The paradoxical role of tumor-infiltrating immune cells in lung cancer

Integrative analyses of multi-omics data constructing tumor microenvironment and immune-related molecular prognosis model in human colorectal cancer

The increasing prevalence and incidence of colorectal cancer (CRC), particularly in young adults, underscore the imperative to comprehend its fundamental mechanisms, discover novel diagnostic and prognostic markers, and enhance therapeutic strategies. Here, we integrated multi-omics data, including gene expression, somatic mutation data and DNA methylation data, to unravel the intricacies of tumor microenvironment (TME) in CRC and search for novel prognostic markers. By calculating the immune score for each patient from the expression profile, we delineated the differential immune cell fraction, constructed an immune-related multi-omics atlas, and identified molecular characteristics. The entire colorectal dataset (n = 343) was randomly divided into training (n = 249) and testing datasets (n = 94). We screened 144 immune-related genes, 6 mutant genes, and 38 methylation probes associated with overall survival (OS). These makers were then incorporated into a 10-gene prognostic model using Lasso and Cox regression in the training dataset, and the model's performance was evaluated in an independent validation dataset. The model exhibited satisfactory results (average concordance index [C-index] = 0.77), with the average 1-year, 3-year, and 5-year AUCs being 0.79, 0.76, and 0.76 in the training dataset and 0.74, 0.80, and 0.90 in the testing dataset. Furthermore, the prognostic model demonstrated applicability in guiding chemotherapy for CRC patients and exhibited a degree of pan-cancer utility in risk stratification. In conclusion, our integrated analysis of multi-omics data revealed immune-related genetic and epigenetic characteristics of the TME. We propose an integrative prognostic model that can stratify risk and guide chemotherapy for CRC patients. The generalizability of the model in risk stratification across different cancer types was validated in Pan-Cancer cohort.

Comprehensive pan-cancer analysis of 33 human cancers reveals immunotherapeutic value of focal adhesion tyrosine kinase

The immune environment in tumors is the key factor affecting the survival and immunotherapeutic response of patients. This research aimed to explore the underlying association between focal adhesion tyrosine kinase (FAK/PTK2) and cancer immunotherapy in 33 human cancers. Gene expression data and clinical features of 33 cancers were retrieved from the Cancer Genome Atlas Database. The immunotherapy cohorts included GSE67501, GSE78220, and IMVIGOR210, which were derived from the comprehensive gene expression database or from previous studies. Clinical parameters including patient age, gender, survival rate, and tumor stage were analyzed to evaluate the prognostic value of FAK/PTK2. FAK/PTK2 activity was detected by single-sample gene set enrichment analysis and used to compare the difference between FAK/PTK2 transcriptome and protein expression levels. To better understand the role of FAK/PTK2 in cancer immunotherapy, we analyzed its correlations with tumor microenvironment and with immune processes/elements (e.g., immune cell infiltration, immunosuppressants, and stimulants) and major histocompatible complexes. Potential pathways associated with FAK/PTK2 signaling in cancers were also explored. Correlations between FAK/PTK2 and 2 immunotherapeutic biomarkers (tumor mutation load and microsatellite instability) were studied. Finally, the 3 independent immunotherapy cohorts were used to study the relationship between FAK/PTK2 and immunotherapeutic response. Although FAK/PTK2 is not closely associated with age (13/33), gender (5/33), or tumor stage (5/33) in any of the studied human cancers, it has potential prognostic value for predicting patient survival. Consistency between FAK/PTK2 activity and expression exists in some cancers (3/33). Generally, FAK/PTK2 is robustly correlated with immune cell infiltration, immune modulators, and immunotherapeutic markers. Moreover, high FAK/PTK2 expression is significantly related to immune-relevant pathways. However, FAK/PTK2 is not significantly correlated with the immunotherapeutic response. Research on the immunotherapeutic value of FAK/PTK2 in 33 human cancers provides evidence regarding the function of FAK/PTK2 and its role in clinical treatment. However, given the use of a bioinformatics approach, our results are preliminary and require further validation.

