Tumor lymphangiogenesis index reveals the immune landscape and immunotherapy response in lung adenocarcinoma.

Background: Lymphangiogenesis (LYM) has an important role in tumor progression and is strongly associated with tumor metastasis. However, the clinical application of LYM has not progressed as expected. The potential value of LYM needs to be further developed in lung adenocarcinoma (LUAD) patients. Methods: The Sequencing data and clinical characteristics of LUAD patients were downloaded from The Cancer Genome Atlas and GEO databases. Multiple machine learning algorithms were used to screen feature genes and develop the LYM index. Immune cell infiltration, immune checkpoint expression, Tumor Immune Dysfunction and Exclusion (TIDE) algorithm and drug sensitivity analysis were used to explore the correlation of LYM index with immune profile and anti-tumor therapy. Results: We screened four lymphangiogenic feature genes (PECAM1, TIMP1, CXCL5 and PDGFB) to construct LYM index based on multiple machine learning algorithms. We divided LUAD patients into the high LYM index group and the low LYM index group based on the median LYM index. LYM index is a risk factor for the prognosis of LUAD patients. In addition, there was a significant difference in immune profile between high LYM index and low LYM index groups. LUAD patients in the low LYM index group seemed to benefit more from immunotherapy based on the results of TIDE algorithm. Conclusion: Overall, we confirmed that the LYM index is a prognostic risk factor and a valuable predictor of immunotherapy response in LUAD patients, which provides new evidence for the potential application of LYM.

Long survival after neoadjuvant and adjuvant camrelizumab plus chemotherapy and surgery in a patient with hepatoid adenocarcinoma of the lung: A case report.

Hepatoid adenocarcinoma of the lung (HAL) is a rare and aggressive subtype of lung cancer. The prognosis for patients with HAL is generally poor and currently, there are only limited treatment options. Here, we present a case of a 47-year-old male diagnosed with locally advanced-stage HAL who achieved a remarkably long disease-free survival after receiving neoadjuvant and adjuvant camrelizumab plus chemotherapy and surgery. This case highlights the potential of immunochemotherapy plus surgery in improving outcomes for patients with HAL.

Prognostic implications of combining EGFR-TKIs and radiotherapy in Stage IV lung adenocarcinoma with 19-Del or 21-L858R mutations: A real-world study.

OBJECTIVE: To elucidate the potential benefits of combining radiotherapy and epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) for individuals with Stage IV lung adenocarcinoma (LUAD) harboring either exon 19 deletion (19-Del) or exon 21 L858R mutation (21-L858R). METHODS: In this real-world retrospective study, 177 individuals with Stage IV LUAD who underwent EGFR-TKIs and radiotherapy at Shandong Cancer Hospital from June 2012 to August 2017 were included. The main focus of this real-world study was overall survival (OS). RESULTS: The clinical characteristics of patients with Stage IV LUAD harboring 19-Del were similar to those harboring 21-L858R (p > 0.05). Overall, the patients had a median OS (mOS) of 32.0 months (95% confidence interval [CI]: 28.6-35.5). Subsequently, multivariate analysis indicated that both EGFR mutations and thoracic radiotherapy were independent predictors of OS (p = 0.001 and 0.013). Furthermore, subgroup analysis highlighted a longer OS for the 19-Del group compared to the 21-L858R group, especially when EGFR-TKIs were combined with bone metastasis or thoracic radiotherapy (mOS: 34.7 vs. 25.1 months and 51.0 vs. 29.6 months; p = 0.0056 and 0.0013, respectively). However, no significant differences were found in OS when considering patients who underwent brain metastasis radiotherapy (mOS: 34.7 vs. 25.1 months; p = 0.088). CONCLUSIONS: Patients with Stage IV LUAD harboring 19-Del experience a notably prolonged OS following combined therapy with EGFR-TKIs and radiotherapy, while this OS benefit is observed despite the absence of substantial differences in the clinical characteristics between the 19-Del and 21-L858R groups.

Deciphering the heterogeneity dominated by tumor-associated macrophages for survival prognostication and prediction of immunotherapy response in lung adenocarcinoma.

