Immune Escape Mechanisms in Non Small Cell Lung Cancer

Roles of naïve CD4+ T cells and their differentiated subtypes in lung adenocarcinoma and underlying potential regulatory pathways

BACKGROUND

Naïve CD4+ T cells and their differentiated counterparts play a significant regulatory role in the tumor immune microenvironment, yet their effects on lung adenocarcinoma (LUAD) are not fully understood.

METHODS

We utilized Mendelian randomization to assess the causal association between naïve CD4+ T cells and LUAD. Employing a modified single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm with The Cancer Genome Atlas (TCGA) database, we determined the infiltration levels of naïve CD4+ T cells and their differentiation subtypes and investigated their correlation with clinical characteristics. Potential regulatory pathways of T helper cells were identified through Mantel tests and Kyoto Encyclopedia of Genes and Genomes (KEGG) database enrichment analysis.

RESULTS

Mendelian randomization analysis revealed an inhibitory effect of naïve CD4+ T cells on LUAD (false discovery rate < 0.05), which was corroborated by observational experiments using TCGA database. Specifically, T helper cell type 2 demonstrated a promotive effect on LUAD in terms of overall, disease-free, and progression-free survival (p < 0.05). Moreover, regulatory T cells exhibited a protective effect on LUAD in terms of disease-specific survival (p < 0.01). Concurrently, we explored the overall impact of naïve CD4+ T cell differentiation subtypes on LUAD, revealing upregulation in pathways such as neutrophil degranulation, MAPK family signaling pathways, and platelet activation, signaling, and aggregation.

CONCLUSION

Naïve CD4+ T cells and their differentiated counterparts play essential regulatory roles in the tumor immune microenvironment, demonstrating bidirectionality in their effects.Thus, elucidating the mechanisms and developing novel cell differentiation-inducing agents will benefit anti-cancer therapy.

Utility of neutrophil-to-lymphocyte ratio as an indicator of tumor immune status in non-small cell lung cancer

BACKGROUND

Neutrophil-to-lymphocyte ratio (NLR) has been reported as a prognostic biomarker in non-small cell lung cancer (NSCLC); however, the underlying biological rationale remains unclear. The present study aimed to explore the potential utility of NLR as a surrogate biomarker for immune response to cancer and to elucidate the underlying mechanism.

METHODS

This retrospective study included the medical records of 120 patients with NSCLC who underwent surgery at the study institution in 2012. NLR in peripheral blood was determined from blood test within 30 days before surgery. Tumor immune status was evaluated using immunohistochemical staining to identify CD3+, CD8+ and FOXP3+ tumor-infiltrating lymphocytes (TILs), and the relationship of NLR, with clinicopathologic characteristics including 5-year overall survival (OS), and the tumor immune status was investigated. The median values of NLR and TIL count were used as cutoff points.

RESULTS

The 5-year OS was significantly better in patients with low NLR (<2.2) than in those with high NLR (≥2.2) (70.1% vs. 56.8%, P = 0.042) and in patients with high CD3+ TIL count (≥242) than in those with low CD3+ TIL count (<242) (70% vs. 56.8%, P = 0.019). Additionally, the CD3+ TIL count was negatively correlated with preoperative NLR (P = 0.005).

CONCLUSION

NLR might potentially reflect the immune status of tumor microenvironment, explaining its impact on prognosis of patients with NSCLC.

Predictive role and molecular biological function of proline-rich small repeat protein SPRR3 in the diagnosis of lung adenocarcinoma

The fascinating role of SPRR3 in various malignant tumors has prompted extensive research to unravel its expression patterns and prognostic significance. To comprehensively investigate SPRR3, we leveraged multiple datasets containing invaluable biomedical information, specifically focusing on the comparative analysis of SPRR3 gene expression levels across different cancer types. Meticulous examination of lung adenocarcinoma allowed us to delve deeper into the correlation between SPRR3 expression and its molecular biological functions. Our comprehensive analysis encompassed 33 malignant tumors, and the results unveiled significant differential expression of SPRR3 across a range of malignancies. Moreover, this aberrant expression of SPRR3 was observed to be closely associated with poorer prognosis in these malignant tumors. Notably, our investigation also unearthed a compelling link between SPRR3 and immune infiltrating cells in lung adenocarcinoma. The utilization of receiver operating characteristic (ROC) curves and survival curves in our study illustrated the immense potential of SPRR3 as a highly accurate predictor of cancer. These findings further emphasize the possibility of SPRR3 serving as a promising diagnostic and prognostic biomarker for a diverse array of cancers.

Lactate-induced activation of tumor-associated fibroblasts and IL-8-mediated macrophage recruitment promote lung cancer progression

Alterations in the tumor microenvironment are closely associated with the metabolic phenotype of tumor cells. Cancer-associated fibroblasts (CAFs) play a pivotal role in tumor growth and metastasis. Existing studies have suggested that lactate produced by tumor cells can activate CAFs, yet the precise underlying mechanisms remain largely unexplored. In this study, we initially identified that lactate derived from lung cancer cells can promote nuclear translocation of NUSAP1, subsequently leading to the recruitment of the transcriptional complex JUNB-FRA1-FRA2 near the DESMIN promoter and facilitating DESMIN transcriptional activation, thereby promoting CAFs' activation. Moreover, DESMIN-positive CAFs, in turn, secrete IL-8, which recruits TAMs or promotes M2 polarization of macrophages, further contributing to the alterations in the tumor microenvironment and facilitating lung cancer progression. Furthermore, we observed that the use of IL-8 receptor antagonists, SB225002, or Navarixin, significantly reduced TAM infiltration and enhanced the therapeutic efficacy of anti-PD-1 or anti-PD-L1 treatment. This finding indicates that inhibiting IL-8R activity can attenuate the impact of CAFs on the tumor microenvironment, thus restraining the progression of lung cancer.

Identification and validation of tryptophan-related gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma reveals a critical role for PTTG1

Introduction

Tryptophan metabolism is strongly associated with immunosuppression and may influence lung adenocarcinoma prognosis as well as tumor microenvironment alterations.

Methods

Sequencing datasets were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Two different clusters were identified by consensus clustering, and prognostic models were established based on differentially expressed genes (DEGs) in the two clusters. We investigated differences in mutational landscapes, enrichment pathways, immune cell infiltration, and immunotherapy between high- and low-risk scoring groups. Single-cell sequencing data from Bischoff et al. were used to identify and quantify tryptophan metabolism, and model genes were comprehensively analyzed. Finally, PTTG1 was analyzed at the pan-cancer level by the pan-TCGA cohort.

Results

Risk score was defined as an independent prognostic factor for lung adenocarcinoma and was effective in predicting immunotherapy response in patients with lung adenocarcinoma. PTTG1 is one of the key genes, and knockdown of PTTG1 in vitro decreases lung adenocarcinoma cell proliferation and migration and promotes apoptosis and down-regulation of tryptophan metabolism regulators in lung adenocarcinoma cells.

Discussion

Our study revealed the pattern and molecular features of tryptophan metabolism in lung adenocarcinoma patients, established a model of tryptophan metabolism-associated lung adenocarcinoma prognosis, and explored the roles of PTTG1 in lung adenocarcinoma progression, EMT process, and tryptophan metabolism.

A disulfidptosis-related glucose metabolism and immune response prognostic model revealing the immune microenvironment in lung adenocarcinoma

Background

Lung adenocarcinoma accounts for the majority of lung cancer cases and impact survival rate of patients severely. Immunotherapy is an effective treatment for lung adenocarcinoma but is restricted by many factors including immune checkpoint expression and the inhibitory immune microenvironment. This study aimed to explore the immune microenvironment in lung adenocarcinoma via disulfidptosis.

Methods

Public datasets of lung adenocarcinoma from the TCGA and GEO was adopted as the training and validation cohort. Based on the differences in the expression of disulfidptosis -related genes, a glucose metabolism and immune response prognostic model was constructed. The prognostic value and clinical relationship of the model were further explored. Immune-related analyses were performed according to CIBERSORT, ssGSEA, TIDE, IPS.

Results

We verified that the model could accurately predict the survival expectancy of lung adenocarcinoma patients. Patients with lung adenocarcinoma and a low-risk score had better survival outcomes according to the model. Moreover, the high-risk group tended to have an immunosuppressive effect, as reflected by the immune cell components, phenotypes and functions. We also found that the clinically relevant immune checkpoint CTLA-4 was significantly higher in low-risk group (P<0.05), indicating that the high-risk group may suffer worse tumor immunotherapy efficacy. Finally, we found that this model has accurate predictive value for the efficacy of immune checkpoint blockade in non-small cell lung cancer (P<0.05).

Conclusion

The prognostic model demonstrated the feasibility of predicting survival and immunotherapy efficacy via disulfidptosis-related genes and will facilitate the development of personalized anticancer therapy.

