Patient-derived Xenografts Engraftment Research Articles

TOWARDS Study: Patient-Derived Xenograft Engraftment Predicts Poor Survival in Patients With Newly Diagnosed Triple-Negative Breast Cancer.

Assessing risk of recurrence for nonmetastatic triple-negative breast cancer (TNBC) is a key determinant of therapeutic strategy. The best predictor of recurrence risk is failure to achieve a pathologic complete response after preoperative chemotherapy, but it imperfectly correlates with the definitive end points of relapse-free and overall survival (OS). The inability to accurately predict recurrence has led to increasingly toxic treatment regimens for patients with early-stage TNBC. Better assays for recurrence risk are needed to tailor aggressive therapy for patients who need it and avoid overtreatment and unnecessary toxicity for those at low risk. The purpose of this study was to determine if patient-derived xenograft (PDX) engraftment of newly diagnosed breast tumors can serve as an accurate predictor of recurrence and death from breast cancer. This study was a blinded noninterventional trial comprising 80 patients with newly diagnosed, nonmetastatic, estrogen receptor (ER)-negative or ER-low breast cancer. PDX engraftment was strongly associated with relapse in 1 year: 8 of 18 (44.4%) patients whose tumors engrafted relapsed versus 1 of 62 (1.6%) patients whose tumors did not engraft (P < .0001). Patients whose tumors engrafted had a hazard ratio (HR) for relapse of 17.5. HRs for OS and breast cancer-specific survival in PDX+ patients were 21.1 and 39.5, respectively. We report that the ability of a tumor to engraft as a PDX predicts early recurrence by serving as a functional readout of aggressiveness and prospectively identifies the most devastating tumors. This provides new opportunity to develop surrogate assays, such as biomarkers of engraftment, which will extend the clinical feasibility of this finding.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.

Abstract PO1-26-01: Leveraging Clinicopathological Factors and Deep Learning-Based Morphometrics for PDX Engraftment Success Prediction in Breast Cancer

Abstract Background: Patient-derived xenografts (PDXs) are pivotal in cancer research. Despite histopathological insights into factors driving PDX success, the role of artificial intelligence (AI) in predicting PDX engraftment remains unexplored. We aimed to bridge this gap by integrating clinicopathological data and AI-based morphometric analysis to predict PDX success in breast cancer. Methods: PDXs were generated from tumor tissues derived from breast cancer patients who had undergone surgical intervention. Clinicopathological information including subtypes, pathological diagnosis, modified Bloom-Richardson system histologic grades, treatment with neoadjuvant chemotherapy (NAC), Miller Payne grade, residual caner burden score, invasive tumor size, lymphovascular invasion status, AJCC 8th T and N stages and the percentage of tumor infiltrating lymphocytes were collected and analyzed. For the image analysis component, whole-slide images (WSIs) of hematoxylin and eosin–stained tissue samples from 64 surgically resected breast cancer patients were used as a training set for an AI model under the supervision of 2 pathologists to extract morphometric features. The model transformed image tiles into patches of morphologically similar patterns, and categorized them into adipose tissue, background, necrosis, invasive carcinoma, carcinoma in situ, stroma, and terminal ductal lobular unit. This trained model was subsequently applied to the WSIs employed in the establishment of PDXs. The classified patches and their relative ratios within the invasive tumor boundary were compiled. The consolidated data from clinicopathological and image analyses were subjected to logistic regression to discern correlates of successful PDX engraftment. Results: Out of the 311 patient tumor samples used for generating PDXs, (131 post-chemotherapy, 180 chemo-naïve), 47 PDXs were successfully established (15.1%). Logistic regression revealed several factors for successful engraftment including NAC treatment with an odds ratio of 6.71 (28.2% vs 5.6%, 95% CI: 2.53 - 17.80, p &amp;lt; 0.001), higher histologic grades (25.3% vs 2.2%, OR = 5.80, 95% CI: 1.49 - 22.63, p = 0.01), triple negative breast cancer compared to hormone receptor-positive cancers (32.0% vs 3.3%, OR = 10.99, 95% CI: 1.26 - 95.89, p = 0.03), and tumors of larger size (OR = 1.34, 95% CI: 1.02 - 1.76, p = 0.03). Interestingly, the percentage of specific tissue patch types within tumor did not significantly impact the likelihood of successful PDX engraftment. However, in our logistic regression analysis based solely on morphometric features, presence of necrosis within the tumor notably enhanced PDX establishment. Specifically, each percent increase in necrosis within tumor boosted the odds of successful PDX creation by 0.01% (OR = 1.0001, 95% CI: 1.00003 - 1.00024, p = 0.01). Conclusions: PDXs are often successfully established from clinically aggressive breast cancers, particularly those with NAC treatment, higher histologic grades, TNBC subtype, and larger tumor size. While morphometric features contribute to the prediction of PDX engraftment success, their importance is surpassed by these clinicopathological factors. However, presence of necrosis emerged as a key morphometric predictor of successful PDX engraftment. Keywords: breast cancer; patient-derived xenograft (PDX); Breast Cancer Morphometrics; Cancer Predictive Modeling. Citation Format: Jongwon Lee, GeonHee Lee, Gyungyub Gong, Hee Jin Lee. Leveraging Clinicopathological Factors and Deep Learning-Based Morphometrics for PDX Engraftment Success Prediction in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-26-01.