Tumor-associated macrophages (TAMs) are a specific subset of macrophages that reside inside the tumor microenvironment. The dynamic interplay between TAMs and tumor cells plays a crucial role in the treatment response and prognosis of lung adenocarcinoma (LUAD). The study aimed to examine the association between TAMs and LUAD to advance the development of targeted strategies and immunotherapeutic approaches for treating this type of lung cancer. The study employed single-cell mRNA sequencing data to characterize the immune cell composition of LUAD and delineate distinct subpopulations of TAMs. The "BayesPrism" and "Seurat" R packages were employed to examine the association between these subgroups and immunotherapy and clinical features to identify novel immunotherapy biomarkers. Furthermore, a predictive signature was generated to forecast patient prognosis by examining the gene expression profile of immunotherapy-associated TAMs subsets and using 104 machine-learning techniques. A comprehensive investigation has shown the existence of a hitherto unidentified subgroup of TAMs known as RGS1 + TAMs, which has been found to have a strong correlation with the efficacy of immunotherapy and the occurrence of tumor metastasis in LUAD patients. CD83 was identified CD83 as a distinct biomarker for the expression of RGS1 + TAMs, showcasing its potential utility as an indicator for immunotherapeutic interventions. Furthermore, the prognostic capacity of the RTMscore signature, encompassing three specific mRNA (NR4A2, MMP14, and NPC2), demonstrated enhanced robustness when contrasted against the comprehensive collection of 104 features outlined in the published study. CD83 has potential as an immunotherapeutic biomarker. Meanwhile, The RTMscore signature established in the present study might be beneficial for survival prognostication.

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

BACKGROUND: Immunogenic cell death (ICD) is a regulated form of cell death that triggers an adaptive immune response. The objective of this study was to investigate the correlation between ICD-related genes (ICDGs) and the prognosis and the immune microenvironment of patients with lung adenocarcinoma (LUAD). METHODS: ICD-associated molecular subtypes were identified through consensus clustering. Subsequently, a prognostic risk model comprising 5 ICDGs was constructed using Lasso-Cox regression in the TCGA training cohort and further tested in the GEO cohort. Enriched pathways among the subtypes were analyzed using GO, KEGG, and GSVA. Furthermore, the immune microenvironment was assessed using ESTIMATE, CIBERSORT, and ssGSEA analyses. RESULTS: Consensus clustering divided LUAD patients into three ICDG subtypes with significant differences in prognosis and the immune microenvironment. A prognostic risk model was constructed based on 5 ICDGs and it was used to classify the patients into two risk groups; the high-risk group had poorer prognosis and an immunosuppressive microenvironment characterized by low immune score, low immune status, high abundance of immunosuppressive cells, and high expression of tumor purity. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor. The five hub genes were verified by TCGA database, cell sublocalization immunofluorescence analysis, IHC images and qRT-PCR, which were consistent with bioinformatics analysis. CONCLUSIONS: The molecular subtypes and a risk model based on ICDGs proposed in our study are both promising prognostic classifications in LUAD, which may provide novel insights for developing accurate targeted cancer therapies.

Purine metabolism in lung adenocarcinoma: A single-cell analysis revealing prognostic and immunotherapeutic insights.

Lung adenocarcinoma (LUAD) is a prevalent subtype of lung cancer, yet the contribution of purine metabolism (PM) to its pathogenesis remains poorly elucidated. PM, a critical component of intracellular nucleotide synthesis and energy metabolism, is hypothesized to exert a significant influence on LUAD development. Herein, we employed single-cell analysis to investigate the role of PM within the tumour microenvironment (TME) of LUAD. PM scoring (PMS) across distinct cell types was determined using AUCell, UCell, singscore and AddModuleScore algorithms. Subsequently, we explored communication networks among cells within high- and low-PMS groups, establishing a robust PM-associated signature (PAS) utilizing a comprehensive dataset comprising LUAD samples from TCGA and five GEO datasets. Our findings revealed that the high-PMS group exhibited intensified cell interactions, while the PAS, constructed using PM-related genes, demonstrated precise prognostic predictive capability. Notably, analysis across the TCGA dataset and five GEO datasets indicated that low-PAS patients exhibited a superior prognosis. Furthermore, the low-PAS group displayed increased immune cell infiltration and elevated CD8A expression, coupled with reduced PD-L1 expression. Moreover, data from eight publicly available immunotherapy cohorts suggested enhanced immunotherapy outcomes in the low-PAS group. These results underscore a close association between PAS and tumour immunity, offering predictive insights into genomic alterations, chemotherapy drug sensitivity and immunotherapy responses in LUAD. The newly established PAS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.

