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Resistance to radiotherapy is a major obstacle for effective cancer treatment. Both cancer-associated fibroblasts (CAF) within the tumor microenvironment (TME) and Notch signaling are implicated in radioresistance, but their potential interrelationship is unclear. Here, we report that irradiated samples obtained from luminal breast cancer patient tumors express higher levels of the Notch ligand Dll1 and have a greater number of αSMA- and FAP-expressing activated CAFs. Single cell transcriptomic profiles further revealed enrichment of an αSMA+ myofibroblastic subpopulation of CAF in Dll1+ tumors. In murine and human patient-derived xenograft models, Dll1+ tumor cells were more radioresistant than Dll1– tumor cells, and genetic and pharmacologic blocking of Dll1-mediated Notch signaling decreased the number of Dll1+ cancer stem cells (CSC) and CAFs and increased Dll1+ tumor cell radiosensitivity. Dll1+ cells recruited CAFs in an IL6-dependent fashion and promoted Wnt ligand secretion by Notch2/3-expressing CAFs, thereby driving Wnt/β-catenin–dependent increases in Dll1+ CSC function to promote metastasis. Treatment with the porcupine inhibitor LGK-974 that inhibits Wnt ligand secretion or pharmacologic blockade of IL6 or Dll1 suppressed CAF-dependent enhancement of Dll1+ CSC function and metastasis in radioresistant tumors. Together, these findings reveal an essential cross-talk between Dll1+ cancer cells and CAFs, which promotes metastasis and radioresistance, which could be therapeutically exploited to improve the outcome of patients with breast cancer. Significance: Dll1+ breast cancer cells activate Notch signaling in cancer-associated fibroblasts that increases Wnt ligand secretion and leads to β-catenin–driven radioresistance and metastasis, opening new therapeutic avenues for breast cancer.

Genomic analysis has recently identified multiple ESR1 gene translocations in estrogen receptor alpha–positive (ERα+) metastatic breast cancer (MBC) that encode chimeric proteins whereby the ESR1 ligand binding domain (LBD) is replaced by C-terminal sequences from many different gene partners. Here we functionally screened 15 ESR1 fusions and identified 10 that promoted estradiol-independent cell growth, motility, invasion, epithelial-to-mesenchymal transition, and resistance to fulvestrant. RNA sequencing identified a gene expression pattern specific to functionally active ESR1 gene fusions that was subsequently reduced to a diagnostic 24-gene signature. This signature was further examined in 20 ERα+ patient-derived xenografts and in 55 ERα+ MBC samples. The 24-gene signature successfully identified cases harboring ESR1 gene fusions and also accurately diagnosed the presence of activating ESR1 LBD point mutations. Therefore, the 24-gene signature represents an efficient approach to screening samples for the presence of diverse somatic ESR1 mutations and translocations that drive endocrine treatment failure in MBC.Significance:This study identifies a gene signature diagnostic for functional ESR1 fusions that drive poor outcome in advanced breast cancer, which could also help guide precision medicine approaches in patients harboring ESR1 mutations.

It includes Supplementary Methods, Supplementary Figures, Supplementary Tables, and Supplementary References

Supplementary Figures

Table S2 - Genes in immune cell clusters

Immunotherapy has potential to prevent and treat metastatic breast cancer, but strategies to enhance immune-mediated killing of metastatic tumors are urgently needed. We report that a ligand-independent isoform of Ron kinase (SF-Ron) is a key target to enhance immune infiltration and eradicate metastatic tumors. Host-specific deletion of SF-Ron caused recruitment of lymphocytes to micrometastases, augmented tumor-specific T-cell responses, and nearly eliminated breast cancer metastasis in mice. Lack of host SF-Ron caused stem-like TCF1+ CD4+ T cells with type I differentiation potential to accumulate in metastases and prevent metastatic outgrowth. There was a corresponding increase in tumor-specific CD8+ T cells, which were also required to eliminate lung metastases. Treatment of mice with a Ron kinase inhibitor increased tumor-specific CD8+ T cells and protected from metastatic outgrowth. These data provide a strong preclinical rationale to pursue small-molecule Ron kinase inhibitors for the prevention and treatment of metastatic breast cancer.Significance:The discovery that SF-Ron promotes antitumor immune responses has significant clinical implications. Therapeutic antibodies targeting full-length Ron may not be effective for immunotherapy; poor efficacy of such antibodies in trials may be due to their inability to block SF-Ron. Our data warrant trials with inhibitors targeting SF-Ron in combination with immunotherapy.This article is highlighted in the In This Issue feature, p. 2945

With the advancement of personalized cancer immunotherapies, new tools are needed to identify tumor antigens and evaluate T-cell responses in model systems, specifically those that exhibit clinically relevant tumor progression. Key transgenic mouse models of breast cancer are generated and maintained on the FVB genetic background, and one such model is the mouse mammary tumor virus-polyomavirus middle T antigen (MMTV-PyMT) mouse—an immunocompetent transgenic mouse that exhibits spontaneous mammary tumor development and metastasis with high penetrance. Backcrossing the MMTV-PyMT mouse from the FVB strain onto a C57BL/6 genetic background, in order to leverage well-developed C57BL/6 immunologic tools, results in delayed tumor development and variable metastatic phenotypes. Therefore, we initiated characterization of the FVB MHC class I H-2q haplotype to establish useful immunologic tools for evaluating antigen specificity in the murine FVB strain. Our study provides the first detailed molecular and immunoproteomic characterization of the FVB H-2q MHC class I alleles, including >8,500 unique peptide ligands, a multiallele murine MHC peptide prediction tool, and in vivo validation of these data using MMTV-PyMT primary tumors. This work allows researchers to rapidly predict H-2 peptide ligands for immune testing, including, but not limited to, the MMTV-PyMT model for metastatic breast cancer. Cancer Immunol Res; 6(6); 636–44. ©2018 AACR.

Table S1 - List of antibodies and reagents

Supplemental Table S1: AUC and PPV for NetH2pan network ensemble Supplemental Table S2: AUC and PPV for prediction of ligands by NetH2pan, trained with or without sequence context of five residues flanking the peptide. Supplemental Table S3. Yield (# of peptides) from soluble MHC transfectants and MMTV-PyMT tumors. Supplemental Table S4. Cancer-associated peptides eluted from MMTV-PyMT tumors. Supplemental Figure S1. MHC Class I peptide tissue extraction approach. Supplemental Figure S2. Peptide overlap with soluble MHC peptide elution and primary tumor cell elution. Supplemental Figure S3. MMTV-PyMT tumors express Class I MHC.

