Mouse-INtraDuctal (MIND): An In Vivo Model for Studying the Underlying Mechanisms of DCIS Malignancy

PUBLICATIONS

12/07/2021

San Antonio Breast Cancer Symposium 2021, Tempus-acknowledged —

Background: Due to widespread adoption of screening mammography, there has been a significant increase in new diagnoses of ductal carcinoma in situ (DCIS). However, DCIS prognosis remains unclear.

Methods: To address this gap, we developed an in vivo model, Mouse-INtraDuctal (MIND), by which patient-derived DCIS epithelial cells are injected intraductally and allowed to progress naturally in mice. The source of DCIS samples reflected clinical practice as predominantly high grade (70%), but also included intermediate grade (27%) and low grade (3%). Thirty-seven patient samples were injected into 202 mouse mammary glands and evaluated for invasive progression at a median duration of 9 months. The expression of clinically relevant biomarkers (ER, PR, Ki-67, HER2 and p53) on patient DCIS FFPE sections and xenografts’ extent of in vivo growth were evaluated for their utility in predicting DCIS invasive progression in the xenografts. Targeted DNA sequencing using Tempus xT oncology assay was used on patient DCIS in order to find a unique pattern of cancer-related gene mutations that predicted DCIS invasiveness in the xenografts.

Results: Similar to human DCIS, the cancer cells formed in situ lesions inside the mouse mammary ducts and mimicked all histologic subtypes including micropapillary, papillary, cribriform, solid, and comedo. Among 37 patient samples injected into 202 xenografts, at median duration of 9 months, 20 samples (54%) injected into 95 xenografts showed in vivo invasive progression while 17 (46%) samples injected into 107 xenografts remained noninvasive. Among the 20 samples that showed invasive progression in the MIND model, 9 patient samples injected into 54 xenografts exhibited a mixed pattern in which some xenografts showed invasive progression while others remained noninvasive. The mean duration of follow-up was not significantly different among the progressed, non-progressed or mixed groups (ANOVA; p-value=0.44). Among the clinically relevant biomarkers, only elevated progesterone receptor expression in patient DCIS and extent of in vivo growth in xenografts predicted an invasive outcome in the xenografts. Tempus xT oncology assay was used on 16 patient DCIS FFPE sections including eight patient DCIS that showed invasive progression (P), five patient DCIS that remained non-invasive (NP) and three patient DCIS that showed a mixed pattern (M) in the xenografts. Variant severity was called using SnpSift which is a program for identifying phenotype relevant variants and predicts the severity of SNPs based on their effect on gene expression and function. COSMIC database was also used to identify mutations with pathogenic scores >0.5. Analysis of the frequency of cancer related pathogenic mutations showed no significant differences (P=27, NP=79, M=43, Kruskal-Wallis: P value=>0.05). There were also no differences in the frequency of low, moderate or high severity mutations (P= 25 highly severe, 120 moderately severe and 50 low-severity; NP=9 highly severe, 58 moderately severe and 28 low severity; M=3 highly severe, 33 moderately severe and 14 low severity; Kruskal-Wallis; P value >0.05).

Conclusions: Highly severe and pathogenic variants in the patient’s DCIS were not associated with whether the DCIS developed into invasive lesions or remained non-invasive in the MIND models. These results are in agreement with previous studies that showed no significant differences in frequency of non-synonymous mutations and CNAs when comparing pure DCIS with synchronous IDC-DCIS. The MIND models are in immunocompromised mice, so the contribution of the immune system to DCIS progression may not recapitulate cancer progression in an immunocompetent state. However, the MIND model suggests that genetic changes in the DCIS are not the primary driver for the development of invasive disease.

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Authors: Aditi Rastogi, Jerome Lin, Yan Hong, Darlene Limback, Hanan S. Elsarraj, Haleigh Harper, Haley Haines, Hayley Hansford, Michael Ricci, Carolyn Kaufman, Emily Wedlock, Mingchu Xu, Jianhua Zhang, Lisa May, Terri Cusick, Marc Inciardi, Mark Redick, Jason Gatewood, Onalisa Winblad, Allison Aripoli, Ashley Huppe, Christa Balanoff, Jamie Wagner, Amanda Amin, Kelsey E. Larson, Lawrence Ricci, Ossama Tawfik, Hana Razek, Ruby O Meierotto, Rashna Madan, Andrew K. Godwin, Jeffrey Thompson, Susan G. Hilsenbeck, Andy Futreal, Alastair Thompson, E. Shelley Hwang, Fang Fan, Nicholas Navin, Fariba Behbod, Grand Challenge PRECISION Consortium.