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16 pages, 10608 KiB

Open AccessArticle

FABP5 Inhibition against PTEN-Mutant Therapy Resistant Prostate Cancer

by Manojit M. Swamynathan, Grinu Mathew, Andrei Aziz, Chris Gordon, Andrew Hillowe, Hehe Wang, Aashna Jhaveri, Jude Kendall, Hilary Cox, Michael Giarrizzo, Gissou Azabdaftari, Robert C. Rizzo, Sarah D. Diermeier, Iwao Ojima, Agnieszka B. Bialkowska, Martin Kaczocha and Lloyd C. Trotman

Cancers 2024, 16(1), 60; https://doi.org/10.3390/cancers16010060 - 21 Dec 2023

Cited by 4 | Viewed by 3700

Abstract

Resistance to standard of care taxane and androgen deprivation therapy (ADT) causes the vast majority of prostate cancer (PC) deaths worldwide. We have developed RapidCaP, an autochthonous genetically engineered mouse model of PC. It is driven by the loss of PTEN and p53, the most common driver events in PC patients with life-threatening diseases. As in human ADT, surgical castration of RapidCaP animals invariably results in disease relapse and death from the metastatic disease burden. Fatty Acid Binding Proteins (FABPs) are a large family of signaling lipid carriers. They have been suggested as drivers of multiple cancer types. Here we combine analysis of primary cancer cells from RapidCaP (RCaP cells) with large-scale patient datasets to show that among the 10 FABP paralogs, FABP5 is the PC-relevant target. Next, we show that RCaP cells are uniquely insensitive to both ADT and taxane treatment compared to a panel of human PC cell lines. Yet, they share an exquisite sensitivity to the small-molecule FABP5 inhibitor SBFI-103. We show that SBFI-103 is well tolerated and can strongly eliminate RCaP tumor cells in vivo. This provides a pre-clinical platform to fight incurable PC and suggests an important role for FABP5 in PTEN-deficient PC. Full article

(This article belongs to the Special Issue PTEN: Regulation, Signalling and Targeting in Cancer)

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29 pages, 3404 KiB

Open AccessReview

Recent Advancement in Breast Cancer Research: Insights from Model Organisms—Mouse Models to Zebrafish

by Sharad S. Singhal, Rachana Garg, Atish Mohanty, Pankaj Garg, Sravani Keerthi Ramisetty, Tamara Mirzapoiazova, Raffaella Soldi, Sunil Sharma, Prakash Kulkarni and Ravi Salgia

Cancers 2023, 15(11), 2961; https://doi.org/10.3390/cancers15112961 - 29 May 2023

Cited by 21 | Viewed by 8782

Abstract

Animal models have been utilized for decades to investigate the causes of human diseases and provide platforms for testing novel therapies. Indeed, breakthrough advances in genetically engineered mouse (GEM) models and xenograft transplantation technologies have dramatically benefited in elucidating the mechanisms underlying the pathogenesis of multiple diseases, including cancer. The currently available GEM models have been employed to assess specific genetic changes that underlay many features of carcinogenesis, including variations in tumor cell proliferation, apoptosis, invasion, metastasis, angiogenesis, and drug resistance. In addition, mice models render it easier to locate tumor biomarkers for the recognition, prognosis, and surveillance of cancer progression and recurrence. Furthermore, the patient-derived xenograft (PDX) model, which involves the direct surgical transfer of fresh human tumor samples to immunodeficient mice, has contributed significantly to advancing the field of drug discovery and therapeutics. Here, we provide a synopsis of mouse and zebrafish models used in cancer research as well as an interdisciplinary ‘Team Medicine’ approach that has not only accelerated our understanding of varied aspects of carcinogenesis but has also been instrumental in developing novel therapeutic strategies. Full article

(This article belongs to the Topic Animal Model in Biomedical Research, 2nd Volume)

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15 pages, 8595 KiB

Open AccessArticle

DWI Metrics Differentiating Benign Intraductal Papillary Mucinous Neoplasms from Invasive Pancreatic Cancer: A Study in GEM Models

by Miguel Romanello Joaquim, Emma E. Furth, Yong Fan, Hee Kwon Song, Stephen Pickup, Jianbo Cao, Hoon Choi, Mamta Gupta, Quy Cao, Russell Shinohara, Deirdre McMenamin, Cynthia Clendenin, Thomas B. Karasic, Jeffrey Duda, James C. Gee, Peter J. O’Dwyer, Mark A. Rosen and Rong Zhou

Cancers 2022, 14(16), 4017; https://doi.org/10.3390/cancers14164017 - 20 Aug 2022