In vivo activity of the dual SYK/FLT3 inhibitor TAK-659 against pediatric acute lymphoblastic leukemia xenografts.

While children with acute lymphoblastic leukemia (ALL) experience close to a 90% likelihood of cure, the outcome for certain high-risk pediatric ALL subtypes remains dismal. Spleen tyrosine kinase (SYK) is a prominent cytosolic nonreceptor tyrosine kinase in pediatric B-lineage ALL (B-ALL). Activating mutations or overexpression of Fms-related receptor tyrosine kinase 3 (FLT3) are associated with poor outcome in hematological malignancies. TAK-659 (mivavotinib) is a dual SYK/FLT3 reversible inhibitor, which has been clinically evaluated in several other hematological malignancies. Here, we investigate the in vivo efficacy of TAK-659 against pediatric ALL patient-derived xenografts (PDXs). SYK and FLT3mRNA expression was quantified by RNA-seq. PDX engraftment and drug responses in NSG mice were evaluated by enumerating the proportion of human CD45+ cells (%huCD45+ ) in the peripheral blood. TAK-659 was administered per oral at 60mg/kg daily for 21 days. Events were defined as %huCD45+ ≥ 25%. In addition, mice were humanely killed to assess leukemia infiltration in the spleen and bone marrow (BM). Drug efficacy was assessed by event-free survival and stringent objective response measures. FLT3 and SYK mRNA expression was significantly higher in B-lineage compared with T-lineage PDXs. TAK-659 was well tolerated and significantly prolonged the time to event in six out of eight PDXs tested. However, only one PDX achieved an objective response. The minimum mean %huCD45+ was significantly reduced in five out of eight PDXs in TAK-659-treated mice compared with vehicle controls. TAK-659 exhibited low to moderate single-agent in vivo activity against pediatric ALL PDXs representative of diverse subtypes.

Cancer "Avatars": Patient-Derived Xenograft Growth Correlation with Postoperative Recurrence and Survival in Pancreaticobiliary Cancer.

Pancreaticobiliary (PB) cancers are a diverse group of cancers with poor prognoses and high rates of recurrence after resection. Patient-derived xenografts (PDX), created from surgical specimens, provide a reliable preclinical research platform and high-fidelity cancer model from which to study these malignancies with consistent recapitulation of their original patient tumors in vivo. However, the relationship between PDX engraftment success (growth or no growth) and patient oncologic outcomes has not been well studied. We sought to evaluate the correlation between successful PDX engraftment and survival in several PB exocrine carcinomas, including the pancreatic and biliary tract. In accordance with IRB and Institutional Animal Care and Use Committee protocols and with appropriate consent and approval, excess tumor tissue obtained from surgical patients was implanted into immunocompromised mice. Mice were monitored for tumor growth to determine engraftment success. PDX tumors were verified to recapitulate their tumors of origin by a hepatobiliary pathologist. Xenograft growth was correlated with clinical recurrence and overall survival data. A total of 384 PB xenografts were implanted. The successful engraftment rate was 41% (158/384). We found that successful PDX engraftment was highly associated with both recurrence-free survival (p < 0.001) and overall survival (p < 0.001) outcomes. Successful PDX tumor generation occurs significantly in advance of clinical recurrences in their corresponding patients (p < 0.001). Successful PB cancer PDX models predict recurrence and survival across tumor types and may provide critical lead time to alter patients' surveillance or treatment plans before cancer recurrence.

