Tumor Microenvironment Of Lung Adenocarcinoma Research Articles

Histopathological Correlation Between High Endothelial Venule Neogenesis and the Tumor Microenvironment in Lung Adenocarcinoma.

The dynamic interplay between cancer cells and the microenvironment involves a wide range of intricate relationships that evolve during different stages of tumor progression. Recent attention has focused on high endothelial venules (HEVs), specialized endothelial cells in tumors with a unique cuboidal shape similar to those in lymph nodes. Previous animal studies have shown that normalization of tumor angiogenesis through anti-VEGFR2 therapy promotes HEV formation. However, few reports exist regarding the relationship between HEVs and preexisting blood vessels or interstitial fibers. In this study, we histologically examined whether tumor vascular structure correlates with HEV neogenesis. A total of 109 patients with pathological stage I lung adenocarcinoma who had undergone curative lung resection at our Institute between 2012 and 2016 were included. HEVs were identified by anti-peripheral node addressin (PNAd) staining. Immunostaining and Elastica-Masson-Goldner staining were performed on tumor sections and quantified. PNAd-positive cells were identified in 102 (93.6%) patients. Nearly all PNAd-positive cells were located within or near immune cell clusters. We investigated the correlation between microvessel structures or interstitial fibers and the number/density of PNAd-positive vessels, but no significant correlation was found. Since PNAd-positive cells were concentrated in immune cell aggregates, we focused our analysis specifically on these regions. Immune cell aggregates with abundant PNAd-positive vessels had a greater microvessel density along with by rich collagen fiber production, and displayed a more mature morphological phenotype of HEVs. The generation of PNAd-positive cells in tumors is governed by an angiogenetic mechanism distinct from that of broader tumor microenvironment. Furthermore, the accumulation of immune cells is associated with increased HEV maturation.

SOX17 expression in tumor-penetrating vessels in relation to CD8+ T-cell infiltration in cancer stroma niches.

Sex-determining region Y-related high-mobility group box 17 protein (SOX17), a proangiogenic transcription factor, is specifically expressed in tumor endothelial cells (TECs) of implanted Lewis lung carcinoma. However, the expression profile of SOX17 is largely unknown in human lung cancer. We aimed to elucidate SOX17 expression in cancer cells and the tumor microenvironment of lung adenocarcinoma. In the present study, we examined SOX17 expression in whole-tissue specimens of 83 lung adenocarcinomas by immunohistochemistry. SOX17 immunoreactivity was minimal in lung adenocarcinoma cells, except in five non-mucinous adenocarcinomas in situ. SOX17 was also expressed in cultured A549 lung adenocarcinoma cells, which is widely used as a model of malignant alveolar type II epithelial cells. Notably, SOX17 immunoreactivity was found in endothelial cells of tumor-penetrating vessels in 19 of 83 lung adenocarcinoma tissue specimens, with statistical significance to stromal infiltration of CD8+ T cells (p < 0.01) but was not associated with the number of tertiary lymph nodes. Although not statistically significant, SOX17 immunoreactivity was related to favorable patient outcomes. Our findings indicate that SOX17 might play a pleiotropic role in lung adenocarcinoma in cancer cells and stromal niches. SOX17-mediated CD8+ T-cell-rich tumor microenvironment might attract interest in improving the effect of cancer immunotherapy.

Construction of a mitophagy-related prognostic signature for predicting prognosis and tumor microenvironment in lung adenocarcinoma

