TIGIT-related transcriptome profile and its association with tumor immune microenvironment in breast cancer

Abstract Immune checkpoints are intensively investigated as targets in cancer immunotherapy. T-cell immunoreceptor with immunoglobulin (Ig) and ITIM domains (TIGIT) are recently emerging as a novel promising target in cancer immunotherapy. Herein, we systematically investigated TIGIT-related transcriptome profile and relevant clinical information derived from a total of 2994 breast cancer patients recorded in The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). We uncovered the relationship between TIGIT and major molecular and clinical characteristics in breast cancer. More importantly, we depicted the landscape of associations between TIGIT and other immune cell populations. Gene ontology analyses and Gene Set Variation Analysis (GSVA) of genes correlated with TIGIT revealed that TIGIT were mainly involved in immune responses and inflammatory activities. In summary, TIGIT expression was tightly related to the aggressiveness of breast cancer; TIGIT might manipulate anti-tumor immune responses by impacting not only T cells but also other immune cells. To the best of our knowledge, this is by far the most comprehensive and largest study characterizing the molecular and clinical features of TIGIT in breast cancer through large-scale transcriptome data.

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Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples

Frontiers in Immunology ◽

10.3389/fimmu.2021.599207 ◽

2021 ◽

Vol 12 ◽

Author(s):

Qiang Liu ◽

Yihang Qi ◽

Jie Zhai ◽

Xiangyi Kong ◽

Xiangyu Wang ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Immunotherapy ◽

Cancer Patients ◽

Immune Cell ◽

Immune Checkpoints ◽

Cell Populations ◽

Breast Cancer Patients ◽

Correlation Pattern ◽

Potential Biomarker

Despite the promising impact of cancer immunotherapy targeting CTLA4 and PD1/PDL1, numerous cancer patients fail to respond. LAG3 (Lymphocyte Activating 3), also named CD233, serves as an alternative inhibitory receptor to be targeted in the clinic. The impacts of LAG3 on immune cell populations and coregulation of immune responses in breast cancer remain largely unknown. To characterize the role of LAG3 in breast cancer, we investigated transcriptome data and associated clinical information derived from 2,994 breast cancer patients. We estimated the landscape of the relationship between LAG3 and 10 types of cell populations of breast cancer. We investigated the correlation pattern between LAG3 and immune modulators in pancancer, particularly the synergistic role of LAG3 with other immune checkpoint members in breast cancer. LAG3 expression was closely related to the malignancy of breast cancer and may serve as a potential biomarker. LAG3 may play an important role in regulating the tumor immune microenvironment of T cells and other immune cells. More important, LAG3 may synergize with CTLA4, PD1/PDL1, and other immune checkpoints, thereby contributing more evidence to improve combination cancer immunotherapy by simultaneously targeting LAG3, PD1/PDL1, and CTLA4.

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Molecular and Clinical Characterization of CCT2 Expression and Prognosis via Large-Scale Transcriptome Profile of Breast Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.614497 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qiang Liu ◽

Yihang Qi ◽

Xiangyi Kong ◽

Xiangyu Wang ◽

Wenxiang Zhang ◽

...

Keyword(s):

Breast Cancer ◽

Survival Analysis ◽

Molecular Chaperone ◽

Large Scale ◽

Molecular Taxonomy ◽

Prognostic Significance ◽

The Cancer Genome Atlas ◽

Breast Cancer Patients ◽

Luminal A ◽

Worse Prognosis

Molecular chaperones play important roles in regulating various cellular processes and malignant transformation. Expression of some subunits of molecular chaperone CCT/TRiC complex have been reported to be correlated with cancer development and patient survival. However, little is known about the expression and prognostic significance of Chaperonin Containing TCP1 Subunit 2 (CCT2). CCT2 is a gene encoding a molecular chaperone that is a member of the chaperonin containing TCP1 complex (CCT), also known as the TCP1 ring complex (TRiC). Through the Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases, we systematically reviewed a total of 2,994 cases with transcriptome data and analyzed the functional annotation of CCT2 by Gene ontology and KEGG analysis. Univariate and multivariate survival analysis were performed to investigate the prognostic value of CCT2 in breast cancer. We found CCT2 was significantly upregulated in various tumors. In breast cancer, CCT2 expression was significantly upregulated in HER2-positive (HER2+) group, and more malignant group. In addition, we investigated correlations between CCT2 and other CCT members. Interestingly, almost all CCTs expression were positively correlated with each other, but not CCT6B. Survival analysis suggested that CCT2 overexpression was independently associated with worse prognosis of patients with breast cancer, especially in luminal A subtype. In summary, our results revealed that CCT2 might be involved in regulating cell cycle pathway, and independently predicted worse prognosis in breast cancer patients. These findings may expand understanding of potential anti-CCT2 treatments. To our knowledge, this is the largest and most comprehensive study characterizing the expression pattern of CCT2 together with its prognostic values in breast cancer.