PLAU and GREM1 are prognostic biomarkers for predicting immune response in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common malignant tumor. Identification of biomarkers and understanding their potential functions will facilitate the treatment and diagnosis in LUAD patients. The yellow module (cor = 0.31, P = 2e-6) was selected as the core module based on weighted gene co-expression network analysis (WGCNA) by integrating RNA-seq data and tumor stage. Two upregulated genes (PLAU and GREM1) in yellow module were identified to be biomarkers. Kaplan-Meier curve analysis displayed that high expression levels of them had a poor overall survival (OS). And, their high expression levels revealed higher tumor stage and relapse possibility in LUAD patients, and could be a prognostic parameter. Both biomarkers showed similar immune cell expression profiles in low- and high-expression groups. Strongly positive correlation between both biomarkers and biomarkers of tumor-infiltrating lymphocytes were also clarified in TCGA-LUAD cohort. Importantly, single gene GSEA showed that transcriptional mis-regulation in cancer and microRNAs in cancer were enriched in LUAD patients. Therefore, a miRNA-mRNA-transcription factors (TFs) co-expression regulatory networks was constructed for each biomarker, various miRNAs and TFs were related to PLAU and GREM1. Among which, 6 downstream TFs were overlapped genes for both biomarkers. Notably, 2 of these TFs (FOXF1 and TFAP2A) exhibited significantly abnormal expression levels. Among which, FOXF1 was downregulated and TFAP2A was upregulated in TCGA-LUAD cohort. Both TFs showed a significantly positive correlation with the expression level of PLAU. In conclusion, we identified 2 biomarkers related to immune response and achieved a good accuracy in predicting OS in patients with LUAD.

NCPAD2 is a favorable predictor of prognostic and immunotherapeutic biomarker for multiple cancer types including lung cancer

BACKGROUND

Non-SMC condensin I complex subunit D2 (NCAPD2) belongs to the chromosomal structural maintenance family. While the different contribution of NCAPD2 to chromosome in mitosis have been thoroughly investigated, much less is known about the expression of NCAPD2 in pan-cancer. Thus, we used a bioinformatics dataset to conduct a pan-cancer analysis of NCAPD2 to determine its regulatory role in tumors.

METHODS

Multiple online databases were analyzed NCAPD2 gene expression, protein level, patient survival and functional enrichment in pan-cancer. Genetic alteration and tumor stemness of NCAPD2 were analyzed using cBioPortal and SangerBox. The GSCA and CellMiner were used to explore the relationship between NCAPD2 and drug sensitivity. The diagnostic value of prognosis was evaluated by ROC curve. Subsequently, the immune infiltration level and immune subtype of NCAPD2 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were analyzed using TIMER1 and TISIDB.

RESULTS

NCAPD2 gene expression was significantly higher in most cancers and associated with clinical stage and poor prognosis. Genomic heterogeneity of NCAPD2 promoted the occurrence and development of tumors. GO enrichment analysis suggested NCAPD2 might be involved in DNA repair and immune response. NCAPD2 was involved in immune infiltration of LUAD and LUSC. ROC curves showed that NCAPD2 has important prognosis diagnostic value in LUAD and LUSC. Moreover, NCAPD2 was drug sensitive to topotecan, which may be an optimize immunotherapy.

CONCLUSIONS

It was found that NCAPD2 was overexpressed in pan-cancers, which was associated with poor outcomes. Importantly, NCAPD2 could be a diagnostic marker and an immune related biomarker for LUAD and LUSC.

Immunological role and clinical prognostic significance of P2RY6 in lung adenocarcinoma: a multi-omics studies and single-cell sequencing analysis

BACKGROUND

There is increasing evidence that recombinant human P2Y purinoceptor 6 (P2RY6) may be involved in inflammatory responses. However, the role of P2RY6 in lung adenocarcinoma (LUAD) remains unknown.

METHODS

We used transcriptomic, genomic, single-cell transcriptomic, and methylation sequencing data from The Cancer Genome Atlas database to analyze the aberrant status and prognostic value of P2RY6 in a variety of tumors. The LUAD single-cell sequencing dataset was used to explore the effect of P2RY6 on the tumor microenvironment. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify immune cells in the tumor microenvironment. We also analyzed the correlation of P2RY6 with immune checkpoints and immune regulation-related genes. The correlation of between tumor mutation burden (TMB), microsatellite instability (MSI), and P2RY6 expression was also analyzed simultaneously. Tissue microarray and immunohistochemistry were employed to assess the expression of P2RY6 in internal tumor samples.

RESULTS

Our findings indicate that P2RY6 exhibits significantly higher expression levels in various cancer tissues, particularly in LUAD. High expression of P2RY6 was closely associated with a poor prognosis for patients, and it plays a role in regulating immune-related pathways, such as cytokine-cytokine receptor interaction. Notably, P2RY6 expression is closely linked to the abundance of CD8 + T cells. Furthermore, we have developed a P2RY6-related inflammation prediction model that demonstrates promising results in predicting the prognosis of LUAD patients, with an AUC (area under the curve) value of 0.83. This performance is significantly better than the traditional TNM staging system. Through single-cell transcriptome sequencing analysis, we observed that high P2RY6 expression is associated with increased intercellular communication. Additionally, pathway enrichment analysis revealed that P2RY6 influences antigen presentation and processing pathways within the LUAD microenvironment.

CONCLUSIONS

This study suggests that P2RY6 would be a new target for immunotherapy in LUAD.

