Microenvironment Analysis of Prognosis and Molecular Signature of Immune-Related Genes in Lung Adenocarcinoma

There is growing evidence on the clinical significance of tumor microenvironment (TME) cells in predicting prognosis and therapeutic effects. However, cell interactions in tumor microenvironments have not been thoroughly studied or systematically analyzed so far. In this study, 22 immune cell components in the lung adenocarcinoma (LUAD) TME were analyzed using gene expression profile from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The TME-based molecular subtypes of LUAD were defined to evaluate further the relationship between molecular subtypes, prognosis, and clinical characteristics. A TME risk score model was constructed by using the differentially expressed genes (DEGs) of molecular subtypes. The relationship between the TME score and clinical characteristics and genomic mutations was compared to identify the genes that have significant associations with the TME. The comprehensive analysis of the TME characteristics may be helpful in revealing the response of LUAD patients to immunotherapy, providing a new strategy for immunotherapy.Key words: Tumor microenvironment, Lung adenocarcinoma, The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Immunotherapy     

肺腺癌中免疫治疗相关氧化应激基因表达的临床意义及其与免疫细胞浸润和药物敏感性的关系

目的：探究肺腺癌中与免疫治疗相关氧化应激基因（IROSG）及其与肿瘤组织免疫浸润和患者预后的关系。方法：从TCGA数据库和GEO数据库下载肺腺癌患者IROSG表达数据及相关临床信息。对非小细胞肺癌免疫治疗队列进行差异基因表达分析以获取免疫治疗相关基因,然后与从GeneCards数据库筛选的氧化应激相关基因取交集得到IROSG。基于得到的IROSG对肺腺癌患者进行分型,对亚型的差异表达基因进行单因素COX、LASSO和多因素COX回归分析以构建预后模型。使用模型公式计算每个患者的风险评分,并将患者划分为高、低风险组。从多个层面验证模型的预测效能,并进行肿瘤微环境（TME）分析、免疫治疗反应预测和药物敏感性分析。结果：通过数据库分析获取82个IROSG,IROSG高表达的肺腺癌患者预后较好（P<0.05）。基于IROSG表达水平分型和风险评分构建的肺腺癌患者预后模型预测能力好,基于风险评分和病例特征等预后因子构建的列线图和校正曲线能较好地预测肺腺癌患者的总生存率。低风险组主要富集于同种异体移植物排斥和自身免疫性疾病等通路,而高风险组主要富集在细胞周期和DNA复制等通路上,且低风险组肺...     

Tumor microenvironment characterization identifies two lung adenocarcinoma subtypes with specific immune and metabolic state

The tumor microenvironment (TME) is a vital component of tumor tissue. Increasing evidence suggests their significance in predicting outcomes and guiding therapies. However, no studies have reported a systematic analysis of the clinicopathologic significance of TME in lung adenocarcinoma (LUAD). Here, we inferred tumor stromal cells in 1184 LUAD patients using computational algorithms based on bulk tumor expression data, and evaluated the clinicopathologic significance of stromal cells. We found LUAD patients showed heterogeneous abundance in stromal cells. Infiltration of stromal cells was influenced by clinicopathologic features, such as age, gender, smoking, and TNM stage. By clustering stromal cells, we identified 2 clinically and molecularly distinct LUAD subtypes with immune active and immune repressed features. The immune active subtype is characterized by repressed metabolism and repressed proliferation of tumor cells, while the immune repressed subtype is characterized by active metabolism and active proliferation of tumor cells. Differentially expressed gene analysis of the two LUAD subtypes identified an immune activation signature. To diagnose TME subtypes practically, we constructed a TME score using principal component analysis based on the immune activation signature. The TME score predicted TME subtypes effectively in 3 independent datasets with areas under the receiver operating characteristic curves of 0.960, 0.812, and 0.819, respectively. In conclusion, we proposed 2 clinically and molecularly distinct LUAD subtypes based on tumor microenvironment that could be valuable in predicting clinical outcome and guiding immunotherapy.     