(A) 231 and 231DXR and (B) HCC and HCCDXR cells were treated with increasing concentrations of doxorubicin (50 - 350 nM) for 48h. Experiments were performed three times in triplicate. Results shown are mean {plus minus} SEM. *(p < 0.05), **(p < 0.01) and ***(p < 0.001) indicate levels of statistically significance.

cells (A) 231 and 231DXR and (B) HCC and HCCDXR cells were treated with increasing concentrations of cetuximab (0,5 - 4 µM), C75 (20 - 60 µM) or EGCG ( 25 - 150 µM) for 4 days. Results are expressed as mean {plus minus} SEM. Experiments were performed at least three times in triplicate. *(p < 0.05), **(p < 0.01) and ***(p < 0.001) indicate levels of statistically significance.

Summary of in vivo studies

Purpose: The frequently elevated activities of the c-src and c-yes products in human epithelial tumors suggest that these activated tyrosine kinases have tumorigenic functions analogous to the v-src and v-yes oncogene products. Studies of v-src–transformed fibroblasts have identified many of the effectors of this potent oncogene; however, because c-src and c-yes lack the mutational and promiscuous activities of their retroviral oncogene homologues, their presumptive tumorigenic functions in human epithelial tumors are more subtle, less well-defined, and await identification of possible effectors more directly relevant to epithelial cells.Experimental Design: We recently identified a transmembrane glycoprotein named Trask that is expressed in epithelial tissues but not fibroblasts and is phosphorylated by SRC kinases in mitotic epithelial cells. In this study, we have surveyed the expression and phosphorylation of Trask in many human epithelial cancer cell lines and surgical tissues and tumors.Results: Trask is widely expressed in human epithelial tissues, but its phosphorylation is tightly regulated and restricted to detached mitotic cells or cells undergoing physiologic shedding. However, abberant Trask phosphorylation is seen in many epithelial tumors from all stages including preinvasive, invasive, and metastatic tumors. Trask phosphorylation requires SRC kinases, and is also aberrantly hyperphosphorylated in the SRC-activated PyMT mouse epithelial tumors and dephosphorylated by the SRC inhibitor treatment of these tumors.Conclusions: The widespread phosphorylation of Trask in many human epithlelial cancers identifies a new potential effector of SRC kinases in human epithelial tumorigenesis.

(A) 231 and 231DXR and (B) HCC and HCCDXR cells were treated with doxorubicin (50-100-150nM) and C75 (20µM for HCC, HCCDXR; 40µM for 231, 231DXR) or the combination for 48h. (C) 231 and 231DXR and (D) HCC and HCCDXR cells were treated with doxorubicin (50-100-150nM), EGCG (100µM for 231, 231DXR; 120µM for HCC, HCCDXR) or the combination of both for 48h. Results shown are mean {plus minus} SEM. *(p < 0.05), **(p < 0.01) and ***(p < 0.001) indicate levels of statistically significance.

Supplementary Data from Phosphorylation of the src Epithelial Substrate Trask Is Tightly Regulated in Normal Epithelia but Widespread in Many Human Epithelial Cancers

Summary of RNA sequencing (RNA seq) data of the Met superfamily kinases in 4 breast PDX models.

Purpose: Triple-negative breast cancer (TNBC) lacks an approved targeted therapy. Despite initial good response to chemotherapy, 30% of the patients relapse within 5 years after treatment. EGFR overexpression is a common marker in TNBC, and its expression has been correlated with poor outcome. Inhibition of fatty acid synthase (FASN) activity leads to apoptosis of human carcinoma cells overexpressing FASN. We tested the hypothesis that blocking FASN in combination with anti-EGFR signaling agents would be an effective antitumor strategy in sensitive and chemoresistant TNBC.Experimental Design: Several TNBC cell lines and 29 primary tumors were included to determine whether FASN is a potential target in TNBC. Doxorubicin-resistant TNBC cell lines (231DXR and HCCDXR) have been developed and characterized in our laboratory. Cellular and molecular interactions of anti-FASN compounds (EGCG and C75) with cetuximab were analyzed. In vivo tumor growth inhibition was evaluated after cetuximab, EGCG, or the combination in TNBC orthoxenograft models.Results: TNBC cell lines showed overexpression of FASN enzyme and its inhibition correlated to FASN levels. FASN staining was observed in all of the 29 TNBC tumor samples. In vitro, EGCG and C75 plus cetuximab showed strong synergism in sensitive and chemoresistant cells. In vivo, the combination of EGCG with cetuximab displayed strong antitumor activity against the sensitive and chemoresistant TNBC orthoxenografts, without signs of toxicity.Conclusions: Our results show that the simultaneous blockade of FASN and EGFR is effective in preclinical models of sensitive and chemoresistant TNBC. Clin Cancer Res; 22(18); 4687–97. ©2016 AACR.

(A) Mice bearing 231 and (B) 231DXR xenografts were treated with saline (Control), EGCG (30mg/Kg, 3 days a week), cetuximab (0.5mg/mice 1 day a week) or the combination (EGCG plus cetuximab) for 12 days. (C) Mice bearing HCC and (D) HCCDXR xenografts were treated with saline (Control), EGCG (30mg/Kg, 3 days a week), cetuximab (100uL/mice 1 day a week) or the combination (EGCG plus cetuximab) for 10 days. Total volume is shown as (Final Volume - Initial Volume). Dots are mean of each experimental group and bars, SEM. *(p < 0.05), **(p < 0.01) and ***(p < 0.001) indicate levels of statistically significance.

A. MCF7 tumor growth rate in NOD/SCID mice implanted with beeswax E2 pellets, commercial 0.72 mg/60 days E2 pellets (Innovative Research of America) and control mice. Both, 0.72 mg/60 days E2 and beeswax E2 pellets equally supported estrogen dependent tumor growth. In contrast, control mice not supplemented with E2 pellets failed to grow tumors. B. Quantification of E2 plasma levels 10 days post implantation of E2 pellets in NOD/SCID mice. The beeswax pellets yielded mean E2 plasma levels of 84 pg/ml with very little variation, which are comparable plasma estrogen levels released from commercially available E2 pellets.

