creating-matched-vivoin-vitro-patient-derived-model-pairs-pdx-pdx

Creating Matched In vivo/In vitro Patient-Derived Model Pairs of PDX and PDX-Derived Organoids for Cancer Pharmacology Research

Patient-derived tumor xenografts (PDXs) are considered the most predictive preclinical models, largely believed to be driven by cancer stem cells (CSC) ...

medium-throughput-drug-radiotherapy-screening-assay-using-patient

Medium-Throughput Drug- and Radiotherapy Screening Assay using Patient-Derived Organoids

Patient-derived organoid (PDO) models allow for long-term expansion and maintenance of primary epithelial cells grown in three dimensions and a ...

Crown Bioscience Inc., San Diego, CA, USA

Crown Bioscience Inc.

The Cancer Genome Atlas (TCGA) project has generated abundant genomic data for human cancers of various histopathology types and enabled exploring cancer molecular pathology per big data approach. We developed a new algorithm based on most differentially expressed genes (DEG) per pairwise comparisons to calculate correlation coefficients to be used to quantify similarity within and between cancer types. We systematically compared TCGA cancers, demonstrating high correlation within types and low correlation between types, thus establishing molecular specificity of cancer types and an alternative diagnostic method largely equivalent to histopathology. Different coefficients for different cancers in study may reveal that the degree of the within-type homogeneity varies by cancer types. We also performed the same calculation using the TCGA-derived DEGs on patient-derived xenografts (PDX) of different histopathology types corresponding to the TCGA types, as well as on cancer cell lines. We, for the first time, demonstrated highly similar patterns for within- and between-type correlation between PDXs and patient samples in a systematic study, confirming the high relevance of PDXs as surrogate experimental models for human diseases. In contrast, cancer cell lines have drastically reduced expression similarity to both PDXs and patient samples. The studies also revealed high similarity between some types, for example, LUSC and HNSCC, but low similarity between certain subtypes, for example, LUAD and LUSC. Our newly developed algorithm seems to be a practical diagnostic method to classify and reclassify a disease, either human or xenograft, with better accuracy than traditional histopathology. Cancer Res; 76(16); 4619-26. ©2016 AACR.

Molecular Pathology of Patient Tumors, Patient-Derived Xenografts, and Cancer Cell Lines.

Immuno-oncology (I/O) research has intensified significantly in recent years due to the breakthrough development and the regulatory approval of several immune checkpoint inhibitors, leading to the rapid expansion of the new discovery of novel I/O therapies, new checkpoint inhibitors and beyond. However, many I/O questions remain unanswered, including why only certain subsets of patients respond to these treatments, who the responders would be, and how to expand patient response (the conversion of non-responders or maximizing response in partial responders). All of these require relevant I/O experimental systems, particularly relevant preclinical animal models. Compared to other oncology drug discovery, e.g. cytotoxic and targeted drugs, a lack of relevant animal models is a major obstacle in I/O drug discovery, and an urgent and unmet need. Despite the obvious importance, and the fact that much I/O research has been performed using many different animal models, there are few comprehensive and introductory reviews on this topic. This article attempts to review the efforts in development of a variety of such models, as well as their applications and limitations for readers new to the field, particularly those in the pharmaceutical industry.

Experimental animal modeling for immuno-oncology.

Experimental animal tumor models have been broadly used to evaluate anticancer drugs in the preclinical setting. They have also been widely applied for drug target discovery and validation, which usually follows four experimental strategies: first, assess the roles of putative drug targets using in vivo tumorigenicity and tumor growth kinetics assays of transplanted tumors, engineered through gain-of-function (GOF) by overexpressing transgene or knock-in (KI) or loss-of-function by gene silencing using knockdown (KD) or knockout (KO) or mutation via mutagenesis procedures; second, similarly genetically engineered mouse models (GEMM), through either germline or somatic cell procedures, are used to test the roles of potential targets in spontaneous tumorigenicity assays; third, patient-derived xenografts (PDXs), which most closely resemble patient genetics and histopathology, are used in tumor inhibition assays for evaluating target-/pathway-specific inhibitors, including large and small molecules, thus assessing the drug target; and fourth, the targets can be assessed in population-based trials, mouse clinical trials (MCT), so that the validation can be generally meaningful as performed in human clinical trials. This chapter outlines the commonly used protocols in cancer drug target research: the first four sections describe four sets of different, specific pharmacology protocols used in the respective cancer modeling stages, with the last section summarizing the common protocols applicable to all four pharmacology modeling steps.

In Vivo Pharmacology Models for Cancer Target Research.

Mouse clinical trials (MCTs) are becoming wildly used in pre-clinical oncology drug development, but a statistical framework is yet to be developed. In this study, we establish such as framework and provide general guidelines on the design, analysis and application of MCTs.

ArticleTotal : 2	Year
Publication title Cited by 9	2021
Publication title Cited by 15	2021

Article	Year
Molecular Pathology of Patient Tumors, Patient-Derived Xenografts, and Cancer Cell Lines. Cancer research\| PubMed ID: 27325646	2016
Experimental animal modeling for immuno-oncology. Pharmacology & therapeutics\| PubMed ID: 28167217	2017
In Vivo Pharmacology Models for Cancer Target Research. Methods in molecular biology (Clifton, N.J.)\| PubMed ID: 30912023	2019
The design, analysis and application of mouse clinical trials in oncology drug development. BMC cancer\| PubMed ID: 31331301	2019

Qi-Xiang Li

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