Molecular classification reveals the sensitivity of lung adenocarcinoma to radiotherapy and immunotherapy: multi-omics clustering based on similarity network fusion.

BACKGROUND: Due to individual differences in tumors and immune systems, the response rate to immunotherapy is low in lung adenocarcinoma (LUAD) patients. Combinations with other therapeutic strategies improve the efficacy of immunotherapy in LUAD patients. Although radioimmunotherapy has been demonstrated to effectively suppress tumors, the underlying mechanisms still need to be investigated. METHODS: Total RNA from LUAD cells was sequenced before and after radiotherapy to identify differentially expressed radiation-associated genes. The similarity network fusion (SNF) algorithm was applied for molecular classification based on radiation-related genes, immune-related genes, methylation data, and somatic mutation data. The changes in gene expression, prognosis, immune cell infiltration, radiosensitivity, chemosensitivity, and sensitivity to immunotherapy were assessed for each subtype. RESULTS: We used the SNF algorithm and multi-omics data to divide TCGA-LUAD patients into three subtypes. Patients with the CS3 subtype had the best prognosis, while those with the CS1 and CS2 subtypes had poorer prognoses. Among the strains tested, CS2 exhibited the most elevated immune cell infiltration and expression of immune checkpoint genes, while CS1 exhibited the least. Patients in the CS2 subgroup were more likely to respond to PD-1 immunotherapy. The CS2 patients were most sensitive to docetaxel and cisplatin, while the CS1 patients were most sensitive to paclitaxel. Experimental validation of signature genes in the CS2 subtype showed that inhibiting the expression of RHCG and TRPA1 could enhance the sensitivity of lung cancer cells to radiation. CONCLUSIONS: In summary, this study identified a risk classifier based on multi-omics data that can guide treatment selection for LUAD patients.

The association of genomic alterations with PD-L1 expression in Chinese patients with EGFR/ALK wild-type lung adenocarcinoma and potential predictive value of Hippo pathway mutations to immunotherapy.

BACKGROUND: The study focuses on PD-L1 expression as an essential biomarker for gauging the response of EGFR/ALK wild-type NSCLC patients to FDA-approved immune checkpoint inhibitors (ICIs). It aims to explore clinical, molecular, and immune microenvironment characteristics associated with PD-L1 expression in EGFR/ALK wild-type lung adenocarcinoma patients eligible for ICI therapy. METHODS: In this retrospective study, tumor samples from 359 Chinese EGFR/ALK wild-type lung adenocarcinoma patients underwent comprehensive evaluations for PD-L1 expression and NGS-targeted sequencing. The investigation encompassed the analysis and comparison of clinical traits, gene mutations, pathways, and immune signatures between two groups categorized by PD-L1 status: negative (TPS < 1%) and positive (TPS ≥ 1%). Additionally, the study explored the link between genomic changes and outcomes following immunotherapy. RESULTS: High tumor mutational burden correlated significantly with PD-L1 positivity in patients with EGFR/ALK wild-type lung adenocarcinoma. Gene alterations, including TP53, KRAS, and others, were more pronounced in the PD-L1 positive group. Pathway analysis highlighted higher frequencies of alterations in pathways like RTK/RAS, p53, and Hippo in PD-L1-positive patients. The Hippo pathway's relevance was confirmed in separate immunotherapy cohorts, associated with better outcomes. In terms of immune cell infiltration, Hippo mutants exhibited higher levels of CD68+ PD-L1+ macrophages, CD8+ T cells, and CD8+ PD-1- T cells. CONCLUSIONS: This study offers insights into genomic features of Chinese EGFR/ALK wild-type lung adenocarcinoma patients based on PD-L1 expression. Notably, Hippo pathway alterations were linked to improved immunotherapy outcomes. These findings suggest connections between the Hippo pathway and PD-L1 expression, warranting further clinical and functional investigations. The research advances our understanding of PD-L1 expression's genomic context and immunotherapy response in EGFR/ALK wild-type lung adenocarcinoma.