Pyroptosis impacts the prognosis and treatment response in gastric cancer via immune system modulation

Pyroptosis plays a vital role in the development of cancers; however, its role in regulating immune cell infiltration in tumor microenvironment (TME) and pyroptosis-related molecular subtypes remain unclear. Herein, we comprehensively analyzed the molecular subtypes mediated by the pyroptosis-related genes (PRGs) in gastric cancer (GC). Three pyroptosis patterns were determined with distinct TME cell-infiltrating characteristics and prognosis. Principal component analysis was performed to establish the pyroptosis score. The high pyroptosis score group was featured by increased activated CD4+ T cell infiltration, better prognosis, elevated tumor mutation burden, higher immune and stromal scores, and enhanced response to immunotherapy. However, the low pyroptosis score group was characterized by poorer survival, decreased immune infiltration, and glycerolipid and histidine metabolism pathways. Additionally, high pyroptosis score was confirmed as an independent favorable prognostic factor for overall survival. Three cohorts designed to analyze the response to immunotherapy verified that patients with higher pyroptosis score showed treatment benefit. In summary, our study demonstrated that pyroptosis regulates the complex TME. Assessing the pyroptosis patterns will advance our understanding on TME features and tumor immunology and provide the rationale for designing personalized immunotherapy strategies.     

Evaluating prognostic value and relevant gene signatures of tumor microenvironment characterization in esophageal carcinoma

BackgroundTumor microenvironment (TME) cells are an important part of tumor tissues. There is increasing evidence that the TME plays a vital role in tumor prognosis, and is associated with patient survival in various kinds of malignances. To date, very little research has been conducted on how to effectively use TME to better evaluate the prognosis of patients with esophageal carcinoma (EC). The concept of a “TME score” was introduced to better distinguish the prognosis of patients.MethodsWe employed bioinformatic methods to investigate the TME infiltration patterns of 160 patients with EC from the Cancer Genome Atlas (TCGA) cohort. TME clusters were identified using k-means clustering methods with 1,000 resampling times. The significance of the survival difference among patients belonging to different TME clusters was assessed by the log-rank test and Kaplan-Meier survival curves. Correlations between immune cell types and survival were calculated by a Cox regression, and the Pearson correlation coefficient (PCC) was used to measure the relationship among different immune cell types. We classified patient into 2 subtypes based on the optimal breakpoint of TME score determined by R package maxstat.ResultsTwo TME phenotypes were defined based on the immune cell type fractions, and patients with a high TME score phenotype had a better prognosis than those with a low TME score phenotype. Kaplan-Meier analysis for differentially expressed micro ribonucleic acids (RNAs) and messenger RNAs also showed that different TME score subtypes were significantly associated with the prognosis of EC. Just as tumor mutational burden can predict the efficacy of immunotherapy, the TME score can predict the efficacy of immune checkpoint inhibitors (ICIs). The genomic alterations of 2 TME score subtypes of EC further revealed that genomic instability is prevalent in TMEs, and patients with a low TME score subtype have a more unstable chromosome status than those with a high subtype.ConclusionsThus, TME score is an emerging prognostic biomarker for predicting the efficacy of ICIs.     

Constructing novel molecular subtypes and an 11-gene signature based on pyroptosis signaling for lung adenocarcinoma

Pyroptosis plays important roles in various cancers. In this study, we focused on lung adenocarcinoma (LUAD) and aimed to develop new molecular subtypes based on pyroptosis signaling. Pyroptosis-related genes were used as a basis to classify molecular subtypes through unsupervised consensus clustering. Gene set enrichment analysis was performed to characterize tumor microenvironment (TME) and functional pathways. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify prognostic genes for establishing a prognostic model. Three molecular subtypes were established with distinct overall survival, TME and enriched pathways. C3 subtype had the longest survival and the highest immune infiltration. 11 prognostic genes were screened to build a prognostic signature for predicting LUAD prognosis. This study emphasized the important role of pyroptosis in LUAD development. Pyroptosis was considered to play critical roles in regulating TME. Moreover, the 11-gene signature could serve as an indicator for predicting LUAD prognosis, and was potential targets for developing targeted drugs.     