Prognostic value of xenograft engraftment in patients with metastatic high-risk neuroblastoma.

Successful engraftment of human cancer biopsies in immunodeficient mice correlates with the poor prognosis of patients. This was reported 30 years ago for children with neuroblastoma, but the standard of care treatment evolved significantly during the last 15 years, leading to improved survival of these patients. Here, we evaluated the association of patient-derived xenograft (PDX) engraftment and prognosis in patients receiving up-to-date treatments for cancers classified as metastatic (stage M) high-risk neuroblastoma (HR-NB) by the International Neuroblastoma Risk Group Staging System (INRGSS). We obtained biopsies from patients with stage M HR-NB. We inoculated biopsy fragments subcutaneously in mice. We studied the association of PDX engraftment with event-free survival (EFS) and overall survival (OS) of patients. Since 2009, we established 17 PDX from 97 samples of 66 patients with stage M HR-NB, with a follow-up of at least two years. Factors associated with higher probability of engraftment were the death as outcome (p=.0006) and the amplification of the gene MYCN in tumors (p=.0271). Patients whose biopsies established a PDX had significantly shorter EFS and OS (p=.0039 and .0002, respectively) than patients whose samples did not engraft. The association of PDX engraftment and OS was significant in patients without MYCN amplification (p=.0041), but not in patients with MYCN amplification (p=.2707). Positive PDX engraftment is a factor related to poor prognosis and fatal outcome in patients with stage M HR-NB treated with up-to-date therapies.

Abstract P2-26-21: The Principal Factors Associated with Engraftment Success of Patient-Derived Xenograft of Breast Cancer

Abstract Background: Patient-derived xenografts (PDXs) are increasingly used in cancer research as tools for studying cancer biology and personalized immunotherapy response. However, a comprehensive evaluation of patient-derived breast cancer xenograft generation rates in various settings is understudied. Methods: We conducted a prospective study of breast cancer patients treated with surgery to generate PDXs. PDXs were characterized by molecular subtypes, specific diagnostic entities, modified Bloom-Richardson system nuclear and histologic grades, treatment with neoadjuvant chemotherapy (NAC), Miller Payne grade, residual caner burden class, invasive tumor size, lymphovascular invasion status, number of positive lymph nodes, and the percentage of tumor infiltrating lymphocytes in the implanted tumors. Results: Three hundred and seventy-two (157 post-chemotherapy, 215 chemo-naïve) patient-derived tumors were implanted and 63 PDXs were established (17.0%). PDX engraftment was higher in the patients with higher nuclear and histologic grades using the modified Bloom-Richardson system (27.6% vs. 3.2%, p = 0.003) and triple negative breast cancer (TNBC) than in those with hormone receptor-positive cancer (36.4% vs. 3.2%, p = 0.02). Tumors from patients who received NAC (30.0% vs. 7.4%, p = 0.05) were also close to being statistically significant for successful PDX generation. Conclusions: PDXs can be established from clinically aggressive breast cancers, especially in patients with high nuclear and histologic grade TNBC treated with NAC. The prediction of engraftment success using these factors would establish cost-effective immunotherapy trials employing PDXs. Citation Format: Jongwon Lee, Uk Lee, Hee Jin Lee, Gyungyub Gong. The Principal Factors Associated with Engraftment Success of Patient-Derived Xenograft of Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-26-21.

Humanized Patient-derived Xenograft Models of Disseminated Ovarian Cancer Recapitulate Key Aspects of the Tumor Immune Environment within the Peritoneal Cavity.

huPDX models are ideal preclinical models for testing novel therapies. They reflect the genetic heterogeneity of the patient population, enhance human myeloid differentiation, and recruit immune cells to the tumor microenvironment.

Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer

Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors revealed no significant association with PDX engraftment rate (p = 0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient’s diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient’s tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC.

Selected Articles from This Issue

Highlights| January 03 2023 Selected Articles from This Issue Author & Article Information Online Issn: 1557-3125 Print Issn: 1541-7786 ©2022 American Association for Cancer Research2022American Association for Cancer Research Mol Cancer Res (2023) 21 (1): 1. https://doi.org/10.1158/1541-7786.MCR-21-1-HI Related Content A commentary has been published: Subtype and Site Specific–Induced Metabolic Vulnerabilities in Prostate Cancer A commentary has been published: GSTA4 Governs Melanoma Immune Resistance and Metastasis A commentary has been published: Mitochondrial Aconitase ACO2 Links Iron Homeostasis with Tumorigenicity in Non–Small Cell Lung Cancer View more A commentary has been published: JAZF1: A Metabolic Regulator of Sensitivity to a Polyamine-Targeted Therapy View less Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Article Versions Icon Versions Version of Record January 3 2023 Citation Selected Articles from This Issue. Mol Cancer Res 1 January 2023; 21 (1): 1. https://doi.org/10.1158/1541-7786.MCR-21-1-HI Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search Advanced Search While several non-small cell lung cancer (NSCLC) oncogenic drivers have been identified and therapeutically targeted, many patients harbor aggressive NSCLC tumors lacking targetable oncogenic drivers. Patient-derived xenograft (PDX) models provide useful resources for novel oncogenic driver discovery, as PDX engraftment in immunocompromised mice is a prognostic indicator of poor disease outcomes. By defining engrafting and non-engrafting NSCLC proteomes using mass spectrometry, Mirhadi and colleagues discovered that engrafting tumors exhibit low mitochondrial aconitase (ACO2) and intracellular labile iron levels. Overexpressing ACO2 limits tumor growth in vivo and abrogating its expression using inducible shRNA enhances colony formation in vitro, underscoring the role of ACO2 as a tumor suppressor in NSCLC. Mechanistically, the authors found that ACO2-isocitrate dehydrogenase (IDH) reaction-generated NADPH inhibits mitoNEET (mNT), which could activate iron response element binding protein 1 (IRP1) to facilitate transferrin receptor stabilization and subsequent iron uptake. Correspondingly, iron supplementation or mNT inhibition using pioglitazone hydrochloride... You do not currently have access to this content.

Patient-derived xenograft models for gastrointestinal tumors: A single-center retrospective study.

Patient-derived xenograft (PDX) models have shown a great efficiency in preclinical and translational applications. Gastrointestinal (GI) tumors have a strong heterogeneity, and the engraftment rate of PDX models remarkably vary. However, the clinicopathological and molecular characteristics affecting the engraftment rate still remain elusive. A total of 312 fresh tumor tissue samples from patients with GI cancer were implanted into immunodeficient mice. The median follow-up time of patients was 37 months. Patients' characteristics were compared in terms of PDX growth and overall survival. PDX models of 3-6 generations were used for drug evaluation. In total, 171 (54.8%, 171/312) PDX models were established, including 85 PDX models of colorectal cancer, 21 PDX models of esophageal cancer, and 65 PDX models of gastric cancer. Other than tumor site, histology, differentiation degree, and serum alpha-fetoprotein (AFP) level, no significant differences were found between transplantation of xenografts and patients' characteristics. For patients who had undergone neoadjuvant therapy, the incidence of tumor formation was higher in those with progressive disease (PD) or stable disease (SD). In gastric cancer, the results showed a higher transplantation rate in deficient mismatch repair (dMMR) tumors, and Ki-67 could be an important factor affecting the engraftment rate. The gene mutation status of RAS and BRAF, two important molecular markers in colorectal cancer, showed a high degree of consistency between patients' tumors and PDXs. However, no significant effects of these two mutations on PDX engraftment rate were observed. More importantly, in this study although KRAS mutations were detected in two clinical cases, evident tumor inhibition was still observed after cetuximab treatment in both PDX models and patients. A large-scale PDX model including 171 cases was successfully established for GI tumors in our center. The relationship between clinicopathological and molecular features and engraftment rates were clarified. Furthermore, this resource provides us with profound insights into tumor heterogeneity, making these models valuable for PDX-guided treatment decisions, and offering the PDX model as a great tool for personalized treatment and translation research.