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An Immune-Related Gene Prognostic Index for Triple-Negative Breast Cancer Integrates Multiple Aspects of Tumor-Immune Microenvironment

Cancers ◽

10.3390/cancers13215342 ◽

2021 ◽

Vol 13 (21) ◽

pp. 5342

Author(s):

Xiaowei Wang ◽

Wenjia Su ◽

Dabei Tang ◽

Jing Jing ◽

Jing Xiong ◽

...

Keyword(s):

Breast Cancer ◽

T Cells ◽

Immune Cell ◽

Cox Regression ◽

Molecular Taxonomy ◽

Prognostic Index ◽

The Cancer Genome Atlas ◽

Immune Checkpoints ◽

Data Set ◽

Cox Regression Analysis

Tumor-immune cell compositions and immune checkpoints comprehensively affect TNBC outcomes. With the significantly improved survival rate of TNBC patients treated with ICI therapies, a biomarker integrating multiple aspects of TIME may have prognostic value for improving the efficacy of ICI therapy. Immune-related hub genes were identified with weighted gene co-expression network analysis and differential gene expression assay using The Cancer Genome Atlas TNBC data set (n = 115). IRGPI was constructed with Cox regression analysis. Immune cell compositions and TIL status were analyzed with CIBERSORT and TIDE. The discovery was validated with the Molecular Taxonomy of Breast Cancer International Consortium data set (n = 196) and a patient cohort from our hospital. Tumor expression or serum concentrations of CCL5, CCL25, or PD-L1 were determined with immunohistochemistry or ELISA. The constructed IRGPI was composed of CCL5 and CCL25 genes and was negatively associated with the patient’s survival. IRGPI also predicts the compositions of M0 and M2 macrophages, memory B cells, CD8+ T cells, activated memory CD4 T cells, and the exclusion and dysfunction of TILs, as well as PD-1 and PD-L1 expression of TNBC. IRGPI is a promising biomarker for predicting the prognosis and multiple immune characteristics of TNBC.

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Molecular and Clinical Characterization of LAG3 in Breast Cancer Through 2994 Samples

10.21203/rs.3.rs-36422/v1 ◽

2020 ◽

Author(s):

Qiang Liu ◽

Yihang Qi ◽

Jie Zhai ◽

Xiangyi Kong ◽

Xiangyu Wang ◽

...

Keyword(s):

Breast Cancer ◽

Immune Response ◽

Cancer Immunotherapy ◽

Cancer Patients ◽

Immune Cell ◽

Immune Checkpoints ◽

Cell Populations ◽

Potential Biomarker ◽

The Impact

Abstract Background Despite the promising impact of cancer immunotherapy targeting CTLA4 and PD1/PDL1, a large number of cancer patients fail to respond. LAG3 (Lymphocyte Activating 3), also named CD233, is a protein Coding gene served as alternative inhibitory receptors to be targeted in the clinic. The impact of LAG3 on immune cell populations and co-regulation of immune response in breast cancer remained largely unknown. Methods To characterize the role of LAG3 in breast cancer, we investigated transcriptome data and associated clinical information derived from a total of 2994 breast cancer patients. Results We observed that LAG3 was closely correlated with major molecular and clinical characteristics, and was more likely to be enriched in higher malignant subtype, suggesting LAG3 was a potential biomarker of triple-negative breast cancer. Furthermore, we estimated the landscape of relationship between LAG3 and ten types of cell populations in breast cancer. Gene ontology analysis revealed LAG3 were strongly correlated with immune response and inflammatory activities. We investigated the correlation pattern between LAG3 and immune modulators in pan-cancer, especially the synergistic role of LAG3 with other immune checkpoints members in breast cancer. Conclusions LAG3 expression was closely related to malignancy of breast cancer and might serve as a potential biomarker; LAG3 might plays an important role in regulating tumor immune microenvironment, not only T cells, but also other immune cells. More importantly, LAG3 might synergize with CTLA4, PD1/ PDL1 and other immune checkpoints, thereby lending more evidences to combination cancer immunotherapy by targeting LAG3, PD1/PDL1, and CTLA4 together.

