Literature DB >> 30317464

Gene expression profile of peripheral blood mononuclear cells may contribute to the identification and immunological classification of breast cancer patients.

Eiji Suzuki1, Masahiro Sugimoto2, Kosuke Kawaguchi3, Fengling Pu3, Ryuji Uozumi4, Ayane Yamaguchi3, Mariko Nishie3, Moe Tsuda3, Takeshi Kotake3, Satoshi Morita4, Masakazu Toi3.   

Abstract

BACKGROUND: It has been reported that the gene expression profile of peripheral blood mononuclear cells (PBMCs) exhibits a unique gene expression signature in several types of cancer. In this study, we aimed to explore the breast cancer patient-specific gene expression profile of PBMCs and discuss immunological insight on host antitumor immune responses.
METHODS: We comprehensively analyzed the gene expression of PBMCs by RNA sequencing in the breast cancer patients as compared to that of healthy volunteers (HVs). Pathway enrichment analysis was performed on MetaCoretm to search the molecular pathways associated with the gene expression profile of PBMCs in cancer patients compared with HVs.
RESULTS: We found a significant unique gene expression signature, such as the Toll-like receptor (TLR) 3- and TLR4-induced Toll/interleukin-1 receptor domain-containing adapter molecule 1 (TICAM1)-specific signaling pathway in the breast cancer patients as compared to that of healthy volunteers. Distinctive immunological gene expression profiles also showed the possibility of classifying breast cancer patients into subgroups such as T-cell inhibitory and monocyte-activating groups independent of known phenotypes of breast cancer.
CONCLUSIONS: These preliminary findings suggest that evaluation of gene expression patterns of PBMCs might be both a less invasive diagnostic procedure and a useful way to reveal immunological insight of breast cancer, including biomarkers for cancer immunotherapy, such as immune checkpoint inhibitor therapy.

Entities:  

Keywords:  Gene expression profile; Immune checkpoint molecule; Immuno-oncology; Peripheral blood mononuclear cells; RNA sequencing

Mesh:

Substances:

Year:  2018        PMID: 30317464     DOI: 10.1007/s12282-018-0920-2

Source DB:  PubMed          Journal:  Breast Cancer        ISSN: 1340-6868            Impact factor:   4.239


  9 in total

1.  Dynamic edge-based biomarker non-invasively predicts hepatocellular carcinoma with hepatitis B virus infection for individual patients based on blood testing.

Authors:  Yiyu Lu; Zhaoyuan Fang; Meiyi Li; Qian Chen; Tao Zeng; Lina Lu; Qilong Chen; Hui Zhang; Qianmei Zhou; Yan Sun; Xuefeng Xue; Yiyang Hu; Luonan Chen; Shibing Su
Journal:  J Mol Cell Biol       Date:  2019-08-19       Impact factor: 6.216

Review 2.  Regulated cell death (RCD) in cancer: key pathways and targeted therapies.

Authors:  Fu Peng; Minru Liao; Rui Qin; Shiou Zhu; Cheng Peng; Leilei Fu; Yi Chen; Bo Han
Journal:  Signal Transduct Target Ther       Date:  2022-08-13

3.  Expression pattern and clinical significance of β-catenin gene and protein in patients with primary malignant and benign bone tumors.

Authors:  Narges Khademian; Alireza Mirzaei; Ameinh Hosseini; Leila Zare; Shima Nazem; Pegah Babaheidarian; Alireza Sheikhi; Zohreh Abdolvahabi; Mostafa Ibrahimi; Khodamorad Jamshidi; Mahtab Rahbar; Vahid Salimi; Masoumeh Tavakoli-Yaraki
Journal:  Sci Rep       Date:  2022-06-08       Impact factor: 4.996

4.  The local and circulating SOX9 as a potential biomarker for the diagnosis of primary bone cancer.

Authors:  Ameinh Hosseini; Alireza Mirzaei; Vahid Salimi; Khodamorad Jamshidi; Pegah Babaheidarian; Soudabeh Fallah; Zahra Rampisheh; Narges Khademian; Zohreh Abdolvahabi; Mehrdad Bahrabadi; Mostafa Ibrahimi; Fatemeh Hosami; Masoumeh Tavakoli-Yaraki
Journal:  J Bone Oncol       Date:  2020-05-31       Impact factor: 4.072

Review 5.  Extra Virgin Olive Oil: Lesson from Nutrigenomics.

Authors:  Stefania De Santis; Marica Cariello; Elena Piccinin; Carlo Sabbà; Antonio Moschetta
Journal:  Nutrients       Date:  2019-09-04       Impact factor: 5.717

6.  Two Distinct Subtypes Revealed in Blood Transcriptome of Breast Cancer Patients With an Unsupervised Analysis.

Authors:  Wenlong Ming; Hui Xie; Zixi Hu; Yuanyuan Chen; Yanhui Zhu; Yunfei Bai; Hongde Liu; Xiao Sun; Yun Liu; Wanjun Gu
Journal:  Front Oncol       Date:  2019-10-01       Impact factor: 6.244

7.  Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer.

Authors:  Xu Yang; Geng-Xi Cai; Bo-Wei Han; Zhi-Wei Guo; Ying-Song Wu; Xiaoming Lyu; Li-Min Huang; Yuan-Bin Zhang; Xin Li; Guo-Lin Ye; Xue-Xi Yang
Journal:  NPJ Breast Cancer       Date:  2021-03-26

8.  Multi-Omics and Informatics Analysis of FFPE Tissues Derived from Melanoma Patients with Long/Short Responses to Anti-PD1 Therapy Reveals Pathways of Response.

Authors:  Saurabh K Garg; Eric A Welsh; Bin Fang; Yuliana I Hernandez; Trevor Rose; Jhanelle Gray; John M Koomen; Anders Berglund; James J Mulé; Joseph Markowitz
Journal:  Cancers (Basel)       Date:  2020-11-26       Impact factor: 6.639

Review 9.  Peripheral Blood Transcriptome in Breast Cancer Patients as a Source of Less Invasive Immune Biomarkers for Personalized Medicine, and Implications for Triple Negative Breast Cancer.

Authors:  Helena Čelešnik; Uroš Potočnik
Journal:  Cancers (Basel)       Date:  2022-01-25       Impact factor: 6.639

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.