BackgroundMitophagy is the selective degradation of mitochondria by autophagy. It becomes increasingly clear that mitophagy pathways are important for cancer cells to adapt to their high-energy needs. However, which genes associated with mitophagy could be used to prognosis cancer is unknown. MethodsWe created a clinical prognostic model using mitophagy-related genes (MRGs) in lung adenocarcinoma (LUAD) patients for the first time, and we employed bioinformatics methods to search for biomarkers that affect the progression and prognosis of LUAD. Transcriptome data for LUAD were obtained from The Cancer Genome Atlas (TCGA) database, and additional expression data from LUAD patients were sourced from the Gene Expression Omnibus (GEO) database. Furthermore, 25 complete MRGs were identified based on annotations from the MSigDB database. ResultsA comparison of the mitophagy scores between the groups with high and low scores was done using receiver operating characteristic (ROC) curves, which also revealed the differential gene expression patterns between the two groups. Using Kaplan-Meier analysis, two prognostic MRGs from the groups with high and low mitophagy scores were identified: TOMM40 and VDAC1. Using univariate and multivariate Cox regression, the relationship between the expression levels of these two genes and prognostic clinical features of LUAD was examined further.The prognosis of LUAD patients was shown to be significantly correlated (P < 0.05) with the expression levels of these two genes. ConclusionsOur prognostic model would improve the prognosis of LUAD and guide clinical treatments.

Identification of KRT80 as a Novel Prognostic and Predictive Biomarker of Human Lung Adenocarcinoma via Bioinformatics Approaches.

According to the 2022 Global Cancer Statistics, lung cancer is the leading cause of cancer-related mortality worldwide. Lung adenocarcinoma (LUAD), which is a histological subtype of Non- Small Cell Lung Cancer (NSCLC), accounts for 40% of primary lung cancer. Therefore, there is an urgent need to identify new prognostic markers as clinical predictive markers for LUAD. This study aimed to investigate the role of Keratin 80 (KRT80) in the prognosis of LUAD and its underlying mechanisms. Bioinformatics analysis was conducted using data retrieved from The Cancer Genome Atlas (TCGA) databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were employed to predict the involved biological processes and signaling pathways, respectively. The LinkedOmics database was utilized to identify differentially expressed genes (DEGs) correlated with KRT80. Nomograms and Kaplan-Meier plots were constructed to evaluate the survival outcomes of patients diagnosed with LUAD. Moreover, TIMER was employed to conduct correlation analyses between KRT80 expression and immune cell infiltration, shedding light on the intricate interplay between KRT80 and the tumor microenvironment in LUAD. To ascertain the RNA and protein expression levels of KRT80 in LUAD and adjacent normal tissues, Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) and immunohistochemistry techniques were employed, respectively. Scrutiny of the TCGA dataset revealed KRT80 up-regulation across pan-cancer tissues, notably elevated in LUAD compared to healthy lung tissues. This finding was validated in our clinical samples, where Kaplan-Meier survival curves indicated poorer survival rates for high KRT80 expression in LUAD. A positive correlation was found between the transcription level of KRT80 in LUAD samples and clinical parameters, such as lymph node metastasis stage, distant metastasis, and pathological stage. Survival, logistic regression, and Cox regression analyses emphasized the clinical prognostic significance of high KRT80 expression in LUAD. Nomogram results underscored the robust predictive potential of KRT80 for the survival of LUAD patients. Gene functional enrichment analyses mainly associated KRT80 with cytokine-cytokine receptor interactions, cell cycle, apoptosis, and chemokine signaling pathways. Based on the results of the immune infiltration analysis, it can be found that the expression of KRT80 is related to the immune cell subsets and survival rate of patients with LUAD. Our research revealed a significant upregulation of KRT80 in LUAD, with heightened KRT80 expression correlating with unfavorable prognosis. This study represents a comprehensive and systematic evaluation of KRT80 expression in LUAD, encompassing its prognostic and diagnostic significance, as well as underlying mechanisms. Our findings suggest that KRT80 may emerge as a novel prognostic and predictive biomarker in LUAD.

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.

Exploring the role of UMP as a molecular marker in the tumor microenvironment of lung adenocarcinoma.