The Novel Fusion Protein Melittin-MIL-2 Exhibits Strong Antitumor Immune Effect in Lung Adenocarcinoma Cell A549

In previous studies, we developed a novel fusion protein named "melittin-MIL-2" which exhibited more anti-tumor activity. However, it remains unclear whether melittin-MIL-2 possesses antitumor immune effect on lung adenocarcinoma. In this study, the immune effect and mechanism of melittin-MIL-2 inhibiting the growth and invasion of lung adenocarcinoma will be investigated, in order to provide novel perspectives for the immunotherapy of lung cancer. The results indicated that melittin-MIL-2 promoted T cell proliferation, enhanced NK cell cytotoxicity, and boosted IFN-γ secretion in PBMCs. After melittin-MIL-2 stimulation, perforin expression and LAK/NK-like killing activities of human PBMCs and NK cells were significantly enhanced. Melittin-MIL-2 is capable of hampering the development and proliferation of lung adenocarcinoma cell A549. ICAM-1 and Fas expression in A549 cells exposed to melittin-MIL-2 rose significantly. The expression levels of TLR8 and VEGF in A549 cells decreased significantly after melittin-MIL-2 stimulation. In vivo, melittin-MIL-2 substantially impeded the growth of lung adenocarcinoma and formed an immune-stimulating microenvironment locally in tumor tissues. In conclusion, the novel fusion protein melittin-MIL-2 exhibits strong anti-tumor immune effect in lung adenocarcinoma cell A549 via activating the LFA-1/ICAM-1 and Fas/FasL pathways to enhance cytolytic activity, upregulating the secretion of IFN-γ and perforin, and boosting LAK/NK-like killing activities. Immuno-effector cells and their secreted cytokines can form immune stimulation microenvironment locally in lung adenocarcinoma Lewis mice tissue.

The prognostic value of immune escape-related genes in lung adenocarcinoma

Background

Lung cancer is one of the most common cancers in humans, and lung adenocarcinoma (LUAD) has become the most common histological type of lung cancer. Immune escape promotes progression of LUAD from the early to metastatic late stages and is one of the main obstacles to improving clinical outcomes for immunotherapy targeting immune detection points. Our study aims to explore the immune escape related genes that are abnormally expressed in lung adenocarcinoma, providing assistance in predicting the prognosis of lung adenocarcinoma and targeted.

Methods

RNA data and related clinical details of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Through weighted gene coexpression network analysis (WGCNA), 3112 key genes were screened and intersected with 182 immune escape genes obtained from a previous study to identify the immune escape-related genes (IERGs). The role of IERGs in LUAD was systematically explored through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses, which were used to enrich the relevant pathways of IERGs. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis were used to identify the key prognostic genes, and a prognostic risk model was constructed. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) and microenvironment cell populations (MCP) counter methods (which can accurately assess the amount of eight immune cell populations and two stromal cell groups) were used to analyze the tumor immune status of the high and low risk subgroups. The protein expression level of the differentially expressed genes in lung cancer samples was determined by using the Human Protein Atlas (HPA) database. A nomogram was constructed, and the prognostic risk model was verified via the Gene Expression Omnibus (GEO) datasets GSE72094 and GSE30219.

Results

Twenty differentially expressed IERGs were obtained. GO analysis of these 20 IERGs revealed that they were mainly associated with the regulation of immune system processes, immune responses, and interferon-γ enrichment in mediating signaling pathways and apoptotic signaling pathways; meanwhile, KEGG analysis revealed that IERGs were associated with necroptosis, antigen processing and presentation, programmed cell death ligand 1 (PD-L1) expression and programmed cell death 1 (PD-1) pathway in tumors, cytokine-cytokine receptor interactions, T helper cell 1 (Th1) and Th2 differentiation, and tumor necrosis factor signaling pathways. Using LASSO and Cox regression analysis, we constructed a four-gene model that could predict the prognosis of patients with LUAD, and the model was validated with a validation cohort. The immunohistochemical results of the HPA database showed that AHSA1 and CEP55 had low expression in normal lung tissue but high expression in lung cancer tissue.

Conclusions

We constructed an IERG-based model for predicting the prognosis of LUAD. Among the genes identified, CEP55 and AHSA1 may be potential prognostic and therapeutic targets, and reducing their expression may represent a novel approach in the treatment of LUAD.

LINC00665 promotes the progression and immune evasion of lung cancer by facilitating the translation of TCF7 protein through dependence on IRES

OBJECTIVE

To investigate the influence of LINC00665 on the development and immune evasion of lung cancer.

METHODS

Tumor tissues and corresponding adjacent tissues were collected from 84 lung cancer patients, categorized into non-metastatic (n = 58) and metastatic (n = 26) groups. LINC00665 expression in lung cancer and metastatic lung cancer tissues was assessed via qRT-PCR. Pearson correlation analysis was conducted to examine the correlation between LINC00665 and immune-modulating cytokines (TGF-β, IL-10, IL-1β, IFN-γ, IL-2, TNF-α). A549 and H1299 cells, with relatively high LINC00665 expression, were used for in vitro studies. Cells were transfected with LINC00665-targeting shRNA, and changes in proliferation, apoptosis, migration, invasion, and NK cell cytotoxicity were assessed. Downstream molecular mechanisms of LINC00665 were investigated using GEO database analysis, highlighting the association with HHLA2. LINC00665's role in promoting HHLA2 expression via binding with TCF7 was explored. In low LINC00665-expressing A549/H1299 cells, overexpression of HHLA2 was performed to evaluate effects on malignant behavior and NK cell sensitivity. A xenograft model was established for in vivo validation through tumor volume and weight measurements, Ki-67 immunoreactivity analysis, and flow cytometry analysis of CD107a + NK cells.

RESULTS

LINC00665, TCF7 mRNA, and HHLA2 mRNA expression levels were significantly higher in lung cancer tissues than adjacent tissues, with non-metastatic lung cancer showing higher expression than metastatic lung cancer. In metastatic lung cancer, LINC00665 positively correlated with immune-suppressive cytokines (TGF-β, IL-10, IL-1β) and negatively correlated with anti-tumor cytokines (IFN-γ, IL-2, TNF-α). LINC00665 knockdown significantly inhibited lung cancer cell growth and metastasis, promoting sensitivity to NK cells. Further analysis revealed that LINC00665 recruits transcription factor TCF7 to upregulate HHLA2 expression in lung cancer cells, thereby facilitating lung cancer development and immune escape.

CONCLUSION

LINC00665, through recruitment of TCF7 and upregulation of HHLA2, inhibits NK cell cytotoxicity, promoting the development and immune evasion of lung cancer.

Identification of a signature of histone modifiers in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is a cancer that is closely associated with epigenetic alterations, and histone modifiers (HMs) are closely related to epigenetic regulation. Therefore, this study aimed to comprehensively explore the function and prognostic value of HMs-based signature in KIRC. HMs were first obtained from top journal. Then, the mRNA expression profiles and clinical information in KIRC samples were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) datasets. Cox regression analysis and least absolute shrinkage and selection operator (Lasso) analysis were implemented to find prognosis-related HMs and construct a risk model related to the prognosis in KIRC. Kaplan-Meier analysis was used to determine prognostic differences between high- and low-risk groups. Immune infiltration and drug sensitivity analysis were also performed between high- and low-risk groups. Eventually, 8 HMs were successfully identified for the construction of a risk model in KIRC. The results of the correlation analysis between risk signature and the prognosis showed HMs-based signature has good prognostic value in KIRC. Results of immune analysis of risk models showed there were significant differences in the level of immune cell infiltration and expression of immune checkpoints between high- and low-risk groups. The results of the drug sensitivity analysis showed that the high-risk group was more sensitive to several chemotherapeutic agents such as Sunitinib, Tipifarnib, Nilotinib and Bosutinib than the low-risk group. In conclusion, we successfully constructed HMs-based prognostic signature that can predict the prognosis of KIRC.

Decoding temporal heterogeneity in NSCLC through machine learning and prognostic model construction

BACKGROUND

Non-small cell lung cancer (NSCLC) is a prevalent and heterogeneous disease with significant genomic variations between the early and advanced stages. The identification of key genes and pathways driving NSCLC tumor progression is critical for improving the diagnosis and treatment outcomes of this disease.

METHODS

In this study, we conducted single-cell transcriptome analysis on 93,406 cells from 22 NSCLC patients to characterize malignant NSCLC cancer cells. Utilizing cNMF, we classified these cells into distinct modules, thus identifying the diverse molecular profiles within NSCLC. Through pseudotime analysis, we delineated temporal gene expression changes during NSCLC evolution, thus demonstrating genes associated with disease progression. Using the XGBoost model, we assessed the significance of these genes in the pseudotime trajectory. Our findings were validated by using transcriptome sequencing data from The Cancer Genome Atlas (TCGA), supplemented via LASSO regression to refine the selection of characteristic genes. Subsequently, we established a risk score model based on these genes, thus providing a potential tool for cancer risk assessment and personalized treatment strategies.

RESULTS

We used cNMF to classify malignant NSCLC cells into three functional modules, including the metabolic reprogramming module, cell cycle module, and cell stemness module, which can be used for the functional classification of malignant tumor cells in NSCLC. These findings also indicate that metabolism, the cell cycle, and tumor stemness play important driving roles in the malignant evolution of NSCLC. We integrated cNMF and XGBoost to select marker genes that are indicative of both early and advanced NSCLC stages. The expression of genes such as CHCHD2, GAPDH, and CD24 was strongly correlated with the malignant evolution of NSCLC at the single-cell data level. These genes have been validated via histological data. The risk score model that we established (represented by eight genes) was ultimately validated with GEO data.

