Immunological Classification of Pancreatic Carcinomas to Identify Immune Index and Provide a Strategy for Patient Stratification

BackgroundCancer immunotherapy has produced significant positive clinical effects in a variety of tumor types. However, pancreatic ductal adenocarcinoma (PDAC) is widely considered to be a “cold” cancer with poor immunogenicity. Our aim is to determine the detailed immune features of PDAC to seek new treatment strategies.MethodsThe immune cell abundance of PDAC patients was evaluated with the single-sample gene set enrichment analysis (ssGSEA) using 119 immune gene signatures. Based on these data, patients were classified into different immune subtypes (ISs) according to immune gene signatures. We analyzed their response patterns to immunotherapy in the datasets, then established an immune index to reflect the different degrees of immune infiltration through linear discriminant analysis (LDA). Finally, potential prognostic markers associated with the immune index were identified based on weighted correlation network analysis (WGCNA) that was functionally validated in vitro.ResultsThree ISs were identified in PDAC, of which IS3 had the best prognosis across all three cohorts. The different expressions of immune profiles among the three ISs indicated a distinct responsiveness to immunotherapies in PDAC subtypes. By calculating the immune index, we found that the IS3 represented higher immune infiltration, while IS1 represented lower immune infiltration. Among the investigated signatures, we identified ZNF185, FANCG, and CSTF2 as risk factors associated with immune index that could potentially facilitate diagnosis and could be therapeutic target markers in PDAC patients.ConclusionsOur findings identified immunologic subtypes of PDAC with distinct prognostic implications, which allowed us to establish an immune index to represent the immune infiltration in each subtype. These results show the importance of continuing investigation of immunotherapy and will allow clinical workers to personalized treatment more effectively in PDAC patients.

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Down-Regulated CLDN10 Predicts Favorable Prognosis and Correlates With Immune Infiltration in Gastric Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.747581 ◽

2021 ◽

Vol 12 ◽

Author(s):

XiongHui Rao ◽

JianLong Jiang ◽

ZhiHao Liang ◽

JianBao Zhang ◽

ZheHong Zhuang ◽

...

Keyword(s):

Gastric Cancer ◽

T Cell ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Her2 Status ◽

Immune Cell Infiltration ◽

Cell Markers ◽

Immune Infiltration

Background: CLDN10, an important component of the tight junctions of epithelial cells, plays a crucial role in a variety of tumors. The effect of CLDN10 expression in gastric cancer, however, has yet to be elucidated.Methods: Differential expression of CLDN10 at the mRNA and protein levels was evaluated using Oncomine, ULCAN, HPA and TIMER2.0 databases. Real-time polymerase chain reaction (RT-PCR) was utilized to further verify the expression of CLDN10 in vitro. Correlations between CLDN10 expression and clinical outcomes of gastric cancer were explored by Kaplan-Meier Plotter. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) were performed via LinkedOmics and GeneMANIA. The correlations between CLDN10 expression and immune cell infiltration and somatic copy number alternations (SCNA) in gastric cancer were explored by TIMER2.0 and GEPIA2.0.Results: CLDN10 expression was lower in gastric cancer compared to adjacent normal tissues, and associated with better prognosis. CLDN10 also showed significant differences at different T stages, Lauren classification, treatments and HER2 status. PPI and GSEA analysis showed that CLDN10 might be involved in signal transmission, transmembrane transport and metabolism. In some major immune cells, low expression of CLDN10 was associated with increased levels of immune cell infiltration. In addition, it was found that different SCNA status in CLDN10 might affect the level of immune cell infiltration. Furthermore, the expression of CLDN10 was significantly associated with the expression of several immune cell markers, especially B cell markers, follicular helper T cell (Tfh) markers and T cell exhaustion markers.Conclusion: Down-regulated CLDN10 was associated with better overall survival (OS) in gastric cancer. And CLDN10 may serve as a potential prognostic biomarker and correlate to immune infiltration levels in gastric cancer.