Molecular parameters impacting the success rate of a lung cancer PDX model.

e20592 Background: Patient-derived xenograft (PDX) models can provide renewable cancer tissue resources, are being increasingly utilized for the molecular characterizations of cancers and preclinical studies on drug activities, and have the potential to advance biomarker identification. Previous research has demonstrated that PDX tumors preserve the histologic and morphologic characteristics and gene expression and mutation patterns of primary tumors, and correlate to patient survival. Tumor histological subtypes and differentiation grades are known to contribute to the success of PDX intake, but little is known about how molecular features associate with the success of PDX engraftment or whether PDX preserves subclonal architecture of primary tumors. Methods: To fill this void, we analyzed 252 primary tumor samples from the SPORE/ICON project at MD Anderson Cancer Center that were used for generating PDXs and had comprehensive genomic, transcriptomic, and immune profiling data available to evaluate the parameters impacting the intake success of lung cancer PDXs. In order to establish the impact of molecular features on PDX intake success we also assessed the fidelity of PDX in representing the molecular features of this cohort of primary tumors. Results: Only 36% of the primary tumors in this study successfully generated a PDX, with Squamous Cell Carcinoma PDX demonstrating an intake rate of 67% and Adenocarcinoma PDX demonstrating an intake rate of 21%. Genomic architecture derived from whole exome sequencing showed not only 43% (38-48%) of mutations shared, but also similar clonal architecture between primary tumors and PDX. Higher copy number aberration burden, high tumor purity and low immune infiltration in primary tumors were found to be associated with successful intake of PDX. Transcriptomics revealed 6,103 genes differentially expressed between primary tumors with successful PDX intake versus those which were unsuccessful. Pathway analysis of these genes indicated that inhibition of cell proliferation, signaling, and migration as well as DNA replication, recombination and repair were associated with PDX intake failure regardless of histology. Conclusions: These findings indicate that PDX intake success is regulated by molecular features and multiomic evaluation of lung cancer primary tumors can be used as a marker for determining which samples to use for PDX model generation.

Development and Validation of an Oral Cavity Cancer Outcomes Prediction Score Incorporating Patient-Derived Xenograft Engraftment

Patient-derived xenografts (PDXs) offer the opportunity to identify patients with oral cavity squamous cell carcinoma (OSCC) who are at risk for recurrence and optimize clinical decision-making. To develop and validate a prediction score for locoregional failure (LRF) and distant metastases (DM) in OSCC that incorporates PDX engraftment in addition to known clinicopathological risk factors. In this retrospective cohort study, PDX models were generated from patients with OSCC treated with curative intent at Princess Margaret Cancer Centre (Toronto, Canada) between 2006 and 2018. The cohort included 288 patients (aged ≥18 years) with a new diagnosis of nonmetastatic (M0) OSCC whose tumor samples were available for engraftment under the skin of xenograft mice. Patients were scored as a nonengrafter if PDX formation did not occur within 6 months. Data analysis was performed between August 2006 and May 2018. All patients received up-front curative-intent surgery followed by either observation or postoperative radiation with or without concurrent chemotherapy based on institutional guidelines. Main outcomes were LRF, DM, and overall survival (OS). Multivariable analysis (MVA) was used to identify predictors of LRF and DM. Factors retained in the final MVA were used to construct a prediction score and classify patients into risk groups. Overall, 288 patients (mean [SD] age at diagnosis, 63.3 [12.3] years; 112 [39%] women and 176 [61%] men) with OSCC were analyzed. The MVA identified pT3-4, pathologic extranodal extension, and engraftment as predictors of LRF and DM. Patients whose tumors engrafted (n = 198) were more likely to develop LRF (hazard ratio [HR], 1.98; 95% CI, 1.24-3.18) and DM (HR, 2.64; 95% CI, 1.21-5.75) compared with nonengrafters. A prediction score based on the aforementioned variables identified patients at high risk and low risk for LRF (43.5% vs 26.5%), DM (38.2% vs 8.4%), and inferior OS (34% vs 66%) at 5 years. Additionally, rapid engraftment was shown to be similarly prognostic, with rapid engrafters demonstrating higher rates of relapse and poor OS. In this cohort study, a prediction score using OSCC PDX engraftment, in conjunction with pT3-4 and pathologic extranodal extension, was associated with improved prognostic utility of existing clinical models and predicted patients at risk for LRF, DM, and poor survival.