e20064 Background: Currently, there is a relatively extensive research emphasis on tumor microenvironment based on single-cell transcriptomics. However, the investigation of the metabolic aspects of tumor microenvironment is relatively rare due to technological limitations. To address this gap, our study employes scFEA and MEBOCOST, which are metabolic level prediction tools based on single-cell transcriptomics, to explore the metabolic landscape of tumor microenvironment in lung adenocarcinoma(LUAD). Methods: This study utilized four single-cell sequencing (scRNA-seq) datasets, two targeted metabolomics datasets, and the TCGA-LUAD RNA sequencing dataset obtained from the Cancer Genomics Data Portal. To perform dimensionality reduction, the Seurat package was employed. Cell annotation was carried out using scType, followed by manual correction using the FindAllMarkers function. Tumor cell clusters were identified by utilizing tumor marker genes and the R package inferCNV. Single-cell metabolic levels were inferred using scFEA. The TCGA-LUAD datasets underwent analysis to estimate and analyze immune levels using estimate and cibersort algorithms. Additionally, scFEA was used for metabolic level analysis, and survival analysis was conducted. UMP differential expression analysis was performed on the targeted metabolomics datasets. Results: Across all four single-cell sequence datasets, metabolites such as (GlcNAc)4 (Man)3 (Asn)1[G00015], B-Alanine[C00099], and UMP[C00105] exhibited significantly higher levels in immune cells compared to tumor cells (P &lt; 0.05). These findings were further validated using the TCGA-LUAD datasets. Cox regression analysis was performed using immune scores and tumor purity scores and based on the median value of risk scores, high and low-risk groups were distinguished. it was observed that UMP levels were higher in the low-risk group. Moreover, higher UMP levels were associated with elevated immune levels and decreased tumor purity. Analysis of targeted metabolomics datasets from various pan-cancer cell lines revealed that UMP expression level in tumor cells was lower than that in B and T cells. Furthermore, in different subtypes of LUAD, including AAH, AIS, MIA, and IAC, UMP expression in tissues gradually decreased as the severity of the subtype increased (P &lt; 0.05). Conclusions: The study revealed that UMP metabolites are expressed at higher levels in immune cells compared to tumor cells within LUAD. Moreover, UMP expression levels showed significant variations among different disease severities of LUAD. These findings indicate that UMP has the potential to serve as a molecular marker for distinguishing between different disease severities. Further research is needed to investigate the underlying mechanisms and validate the diagnostic usefulness of UMP in LUAD.

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

AbstractBackgroundImmune 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.MethodsBy 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.ResultsLUAD 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.ConclusionsThese 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.

Knockdown of heat shock protein family D member 1 (HSPD1) in lung cancer cell altered secretome profile and cancer-associated fibroblast induction

The crosstalk between lung cancer cells and cancer-associated fibroblast (CAF) is pivotal in cancer progression. Heat shock protein family D member 1 (HSPD1) is a potential prognostic biomarker associated with the tumor microenvironment in lung adenocarcinoma (LUAD). However, the role of HSPD1 in CAF activation remains unclear. This study established stable HSPD1-knockdown A549 lung cancer cells using a lentivirus-mediated shRNA transduction. A targeted label-free proteomic analysis identified six significantly altered secretory proteins in the shHSPD1-A549 secretome compared to shControl-A549. Functional enrichment analysis highlighted their involvement in cell-to-cell communication and immune responses within the tumor microenvironment. Additionally, most altered proteins exhibited positive correlations and significant prognostic impacts on LUAD patient survival. Investigations on the effects of lung cancer secretomes on lung fibroblast WI-38 cells revealed that the shControl-A549 secretome stimulated fibroblast proliferation, migration, and CAF marker expression. These effects were reversed upon the knockdown of HSPD1 in A549 cells. Altogether, our findings illustrate the role of HSPD1 in mediating CAF induction through secretory proteins, potentially contributing to the progression and aggressiveness of lung cancer.

Analysis of cancer-associated fibroblasts related genes identifies COL11A1 associated with lung adenocarcinoma prognosis