Cited by 8 | Viewed by 2588

Abstract

KPC (Kras^G12D:Trp53^R172H:Pdx1-Cre) and CKS (Kras^G12D:Smad4^L/L:Ptf1a-Cre) mice are genetically engineered mouse (GEM) models that capture features of human pancreatic ductal adenocarcinoma (PDAC) and intraductal papillary mucinous neoplasms (IPMN), respectively. We compared these autochthonous tumors using quantitative imaging metrics from diffusion-weighted MRI (DW-MRI) and dynamic contrast enhanced (DCE)-MRI in reference to quantitative histological metrics including cell density, fibrosis, and microvasculature density. Our results revealed distinct DW-MRI metrics between the KPC vs. CKS model (mimicking human PDAC vs. IPMN lesion): the apparent diffusion coefficient (ADC) of CKS tumors is significantly higher than that of KPC, with little overlap (mean ± SD

2.24 \pm 0.2

vs.

1.66 \pm 0.2

p < 10^{- 10}

) despite intratumor and intertumor variability. Kurtosis index (KI) is also distinctively separated in the two models. DW imaging metrics are consistent with growth pattern, cell density, and the cystic nature of the CKS tumors. Coregistration of ex vivo ADC maps with H&E-stained sections allowed for regional comparison and showed a correlation between local cell density and ADC value. In conclusion, studies in GEM models demonstrate the potential utility of diffusion-weighted MRI metrics for distinguishing pancreatic cancer from benign pancreatic cysts such as IPMN. Full article

(This article belongs to the Special Issue Characterization of Tumor Physiology Using Magnetic Resonance Imaging (MRI))

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21 pages, 637 KiB

Open AccessReview

Patient-Derived Xenograft Models of Pancreatic Cancer: Overview and Comparison with Other Types of Models

by Patrick L. Garcia, Aubrey L. Miller and Karina J. Yoon

Cancers 2020, 12(5), 1327; https://doi.org/10.3390/cancers12051327 - 22 May 2020

Cited by 55 | Viewed by 7786

Abstract

Pancreatic cancer (PC) is anticipated to be second only to lung cancer as the leading cause of cancer-related deaths in the United States by 2030. Surgery remains the only potentially curative treatment for patients with pancreatic ductal adenocarcinoma (PDAC), the most common form of PC. Multiple recent preclinical studies focus on identifying effective treatments for PDAC, but the models available for these studies often fail to reproduce the heterogeneity of this tumor type. Data generated with such models are of unknown clinical relevance. Patient-derived xenograft (PDX) models offer several advantages over human cell line-based in vitro and in vivo models and models of non-human origin. PDX models retain genetic characteristics of the human tumor specimens from which they were derived, have intact stromal components, and are more predictive of patient response than traditional models. This review briefly describes the advantages and disadvantages of 2D cultures, organoids and genetically engineered mouse (GEM) models of PDAC, and focuses on the applications, characteristics, advantages, limitations, and the future potential of PDX models for improving the management of PDAC. Full article

(This article belongs to the Special Issue Patient-Derived Xenograft-Models in Cancer Research)

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16 pages, 708 KiB

Open AccessReview

Genetically Engineered Mouse Models for Liver Cancer

by Kyungjoo Cho, Simon Weonsang Ro, Sang Hyun Seo, Youjin Jeon, Hyuk Moon, Do Young Kim and Seung Up Kim

Cancers 2020, 12(1), 14; https://doi.org/10.3390/cancers12010014 - 19 Dec 2019

Cited by 33 | Viewed by 7226

Abstract

Liver cancer is the fourth leading cause of cancer-related death globally, accounting for approximately 800,000 deaths annually. Hepatocellular carcinoma (HCC) is the most common type of liver cancer, comprising approximately 80% of cases. Murine models of HCC, such as chemically-induced models, xenograft models, and genetically engineered mouse (GEM) models, are valuable tools to reproduce human HCC biopathology and biochemistry. These models can be used to identify potential biomarkers, evaluate potential novel therapeutic drugs in pre-clinical trials, and develop molecular target therapies. Considering molecular target therapies, a novel approach has been developed to create genetically engineered murine models for HCC, employing hydrodynamics-based transfection (HT). The HT method, coupled with the Sleeping Beauty transposon system or the CRISPR/Cas9 genome editing tool, has been used to rapidly and cost-effectively produce a variety of HCC models containing diverse oncogenes or inactivated tumor suppressor genes. The versatility of these models is expected to broaden our knowledge of the genetic mechanisms underlying human hepatocarcinogenesis, allowing the study of premalignant and malignant liver lesions and the evaluation of new therapeutic strategies. Here, we review recent advances in GEM models of HCC with an emphasis on new technologies. Full article

(This article belongs to the Special Issue Models of Experimental Liver Cancer)

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