Profiles of immune infiltration in the tumor microenvironment of hepatocellular carcinoma

BackgroundThus far, few studies have systematically analyzed the profiles of immune cells infiltrated in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC). Therefore, the purpose of our study was to comprehensively analyze the 22 tumor-infiltrating immune cells (TIICs) and the immune subtypes of HCC, as well as the factors associated with the prognosis of HCC patients.MethodsIn this study, we evaluated the abundance of 22 tumor-infiltrating immunocytes of 371 HCC patients from The Cancer Genome Atlas (TCGA) database by using the CIBERSORT algorithm, and defined immune subtypes of HCC according to unsupervised cluster analysis. The immune score of HCC patients was calculated by the prognostic regression model, while the survival analysis was evaluated by the Kaplan-Meier method. In addition, the consistency index of TIICs and principal component analysis (PCA) of immunomodulator genes were estimated.ResultsThe results of this study showed that three distinct immune subtypes of HCC were stratified, and the C1 subtype and C3 subtype were correlated with a good prognosis. The cellular composition of three immune subtypes was different. Moreover, immunomodulator gene and programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) expression in the C1 subtype was significantly higher (P<0.05).ConclusionsThis suggested that the low immune score of HCC patients is associated with better clinical outcomes. In addition, the interaction network of cluster of differentiation CD8+ T cells was mainly concentrated in the C1 subtype. Taken together, this study showed that tumor-infiltrating immune cells can perhaps be an important determinant of clinical outcomes of patients with HCC and may provide biomarkers to reflect the immunotherapy response. Notably, the C1 subtype of HCC may be used as an important predictive factor for immunotherapy response.     

N6-methyladenosine (m6A) regulatory gene divides hepatocellular carcinoma into three subtypes

BackgroundThe N6-methyladenosine (m6A) plays an important role in epigenetic modification and tumor progression, but the modulations of m6A in hepatocellular carcinoma (HCC) have not been determined while the relationship between m6A regulation and immune cell infiltration remains unclear.MethodsThis study investigated the modification patterns of m6A by analyzing HCC samples from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset, and performed molecular typing based on the characteristics of immune cell infiltration. The m6Ascore was also constructed to quantify m6A modifications and predict the immunotherapy response and prognosis of HCC patients.ResultsOf the 364 samples, 31 (8.52%) were genetically altered in the m6A regulatory gene, with the highest frequency of mutations in HNRNPC, ZC3H13, and LRPPRC. Three distinct molecular subtypes of m6A were identified in 590 HCC samples, which were associated with different immune cell infiltrates: immunodepletion type, immune activation type, and immune immunity type. According to the construction of the m6Ascore system in the m6A genotype, HCC patients could be divided into high and low groups. The m6A modified pattern, characterized by immune immunity and immune failure, showed a lower score and a better prognosis. However, the immune-activated type of m6A had a higher score and a poorer prognosis. Further analysis showed that the m6Ascore was correlated with tumor mutation burden (TMB), and the higher the TMB, the worse the prognosis. m6Ascore was also correlated with the expression of cytotoxic T-lymphocyte-associated protein 4 (CTAL-4), and the higher the score, the higher the expression of HCC in patients.ConclusionsHCC has a unique m6A modification pattern, and 3 different m6A subtypes help to classify HCC, provide knowledge of drug regimens for immunotherapy, and can be used to predict treatment response and prognosis.     

嘌呤能受体X1与肺腺癌预后及免疫细胞浸润的相关性研究

目的：探索嘌呤能受体X1(purinergic receptor，P2RX1)与肺腺癌(LUAD)患者预后及免疫细胞浸润的相关性。方法：利用生物信息学技术分析非小细胞肺癌中P2RX1的表达及其甲基化与患者预后的关系，对P2RX1共表达基因进行富集分析并筛选核心基因。利用TIMER 2.0数据库、R软件等分析P2RX1与免疫细胞、免疫检查点、免疫基质评分等的相关性。结果：P2RX1在LUAD中表达下调，低表达P2RX1的患者预后较差(P<0.05)，且P2RX1与肿瘤纯度、分期等临床病理因素有关(P<0.05)。P2RX1的表达与肺鳞癌患者预后无明显相关。Cg06475633等P2RX1 CpG位点甲基化与患者预后相关。P2RX1共表达基因主要富集于免疫细胞活化、分化等通路和生物学进程，核心基因主要包括BTK、IKZF1等。P2RX1的表达与B细胞浸润、免疫/基质评分、PD-1、CTLA-4等多个免疫检查点显著相关(P<0.05)。结论：P2RX1有望成为LUAD诊断和免疫治疗的新靶点。     