BackgroundThe treatment of lung adenocarcinoma is difficult due to the limited therapeutic options. Cancer-associated fibroblasts play an important role in the development of cancers. This study aimed to identify a promising molecular target associated with cancer-associated fibroblasts for the treatment of lung adenocarcinoma.MethodsThe Cancer Genome Atlas lung adenocarcinoma dataset was used to screen hub genes associated with cancer-associated fibroblasts via the EPIC algorithm and Weighted Gene Co-expression Network Analysis. Multiple databases were used together with our data to verify the differential expression and survival of COL11A1. Functional enrichment analysis and the single-cell TISCH database were used to elucidate the mechanisms underlying COL11A1 expression. The correlation between COL11A1 and immune checkpoint genes in human cancers was also evaluated.ResultsUsing the EPIC algorithm and Weighted Gene Co-expression Network Analysis, 13 hub genes associated with cancer-associated fibroblasts in lung adenocarcinoma were screened. Using the GEPIA database, Kaplan-Meier Plotter database, GSE72094, GSE75037, GSE32863, and our immunohistochemistry experiment data, we confirmed that COL11A1 overexpresses in lung adenocarcinoma and that high expression of COL11A1 is associated with a poor prognosis. COL11A1 has a genetic alteration frequency of 22% in patients with lung adenocarcinoma. COL11A1 is involved in the extracellular matrix activities of lung adenocarcinoma. Using the TISCH database, we found that COL11A1 is mainly expressed by cancer-associated fibroblasts in the tumor microenvironment rather than by lung adenocarcinoma cells. Finally, we found that COL11A1 is positively correlated with HAVCR2(TIM3), CD274 (PD-L1), CTLA4, and LAG3 in lung adenocarcinoma.ConclusionCOL11A1 may be expressed and secreted by cancer-associated fibroblasts, and a high expression of COL11A1 may result in T cell exhaustion in the tumor microenvironment of lung adenocarcinoma. COL11A1 may serve as an attractive biomarker to provide new insights into cancer therapeutics.

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

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). 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. 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. 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.

Identification of CNKSR1 as a biomarker for “cold” tumor microenvironment in lung adenocarcinoma: An integrative analysis based on a novel workflow

BackgroundTherapies targeting PD1/PD-L1 pathway have revolutionized the treatment of lung cancer. However, anti-PD1/PD-L1 therapies have proven beneficial for only a select group of lung adenocarcinoma (LUAD) patients and generally do not work for immuno-cold tumors characterized by a lack of immune cell infiltration. Identifying novel biomarkers is vital to broad therapeutic options for LUAD patients with no response to anti-PD1/PD-L1 immunotherapies. MethodsOur study has developed a novel strategy to identify a promising biomarker that addresses the limitations of anti-PD1/PD-L1 immunotherapy in treating immunological cold tumors. We exacted LUAD RNA-seq data from the Cancer Genome Atlas database (TCGA). Using several machine learning methods, we identified the candidate biomarker. Based on the expression level of PD-L1 and the identified biomarker, samples were categorized into four groups. We further used ESTIMATE, ssGSEA, and CIBERSORT algorithms to calculate the immune infiltration level of each group. The results were validated in three independent bulk datasets and one scRNA-seq dataset. Immunohistochemistry (IHC) assessments were performed in clinical samples to further evaluate the coexpression of CNKSR1 and PD-L1, and to compare CD8 + T cell infiltration among groups. ResultsAfter comprehensive analyses, CNKSR1 was identified as a novel promising biomarker for immuno-cold LUAD. CNKSR1 mRNA expression levels exhibited a negative correlation with both PD-L1 mRNA expression and the extent of immune cell infiltration in LUAD. Besides, in contrast to the significant association between the expression of PD-L1 and the majority of other well-established or widely studied immune checkpoint molecules, a mutually exclusive expression pattern is observed between CNKSR1 and these molecules. The aforementioned results were consistent in validation datasets. The prognostic model built based on the CNKSR1 coexpression module also showed robust predictive performance. Additionally, IHC assessments have confirmed that the coexpression of CNKSR1 and PD-L1 is rare in LUAD samples. Notably, LUADs in the high-CNKSR1 group, characterized by high CNKSR1 but low PD- L1 expression, demonstrated reduced infiltration of CD8+ T cells. ConclusionsIn summary, CNKSR1 emerges as a promising biomarker for immune-cold LUADs, and the study into CNKSR1 modulating T-cell infiltration may lead to the identification of compensatory molecules to enhance the effectiveness of current immunotherapy for LUAD.

Heterogeneity of Lipid Metabolism and its Clinical and Immune Correlation in Lung Adenocarcinoma.

