Overexpression of Malat1 drives metastasis through inflammatory reprogramming of the tumor microenvironment.

Expression of the long noncoding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) correlates with tumor progression and metastasis in many tumor types. However, the impact and mechanism of action by which MALAT1 promotes metastatic disease remain elusive. Here, we used CRISPR activation (CRISPRa) to overexpress MALAT1/Malat1 in patient-derived lung adenocarcinoma (LUAD) cell lines and in the autochthonous K-ras/p53 LUAD mouse model. Malat1 overexpression was sufficient to promote the progression of LUAD to metastatic disease in mice. Overexpression of MALAT1/Malat1 enhanced cell mobility and promoted the recruitment of protumorigenic macrophages to the tumor microenvironment through paracrine secretion of CCL2/Ccl2. Ccl2 up-regulation was the result of increased global chromatin accessibility upon Malat1 overexpression. Macrophage depletion and Ccl2 blockade counteracted the effects of Malat1 overexpression. These data demonstrate that a single lncRNA can drive LUAD metastasis through reprogramming of the tumor microenvironment.

TMPRSS2 is a tumor suppressor and its downregulation promotes antitumor immunity and immunotherapy response in lung adenocarcinoma.

BACKGROUND: TMPRSS2, a key molecule for SARS-CoV-2 invading human host cells, has an association with cancer. However, its association with lung cancer remains insufficiently unexplored. METHODS: In five bulk transcriptomics datasets, one single-cell RNA sequencing (scRNA-seq) dataset and one proteomics dataset for lung adenocarcinoma (LUAD), we explored associations between TMPRSS2 expression and immune signatures, tumor progression phenotypes, genomic features, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we performed experimental validation of the bioinformatics findings. RESULTS: TMPRSS2 expression levels correlated negatively with the enrichment levels of both immune-stimulatory and immune-inhibitory signatures, while they correlated positively with the ratios of immune-stimulatory/immune-inhibitory signatures. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor progression, and worse survival in LUAD. We further validated that TMPRSS2 was downregulated with tumor progression in the LUAD cohort we collected from Jiangsu Cancer Hospital, China. In vitro and in vivo experiments verified the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1. CONCLUSIONS: TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a potential link between lung cancer and pneumonia caused by SARS-CoV-2 infection.

Insights into the heterogeneity of the tumor microenvironment in lung adenocarcinoma and squamous carcinoma through single-cell transcriptomic analysis: Implications for distinct immunotherapy outcomes.

BACKGROUND: Immune checkpoint blockade has emerged as a key strategy to the therapy landscape of non-small cell lung cancer (NSCLC). However, notable differences in immunotherapeutic outcomes exist between the two primary NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). This disparity may stem from the tumor immune microenvironment's heterogeneity at the transcriptome level. METHODS: By integrative analysis of transcriptomic characterization of 38 NSCLC patients by single-cell RNA sequencing, the present study revealed a distinct tumor microenvironment (TME) between LUAD and LUSC, with relevant results further confirmed in bulk transcriptomic and multiplex immunofluorescence (mIF) validation cohort of neoadjuvant immunotherapy patients. RESULTS: LUAD exhibited a more active immune microenvironment compared to LUSC. This included highly expression of HLA I/II in cancer cells, reinforced antigen presentation potential of dendritic cells and enhanced cytotoxic activity observed in T/NK cells. In LUSC, cancer cells highly expressed genes belonging to the aldo-keto reductases, glutathione S-transferases and aldehyde dehydrogenase family, negatively correlating with immunotherapy outcomes in the validation cohort of our center. Further analysis revealed elevated infiltrated cancer-associated fibroblasts (CAFs) in LUSC, which was corroborated in The Cancer Genome Atlas cohort. Corresponding increased infiltration of ADH1B+ CAFs in major pathologic response (MPR) patients and the higher presence of FAP+ CAFs in non-MPR patients were demonstrated by multiplex mIF. Moreover, upregulating immunosuppressive extracellular matrix remodeling was identified in LUSC. CONCLUSIONS: These comprehensive analyses advance the understanding of the differences in TME between LUAD and LUSC, offering insights for patient selection and developing subtype-specific treatment strategies.

Identifying and assessing a prognostic model based on disulfidptosis-related genes: implications for immune microenvironment and tumor biology in lung adenocarcinoma.