Lineage-specific intolerance to oncogenic drivers restricts histological transformation.

Lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) are thought to originate from different epithelial cell types in the lung. Intriguingly, LUAD can histologically transform into SCLC after treatment with targeted therapies. In this study, we designed models to follow the conversion of LUAD to SCLC and found that the barrier to histological transformation converges on tolerance to Myc, which we implicate as a lineage-specific driver of the pulmonary neuroendocrine cell. Histological transformations are frequently accompanied by activation of the Akt pathway. Manipulating this pathway permitted tolerance to Myc as an oncogenic driver, producing rare, stem-like cells that transcriptionally resemble the pulmonary basal lineage. These findings suggest that histological transformation may require the plasticity inherent to the basal stem cell, enabling tolerance to previously incompatible oncogenic driver programs.

Survival outcomes of targeted and immune consolidation therapies in locally advanced unresectable lung adenocarcinoma.

BACKGROUND: Locally advanced non-small cell lung cancer (LA-NSCLC) presents unique challenges due to its progression and tumor heterogeneity. The effectiveness of consolidation therapies, particularly in patients with gene mutations, remains an area of active investigation. METHODS: In this retrospective cohort study, we examined data from 3,454 patients with unresectable lung adenocarcinoma (LUAD), narrowing our focus to 242 individuals with stage II/III. We gathered patient data, such as demographics, ECOG status, histology, treatment specifics, and gene expression, from patients in China. The study's primary outcome was overall survival (OS), while progression-free survival (PFS) served as the secondary outcome. RESULTS: In this study, 50 % of the 242 patients underwent only radical chemoradiotherapy, with 45.87 % (111/242) exhibiting driver gene mutations, predominantly EGFR (58.57 %), followed by KRAS and ALK. Patients with mutations who received either targeted or immune consolidation therapy demonstrated a significantly longer median PFS (42.97 months vs. 24.87 months, p = 0.014) and improved OS (not reached vs. 24.37 months, p = 0.006), compared to those without consolidation therapy. Targeted therapy in mutant patients resulted in an extended median PFS (42.87 months) compared to immune therapy (27.03 months, p = 0.029), with no significant difference in OS. Median PFS and OS were similar between mutant and wild-type patients receiving immune therapy (p = 0.380 and p = 0.928, respectively). CONCLUSION: This study underscores the efficacy of targeted consolidation therapy in enhancing PFS in LUAD patients with genetic mutations. It also shows that immune consolidation therapy provides similar survival benefits to mutant and wild-type patients. Future research should focus on optimizing these therapies for improved patient outcomes.

Combining TIGIT blockade with IL-15 stimulation is a promising immunotherapy strategy for lung adenocarcinoma.

BACKGROUND: T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) is an immune checkpoint molecule that suppresses CD8+ T-cell function in cancer. However, the expression profile and functional significance of TIGIT in the immune microenvironment of lung adenocarcinoma (LUAD) remain elusive. Interleukin (IL)-15 has emerged as a promising candidate for enhancing CD8+ T-cell mediated tumour eradication. Exploring therapeutic strategies that combine IL-15 with TIGIT blockade in LUAD is warranted. METHODS: We investigated the regulatory network involving coinhibitory TIGIT and CD96, as well as costimulatory CD226 in LUAD using clinical samples. The potential role of TIGIT in regulating the pathogenesis of LUAD was addressed through a murine model with transplanted tumours constructed in Tigit-/- mice. The therapeutic strategy that combines TIGIT blockade with IL-15 stimulation was verified using a transplanted tumour murine model and a patient-derived organoid (PDO) model. RESULTS: The frequency of TIGIT+ CD8+ T cells was significantly increased in LUAD. Increased TIGIT expression indicated poorer prognosis in LUAD patients. Furthermore, the effector function of TIGIT+ CD8+ tumour-infiltrating lymphocytes (TILs) was impaired in LUAD patients and TIGIT inhibited antitumour immune response of CD8+ TILs in tumour-bearing mice. Mechanistically, IL-15 enhanced the effector function of CD8+ TILs but stimulated the expression of TIGIT on CD8+ TILs concomitantly. The application of IL-15 combined with TIGIT blockade showed additive effects in enhancing the cytotoxicity of CD8+ TILs and thus further increased the antitumour immune response in LUAD. CONCLUSIONS: Our findings identified TIGIT as a promising therapeutic target for LUAD. LUAD could benefit more from the combined therapy of IL-15 stimulation and TIGIT blockade.

