Novel immune-related genes in the tumor microenvironment with prognostic value in breast cancer

Abstract Background Breast cancer is one of the most frequently diagnosed cancers among women worldwide. Alterations in the tumor microenvironment (TME) have been increasingly recognized as key in the development and progression of breast cancer in recent years. To deeply comprehend the gene expression profiling of the TME and identify immunological targets, as well as determine the relationship between gene expression and different prognoses is highly critical. Methods The stromal/immune scores of breast cancer patients from The Cancer Genome Atlas (TCGA) were employed to comprehensively evaluate the TME. Then, TME characteristics were assessed, overlapping genes of the top 3 Gene Ontology (GO) terms and upregulated differentially expressed genes (DEGs) were analyzed. Finally, through combined analyses of overall survival, time-dependent receiver operating characteristic (ROC), and protein-protein interaction (PPI) network, novel immune related genes with good prognosis were screened and validated in both TCGA and GEO database. Results Although the TME did not correlate with the stages of breast cancer, it was closely associated with the subtypes of breast cancer and gene mutations (CDH1, TP53 and PTEN), and had immunological characteristics. Based on GO functional enrichment analysis, the upregulated genes from the high vs low immune score groups were mainly involved in T cell activation, the external side of the plasma membrane, and receptor ligand activity. The top GO terms of the upregulated DEGs from the high vs low immune score groups exhibited better prognosis in breast cancer; 15 of them were related to good prognosis in breast cancer, especially CD226 and KLRC4-KLRK1. Conclusions High CD226 and KLRC4-KLRK1 expression levels were identified and validated to correlate with better overall survival in specific stages or subtypes of breast cancer. CD226, KLRC4-KLRK1 and other new targets seem to be promising avenues for promoting antitumor targeted immunotherapy in breast cancer.

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Novel immune-related genes in the tumor microenvironment with prognostic value in breast cancer

10.21203/rs.3.rs-35657/v3 ◽

2020 ◽

Author(s):

Wen Tan ◽

Maomao Liu ◽

Liangshan Wang ◽

Yang Guo ◽

Changsheng Wei ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

Tumor Microenvironment ◽

T Cell Activation ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Network Analyses ◽

Immune Score ◽

Go Terms

Abstract Background: Breast cancer is one of the most frequently diagnosed cancers among women worldwide. Alterations in the tumor microenvironment (TME) have been increasingly recognized as key in the development and progression of breast cancer in recent years. To deeply comprehend the gene expression profiling of the TME and identify immunological targets, as well as determine the relationship between gene expression and different prognoses is highly critical. Results: The stromal/immune scores of breast cancer patients from The Cancer Genome Atlas were employed to comprehensively evaluate the TME. Although the TME did not correlate with the stages of breast cancer, it was closely associated with the subtypes of breast cancer and gene mutations (CDH1, TP53 and PTEN), and had immunological characteristics. Based on Gene Ontology (GO) functional enrichment analysis, the upregulated genes from the high vs low immune score groups were mainly involved in T cell activation, the external side of the plasma membrane, and receptor ligand activity. We further analyzed and screened the overlapping genes of the top 3 GO terms and upregulated differentially expressed genes (DEGs). Overall survival, time-dependent receiver operating characteristic (ROC), and protein-protein interaction (PPI) network analyses revealed that the genes of the top GO terms of the upregulated DEGs from the high vs low immune score groups exhibited better prognosis in breast cancer; 15 of them were related to good prognosis in breast cancer, especially CD226 and KLRC4-KLRK1.Conclusions: High CD226 and KLRC4-KLRK1 expression levels were identified and validated to correlate with better overall survival in specific stages or subtypes of breast cancer. CD226, KLRC4-KLRK1 and other new targets seem to be promising avenues for promoting antitumor targeted immunotherapy in breast cancer.