Supplementary Data from Dll1-Mediated Notch Signaling Drives Tumor Cell Cross-talk with Cancer-Associated Fibroblasts to Promote Radioresistance in Breast Cancer

(A) 231 and 231DXR and (B) HCC and HCCDXR. mRNA levels were obtained by Real-Time PCR and normalized against the β-actin gene. Results shown are mean {plus minus} SEM from 3 independent experiments.

TNBC Patients demographics and clinical characteristics (n=26).

(A) 231 and 231DXR cells were treated with increasing concentrations of EGCG ( 100 - 200 µM) or C75 (30 - 90 µM) for 48h. (B) HCC and HCCDXR cells were treated with increasing concentrations of EGCG ( 100 - 250 µM) or C75 (20 - 60 µM) for 48h. Results are expressed as mean {plus minus} SEM. Experiments were performed at least three times in triplicate.

Purpose: Recent studies have demonstrated that short-form Ron (sfRon) kinase drives breast tumor progression and metastasis through robust activation of the PI3K pathway. We reasoned that upfront, concurrent inhibition of sfRon and PI3K might enhance the antitumor effects of Ron kinase inhibitor therapy while also preventing potential therapeutic resistance to tyrosine kinase inhibitors (TKI).Experimental Design: We used patient-derived breast tumor xenografts (PDX) as high-fidelity preclinical models to determine the efficacy of single-agent or dual Ron/PI3K inhibition. We tested the Ron kinase inhibitor ASLAN002 with and without coadministration of the PI3K inhibitor NVP-BKM120 in hormone receptor–positive [estrogen receptor (ER)+/progesterone receptor (PR)+] breast PDXs with and without PIK3CA gene mutation.Results: Breast PDX tumors harboring wild-type PIK3CA showed a robust response to ASLAN002 as a single agent. In contrast, PDX tumors harboring mutated PIK3CA demonstrated partial resistance to ASLAN002, which was overcome with addition of NVP-BKM120 to the treatment regimen. We further demonstrated that concurrent inhibition of sfRon and PI3K in breast PDX tumors with wild-type PIK3CA provided durable tumor stasis after therapy cessation, whereas discontinuation of either monotherapy facilitated tumor recurrence.Conclusions: Our work provides preclinical rationale for targeting sfRon in patients with breast cancer, with the important stipulation that tumors harboring PIK3CA mutations may be partially resistant to Ron inhibitor therapy. Our data also indicate that tumors with wild-type PIK3CA are most effectively treated with an upfront combination of Ron and PI3K inhibitors for the most durable response. Clin Cancer Res; 21(24); 5588–600. ©2015 AACR.

Resistance to radiotherapy is a major obstacle for effective cancer treatment. Both cancer-associated fibroblasts (CAF) within the tumor microenvironment (TME) and Notch signaling are implicated in radioresistance, but their potential interrelationship is unclear. Here, we report that irradiated samples obtained from luminal breast cancer patient tumors express higher levels of the Notch ligand Dll1 and have a greater number of αSMA- and FAP-expressing activated CAFs. Single cell transcriptomic profiles further revealed enrichment of an αSMA+ myofibroblastic subpopulation of CAF in Dll1+ tumors. In murine and human patient-derived xenograft models, Dll1+ tumor cells were more radioresistant than Dll1– tumor cells, and genetic and pharmacologic blocking of Dll1-mediated Notch signaling decreased the number of Dll1+ cancer stem cells (CSC) and CAFs and increased Dll1+ tumor cell radiosensitivity. Dll1+ cells recruited CAFs in an IL6-dependent fashion and promoted Wnt ligand secretion by Notch2/3-expressing CAFs, thereby driving Wnt/β-catenin–dependent increases in Dll1+ CSC function to promote metastasis. Treatment with the porcupine inhibitor LGK-974 that inhibits Wnt ligand secretion or pharmacologic blockade of IL6 or Dll1 suppressed CAF-dependent enhancement of Dll1+ CSC function and metastasis in radioresistant tumors. Together, these findings reveal an essential cross-talk between Dll1+ cancer cells and CAFs, which promotes metastasis and radioresistance, which could be therapeutically exploited to improve the outcome of patients with breast cancer.Significance:Dll1+ breast cancer cells activate Notch signaling in cancer-associated fibroblasts that increases Wnt ligand secretion and leads to β-catenin–driven radioresistance and metastasis, opening new therapeutic avenues for breast cancer.

Representative co-IP Western blot showing interaction between sfRon and the p85a subunit of PI3K in MCF7-sfRon cells treated with DMSO or increasing amounts of ASALAN002, and in tumors harvested from NOD/SCID mice bearing HCI-011 (PIK3CAWT) PDX. Mice bearing PDXs received a single dose of ASLAN002 (50 mg/kg) or vehicle and tumors were harvested 3 h later. For co-immunprecipititation studies, whole-cell extracts were immunoprecipitated with anti-p85a antibody followed by Western blot with anti-Ron antibody. Results indicate that inhibition of sfRon in both MCF7 cells and PDX tumors leads to dissociation of p85a subunit of PI3K from sfRon. The mock IP represents the same conditions as the other IPs, but without inclusion of protein lysate.

XLSX file - 20K, Description and specifics regarding the ILC E2 geneset.

Supplementary Methods, Figures 1-7 from Protein Arginine Methyltransferase 5 Accelerates Tumor Growth by Arginine Methylation of the Tumor Suppressor Programmed Cell Death 4

PDF file - 89K, Expression of genes in the ILC E2 geneset in MCF-7 and MM134 cells following treatment with anti-estrogens.

PDF file - 53K, E2 regulation of ER target genes in ILC cells.

PDF file - 137K

PDF file - 165K, Cell viability assays following kinase inhibition.