Identification of Prognostic Markers of Gynecologic Cancers Utilizing Patient-Derived Xenograft Mouse Models.

Simple SummaryAs a preclinical model for personalized cancer therapy, the patient-derived xenograft (PDX) model is suitable because it provides the best representation of the original tumor, but it still has many limitations. We analyzed gynecologic cancer PDX models with their clinical information and gene expression profiling, and found that the success rate of PDX correlated with the patient’s tumor grade and prognosis. Moreover, we showed that the faster the tumor progressed in PDXs, the poorer the prognosis in ovarian cancer patients. We confirmed that the differentially expressed genes (DEGs) selected according to PDX engraftment status could be a prognosis marker of ovarian clear cell cancer patients. This study paves the way for a better application of the PDX in gynecologic cancer.Patient-derived xenografts (PDXs) are important in vivo models for the development of precision medicine. However, challenges exist regarding genetic alterations and relapse after primary treatment. Thus, PDX models are required as a new approach for preclinical and clinical studies. We established PDX models of gynecologic cancers and analyzed their clinical information. We subcutaneously transplanted 207 tumor tissues from patients with gynecologic cancer into nude mice from 2014 to 2019. The successful engraftment rate of ovarian, cervical, and uterine cancer was 47%, 64%, and 56%, respectively. The subsequent passages (P2 and P3) showed higher success and faster growth rates than the first passage (P1). Using gynecologic cancer PDX models, the tumor grade is a common clinical factor affecting PDX establishment. We found that the PDX success rate correlated with the patient’s prognosis, and also that ovarian cancer patients with a poor prognosis had a faster PDX growth rate (p < 0.0001). Next, the gene sets associated with inflammation and immune responses were shown in high-ranking successful PDX engraftment through gene set enrichment analysis and RNA sequencing. Up-regulated genes in successful engraftment were found to correlate with ovarian clear cell cancer patient outcomes via Gene Expression Omnibus dataset analysis.

Establishment and evaluation of retroperitoneal liposarcoma patient-derived xenograft models: an ideal model for preclinical study.

Retroperitoneal liposarcoma (RLPS) is one of the most common subtypes of retroperitoneal soft tissue sarcomas. It is characterized by poor sensitivity to radiotherapy and chemotherapy and a low success rate of complete surgical resection. However, there are few reliable preclinical RLPS models for target discovery and therapy research. In this study, we aimed to establish RLPS patient-derived xenograft (PDX) models that are useful for biological research and preclinical drug trials. A total of 56 freshly resected RLPS tissues were subcutaneously transplanted into non-obese diabetic-severe combined immune deficient (NOD-SCID) mice, with subsequent xenotransplantation into second-generation mice. The tumor engraftment rate of first generation PDXs was 44.64%, and higher success rates were obtained from implantations of dedifferentiated, myxous, pleomorphic, high-grade liposarcomas and those with retroperitoneal organ infiltration. The first- and second- generation PDX models preserved the histopathological morphology, gene mutation profiles and MDM2 amplification of the primary tissues. PDX models can also provide the benefit of retaining original tumor biology and microenvironment characteristics, such as abnormal adipose differentiation, elevated Ki67 levels, high microvessel density, cancer-associated fibroblast presence, and tumor-associated macrophage infiltration. Overall survival (OS) and disease-free survival (DFS) of patients with successful first-generation PDX engraftment were significantly poorer than those with failed engraftment. Treatment with MDM2 inhibitor RG7112 significantly suppressed tumor growth of DDLPS PDX in mice. In conclusion, we successfully established RLPS PDX models that were histologically, genetically, and molecularly consistent with the original tissues. These models might provide opportunities for advancing RLPS tumor biology research, facilitating the development of novel drugs, particularly those targeting MDM2 amplification, adipose differentiation process, angiogenesis, cancer-associated fibroblasts, and so on.