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Novel immune-related genes in the tumor microenvironment with prognostic value in breast cancer

10.21203/rs.3.rs-35657/v2 ◽

2020 ◽

Author(s):

Wen Tan ◽

Maomao Liu ◽

Liangshan Wang ◽

Yang Guo ◽

Changsheng Wei ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

Tumor Microenvironment ◽

T Cell Activation ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Network Analyses ◽

Immune Score ◽

Go Terms

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Novel immune-related genes in the tumor microenvironment with prognostic value in breast cancer

10.21203/rs.3.rs-35657/v1 ◽

2020 ◽

Author(s):

Wen Tan ◽

Maomao Liu ◽

Liangshan Wang ◽

Yang Guo ◽

Changsheng Wei ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

Tumor Microenvironment ◽

T Cell Activation ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Network Analyses ◽

Immune Score ◽

Go Terms

Abstract Background Breast cancer is one of the most frequently diagnosed cancers among women worldwide. Alterations in the tumor microenvironment (TME) have been increasingly recognized as key in the development and progression of breast cancer in recent years. To deeply comprehend the gene expression profiling of the TME and identify immunological targets, as well as determine the relationship between gene expression and different prognoses is highly critical. Results The stromal/immune scores of breast cancer patients from The Cancer Genome Atlas were employed to comprehensively evaluate the TME. Although the TME did not correlate with the stages of breast cancer, it was closely associated with the subtypes of breast cancer and gene mutations (CDH1, TP53 and PTEN), and had immunological characteristics. Based on Gene Ontology (GO) functional enrichment analysis, the upregulated genes from the high vs low immune score groups were mainly involved in T cell activation, the external side of the plasma membrane, and receptor ligand activity. We further analyzed and screened the overlapping genes of the top 3 GO terms and upregulated differentially expressed genes (DEGs). Overall survival, time-dependent receiver operating characteristic (ROC), and protein-protein interaction (PPI) network analyses revealed that the genes of the top GO terms of the upregulated DEGs from the high vs low immune score groups exhibited better prognosis in breast cancer; 15 of them were related to good prognosis in breast cancer, especially CD226 and KLRC4-KLRK1. Conclusions High CD226 and KLRC4-KLRK1 expression levels were identified and validated to correlate with better overall survival in specific stages or subtypes of breast cancer. CD226, KLRC4-KLRK1 and other new targets seem to be promising avenues for promoting antitumor targeted immunotherapy in breast cancer.

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Exploration of Tumor Microenvironment-Related Biomarkers for the Prognosis of Triple Negative Breast Cancer

10.21203/rs.3.rs-510169/v1 ◽

2021 ◽

Author(s):

Xiaorui Han ◽

Zaiyi Liu ◽

Changhong Liang

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

Tumor Microenvironment ◽

Triple Negative Breast Cancer ◽

Stromal Cells ◽

Prognostic Model ◽

Triple Negative ◽

High Efficiency ◽

Functional Enrichment

Abstract Background: Triple negative breast cancer (TNBC) is one of the most disastrous breast cancer subtypes world widely. The tumor microenvironment (TME), especially the infiltration of immune and stromal cells, are highly related to the occurrence, development and prognosis of breast cancer. Therefore, exploration of TME-related biomarkers is greatly important for improving overall survival rate of TNBC patients. Methods: The open-assess Cancer Genome Atlas (TCGA) database provides gene expression profile for a variety of malignant tumors allowing researchers to explore genes demonstrating TME in the prognosis prediction of TNBC. In our present study, ESTIMATE algorithm was used to calculate the immune and stromal scores in accordance with the characteristics of specific genes in immune and stromal cells, and divide them into high and low-score groups. Limma R package was then utilized to screen differentially expressed genes (DEGs). After that, functional enrichment analysis and protein-protein interaction (PPI) network were performed to explore the bio-information of the DEGs and their encoded proteins. Subsequently, the identified these genes were further verified in the Gene Expression Omnibus (GEO) datasets. Results: Eight genes, including ACAP1, DUSP1, LYZGZMA, SASH3, CCL5, CD74, and DPT, were explored to closely related to the TME of TNBC. A prognostic model containing these selected genes was established with a high efficiency in the prediction of the poor prognosis of TNBC patients.Conclusion: An eight-gene prognostic model was a considerably reliable approach for predicting the overall survival of TNBC patients, and could help clinicians selecting personalized treatments for their TNBC patients.

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Identification of prognostic immune-related gene signature associated with tumor microenvironment of colorectal cancer

BMC Cancer ◽

10.1186/s12885-021-08629-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yuanyuan Wang ◽

Wei Li ◽

Xiaojing Jin ◽

Xia Jiang ◽

Shang Guo ◽

...