Investigating the role of Kinesin family in lung adenocarcinoma via integrated bioinformatics approach

Lung cancer is the leading cause of mortality from cancer worldwide. Lung adenocarcinoma (LUAD) is a type of non-small cell lung cancer (NSCLC) with highest prevalence. Kinesins a class of motor proteins are shown to be involved in carcinogenesis. We conducted expression, stage plot and survival analyses on kinesin superfamily (KIF) and scrutinized the key prognostic kinesins. Genomic alterations of these kinesins were studied thereafter via cBioPortal. A protein-protein interaction network (PPIN) of selected kinesins and 50 closest altering genes was constructed followed by gene ontology (GO) term and pathway enrichment analyses. Multivariate survival analysis based on CpG methylation of selected kinesins was performed. Lastly, we conducted tumor immune infiltration analysis. Our results found KIF11/15/18B/20A/2C/4A/C1 to be significantly upregulated and correlated with poor survival in LUAD patients. These genes also showed to be highly associated with cell cycle. Out of our seven selected kinesins, KIFC1 showed the highest genomic alteration with highest number of CpG methylation. Also, CpG island (CGI) cg24827036 was discovered to be linked to LUAD prognosis. Therefore, we deduced that reducing the expression of KIFC1 could be a feasible treatment strategy and that it can be a wonderful individual prognostic biomarker. CGI cg24827036 can also be used as a therapy site in addition to being a great prognostic biomarker.

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

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

Differential Expression of AP-2 Transcription Factors Family in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma-A Bioinformatics Study

Members of the activator protein 2 (AP-2) transcription factor (TF) family are known to play a role in both physiological processes and cancer development. The family comprises five DNA-binding proteins encoded by the TFAP2A to TFAP2E genes. Numerous scientific reports describe differential expression of these TF and their genes in various types of cancer, identifying among them a potential oncogene or suppressor like TFAP2A or TFAP2C. Other reports suggest their influence on disease development and progression, as well as response to treatment. Not all members of this AP-2 family have been comprehensively studied thus far. The aim of the present article is to gather and discuss knowledge available in bioinformatics databases regarding all five members of this family and to differentiate them in relation to the two most common lung cancer subtypes: adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). In addition, to assess the difference in levels depending on a number of clinicopathological factors, the impact on patient survival and interactions with tumor-infiltrating immune cells. This article may help to identify the target for further original research that may contribute to the discovery of new diagnostic biomarkers and define the molecular differences between LUAD and LUSC, which may affect the therapy effectiveness improvement and longer survival.

Characterisation of tumour-immune phenotypes and PD-L1 positivity in squamous bladder cancer

AIMS

Immune checkpoint inhibitor (ICI) therapy has become a viable treatment strategy in bladder cancer. However, treatment responses vary, and improved biomarkers are needed. Crucially, the characteristics of immune cells remain understudied especially in squamous differentiated bladder cancer (sq-BLCA). Here, we quantitatively analysed the tumour-immune phenotypes of sq-BLCA and correlated them with PD-L1 expression and FGFR3 mutation status.

METHODS

Tissue microarrays (TMA) of n = 68 non-schistosomiasis associated pure squamous cell carcinoma (SCC) and n = 46 mixed urothelial carcinoma with squamous differentiation (MIX) were subjected to immunohistochemistry for CD3, CD4, CD8, CD56, CD68, CD79A, CD163, Ki67, perforin and chloroacetate esterase staining. Quantitative image evaluation was performed via digital image analysis.

RESULTS

Immune infiltration was generally higher in stroma than in tumour regions. B-cells (CD79A) were almost exclusively found in stromal areas (sTILs), T-lymphocytes and macrophages were also present in tumour cell areas (iTILs), while natural killer cells (CD56) were nearly missing in any area. Tumour-immune phenotype distribution differed depending on the immune cell subset, however, hot tumour-immune phenotypes (high density of immune cells in tumour areas) were frequently found for CD8 + T-cells (33%), especially perforin + lymphocytes (52.2%), and CD68 + macrophages (37.6%). Perforin + CD8 lymphocytes predicted improved overall survival in sq-BLCA while high PD-L1 expression (CPS ≥ 10) was significantly associated with higher CD3 + , CD8 + and CD163 + immune cell density and high Ki67 (density) of tumour cells. Furthermore, PD-L1 expression was positively associated with CD3 + /CD4 + , CD3 + /CD8 + and CD68 + /CD163 + hot tumour-immune phenotypes. FGFR3 mutation status was inversely associated with CD8 + , perforin + and CD79A + lymphocyte density.

CONCLUSIONS

Computer-based image analysis is an efficient tool to analyse immune topographies in squamous bladder cancer. Hot tumour-immune phenotypes with strong PD-L1 expression might pose a promising subgroup for clinically successful ICI therapy in squamous bladder cancer and warrant further investigation.

Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinoma

Lung cancer is one of the most common malignant tumors, and ranks high in the list of mortality due to cancers. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite progress in the diagnosis and treatment of lung cancer, the prognosis of these patients remains dismal. Therefore, it is crucial to identify the predictors and treatment targets of lung cancer to provide appropriate treatments and improve patient prognosis. In this study, the gene modules related to immunotherapy were screened by weighted gene co-expression network analysis (WGCNA). Using unsupervised clustering, patients in The Cancer Genome Atlas (TCGA) were divided into three clusters based on the gene expression. Next, gene clustering was performed on the prognosis-related differential genes, and a six-gene prognosis model (comprising PLK1, HMMR, ANLN, SLC2A1, SFTPB, and CYP4B1) was constructed using least absolute shrinkage and selection operator (LASSO) analysis. Patients with LUAD were divided into two groups: high-risk and low-risk. Significant differences were found in the survival, immune cell infiltration, Tumor mutational burden (TMB), immune checkpoints, and immune microenvironment between the high- and low-risk groups. Finally, the accuracy of the prognostic model was verified in the Gene Expression Omnibus (GEO) dataset in patients with LUAD (GSE30219, GSE31210, GSE50081, GSE72094).

Comprehensive analysis of somatic mutator-derived and immune infiltrates related lncRNA signatures of genome instability reveals potential prognostic biomarkers involved in non-small cell lung cancer

Background: The function and features of long non-coding RNAs (lncRNAs) are already attracting attention and extensive research on their role as biomarkers of prediction in lung cancer. However, the signatures that are both related to genomic instability (GI) and tumor immune microenvironment (TIME) have not yet been fully explored in previous studies of non-small cell lung cancer (NSCLC).

Method: The clinical characteristics, RNA expression profiles, and somatic mutation information of patients in this study came from The Cancer Genome Atlas (TCGA) database. Cox proportional hazards regression analysis was performed to construct genomic instability-related lncRNA signature (GIrLncSig). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the potential functions of lncRNAs. CIBERSORT was used to calculate the proportion of immune cells in NSCLC.

Result: Eleven genomic instability-related lncRNAs in NSCLC were identified, then we established a prognostic model with the GIrLncSig ground on the 11 lncRNAs. Through the computed GIrLncSig risk score, patients were divided into high-risk and low-risk groups. By plotting ROC curves, we found that patients in the low-risk group in the test set and TCGA set had longer overall survival than those in the high-risk group, thus validating the survival predictive power of GIrLncSig. By stratified analysis, there was still a significant difference in overall survival between high and low risk groups of patients after adjusting for other clinical characteristics, suggesting the prognostic significance of GIrLncSig is independent. In addition, combining GIrLncSig with TP53 could better predict clinical outcomes. Besides, the immune microenvironment differed significantly between the high-risk and the low-risk groups, patients with low risk scores tend to have upregulation of immune checkpoints and chemokines. Finally, we found that high-risk scores were associated with increased sensitivity to chemotherapy.

Conclusion: we provided a new perspective on lncRNAs related to GI and TIME and revealed the worth of them in immune infiltration and immunotherapeutic response. Besides, we found that the expression of AC027288.1 is associated with PD-1 expression, which may be a potential prognostic marker in immune checkpoint inhibitor response to improve the prediction of clinical survival in NSCLC patients.

DIRAS2 Is a Prognostic Biomarker and Linked With Immune Infiltrates in Melanoma

Background

Skin cutaneous melanoma (SKCM) is a highly malignant skin tumor. DIRAS2 is considered to be a tumor suppressor gene; however, its function in SKCM has not been explored.

Methods

The Gene Expression Profiling Interactive Analysis (GEPIA) was implemented to investigate the expression of DIRAS2 in SKCM, and plot the survival curve to determine the effect of DIRAS2 on the survival rates of SKCM patients. Then, the correlation between DIRAS2 and tumor immune infiltration was also discussed, and the expression of DIRAS2 and immune infiltration level in SKCM immune cells was determined using TIMER. The top 100 genes most associated with DIRAS2 expression were used for functional enrichment analysis. In order to confirm the anti-cancer effects of DIRAS2 in SKCM in the data analysis, in vitro assays as well as in vivo studies of DIRAS2 on SKCM tumor cell proliferation, migration, invasion, and metastasis were conducted. Western blot and immunofluorescence assay were employed to study the relationship between DIRAS2 and Wnt/β-catenin signaling pathway in SKCM.