Invasive lobular carcinoma (ILC) is a histologic subtype of breast cancer that is frequently associated with favorable outcomes, as approximately 90% of ILC express the estrogen receptor (ER). However, recent retrospective analyses suggest that patients with ILC receiving adjuvant endocrine therapy may not benefit as much as patients with invasive ductal carcinoma. On the basis of these observations, we characterized ER function and endocrine response in ILC models. The ER-positive ILC cell lines MDA MB 134VI (MM134) and SUM44PE were used to examine the ER-regulated transcriptome via gene expression microarray analyses and ER ChIP-Seq, and to examine response to endocrine therapy. In parallel, estrogen response was assessed in vivo in the patient-derived ILC xenograft HCI-013. We identified 915 genes that were uniquely E2 regulated in ILC cell lines versus other breast cancer cell lines, and a subset of these genes were also E2 regulated in vivo in HCI-013. MM134 cells were de novo tamoxifen resistant and were induced to grow by 4-hydroxytamoxifen, as well as other antiestrogens, as partial agonists. Growth was accompanied by agonist activity of tamoxifen on ER-mediated gene expression. Though tamoxifen induced cell growth, MM134 cells required fibroblast growth factor receptor (FGFR)-1 signaling to maintain viability and were sensitive to combined endocrine therapy and FGFR1 inhibition. Our observation that ER drives a unique program of gene expression in ILC cells correlates with the ability of tamoxifen to induce growth in these cells. Targeting growth factors using FGFR1 inhibitors may block survival pathways required by ILC and reverse tamoxifen resistance. Cancer Res; 74(5); 1463–74. ©2014 AACR.

XLSX file - 2042K, Lists for genes regulated by E2 in MM134 and SUM44 cells, and for categories of genes based on cell type specificity.

PDF file - 52K, Motif analysis of ER binding sites identified in MM134 by ChIP-seq.

XLSX file - 17K, Expression data from estrogen deprivation studies using PDX HCI-013.

Genomic analysis has recently identified multiple ESR1 gene translocations in estrogen receptor alpha–positive (ERα+) metastatic breast cancer (MBC) that encode chimeric proteins whereby the ESR1 ligand binding domain (LBD) is replaced by C-terminal sequences from many different gene partners. Here we functionally screened 15 ESR1 fusions and identified 10 that promoted estradiol-independent cell growth, motility, invasion, epithelial-to-mesenchymal transition, and resistance to fulvestrant. RNA sequencing identified a gene expression pattern specific to functionally active ESR1 gene fusions that was subsequently reduced to a diagnostic 24-gene signature. This signature was further examined in 20 ERα+ patient-derived xenografts and in 55 ERα+ MBC samples. The 24-gene signature successfully identified cases harboring ESR1 gene fusions and also accurately diagnosed the presence of activating ESR1 LBD point mutations. Therefore, the 24-gene signature represents an efficient approach to screening samples for the presence of diverse somatic ESR1 mutations and translocations that drive endocrine treatment failure in MBC. Significance: This study identifies a gene signature diagnostic for functional ESR1 fusions that drive poor outcome in advanced breast cancer, which could also help guide precision medicine approaches in patients harboring ESR1 mutations.

Patient-derived xenografts (PDXs) model human intra-tumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histological imaging via hematoxylin and eosin (H&E) staining is performed on PDX samples for routine assessment and, in principle, captures the complex interplay between tumor and stromal cells. Deep learning (DL)-based analysis of large human H&E image repositories has extracted inter-cellular and morphological signals correlated with disease phenotype and therapeutic response. Here, we present an extensive, pan-cancer repository of nearly 1,000 PDX and paired human progenitor H&E images. These images, curated from the PDXNet consortium, are associated with genomic and transcriptomic data, clinical metadata, pathological assessment of cell composition, and, in several cases, detailed pathological annotation of tumor, stroma, and necrotic regions. We demonstrate that DL can be applied to these images to classify tumor regions with an accuracy of 0.87. Further, we show that DL can predict xenograft-transplant lymphoproliferative disorder, the unintended outgrowth of human lymphocytes at the transplantation site, with an accuracy of 0.97. This repository enables PDX-specific investigations of cancer biology through histopathological analysis and contributes important model system data that expand on existing human histology repositories. We expect the PDXNet Image Repository to be valuable for controlled digital pathology analysis, both for the evaluation of technical issues such as stain normalization and for development of novel computational methods based on spatial behaviors within cancer tissues. Citation Format: Brian S. White, Xing Yi Woo, Soner Koc, Todd Sheridan, Steven B. Neuhauser, Shidan Wang, Yvonne A. Evrard, John David Landua, R Jay Mashl, Sherri R. Davies, Bingliang Fang, Maria Gabriela Raso, Kurt W. Evans, Matthew H. Bailey, Yeqing Chen, Min Xiao, Jill Rubinstein, Ali Foroughi pour, Lacey Elizabeth Dobrolecki, Maihi Fujita, Junya Fujimoto, Guanghua Xiao, Ryan C. Fields, Jacqueline L. Mudd, Xiaowei Xu, Melinda G. Hollingshead, Shahanawaz Jiwani, PDXNet consortium, Tiffany A. Wallace, Jeffrey A. Moscow, James H. Doroshow, Nicholas Mitsiades, Salma Kaochar, Chong-xian Pan, Moon S. Chen, Luis G. Carvajal-Carmona, Alana L. Welm, Bryan E. Welm, Ramaswamy Govindan, Shunqiang Li, Michael A. Davies, Jack A. Roth, Funda Meric-Bernstam, Yang Xie, Meenhard Herlyn, Li Ding, Michael T. Lewis, Carol J. Bolt, Dennis A. Dean, Jeffrey H. Chuang. A pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5407.