Patient-Derived Xenograft Engraftment Predicts Oral Cavity Cancer Outcomes

Patient-derived xenografts (PDX) can help identify oral cavity squamous cell carcinoma (OSCC) patients at risk for disease recurrence and optimize clinical decision-making. In this study, we develop and validate a prediction score for locoregional failure (LRF) and distant metastases (DM) in OSCC that incorporates PDX engraftment in addition to known clinicopathological risk factors.PDX models were generated from OSCC patients. Patients were scored as a ''non-engrafter" if PDX formation did not occur within 6 months. Multivariable analysis (MVA) was used to identify predictors of LRF and DM. Factors retained in the final MVA were used to construct a prediction score and classify patients into risk groups using a 10-fold cross-validation approach.Overall 288 OSCC patients were analyzed. MVA identified pT3-4, pENE, and engraftment as predictors of LRF and DM. Patients whose tumors engrafted (n = 198) were more likely to develop LRF (HR 1.98, 95% CI: 1.24-3.18, P < 0.01), and DM (HR 2.64, 95% CI 1.21-5.75, P < 0.01) compared to non-engrafters. A prediction score based on the aforementioned variables identified patients at high-risk (defined as having at least two of the three high risk features i.e., engraftment, pT3-4, pENE) and low-risk for LRF (43.5% vs 26.5% at 5-years, P < 0.001), DM (38.2% vs 8.4% at 5-years, P < 0.001), and poorer 5-year OS (34% vs 66%, P < 0.001). The prediction model that included engraftment had the highest discriminatory capacity in the cross-validation analysis (AUC: 67.8 [63.5-72.9]), while removal of engraftment as a predictor resulted in a lower c-index (AUC: 62.7 [57.0-68.4]). In patients classified based on a clinical score only (i.e., presence or absence of pT3-4 and pENE), engraftment remained useful in identifying those with worse outcomes. Compared to non-engrafters, engraftment was associated with higher rates of DM (15.8% vs. 5.4%, P < 0.05) in clinically "high risk" patients as well as higher rates of LRF (31.9% vs. 13.8%, P < 0.05) in clinically "low risk" patients at 5-years. Finally, engraftment was associated with poorer 5-year OS in both clinically "high risk" (36% vs. 65%, P < 0.05), and "low risk" patients (57% vs. 78%, P < 0.01).A prediction score utilizing OSCC PDX engraftment, in conjunction with pT3-4 and pENE, improves the prognostic utility of existing clinical models and predicts patients at risk for LRF, DM and poor survival.

45: Patient-Derived Xenograft Engraftment Predicts Oral Cavity Cancer Outcomes

45: Patient-Derived Xenograft Engraftment Predicts Oral Cavity Cancer Outcomes

Patient-Derived Xenograft Models for Intrahepatic Cholangiocarcinoma and Their Application in Guiding Personalized Medicine.