The role of lipid metabolism in lung adenocarcinoma (LUAD) is not completely researched. Lipid metabolism reprogramming is a characteristic of malignancies and contributes to carcinogenesis and progression. The transcriptome and scRNA- seq data and clinical information were downloaded from the public databases. Lipid metabolism pathways were collected from the MSigDB database, and molecular subtypes were classified based on lipid metabolism features via consensus clustering. The bidirectional crosstalk between immune cells and malignant cells was analyzed. Differences in lipid metabolism at the single-cell level and their correlation with the tumor microenvironment (TME) were also studied. LUAD patients were classified into two subtypes, showing distinct mutation and lipid metabolism features based on lipid metabolism characteristics. Meanwhile, significant differences in the overall survival, clinical characteristics, and immune landscape were observed between the two subtypes. We also found that clust1 had higher oxidative stress status. There were 116 differentially expressed genes between the two subtypes, which were significantly associated with cell cycle progression. We identified 4001 immune cells, including 483 malignant cells and 3518 normal cells, and found active intercellular communication and significant differences in lipid metabolism characteristics between the malignant cells and normal cells. Furthermore, several lipid metabolism pathways were found to be associated with TME factors, including hypoxia and angiogenesis. The current findings indicated that lipid metabolism was involved in the development and cellular heterogeneity of LUAD and revealed widespread reprogramming across multiple cellular elements in the TME of LUAD. This characterization improved the current understanding of tumor biology and enabled the identification of novel targets for immunotherapy.

Abstract 171: Chemotherapeutic agent, cisplatin, influences the proportion of TREM2 (+) M2 macrophages in the TME of LUAD

Abstract Background: Triggering receptor expressed on myeloid cells (TREM2) serves as an immune signaling hub that senses and interacts with a wide range of ligands arising from damaged tissues in pathologic conditions. Despite TREM2’s diverse role in casting immune suppressive environment, the effects of chemotherapy on tumor microenvironment (TME), TREM2 and their interactions are not well established. In this study, we aimed to investigate the characteristics of TREM2 (+) Mφ within the lung TME (Tu), focusing on the impact of chemotherapy on the immune dynamics of lung adenocarcinoma (LUAD). Method: Changes in the number and distribution of Mφ subclusters in normal appearing lung tissue (NL) and Tu were examined using open-source single cell RNA sequencing (scRNA-seq) datasets and immunofluorescent staining of lung cancer-induced Kras-G12D mouse tissue. Clinical measures affecting the expression of TREM2 were explored using the TCGA-LUAD and -LUSC datasets, and the effects of anticancer drugs and the apoptotic cells on Mφ were observed by differentiating THP1 cells into M0, M1, and M2. Results: scRNA-seq analysis on LUAD datasets showed that Mφ were the second most abundant cell population that constitutes the lung TME, and the proportion of Mφ in the Tu decreases compared to NL. Among the Mφ subclusters in Tu, a subcluster which specifically increased in Tu shows enrichment of apoptotic cell clearance gene sets, including TREM2. In lung cancer induced Kras-G12D mouse, compared to NL the Tu has an increase in M2 proportion, showing the characteristics of interstitial Mφ in addition with overexpression of TREM2 and enrichment of monocyte chemotaxis gene set enrichment. Among TCGA-LUAD, the high TMB group has low TREM2 expression, and the proportion of TREM2 (+) M2 in the Tu decreases in cisplatin-treated Kras-G12D mouse Tu, suggesting the expression of TREM2 in M2 is suppressed by either cisplatin treatment itself or active immunity in Tu. Additionally, we are going to observe the effect on TREM2 expression by adding cisplatin treated A549-GFP cells or cisplatin alone, to the THP-1 cells that were differentiated into M0, M1, or M2 state. Conclusion: In addition to changes in the lung immune environment due to the tumor, anticancer treatment changes in the characteristics of M2 in TME, in terms of decrease in TREM2 (+) Mφ fraction. Considering that TREM2 plays a central inhibitory role in the tumor immune environment, the effect of anticancer chemotherapeutic agents should be considered in the development TREM2 targeting agents. Citation Format: Yoon Jin Cha, Min Kyung Park, Yoon Soo Chang. Chemotherapeutic agent, cisplatin, influences the proportion of TREM2 (+) M2 macrophages in the TME of LUAD [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 171.