Metastatic breast cancer is the overwhelming cause of breast cancer mortality and is still incurable. The rapid development of immunotherapy is an exciting new area of research in metastatic breast cancer. However, the extreme immunosuppressive tumor environment poses a major challenge. A better understanding of how the immune system can be harnessed against metastatic cancer is required to improve patient outcomes. We previously showed that expression of the receptor tyrosine kinase Ron in the host, rather than Ron's tumor expression, contributed to tumor-associated immunosuppression and duo inhibition of Ron and CTLA-4 significantly reduced metastatic outgrowth. However, the actual mechanism remains unclear. The present study provides evidence that the N-terminal truncated isoform, short-form Ron (SF-Ron), is the major contributor in suppressing the anti-tumor immune responses and promoting metastatic outgrowth. Genetic deletion of host SF-Ron nearly eliminated breast cancer metastasis in mice, lead to systemic immune-activation, increased recruitment of lymphocytes to the site of metastasis, and augmented tumor-specific T-cell responses. Lack of SF-Ron also leads to the accumulation of CD4+ T-cells in the metastatic lungs and endowed with anti-tumor potential. Importantly, mice treated with small molecule Ron kinase inhibitor that targets both Ron and SF-Ron, produced significantly higher, active, tumor-specific CD8+ T-cells. Our study indicates that blocking Ron, especially the SF-Ron, remodels the metastatic lung microenvironment to enhance anti-tumor immunity. This study sheds light on the potential non-redundant roles of full-length and SF-Ron isoforms in mediating breast cancer metastasis and anti-tumor immune responses; and highlights the relevance of combining Ron inhibitors with immunotherapeutic agents to potentially improve treatment efficacy for metastatic breast cancer patients. Citation Format: Shu-Chin Alicia Lai, Harika Gundlapalli, Huseyin A Ekiz, Alana L Welm. Inhibition of short-form ron eliminates breast cancer metastases through an immune-mediated mechanism [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS17-24.

The bone is the most common site of metastasis and the usual first site of recurrence in metastatic breast cancer. Bone metastasis is incurable and causes severe pain with significant bone loss in breast cancer patients. Current treatments for bone metastasis aim to diminish bone loss; however, most patients still progress on current therapies, making it critical to identify new therapeutic targets. We have identified the receptor Recepteur d'Origine Nantais (RON) as a target for treating metastatic breast cancer. RON is the receptor for the macrophage stimulating protein (MSP) and has both tumor-intrinsic and -extrinsic roles in metastasis. The gene encoding RON (MST1R in human or Stk in mouse) gives rise to two transcripts coding for full-length RON (FL-RON) and short-form RON (SF-RON) isoforms, where SF-RON lacks the ligand-binding domain for MSP and is constitutively active. In mouse breast cancer lung metastasis models, deletion of kinase activity from both isoforms of RON in the host nearly eradicates tumors through increased anti-tumor immunity. More recently, we identified SF-RON as the main isoform mediating tumor-associated immunity in these models, with loss of SF-RON promoting increased anti-tumor T cell activity. In the bone, loss of kinase activity from both isoforms of RON protects against bone loss, but its role in anti-tumor immunity is unknown. We now aim to delineate the role of SF-RON-mediated anti-tumor immune responses in the bone, where immunotherapy has been less effective. In SF-RON knockout mice (RonSF-/-), tumor cells injected into the bone grow for a short time but are undetectable by endpoint. Preliminary analyses suggest the importance of immune-mediated clearance in the loss of tumors in RonSF-/- mice as depletion of CD8+ T cells rescued tumor growth by approximately 50%. To gain insight into the role of immune cell populations in this anti-tumor response, we utilized immunohistochemistry and flow cytometry to characterize specific immune cells in bone metastasis. Initial results suggest increased infiltration of T cells, B cells, and NK cells into the tumors in the bones of RonSF-/- mice compared to wild-type controls. Notably, these immune cell populations are all known to play a significant role in the anti-tumor response in other models. Future work will utilize depletion studies to further investigate the role of T cells, B Cells, and NK cells in SF-RON-mediated tumor clearance in the bone. This work will help elucidate a role for host SF-RON in breast cancer bone metastasis and its potential to be a potent immunotherapy target for the treatment of bone metastasis. Citation Format: Clint H Valencia, Jaime Fornetti, Alana L Welm. Defining the immune milieu in short-form RON-mediated tumor clearance in breast cancer bone metastasis [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr A55.

The inclusion of patient advocates in basic cancer research has emerged as a valuable practice to ensure research is intentional, to support effective communication with broader audiences, and to directly connect researchers with those whom they are striving to help. Despite this value, many researchers do not work with patient advocates. To understand why and build a roadmap for more engagement in the future, we hosted a workshop with patient advocates and research scientists then presented findings and discussed further at an international conference. We acknowledged four main barriers: 1) It is not clear to everyone why patient advocates should be included in research, 2) Researchers are worried about saying the wrong thing, 3) Researchers do not know where to meet patient advocates, and 4) Researchers do not know how to include patient advocates in research. We identified best practices from various organizations and opportunities to overcome these barriers in the short- and long-term. This is the first time a multi-stakeholder group has come together to provide ways to support research scientists with overcoming barriers to regularly working with patient advocates. Ultimately, these relationships will improve cancer research and more quickly accomplish our collective goal of improving lives of those who have been diagnosed with cancer. Citation Format: Hillary Stires, Igor Bado, Thelma Brown, Martha Carlson, Isaac S. Chan, Gloria V. Echeverria, Andrew J. Ewald, Carla Lloyd, Julia Maues, Steffi Oesterreich, Robert N. Riter, Kelly Shanahan, Alana L. Welm, Josh Newby. A framework for research scientists to include patient advocates in cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1014.

Selection of the treatments most likely to combat a patient’s tumor is a central aim of precision oncology. We are currently developing a functional precision oncology program at the University of Utah and Huntsman Cancer Institute that combines the multi-omic characterization of a patient's tumor with the functional screening of relevant drug candidates in patient-derived organoid tumor models to identify which drugs are uniquely capable of combating the patient’s cancer. Here we present our model-based approach for utilizing the multi-omic tumor data to computationally predict the patient’s response to each drug. In this approach, we first identify the genomic and transcriptomic vulnerabilities of the tumor as genes harboring somatic DNA mutations or copy number changes (from paired tumor/normal WGS/WES DNA sequencing data), as well as genes whose expression levels have been significantly altered in the tumor (based on bulk or single-cell RNA sequencing data). Second, using targeting information from drug-gene interaction databases (DGIdb) we compile a list of genes targeted by each drug relevant in the patient’s treatment. Third, we utilize gene interaction database knowledge (KEGG) to construct a gene interaction graph to link each drug’s gene targets with all of the tumor’s vulnerability genes. We then identify all gene interaction paths connecting specific drug target genes with specific vulnerability genes; and score each path and combine all path-specific scores for the target-vulnerability gene pair. Subsequently, we further combine all pairwise scores across all drug target genes and all tumor vulnerability genes and determine the statistical significance of the resulting score by sampling the background distribution of such scores across random drugs, target genes, and vulnerability genes. We have applied our algorithm to predict drug response in advanced breast cancer patients as well as using publicly available tumor cell line data (GDSC2). We have found a high level of concordance between our computational prediction and organoid/cell line screening results, clearly separating sensitive and non-sensitive models. Using Bayesian probability, we compare the drug-specific score distributions of sensitive and non-sensitive models and are able to identify sensitive cell lines/patients with high accuracy. By encapsulating available information on direct gene-gene interactions, the drug’s direct gene targets and the collected omic vulnerabilities of the tumor, our model is not only capable of predicting sensitivity to both targeted and chemotherapy agents, but can also provide a mechanistic understanding for the targeting of the tumor. Our approach will be validated and fine-tuned on a large cohort of breast and brain cancer patients as well as patient PDX models, interrogating gene-target interactions to identify novel relevant target genes/pathways. Citation Format: Szabolcs Tarapcsak, Yi Qiao, Xiaomeng Huang, Tony Di Sera, Matthew H. Bailey, Bryan E. Welm, Alana L. Welm, Gabor T. Marth. Model-based cancer therapy selection by linking tumor vulnerabilities to drug mechanism [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2723.