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Immune Cell Modulation of the Extracellular Matrix Contributes to the Pathogenesis of Pancreatic Cancer

Biomolecules ◽

10.3390/biom11060901 ◽

2021 ◽

Vol 11 (6) ◽

pp. 901

Author(s):

Ramiz S. Ahmad ◽

Timothy D. Eubank ◽

Slawomir Lukomski ◽

Brian A. Boone

Keyword(s):

Pancreatic Cancer ◽

Extracellular Matrix ◽

Immune Cells ◽

Immune Cell ◽

Treatment Strategies ◽

Stellate Cells ◽

Pancreatic Stellate Cells ◽

Ductal Adenocarcinoma ◽

Cellular Mechanisms ◽

Novel Treatment Strategies

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a five-year survival rate of only 9%. PDAC is characterized by a dense, fibrotic stroma composed of extracellular matrix (ECM) proteins. This desmoplastic stroma is a hallmark of PDAC, representing a significant physical barrier that is immunosuppressive and obstructs penetration of cytotoxic chemotherapy agents into the tumor microenvironment (TME). Additionally, dense ECM promotes hypoxia, making tumor cells refractive to radiation therapy and alters their metabolism, thereby supporting proliferation and survival. In this review, we outline the significant contribution of fibrosis to the pathogenesis of pancreatic cancer, with a focus on the cross talk between immune cells and pancreatic stellate cells that contribute to ECM deposition. We emphasize the cellular mechanisms by which neutrophils and macrophages, specifically, modulate the ECM in favor of PDAC-progression. Furthermore, we investigate how activated stellate cells and ECM influence immune cells and promote immunosuppression in PDAC. Finally, we summarize therapeutic strategies that target the stroma and hinder immune cell promotion of fibrogenesis, which have unfortunately led to mixed results. An enhanced understanding of the complex interactions between the pancreatic tumor ECM and immune cells may uncover novel treatment strategies that are desperately needed for this devastating disease.

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Prognostic Value and Immune Infiltration of ARMC10 in Pancreatic Adenocarcinoma Via Integrated Bioinformatics Analyses

10.21203/rs.3.rs-936587/v1 ◽

2021 ◽

Author(s):

Tianhao Li ◽

Xiaohan Qin ◽

Cheng Qin ◽

Bangbo Zhao ◽

Hongtao Cao ◽

...

Keyword(s):

Pancreatic Adenocarcinoma ◽

Formation Rate ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Primary Therapy ◽

Migration Ability ◽

Bioinformatics Analyses ◽

Immune Infiltration

Abstract Background: Armadillo repeat-containing 10 (ARMC10) is involved in the progression of multiple types of tumors. Pancreatic adenocarcinoma (PAAD) is a lethal disease with poor survival and prognosis.Methods: We acquired the data of ARMC10 in PAAD patients from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) datasets and compared the expression level with normal pancreatic tissues. We evaluated the relevance between ARMC10 expression and clinicopathological factors, immune infiltration degree and prognosis in PAAD.Results: High expression of ARMC10 was relevant to T stage, M stage, pathologic stage, histologic grade, residual tumor, primary therapy outcome (P<0.05) and related to lower Overall-Survival (OS), Disease-Specific Survival (DSS), and Progression-Free Interval (PFI). Gene set enrichment analysis showed that ARMC10 was related to methylation in neural precursor cells (NPC), G alpha (i) signaling events, APC targets, energy metabolism, potassium channels and IL10 synthesis. The expression level of ARMC10 was positively related to the abundance of T helper cells and negatively to that of plasmacytoid dendritic cells (pDCs). Knocking down of ARMC10 could lead to lower proliferation, invasion, migration ability and colony formation rate of PAAD cells in vitro.Conclusions: Our research firstly discovered ARMC10 as a novel prognostic biomarker for PAAD patients and played a crucial role in immune regulation in PAAD.

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Identification of a gene set correlated with immune status in ovarian cancer by transcriptome-wide data mining

10.21203/rs.3.rs-17604/v1 ◽

2020 ◽

Author(s):

Lili Fan ◽

Han Lei ◽

Ying Lin ◽

Zhengwei Zhou ◽

Guang Shu ◽

...