CONCLUSION

In summary, our study contributes to the identification of temporal heterogeneous biomarkers in NSCLC, thus offering insights into disease progression mechanisms and potential therapeutic targets. The developed workflow demonstrates promise for future applications in clinical practice.

Progress and application of lung-on-a-chip for lung cancer

Lung cancer is a malignant tumour with the highest incidence and mortality worldwide. Clinically effective therapy strategies are underutilized owing to the lack of efficient models for evaluating drug response. One of the main reasons for failure of anticancer drug therapy is development of drug resistance. Anticancer drugs face severe challenges such as poor biodistribution, restricted solubility, inadequate absorption, and drug accumulation. In recent years, "organ-on-a-chip" platforms, which can directly regulate the microenvironment of biomechanics, biochemistry and pathophysiology, have been developed rapidly and have shown great potential in clinical drug research. Lung-on-a-chip (LOC) is a new 3D model of bionic lungs with physiological functions created by micromachining technology on microfluidic chips. This approach may be able to partially replace animal and 2D cell culture models. To overcome drug resistance, LOC realizes personalized prediction of drug response by simulating the lung-related microenvironment in vitro, significantly enhancing therapeutic effectiveness, bioavailability, and pharmacokinetics while minimizing side effects. In this review, we present an overview of recent advances in the preparation of LOC and contrast it with earlier in vitro models. Finally, we describe recent advances in LOC. The combination of this technology with nanomedicine will provide an accurate and reliable treatment for preclinical evaluation.

Mitochondrial ribosomal protein S24 is associated with immunosuppressive microenvironment and cold tumor in lung adenocarcinoma

Objective

MRPS24 (Mitochondrial Ribosomal Protein S24) belongs to the mitochondrial ribosomal protein family, which participates in the protein synthesis of the mitochondrion. However, the relationship of MRPS24 with lung adenocarcinoma (LUAD) remained unknown. We aimed to identify its immunological and functional mechanisms in LUAD.

Methods

The analysis of MRPS24 expression, clinical features, diagnosis, prognosis, function analysis, genetic alteration, copy number variations, methylation, and tumor microenvironment was investigated by the TCGA, UCSC Xena, GEO, HPA, GEPIA, cBioPortal, MethSurv, TIMER, TIMER2.0, and TISIDB databases.

Results

MRPS24 was found to be more abundant in LUAD tumor tissue than in normal tissue. High levels of MRPS24 expression were found to be an independent prognostic factor by multivariate analysis. Functional analysis revealed that MRPS24 expression was associated with the immune, cell cycle and methylation. MRPS24 methylation level was inversely linked with its expression (p < 0.001). Patients with low MRPS24 methylation had a worse prognosis than those with high methylation (p < 0.05). In addition, the result revealed that the MRPS24 expression was inversely linked to the immune cell infiltration in LUAD. Finally, the validations of the expression level, prognosis, and immune cell infiltration of MRPS24 were in accordance with our previous results.

Conclusions

This study systematically explored that MRPS24 expression was significantly correlated with prognosis, tumorigenesis, genetic alteration, copy number variations, methylation, and immune cell infiltration in LUAD. MRPS24 might be a potential immune-related biomarker in the development and treatment of LUAD, thereby acting as a promising predictor of immunotherapy response in LUAD.

Prognostic and onco-immunological value of immune-related eRNAs-driven genes in lung adenocarcinoma

BACKGROUND

We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.

MATERIALS AND METHODS

Pearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.

RESULTS

Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.

CONCLUSION

Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

Mechanisms of resistance to targeted therapy and immunotherapy in non-small cell lung cancer: promising strategies to overcoming challenges

Resistance to targeted therapy and immunotherapy in non-small cell lung cancer (NSCLC) is a significant challenge in the treatment of this disease. The mechanisms of resistance are multifactorial and include molecular target alterations and activation of alternative pathways, tumor heterogeneity and tumor microenvironment change, immune evasion, and immunosuppression. Promising strategies for overcoming resistance include the development of combination therapies, understanding the resistance mechanisms to better use novel drug targets, the identification of biomarkers, the modulation of the tumor microenvironment and so on. Ongoing research into the mechanisms of resistance and the development of new therapeutic approaches hold great promise for improving outcomes for patients with NSCLC. Here, we summarize diverse mechanisms driving resistance to targeted therapy and immunotherapy in NSCLC and the latest potential and promising strategies to overcome the resistance to help patients who suffer from NSCLC.

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.

StellarPath: Hierarchical-vertical multi-omics classifier synergizes stable markers and interpretable similarity networks for patient profiling

The Patient Similarity Network paradigm implies modeling the similarity between patients based on specific data. The similarity can summarize patients' relationships from high-dimensional data, such as biological omics. The end PSN can undergo un/supervised learning tasks while being strongly interpretable, tailored for precision medicine, and ready to be analyzed with graph-theory methods. However, these benefits are not guaranteed and depend on the granularity of the summarized data, the clarity of the similarity measure, the complexity of the network's topology, and the implemented methods for analysis. To date, no patient classifier fully leverages the paradigm's inherent benefits. PSNs remain complex, unexploited, and meaningless. We present StellarPath, a hierarchical-vertical patient classifier that leverages pathway analysis and patient similarity concepts to find meaningful features for both classes and individuals. StellarPath processes omics data, hierarchically integrates them into pathways, and uses a novel similarity to measure how patients' pathway activity is alike. It selects biologically relevant molecules, pathways, and networks, considering molecule stability and topology. A graph convolutional neural network then predicts unknown patients based on known cases. StellarPath excels in classification performances and computational resources across sixteen datasets. It demonstrates proficiency in inferring the class of new patients described in external independent studies, following its initial training and testing phases on a local dataset. It advances the PSN paradigm and provides new markers, insights, and tools for in-depth patient profiling.

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BACKGROUND

Human discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.

METHODS

Multiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.

RESULTS

High DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.

CONCLUSION

Our research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

Anti-cancer effects of Coix seed extract through KCTD9-mediated ubiquitination of TOP2A in lung adenocarcinoma

BACKGROUND

Coix seed extract (CSE), a traditional Chinese medicine, has been reported as an adjunctive therapy in cancers. However, the molecular targets are largely unclear. The study is designed to unveil its function in lung adenocarcinoma (LUAD) and the possible molecular mechanism.

METHODS

The HERB database was utilized to predict the molecular targets of the Coix seed, followed by prognostic value prediction in the Kaplan-Meier Plotter database. LUAD cells were infected with sh-KCTD9 after co-culture with CSE, and cell viability, growth, proliferation, and apoptosis were determined. The substrates of KCTD9 were predicted using a protein-protein interaction network and verified. The expression of PD-L1, the contents of TNF-α, IFN-γ, CXCL10, and CXCL9 in the co-culture system of LUAD cells and T cells and the proliferation of T cells were evaluated to study the immune escape of LUAD cells in response to CSE and sh-KCTD9. Lastly, tumor growth and immune escape were observed in tumor-bearing mice.

RESULTS

CSE inhibited malignant behavior and immune escape of LUAD cells, and the reduction of KCTD9 reversed the inhibitory effect of CSE on malignant behavior and immune escape of LUAD cells. Knockdown of KCTD9 expression inhibited ubiquitination modification of TOP2A, and knockdown of TOP2A suppressed immune escape of LUAD cells in the presence of knockdown of KCTD9. CSE exerted anticancer effects in mice, but the reduction of KCTD9 partially compromised the anticancer effect of CSE.

CONCLUSION

CSE inhibits immune escape and malignant progression of LUAD through KCTD9-mediated ubiquitination modification of TOP2A.

Integrative bioinformatics analysis reveals ECM and nicotine-related genes in both LUAD and LUSC, but different lung fibrosis-related genes are involved in LUAD and LUSC

There are several bioinformatics studies related to lung cancer, but most of them have mainly focused on either microarray data or RNA-Seq data alone. In this study, we have combined both types of data to identify differentially expressed genes (DEGs) specific to lung cancer subtypes. We obtained six microarray datasets from the GEO and also the expression matrix of LUSC and LUAD from TCGA, which were analyzed by GEO2R tool and GEPIA2, respectively. Enrichment analyses of DEGs were performed using the Enrichr database. Protein module identification was done by MCODE plugin in cytoscape software. We identified 30 LUAD-specific, 17 LUSC-specific, and 17 DEGs shared between LUAD and LUSC. Enrichment analyses revealed that LUSC-specific DEGs are involved in lung fibrosis. In addition, DEGs shared between LUAD and LUSC are involved in extracellular matrix (ECM), nicotine metabolism, and lung fibrosis. We identified lung fibrosis-related genes, including SPP1, MMP9, and CXCL2, involved in both LUAD and LUSC, but SERPINA1 and PLAU genes involved only in LUSC. We also found an important module separately for LUAD-specific, LUSC-specific, and shared DEGs between LUSC and LUAD. S100P, GOLM, AGR2, AK1, TMEM125, SLC2A1, COL1A1, and GHR genes were significantly associated with survival. Our findings suggest that different lung fibrosis-related genes may play roles in LUSC and LUAD. Additionally, nicotine metabolism and ECM remodeling were found to be associated with both LUSC and LUAD, regardless of subtype, emphasizing the role of smoking in the development of lung cancer and ECM in the high aggressiveness and mortality of lung cancer.