Results

DIRAS2 expression was shown to be significantly correlated with tumor grade using univariate logistic regression analysis. DIRAS2 was found to be an independent prognostic factor for SKCM in multivariate analysis. Of note, DIRAS2 expression levels were positively correlated with the infiltration levels of B cells, CD4+ T cells, and CD8+ T cells in SKCM. The infiltration of B cells, CD4+ T cells, and CD8+ T cells was positively correlated with the cumulative survival rate of SKCM patients. In vitro experiments suggested that proliferation, migration, invasion, and metastasis of SKCM tumor cells were distinctly enhanced after DIRAS2 knockdown. Furthermore, DIRAS2 depletion promoted melanoma growth and metastasis in vivo. As for the mechanism, silencing DIRAS2 can activate the signal transduction of the Wnt/β-catenin signaling pathway.

Conclusion

DIRAS2 functions as a tumor suppressor gene in cases of SKCM by inhibiting the Wnt/β-catenin signaling. It is also associated with immune infiltration in SKCM.

[Research Status of Tumor-associated Fibroblasts Regulating Immune Cells]

Cancer-associated fibroblasts (CAFs) and tumor-infiltrating immune cells are the most essential components of the tumor microenvironment (TME). They communicate with each other in tumor microenvironment and play a critical role in tumorigenesis and development. CAFs are very heterogeneous and different subtypes of CAFs display different functions. At the same time, it can contribute to the regulation of the function of tumor-infiltrating immune cells and eventually result in the carcinogenesis, tumor progression, invasion, metastasis and other biological behaviors of tumors by producting various growth factors and cytokines etc. Based on the current research results at home and abroad, this paper reviews the recent research progress on the regulation of CAFs on infiltrating immune cells in tumor microenvironment.
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Nanomedicine Strategies for Management of Drug Resistance in Lung Cancer

Lung cancer (LC) is one of the leading causes of cancer occurrence and mortality worldwide. Treatment of patients with advanced and metastatic LC presents a significant challenge, as malignant cells use different mechanisms to resist chemotherapy. Drug resistance (DR) is a complex process that occurs due to a variety of genetic and acquired factors. Identifying the mechanisms underlying DR in LC patients and possible therapeutic alternatives for more efficient therapy is a central goal of LC research. Advances in nanotechnology resulted in the development of targeted and multifunctional nanoscale drug constructs. The possible modulation of the components of nanomedicine, their surface functionalization, and the encapsulation of various active therapeutics provide promising tools to bypass crucial biological barriers. These attributes enhance the delivery of multiple therapeutic agents directly to the tumor microenvironment (TME), resulting in reversal of LC resistance to anticancer treatment. This review provides a broad framework for understanding the different molecular mechanisms of DR in lung cancer, presents novel nanomedicine therapeutics aimed at improving the efficacy of treatment of various forms of resistant LC; outlines current challenges in using nanotechnology for reversing DR; and discusses the future directions for the clinical application of nanomedicine in the management of LC resistance.

Identification of tumor immune infiltration-associated lncRNAs for improving prognosis and immunotherapy response of patients with non-small cell lung cancer

BACKGROUND

Increasing evidence has demonstrated the functional relevance of long non-coding RNAs (lncRNAs) to immunity regulation and the tumor microenvironment in non-small cell lung cancer (NSCLC). However, tumor immune infiltration-associated lncRNAs and their value in improving clinical outcomes and immunotherapy remain largely unexplored.

METHODS

We developed a computational approach to identify an lncRNA signature (TILSig) as an indicator of immune cell infiltration in patients with NSCLC through integrative analysis for lncRNA, immune and clinical profiles of 115 immune cell lines, 187 NSCLC cell lines and 1533 patients with NSCLC. Then the influence of the TILSig on the prognosis and immunotherapy in NSCLC was comprehensively investigated.

RESULTS

Computational immune and lncRNA profiling analysis identified an lncRNA signature (TILSig) consisting of seven lncRNAs associated with tumor immune infiltration. The TILSig significantly stratified patients into the immune-cold group and immune-hot group in both training and validation cohorts. These immune-hot patients exhibit significantly improved survival outcome and greater immune cell infiltration compared with immune-cold patients. Multivariate analysis revealed that the TILSig is an independent predictive factor after adjusting for other clinical factors. Further analysis accounting for TILSig and immune checkpoint gene revealed that the TILSig has a discriminatory power in patients with similar expression levels of immune checkpoint genes and significantly prolonged survival was observed for patients with low TILSig and low immune checkpoint gene expression implying a better response to immune checkpoint inhibitor (ICI) immunotherapy.

CONCLUSIONS

Our finding demonstrated the importance and value of lncRNAs in evaluating the immune infiltrate of the tumor and highlighted the potential of lncRNA coupled with specific immune checkpoint factors as predictive biomarkers of ICI response to enable a more precise selection of patients.