Identification of Stem Cell-related Gene Markers by Comprehensive Transcriptome Analysis to Predict the Prognosis and Immunotherapy of Lung Adenocarcinoma.

BACKGROUND: Cancer stem cells (CSCs) contribute to metastasis and drug resistance to immunotherapy in lung adenocarcinoma (LUAD), so the stemness evaluation of cancer cells is of great significance. METHOD: The single-cell RNA sequencing (scRNA-seq) data of the GSE149655 dataset were collected and analyzed. Malignant cells were distinguished by CopyKAT. CytoTRACE score of marker genes in malignant cells was counted by CytoTRACE to construct the stemness score formula. Sample stemness score in TCGA was determined by the formula and divided into high-, medium- and low-stemness score groups. LASSO and COX regression analyses were carried out to screen the key genes related to the prognosis of LUAD from the differentially expressed genes (DEGs) in high- and low-stemness score groups and a risk score model was constructed. RESULT: Seven types of cells were identified from a total of 4 samples, and 193 marker genes of 3455 malignant cells were identified. There were 1098 DEGs between low- and high-stemness score groups of TCGA, of which CPS1, CENPK, GJB3, and TPSB2 constituted gene signatures. The 4-gene signature could independently evaluate LUAD survival in the training and validation sets and showed an acceptable area under the receiver operator characteristic (ROC) curves (AUCs). CONCLUSION: This study provides insights into the cellular heterogeneity of LUAD and develops a new cancer stemness evaluation indicator and a 4-gene signature as a potential tool for evaluating the response of LUAD to immune checkpoint blockade (ICB) therapy or antineoplastic therapy.

Classification and immunotherapy assessment of lung adenocarcinoma based on coagulation-related genes.

Introduction: This study on lung adenocarcinoma (LUAD), a common lung cancer subtype with high mortality. Aims: This study focuses on how tumor cell interactions affect immunotherapy responsiveness. Methods: Using public databases, we used non-negative matrix factorization clustering method, ssGSEA, CIBERSORT algorithm, immunophenotype score, survival analysis, protein-protein interaction network method to analyze gene expression data and coagulation-related genes. Results: We divided LUAD patients into three coagulation-related subgroups with varying immune characteristics and survival rates. A cluster of three patients, having the highest immune infiltration and survival rate, also showed the most potential for immunotherapy. We identified five key genes influencing patient survival using a protein-protein interaction network. Conclusion: This research offers valuable insights for forecasting prognosis and immunotherapy responsiveness in LUAD patients, helping to inform clinical treatment strategies.

Vasculogenic mimicry-associated novel gene signature predicted prognosis and response to immunotherapy in lung adenocarcinoma.

BACKGROUNDS: It was highlighted by recent studies on the biological significance of vasculogenic mimicry (VM) in tumorigenicity and progression. However, it is unclear whether VM also plays a potential role in immune regulation and tumor microenvironment (TME) formation. METHODS: To identify patterns of VM alterations and VM-associated genetic features in non-small cell lung adenocarcinoma, we have screened 309 VM regulators and performed consensus molecular typing by the NMF algorithm. The ssGSEA and CIBORSORT algorithms were employed to measure the relative infiltration of distinct immune cell subpopulations. Individual tumors with immune responses were evaluated for alteration patterns of VM with typing-based differential genes. RESULTS: In 490 LUAD samples, two distinctive VM alteration patterns connected to different clinical outcomes and biochemical pathways were established. TME characterization showed that the observed VM patterns were primarily saturated with cell proliferation and metabolic pathways and higher in immune cell infiltration of the C1 type. Vasculogenic mimicry-related genes (VMRG) risk scores were constructed to divide patients with lung adenocarcinoma into subgroups with high and low scores. Patients with lower scores had better immunological scores and longer survival times. Upon further investigation, higher scores were positively correlated with higher tumor mutation burden (TMB), M1-type macrophages and immune checkpoint molecules. Nevertheless, in two other immunotherapy cohorts, individuals with lower scores had enhanced immune responses and long-lasting therapeutic benefits. Finally, we monitored the ANLN gene from the VMRG model, which was highly expressed in lung adenocarcinoma tissues and negatively correlated with prognosis; it was also highly expressed in lung adenocarcinoma cell lines, and knockdown of ANLN elicited low expression of VEGFA, MMP2 and MMP9. CONCLUSION: This study highlights that VM modifications are significantly associated with the diversity and complexity of TME, revealing new features of the immune microenvironment in lung adenocarcinoma and providing a new strategy for immunotherapy. Screening ANLN as a critical target for vasculogenic mimicry in lung adenocarcinoma provides a novel perspective for the targeted treatment of lung adenocarcinoma.