BackgroundIntrahepatic cholangiocarcinoma (ICC) remains one of the most intractable malignancies. The development of effective drug treatments for ICC is seriously hampered by the lack of reliable tumor models. At present, patient derived xenograft (PDX) models prove to accurately reflect the genetic and biological diversity required to decipher tumor biology and therapeutic vulnerabilities. This study was designed to investigate the establishment and potential application of PDX models for guiding personalized medicine and identifying potential biomarker for lenvatinib resistance.MethodsWe generated PDX models from 89 patients with ICC and compared the morphological and molecular similarities of parental tumors and passaged PDXs. The clinicopathologic features affecting PDX engraftment and the prognostic significance of PDX engraftment were analyzed. Drug treatment responses were analyzed in IMF-138, IMF-114 PDX models and corresponding patients. Finally, lenvatinib treatment response was examined in PDX models and potential drug resistance mechanism was revealed.ResultsForty-nine PDX models were established (take rate: 55.1%). Successful PDX engraftment was associated with negative HbsAg (P = 0.031), presence of mVI (P = 0.001), poorer tumor differentiation (P = 0.023), multiple tumor number (P = 0.003), presence of lymph node metastasis (P = 0.001), and later TNM stage (P = 0.039). Moreover, patients with tumor engraftment had significantly shorter time to recurrence (TTR) (P < 0.001) and worse overall survival (OS) (P < 0.001). Multivariate analysis indicated that PDX engraftment was an independent risk factor for shortened TTR (HR = 1.84; 95% CI, 1.05–3.23; P = 0.034) and OS (HR = 2.13; 95% CI, 1.11–4.11; P = 0.024). PDXs were histologically and genetically similar to their parental tumors. We also applied IMF-138 and IMF-114 PDX drug testing results to guide clinical treatment for patients with ICC and found similar treatment responses. PDX models also facilitated personalized medicine for patients with ICC based on drug screening results using whole exome sequencing data. Additionally, PDX models reflected the heterogeneous sensitivity to lenvatinib treatment and CDH1 might be vital to lenvatinib-resistance.ConclusionPDX models provide a powerful platform for preclinical drug discovery, and potentially facilitate the implementation of personalized medicine and improvement of survival of ICC cancer patient.

Patient-Derived Xenograft Engraftment and Breast Cancer Outcomes in a Prospective Neoadjuvant Study (BEAUTY).

Patient-derived xenografts (PDX) are a research tool for studying cancer biology and drug response phenotypes. While engraftment rates are higher for tumors with more aggressive characteristics, it is uncertain whether engraftment is prognostic for cancer recurrence. In a prospective study of patients with breast cancer treated with neoadjuvant chemotherapy (NAC) with taxane ± trastuzumab followed by anthracycline-based chemotherapy, we report the association between breast cancer events and PDX engraftment using tumors derived from treatment naïve (pre-NAC biopsies from 113 patients) and treatment resistant (post-NAC at surgery from 34 patients). Gray test was used to assess whether the cumulative incidence of a breast cancer event differs with respect to either pre-NAC PDX engraftment or post-NAC PDX engraftment. With a median follow-up of 5.7 years, the cumulative incidence of breast cancer relapse did not differ significantly according to pre-NAC PDX engraftment (5-year rate: 13.6% vs. 13.4%; P = 0.89). However, the incidence of a breast event was greater for patients with post-NAC PDX engraftment (5-year rate: 50.0% vs. 19.6%), but this did not achieve significance (P = 0.11). In treatment-naïve breast cancer receiving standard NAC, PDX engraftment was not prognostic for breast cancer recurrence. Further study is needed to establish whether PDX engraftment in the treatment-resistant setting is prognostic for cancer recurrence.

Gene expression profiles of the original tumors influence the generation of PDX models of lung squamous cell carcinoma

Patient-derived xenograft (PDX) murine models are employed for preclinical research on cancers, including non-small cell lung cancers (NSCLCs). Even though lung squamous cell carcinomas (LUSCs) show the highest engraftment rate among NSCLCs, half of them nevertheless show PDX failure in immunodeficient mice. Here, using immunohistochemistry and RNA sequencing, we evaluated the distinct immunohistochemical and gene expression profiles of resected LUSCs that showed successful engraftment. Among various LUSCs, including the basal, classical, secretory, and primitive subtypes, those in the non-engrafting (NEG) group showed gene expression profiles similar to the pure secretory subtype with positivity for CK7, whereas those in the engrafting (EG) group were similar to the mixed secretory subtype with positivity for p63. Pathway analysis of 295 genes that demonstrated significant differences in expression between NEG and EG tumors revealed that the former had enriched expression of genes related to the immune system, whereas the latter had enriched expression of genes related to the cell cycle and DNA replication. Interestingly, NEG tumors showed higher infiltration of B cells (CD19+) and follicular dendritic cells (CD23+) in lymph follicles than EG tumors. Taken together, these findings suggest that the PDX cancer model of LUSC represents only a certain population of LUSCs and that CD19- and CD23-positive tumor-infiltrating immune cells in the original tumors may negatively influence PDX engraftment in immunodeficient mice.