GPX8+ cancer-associated fibroblast, as a cancer-promoting factor in lung adenocarcinoma, is related to the immunosuppressive microenvironment

BackgroundCancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment of lung adenocarcinoma (LUAD) and are often associated with poorer clinical outcomes. This study aimed to screen for CAF-specific genes that could serve as promising therapeutic targets for LUAD.MethodsWe established a single-cell transcriptional profile of LUAD, focusing on genetic changes in fibroblasts. Next, we identified key genes associated with fibroblasts through weighted gene co-expression network analysis (WGCNA) and univariate Cox analysis. Then, we evaluated the relationship between glutathione peroxidase 8 (GPX8) and clinical features in multiple independent LUAD cohorts. Furthermore, we analyzed immune infiltration to shed light on the relationship between GPX8 immune microenvironment remodeling. For clinical treatment, we used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the immunotherapy prediction efficiency of GPX8. After that, we screened potential therapeutic drugs for LUAD by the connectivity map (cMAP). Finally, we conducted a cell trajectory analysis of GPX8+ CAFs to show their unique function.ResultsFibroblasts were found to be enriched in tumor tissues. Then we identified GPX8 as a key gene associated with CAFs through comprehensive bioinformatics analysis. Further analysis across multiple LUAD cohorts demonstrated the relationship between GPX8 and poor prognosis. Additionally, we found that GPX8 played a role in inducing the formation of an immunosuppressive microenvironment. The TIDE method indicated that patients with low GPX8 expression were more likely to be responsive to immunotherapy. Using the cMAP, we identified beta-CCP as a potential drug-related to GPX8. Finally, cell trajectory analysis provided insights into the dynamic process of GPX8+ CAFs formation.ConclusionsThis study elucidates the association between GPX8+ CAFs and poor prognosis, as well as the induction of immunosuppressive formation in LUAD. These findings suggest that targeting GPX8+ CAFs could potentially serve as a therapeutic strategy for the treatment of LUAD.

Abstract C116: Oncogenic Kras signaling shapes the tumor microenvironment in lung adenocarcinoma

Abstract Despite advancements in targeted therapy and immunotherapy, lung cancer remains the leading cause of cancer-related deaths in both men and women worldwide, with an estimated 2.2 million deaths each year. At 85%, non-small cell lung cancer (NSCLC) is by far the most common subtype, comprising adenocarcinomas and lung squamous cell carcinoma. Mutations in Kirsten rat sarcoma viral oncogene homolog (KRAS), epidermal growth factor receptor (EGFR) and anaplastic lymphoma receptor tyrosine kinase (ALK) genes are common, with the worst overall survival in KRAS mutant adenocarcinoma patients. About 40% of lung tumors with KRAS mutations also harbor mutations in tumor protein p53 gene (TP53), a tumor suppressor gene. KrasG12C and KrasG12D are both prevalent mutations in lung cancer. Sotorasib, a KrasG12C inhibitor, was recently approved for treatment of NSCLC. However, only 37% of patients have an objective response to Sotorasib, with a median duration of just 11 months. The KrasG12D inhibitor MRTX1133 is entering clinical trials; elucidating the mechanism of action and potential resistance is imperative to design combination treatment approaches. While cell-intrinsic mechanisms of resistance in epithelial oncogenic KRASG12D (Kras*) are well studied, our group and others have shown that KRASG12D also extrinsically regulates the tumor microenvironment (TME) in pancreatic cancer. Whether and how this oncogene regulates the TME of lung cancer is less understood. To study the crosstalk between epithelial lung cells expressing oncogenic KRAS and the surrounding TME, we have established a triple transgenic murine model of Kras*-driven NSCLC, wherein both lung epithelial-specific expression of Kras* and expression of mutant TP53R172H (Tp53*) can be controlled in an inducible and reversible manner. Our preliminary data show that expression of Kras* drives tumor growth, while Kras* depletion results in regression, even in the presence of Tp53*. Here we interrogate how Kras* modulates the TME in lung adenocarcinomas. Harnessing scRNA sequencing, immunohistochemistry, and multiple biochemical approaches, we will provide insight into changes in stromal and immune contexture upon Kras* depletion in mice. Citation Format: Rachael Baliira, Emily Lasse Opsahl, Ivana Barravecchia, Marina Pasca di Magliano, Stefanie Galban. Oncogenic Kras signaling shapes the tumor microenvironment in lung adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C116.

