ABSTRACT
Purpose@#In this study, we aimed to establish humanized patient-derived xenograft (PDX) models for triple-negative breast cancer (TNBC) using cord blood (CB) hematopoietic stem cells (HSCs). Additionally, we attempted to characterize the immune microenvironment of the humanized PDX model to understand the potential implications of altered tumorimmune interactions in the humanized PDX model on the behavior of TNBC cells. @*Methods@#To establish a humanized mouse model, high-purity CD34+ HSCs from CB were transplanted into immunodeficient NOD scid γ mice. Peripheral and intratumoral immune cell compositions of humanized and non-humanized mice were compared. Additionally, RNA sequencing of the tumor tissues was performed to characterize the gene expression features associated with humanization. @*Results@#After transplanting the CD34+ HSCs, CD45+ human immune cells appeared within five weeks. A humanized mouse model showed viable human immune cells in the peripheral blood, lymphoid organs, and in the tumor microenvironment. Humanized TNBC PDX models showed varying rates of tumor growth compared to that of non-humanized mice.RNA sequencing of the tumor tissue showed significant alterations in tumor tissues from the humanized models. tumor necrosis factor receptor superfamily member 11B (TNFRSF11B) is a shared downregulated gene in tumor tissues from humanized models. Silencing of TNFRSF11B in TNBC cell lines significantly reduced cell proliferation, migration, and invasion in vitro. Additionally, TNFRSF11B silenced cells showed decreased tumorigenicity and metastatic capacity in vivo. @*Conclusion@#Humanized PDX models successfully recreated tumor-immune interactions in TNBC. TNFRSF11B, a commonly downregulated gene in humanized PDX models, may play a key role in tumor growth and metastasis. Differential tumor growth rates and gene expression patterns highlighted the complexities of the immune response in the tumor microenvironment of humanized PDX models.
ABSTRACT
Purpose@#Patients with triple-negative breast cancer (TNBC) have an increased risk of distant metastasis compared to those with other subtypes. In this study, we aimed to identify the genes associated with distant metastasis in TNBC and their underlying mechanisms. @*Methods@#We established patient-derived xenograft (PDX) models using surgically resected breast cancer tissues from 31 patients with TNBC. Among these, 15 patients subsequently developed distant metastases. Candidate metastasis-associated genes were identified using RNA sequencing. In vitro wound healing, proliferation, migration, and invasion assays and in vivo tumor xenograft and metastasis assays were performed to determine the functional importance of aldo-keto reductase family 1 member C2 (AKR1C2). Additionally, we used the METABRIC dataset to investigate the potential role of AKR1C2 in regulating TNBC subtypes and their downstream signaling activities. @*Results@#RNA sequencing of primary and PDX tumors showed that genes involved in steroid hormone biosynthesis, including AKR1C2, were significantly upregulated in patients who subsequently developed metastasis. In vitro and in vivo assays showed that silencing of AKR1C2 resulted in reduced cell proliferation, migration, invasion, tumor growth, and incidence of lung metastasis. AKR1C2 was upregulated in the luminal androgen receptor (LAR) subtype of TNBC in the METABRIC dataset, and AKR1C2 silencing resulted in the downregulation of LAR classifier genes in TNBC cell lines. The androgen receptor (AR) gene was a downstream mediator of AKR1C2-associated phenotypes in TNBC cells. AKR1C2 expression was associated with gene expression pathways that regulate AR expression, including JAK-STAT signaling or interleukin 6 (IL-6). The levels of phospho-signal transducer and activator of transcription and IL-6, along with secreted IL-6, were significantly downregulated in AKR1C2-silenced TNBC cells. @*Conclusion@#Our data indicate that AKR1C2 is an important regulator of cancer growth and metastasis in TNBC and may be a critical determinant of LAR subtype features.