Upregulation of M6A Reader HNRNPA2B1 Associated with Poor Prognosis and Tumor Progression in Lung Adenocarcinoma

BACKGROUND

Lung cancer is the most prevalent malignancy worldwide, and lung adenocarcinoma (LUAD) accounts for a substantial proportion of all cases. N6-methyladenosine (m6A) is the most frequent post-transcriptional modification in mRNAs that also plays a role in cancer development. Heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1) is a reader of m6A modification, which can affect tumor invasion, migration, and proliferation.

OBJECTIVES

The purpose of this study was to explore the prognostic factors of LUAD based on m6A through bioinformatics analysis.

MATERIALS AND METHODS

The expression levels and prognostic significance of HNRNPA2B1 in LUAD were analyzed on the basis of data extracted from the UALCAN, GEPIA, NCBI-GEO, Human Protein Atlas, STRING, miRDB, TargetScan, PROMO, Starbase, UCSC Xena browser, TIMER, and TISIDB databases. HNRNPA2B1 protein and mRNA levels in several LUAD cell lines were detected by western blotting and qRT-PCR. CCK8, wound-healing and transwell assays were performed to evaluate the proliferation, invasion, and migration abilities of LUAD cells.

RESULTS

HNRNPA2B1 mRNA was found to be significantly overexpressed in LUAD tissues, and its high levels correlated with poor OS and DFS. The genes co-expressed with HNRNPA2B1 were related to mRNA production, cell cycle, and histone binding. To determine the mechanistic basis of HNRNPA2B1 in LUAD, we next predicted the microRNAs and transcription factors that were directly associated with HNRNPA2B1, as well as copy number changes. In addition, it was found that HNRNPA2B1 expression was significantly related to CD4+ T cells, neutrophils, lymphocytes, immunomodulators, and chemokines. Besides, knocking down HNRNPA2B1 in the LUAD cells led to a significant reduction in their proliferation, invasion, and migration rates in vitro.

CONCLUSION

Elevated HNRNPA2B1 is a risk factor in LUAD and portends a poor prognosis.

Immunogenicity of cancer cells: An overview

The immune system assumes a pivotal role in the organism's capacity to discern and obliterate malignant cells. The immunogenicity of a cancer cell pertains to its proficiency in inciting an immunological response. The prowess of immunogenicity stands as a pivotal determinant in the triumph of formulating immunotherapeutic methodologies. Immunotherapeutic strategies include immune checkpoint inhibitors, chimeric antigen receptor (CAR) T-cell therapy, and on vaccines. Immunogenic cell death (ICD) epitomizes a form of cellular demise that incites an immune response against dying cells. ICD is characterized by the liberation of distinct specific molecules that activate the immune system, thereby leading to the identification and elimination of dying cells by immunocytes. One of the salient characteristics inherent to the ICD phenomenon resides in the vigorous liberation of adenosine triphosphate (ATP) by cellular entities dedicated to embarking upon the process of programmed cell death, yet refraining from complete apoptotic demise. ICD is initiated by a sequence of molecular events that occur during cell death. These occurrences encompass the unveiling or discharge of molecules such as calreticulin, high-mobility group box 1 (HMGB1), and adenosine triphosphate (ATP) from dying cells. These molecules act as "eat me" signals, which are recognized by immune cells, thereby prompting the engulfment and deterioration of expiring cells by phagocytes including various pathways such as Necroptosis, Apoptosis, and pyroptosis. Here, we review our current understanding of the pathophysiological importance of the immune responses against dying cells and the mechanisms underlying their activation. Overall, the ICD represents an important mechanism by which the immune system recognizes and eliminates dying cells, including cancer cells. Understanding the molecular events that underlie ICD bears the potential to engender innovative cancer therapeutics that harness the power of the immune system to combat cancer.

HER2 Alterations in Non-Small Cell Lung Cancer: Biologico-Clinical Consequences and Interest in Therapeutic Strategies

Lung cancer stands as the first cause of death by cancer in the world. Despite the improvement in patients' outcomes in the past decades through the development of personalized medicine approaches, a substantial portion of patients remains ineligible for targeted therapies due to the lack of a "druggable" molecular target. HER2, a receptor tyrosine kinase member of the EGFR/ErbB family, is known to show oncogenic properties. In this review, we focus on the different HER2 dysregulation mechanisms that have been observed in non-small cell lung cancer (NSCLC): gene mutation, gene amplification, protein overexpression and protein hyper-phosphorylation, the latter suggesting that HER2 dysregulation can occur independently of any molecular aberration. These HER2 alterations inevitably have consequences on tumor biology. Here, we discuss how they are not only involved in abnormal proliferation and survival of cancer cells but also potentially in increased angiogenic properties, mesenchymal features and tumor immune escape. Finally, we review the impact of these HER2 alterations in various therapeutic approaches. While standard chemotherapy and groundbreaking immunotherapy seem rather ineffective for HER2-altered NSCLCs, the development of HER2-targeted therapies such as tyrosine kinase inhibitors, anti-HER2 antibodies and especially antibody-drug conjugates could provide new hopes for patients.

Replication-incompetent influenza A viruses armed with IFN-γ effectively mediate immune modulation and tumor destruction in mice harboring lung cancer

Low pathogenic influenza A viruses (IAVs) have shown promising oncolytic potential in lung cancer-bearing mice. However, as replication-competent pathogens, they may cause side effects in immunocompromised cancer patients. To circumvent this problem, we genetically engineered nonreplicating IAVs lacking the hemagglutinin (HA) gene (ΔHA IAVs), but reconstituted the viral envelope with recombinant HA proteins to allow a single infection cycle. To optimize the therapeutic potential and improve immunomodulatory properties, these replication-incompetent IAVs were complemented with a murine interferon-gamma (mIFN-γ) gene. After intratracheal administration to transgenic mice that develop non-small cell lung cancer (NSCLC), the ΔHA IAVs induced potent tumor destruction. However, ΔHA IAVs armed with mIFN-γ exhibited an even stronger and more sustained effect, achieving 85% tumor reduction at day 12 postinfection. In addition, ΔHA-mIFN-γ viruses were proven to be efficient in recruiting and activating natural killer cells and macrophages from the periphery and in inducing cytotoxic T lymphocytes. Most important, both viruses, and particularly IFN-γ-encoding viruses, activated tumor-associated alveolar macrophages toward a proinflammatory M1-like phenotype. Therefore, replication-incompetent ΔHA-mIFN-γ-IAVs are safe and efficient oncolytic viruses that additionally exhibit immune cell activating properties and thus represent a promising innovative therapeutic option in the fight against NSCLC.

CD4 levels and NSCLC metastasis: the benefits of maintaining moderate levels

OBJECTIVES

Prior researches indicate that peripheral blood CD4 levels have an inverse correlation with distant tumor metastasis in non-small cell lung cancer (NSCLC). However, the linear relationship between CD4 and distant metastasis lacks clarity. Hence, the objective of this study was to ascertain the linear relationship between CD4 and distant metastasis in NSCLC patients.

METHODS

This retrospective study analyzed clinical and laboratory data of NSCLC patients between March 2016 and July 2022 at the Cancer Hospital of Anhui University of Technology. The study first applied a generalized summation model and smoothing curve fitting to determine if there was a linear relationship between CD4 and NSCLC metastasis. Secondarily, univariate logistic analysis and multiple linear regression were used to analyze the odds ratio (OR) of CD4 as a continuous variable, dichotomous variable, and trichotomous variable when predicting NSCLC metastasis. In addition, stratified and subgroup analyses were conducted to assess the reliability of CD4 in different NSCLC patient populations.

RESULTS

The study included a total of 213 NSCLC patients, among which 122 had distant metastasis and 91 had no metastasis. The smoothing curve fitting analysis revealed a U-shaped relationship between CD4 and NSCLC metastasis with a threshold effect. The univariate logistic analysis indicated that continuous CD4 expression was not significantly associated with NSCLC metastasis (P = 0.051); however, high levels of CD4 expression (≥ 35.06%) were found to be a protective factor against NSCLC metastasis when CD4+ T was a dichotomous variable (OR = 0.49, P = 0.010). Furthermore, multivariate linear regression models showed that low (< 32%) or high levels (> 44%) of CD4 significantly increased the risk of NSCLC metastasis compared to medium levels (32-44%) when CD4+ T was trichotomized. The significance was maintained in stratified analysis in relation to age, sex, type of pathology, smoke, PS, and T stage. CD4 levels were U-shaped in relation to different sites of distant metastases (bone, brain, liver), but not with lung metastases.

CONCLUSIONS

A threshold effect is shown to exist between the peripheral blood CD4 and distant metastasis in NSCLC patients. It was revealed that the risk of distant metastasis is lower when CD4 is maintained between 32 and 44%, whereas low (< 32%) or high (> 44) levels of CD4 are associated with an increased risk of distant metastasis in NSCLC patients.