Introduction: Lung cancer, with the highest global mortality rate among cancers, presents a grim prognosis, often diagnosed at an advanced stage in nearly 70% of cases. Recent research has unveiled a novel mechanism of cell death termed disulfidptosis, which is facilitated by glucose scarcity and the protein SLC7A11. Methods: Utilizing the least absolute shrinkage and selection operator (LASSO) regression analysis combined with Cox regression analysis, we constructed a prognostic model focusing on disulfidptosis-related genes. Nomograms, correlation analyses, and enrichment analyses were employed to assess the significance of this model. Among the genes incorporated into the model, CHRNA5 was selected for further investigation regarding its role in LUAD cells. Biological functions of CHRNA5 were assessed using EdU, transwell, and CCK-8 assays. Results: The efficacy of the model was validated through internal testing and an external validation set, with further evaluation of its robustness and clinical applicability using a nomogram. Subsequent correlation analyses revealed associations between the risk score and infiltration of various cancer types, as well as oncogene expression. Enrichment analysis also identified associations between the risk score and pivotal biological processes and KEGG pathways. Our findings underscore the significant impact of CHRNA5 on LUAD cell proliferation, migration, and disulfidptosis. Conclusion: This study successfully developed and validated a robust prognostic model centered on disulfidptosis-related genes, providing a foundation for predicting prognosis in LUAD patients.

The deubiquitinase USP2a promotes tumor immunosuppression by stabilizing immune checkpoint B7-H4 in lung adenocarcinoma harboring EGFR-activating mutants.

B7-H4 is an immune checkpoint crucial for inhibiting CD8+ T-cell activity. A clinical trial is underway to investigate B7-H4 as a potential immunotherapeutic agent. However, the regulatory mechanism of B7-H4 degradation via the ubiquitin-proteasome pathway (UPP) remains poorly understood. In this study, we discovered that proteasome inhibitors effectively increased B7-H4 expression, while EGFR-activating mutants promoted B7-H4 expression through the UPP. We screened B7-H4 binding proteins by co-immunoprecipitation and mass spectrometry and found that USP2a acted as a deubiquitinase of B7-H4 by removing K48- and K63-linked ubiquitin chains from B7-H4, leading to a reduction in B7-H4 degradation. EGFR mutants enhanced B7-H4 stability by upregulating USP2a expression. We further investigated the role of USP2a in tumor growth in vivo. Depletion of USP2a in L858R/LLC cells inhibited tumor cell proliferation, consequently suppressing tumor growth in immune-deficient nude mice by destabilizing downstream molecules such as Cyclin D1. In an immune-competent C57BL/6 mouse tumor model, USP2a abrogation facilitated infiltration of CD95+CD8+ effector T cells and hindered infiltration of Tim-3+CD8+ and LAG-3+CD8+ exhausted T cells by destabilizing B7-H4. Clinical lung adenocarcinoma samples showed a significant correlation between B7-H4 abundance and USP2a expression, indicating the contribution of the EGFR/USP2a/B7-H4 axis to tumor immunosuppression. In summary, this study elucidates the dual effects of USP2a in tumor growth by stabilizing Cyclin D1, promoting tumor cell proliferation, and stabilizing B7-H4, contributing to tumor immunosuppression. Therefore, USP2a represents a potential target for tumor therapy.

Single-cell analysis identifies PLK1 as a driver of immunosuppressive tumor microenvironment in LUAD.

PLK1 (Polo-like kinase 1) plays a critical role in the progression of lung adenocarcinoma (LUAD). Recent studies have unveiled that targeting PLK1 improves the efficacy of immunotherapy, highlighting its important role in the regulation of tumor immunity. Nevertheless, our understanding of the intricate interplay between PLK1 and the tumor microenvironment (TME) remains incomplete. Here, using genetically engineered mouse model and single-cell RNA-seq analysis, we report that PLK1 promotes an immunosuppressive TME in LUAD, characterized with enhanced M2 polarization of tumor associated macrophages (TAM) and dampened antigen presentation process. Mechanistically, elevated PLK1 coincides with increased secretion of CXCL2 cytokine, which promotes M2 polarization of TAM and diminishes expression of class II major histocompatibility complex (MHC-II) in professional antigen-presenting cells. Furthermore, PLK1 negatively regulates MHC-II expression in cancer cells, which has been shown to be associated with compromised tumor immunity and unfavorable patient outcomes. Taken together, our results reveal PLK1 as a novel modulator of TME in LUAD and provide possible therapeutic interventions.

Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression.

BACKGROUND: Due to the unfavorable prognosis associated with lung adenocarcinoma (LUAD), the development of targeted therapies and immunotherapies is essential. Cuproptosis, an emerging form of regulated cell death, is implicated in mitochondrial metabolism and is induced by copper ions. This study aimed to explore the prognostic value of cuproptosis- and immune-related genes (CIRGs) in LUAD. METHODS: We used The Cancer Genome Atlas database to develop a prognostic prediction model for LUAD patients based on eight CIRGs. Using Cox regression analysis, we determined that the CIRG signature is a reliable, independent prognostic factor. We further identified PSMD11 as a critical CIRG and performed immunohistochemistry to study the protein expression levels of PSMD11 in LUAD tissues. We also investigated the impact of PSMD11 on the biological behavior of lung cancer cell lines. RESULTS: We found that patients with low PSMD11 expression levels displayed an improved prognosis compared with those with high PSMD11 expression levels. Overexpression of PSMD11 enhanced proliferation, migration, invasion, and tumor growth of lung carcinoma cell line A549, while PSMD11 knockdown diminished proliferation, migration, invasion, and tumor growth of lung carcinoma cell line PC9. Additionally, we discovered that PSMD11 expression was positively correlated with the infiltration of myeloid-derived suppressor cells and the increased expression of immunosuppressive molecules. CONCLUSION: These findings suggest that PSMD11 may serve as a valuable prognostic biomarker and therapeutic target for LUAD.

Density of tumor-infiltrating NK and Treg cells is associated with 5 years progression-free and overall survival in resected lung adenocarcinoma.

Surgical resection of pulmonary adenocarcinoma is considered to be curative but progression-free survival (PFS) has remained highly variable. Antitumor immune response may be important, however, the prognostic significance of tumor-infiltrating natural killer (NK) and regulatory T (Treg) lymphocytes is uncertain. Resected pulmonary adenocarcinoma tissues (n = 115) were studied by immunohistochemical detection of NKp46 and FoxP3 positivity to identify NK and Treg cells, respectively. Association of cell densities with clinicopathological features and progression-free survival (PFS) as well as overall survival (OS) were analyzed with a follow-up time of 60 months. Both types of immune cells were accumulated predominantly in tumor stroma. NK cell density showed association with female gender, non-smoking and KRAS wild-type status. According to Kaplan-Meier analysis, PFS and OS proved to be longer in patients with high NK or Treg cell densities (p = 0.0293 and p = 0.0375 for PFS, p = 0.0310 and p = 0.0448 for OS, respectively). Evaluating the prognostic effect of the combination of NK and Treg cell density values revealed that PFS and OS were significantly longer in NKhigh/Treghigh cases compared to the other groups combined (p = 0.0223 and p = 0.0325, respectively). Multivariate Cox regression analysis indicated that high NK cell density was independent predictor of longer PFS while high NK and high Treg cell densities both proved significant predictors of longer OS. The NKhigh/Treghigh combination also proved to be an independent prognostic factor for both PFS and OS. In conclusion, NK and Treg cells can be components of the innate and adaptive immune response at action against progression of pulmonary adenocarcinoma.

Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provide both common and discordant biological insights.

Whether single-cell RNA-sequencing (scRNA-seq) captures the same biological information as single-nucleus RNA-sequencing (snRNA-seq) remains uncertain and likely to be context-dependent. Herein, a head-to-head comparison was performed in matched normal-adenocarcinoma human lung samples to assess biological insights derived from scRNA-seq versus snRNA-seq and better understand the cellular transition that occurs from normal to tumoral tissue. Here, the transcriptome of 160,621 cells/nuclei was obtained. In non-tumor lung, cell type proportions varied widely between scRNA-seq and snRNA-seq with a predominance of immune cells in the former (81.5%) and epithelial cells (69.9%) in the later. Similar results were observed in adenocarcinomas, in addition to an overall increase in cell type heterogeneity and a greater prevalence of copy number variants in cells of epithelial origin, which suggests malignant assignment. The cell type transition that occurs from normal lung tissue to adenocarcinoma was not always concordant whether cells or nuclei were examined. As expected, large differential expression of the whole-cell and nuclear transcriptome was observed, but cell-type specific changes of paired normal and tumor lung samples revealed a set of common genes in the cells and nuclei involved in cancer-related pathways. In addition, we showed that the ligand-receptor interactome landscape of lung adenocarcinoma was largely different whether cells or nuclei were evaluated. Immune cell depletion in fresh specimens partly mitigated the difference in cell type composition observed between cells and nuclei. However, the extra manipulations affected cell viability and amplified the transcriptional signatures associated with stress responses. In conclusion, research applications focussing on mapping the immune landscape of lung adenocarcinoma benefit from scRNA-seq in fresh samples, whereas snRNA-seq of frozen samples provide a low-cost alternative to profile more epithelial and cancer cells, and yield cell type proportions that more closely match tissue content.