Methylation Regulation of TLR3 on Immune Parameters in Lung Adenocarcinoma

This study aims to analyze the methylation regulation of TLR3 in lung adenocarcinoma (LUAD) and to explore the association of TLR3 expression with immune microenvironment. TLR3 has a decreased expression in LUAD tissues and low expression of TLR3 is not only associated with poor prognosis in patients with LUAD, but also can be used as a diagnostic marker. Bisulfite sequencing PCR (BSP) results showed that the methylation level in the promoter of TLR3 was negatively correlated with the level of TLR3 mRNA in LUAD tissues. TIMER analysis showed that TLR3 was negatively correlated with the tumor purity of LUAD and positively with immune cell infiltration to some extent. ESTIMATE analysis also suggested that TLR3 expression and its methylation had significant correlation with immune score. The lower immune scores were associated with the late stage of LUAD and poor prognosis. The high expression of TLR3 might inhibit the development of LUAD by activating apoptosis pathway. The proteins interacted with TLR3 were mainly involved in the apoptosis pathway and positively correlated with the key genes (MYD88, Caspase 8, BIRC3, PIK3R1) in this pathway. Therefore, TLR3 as a key biomarker for prognosis and diagnosis in LUAD, might be considered as a potential epigenetic and immunotherapeutic target.

NEIL3 may act as a potential prognostic biomarker for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death. This study aimed to develop and validate reliable prognostic biomarkers and signature.

METHODS

Differentially expressed genes were identified based on three Gene Expression Omnibus (GEO) datasets. Based on 1052 samples' data from our cohort, GEO and The Cancer Genome Atlas, we explored the relationship of clinicopathological features and NEIL3 expression to determine clinical effect of NEIL3 in LUAD. Western blotting (22 pairs of tumor and normal tissues), Real-time quantitative PCR (19 pairs of tumor and normal tissues), and immunohistochemical analyses (406-tumor tissues subjected to microarray) were conducted. TIMER and ImmuCellAI analyzed relationship between NEIL3 expression and the abundance of tumor-infiltrating immune cells in LUAD. The co-expressed-gene prognostic signature was established based on the Cox regression analysis.

RESULTS

This study identified 502 common differentially expressed genes and confirmed that NEIL3 was significantly overexpressed in LUAD samples (P < 0.001). Increased NEIL3 expression was related to advanced stage, larger tumor size and poor overall survival (p < 0.001) in three LUAD cohorts. The proportions of natural T regulatory cells and induced T regulatory cells increased in the high NEIL3 group, whereas those of B cells, Th17 cells and dendritic cells decreased. Gene set enrichment analysis indicated that NEIL3 may activate cell cycle progression and P53 signaling pathway, leading to poor outcomes. We identified nine prognosis-associated hub genes among 370 genes co-expressed with NEIL3. A 10-gene prognostic signature including NEIL3 and nine key co-expressed genes was constructed. Higher risk-score was correlated with more advanced stage, larger tumor size and worse outcome (p < 0.05). Finally, the signature was verified in test cohort (GSE50081) with superior diagnostic accuracy.

CONCLUSIONS

This study suggested that NEIL3 has the potential to be an immune-related therapeutic target and an independent predictor of LUAD prognosis. We also developed a prognostic signature for LUAD with a precise diagnostic accuracy.

Investigation on Potential Correlation Between Small Nuclear Ribonucleoprotein Polypeptide A and Lung Cancer

SNRPA (small nuclear ribonucleoprotein polypeptide A) gene is essential for the pre-mRNA splicing process. Using the available datasets of TCGA or GEO, we aimed at exploring the potential association between the SNRPA gene and lung cancer by several online tools (such as GEIPA2, MEXPRESS, Oncomine) and bioinformatics analysis software (R or GSEA). SNRPA was highly expressed in the tissues of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma tissue (LUSC), compared with control tissues. The high SNRPA expression was associated with a poor survival prognosis of LUAD cases, while the genetic alteration within SNRPA was linked to the overall survival prognosis of LUSC cases. There was a potential correlation between promoter methylation and the expression of SNRPA for LUAD. Compared with normal tissues, we observed a higher phosphorylation level at the S115 site of SNRPA protein (NP_004587.1) (p = 0.002) in the primary LUAD tissues. The potential ATR kinase of the S115 site was predicted. Besides, SNRPA expression in lung cancer was negatively correlated with the infiltration level of M2 macrophage but positively correlated with that of Follicular B helper T cells, in both LUAD and LUSC. The enrichment analysis of SNRPA-correlated genes showed that cell cycle and ubiquitin mechanism-related issues were mainly observed for LUAD; however, RNA splicing-related cellular issues were mainly for LUSC. In summary, the SNRPA gene was identified as a potential prognosis biomarker of lung cancer, especially lung adenocarcinoma, which sheds new light on the association between the spliceosomal complex component and tumorigenesis.

