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Tumor Microenvironment Can Predict Chemotherapy Response of Patients with Triple-Negative Breast Cancer Receiving Neoadjuvant Chemotherapy.

Authors
  • Kim, Dongjin1
  • Yu, Yeuni2
  • Jung, Ki Sun3
  • Kim, Yun Hak4, 5, 6
  • Kim, Jae-Joon7
  • 1 Interdisciplinary Program of Genomic Data Science, Pusan National University, Yangsan, Korea. , (North Korea)
  • 2 Biomedical Research Institute, Pusan National University School of Medicine, Yangsan, Korea. , (North Korea)
  • 3 Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Korea. , (North Korea)
  • 4 Periodontal Disease Signaling Network Research Center, Pusan National University School of Dentistry, Yangsan, Korea. , (North Korea)
  • 5 Department of Anatomy, Pusan National University School of Medicine, Yangsan, Korea. , (North Korea)
  • 6 Department of Biomedical Informatics, Pusan National University School of Medicine, Yangsan, Korea. , (North Korea)
  • 7 Division of Hematology and Oncology, Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan, Korea. , (North Korea)
Type
Published Article
Journal
Cancer research and treatment
Publication Date
Jan 01, 2024
Volume
56
Issue
1
Pages
162–177
Identifiers
DOI: 10.4143/crt.2023.330
PMID: 37499695
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Triple-negative breast cancer (TNBC) is a breast cancer subtype that has poor prognosis and exhibits a unique tumor microenvironment. Analysis of the tumor microbiome has indicated a relationship between the tumor microenvironment and treatment response. Therefore, we attempted to reveal the role of the tumor microbiome in patients with TNBC receiving neoadjuvant chemotherapy. We collected TNBC patient RNA-sequencing samples from the Gene Expression Omnibus and extracted microbiome count data. Differential and relative abundance were estimated with linear discriminant analysis effect size. We calculated the immune cell fraction with CIBERSORTx and conducted survival analysis using the Cancer Genome Atlas patient data. Correlations between the microbiome and immune cell compositions were analyzed and a prediction model was constructed to estimate drug response. Among the pathological complete response group (pCR), the beta diversity varied considerably; consequently, 20 genera and 24 species were observed to express a significant differential and relative abundance. Pandoraea pulmonicola and Brucella melitensis were found to be important features in determining drug response. In correlation analysis, Geosporobacter ferrireducens, Streptococcus sanguinis, and resting natural killer cells were the most correlated factors in the pCR, whereas Nitrosospira briensis, Plantactinospora sp. BC1, and regulatory T cells were key features in the residual disease group. Our study demonstrated that the microbiome analysis of tumor tissue can predict chemotherapy response of patients with TNBC. Further, the immunological tumor microenvironment may be impacted by the tumor microbiome, thereby affecting the corresponding survival and treatment response.

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