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Gene Signatures and Cancer-Immune Phenotypes Based on m6A Regulators in Breast Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.756412 ◽

2021 ◽

Vol 11 ◽

Author(s):

Guanghui Zhao ◽

Junhua An ◽

Qian Pu ◽

Wenwen Geng ◽

Haiyun Song ◽

...

Keyword(s):

Breast Cancer ◽

Immune Cell ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Clinical Samples ◽

Immune Cell Infiltration ◽

Breast Cancer Patients ◽

Gene Signatures ◽

Immune Phenotypes ◽

Processing Stability

The N6-methyladenosine (m6A) has been considered as a new layer of epitranscriptomic regulation on mRNA processing, stability, and translation. However, potential roles of m6A RNA methylation modification in tumor immune microenvironment (TIME) of breast cancer are yet fully understood. In this study, we comprehensively evaluated the genetic variations and transcript expressions of 15 m6A regulators in 1,079 breast cancer samples from the Cancer Genome Atlas (TCGA) database. We validated major regulators had significantly differential mRNA and protein expression in tumor tissue compared to normal tissues from 39 pairs of clinical breast cancer samples with different molecular subtypes, and especially high expression of m6A readers YTHDF1 and YTHDF3 predicted poor survival. Two clusters of breast cancer patients identified by the 15 m6A regulators’ pattern showed distinct overall survival, immune activation status, and immune cell infiltration, and clinical samples confirmed the diversity of lymphocytic infiltration. The profiles of these two clusters accorded with that of two classical cancer-immune phenotypes, immune-excluded and immune-inflamed phenotypes, it suggested that m6A regulators-based patterns might serve as crucial mediators of TIME in breast cancer. Moreover, the m6A phenotype-related gene signatures could also be survival predictor in breast cancer. Therefore, comprehensive evaluation of tumor m6A modification pattern will contribute to enhance our understanding of the characterization of immune cell infiltration in the tumor microenvironment and promote the responsiveness of breast cancer to immunotherapy.

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Tumor Microenvironment Subtypes and Immune-Related Signatures for the Prognosis of Breast Cancer

BioMed Research International ◽

10.1155/2021/6650107 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Yiqun Han ◽

Jiayu Wang ◽

Binghe Xu

Keyword(s):

Breast Cancer ◽

Clinical Practice ◽

Tumor Microenvironment ◽

Prognostic Model ◽

Cox Regression ◽

Molecular Taxonomy ◽

The Cancer Genome Atlas ◽

Molecular Heterogeneity ◽

Consensus Clustering ◽

Breast Cancer Patients

Objective. To better understand the immune-related heterogeneity of tumor microenvironment (TME) and establish a prognostic model for breast cancer in clinical practice. Methods. For the 2620 breast cancer cases obtained from The Cancer Genome Atlas and the Molecular Taxonomy of Breast Cancer International Consortium, the CIBERSORT algorithm was performed to identify the immunological pattern, which underwent consensus clustering to curate TME subtypes, and biological profiles were explored by enrichment analysis. Random forest analysis, least absolute shrinkage, and selection operator analysis, in addition to uni- and multivariate COX regression analyses, were successively employed to precisely select the significant genes with prediction values for the introduction of the prognostic model. Results. Three TME subtypes with distinct molecular and clinical features were identified by an unsupervised clustering approach, of which the molecular heterogeneity could be the result of cell cycle dysfunction and the variation of cytotoxic T lymphocyte activity. A total of 15 significant genes were proposed to construct the prognostic immune-related score system, and a predictive model was established in combination with clinicopathological characteristics for the survival of breast cancer patients. For immunological signatures, proactivity of CD8 T lymphocytes and hyperangiogenesis could be attributed to heterogeneous survival profiles. Conclusions. We developed and validated a prognostic model based on immune-related signatures for breast cancer. This promising model is justified for validation and optimized in future clinical practice.

