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

被引:2
|
作者
Kim, Dongjin [1 ]
Yu, Yeuni [2 ]
Jung, Ki Sun [3 ]
Kim, Yun Hak [4 ,5 ,6 ,8 ,9 ]
Kim, Jae-Joon [7 ]
机构
[1] Pusan Natl Univ, Interdisciplinary Program Genom Data Sci, Yangsan, South Korea
[2] Pusan Natl Univ, Biomed Res Inst, Sch Med, Yangsan, South Korea
[3] Pusan Natl Univ, Yangsan Hosp, Sch Med, Dept Internal Med, Yangsan, South Korea
[4] Pusan Natl Univ, Periodontal Dis Signaling Network Res Ctr, Sch Dent, Yangsan, South Korea
[5] Pusan Natl Univ, Sch Med, Dept Anat, Yangsan, South Korea
[6] Pusan Natl Univ, Sch Med, Dept Biomed Informat, Yangsan, South Korea
[7] Pusan Natl Univ, Yangsan Hosp, Dept Internal Med, Div Hematol & Oncol, 20 Geumo Ro, Yangsan 50612, South Korea
[8] Pusan Natl Univ, Dept Anat, 20 Geumo Ro, Yangsan 50612, South Korea
[9] Pusan Natl Univ, Dept Biomed Informat, 20 Geumo Ro, Yangsan 50612, South Korea
来源
CANCER RESEARCH AND TREATMENT | 2024年 / 56卷 / 01期
基金
新加坡国家研究基金会;
关键词
Key words Microbiota; Triple-negative breast neoplasms; Neoadjuvant therapy; MICROBIOME; MANAGEMENT; EXPRESSION; THERAPY;
D O I
10.4143/crt.2023.330
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose 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. Materials and Methods 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. Results 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. Conclusion 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.
引用
收藏
页码:162 / 177
页数:16
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