Single-cell dissection reveals the role of aggrephagy patterns in tumor microenvironment components aiding predicting prognosis and immunotherapy on lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the leading malignant cancers. Aggrephagy plays a critical role in key genetic events for various cancers; yet, how aggrephagy functions within the tumor microenvironment (TME) in LUAD remains to be elucidated. METHODS: In this study, by sequential non-negative matrix factorization (NMF) algorithm, pseudotime analysis, cell-cell interaction analysis, and SCENIC analysis, we have shown that aggrephagy genes demonstrated various patterns among different cell types in LUAD TME. LUAD and Immunotherapy cohorts from public repository were used to determine the prognosis and immune response of aggrephagy TME subtypes. The aggrephagy-deprived prognostic score (ADPS) was quantified based on machine learning algorithms. RESULTS: The cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and CD8+ T cells have various aggrephagy patterns, which enhance the intensity of intercellular communication and transcription factor activation. Furthermore, based on the signatures of the newly defined aggrephagy cell subtypes and expression profiles of large cohorts in LUAD patients, we determine that DYNC1I2+CAF-C1, DYNLL1+CAF-C2, PARK7+CAF-C3, VIM+Mac-C1, PARK7+Mac-C2, VIM+CD8+T_cells-C1, UBA52+CD8+T_cells-C2, TUBA4A+CD8+T_ cells-C3, and TUBA1A+CD8+T_cells-C4 are crucial prognostic factors for LUAD patients. The developed ADPS could predict survival outcomes and immunotherapeutic response across ten cohorts (n = 1838), and patients with low ADPS owned a better prognosis, lower genomic alterations, and are more sensitive to immunotherapy. Meanwhile, based on PRISM, CTRP, and CMAP databases, PLK inhibitor BI-2536, may be a potential agent for patients with high ADPS. CONCLUSIONS: Taken together, our novel and systematic single-cell analysis has revealed the unique role of aggrephagy in remodeling the TME of LUAD. As a newly demonstrated biomarker, the ADPS facilitates the clinical management and individualized treatment of LUAD.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma.

INTRODUCTION: Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer. AREAS COVERED: Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity. EXPERT OPINION: Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.

Classification of SLC family-related genes involved in ferroptosis predicts lung cancer prognosis and immunotherapy response.

Lung adenocarcinoma, the most frequent type of lung cancer, is the leading cause of cancer-related deaths worldwide. Ferroptosis, controlled cell death that involves a high degree of iron-dependent lipid peroxidation, has been linked to tumor therapy sensitivity, patient prognosis, and cancer development. The solute carrier superfamily has over 400 members and comprises the largest class of transporters in the human genome. Solute carrier proteins can facilitate the movement of different substrates across biological membranes, which is crucial for physiological activities, including ferroptosis. Here, we developed a new model to further explore the role of the solute carrier family in ferroptosis in the lung adenocarcinoma immunological milieu. We used consensus clustering to classify patients with lung cancer into two subgroups (cluster1 and cluster2). Patients in the cluster1 subtype had a better prognosis and higher immune cell infiltration ratios than those in the cluster2 subtype. Furthermore, to evaluate the prognosis, the immune cell infiltration ratio, and the medication sensitivity of patients with lung adenocarcinoma, we developed gene scores related to the solute carrier family. In conclusion, we successfully developed a model incorporating the solute carrier family and ferroptosis to predict survival and the impact of immunotherapy on patients with lung cancer.

Comprehensive analyses for the coagulation and macrophage-related genes to reveal their joint roles in the prognosis and immunotherapy of lung adenocarcinoma patients.