结直肠癌免疫微环境中肿瘤相关巨噬细胞的作用

结直肠癌（colorectal cancer,CRC）的发生、发展不仅与肿瘤细胞本身的特性相关,也与肿瘤微环境（tumor microenvironment,TME）密切相关。肿瘤细胞及其微环境通过分泌多种细胞因子,将循环血液中的单核细胞招募至TME并使其极化为肿瘤相关巨噬细胞（tumor-associated macrophages,TAMs）。作为TME中最丰富的免疫细胞之一,TAMs的功能和特点与M2型巨噬细胞相似,TAMs主要具有刺激肿瘤细胞增殖、血管生成、基质重塑和促进肿瘤细胞侵袭及转移等作用。在多数肿瘤中,TAMs主要发挥促肿瘤作用并与患者的不良预后相关;但在CRC中,TAMs的作用仍存争议。本文主要就CRC免疫微环境中TAMs的作用及其机制进行综述,以展示TAMs对CRC患者的病程进展及预后的影响并探讨TAMs作为CRC免疫治疗靶点的可行性。      

Molecular subtypes based on CNVs related gene signatures identify candidate prognostic biomarkers in lung adenocarcinoma

The classical factors for predicting prognosis currently cannot meet the developing requirements of individualized and accurate prognostic evaluation in lung adenocarcinoma (LUAD). With the rapid development of high-throughput DNA sequencing technologies, genomic changes have been discovered. These sequencing data provide unprecedented opportunities for identifying cancer molecular subtypes. In this article, we classified LUAD into two distinct molecular subtypes (Cluster 1 and Cluster 2) based on Copy Number Variations (CNVs) and mRNA expression data from the Cancer Genome Atlas (TCGA) based on non-negative matrix factorization. Patients in Cluster 1 had worse outcomes than that in Cluster 2. Molecular features in subtypes were assessed to explain this phenomenon by analyzing differential expression genes expression pattern, which involved in cellular processes and environmental information processing. Analysis of immune cell populations suggested different distributions of CD4+ T cells, CD8+ T cells, and dendritic cells in the two subtypes. Subsequently, two novel genes, TROAP and RASGRF1, were discovered to be prognostic biomarkers in TCGA, which were confirmed in {"type":"entrez-geo","attrs":{"text":"GSE31210","term_id":"31210"}}GSE31210 and Tianjin Medical University Cancer Institute and Hospital LUAD cohorts. We further proved their crucial roles in cancers by vitro experiments. TROAP mediates tumor cell proliferation, cycle, invasion, and migration, not apoptosis. RASGRF1 has a significant effect on tumor microenvironment. In conclusion, our study provides a novel insight into molecular classification based on CNVs related genes in LUAD, which may contribute to identify new molecular subtypes and target genes.     

Analysis of the tumor microenvironment and mutation burden identifies prognostic features in thymic epithelial tumors

Thymic epithelial tumors (TETs) are one of the rarest adult malignancies in the anterior mediastinum. Thymic carcinomas (TCs) are less prevalent among TETs, but they are more clinically aggressive. Immunotherapy has emerged as a promising therapeutic approach for refractory TETs, even though chemotherapy remains the conventional treatment for the advanced disease. However, limited attention has been paid to the features of the tumor microenvironment (TME) which might provide clinically relevant information and guide treatment regimen design. Especially, to date, there have been only a few studies focusing on the differences between the TME and genomic features preserved by TETs and TCs. We analyzed the TME and genomic characteristics of TETs using RNA sequencing and whole-exome sequencing, finding that distinct characteristics of TME in different pathogenic subtypes of TETs. According to those findings, we found that thymic carcinomas had significantly lower expression of HMGB1, a pro-inflammatory cytokine-related gene, than thymomas, and low HMGB1 expression was linked to a poor prognosis. Additionally, higher mutation burdens were significantly associated with the later stage and more advanced pathological types. Thymoma patients with lower mutation burdens tended to relapse within 3 years. In summary, different characteristics of TME and genomic features between thymoma and thymic carcinoma were associated with clinical outcomes of TETs and presented promisingly predictive value for efficacy and toxicity of immunotherapy.     

