Patient-derived xenograft (PDX) mouse models involve the direct transfer of fresh human tumor samples into immunodeficient mice following surgical resection or other medical operations. Gene expression in tumors may be maintained by serial passages of tumors from mouse to mouse. These models aid research into tumor biology and pharmacology without manual manipulation of cell cultures in vitro. and are widely used in individualized cancer therapy/translational medicine, drug development and coclinical trials. PDX models exhibit higher predictive values for clinical outcomes than cell line-derived xenograft models and genetically engineered mouse models. However, PDX models are associated with certain challenges in clinical application. The present study reviewed current collections of PDX models and assessed the challenges and future directions of this field.

Background: Papillary carcinoma is an uncommon type of breast cancer. Additionally, patients with huge breast papillary carcinoma are extremely rare in clinical practice. To improve therapeutic effect on such patients, it is urgent to explore biologically and clinically relevant models of the disease to discover effective drugs. Methods: We collected surgical tumor specimens from a 63-year-old Chinese woman who has been diagnosed breast papillary carcinoma. The tumor was more than 15 cm in diameter, and applied to establish patient-derived papillary carcinoma organoids that could continuously propagate for more than 6 months. Results: The papillary carcinoma organoids matched the histological characteristics of orginal tumor by H&E staining identification, and maintained the expression of the breast cancer biomarkers by IHC, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2) and antigen Ki-67 (Ki67). In addition, we performed a 3-D drug screening to examine the effects of endocrine drugs (Fulvestrant, Tamoxifen) and targeted therapy drugs (Palbociclib, Everolimus, BKM120) on breast papillary carcinoma in the mimic in vivo environment. The drug sensitivities of our breast papillary carcinoma organoids were investigated as follows, Fulvestrant (IC 50 0.275 μmol), Palbociclib (IC 50 2.21 μmol), BKM120 (IC 50 3.81 μmol), Everolimus (IC 50 4.45 μmol), Tamoxifen (IC 50 19.13 μmol). Conclusions: These results showed that an effective organoid platform for 3-D in vitro culture of breast cancer organoids from patients with breast papillary carcinoma could be used to identify possible treatments, and might be commonly applied to explore clinicopathological characteristics of breast papillary carcinoma.

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BACKGROUND: ESR1 mutations are frequently detected in ER+ MBC, and have been reported to be associated with endocrine therapy resistance. However, there are little researches to validate whether dynamic monitoring of ESR1 mutations could serve as a predictive plasma biomarker of acquired resistance to endocrine therapy. Therefore, in this study, we performed longitudinal circulating tumor DNA (ctDNA) detection to evaluate the clinical implications of monitoring ESR1 mutations. METHODS: We performed longitudinal dynamic mutation analyses of plasma samples from 45 patients with metastatic breast cancer (MBC) and sequencing paired biopsy tissues, using a targeted NGS panel of 425 genes. These patients were treated at the Second Affiliated Hospital of Dalian Medical University between January 2017 and February 2019 with written informed consent. RESULTS: Mutations profiles were highly concordant between plasma and paired tissue samples from 45 MBC patients (r = 0.96, P < 0.0001). ESR1 mutations were enriched in ER+ MBC patients after AI therapy (17.8%, 8/45). The median time from AI endocrine therapies to the initial detection of ESR1 mutation was 39 months (95% CI 21.32–57.57). Some hotspot mutations (Y537S (n = 5), Y537N (n = 1), D538G (n = 2), E380Q (n = 2)) and several rare mutations (L345SfsX7, 24fs, G344delinsGC) were identified in our cohort. In addition, we observed that two patients obtained multiple ESR1 mutations over the course of treatment (Y537N/Y537S/D538G, L345SfsX7/24fs/E380Q). Through dynamically monitoring ESR1 mutations by ctDNA, we demonstrated that the change of allele frequency of ESR1 mutations was an important biomarker, which could predict endocrine resistance of ER+ MBC in our study. We also observed that the combination of everolimus in four cases with acquired ESR1 mutations showed longer PFS than other therapies without everolimus. CONCLUSION: The dynamic monitoring of ESR1 mutations by ctDNA is a promising tool to predict endocrine therapy resistance in ER+ MBC patients.

Despite marked advances in breast cancer therapy, breast cancer-associated leptomeningeal metastasis (LM), a particularly aggressive syndrome with multifocal seeding of the leptomeninges by tumor cells, still carries an abysmal prognosis. A major problem with breast cancer LM surveillance is the lack of an effective and sensitive means to track dynamic changes of the disease. Cytology detection of cerebrospinal fluid (CSF) is considered the gold standard for LM diagnosis but has a high false-negative rate with a limited sensitivity. Here we applied subtraction enrichment and immunostaining-fluorescence in situ (SE-i•FISH) method, a technique previously used for isolating circulating tumor cells (CTCs) from the peripheral blood, to detect, enumerate, and track cerebrospinal fluid-derived tumor cells (CSFTCs) in CSF samples from 8 breast cancer patients. Comparing with cytology test, we found SE-i•FISH method can accurately and feasibly detect CSFTCs for the diagnosis of breast cancer-associated LM and monitor the disease progression. We also isolated and cultured CSFTCs from these cancer patients and performed genomic sequencing on CSFTCs of two patients. Genomic analysis of CSFTCs against corresponding archival primary breast tumors revealed clonal relationships with some ongoing evolution. Further drug sensitivity test on cultured CSFTCs based on genomic analysis data helped identify promising treatment options for the patient tested. Together, our results suggest that CSFTCs detection using SE-i•FISH platform could serve as a sensitive and accurate method to make the diagnosis and a promising approach to monitor tumor dynamics and treatment response for breast cancer-associated LM.