CDK4/6 inhibitors (CDK4/6i) in combination with antiestrogens have revolutionized the treatment of ER+ metastatic breast cancer (MBC), significantly prolonging survival. However, this combination is not curative, and tumors eventually acquire resistance. Following progression on this combination, patients are left with limited treatment options. A diverse array of mechanisms of resistance to CDK4/6i + antiestrogens have been described. However, laboratory models that capture this heterogeneity of resistance mechanisms are lacking. Patient-derived organoids (PDOs) provide a rapid, robust and reliable platform that recapitulates intra-tumor heterogeneity, partially mimics the cancer microenvironment, and accurately predicts drug response. We aspired to generate a platform of CDK4/6i-resistant breast cancer PDOs to serve as models for understanding acquired resistance to CDK4/6i + antiestrogens and identifying therapies to overcome resistance. We successfully established 16 PDOs out of 32 biopsies (50% efficiency) of metastates from patients with ER+ MBC progressing on CDK4/6i (palbociclib or abemaciclib) + antiestrogens (letrozole or fulvestrant; median response to combination = 9 months). Our collection includes PDOs derived from lobular (n=3) and inflammatory (n=2) breast cancers and reflects racial/ethnic diversity (50% white/not Hispanic; 18.8% Hispanic; 12.5% Black; 12.5% other/unknown). Next-gen sequencing reports were available for 10 patients from which organoids were established, revealing alterations associated with CDK4/6i and/or antiestrogen resistance, including ESR1 (n=2), HER2/ERBB2 (n=2), PTEN (n=2), CCNE1 (n=1), NF1 (n=1), and ARID1A (n=1). Furthermore, one biopsy and its derived organoid lost ER expression, and 5 harbored PIK3CA activating mutations. Thus far, we have performed targeted DNA-sequencing on 7 PDOs and found 13/15 (86.7%) concordance with driver mutations from tumor NGS reports. PDOs established from CDK4/6i-resistant biopsies maintained resistance to palbociclib or abemaciclib ± fulvestrant (500 nM each) in 3D cell viability assays (6 days of treatment). In contrast, control PDOs established from primary ER+ breast cancer surgical samples (n=2) were sensitive to each CDK4/6i ± fulvestrant (median viability for combination=25.6-31.5% for control vs 65.2-80.5% for resistant). GSEA analysis of RNA-seq data from control (n=2) and CDK4/6i-resistant (n=6) PDOs cultured in estrogen-depleted media ± 200 nM palbociclib revealed that palbociclib treatment resulted in downregulation of E2F target and G2M checkpoint signatures in control but not resistant PDOs. Next, we performed a high-throughput screen of 1,000 compounds in 3 resistant PDOs. One PDO showed exquisite sensitivity to G2/M cell cycle checkpoint components, including CDK1, PLK1, Aurora kinase, ATR, Chk1, and Wee1 inhibitors. Finally, treatment of 10 resistant PDOs with the CDK2/4/6 inhibitor PF-06873600 revealed that the CCNE1 (cyclin E1)-amplified PDO was highly sensitive (IC50=130 nM vs >1000 nM), supporting that CCNE1-amplified tumors are vulnerable to CDK2 inhibition. Conclusions: PDOs can be successfully established from ER+ MBC biopsies, maintain the resistant phenotype in culture, retain driver alterations found in tumors from which they were derived, and fail to suppress E2F targets following treatment with CDK4/6i. Therefore, these PDOs represent valuable models to understand and explore diverse mechanisms of CDK4/6i resistance and therapeutic vulnerabilities. Citation Format: Ariella B. Hanker, Sumanta Chatterjee, Yunguan Wang, Dan Ye, Dhivya R. Sudhan, Brian M. Larsen, Lauren C. Smith, Yilin Zhang, Vishal Kandagatla, Kuntal Majmudar, Ezequiel Renzulli, Saurabh Mendiratta, Kimberly Blackwell, Alana L. Welm, Sunati Sahoo, Nisha Unni, Cheryl M. Lewis, Tao Wang, Ameen A. Salahudeen, Carlos L. Arteaga. A platform of CDK4/6 inhibitor-resistant patient-derived breast cancer organoids illuminates mechanisms of resistance and therapeutic vulnerabilities [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD2-01.

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.

Patient derived xenografts (PDX) are valuable, clinically-relevant models of cancer. Their close genomic, phenotypic, and temporal association with patient tumors makes them well-suited for pre-clinical and co-clinical studies that assess the potential of new therapeutics. However, PDX models are not amenable to large-scale drug sensitivity studies or real-time precision oncology due to their relatively slow growth, high cost, and low throughput. To address this, we established and characterized organoid lines from breast cancer patient tumors and PDXs and evaluated their fidelity to the original tumors and their utility in high-throughput therapeutic studies. Results of comparisons between in vitro and in vivo patient-derived models of breast cancer will be presented, along with extension of this technology to inform patient care in an IRB-approved study of precision oncology. Our work demonstrates that breast cancer organoid models are a powerful parallel resource to PDX models, especially useful for efficient determination of drug responses, and are amenable to informing real-time patient care in a functional precision oncology setting. Citation Format: Alana L. Welm. Using patient-derived models for functional precision oncology in advanced breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr SY16-02.

