target for LUAD treatment.

Clinical Implications of Circulating Circular RNAs in Lung Cancer

Circular RNAs (circRNAs) are single-stranded RNAs with a covalently closed-loop structure that increases their stability; thus, they are more advantageous to use as liquid biopsy markers than linear RNAs. circRNAs are thought to be generated by back-splicing of pre-mRNA transcripts, which can be facilitated by reverse complementary sequences in the flanking introns and trans-acting factors, such as splicing regulatory factors and RNA-binding factors. circRNAs function as miRNA sponges, interact with target proteins, regulate the stability and translatability of other mRNAs, regulate gene expression, and produce microproteins. circRNAs are also found in the body fluids of cancer patients, including plasma, saliva, urine, and cerebrospinal fluid, and these “circulating circRNAs” can be used as cancer biomarkers. In lung cancer, some circulating circRNAs have been reported to regulate cancer progression and drug resistance. Circulating circRNAs have significant diagnostic value and are associated with the prognosis of lung cancer patients. Owing to their functional versatility, heightened stability, and practical applicability, circulating circRNAs represent promising biomarkers for lung cancer diagnosis, prognosis, and treatment monitoring.

Serum exosomal miR ‐16‐5p functions as a tumor inhibitor and a new biomarker for PD‐L1 inhibitor‐dependent immunotherapy in lung adenocarcinoma by regulating PD‐L1 expression

Objectives

We aimed at investigating whether serum exosomal miR‐16‐5p could be utilized as an immunotherapy biomarker in lung adenocarcinoma (LUAD) patients administered by programmed cell death ligand‐1 (PD‐L1) inhibitors, and to evaluate its functions in LUAD progression.

Methods

Sixty LUAD sufferers and 20 healthy controls (HCs) were covered in this work. We applied both IHC and WB to examine PD‐L1 level in clinical tissue samples and utilized WB to quantify PD‐L1 expression in LUAD cells and LUAD xenograft tissues, respectively. Transmission electron microscopy (TEM), WB, and nanoparticle tracking analysis (NTA) were executed to confirm the exosomes isolated from serum specimens and cell culture media. To quantify of exosomal miR‐16‐5p level from serum and culture medium of cultured cell, qRT‐PCR experiment was utilized. The connection between tissue PD‐L1 level and serum exosomal miR‐16‐5p expression in PD‐L1‐positive sufferers administered by PD‐L1 inhibitors was verified using Spearman correlation coefficient analysis. In addition, the overall survival (OS) and progression‐free survival (PFS) rates among PD‐L1 inhibitor managed sufferers were acquired through a follow‐up visit. Finally, we used a group of assays, including 5‐bromo‐2′‐dexoyuridine (BrdU) and colony formation test, wound healing experiment, flow cytometry, and nude mice xenograft experiment, to explore the functions of circulating exosomal miR‐16‐5p on LUAD cell proliferation, apoptosis, and migration, as well as tumor development, respectively.

Results

PD‐L1 expression was positively related to T stage (tumor size stage), and PD‐L1 inhibitor treatment reduced the PD‐L1 expression and mitigated T stage in PD‐L1‐positive LUAD sufferers. For PD‐L1‐positive LUAD sufferers, elevated PD‐L1 expression or reduced serum exosomal miR‐16‐5p level were linked to longer PFS and OS upon PD‐L1 inhibitor treatment. The number of exosomes in patient's serum was more than that in the serum of healthy individuals, and PD‐L1 inhibitor treatment decreased the number of serum‐derived exosomes in PD‐L1‐positive LUAD sufferers. Exosome‐derived miR‐16‐5p was downregulated in patient's serum and cell culture medium, and this was negatively linked to tumor stage and PD‐L1 expression. Meanwhile, PD‐L1 inhibitor treatment could increase the serum exosomal miR‐16‐5p expression, and the expression change of serum exosomal miR‐16‐5p was diametrically related to PD‐L1 after the treatment. Moreover, the overexpression of PD‐L1 accelerated tumor growth and decreased the exosomal miR‐16‐5p content in cell culture media, while exosomal miR‐16‐5p overexpression in cell culture media inhibited tumor development by decreasing the PD‐L1 expression. Exosomal miR‐16‐5p overexpression in cell culture media also depressed LUAD cell proliferation and migration, and stimulated cell apoptosis, especially in the cells which cultured in the mediums with PD‐L1 inhibitor in vitro.

Conclusions

Serum exosomal miR‐16‐5p may be a latent tumor inhibitor and a new biomarker for PD‐L1 inhibitor‐dependent immunotherapy in LUAD by regulating the PD‐L1 expression.

LncRNA-AC068228.1 Is a Novel Prognostic Biomarker That Promotes Malignant Phenotypes in Lung Adenocarcinoma

Background

The crucial roles played by lncRNA-AC068228.1 in primary malignant cancer remain poorly understood. This study aimed at examining the clinical significance and evaluating the biological function of AC068228.1 in lung adenocarcinoma (LUAD).

Methods

We used data obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and the Gene Expression Omnibus (GEO) database to examine the expression of AC068228.1 in LUAD patients, and the prognostic and diagnostic value of those levels. Functional experiments were conducted to determine the function of AC068228.1 on LUAD cells. Signaling pathway enrichment analysis of AC068228.1 was conducted using the clusterProfiler and Gene Set Enrichment Analysis (GSEA) software. We analyzed the correlation between AC068228.1 expression and immune infiltration level in LUAD using the single-sample gene set enrichment analysis (ssGSEA) method by the R package GSVA.

Results

AC068228.1 expression was significantly elevated in LUAD tissues compared with normal tissues. Higher expression of AC068228.1 was strongly correlated with adverse clinical outcomes and was identified as an independent prognostic marker for LUAD patients. GSEA and infiltration analysis confirmed that AC068228.1 expression was significantly correlated with immune cells infiltrating in LUAD. Knockdown of AC068228.1 inhibited the cell proliferation and cell migration of LUAD.

Conclusions

AC068228.1 was upregulated in LUAD and was significantly correlated with adverse clinical outcomes. Meanwhile, it was associated with immune cell infiltration and could be used as a promising diagnostic and prognostic biomarker for LUAD patients.

Identification of Tumor Antigens and Immune Subtypes in Lung Adenocarcinoma for mRNA Vaccine Development

Cancer vaccines are emerging as a viable strategy for cancer treatment. In the current study, we screened for genes associated with the prognosis of patients with lung adenocarcinoma and positively correlated with antigen-presenting cell infiltration and identified KLRG1 and CBFA2T3 as potential tumor antigens for mRNA vaccines in lung adenocarcinoma (LUAD). Further analyses of immune subtypes revealed that patients with early-stage LUAD, high immune cell infiltration, high immune checkpoint expression, and low tumor mutation burden might benefit from mRNA vaccination. Moreover, we identified four biomarkers that can be used to assess mRNA vaccination suitability. We also identified potentially sensitive anti-cancer drugs for populations not suitable for vaccination by means of anti-cancer drug susceptibility prediction. Overall, we provided a new perspective for mRNA vaccine treatment strategies for LUAD and emphasized the importance of precise and personalized treatments.