Death associated protein kinase 1 predicts the prognosis and the immunotherapy response of various cancers.

BACKGROUND: Death Associated Protein Kinase 1 (DAPK1) is a calcium/calmodulin-dependent serine/threonine kinase, which has been reported to be a tumor suppressor with unbalanced expression in various tissues. However, its function in tumor immunotherapy is still unclear. METHODS: The online GEPIA2 database was used to support TCGA results. We explored the DAPK1 pan-cancer genomic alteration analysis using the cBioPortal web tool. The Human Protein Atlas (HPA) was employed to mine DAPK1 protein information. We verified the expression of DAPK1 in lung adenocarcinoma samples using RT-qPCR. Subsequently, the relationship between the expression of DAPK1 and the clinical stage was analyzed. We used TIMER2.0 as the primary platform for studying DAPK1-related immune cell infiltration. Associations between DAPK1 and immunotherapy biomarkers were analyzed using Spearman correlation analysis. TMB and MSI expression was also examined. Finally, we used Kaplan-Meier Plots to evaluate the relationship between DAPK1 expression and the efficacy of immunotherapy. RESULTS: DAPK1 is aberrantly expressed in most cancer types and has prognostic power in various cancers. Gene mutation was the most common DAPK1 alteration across pan-cancers. The DAPK1 protein was mainly localized to tumor cell centrosomes. DAPK1 was also significantly associated with immune-activated hallmarks, immune cell infiltration, and the expression of immunomodulators. Notably, DAPK1 can also significantly predict responses to anti-PD1 and anti-CTLA-4 therapy in cancer patients. CONCLUSIONS: Our findings suggest that DAPK1 may not only be an effective prognostic factor in cancer patients but may also function as a promising predictive immunotherapy biomarker for cancer patients treated with immune checkpoint inhibitors.

Associations between immune cell phenotypes and lung cancer subtypes: insights from mendelian randomization analysis.

INTRODUCTION: Lung cancer is a common malignant tumor, and different types of immune cells may have different effects on the occurrence and development of lung cancer subtypes, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). However, the causal relationship between immune phenotype and lung cancer is still unclear. METHODS: This study utilized a comprehensive dataset containing 731 immune phenotypes from the European Bioinformatics Institute (EBI) to evaluate the potential causal relationship between immune phenotypes and LUSC and LUAD using the inverse variance weighted (IVW) method in Mendelian randomization (MR). Sensitivity analyses, including MR-Egger intercept, Cochran Q test, and others, were conducted for the robustness of the results. The study results were further validated through meta-analysis using data from the Transdisciplinary Research Into Cancer of the Lung (TRICL) data. Additionally, confounding factors were excluded to ensure the robustness of the findings. RESULTS: Among the final selection of 729 immune cell phenotypes, three immune phenotypes exhibited statistically significant effects with LUSC. CD28 expression on resting CD4 regulatory T cells (OR 1.0980, 95% CI: 1.0627-1.1344, p < 0.0001) and CD45RA + CD28- CD8 + T cell %T cell (OR 1.0011, 95% CI: 1.0007; 1.0015, p < 0.0001) were associated with increased susceptibility to LUSC. Conversely, CCR2 expression on monocytes (OR 0.9399, 95% CI: 0.9177-0.9625, p < 0.0001) was correlated with a decreased risk of LUSC. However, no significant causal relationships were established between any immune cell phenotypes and LUAD. CONCLUSION: This study demonstrates that specific immune cell types are associated with the risk of LUSC but not with LUAD. While these findings are derived solely from European populations, they still provide clues for a deeper understanding of the immunological mechanisms underlying lung cancer and may offer new directions for future therapeutic strategies and preventive measures.

NGEF is a potential prognostic biomarker and could serve as an indicator for immunotherapy and chemotherapy in lung adenocarcinoma.