Background: Endocrine therapy resistance is common and is a leading cause of breast cancer-related death. Thus, the search for therapeutic targets based on mechanistic insights into endocrine therapy resistance continues. Kinases are important drug targets and regulators in cells, many of which are involved in tumorigenesis and the development of treatment resistance. Mass spectrometry-based kinome analysis has been impeded by the low abundance of individual kinases. Here we utilized kinase inhibitor-conjugated beads to enrich and thereby sensitively profile the kinome of estrogen receptor-positive (ER+) breast cancer patient-derived xenograft (PDX) tumors under estradiol-deprivation treatment. Experimental design and methods: We harvested tumor samples from 20 breast PDX lines with various degrees of estradiol (E2) dependence in ovariectomized SCID-beige mice with and without E2 supplementation (n=3 per PDX line per arm). The kinases in the tumor lysates were enriched using kinase inhibitor pulldown (KIP) beads and the tightly bound kinases were quantified by mass spectrometry. To identify candidates, we selected for kinases that were highly E2-regulated in the E2-dependent PDX lines but constitutively expressed in E2-independent PDX lines. Survival analysis of candidate kinases in patients with ER+ breast cancer was performed using the METABRIC dataset. Results: Each PDX line had a unique yet reproducible kinome. To seek kinases with consistent relationships with estrogen dependence, we sought kinases that were statistically differentially expressed in tumors between E2 supplied and deprived conditions. Noticeably, membrane-associated tyrosine-and threonine-specific cdc2-inhibitory kinase (PKMYT1), a WEE family kinase known to have estrogen response elements (EREs) in its regulatory region, was significantly decreased after E2 deprivation in E2-dependent PDXs (log2 fold change = -7.86, p Conclusion: Here, we analyzed the kinomes of 20 ER+ breast cancer PDX tumors with or without E2 by mass spectrometry. We discovered that PKMYT1 is a marker of hormone independent growth and poor outcome. Ongoing experiments that study the effects of PKMYT1 inhibition in both ER-dependent and independent circumstances will be presented. Citation Format: Anran Chen, Beom-Jun Kim, Doug W Chan, Purba Singh, Lacey E Dobrolecki, Jonathan T Lei, Shunqiang Li, Alana L Welm, Michael T Lewis, Matthew J Ellis. Kinome profiling of ER+ breast cancer PDXs identifies PKMYT1 as a marker of hormone independent growth and poor outcome [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD8-02.

Background: Predicting the risk of relapse in patients with non-metastatic breast cancer is important for medical decisions and patient counseling. For patients who receive neoadjuvant chemotherapy, pathologic response and especially pathologic complete response (pCR) has been associated with risk of relapse; however this association is imperfect. Our prior work in patient-derived xenograft (PDX) models indicated that tumor engraftment in mice correlated with risk of recurrence. To understand further the prognostic utility of PDX, we designed a prospective clinical trial to determine the correlation between PDX generation with residual disease following neoadjuvant chemotherapy and relapse. Preliminary data are presented. Methods: Women with newly diagnosed non-metastatic hormone receptor low-positive (HR-low, ER and/or PR ≤ 10%) or negative breast cancer planned to receive systemic chemotherapy prior to definitive surgery were eligible. Tumor tissue at diagnosis was orthotopically implanted in NOD/SCID mice. The primary objective of the study is to correlate the ability of a tumor to engraft in mice with pathologic responses and clinical outcomes. Results: Between 12/2016 and 2/2020, 58 patients enrolled (triple negative breast cancer (TNBC), n=37; HR-low or negative/Her2+, n=11; or HR-low/Her2-, n=8; mixed, n=1). PDXs were successfully established from 16 patients. Patients uniformly received intensive preoperative chemotherapy per standard of care. Among the 12 patients whose tumors engrafted in mice (PDX(+)) and underwent surgery, the pCR rate was 41.7%. In the subgroup of patients with postoperative follow up >6 months (n=9), 3 patients had achieved a pCR, 1 of whom recurred; and 6 patients had residual disease, 3 of whom recurred (overall relapse rate 44.4%). All patients who relapsed (TNBC n=3; HR-low/Her2- n=1), experienced a very early relapse ( Among the 38 patients whose tumors did not engraft (PDX(-)) and underwent surgery, the overall pCR rate was 60.6%. In the subgroup of patients with postoperative follow up >6 months (n=30), 18 patients had achieved a pCR of whom none recurred, and 12 had residual disease of whom 1 patient (with TNBC) had locoregional recurrence 35.1 months after her definitive surgery (relapse rate 3.3%). She underwent repeat surgery followed by radiation therapy and 5.5 months after her recurrence, she remains disease-free. Achievement of pCR was not statistically different between the PDX(+) and PDX(-) group. In the entire cohort, the presence of residual disease was associated with high risk of relapse (22.2%) as compared to the achievement of pCR (4.8%, p = 0.16). However, successful tumor engraftment was associated not only with a higher risk of relapse (44.4% vs 3.3%, p = 0.0068, odds ratio 20.45), but also an early and exceptionally aggressive relapse. Conclusion. Our functional studies not only identify a patient population with a high risk of relapse with greater precision than the achievement of pCR, but also identify patients whose relapse has a particularly aggressive natural history. We established models that recapitulate this aggressive disease and in-depth genomic studies are underway. These studies will lead us to better patient stratification on the basis of risk of relapse and novel therapeutic strategies focused on patients with exceptionally aggressive breast cancers that our current diagnostic methods cannot identify. Citation Format: Christos Vaklavas, Zhengtao Chu, Rachel E Factor, Alana L Welm, Bryan E Welm, Cindy B Matsen. Towards personalized medicine - patient-derived breast tumor grafts as predictors of relapse and response to therapy. Preliminary results [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD7-01.