Keyword(s):

Ovarian Cancer ◽

Immune Cell ◽

Good Prognosis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Survival Prognosis ◽

Immune Activity ◽

Gene Set ◽

Immune Infiltration ◽

Keywords Ovarian Cancer

Abstract Background : Ovarian cancer (OC) is a serious tumor disease in gynecology. Many papers have reported that high tumor mutational burden (TMB) can generate many neoantigens to result in a higher degree of tumor immune infiltration, so our study aims to predict the key molecules in OC immunotherapy by combined TMB with immunoactivity-related gene. Method: We divided OC cases into two groups: the low & high TMB group hinged on the somatic mutation data from the Cancer Genome Atlas (TCGA). We also used single-sample gene set enrichment analysis (ssGSEA) scores of immune cell types to conduct unsupervised clustering of OC patients in the TCGA cohort and some of them were defined as the low & high immunity group. Besides, to further understand the function of these genes, we conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, protein-protein interaction network, survival prognosis analysis and immune infiltration analysis. Finally, the effects on prognosis and immunotherapy in OC patients were explored by the Group on Earth Observations verification the patients' responses to immunotherapy. Results: We found that the higher the TMB was associated with the higher OC grades. Moreover, both high TMB and high immunity were significantly correlated with a good prognosis of OC. Then, 14 up-regulated differential expression genes (Up-DEGs) that were closely related to the prognosis of OC patients were screened according to the high TMB group and the high immunity group. Next, pathway analysis revealed that Up-DGEs were mainly involved in immune response and T cell proliferation. Finally, four genes had a good prognosis and were validated in the GEO dataset which included CXCL13, FCRLA, PLA2G2D, and MS4A1. We also identified that four genes had a good prognosis in melanoma patients treated with anti-PD-L1 and anti-CTLA-4 in the TIDE database. Conclusion: High TMB can promote immune cell infiltration and increases immune activity. And our analysis also demonstrated that the higher the TMB, the higher the immune activity, the better the prognosis of OC. Altogether, we found that CXCL13, FCRLA, PLA2G2D, and MS4A1 may be biomarkers for OC immunotherapy. Keywords: ovarian cancer, TMB, immune cells infiltration, survival prognosis.

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Morphological classification of pancreatic ductal adenocarcinoma that predicts molecular subtypes and correlates with clinical outcome

Gut ◽

10.1136/gutjnl-2019-318217 ◽

2019 ◽

Vol 69 (2) ◽

pp. 317-328 ◽

Cited By ~ 9

Author(s):

Sangeetha N Kalimuthu ◽

Gavin W Wilson ◽

Robert C Grant ◽

Matthew Seto ◽

Grainne O’Kane ◽

...

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Molecular Subtypes ◽

Differentially Expressed Gene ◽

Biological Significance ◽

Treatment Strategies ◽

Ductal Adenocarcinoma ◽

Rna Seq ◽

Gene Signatures ◽

Significant Difference ◽

Morphological Patterns

IntroductionTranscriptional analyses have identified several distinct molecular subtypes in pancreatic ductal adenocarcinoma (PDAC) that have prognostic and potential therapeutic significance. However, to date, an indepth, clinicomorphological correlation of these molecular subtypes has not been performed. We sought to identify specific morphological patterns to compare with known molecular subtypes, interrogate their biological significance, and furthermore reappraise the current grading system in PDAC.DesignWe first assessed 86 primary, chemotherapy-naive PDAC resection specimens with matched RNA-Seq data for specific, reproducible morphological patterns. Differential expression was applied to the gene expression data using the morphological features. We next compared the differentially expressed gene signatures with previously published molecular subtypes. Overall survival (OS) was correlated with the morphological and molecular subtypes.ResultsWe identified four morphological patterns that segregated into two components (‘gland forming’ and ‘non-gland forming’) based on the presence/absence of well-formed glands. A morphological cut-off (≥40% ‘non-gland forming’) was established using RNA-Seq data, which identified two groups (A and B) with gene signatures that correlated with known molecular subtypes. There was a significant difference in OS between the groups. The morphological groups remained significantly prognostic within cancers that were moderately differentiated and classified as ‘classical’ using RNA-Seq.ConclusionOur study has demonstrated that PDACs can be morphologically classified into distinct and biologically relevant categories which predict known molecular subtypes. These results provide the basis for an improved taxonomy of PDAC, which may lend itself to future treatment strategies and the development of deep learning models.