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Comprehensive Analysis of the Immune and Prognostic Implication of TRIM8 in Breast Cancer

10.21203/rs.3.rs-1152767/v1 ◽

2021 ◽

Author(s):

Cheng Yan ◽

Qingling Liu ◽

Mingkun Nie ◽

Wei Hu ◽

Ruoling Jia

Keyword(s):

Breast Cancer ◽

Cox Regression ◽

Molecular Taxonomy ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Survival Prediction ◽

Mrna Levels ◽

Breast Cancer Patients ◽

Prognostic Signature ◽

Normal Tissues

Abstract Background: Breast cancer remains one of most lethal illnesses for female and the most common malignancies among women, making it important to discover novel biomarkers and therapeutic targets for breast cancer. Immunotherapy has become a promising therapeutic tool for breast cancer. The role of TRIM8 in breast cancer has rarely been reported. Method: Here we identified TRIM8 expression and its potential functions on survival in patients with breast cancer using TCGA (The cancer genome atlas), GEO (Gene expression omnibus) database and METABRIC (Molecular Taxonomy of Breast Cancer International Consortium). Then, TIMER and TISIDB databases were used to investigate the correlations between TRIM8 mRNA levels and immune characteristics. Using stepwise cox regression, we established an immune prognostic signature based on five differentially expression immune-related genes (DE-IRGs). Finally, a nomogram, accompanied by a calibration curve was proposed to predict 1-, 3-, and 5-year survival for breast cancer patients. Results: We found that TRIM8 expression was dramatically lower in breast cancer tissues in comparison with normal tissues. Lower TRIM8 expression was related with worse prognosis in breast cancer. TIMER and TISIDB analysis showed that there were strong correlations between TRIM8 expression and immune characteristics. The receiver operating characteristic (ROC) curve confirmed the good performance in survival prediction, showing good accuracy of the immune prognostic signature. We demonstrated the model usefulness of predictions by nomogram and calibration curves. Our findings indicated that TRIM8 might be a potential link between progression and prognosis survival of breast cancer.Conclusion: This is a comprehensive study to reveal that TRIM8 may serve as a potential prognostic biomarker associating with immune characteristics and provide a novel therapeutic target for the treatment of breast cancer.

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Hypoxia-Associated Prognostic Markers and Competing Endogenous RNA Co-Expression Networks in Breast Cancer

Frontiers in Oncology ◽

10.3389/fonc.2020.579868 ◽

2020 ◽

Vol 10 ◽

Author(s):

Peng-Ju Gong ◽

You-Cheng Shao ◽

Si-Rui Huang ◽

Yi-Fan Zeng ◽

Xiao-Ning Yuan ◽

...

Keyword(s):

Breast Cancer ◽

T Cell ◽

Prognostic Markers ◽

Immune Cell ◽

Tumor Hypoxia ◽

Gene Expression Signature ◽

The Cancer Genome Atlas ◽

Breast Cancer Patients ◽

Related Gene ◽

Primary Tumors

ObjectiveMany primary tumors have insufficient supply of molecular oxygen, called hypoxia. Hypoxia is one of the leading characteristics of solid tumors resulting in a higher risk of local failure and distant metastasis. It is quite necessary to investigate the hypoxia associated molecular hallmarks in breast cancer.Materials and MethodsAccording to the published studies, we selected 13 hypoxia related gene expression signature to define the hypoxia status of breast cancer using ConsensusClusterPlus package based on the data from The Cancer Genome Atlas (TCGA). Subsequently, we characterized the infiltration of 24 immune cell types under different hypoxic conditions. Furthermore, the differentially expressed hypoxia associated microRNAs, mRNAs and related signaling pathways were analyzed and depicted. On this basis, a series of prognostic markers related to hypoxia were identified and ceRNA co-expression networks were constructed.ResultsTwo subgroups (cluster1 and cluster2) were identified and the 13 hypoxia related gene signature were all up-regulated in cluster1. Thus, we defined the cluster1 as “hypoxic subgroup” compared with cluster2. The infiltration of CD8+ T cell and CD4+ T cell were lower in cluster1 while the nTreg cell and iTreg cell were higher, indicating that there was immunosuppressive status in cluster1. We observed widespread hypoxia-associated dysregulation of microRNAs and mRNAs. Next, a risk signature for predicting prognosis of breast cancer patients was established based on 12 dysregulated hypoxia associated prognostic genes. Two microRNAs, hsa-miR-210-3p and hsa-miR-190b, with the most significant absolute logFC value were related to unfavorable and better prognosis, respectively. Several long non-coding RNAs were predicted to be microRNA targets and positively correlated with two selected mRNAs, CPEB2 and BCL11A. Predictions based on the SNHG16-hsa-miR-210-3p-CPEB2 and LINC00899/PSMG3-AS1/PAXIP-AS1-hsa-miR-190b-BCL11A ceRNA regulation networks indicated that the two genes might act as tumor suppressor and oncogene, respectively.ConclusionHypoxia plays an important role in the initiation and progression of breast cancer. Our research provides potential mechanisms into molecular-level understanding of tumor hypoxia.