BACKGROUND: Neuronal guanine nucleotide exchange factor (NGEF) plays a key role in several cancers; however, its role in lung adenocarcinoma (LUAD) remains unclear. The aim of this study was to evaluate the efficacy of NGEF as a prognostic biomarker and potential therapeutic target for LUAD. METHODS: NGEF expression data for multiple cancers and LUAD were downloaded from multiple databases. The high- and low-NGEF expression groups were constructed based on median NGEF expression in LUAD samples, and then performed Kaplan-Meier survival analysis. Differentially expressed genes (DEGs) from the two NGEF expression groups were screened and applied to construct a protein-protein interaction network. The primary pathways were obtained using gene set enrichment analysis. The associations between NGEF expression and clinical characteristics, immune infiltration, immune checkpoint inhibitors (ICIs), sensitivity to chemotherapy, and tumor mutation burden (TMB) were investigated using R. Levels of NGEF expression in the lung tissue was validated using single-cell RNA sequencing, quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blot analysis. RESULTS: The expression of NGEF mRNA was upregulated in multiple cancers. mRNA and protein expression levels of NGEF were higher in patients with LUAD than in controls, as validated using qPCR and western blot. High NGEF expression was an independent prognostic factor for LUAD and was associated with advanced tumor stage, large tumor size, more lymph node metastasis, and worse overall survival (OS). A total of 182 overlapping DEGs were screened between The Cancer Genome Atlas and GSE31210, among which the top 20 hub genes were identified. NGEF expression was mainly enriched in the pathways of apoptosis, cell cycle, and DNA replication. Moreover, elevated NGEF expression were associated with a high fraction of activated memory CD4+ T cells and M0 macrophages; elevated expression levels of the ICIs: programmed cell death 1 and programmed cell death 1 ligand 1 expression; higher TMB; and better sensitivity to bortezomib, docetaxel, paclitaxel, and parthenolide, but less sensitivity to axitinib and metformin. CONCLUSION: NGEF expression is upregulated in LUAD and is significantly associated with tumor stages, OS probability, immune infiltration, immunotherapy response, and chemotherapy response. NGEF may be a potential diagnostic and prognostic biomarker and therapeutic target in LUAD.

Down-regulation of KLRB1 is associated with increased cell growth, metastasis, poor prognosis, as well as a dysfunctional immune microenvironment in LUAD.

Killer cell lectin-like receptor B1 (KLRB1) is implicated in cancer progression and immunity. In this study, we aimed to evaluate the expression levels of KLRB1 in lung adenocarcinoma (LUAD) and analyze the relationship between KLRB1 expression levels, LUAD progression, and the tumor immune microenvironment. KLRB1 levels in LUAD were analyzed using data from the TCGA and XENA databases. Additionally, the diagnostic values of KLRB1 were analyzed in patients with LUAD. Survival and meta-analyses were employed to investigate the relationship between KLRB1 levels and other prognostic factors in patients with LUAD. Bioinformatics and cellular experiments were used to understand the functions and mechanisms of KLRB1. In addition, correlation analysis was used to investigate the relationship between KLRB1 levels and the immune microenvironment in LUAD. Reduced KLRB1 expression in LUAD was found to positively correlate with tumor size, distant metastasis, pathological stage, age, overall survival, diagnostic value, and disease-specific survival in patients with LUAD (P < 0.05). Conversely, increased KLRB1 expression was found to positively correlate with the overall survival and disease-specific survival in patients with LUAD (P < 0.05). We also found that the overexpression of KLRB1 can inhibit the proliferation, migration, and invasion of LUAD cells and promote apoptosis. KLRB1 was involved in immune cell differentiation, NF-kB, PD-L1, and PD-1 checkpoint pathways and others. Additionally, KLRB1 expression was linked to tumor purity, stromal, immune, and estimate scores, the levels of immune cells including B cells, CD8+ T cells, and CD4+ T cells, and immune cell markers in LUAD. Reduced KLRB1 expression has a significant positive correlation with diagnosis, poor prognosis, and immunity to cancer in patients with LUAD. KLRB1 inhibited cell proliferation and migration in patients with LUAD. These results suggest that KLRB1 may serve as a potential therapeutic target in patients with LUAD.

Comprehensive molecular analyses of cuproptosis-related genes with regard to prognosis, immune landscape, and response to immune checkpoint blockers in lung adenocarcinoma.