Single-cell profiling reveals the heterogeneity of NK cells during anti-PD-1 therapy in non-small-cell lung cancer

BACKGROUND

The efficacy of immune checkpoint inhibitors remains limited in non-small cell lung cancer (NSCLC). Natural killer (NK) cells serve as the key element of innate immunity and play an important role in anti-tumor immunity, the impact of NK cells on efficacy of anti-PD-1 therapy in NSCLC is worth exploring.

METHODS

We analyzed single-cell transcriptome data derived from biopsies of NSCLC patients receiving anti-PD-1 treatment. Immune cell subtypes were identified and further cell-cell communication were analyzed and verified.

RESULTS

We observed totally 6 distinct NK cells clusters in NSCLC infiltrating immune cells. It's worth noting that enrichment of immature NK cells was found in responsive group. A series of marker genes of immature NK cells were associated with anti-PD-1 response and related to immune regulation processes such as antigen processing, Th1, Th17 cells activation. Moreover, effector CD8+ T cells were significantly enriched in responsive group and showed similar trajectories with immature NK cells. Cell-cell communication analysis showed that immature NK cells showed strong interactions with Th17 cells and effector CD8+ T cells. Furthermore, when validating the expression of immature NK cells marker genes, we found that CXCR4 was associated with enriched infiltration of CD8+ T cells.

CONCLUSIONS

In conclusion, immature NK cells may facilitate the efficacy of anti-PD-1 therapy by interacting with Th1 cells, Th17 cells and enhancing infiltration of effector CD8+ T cells. Our data suggested that NK cells could be a promising target to improve the prognosis of NSCLC patients.

Homologous recombination repair gene-based risk model predicts prognosis and immune microenvironment for primary lung cancer after previous malignancies

BACKGROUND

Homologous recombination repair (HRR) plays an important role in cancer development, drug resistance, and immune escape, but the role of HRR genes in primary lung cancer (PLC) after previous malignancies is unclear.

METHODS

We used HRR-related score constrcted by HRR genes to classify patients into two groups and compared clinical progression, differential genes, and their functions between them. Then, we constructed a prognostic risk model based on HRR-related score and screened key differentially expressed genes. We evaluated the potential roles, mutational information, and immune correlations of key genes. Finally, we compared the long-term prognosis and immune correlations of different prognostic risk subgroups.

RESULTS

We found that HRR-related score was associated with T-stage, immunotherapy sensitivity, and prognosis of PLC after previous malignancies. Differential genes between HRR-related low-score and high-score groups are mainly involved in DNA replication and repair processes, such as the cell cycle. We identified three key genes, ABO, SERPINE2, and MYC, by machine learning, and MYC had the highest amplification mutation frequency. We verified that the key gene-based prognostic model can better assess the prognosis of patients. The risk score of the prognostic model was associated with immune microenvironment and efficacy of immunotherapy.

CONCLUSIONS

Overall, we identified three key genes ABO, SERPINE2, and MYC associated with HRR status in PLC after previous malignancies. The risk model based on key genes is associated with immune microenvironment and can well predict the prognosis for PLC after previous malignancies.

CD47: The Next Frontier in Immune Checkpoint Blockade for Non-Small Cell Lung Cancer

The success of PD-1/PD-L1-targeted therapy in lung cancer has resulted in great enthusiasm for additional immunotherapies in development to elicit similar survival benefits, particularly in patients who do not respond to or are ineligible for PD-1 blockade. CD47 is an immunosuppressive molecule that binds SIRPα on antigen-presenting cells to regulate an innate immune checkpoint that blocks phagocytosis and subsequent activation of adaptive tumor immunity. In lung cancer, CD47 expression is associated with poor survival and tumors with EGFR mutations, which do not typically respond to PD-1 blockade. Given its prognostic relevance, its role in facilitating immune escape, and the number of agents currently in clinical development, CD47 blockade represents a promising next-generation immunotherapy for lung cancer. In this review, we briefly summarize how tumors disrupt the cancer immunity cycle to facilitate immune evasion and their exploitation of immune checkpoints like the CD47-SIRPα axis. We also discuss approved immune checkpoint inhibitors and strategies for targeting CD47 that are currently being investigated. Finally, we review the literature supporting CD47 as a promising immunotherapeutic target in lung cancer and offer our perspective on key obstacles that must be overcome to establish CD47 blockade as the next standard of care for lung cancer therapy.

Immunotherapy and biomarkers in patients with lung cancer with tuberculosis: Recent advances and future Directions

Lung cancer (LC) and tuberculosis (TB) are two major global public health problems, and the incidence of LC-TB is currently on the rise. Therefore effective clinical interventions are crucial for LC-TB. The aim of this review is to provide up-to-date information on the immunological profile and therapeutic biomarkers in patients with LC-TB. We discuss the immune mechanisms involved, including the immune checkpoints that play an important role in the treatment of patients with LC-TB. In addition, we explore the susceptibility of patients with LC to TB and summarise the latest research on LC-TB. Finally, we discuss future prospects in this field, including the identification of potential targets for immune intervention. In conclusion, this review provides important insights into the complex relationship between LC and TB and highlights new advances in the detection and treatment of both diseases.

MiR-101-3p targets KPNA2 to inhibit the progression of lung squamous cell carcinoma cell lines

We herein discuss the impacts of miR-101-3p on the tumorigenesis-related cell behaviors in lung squamous cell carcinoma (LUSC) by repressing KPNA2. TCGA database was utilized to measure miR-101-3p and KPNA2 levels in LUSC tissues and cells. The interaction of miR-101-3p and KPNA2-3'UTR was determined by dual luciferase assay. Western blot evaluated the protein level of KPNA2. MiR-101-3p was under-expressed in LUSC cells while KPNA2 was overexpressed. Western blot confirmed the impact of KPNA2 expression on cancer cell progression. The negative regulatory impact of miR-101-3p on KPNA2 was also verified. In vitro cell function assays revealed the suppressing effect of high miR-101-3p expression on cell invasion, migration and viability, as well as its promoting effect on apoptosis. Up-regulated miR-101-3p weakened the promoting effect of overexpressed KPNA2 on LUSC malignant progression. To conclude, miR-101-3p repressed viability, invasion, and migration, and facilitated cell apoptosis in LUSC by suppressing KPNA2.

Polo-like Kinase 4: A Multifaceted Marker Linking Tumor Aggressiveness and Unfavorable Prognosis, and Insights into Therapeutic Strategies

(1) Background: This study investigated whether polo-like kinase 4 (PLK4) is a suitable therapeutic target or biomarker for lung adenocarcinoma (LUAD). (2) Methods: We acquired LUAD data from The Cancer Genome Atlas (TCGA) database through the UCSC Xena data portal. Gene expression, clinical, survival, and mutation data from multiple samples were analyzed. Gene enrichment analysis, unsupervised clustering of PLK4-related pathways, and differential gene expression analyses were performed. Additionally, correlations, t-tests, survival analyses, and statistical analyses were performed. (3) Results: PLK4 expression was higher in LUAD tissues than in normal tissues and was associated with poor prognosis for both overall and progression-free survival in LUAD. PLK4 was highly correlated with cell-proliferation-related pathways using Gene Ontology (GO) biological process terms. PLK4 expression and pathways that were highly correlated with PLK4 expression levels were upregulated in patients with LUAD with the TP53 mutation. (4) Conclusions: PLK4 expression affects the survival of patients with LUAD and is a potential therapeutic target for LUAD with TP53 mutations.

Predicting lung adenocarcinoma prognosis, immune escape, and pharmacomic profile from arginine and proline-related genes

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease that ranks first in morbidity and mortality. Abnormal arginine metabolism is associated with inflammatory lung disease and may influence alterations in the tumor immune microenvironment. However, the potential role of arginine and proline metabolic patterns and immune molecular markers in LUAD is unclear. Gene expression, somatic mutations, and clinicopathological information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was performed to identify metabolic genes associated with overall survival (OS). Unsupervised clustering divided the sample into two subtypes with different metabolic and immunological profiles. Gene set enrichment analysis (GESA) and gene set variation analysis (GSVA) were used to analyze the underlying biological processes of the two subtypes. Drug sensitivity between subtypes was also predicted; then prognostic features were developed by multivariate Cox regression analysis. In addition, validation was obtained in the GSE68465, and GSE50081 dataset. Then, gene expression, and clinical characterization of hub genes CPS1 and SMS were performed; finally, in vitro validation experiments for knockdown of SMS were performed in LUAD cell lines. In this study, we first identified 12 arginine and proline-related genes (APRGs) significantly associated with OS and characterized the clinicopathological features and tumor microenvironmental landscape of two different subtypes. Then, we established an arginine and proline metabolism-related scoring system and identified two hub genes highly associated with prognosis, namely CPS1, and SMS. In addition, we performed CCK8, transwell, and other functional experiments on SMS to obtain consistent results. Our comprehensive analysis revealed the potential molecular features and clinical applications of APRGs in LUAD. A model based on 2 APRGs can accurately predict survival outcomes in LUAD, improve our understanding of APRGs in LUAD, and pave a new pathway to guide risk stratification and treatment strategy development for LUAD patients.