TCGA database analysis of the tumor mutation burden and its clinical significance in colon cancer

BackgroundColon cancer is one of the most common malignant tumors, with high rates of incidence and death. The tumor mutational burden (TMB), which is characterized by microsatellite instability, has been becoming a powerful predictor which can show tumor behavior and response to immunotherapy.MethodsIn this study, we analyzed 437 mutation data of colon cancer samples obtained from The Cancer Genome Atlas (TCGA) and divided patients into low- and high-TMB groups according to the TMB value. Then we identified differentially-expressed genes (DEGs), conducted immune cell infiltration and survival analyses between groups.ResultsThe higher TMB of the patients with colon cancer predicts a poorer prognosis. Functional analysis was performed to assess the prognostic value of the top 30 core genes. The CIBER-SORT algorithm was used to investigate the correlation between the immune cells and TMB subtypes. An immune prognosis model was constructed to screen out immune genes related to prognosis, and the tumor immunity assessment resource (TIMER) was then used to determine the correlation between gene expression and the abundance of tumor-infiltrating immune cell subsets in colon cancer. We observed that APC, TP53, TTN, KRAS, MUC16, SYNE1, PIK3CA have higher somatic mutations. DEGs enrichment analysis showed that they are involved in the regulation of neuroactive ligand-receptor interaction, the Cyclic adenosine monophosphate (cAMP) signaling pathway, the calcium signaling pathway, and pantothenate and Coenzyme A (CoA) biosynthesis. The difference in the abundance of various white blood cell subtypes showed that Cluster of Differentiation 8 (CD8) T cells (P=0.008), activated CD4 memory T cells (P=0.019), M1 macrophages (P=0.002), follicular helper T cells (P=0.034), activated Natural killer (NK cell) cells (P=0.017) increased remarkably, while M0 macrophages significantly reduced (P=0.025). The two immune model genes showed that secretin (SCT) was negatively correlated with survival, while Guanylate cyclase activator 2A (GUCA2A) was positively correlated.ConclusionsThis study conducted a systematically comprehensive analysis of the prediction and clinical significance of TMB in colon cancer in identification, monitoring, and prognosis of colon cancer, and providing reference information for immunotherapy.     

The spatial distribution of immune cell subpopulations in hepatocellular carcinoma

Infiltrating immune cells in the tumor microenvironment (TME) influence tumor progression and patient prognosis, making them attractive therapeutic targets for immunotherapy research. A deeper understanding of immune cell distributions in the TME in hepatocellular carcinoma (HCC) is needed to identify interactions among different immune cell types that might impact the effectiveness of potential immunotherapies. We performed multiplex immunohistochemistry using a tissue microarray of samples from 302 patients with HCC to elucidate the spatial distributions of immune cell subpopulations (CD3⁺, CD4⁺, CD8⁺, CD66b⁺, and CD68⁺) in HCC and normal liver tissues. We analyzed the associations between different immune subpopulations using Pearson''s correlation. G(r) functions, K(r) functions and Euclidean distance were applied to characterize the bivariate distribution patterns among the immune cell types. Cox regression and Kaplan‐Meier analysis were used to evaluate the associations between tumor infiltration by different immune cells and patient outcomes after curative surgery. We also analyzed the relationship between the spatial distribution of different immune cell subpopulations with HCC patient prognosis. We found that the immune cell spatial distribution in the HCC TME is heterogeneous. Our study provides a theoretical basis for HCC immunotherapy.     