BACKGROUND: Recent studies have emphasized the importance of the biological processes of different forms of cell death in tumor heterogeneity and anti-tumor immunity. Nonetheless, the relationship between cuproptosis and lung adenocarcinoma (LUAD) remains largely unexplored. METHODS: Data for 793 LUAD samples and 59 normal lung tissues obtained from TCGA-LUAD cohort GEO datasets were used in this study. A total of 165 LUAD tissue samples and paired normal lung tissue samples obtained from our hospital were used to verify the prognostic value of dihydrolipoamide S-acetyltransferase (DLAT) and dihydrolipoamide branched chain transacylase E2 (DBT) for LUAD. The cuproptosis-related molecular patterns of LUAD were identified using consensus molecular clustering. Recursive feature elimination with random forest and a tenfold cross-validation method was applied to construct the cuproptosis score (CPS) for LUAD. RESULTS: Bioinformatic and immunohistochemistry (IHC) analyses revealed that 13 core genes of cuproptosis were all significantly elevated in LUAD tissues, among which DBT and DLAT were associated with poor prognosis (DLAT, HR = 6.103; DBT, HR = 4.985). Based on the expression pattern of the 13 genes, two distinct cuproptosis-related patterns have been observed in LUAD: cluster 2 which has a relatively higher level of cuproptosis was characterized by immunological ignorance; conversely, cluster 1 which has a relatively lower level of cuproptosis is characterized by TILs infiltration and anti-tumor response. Finally, a scoring scheme termed the CPS was established to quantify the cuproptosis-related pattern and predict the prognosis and the response to immune checkpoint blockers of each individual patient with LUAD. CONCLUSION: Cuproptosis was found to influence tumor microenvironment (TME) characteristics and heterogeneity in LUAD. Patients with a lower CPS had a relatively better prognosis, more abundant immune infiltration in the TME, and an enhanced response to immune checkpoint inhibitors.

Single-cell sequencing of tumour infiltrating T cells efficiently identifies tumour-specific T cell receptors based on the T cell activation score.

Adoptively transferred T cell receptor-engineered T cells are a promising cancer treatment strategy, and the identification of tumour-specific TCRs is essential. Previous studies reported that tumour-reactive T cells and TCRs could be isolated based on the expression of activation markers. However, since T cells with different cell states could not respond uniformly to activation but show a heterogeneous expression profile of activation and effector molecules, isolation of tumour-reactive T cells based on single activation or effector molecules could result in the absence of tumour-reactive T cells; thus, combinations of multiple activation and effector molecules could improve the efficiency of isolating tumour-specific TCRs. We enrolled two patients with lung adenocarcinoma and obtained their tumour infiltrating lymphocytes (TILs) and autologous tumour cells (ATCs). TILs were cocultured with the corresponding ATCs for 12 h and subjected to single-cell RNA sequencing. First, we identified three TCRs with the highest expression levels of IFNG and TNFRSF9 mRNA for each patient, yet only the top one or two recognized the corresponding ATCs in each patient. Next, we defined the activation score based on normalized expression levels of IFNG, IL2, TNF, IL2RA, CD69, TNFRSF9, GZMB, GZMA, GZMK, and PRF1 mRNA for each T cell and then identified three TCRs with the highest activation score for each patient. We found that all three TCRs in each patient could specifically identify corresponding ATCs. In conclusion, we established an efficient approach to isolate tumour-reactive TCRs based on combinations of multiple activation and effector molecules through single-cell RNA sequencing.

An exosomes-related lncRNA prognostic model correlates with the immune microenvironment and therapy response in lung adenocarcinoma.