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Association between cetuximab response and differential immunologic gene expression signatures in colorectal cancer metastases.

Journal of Clinical Oncology ◽

10.1200/jco.2016.34.4_suppl.558 ◽

2016 ◽

Vol 34 (4_suppl) ◽

pp. 558-558 ◽

Cited By ~ 1

Author(s):

Michael Sangmin Lee ◽

Benjamin Garrett Vincent ◽

Autumn Jackson McRee ◽

Hanna Kelly Sanoff

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

T Cells ◽

T Cell ◽

Immune Cell ◽

Expression Profiles ◽

Gene Set Enrichment Analysis ◽

Activated T Cells ◽

Gene Sets

558 Background: Different immune cell infiltrates into colorectal cancer (CRC) tumors are associated with different prognoses. Tumor-associated macrophages contribute to immune evasion and accelerated tumor progression. Conversely, tumor infiltrating lymphocytes at the invasive margin of CRC liver metastases are associated with improved outcomes with chemotherapy. Cetuximab is an IgG1 monoclonal antibody against epidermal growth factor receptor (EGFR) and stimulates antibody-dependent cellular cytotoxicity (ADCC) in vitro. However, it is unclear in humans if response to cetuximab is modulated by the immune response. We hypothesized that different immune patterns detected in gene expression profiles of CRC metastases are associated with different responses to cetuximab. Methods: We retrieved gene expression data from biopsies of metastases from 80 refractory CRC patients treated with cetuximab monotherapy (GEO GSE5851). Samples were dichotomized by cetuximab response as having either disease control (DC) or progressive disease (PD). We performed gene set enrichment analysis (GSEA) with GenePattern 3.9.4 using gene sets of immunologic signatures obtained from the Molecular Signatures Database v5.0. Results: Among the 68 patients with response annotated, 25 had DC and 43 had PD. In the PD cohort, 59/1910 immunologic gene sets had false discovery rate (FDR) < 0.1. Notably, multiple gene sets upregulated in monocyte signatures were associated with PD. Also, gene sets consistent with PD1-ligated T cells compared to control activated T cells (FDR = 0.052) or IL4-treated CD4 T cells compared to controls (FDR = 0.087) were associated with PD. Conclusions: Cetuximab-resistant patients tended to have baseline increased expression of gene signatures reflective of monocytic infiltrates, consistent with also having increased expression of the IL4-treated T-cell signature. Cetuximab resistance was also associated with increased expression of the PD1-ligated T cell signature. These preliminary findings support further evaluation of the effect of differential immune infiltrates in prognosis of metastatic CRC treated with cetuximab.

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Prognostic Significance and Immune Infiltration of Microenvironment‐related Signatures in Pancreatic Cancer

10.21203/rs.3.rs-60885/v1 ◽

2020 ◽

Author(s):

Qian Lu ◽

Yu Zhang ◽

Weihong Gu ◽

Xinrong Ji ◽

Zhong Chen

Keyword(s):

Pancreatic Cancer ◽

Overall Survival ◽

Immune Cell ◽

Differential Expression Analysis ◽

Prognostic Significance ◽

Ductal Adenocarcinoma ◽

Immune Infiltration ◽

Protein Protein Interaction ◽

Tumor Tissues ◽

Cox Analysis

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the highly fatal and most aggressive types of malignancies and accounts for the vast majority of Pancreatic Cancer (PC). Numerous studies have reported that the tumor microenvironment (TME) was significantly correlated with the oncogenesis, progress, and prognosis of various malignancies. Therefore, mining of TME-related genes is reasonably important to improve the overall survival (OS) of patients with PDAC. Methods: The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to identify differential expressed genes (DEGs). Functional and pathway enrichment analyses, protein–protein interaction (PPI) network construction and module analysis, overall survival analysis and tumor immune estimation resource (TIMER) database analysis were then performed on DEGs. Results: Data analysis indicated that higher immune scores were correlated with better overall survival (P = 0.033). Differential expression analysis obtained 90 intersection genes influencing both stromal and immune scores. Among these intersection genes, CA9, EBI3, SPOCK2, WDFY4, CD1D and CCL22 were significantly correlated with OS in PDAC patients. Moreover, multivariate Cox analysis revealed that CA9, SPOCK2 and CD1D were the most significant prognostic genes, and were closely correlated with immune infiltration in TCGA cohort. Further analysis indicated that CD1D were significantly related with immune cell biomarkers for PDAC patients. Conclusions: In summary, our findings provide a more comprehensive insight into TME and show a list of prognostic immune associated genes in PDAC. However, further studies on these genes need to be performed to gain additional understanding of the association between TME and prognosis in PDAC.