Comprehensive analysis of circulating cell-free RNAs in blood for diagnosing non-small cell lung cancer

Early screening and detection of non-small cell lung cancer (NSCLC) is crucial due to the significantly low survival rate in advanced stages. Blood-based liquid biopsy is non-invasive test to assistant disease diagnosis, while cell-free RNA is one of the promising biomarkers in blood. However, the disease related signatures have not been explored completely for most cell-free RNA transcriptome sequencing (cfRNA-Seq) datasets. To address this gap, we developed a comprehensive cfRNA-Seq pipeline for data analysis and constructed a machine learning model to facilitate noninvasive early diagnosis of NSCLC. The results of our study have demonstrated the identification of differential mRNA, lncRNAs and miRNAs from cfRNA-Seq, which have exhibited significant association with development and progression of lung cancer. The classifier based on gene expression signatures achieved an impressive area under the curve (AUC) of up to 0.9, indicating high specificity and sensitivity in both cross-validation and independent test. Furthermore, the analysis of T cell and B cell immune repertoire extracted from cfRNA-Seq have provided insights into the immune status of cancer patients, while the microbiome analysis has revealed distinct bacterial and viral profiles between NSCLC and normal samples. In our future work, we aim to validate the existence of cancer associated T cell receptors (TCR)/B cell receptors (BCR) and microorganisms, and subsequently integrate all identified signatures into diagnostic model to improve the prediction accuracy. This study not only provided a comprehensive analysis pipeline for cfRNA-Seq dataset but also highlights the potential of cfRNAs as promising biomarkers and models for early NSCLC diagnosis, emphasizing their importance in clinical settings.

Identification of age- and immune-related gene signatures for clinical outcome prediction in lung adenocarcinoma

BACKGROUND

The understanding of the factors causing decreased overall survival (OS) in older patients compared to younger patients in lung adenocarcinoma (LUAD) remains.

METHODS

Gene expression profiles of LUAD were obtained from publicly available databases by Kaplan-Meier analysis was performed to determine whether age was associated with patient OS. The immune cell composition in the tumor microenvironment (TME) was evaluated using CIBERSORT. The fraction of stromal and immune cells in tumor samples were also using assessed using multiple tools including ESTIMATE, EPIC, and TIMER. Differentially expressed genes (DEGs) from the RNA-Seq data that were associated with age and immune cell composition were identified using the R package DEGseq. A 22-gene signature composed of DEGs associated with age and immune cell composition that predicted OS were constructed using Least Absolute Shrinkage and Selection Operator (LASSO).

RESULTS

In The Cancer Genome Atlas (TCGA)-LUAD dataset, we found that younger patients (≤70) had a significant better OS compared to older patients (>70). In addition, older patients had significantly higher expression of immune checkpoint proteins including inhibitory T cell receptors and their ligands. Moreover, analyses using multiple bioinformatics tools showed increased immune infiltration, including CD4+ T cells, in older patients compared to younger patients. We identified a panel of genes differentially expressed between patients >70 years compared to those ≤70 years, as well as between patients with high or low immune scores and selected 84 common genes to construct a prognostic gene signature. A risk score calculated based on 22 genes selected by LASSO predicted 1, 3, and 5-year OS, with an area under the curve (AUC) of 0.72, 0.72, 0.69, receptively, in TCGA-LUAD dataset and an independent validation dataset available from the European Genome-phenome Archive (EGA).

CONCLUSION

Our results demonstrate that age contributes to OS of LUAD patients atleast in part through its association with immune infiltration in the TME.

Immune microenvironment analysis and novel biomarkers of early-stage lung adenocarcinoma evolution

Background

Lung cancer is the deadliest and most diagnosed type of cancer worldwide. The 5-year survival rate of lung adenocarcinoma (LUAD) dropped significantly when tumor stages advanced. Patients who received surgically resecting at the pre-invasive stage had a 5-year survival rate of nearly 100%. However, the study on the differences in gene expression profiles and immune microenvironment among pre-invasive LUAD patients is still lacking.

Methods

In this study, the gene expression profiles of three pre-invasive LUAD stages were compared using the RNA-sequencing data of 10 adenocarcinoma in situ (AIS) samples, 12 minimally invasive adenocarcinoma (MIA) samples, and 10 invasive adenocarcinoma (IAC) samples.

Results

The high expression levels of PTGFRN (Hazard Ratio [HR] = 1.45; 95% Confidence Interval [CI]: 1.08-1.94; log-rank P = 0.013) and SPP1 (HR = 1.44; 95% CI: 1.07-1.93; log-rank P = 0.015) were identified to be associated with LUAD prognosis. Moreover, the early LUAD invasion was accompanied by the enhancement of antigen presentation ability, reflected by the increase of myeloid dendritic cells infiltration rate (Cuzick test P < 0.01) and the upregulation of seven important genes participating in the antigen presentation, including HLA-A (Cuzick test P = 0.03), MICA (Cuzick test P = 0.01), MICB (Cuzick test P = 0.01), HLA-DPA1 (Cuzick test P = 0.04), HLA-DQA2 (Cuzick test P < 0.01), HLA-DQB1 (Cuzick test P = 0.03), and HLA-DQB2 (Cuzick test P < 0.01). However, the tumor-killing ability of the immune system was inhibited during this process, as there were no rising cytotoxic T cell activity (Cuzick test P = 0.20) and no increasing expression in genes encoding cytotoxic proteins.

Conclusion

In all, our research elucidated the changes in the immune microenvironment during early-stage LUAD evolution and may provide a theoretical basis for developing novel early-stage lung cancer therapeutic targets.

Cancer Cell-Intrinsic Alterations Associated with an Immunosuppressive Tumor Microenvironment and Resistance to Immunotherapy in Lung Cancer

Despite the great clinical success of immunotherapy in lung cancer patients, only a small percentage of them (<40%) will benefit from this therapy alone or combined with other strategies. Cancer cell-intrinsic and cell-extrinsic mechanisms have been associated with a lack of response to immunotherapy. The present study is focused on cancer cell-intrinsic genetic, epigenetic, transcriptomic and metabolic alterations that reshape the tumor microenvironment (TME) and determine response or refractoriness to immune checkpoint inhibitors (ICIs). Mutations in KRAS, SKT11(LKB1), KEAP1 and TP53 and co-mutations of these genes are the main determinants of ICI response in non-small-cell lung cancer (NSCLC) patients. Recent insights into metabolic changes in cancer cells that impose restrictions on cytotoxic T cells and the efficacy of ICIs indicate that targeting such metabolic restrictions may favor therapeutic responses. Other emerging pathways for therapeutic interventions include epigenetic modulators and DNA damage repair (DDR) pathways, especially in small-cell lung cancer (SCLC). Therefore, the many potential pathways for enhancing the effect of ICIs suggest that, in a few years, we will have much more personalized medicine for lung cancer patients treated with immunotherapy. Such strategies could include vaccines and chimeric antigen receptor (CAR) cells.

A prognostic and immunotherapeutic predictive model based on the cell-originated characterization of tumor microenvironment in lung adenocarcinoma

Tumor microenvironment (TME) plays a crucial role in predicting prognosis and response to therapy in lung cancer. Our study established a prognostic and immunotherapeutic predictive model, the tumor immune cell score (TICS), by differentiating cell origins in lung adenocarcinoma (LUAD) based on the transcriptomic data of 2,510 patients in 14 independent cohorts, including 12 public datasets and two in-house cohorts. The high TICS was associated with prolonged overall survival (OS), especially in the early-stage LUAD. For the advanced-stage LUAD, high TICS predicted a superior OS in patients who were treated with immunotherapy instead of chemotherapy or TKI. The result suggested that TICS could serve as an indicator for the prognostic stratification management of patients in the early-stage LUAD, and as a potential guide for therapeutic decision-marking in the advanced-stage LUAD. Our findings provided an insight into prognosis stratification and potential guidance for treatment strategy selection.

Targeting programmed cell death protein 1 (PD-1) for treatment of non-small-cell lung carcinoma (NSCLC); the recent advances

The immune system uses various immune checkpoint axes to adjust responses, support homeostasis, and deter self-reactivity and autoimmunity. Nevertheless, non-small-cell lung carcinoma (NSCLC) can use protective mechanisms to facilitate immune evasion, which leads to potentiated cancer survival and proliferation. In this light, many blocking anti-bodies have been developed to negatively regulate checkpoint molecules, in particular, programmed cell death protein 1 (PD-1) / PD-ligand 1 (L1), and bypass these immune suppressive mechanisms. Meanwhile, anti-PD-1 anti-bodies such as nivolumab, pembrolizumab, cemiplimab, and sintilimab have shown excellent competence in successfully inspiring immune responses versus NSCLC. Accordingly, the United States Food and Drug Administration (FDA) has recently approved nivolumab (alone or in combination with ipilimumab) and pembrolizumab (alone or in combination with chemotherapy) as first-line treatment for advanced NSCLC patients. However, PD-1 blockade monotherapy remains inefficient in more than 60% of NSCLC patients, and many patients don't respond or acquire resistance to this modality. Also, toxicities related to anti-PD-1 anti-body have been progressively identified in clinical trials and oncology practice. Herein, we will outline the clinical benefits of PD-1 blockade therapy alone or in combination with other treatments (e.g., chemotherapy, radiotherapy, anti-angiogenic therapy) in NSCLC patients. Moreover, we will take a glimpse into the recently identified predictive biomarkers to determine patients most likely to suffer serious adverse events to decrease untoward toxicity risk and diminish treatment costs.