Expression of ATP/GTP Binding Protein 1 Has Prognostic Value for the Clinical Outcomes in Non-Small Cell Lung Carcinoma

ATP/GTP binding protein 1 (AGTPBP1) encodes a crucial protein, cytosolic carboxypeptidase 1 (CCP1), which plays a role in modulating the polyglutamylation of tubulin and has been studied in degenerative diseases. However, the role of AGTPBP1 in malignancy has not been completely studied yet. In this study, we examined the role of AGTPBP1 in cancer progression, its association with patient survival, and related mechanisms in lung cancer, using the A549 cell line and lung cancer gene expression datasets. AGTPBP1 knockdown increased the proliferation, migration, sphere formation, and drug resistance of A549 cells. Lung cancer datasets revealed significantly lower mRNA and protein expression levels of AGTPBP1 in lung cancer tissues, as compared to those in normal tissues. Importantly, AGTPBP1 expression positively correlated with patient survival. Analysis of co-expressed genes revealed that AGTPBP1 expression positively correlated with immune infiltration in lung cancer. Our results conclusively suggested that AGTPBP1 expression was correlated with cancer progression and immune infiltration in lung cancer.

Multi-omics Data Analyses Construct TME and Identify the Immune-Related Prognosis Signatures in Human LUAD

Lung cancer has been the focus of attention for many researchers in recent years for the leading contribution to cancer-related death worldwide, in which lung adenocarcinoma (LUAD) is the most common histological type. However, the potential mechanism behind LUAD initiation and progression remains unclear. Aiming to dissect the tumor microenvironment of LUAD and to discover more informative prognosis signatures, we investigated the immune-related differences in three types of genetic or epigenetic characteristics (expression status, somatic mutation, and DNA methylation) and considered the potential roles that these alterations have in the immune response and both the immune-related metabolic and neural systems by analyzing the multi-omics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct the prognostic prediction model. For the prognostic predictions on the independent test set, the performance of the trained models (average concordance index [C-index] = 0.839) is satisfied, with average 1-year, 3-year, and 5-year areas under the curve (AUCs) equal to 0.796, 0.786, and 0.777. Finally, the overall model was constructed based on all samples, which comprised 27 variables and achieved a high degree of accuracy on the 1-year (AUC = 0.861), 3-year (AUC = 0.850), and 5-year (AUC = 0.916) survival predictions.

Pan-Cancer Analysis of Immune Cell Infiltration Identifies a Prognostic Immune-Cell Characteristic Score (ICCS) in Lung Adenocarcinoma

Background: The tumor microenvironment (TME) consists of heterogeneous cell populations, including malignant cells and nonmalignant cells that support tumor proliferation, invasion, and metastasis through extensive cross talk. The intra-tumor immune landscape is a critical factor influencing patient survival and response to immunotherapy.

Methods: Gene expression data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. Immune cell infiltration was determined by single-sample Gene Set Enrichment Analysis (ssGSEA) depending on the integrated immune gene sets from published studies. Univariate analysis was used to determine the prognostic value of the infiltrated immune cells. Least absolute shrinkage and selection operator (LASSO) regression was performed to screen for the most survival-relevant immune cells. An immune-cell characteristic score (ICCS) model was constructed by using multivariate Cox regression analysis.

Results: The immune cell infiltration patterns across 32 cancer types were identified, and patients in the high immune cell infiltration cluster had worse overall survival (OS) but better progression-free interval (PFI) compared to the low immune cell infiltration cluster. However, immune cell infiltration showed inconsistent prognostic value depending on the cancer type. High immune cell infiltration (High CI) indicated a worse prognosis in brain lower grade glioma (LGG), glioblastoma multiforme (GBM), and uveal melanoma (UVM), and favorable prognosis in adrenocortical carcinoma (ACC), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), sarcoma (SARC), and skin cutaneous melanoma (SKCM). LUAD prognosis was significantly influenced by the infiltration of 13 immune cell types, with high infiltration of all but Type 2 T helper (Th2) cells correlating with a favorable prognosis. The ICCS model based on six most survival-relevant immune cell populations was generated that classified patients into low- and high-ICCS groups with good and poor prognoses, respectively. The multivariate and stratified analyses further revealed that the ICCS was an independent prognostic factor for LUAD.

Conclusions: The infiltration of immune cells in 32 cancer types was quantified, and considerable heterogeneity was observed in the prognostic relevance of these cells in different cancer types. An ICCS model was constructed for LUAD with competent prognostic performance, which can further deepen our understanding of the TME of LUAD and can have implications for immunotherapy.