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ImSig: A resource for the identification and quantification of immune signatures in blood and tissue transcriptomics data

10.1101/077487 ◽

2016 ◽

Author(s):

Ajit Johnson Nirmal ◽

Tim Regan ◽

Barbara Bo-Ju Shih ◽

David Arthur Hume ◽

Andrew Harvey Sims ◽

...

Keyword(s):

Immune Cell ◽

Cell Types ◽

Clinical Samples ◽

Marker Genes ◽

Immune Gene ◽

Gene Signatures ◽

Transcriptomic Data ◽

Prognostic Assessment ◽

The Status ◽

Transcriptomics Data

AbstractThe outcome of many diseases is commonly correlated with the immune response at the site of pathology. The ability to monitor the status of the immune system in situ provides a mechanistic understanding of disease progression, a prognostic assessment and a guide for therapeutic intervention. Global transcriptomic data can be deconvoluted to provide an indication of the cell types present and their activation state, but the gene signatures proposed to date are either disease-specific or have been derived from data generated from isolated cell populations. Here we describe an improved set of immune gene signatures, ImSig, derived based on their co-expression in blood and tissue datasets. ImSig includes validated lists of marker genes for the main immune cell types and a number of core pathways. When used in combination with network analysis, ImSig is an accurate and easy to use approach for monitoring immune phenotypes in transcriptomic data derived from clinical samples.

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ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

Canadian Journal of Gastroenterology and Hepatology ◽

10.1155/2022/3163955 ◽

2022 ◽

Vol 2022 ◽

pp. 1-14

Author(s):

Yuanyuan Feng ◽

Xinfang Tang ◽

Changcheng Li ◽

Ying Su ◽

Xiaoyu Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Migration And Invasion ◽

Risk Indicator ◽

Immune Cell Infiltration

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

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CDKN2B-AS1 Promotes Malignancy as a Novel Prognosis-Related Molecular Marker in the Endometrial Cancer Immune Microenvironment

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.721676 ◽

2021 ◽

Vol 9 ◽

Author(s):

Di Yang ◽

Jian Ma ◽

Xiao-Xin Ma

Keyword(s):

Endometrial Cancer ◽

Immune Cell ◽

Quantitative Polymerase Chain Reaction ◽

Treatment Strategies ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Immune Infiltration ◽

Lncrna Expression ◽

Ec Cells

The prognosis of patients with endometrial cancer (EC) is closely associated with immune cell infiltration. Although abnormal long non-coding RNA (lncRNA) expression is also linked to poor prognosis in patients with EC, the function and action mechanism of immune infiltration-related lncRNAs underlying the occurrence and development of EC remains unclear. In this study, we analyzed lncRNA expression using The Cancer Genome Atlas and clinical data and identified six lncRNAs as prognostic markers for EC, all of which are associated with the infiltration of immune cell subtypes, as illustrated by ImmLnc database and ssGSEA analysis. Real-time quantitative polymerase chain reaction showed that CDKN2B-AS1 was significantly overexpressed in EC, whereas its knockdown inhibited the proliferation and invasion of EC cells and the in vivo growth of transplanted tumors in nude mice. Finally, we constructed a competing endogenous RNA regulatory network and conducted Gene Ontology enrichment analysis to elucidate the potential molecular mechanism underlying CDKN2B-AS1 function. Overall, we identified molecular targets associated with immune infiltration and prognosis and provide new insights into the development of molecular therapies and treatment strategies against EC.

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