Keyword(s):

Colorectal Cancer ◽

Tumor Microenvironment ◽

Expression Profiles ◽

Functional Enrichment ◽

Clinical Parameters ◽

Cox Regression Analysis ◽

Ppi Networks ◽

Tumor Purity ◽

Immune Related Genes ◽

Immune Score

Abstract Background The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC). Methods Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database. Results Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717–0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates. Conclusions In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.

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Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression

PeerJ ◽

10.7717/peerj.12680 ◽

2022 ◽

Vol 10 ◽

pp. e12680

Author(s):

Peng Wang ◽

Zexin Zhang ◽

Bin Yin ◽

Jiayuan Li ◽

Cheng Xialin ◽

...

Keyword(s):

Gene Expression ◽

T Cell Activation ◽

Immune Cells ◽

Expression Profiles ◽

Functional Enrichment ◽

Prognostic Biomarkers ◽

Burn Patients ◽

Th Cells ◽

Key Genes ◽

Immune Related Genes

Background Burn patients are prone to infection as well as immunosuppression, which is a significant cause of death. Currently, there is a lack of prognostic biomarkers for immunosuppression in burn patients. This study was conducted to identify immune-related genes that are prognosis biomarkers in post-burn immunosuppression and potential targets for immunotherapy. Methods We downloaded the gene expression profiles and clinical data of 213 burn patients and 79 healthy samples from the Gene Expression Omnibus (GEO) database. Immune infiltration analysis was used to identify the proportion of circulating immune cells. Functional enrichment analyses were carried out to identify immune-related genes that were used to build miRNA-mRNA networks to screen key genes. Next, we carried out correlation analysis between immune cells and key genes that were then used to construct logistic regression models in GSE77791 and were validated in GSE19743. Finally, we determined the expression of key genes in burn patients using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Results A total of 745 differently expressed genes were screened out: 299 were up-regulated and 446 were down-regulated. The number of Th-cells (CD4+) decreased while neutrophils increased in burn patients. The enrichment analysis showed that down-regulated genes were enriched in the T-cell activation pathway, while up-regulated genes were enriched in neutrophil activation response in burn patients. We screened out key genes (NFATC2, RORA, and CAMK4) that could be regulated by miRNA. The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945. Finally, we determined that NFATC2, RORA, and CAMK4 were down-regulated in burn patients. Conclusion We found that NFATC2, RORA, and CAMK4 were likely prognostic biomarkers in post-burn immunosuppression and potential immunotherapeutic targets to convert Th-cell dysfunction.

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Identification of prognostic immune‐related gene signature associated with tumor microenvironment of colorectal cancer

10.21203/rs.3.rs-125538/v1 ◽

2020 ◽

Author(s):

Yuanyuan Wang ◽

Wei Li ◽

Xiaojing Jin ◽

Xia Jiang ◽

Shang Guo ◽

...

Keyword(s):

Colorectal Cancer ◽

Tumor Microenvironment ◽

Expression Profiles ◽

Functional Enrichment ◽

Clinical Parameters ◽

Cox Regression Analysis ◽

Ppi Networks ◽

Tumor Purity ◽

Immune Related Genes ◽

Immune Score

Abstract Background The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC). Methods Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database. Results Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C‐index of 0.769 (95%CI, 0.717–0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen‐IRGs signature. The AUC for 1‐, 3‐, and 5‐year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates. Conclusions In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.

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Clinical, pathological, and PAM50 gene expression features of HER2-low breast cancer

npj Breast Cancer ◽

10.1038/s41523-020-00208-2 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Francesco Schettini ◽

