scholarly journals Peer Review #2 of "A systematic review of the validity of patient derived xenograft (PDX) models: the implications for translational research and personalised medicine (v0.1)"

Author(s):  
M van Smeden
PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5981 ◽  
Author(s):  
Anne T. Collins ◽  
Shona H. Lang

Patient-derived xenograft (PDX) models are increasingly being used in oncology drug development because they offer greater predictive value than traditional cell line models. Using novel tools to critique model validity and reliability we performed a systematic review to identify all original publications describing the derivation of PDX models of colon, prostate, breast and lung cancer. Validity was defined as the ability to recapitulate the disease of interest. The study protocol was registered with the Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies (CAMARADES). Searches were performed in Embase, MEDLINE and Pubmed up to July 2017. A narrative data synthesis was performed. We identified 105 studies of model validations; 29 for breast, 29 for colon, 25 for lung, 23 for prostate and 4 for multiple tissues. 133 studies were excluded because they did not perform any validation experiments despite deriving a PDX. Only one study reported following the ARRIVE guidelines; developed to improve the standard of reporting for animal experimentation. Remarkably, half of all breast (52%) and prostate (50%) studies were judged to have high concern, in contrast to 16% of colon and 28% of lung studies. The validation criteria that most commonly failed (evidence to the contrary) were: tissue of origin not proven and histology of the xenograft not comparable to the parental tumour. Overall, most studies were categorized as unclear because one or more validation conditions were not reported, or researchers failed to provide data for a proportion of their models. For example, failure to demonstrate tissue of origin, response to standard of care agents and to exclude development of lymphoma. Validation tools have the potential to improve reproducibility, reduce waste in research and increase the success of translational studies.


2020 ◽  
Vol 122 (5) ◽  
pp. 680-691 ◽  
Author(s):  
Alvin Kamili ◽  
Andrew J. Gifford ◽  
Nancy Li ◽  
Chelsea Mayoh ◽  
Shu-Oi Chow ◽  
...  

Abstract Background Predictive preclinical models play an important role in the assessment of new treatment strategies and as avatar models for personalised medicine; however, reliable and timely model generation is challenging. We investigated the feasibility of establishing patient-derived xenograft (PDX) models of high-risk neuroblastoma from a range of tumour-bearing patient materials and assessed approaches to improve engraftment efficiency. Methods PDX model development was attempted in NSG mice by using tumour materials from 12 patients, including primary and metastatic solid tumour samples, bone marrow, pleural fluid and residual cells from cytogenetic analysis. Subcutaneous, intramuscular and orthotopic engraftment were directly compared for three patients. Results PDX models were established for 44% (4/9) of patients at diagnosis and 100% (5/5) at relapse. In one case, attempted engraftment from pleural fluid resulted in an EBV-associated atypical lymphoid proliferation. Xenogeneic graft versus host disease was observed with attempted engraftment from lymph node and bone marrow tumour samples but could be prevented by T-cell depletion. Orthotopic engraftment was more efficient than subcutaneous or intramuscular engraftment. Conclusions High-risk neuroblastoma PDX models can be reliably established from diverse sample types. Orthotopic implantation allows more rapid model development, increasing the likelihood of developing an avatar model within a clinically useful timeframe.


Cells ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 418 ◽  
Author(s):  
Yoshikatsu Koga ◽  
Atsushi Ochiai

Patient-derived xenograft (PDX) models are used as powerful tools for understanding cancer biology in PDX clinical trials and co-clinical trials. In this systematic review, we focus on PDX clinical trials or co-clinical trials for drug development in solid tumors and summarize the utility of PDX models in the development of anti-cancer drugs, as well as the challenges involved in this approach, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Recently, the assessment of drug efficacy by PDX clinical and co-clinical trials has become an important method. PDX clinical trials can be used for the development of anti-cancer drugs before clinical trials, with their efficacy assessed by the modified response evaluation criteria in solid tumors (mRECIST). A few dozen cases of PDX models have completed enrollment, and the efficacy of the drugs is assessed by 1 × 1 × 1 or 3 × 1 × 1 approaches in the PDX clinical trials. Furthermore, co-clinical trials can be used for personalized care or precision medicine with the evaluation of a new drug or a novel combination. Several PDX models from patients in clinical trials have been used to assess the efficacy of individual drugs or drug combinations in co-clinical trials.


2021 ◽  
Vol 22 (17) ◽  
pp. 9369
Author(s):  
Tomohito Tanaka ◽  
Ruri Nishie ◽  
Shoko Ueda ◽  
Shunsuke Miyamoto ◽  
Sousuke Hashida ◽  
...  