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Molecular and clinical characterization of CCT2 expression at transcriptional level via 2994 samples of breast cancer

10.21203/rs.3.rs-44221/v1 ◽

2020 ◽

Author(s):

Qiang Liu ◽

Yihang Qi ◽

Xiangyu Wang ◽

Xiangyi Kong ◽

Yi Fang ◽

...

Keyword(s):

Breast Cancer ◽

Survival Analysis ◽

Molecular Taxonomy ◽

Prognostic Significance ◽

The Cancer Genome Atlas ◽

Transcriptional Level ◽

Breast Cancer Patients ◽

Luminal A ◽

Her2 Positive ◽

Worse Prognosis

Abstract BackgroundMolecular chaperones play important roles in regulating various cellular processes and malignant transformation. Expression of some subunits of molecular chaperonen CCT/TRiC complex have been reported to be correlated with cancer development and patient survival. However, little is known about the expression and prognostic significance of Chaperonin Containing TCP1 Subunit 2 (CCT2), a gene encoding a molecular chaperone that is a member of the chaperonin containing TCP1 complex (CCT), also known as the TCP1 ring complex (TRiC).MethodThrough the Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases, we systematically reviewed a total of 2994 cases with transcriptome data and analyzed the functional annotation of CCT2 by Gene ontology (GO) and KEGG analysis. Univariate and multivariate survival analysis were performed to investigate the prognostic value of CCT2 in breast cancer.ResultsWe found CCT2 was significantly upregulated in various tumors. In breast cancer, CCT2 expression was significantly upregulated in HER2-positive (HER2+) group, and more malignant group. In addition, we investigated correlations between CCT2 and other CCT members. Interestingly, almost all CCTs expression were positively correlated with each other, but not CCT6B. Survival analysis suggested that CCT2 overexpression was independently associated with worse prognosis of patients with breast cancer, especially in luminal A subtype.ConclusionIn summary, our results revealed that CCT2 might be involved in regulating cell cycle pathway, and independently predicted worse prognosis in breast cancer patients. These findings may expand understanding of potential anti-CCT2 treatments. To our knowledge, this is the largest and most comprehensive study characterizing the expression pattern of CCT2 together with its prognostic values in breast cancer.

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CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer

Scientific Reports ◽

10.1038/s41598-021-83913-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kelly E. Craven ◽

Yesim Gökmen-Polar ◽

Sunil S. Badve

Keyword(s):

Breast Cancer ◽

T Cells ◽

Triple Negative Breast Cancer ◽

Molecular Mechanisms ◽

Triple Negative ◽

Immune Cell ◽

Molecular Taxonomy ◽

The Cancer Genome Atlas ◽

Activated T Cells ◽

Cancer Immunoediting

AbstractStudies have shown that the presence of tumor infiltrating lymphocytes (TILs) in Triple Negative Breast Cancer (TNBC) is associated with better prognosis. However, the molecular mechanisms underlying these immune cell differences are not well delineated. In this study, analysis of hematoxylin and eosin images from The Cancer Genome Atlas (TCGA) breast cancer cohort failed to show a prognostic benefit of TILs in TNBC, whereas CIBERSORT analysis, which quantifies the proportion of each immune cell type, demonstrated improved overall survival in TCGA TNBC samples with increased CD8 T cells or CD8 plus CD4 memory activated T cells and in Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) TNBC samples with increased gamma delta T cells. Twenty-five genes showed mutational frequency differences between the TCGA high and low T cell groups, and many play important roles in inflammation or immune evasion (ATG2B, HIST1H2BC, PKD1, PIKFYVE, TLR3, NOTCH3, GOLGB1, CREBBP). Identification of these mutations suggests novel mechanisms by which the cancer cells attract immune cells and by which they evade or dampen the immune system during the cancer immunoediting process. This study suggests that integration of mutations with CIBERSORT analysis could provide better prediction of outcomes and novel therapeutic targets in TNBC cases.

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