Identification and prognostic biomarkers among ZDHHC4/12/18/24, and APT2 in lung adenocarcinoma

S-palmitoylases and S-depalmitoylases are differentially expressed in various cancers and several malignant tumors and show a strong prognostic ability. Notwithstanding, the potential clinical impact of S-palmitoylases and S-depalmitoylases, particularly in the prognosis and progression of lung adenocarcinoma (LUAD), has not been clarified. Expression levels of S-palmitoylases and S-depalmitoylases in LUAD were investigated using TCGA. GEPIA was used to evaluate the mRNA levels of S-palmitoylases and S-depalmitoylases at different pathological stages. Metascape was used to investigate the biological significance of S-palmitoylases and S-depalmitoylases. The Kaplan–Meier plotter was used to analyze the prognostic value of S-palmitoylases and S-depalmitoylases. CBioportal was used to analyze gene alterations in S-palmitoylases and S-depalmitoylases. UALCAN was used to examine DNA promoter methylation levels of S-palmitoylases and S-depalmitoylases. Finally, we investigated the relationship between S-palmitoylases, S-depalmitoylases, and tumor-infiltrating immune cells using TIMER. Correlations with immune checkpoint-related genes were determined using the R packages reshape2, ggpubr, ggplot2, and corrplot. PCR was also performed to assess the degree of ZDHHC4/12/18/24 and APT2 transcript expression in lung adenocarcinoma and adjacent normal lung tissues. HPA was utilized to investigate protein levels of S-palmitoylases and S-depalmitoylases in LUAD and normal lung tissue. Our study found that ZDHHC2/3/4/5/6/7/9/12/13/16/18/20/21/23/24, APT1/2, PPT1, LYPLAL1, ABHD4/10/11/12/13 and ABHD17C mRNA expression was significantly upregulated in LUAD, whereas ZDHHC1/8/11/11B/14/15/17/19/22, ABHD6/16A and ABHD17A mRNA expression was significantly downregulated. The functions of the differentially expressed S-palmitoylases and S-depalmitoylases were mainly associated with protein-cysteine S-palmitoyltransferase and protein-cysteine S-acyltransferase activities. Patients with high expression of ZDHHC4/12/18/24, APT2, ABHD4, ABHD11 and ABHD12 had a shorter overall survival. Infiltration of six immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) was closely associated with the expression of ZDHHC4/12/18/24 and APT2. ZDHHC4/12/18/24 and APT2 positively correlated with the immune checkpoint-related gene CD276. We assessed the mRNA levels of ZDHHC4/12/18/24 and APT2 using qRT-PCR and found increased expression of ZDHHC4/12/18/24 in LUAD compared with healty control lung tissues. ZDHHC4/12/18/24, and APT2 are potential prognostic biomarkers of LUAD. Their expression levels could be related to the tumor microenvironment in LUAD.

Discovery of a novel ROS-based signature for predicting prognosis and immunosuppressive tumor microenvironment in lung adenocarcinoma.

The role of reactive oxygen species (ROS) is critical in the emergence and progression of lung adenocarcinoma (LUAD), affecting cell survival, proliferation, angiogenesis, and metastasis. Further investigations are needed to elucidate these effects' precise pathways and devise therapeutic approaches targeting ROS. Moreover, the expression pattern and clinical significance of the ROS-related genes in LUAD remain elusive. Through comprehensive analysis incorporating 1494 LUAD cases from The Cancer Genome Atlas, six Gene Expression Omnibus series, and a Chinese LUAD cohort, we identified a ROS-related signature with substantial predictive value in various LUAD patient cohorts. The ROS-related signature has demonstrated a significant negative relationship with antitumor immunity and dendritic cell maturation and activation. Moreover, The ROS-related signature showed predictive value on immunotherapy outcomes across multiple types of solid tumors, including LUAD. These findings reinforce the ROS-related signature as a predictive tool for LUAD and provide new insights into its link with antitumor immunity and immunotherapy efficacy. These results have implications for refining clinical assessments and tailoring immunotherapeutic strategies for patients with LUAD.

Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma

BackgroundThe extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response. MethodsGene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD. ResultsA risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity. ConclusionA novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.

Link between m6A modification and infiltration characterization of tumor microenvironment in lung adenocarcinoma.

N6-methyladenosine (m6A) RNA methylation plays a pivotal role in immune responses and the onset and advancement of cancer. Nonetheless, the precise impact of m6A modification in lung adenocarcinoma (LUAD) and its associated tumor microenvironment (TME) remains to be fully elucidated. Here, we distinguished distinct m6A modification patterns within two separate LUAD cohorts using a set of 21 m6A regulators. The TME characteristics associated with these two patterns align with the immune-inflamed and immune-excluded phenotypes, respectively. We identified 2064 m6A-related genes, which were used as a basis to divide all LUAD samples into three distinct m6A gene clusters. We applied a scoring system to evaluate the m6A gene signature of the m6A modification pattern in individual patients. To authenticate the categorization significance of m6A modification patterns, we established a correlation between m6A score and TME infiltration profiling, tumor somatic mutations, and responses to immunotherapy. A high level of m6A modification may be associated with the aggressiveness and poor prognosis of LUAD. Further studies should investigate the mechanism of action of m6A regulators and m6A-related genes to improve the diagnosis and treatment of patients with LUAD.

RUNX1 as a Potential Target for Combined Radioimmunotherapy of Lung Adenocarcinoma

Radioimmunotherapy for non-small cell lung cancer has good clinical application prospects. The role and mechanism of RUNX1 in DNA damage repair were explored for its potential role in lung adenocarcinoma radioimmunotherapy. To study the effect of RUNX1 expression level on the expression of DNA damage repair system related factors and radiation sensitivity of lung adenocarcinoma cells. As an important nuclear transcription factor, RUNX1 was explored whether directly regulating the expression of Nrf2, Rad51, BRCA1, and verifying their respective DNA binding sites in the promoter region through relevant databases. To observe the effect of RUNX1 knockout and overexpression on the expression level of PD-L1 in tumor cells at the cell level; The effect of RUNX1 expression level on the sorting and presentation of PD-L1 cells was investigated by the method of nucleocytoplasmic separation. According to literature reports, CMTM6 and ALIX play a key role in the process of PD-L1 cell sorting and presentation, and explore whether RUNX1 plays a role through this factor. The effect of phosphorylation level of different splicing bodies of RUNX1 (RUNX1a/b/c) on the expression level and DNA damage repair system related factors on tumor radiosensitivity were also explored. According to TCGA database, RUNX1 is highly expressed and phosphorylated in lung adenocarcinoma. Through gene comparison with the database, it was found that RUNX1 binding sites existed in the promoter region of several factors related to this study, including ALIX, Nrf2, BRCA1, RAD51, ATM, H2AX, etc. After being activated by MAPKp38 phosphorylation, RUNX1a can positively regulate Nrf2 signal pathway. The expression of RUNX1 and p-RUNX1 is time-dependent on ionizing radiation. At the same time, it was found that the expression of RUNX1 and p-RUNX1 was dose-dependent on ionizing radiation, and the expression trend of Nrf2 signal pathway related factors was consistent with RUNX1. RUNX1 regulates the expression of PD-L1, BRCA1, ALIX and Nrf2. Bioinformatics analysis and flow cytometry data show that RUNX1 has inhibitory effect on tumor microenvironment of lung adenocarcinoma. RUNX1 regulates DNA damage repair system and has inhibitory effect on tumor immunity. Inhibiting the expression of RUNX1 in lung adenocarcinoma cells can enhance the effect of radioimmunotherapy.