FGL2 is positively correlated with enhanced antitumor responses mediated by T cells in lung adenocarcinoma

Lung cancer is the most common malignant tumor, accounting for 25% of cancer-related deaths and 14% of new cancers worldwide. Lung adenocarcinoma is the most common type of pulmonary cancer. Although there have been some improvements in the traditional therapy of lung cancer, the outcome and prognosis of patients remain poor. Lung cancer is the leading cause of cancer-related deaths worldwide, with 1.8 million new cases being diagnosed each year. Precision medicine based on genetic alterations is considered a new strategy of lung cancer treatment that requires highly specific biomarkers for precision diagnosis and treatment. Fibrinogen-like protein 2 (FGL2) plays important roles in both innate and adaptive immunity. However, the diagnostic value of FGL2 in lung cancer is largely unknown. In this study, we systematically investigated the expression profile and potential functions of FGL2 in lung adenocarcinoma. We used the TCGA and Oncomine datasets to compare the FGL2 expression levels between lung adenocarcinoma and adjacent normal tissues. We utilized the GEPIA, PrognoScan and Kaplan-Meier plotter databases to analyze the relationship between FGL2 expression and the survival of lung adenocarcinoma patients. Then, we investigated the potential roles of FGL2 in lung adenocarcinoma with the TIMER database and functional enrichment analyses. We found that FGL2 expression was significantly lower in lung adenocarcinoma tissue compared with adjacent normal tissue. A high expression level of FGL2 was correlated with better prognostic outcomes of lung adenocarcinoma patients, including overall survival and progression-free survival. FGL2 was positively correlated with the infiltration of immune cells, including dendritic cells, CD8+ T cells, macrophages, B cells, and CD4+ T cells, in lung adenocarcinoma. Functional enrichment analyses also showed that a high expression level of FGL2 was positively correlated with enhanced T cell activities, especially CD8+ T cell activation. Thus, we propose that high FGL2 expression, which is positively associated with enhanced antitumor activities mediated by T cells, is a beneficial marker for lung adenocarcinoma treatment outcomes.

Molecular Signature of Subtypes of Non-Small-Cell Lung Cancer by Large-Scale Transcriptional Profiling: Identification of Key Modules and Genes by Weighted Gene Co-Expression Network Analysis (WGCNA)

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies consisting essentially of adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Although the diagnosis and treatment of ADC and SCC have been greatly improved in recent decades, there is still an urgent need to identify accurate transcriptome profile associated with the histological subtypes of NSCLC. The present study aims to identify the key dysregulated pathways and genes involved in the development of lung ADC and SCC and to relate them with the clinical traits. The transcriptional changes between tumour and normal lung tissues were investigated by RNA-seq. Gene ontology (GO), canonical pathways analysis with the prediction of upstream regulators, and weighted gene co-expression network analysis (WGCNA) to identify co-expressed modules and hub genes were used to explore the biological functions of the identified dysregulated genes. It was indicated that specific gene signatures differed significantly between ADC and SCC related to the distinct pathways. Of identified modules, four and two modules were the most related to clinical features in ADC and SCC, respectively. CTLA4, MZB1, NIP7, and BUB1B in ADC, as well as GNG11 and CCNB2 in SCC, are novel top hub genes in modules associated with tumour size, SUVmax, and recurrence-free survival. Our research provides a more effective understanding of the importance of biological pathways and the relationships between major genes in NSCLC in the perspective of searching for new molecular targets.

Correlating tumor-infiltrating lymphocytes and lung cancer stem cells: a cross-sectional study

Background

Lung cancer stem cells (LCSCs) are endowed with high aldehyde dehydrogenase (ALDH) expression and play roles in tumor proliferation, metastasis, and drug resistance. Their elusive nature may allow them to escape the immune response by tumor-infiltrating lymphocytes (TILs), which can positively affect the outcome in non-small cell lung cancer (NSCLC) patients. Despite independent investigations on both LCSCs and TILs, the relationship between the two has been very marginally considered. We analyzed whether these two cell types may be related as a prerequisite for novel diagnostic and therapeutic approaches.

Methods

In this cross-sectional study, NSCLC human surgical specimens from 12 patients were tested by ALDEFLUOR assay to identify ALDH^high cells. Fluorescence-activated cell sorting (FACS) analyses for CD3+, CD4+, and CD8+ TILs were performed in combination with immunohistochemistry evaluation.

Results

Statistically positive correlations were found between ALDH+ and CD8+, and between ALDH+ and CD3+ cells populations; no correlation was found between ALDH+ and CD4+ cells. The expression of CD3+ and CD8+ by cells accounted for 40.1% and 58.7%, respectively, of the variability of ALDH+ cell expression by an R-squared index, which highlights the strong correlation between TILs and LCSCs. Immunohistochemistry revealed 6-25% positive cells.

Conclusions

We report a correlation between cytotoxic TILs and LCSCs, which may contribute to the future development of targeted therapies focusing on the different roles of lymphocytes against lung cancer.