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

OBJECTIVES

This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy.

METHODS

LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activities and pathways in different risk populations, we calculated immune checkpoints, immune escape, immune phenomena (IPS), and tumor mutation burden (TMB) based on TCGA datasets. Finally, the relationship between the model and drug sensitivity was analyzed.

RESULTS

Fifteen (15) key differentially expressed genes (DEGs) with prognostic value were screened and a new prognostic model was constructed. Four hundred and forty-three (443) samples were grouped into two different risk cohorts based on median model risk values. It was observed that survival rates in high-risk groups were significantly low. ROC curves were used to evaluate the model's accuracy in determining the survival time and clinical outcome of LUAD patients. Cox analysis of various clinical factors proved that the risk score has great potential as an independent prognostic factor. The results of immunological analysis can reveal the immune infiltration and the activity of related functions in different pathways in the two risk groups, and immunotherapy was more effective in low-risk patients. Most chemotherapeutic agents are more sensitive to low-risk patients, making them more likely to benefit.

CONCLUSION

A novel prognostic model for LUAD patients was established based on IGRG, which could more accurately predict the prognosis and an effective immunotherapy approach for patients.

Mesenchymal stem cells can prevent or promote the progression of colon cancer based on their timing of administration

BACKGROUND

Mesenchymal stem cell (MSC) therapy has been shown to have some therapeutic effects in rodent models and patients with IBD; however, its role in colon tumor models is controversial. In this study, the potential role and mechanisms of bone marrow-derived MSCs (BM-MSCs) in colitis-associated colon cancer (CAC) were investigated.

METHODS

The CAC mouse model was established with azoxymethane (AOM) and dextran sulfate sodium (DSS). The mice were administered an intraperitoneal injection of MSCs once weekly for different periods. The progression of CAC and the cytokine expression in tissues was assessed. Immunofluorescence staining was used to detect MSCs localization. Levels of immune cells in the spleen and lamina propria of the colon were detected using flow cytometry. A co-culture of MSCs and naïve T cells was performed to determine the effect of MSCs on naïve T cell differentiation.

RESULTS

Early administration of MSCs inhibited the occurrence of CAC, while late administration promoted the progression of CAC. The inhibitory effect of early injection in mice was characterized by the expression of inflammatory cytokines in colon tissue was decreased, and induction of T regulatory cells (Tregs) infiltration via TGF-β. The promotive effect of late injection was characterized by a shift of T helper (Th) 1/Th2 immune balance toward a Th2 phenotype through IL-4 secretion. IL-12 can reverse this shift to Th2 accumulation in mice.

CONCLUSION

MSCs can curb the progression of colon cancer by inducing Treg accumulation via TGF-β at the early stage of inflammatory transformation but promote the progression of colon cancer by inducing a shift in Th1/Th2 immune balance to Th2 through IL-4 secretion at the late stage. And the immune balance of Th1/Th2 influenced by MSCs could be reversed by IL-12.

Nucleoporin 107 is a prognostic biomarker in hepatocellular carcinoma associated with immune infiltration

OBJECTIVE

To assess the diagnostic value and clinical significance of nucleoporin 107 (NUP107) in hepatocellular carcinoma (HCC), and explore the possible mechanisms.

METHODS

The transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and GEO databases. Tissue specimens were collected from HCC patients in the Guangxi area. According to the expression levels and prognostic characteristics of NUP107, ROC curves and nomogram models were constructed using the R package.

RESULTS

NUP107 was highly expressed in 26 human cancers including HCC, and was associated with advanced HCC staging and worse prognosis. NUP107 showed satisfactory ability to predict the prognosis of HCC patients (AUC >0.8). Results of gene set enrichment analysis (GSEA) further showed that NUP107 was mainly associated with cell cycle-related pathways such as the cell cycle, DNA replication, G2M checkpoint, E2F target, and mitotic spindle. In addition, NUP107 was also associated with immune infiltration in HCC and showed significant positive correlation with immune checkpoints (PD-L1 and TIM-3).

Rhodiola rosea polysaccharides-based nanoparticles loaded with DOX boosts chemo-immunotherapy for triple-negative breast cancer by re-educating tumor-associated macrophages

Efficient encapsulation and tumor targeting ability are the key issues for hydrophobic drugs delivery vectors in cancer therapy. In the current study, Rhodiola rosea polysaccharides (RHPs) serve as an immunoactive vector for drug delivery with tumor-associated macrophages (TAMs) modulating ability and typical structural characteristics. Firstly, Folic acid (FA) and stearic acid (SA) were chemically modified to the backbone of RHPs to obtain the self-assemble and tumor targeting behaviors. Then, the hydrophobic drug (Doxorubicin, DOX) was encapsulated in the RHPs derivatives (FA-RHPs-SA) with high efficiency. Moreover, the optimal formed DOX@FA-RHPs-SA were around 196 nm with uniform size distribution and a pH-sensitive release capacity in different acidic conditions. In vitro experiments demonstrated that DOX@FA-RHPs-SA could efficiently uptake by tumor cells. Furthermore, the modulatory function of the FA-RHPs-SA on RAW264.7 macrophages was also demonstrated in the transition from M0 to M1 phenotypes, and the M2 differentiated into the M1. Finally, in vivo antitumor study revealed that the inhibitory effect of DOX@FA-RHPs-SA was superior to the DOX monotherapy treatment, and the new preparation worked synergistically by inducing tumor cell apoptosis and modulating immune cell function. In summary, this study describes a RHPs-based hydrophobic delivery vector and achieved an additional helpful antitumor effect by modulating TAMs.

Argon gas plasma-treated physiological solutions stimulate immunogenic cell death and eradicates immunosuppressive CD47 protein in lung carcinoma

Cold atmospheric plasma-treated liquids (PTLs) exhibit selective toxicity toward tumor cells and are provoked by a cocktail of reactive oxygen and nitrogen species in such liquids. Compared to the gaseous phase, these reactive species are more persistent in the aqueous phase. This indirect plasma treatment method has gradually gathered interest in the discipline of plasma medicine to treat cancer. PTL's motivated effect on immunosuppressive proteins and immunogenic cell death (ICD) in solid cancer cells is still not explored. In this study, we aimed to induce immunomodulation by plasma-treated Ringer's lactate (PT-RL) and phosphate-buffered saline (PT-PBS) solutions for cancer treatment. PTLs induced minimum cytotoxicity in normal lung cells and inhibited cancer cell growth. ICD is confirmed by the enhanced expression of damage-associated molecular patterns (DAMPs). We evidenced that PTLs induce intracellular nitrogen oxide species accumulation and elevate immunogenicity in cancer cells owing to the production of pro-inflammatory cytokines, DAMPs, and reduced immunosuppressive protein CD47 expression. In addition, PTLs influenced A549 cells to elevate the organelles (mitochondria and lysosomes) in macrophages. Taken together, we have developed a therapeutic approach to potentially facilitate the selection of a suitable candidate for direct clinical applications.

Costimulatory molecule-related lncRNA model as a potential prognostic biomarker in non-small cell lung cancer

OBJECTIVE

Costimulatory molecules have been demonstrated to exert essential roles in multiple cancers. However, their role in lung cancer remains elusive. Here, we sought to identify costimulatory molecule-related lncRNAs in non-small cell lung cancer (NSCLC) and establish a prognostic signature to predict the prognosis of patients with NSCLC.

METHODS

A total of 535 lung adenocarcinoma (LUAD) and 502 lung squamous cell carcinoma (LUSC) patients from the cancer genome atlas (TCGA) database were recruited. A novel costimulatory molecule-based lncRNA prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival. The Homo_sapiens.GRCh38 data set was set as a reference file for probe annotation.

RESULTS

A total of 593 costimulatory molecule-related lncRNAs were extracted. After analysis, six costimulatory molecule-related lncRNAs (AC084859.1, AC079949.2, HSPC324, LINC01150, LINC01150, and AC090617.5) were screened. A prognostic model based on the six lncRNAs was established using systematic bioinformatics analyses. The prognostic model had a prognostic value in NSCLC patients. Furthermore, a prognostic nomogram was established based on clinical parameters and a risk-score model. Patients with different risk scores had considerably different tumor-infiltrating immune cells, somatic mutational loading, clinical outcomes, signaling pathways, and immunotherapy efficacy. In addition, LINC01137 was associated with unfavorable disease outcomes and fueled tumor progression in NSCLC.

CONCLUSION

Taken together, our study demonstrated that a costimulatory molecule-related lncRNA model could be a potential prognostic biomarker in NSCLC. Moreover, LINC01137 could facilitate the proliferation and invasion of lung cancer.