Recent research highlights the significance of exosomes and long noncoding RNAs (lncRNAs) in cancer progression and drug resistance, but their role in lung adenocarcinoma (LUAD) is not fully understood. We analyzed 121 exosome-related (ER) mRNAs from the ExoBCD database, along with mRNA and lncRNA expression profiles of TCGA-LUAD using "DESeq2", "survival," "ConsensusClusterPlus," "GSVA," "estimate," "glmnet," "clusterProfiler," "rms," and "pRRophetic" R packages. This comprehensive approach included univariate cox regression, unsupervised consensus clustering, GSEA, functional enrichment analysis, and prognostic model construction. Our study identified 134 differentially expressed ER-lncRNAs, with 19 linked to LUAD prognosis. These ER-lncRNAs delineated two patient subtypes, one with poorer outcomes. Additionally, 286 differentially expressed genes were related to these ER-lncRNAs, 261 of which also correlated with LUAD prognosis. We constructed an ER-lncRNA-related prognostic model and calculated an ER-lncRNA-related risk score (ERS), revealing that a higher ERS correlates with poor overall survival in both the Meta cohort and two validation cohorts. The ERS potentially serves as an independent prognostic factor, and the prognostic model demonstrates superior predictive power. Notably, significant differences in the immune landscape were observed between the high- and low-ERS groups. Drug sensitivity analysis indicated varying responses to common chemotherapy drugs based on ERS stratification, with the high-ERS group showing greater sensitivity, except to rapamycin and erlotinib. Experimental validation confirmed that thymidine kinase 1 enhances lung cancer invasion, metastasis, and cell cycle progression. Our study pioneers an ER-lncRNA-related prognostic model for LUAD, proposing that ERS-based risk stratification could inform personalized treatment strategies to improve patient outcomes.

Prediction of prognosis and immunotherapy efficacy based on metabolic landscape in lung adenocarcinoma by bulk, single-cell RNA sequencing and Mendelian randomization analyses.

Immunotherapy has been a remarkable clinical advancement in cancer treatment, but only a few patients benefit from it. Metabolic reprogramming is tightly associated with immunotherapy efficacy and clinical outcomes. However, comprehensively analyzing their relationship is still lacking in lung adenocarcinoma (LUAD). Herein, we evaluated 84 metabolic pathways in TCGA-LUAD by ssGSEA. A matrix of metabolic pathway pairs was generated and a metabolic pathway-pair score (MPPS) model was established by univariable, LASSO, multivariable Cox regression analyses. The differences of metabolic reprogramming, tumor microenvironment (TME), tumor mutation burden and drug sensitivity in different MPPS groups were further explored. WGCNA and 117 machine learning algorithms were performed to identify MPPS-related genes. Single-cell RNA sequencing and in vitro experiments were used to explore the role of C1QTNF6 on TME. The results showed MPPS model accurately predicted prognosis and immunotherapy efficacy of LUAD patients regardless of sequencing platforms. High-MPPS group had worse prognosis, immunotherapy efficacy and lower immune cells infiltration, immune-related genes expression and cancer-immunity cycle scores than low-MPPS group. Seven MPPS-related genes were identified, of which C1QTNF6 was mainly expressed in fibroblasts. High C1QTNF6 expression in fibroblasts was associated with more infiltration of M2 macrophage, Treg cells and less infiltration of NK cells, memory CD8+ T cells. In vitro experiments validated silencing C1QTNF6 in fibroblasts could inhibit M2 macrophage polarization and migration. The study depicted the metabolic landscape of LUAD and constructed a MPPS model to accurately predict prognosis and immunotherapy efficacy. C1QTNF6 was a promising target to regulate M2 macrophage polarization and migration.

Inflammation-based lung adenocarcinoma molecular subtype identification and construction of an inflammation-related signature with bulk and single-cell RNA-seq data.

The role of inflammation is increasingly understood to have a central influence on therapeutic outcomes and prognosis in lung adenocarcinoma (LUAD). However, the detailed molecular divisions involved in inflammatory responses are yet to be fully elucidated. Our study identified two main inflammation-oriented LUAD grades: the inflammation-low (INF-low) and the inflammation-high (INF-high) subtypes. Both presented with unique clinicopathological features, implications for prognosis, and distinctive tumor microenvironment profiles. Broadly, the INF-low grade, marked by its dominant immunosuppressive tumor microenvironment, was accompanied by less favorable prognostic outcomes and a heightened prevalence of oncogenic mutations. In contrast, the INF-high grade exhibited more optimistic clinical trajectories, underscored by its immune-active environment. In addition, our efforts led to the conceptualization and empirical validation of an inflammation-centric predictive model with considerable predictive potency. Our study paves the way for a refined inflammation-centric LUAD classification and fosters a deeper understanding of tumor microenvironment intricacies.

Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most invasive malignant tumor of the respiratory system. It is also the common pathological type leading to the death of LUAD. Maintaining the homeostasis of immune cells is an important way for anti-tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied. METHODS: We constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis-related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10-gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)-LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1-year, 3-year, and 5-year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high-risk group and low-risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10-gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis. CONCLUSION: We identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. The reliability of the prediction model was confirmed at bioinformatics level, cellular level, and gene level.

Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.

Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing "danger signals" to stimulate the body's immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.