Nuria Chic ◽

Fara Brasó-Maristany ◽

Laia Paré ◽

Tomás Pascual ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

High Activity ◽

Triple Negative ◽

Her2 Expression ◽

Drug Conjugates ◽

Molecular Features ◽

Biological Heterogeneity ◽

Antibody Drug

AbstractNovel antibody-drug conjugates against HER2 are showing high activity in HER2-negative breast cancer (BC) with low HER2 expression (i.e., 1+ or 2+ and lack of ERBB2 amplification). However, the clinical and molecular features of HER2-low BC are yet to be elucidated. Here, we collected retrospective clinicopathological and PAM50 data from 3,689 patients with HER2-negative disease and made the following observations. First, the proportion of HER2-low was higher in HR-positive disease (65.4%) than triple-negative BC (TNBC, 36.6%). Second, within HR-positive disease, ERBB2 and luminal-related genes were more expressed in HER2-low than HER2 0. In contrast, no gene was found differentially expressed in TNBC according to HER2 expression. Third, within HER2-low, ERBB2 levels were higher in HR-positive disease than TNBC. Fourth, HER2-low was not associated with overall survival in HR-positive disease and TNBC. Finally, the reproducibility of HER2-low among pathologists was suboptimal. This study emphasizes the large biological heterogeneity of HER2-low BC, and the need to implement reproducible and sensitive assays to measure low HER2 expression.

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DNAJC28 expression associates with survival in triple negative breast cancer.

10.31219/osf.io/v45h2 ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Overall Survival ◽

Cancer Patients ◽

Triple Negative Breast Cancer ◽

Microarray Data ◽

Triple Negative ◽

Breast Cancer Patients ◽

Primary Tumors ◽

Significant Gene

We mined published microarray data (1) to understand the most significant gene expression differences in the tumors of triple negative breast cancer patients based on survival following treatment: dead or alive. We observed significant transcriptome-wide differential expression of DnaJ (Hsp40) homolog, subfamily C, member 28, encoded by DNAJC28 when comparing the primary tumors of triple negative breast cancer patients dead or alive. Importantly, DNAJC28 expression was correlated with overall survival in patients with breast cancer. DNAJC28 may be of relevance as a biomarker or as a molecule of interest in understanding the etiology or progression of triple negative breast cancer.

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83 Spatially resolved transcriptomic and proteomic investigation of breast cancer and its immune microenvironment

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.083 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A91-A91

Author(s):

Jennifer Chew ◽

Cedric Uytingco ◽

Rapolas Spalinskas ◽

Yifeng Yin ◽

Joe Shuga ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Tumor Microenvironment ◽

Protein Expression ◽

Protein Detection ◽

Response To Therapy ◽

Pathological Examination ◽

Multi Drug Resistance ◽

Spatially Resolved ◽

Gene And Protein Expression

BackgroundThe tumor microenvironment (TME) is composed of highly heterogeneous extracellular structures and cell types such as endothelial cells, immune cells, and fibroblasts that dynamically influence and communicate with each other. The constant interaction between a tumor and its microenvironment plays a critical role in cancer development and progression and can significantly affect a tumor’s response to therapy and capacity for multi-drug resistance. High resolution analyses of gene and protein expression with spatial context can provide deeper insights into the interactions between tumor cells and surrounding cells within the TME, where a better understanding of the underlying biology can improve treatment efficacy and patient outcomes. Here, we demonstrated the ability to perform streamlined multi-omic tumor analyses by utilizing the 10X Genomics Visium Spatial Gene Expression Solution for FFPE with multiplex protein enablement. This technique simultaneously assesses gene and protein expression to elucidate the immunological profile and microenvironment of different breast cancer samples in conjunction with standard pathological methods.MethodsSerial (5 µm) sections of FFPE human breast cancer samples were placed on Visium Gene Expression (GEX) slides. The Visium GEX slides incorporate ~5,000 molecularly barcoded, spatially encoded capture spots onto which tissue sections are placed, stained, and imaged. Following incubation with a human whole transcriptome, probe-based RNA panel and an immuno-oncology oligo-tagged antibody panel, developed with Abcam conjugated antibodies, the tissues are permeabilized and the representative probes are captured. Paired GEX and protein libraries are generated for each section and then sequenced on an Illumina NovaSeq at a depth of ~50,000 reads per spot. Resulting reads from both libraries are aligned and overlaid with H&E-stained tissue images, enabling analysis of both mRNA and protein expression. Additional analyses and data visualizations were performed on the Loupe Browser v4.1 desktop software.ConclusionsSpatial transcriptomics technology complements pathological examination by combining histological assessment with the throughput and deep biological insight of highly-multiplexed protein detection and RNA-seq. Taken together, our work demonstrated that Visium Spatial technology provides a spatially-resolved, multi-analyte view of the tumor microenvironment, where a greater understanding of cellular behavior in and around tumors can help drive discovery of new biomarkers and therapeutic targets.

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