The emerging role of PPAR-alpha in breast cancer

Breast cancer has been confirmed to have lipid disorders in the tumour microenvironment. Peroxisome proliferator-activated receptor alpha (PPARα) is a ligand-activated transcriptional factor that belongs to the family of nuclear receptors. PPARα regulates the expression of genes involved in fatty acid homeostasis and is a major regulator of lipid metabolism. Because of its effects on lipid metabolism, an increasing number of studies have investigated the relationship of PPARα with breast cancer. PPARα has been shown to impact the cell cycle and apoptosis in normal cells and tumoral cells through regulating genes of the lipogenic pathway, fatty acid oxidation, fatty acid activation, and uptake of exogenous fatty acids. Besides, PPARα is involved in the regulation of the tumour microenvironment (anti-inflammation and inhibition of angiogenesis) by modulating different signal pathways such as NF-κB and PI3K/AKT/mTOR. Some synthetic PPARα ligands are used in adjuvant therapy for breast cancer. PPARα agonists are reported to reduce the side effects of chemotherapy and endocrine therapy. In addition, PPARα agonists enhance the curative effects of targeted therapy and radiation therapy. Interestingly, with the emerging role of immunotherapy, attention has been focused on the tumour microenvironment. The dual functions of PPARα agonists in immunotherapy need further research. This review aims to consolidate the operations of PPARα in lipid-related and other ways, as well as discuss the current and potential applications of PPARα agonists in tackling breast cancer.

Identification and vitro verification of the potential drug targets of active ingredients of Chonglou in the treatment of lung adenocarcinoma based on EMT-related genes

Lung adenocarcinoma (LUAD) is the main histological type of lung cancer with an unfavorable survival rate. Metastasis is the leading LUAD-related death with Epithelial-Mesenchymal Transition (EMT) playing an essential role. The anticancer efficacies of the active ingredients in Chonglou have been widely reported in various cancers. However, the potential therapeutic targets of the Chonglou active ingredients in LUAD patients remain unknown. Here, the network pharmacology and bioinformatics were performed to analyze the associations of the clinical characteristics, immune infiltration factors and m⁶A-related genes with the EMT-related genes associated with LUAD (EMT-LUAD related genes), and the molecular docking, STRING, GO, and KEGG enrichment for the drug targets of Chonglou active ingredients associated with EMT (EMT-LUAD-Chonglou related genes). And, cell viability analysis and cell invasion and infiltration analysis were used to confirm the theoretical basis of this study. A total of 166 EMT-LUAD related genes were identified and a multivariate Cox proportional hazards regression model with a favorable predictive accuracy was constructed. Meanwhile, the immune cell infiltration, immune cell subsets, checkpoint inhibitors and the expression of m⁶A-related genes were significantly associated with the risk scores for EMT-LUAD related genes with independent significant prognostic value of all included LUAD patients. Furthermore, 12 EMT-LUAD-Chonglou related genes with five core drug targets were identified, which participated in LUAD development through extracellular matrix disassembly, collagen metabolic process, collagen catabolic process, extracellular matrix organization, extracellular structure organization and inflammatory response. Moreover, we found that the active ingredients of Chonglou could indeed inhibit the progression of lung adenocarcinoma cells. These results are oriented towards EMT-related genes to achieve a better understanding of the role of Chonglou and its targets in osteosarcoma development and metastasis, thus guiding future preclinical studies and facilitating clinical translation of LUAD treatment.

Radiation Recall Pneumonitis Anticipates Bilateral Immune-Induced Pneumonitis in Non-Small Cell Lung Cancer

Radiation recall pneumonitis (RRP) is a rare inflammatory reaction that occurs in previously irradiated fields, and it may be caused by various triggering agents. Immunotherapy has been reported to potentially be one of these triggers. However, precise mechanisms and specific treatments have not been explored yet due to a lack of data in this setting. Here, we report a case of a patient who received radiation therapy and immune checkpoint inhibitor therapy for non-small cell lung cancer. He developed first radiation recall pneumonitis and subsequently immune-checkpoint inhibitor-induced pneumonitis (IIP). After presenting the case, we discuss the currently available literature on RRP and the challenges of differential diagnosis between RRP, IIP, and other forms of pneumonitis. We believe that this case is of particular clinical value since it highlights the importance of including RRP in a differential diagnosis of lung consolidation during immunotherapy. Furthermore, it suggests that RRP might anticipate more extensive ICI-induced pneumonitis.

LncRNA LINC01833 is a Prognostic Biomarker and Correlates with Immune Infiltrates in Patients with Lung Adenocarcinoma by Integrated Bioinformatics Analysis

Due to the absence of accurate tools for early detection and successful treatment, lung adenocarcinoma (LUAD) is one of the most aggressive tumors with high morbidity and mortality globally. It is absolutely necessary to investigate the process behind its development and search for new biomarkers that could aid in the early detection of LUAD. There is a correlation between the immune microenvironment of the tumor and the prognosis of lung cancer as well as the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been identified as potential prognostic biomarkers linked to immunological activities. In this study, we identified 1 downregulated lncRNA and 76 upregulated lncRNAs in LUAD samples from TCGA datasets. Among the 77 dysregulated lncRNAs, our attention focused on lncRNA LINC01833 (LINC01833). When compared with nontumor specimens, the level of expression of LINC01833 was shown to be significantly elevated in LUAD samples. In addition, the data of the ROC study revealed that LUAD patients with high LINC01833 expression had an AUC value of 0.840 (95% confidence interval: 0.804 to 0.876). There was a correlation between high LINC01833 expression and an advanced clinical stage. Patients who had a high expression of LINC01833 were shown to have a lower overall survival rate (p < 0.001) and a lower disease-specific survival rate (p = 0.004) in comparison to patients who were in the low LINC01833 group, according to the data on survival. In addition, the results of the multivariate analysis revealed that high LINC01833 expression was an independent predictor of poor survival in LUAD. Moreover, the immune analysis revealed that we found that the expression of LINC01833 was positively associated with Th2 cells, aDC, and Tgd, while negatively associated with Mast cells, Tcm, Eosinophils, iDC, DC, Tem, Th17 cells, and pDC. Overall, our data point to the possibility that the unique lncRNA LINC01833 might be employed as a diagnostic and prognostic marker, and as a result, it has a significant impact on clinical practice.

Prognostic value of NOX2 as a potential biomarker for lung adenocarcinoma using TCGA and clinical validation

Lung adenocarcinoma (LUAD) is associated with high morbidity and mortality; therefore, effective biomarkers are essential. In recent years, a rapid increase in the efficiency of high‑throughput sequencing technologies and the continuous improvement of comprehensive online databases have facilitated the study of the genomic changes that affect tumor progression, including the identification of tumor biomarkers. Therefore, the identification of genes that may affect the progression and prognosis of LUAD is necessary. In the present study, the CIBERSORT and ESTIMATE bioinformatics packages were used to evaluate data from The Cancer Genome Atlas, including assessment of the proportion of tumor‑infiltrating immune cells in the tumor microenvironment, Cox regression analysis of differentially expressed genes and cross analysis of protein‑protein interaction networks. Myeloid cell NADPH oxidase isoform 2 (NOX2), an indispensable gene in the immune system, was demonstrated to serve a vital role in LUAD pathogenesis. Western blotting and immunohistochemistry confirmed that, at the protein level, NOX2 expression was increased in normal cells compared with cancer cells. Furthermore, reverse transcription‑quantitative PCR results at the mRNA level were consistent with these results, which confirmed that the abundance of NOX2 was significantly reduced in LUAD patients. NOX2 may be used as a novel marker and an independent prognostic indicator of LUAD. Its potential function was enriched in tumor immune and metabolic signaling pathways, which could provide clues for the study of the signaling pathways and molecular networks related to the disease progression of LUAD, which would be helpful for the assessment of prognosis in the clinical setting.

Identification of natural killer cell associated subtyping and gene signature to predict prognosis and drug sensitivity of lung adenocarcinoma

Introduction: This research explored the immune characteristics of natural killer (NK) cells in lung adenocarcinoma (LUAD) and their predictive role on patient survival and immunotherapy response. Material and methods: Molecular subtyping of LUAD samples was performed by evaluating NK cell-associated pathways and genes in The Cancer Genome Atlas (TCGA) dataset using consistent clustering. 12 programmed cell death (PCD) patterns were acquired from previous study. Riskscore prognostic models were constructed using Least absolute shrinkage and selection operator (Lasso) and Cox regression. The model stability was validated in Gene Expression Omnibus database (GEO). Results: We classified LUAD into three different molecular subgroups based on NK cell-related genes, with the worst prognosis in C1 patients and the optimal in C3. Homologous Recombination Defects, purity and ploidy, TMB, LOH, Aneuploidy Score, were the most high-expressed in C1 and the least expressed in C3. ImmuneScore was the highest in C3 type, suggesting greater immune infiltration in C3 subtype. C1 subtypes had higher TIDE scores, indicating that C1 subtypes may benefit less from immunotherapy. Generally, C3 subtype presented highest PCD patterns scores. With four genes, ANLN, FAM83A, RHOV and PARP15, we constructed a LUAD risk prediction model with significant differences in immune cell composition, cell cycle related pathways between the two risk groups. Samples in C1 and high group were more sensitive to chemotherapy drug. The score of PCD were differences in high- and low-groups. Finally, we combined Riskscore and clinical features to improve the performance of the prediction model, and the calibration curve and decision curve verified that the great robustness of the model. Conclusion: We identified three stable molecular subtypes of LUAD and constructed a prognostic model based on NK cell-related genes, maybe have a greater potential for application in predicting immunotherapy response and patient prognosis.