Purpose: This study aims to explore novel biomarkers related to the coagulation process and tumor-associated macrophage (TAM) infiltration in lung adenocarcinoma (LUAD). Methods: The macrophage M2-related genes were obtained by Weighted Gene Co-expression Network Analysis (WGCNA) in bulk RNA-seq data, while the TAM marker genes were identified by analyzing the scRNA-seq data, and the coagulation-associated genes were obtained from MSigDB and KEGG databases. Survival analysis was performed for the intersectional genes. A risk score model was subsequently constructed based on the survival-related genes for prognosis prediction and validated in external datasets. Results: In total, 33 coagulation and macrophage-related (COMAR) genes were obtained, 19 of which were selected for the risk score model construction. Finally, 10 survival-associated genes (APOE, ARRB2, C1QB, F13A1, FCGR2A, FYN, ITGB2, MMP9, OLR1, and VSIG4) were involved in the COMAR risk score model. According to the risk score, patients were equally divided into low- and high-risk groups, and the prognosis of patients in the high-risk group was significantly worse than that in the low-risk group. The ROC curve indicated that the risk score model had high sensitivity and specificity, which was validated in multiple external datasets. Moreover, the model also had high efficacy in predicting the clinical outcomes of LUAD patients who received anti-PD-1/PD-L1 immunotherapy. Conclusion: The COMAR risk score model constructed in this study has excellent predictive value for the prognosis and immunotherapeutic clinical outcomes of patients with LUAD, which provides potential biomarkers for the treatment and prognostic prediction.

KEAP1 mutation in lung adenocarcinoma promotes immune evasion and immunotherapy resistance.

Lung cancer treatment has benefited greatly through advancements in immunotherapies. However, immunotherapy often fails in patients with specific mutations like KEAP1, which are frequently found in lung adenocarcinoma. We established an antigenic lung cancer model and used it to explore how Keap1 mutations remodel the tumor immune microenvironment. Using single-cell technology and depletion studies, we demonstrate that Keap1-mutant tumors diminish dendritic cell and T cell responses driving immunotherapy resistance. This observation was corroborated in patient samples. CRISPR-Cas9-mediated gene targeting revealed that hyperactivation of the NRF2 antioxidant pathway is responsible for diminished immune responses in Keap1-mutant tumors. Importantly, we demonstrate that combining glutaminase inhibition with immune checkpoint blockade can reverse immunosuppression, making Keap1-mutant tumors susceptible to immunotherapy. Our study provides new insight into the role of KEAP1 mutations in immune evasion, paving the way for novel immune-based therapeutic strategies for KEAP1-mutant cancers.

Single-cell analysis reveals exosome-associated biomarkers for prognostic prediction and immunotherapy in lung adenocarcinoma.

BACKGROUND: Exosomes play a crucial role in tumor initiation and progression, yet the precise involvement of exosome-related genes (ERGs) in lung adenocarcinoma (LUAD) remains unclear. METHODS: We conducted a comprehensive investigation of ERGs within the tumor microenvironment (TME) of LUAD using single-cell RNA sequencing (scRNA-seq) analysis. Multiple scoring methods were employed to assess exosome activity (EA). Differences in cell communication were examined between high and low EA groups, utilizing the "CellChat" R package. Subsequently, we leveraged multiple bulk RNA-seq datasets to develop and validate exosome-associated signatures (EAS), enabling a multifaceted exploration of prognosis and immunotherapy outcomes between high- and low-risk groups. RESULTS: In the LUAD TME, epithelial cells demonstrated the highest EA, with even more elevated levels observed in advanced LUAD epithelial cells. The high-EA group exhibited enhanced intercellular interactions. EAS were established through the analysis of multiple bulk RNA-seq datasets. Patients in the high-risk group exhibited poorer overall survival (OS), reduced immune infiltration, and decreased expression of immune checkpoint genes. Finally, we experimentally validated the high expression of SEC61G in LUAD cell lines and demonstrated that knockdown of SEC61G reduced the proliferative capacity of LUAD cells using colony formation assays. CONCLUSION: The integration of single-cell and bulk RNA-seq analyses culminated in the development of the profound and significant EAS, which imparts invaluable insights for the clinical diagnosis and therapeutic management of LUAD patients.