Background: Patient-derived xenograft (PDX) models have been a focus of attention because they closely resemble the tumor features of patients and retain the molecular and histological features of diseases. They are promising tools for translational research. In the current systematic review, we identify publications on PDX models of cervical cancer (CC-PDX) with descriptions of main methodological characteristics and outcomes to identify the most suitable method for CC-PDX. Methods: We searched on PubMed to identify articles reporting CC-PDX. Briefly, the main inclusion criterion for papers was description of PDX created with fragments obtained from human cervical cancer specimens, and the exclusion criterion was the creation of xenograft with established cell lines. Results: After the search process, 10 studies were found and included in the systematic review. Among 98 donor patients, 61 CC-PDX were established, and the overall success rate was 62.2%. The success rate in each article ranged from 0% to 75% and was higher when using severe immunodeficient mice such as severe combined immunodeficient (SCID), nonobese diabetic (NOD) SCID, and NOD SCID gamma (NSG) mice than nude mice. Subrenal capsule implantation led to a higher engraftment rate than orthotopic and subcutaneous implantation. Fragments with a size of 1–3 mm3 were suitable for CC-PDX. No relationship was found between the engraftment rate and characteristics of the tumor and donor patient, including histology, staging, and metastasis. The latency period varied from 10 days to 12 months. Most studies showed a strong similarity in pathological and immunohistochemical features between the original tumor and the PDX model. Conclusion: Severe immunodeficient mice and subrenal capsule implantation led to a higher engraftment rate; however, orthotopic and subcutaneous implantation were alternatives. When using nude mice, subrenal implantation may be better. Fragments with a size of 1–3 mm3 were suitable for CC-PDX. Few reports have been published about CC-PDX; the results were not confirmed because of the small sample size.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hua Sun ◽  
Song Cao ◽  
R. Jay Mashl ◽  
Chia-Kuei Mo ◽  
Simone Zaccaria ◽  
...  

AbstractDevelopment of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs’ recapitulation of human tumors.


2021 ◽  
Vol 11 (2) ◽  
pp. 140
Author(s):  
Prabal Subedi ◽  
Maria Gomolka ◽  
Simone Moertl ◽  
Anne Dietz

Background and objectives: Exposure to ionizing radiation (IR) has increased immensely over the past years, owing to diagnostic and therapeutic reasons. However, certain radiosensitive individuals show toxic enhanced reaction to IR, and it is necessary to specifically protect them from unwanted exposure. Although predicting radiosensitivity is the way forward in the field of personalised medicine, there is limited information on the potential biomarkers. The aim of this systematic review is to identify evidence from a range of literature in order to present the status quo of our knowledge of IR-induced changes in protein expression in normal tissues, which can be correlated to radiosensitivity. Methods: Studies were searched in NCBI Pubmed and in ISI Web of Science databases and field experts were consulted for relevant studies. Primary peer-reviewed studies in English language within the time-frame of 2011 to 2020 were considered. Human non-tumour tissues and human-derived non-tumour model systems that have been exposed to IR were considered if they reported changes in protein levels, which could be correlated to radiosensitivity. At least two reviewers screened the titles, keywords, and abstracts of the studies against the eligibility criteria at the first phase and full texts of potential studies at the second phase. Similarly, at least two reviewers manually extracted the data and accessed the risk of bias (National Toxicology Program/Office for Health Assessment and Translation—NTP/OHAT) for the included studies. Finally, the data were synthesised narratively in accordance to synthesis without meta analyses (SWiM) method. Results: In total, 28 studies were included in this review. Most of the records (16) demonstrated increased residual DNA damage in radiosensitive individuals compared to normo-sensitive individuals based on γH2AX and TP53BP1. Overall, 15 studies included proteins other than DNA repair foci, of which five proteins were selected, Vascular endothelial growth factor (VEGF), Caspase 3, p16INK4A (Cyclin-dependent kinase inhibitor 2A, CDKN2A), Interleukin-6, and Interleukin-1β, that were connected to radiosensitivity in normal tissue and were reported at least in two independent studies. Conclusions and implication of key findings: A majority of studies used repair foci as a tool to predict radiosensitivity. However, its correlation to outcome parameters such as repair deficient cell lines and patients, as well as an association to moderate and severe clinical radiation reactions, still remain contradictory. When IR-induced proteins reported in at least two studies were considered, a protein network was discovered, which provides a direction for further studies to elucidate the mechanisms of radiosensitivity. Although the identification of only a few of the commonly reported proteins might raise a concern, this could be because (i) our eligibility criteria were strict and (ii) radiosensitivity is influenced by multiple factors. Registration: PROSPERO (CRD42020220064).


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