Identification of Novel CD74-NRG2α Fusion From Comprehensive Profiling of Lung Adenocarcinoma in Japanese Never or Light Smokers

IntroductionStudies are yet to characterize the differences in molecular profiles of lung adenocarcinoma (LUAD) among divergent ethnic groups. Herein, we conducted comprehensive molecular profiling of LUAD in never or light smokers from Asia to discover novel targetable mutations and prognostic biomarkers of this distinct disease entity.MethodsWe analyzed 996 cases of Japanese LUAD and performed whole-exome sequencing and RNA-seq in 125 cases of Japanese LUAD negative for the driver oncogenes defined by conventional laboratory testing. We also investigated the clinical and pathologic characteristics among the 996 cases.ResultsDriver oncogenes were identified in 88 cases (70.4%) with specific hotspot mutations differing from those in The Cancer Genome Atlas study. Two actionable novel fusions of FGFR2 and NRG2α were also identified. Clustering on the basis of mRNA expression profiles, but not genetic mutational ones, could predict patient prognosis. The risk score generated by the expression of a three-gene set was a strong prognostic marker for overall survival and progression-free survival in our cohort, and was further validated using The Cancer Genome Atlas cohort. Among the 996 cases, each driver alteration is distributed across all histologic subtypes. Adenocarcinoma in situ was identified to harbor driver mutations, suggesting that these alterations are early events in the pathogenesis of LUAD. ERBB2 mutations were over-represented in young adults.ConclusionsThis study indicates the value of applying gene expression profiling for predicting the prognosis after a surgical operation, and that the identification of actionable mutations is important for optimizing targeted drugs in Japanese LUAD.     

CDHR2在肺腺癌中的表达及其与预后的关系

目的探讨CDHR2在肺腺癌(LUAD)组织中的表达及其与临床病理特征和预后的关系,并分析CDHR2与LUAD肿瘤免疫浸润的关系。方法挖掘TCGA、GEPIA数据库中CDHR2在LUAD中的表达及与预后的关系;免疫组织化学染色检测83例LUAD患者的癌组织及癌旁正常组织中CDHR2的表达情况,并分析其与患者临床病理特征及无病生存期(DFS)的关系。通过TIMER和CIBERSORT数据库分析CDHR2与LUAD肿瘤免疫浸润水平之间的关系。结果 TCGA数据集中515例LUAD组织的CDHR2表达水平显著高于59例癌旁正常组织(P<0.05)。GEPIA数据库发现CDHR2高表达与较差的总生存期(OS)有关(P<0.05)。免疫组化显示CDHR2蛋白在LUAD组织中的高表达率为66.3%(55/83),高于癌旁组织的37.3%(31/83),差异有统计学意义(P<0.05)。CDHR2蛋白表达与TNM分期有关(P<0.05)。CDHR2蛋白高表达患者的中位DFS为44.6(95%CI:39.5～49.7)个月,短于低表达患者的57.3(95%CI:49.9～64.8...     

胃肠道间质肿瘤：微环境特点及免疫治疗思路

胃肠道间质肿瘤(GIST)是胃肠道最常见的间充质来源的肿瘤,对放化疗敏感性低。近二十年来,以伊马替尼为代表的酪氨酸激酶抑制剂类药物在很大程度上改善了GIST患者的预后,但仍有相当数量的患者出现原发或继发性耐药,因此需要开拓新的治疗方法。随着肿瘤免疫治疗的基础与临床研究的进展,越来越多的肿瘤患者从免疫治疗中获益。但是,免疫治疗在GIST中的应用却较为缓慢。目前,免疫检查点抑制剂治疗在GIST中的应用取得了初步进展,未来还需要有更多的循证证据。在发展迅速的免疫细胞疗法和肿瘤疫苗领域,目前尚无相关新技术用于GIST的临床研究。尽管如此,GIST的免疫微环境具有丰富的免疫细胞浸润,提示GIST是潜在的免疫治疗优势病种。但是,免疫治疗在GIST中的应用不能“照搬”上皮来源肿瘤的特征,必须在充分了解GIST免疫特征的基础上,进行针对性研究,开发出基于GIST的免疫治疗策略,才能使免疫治疗真正改善患者的预后。