Although the RAF>MEK>ERK MAP kinase pathway is key to the development of many RAS-mutated cancers, efforts to target this pathway with pharmacologic inhibitors have failed to deliver clinical benefit to patients. Here we show that inhibition of RAS>RAF>MEK>ERK signaling in RAS-mutated cancer cell lines elicits autophagy, a process of cellular recycling that protects cancer cells from the potentially cytotoxic effects of RAF>MEK>ERK pathway inhibition. Furthermore, combined inhibition of MEK1/2 plus autophagy displays synergistic antiproliferative effects against cell lines in vitro and promotes regression of xenografted patient-derived tumors in mice. Finally, treatment of a cancer patient with the combination of trametinib plus hydroxychloroquine resulted in a partial, but nonetheless striking, disease response. These data suggest that this combination therapy may represent a novel strategy to target RAS-driven malignancies such as melanoma, lung, and pancreatic cancer. Citation Format: Conan Kinsey, Soledad Camolotto, Amelie Boespflug, Katrin Gullien, Amanda Truong, Mona Foth, Jill Shea, Michael Seipp, Jeffrey Yap, Lance Burrell, David Lum, Jonathan Whisenant, Courtney Cavalier, Kaitren Rehbein, Stephanie Cutler, Kajsa Afotler, Alana Welm, Bryan Welm, Courtney Scaife, Eric Snyder, Martin McMahon. Targeting MEK1/2 inhibitor resistance in RAS-mutated cancers [abstract]. In: Proceedings of the AACR Special Conference on Melanoma: From Biology to Target; 2019 Jan 15-18; Houston, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(19 Suppl):Abstract nr IA25.

Purpose: Recent studies have demonstrated that short-form Ron (sfRon) kinase drives breast tumor progression and metastasis through robust activation of the PI3K pathway. We reasoned that upfront, concurrent inhibition of sfRon and PI3K might enhance the antitumor effects of Ron kinase inhibitor therapy while also preventing potential therapeutic resistance to tyrosine kinase inhibitors (TKI). Experimental Design: We used patient-derived breast tumor xenografts (PDX) as high-fidelity preclinical models to determine the efficacy of single-agent or dual Ron/PI3K inhibition. We tested the Ron kinase inhibitor ASLAN002 with and without coadministration of the PI3K inhibitor NVP-BKM120 in hormone receptor–positive [estrogen receptor (ER)+/progesterone receptor (PR)+] breast PDXs with and without PIK3CA gene mutation. Results: Breast PDX tumors harboring wild-type PIK3CA showed a robust response to ASLAN002 as a single agent. In contrast, PDX tumors harboring mutated PIK3CA demonstrated partial resistance to ASLAN002, which was overcome with addition of NVP-BKM120 to the treatment regimen. We further demonstrated that concurrent inhibition of sfRon and PI3K in breast PDX tumors with wild-type PIK3CA provided durable tumor stasis after therapy cessation, whereas discontinuation of either monotherapy facilitated tumor recurrence. Conclusions: Our work provides preclinical rationale for targeting sfRon in patients with breast cancer, with the important stipulation that tumors harboring PIK3CA mutations may be partially resistant to Ron inhibitor therapy. Our data also indicate that tumors with wild-type PIK3CA are most effectively treated with an upfront combination of Ron and PI3K inhibitors for the most durable response. Clin Cancer Res; 21(24); 5588–600. ©2015 AACR.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, which could impact the capacity of PDXs for faithful modeling of patient treatment response. Such results contrast with reports that have observed genomic fidelity of PDX models with respect to the originating patient tumors and from early to late passages by direct DNA measurements (DNA sequencing or SNP arrays). Here we resolve these contradicting observations by systematically evaluating CNA changes and the genes they affect during engraftment and passaging in a large, internationally collected set of PDX models, comparing both RNA and DNA-based approaches. The data collected, as part of the U.S. National Cancer Institute (NCI) PDXNet (PDX Development and Trial Centers Research Network) Consortium and EurOPDX consortium, comprises 1548 patient (PT) and PDX datasets (1451 unique samples) from 509 models derived from American, European and Asian cancer patients, spanning across 16 tumor types. By assessing copy number changes by pairwise (PT-PDX or PDX-PDX) correlation and residual analysis to control for systematic biases, our study demonstrates that prior reports of systematic copy number divergence between PTs and PDXs are incorrect, and confirms the high retention of copy number during PDX engraftment and passaging. Moreover, only a small proportion of models show large CNA discordance between the samples, suggesting that the variations observed in PDX are mainly due to rare clonal selection of individual tumors rather than murine pressures. This large scale data analysis also reveals several other findings that clarify the evolutionary process in PDXs. We do observe larger deviations between PT-PDX than in PDX-PDX comparisons, likely due to dilution of PT signal by human stromal cells. Interestingly, we found that a major contributor to the differences between PDX samples is lineage-specific drift associated with splitting of tumors into fragments during PDX propagation. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models, suggesting the lack of systematic copy number evolution driven by the PDX mouse host. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region tumor samples or intra-patient samples. Thus concerns about the genetic stability of the PDX system are likely to be less important than the spatial heterogeneity of solid tumors themselves. This result is consistent with our results on lineage effects during passaging, which indicate that intratumoral spatial evolution is the major reason for genetic drift. Our in-depth tracking of CNAs throughout PDX engraftment and passaging confirms that tumors engrafted and passaged in PDX models maintain a high degree of molecular fidelity to the original patient tumors and their suitability for pre-clinical drug testing. This work also finely enumerates the copy number profiles in hundreds of publicly available models, which will enable researchers to assess the suitability of each for individualized treatment studies. Citation Format: Xing Yi Woo, Jessica Giordano, Anuj Srivastava, Zi-Ming Zhao, Michael W. Lloyd, Roebi de Bruijn, Yun-Suhk Suh, Jong-Il Kim, Han-Kwang Yang, Charles Lee, Dennis A. Dean, Brandi Davis-Dusenbery, Yvonne A. Evrard, James H. Doroshow, Alana L. Welm, Bryan Welm, Michael T. Lewis, Bingliang Fang, Jack A. Roth, Funda Meric-Bernstam, Meenhard Herlyn, Michael Davies, Li Ding, Shunqiang Li, Ramaswamy Govindan, Claudio Isella, Jeffrey A. Moscow, Livio Trusolino, Annette Byrne, Jos Jonkers, Carol J. Bult, Enzo Medico, Jeffrey H. Chuang, PDXNET consortium & EurOPDX consortium. Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1673.