Gene expression profiles can predict panitumumab monotherapy responsiveness in human tumor xenograft models

Preclinical Organotypic Models for the Assessment of Novel Cancer Therapeutics and Treatment

The immense costs in both financial terms and preclinical research effort that occur in the development of anticancer drugs are unfortunately not matched by a substantial increase in improved clinical therapies due to the high rate of failure during clinical trials. This may be due to issues with toxicity or lack of clinical effectiveness when the drug is evaluated in patients. Currently, much cancer research is driven by the need to develop therapies that can exploit cancer cell adaptations to conditions in the tumor microenvironment such as acidosis and hypoxia, the requirement for more-specific, targeted treatments, or the exploitation of 'precision medicine' that can target known genomic changes in patient DNA. The high attrition rate for novel anticancer therapies suggests that the preclinical methods used in screening anticancer drugs need improvement. This chapter considers the advantages and disadvantages of 3D organotypic models in both cancer research and cancer drug screening, particularly in the areas of targeted drugs and the exploitation of genomic changes that can be used for therapeutic advantage in precision medicine.

Establishment and evaluation of four different types of patient-derived xenograft models

Background

Patient-derived xenografts (PDX) have a biologically stable in tumor architecture, drug responsiveness, mutational status and global gene-expression patterns. Numerous PDX models have been established to date, however their thorough characterization regarding the tumor formation and rates of tumor growth in the established models remains a challenging task. Our study aimed to provide more detailed information for establishing the PDX models successfully and effectively.

Methods

We transplanted four different types of solid tumors from 108 Chinese patients, including 21 glioblastoma (GBM), 11 lung cancers (LC), 54 gastric cancers (GC) and 21 colorectal cancers (CRC), and took tumor tissues passaged for three successive generations. Here we report the rate of tumor formation, tumor-forming times, tumor growth curves and mortality of mice in PDX model. We also report H&E staining and immunohistochemistry for HLA-A, CD45, Ki67, GFAP, and CEA protein expression between patient cancer tissues and PDX models.

Results

Tumor formation rate increased significantly in subsequent tumor generations. Also, the survival rates of GC and CRC were remarkably higher than GBM and LC. As for the time required for the formation of tumors, which reflects the tumor growth rate, indicated that tumor growth rate always increased as the generation number increased. The tumor growth curves also illustrate this law. Similarly, the survival rate of PDX mice gradually improved with the increased generation number in GC and CRC. And generally, there was more proliferation (Ki67+) in the PDX models than in the patient tumors, which was in accordance with the results of tumor growth rate. The histological findings confirm similar histological architecture and degrees of differentiation between patient cancer tissues and PDX models with statistical analysis by GraphPad Prism 5.0.

Conclusion

We established four different types of PDX models successfully, and our results add to the current understanding of the establishment of PDX models and may contribute to the extension of application of different types of PDX models.

Evaluation of anti-tumorigenic activity of BP3B against colon cancer with patient-derived tumor xenograft model

BACKGROUND

KIOM-CRC#BP3B (BP3B) is a novel herbal prescription that is composed of three plant extracts. Our preliminary study identified that BP3B exhibited potent anti-proliferative activity against various types of cancer cell lines in vitro. Because the in vivo anti-tumor effect of BP3B is not evaluated before clinical trial, we want to test it using patient's samples.

METHODS

To confirm the in vivo anti-cancer effect of BP3B, we used genetically characterized patient-derived colon tumor xenograft (PDTX) mouse model. Anti-cancer activity was evaluated with apoptosis, proliferation, angiogenesis and histological analysis.

RESULTS

Oral administration of BP3B significantly inhibited the tumor growth in two PDTX models. Furthermore, TUNEL assay showed that BP3B induced apoptosis of tumor tissues, which was associated with degradation of PARP and Caspase 8 and activation of Caspase 3. We also observed that BP3B inhibited cancer cell proliferation by down-regulation of Cyclin D1 and induction of p27 proteins. Inhibition of angiogenesis in BP3B-treated group was observed with immunofluorescence staining using CD31 and Tie-2 antibodies.

CONCLUSION

These findings indicated that BP3B has a strong growth-inhibitory activity against colon cancer in in vivo model and will be a good therapeutic candidate for treatment of refractory colon cancer.

CASTIN: a system for comprehensive analysis of cancer-stromal interactome

BACKGROUND

Cancer microenvironment plays a vital role in cancer development and progression, and cancer-stromal interactions have been recognized as important targets for cancer therapy. However, identifying relevant and druggable cancer-stromal interactions is challenging due to the lack of quantitative methods to analyze whole cancer-stromal interactome.

RESULTS

We present CASTIN (CAncer-STromal INteractome analysis), a novel framework for the evaluation of cancer-stromal interactome from RNA-Seq data using cancer xenograft models. For each ligand-receptor interaction which is derived from curated protein-protein interaction database, CASTIN summarizes gene expression profiles of cancer and stroma into three evaluation indices. These indices provide quantitative evaluation and comprehensive visualization of interactome, and thus enable to identify critical cancer-microenvironment interactions, which would be potential drug targets. We applied CASTIN to the dataset of pancreas ductal adenocarcinoma, and successfully characterized the individual cancer in terms of cancer-stromal relationships, and identified both well-known and less-characterized druggable interactions.

CONCLUSIONS

CASTIN provides comprehensive view of cancer-stromal interactome and is useful to identify critical interactions which may serve as potential drug targets in cancer-microenvironment. CASTIN is available at: http://github.com/tmd-gpat/CASTIN .

Targeting tumour hypoxia to prevent cancer metastasis. From biology, biosensing and technology to drug development: the METOXIA consortium

The hypoxic areas of solid cancers represent a negative prognostic factor irrespective of which treatment modality is chosen for the patient. Still, after almost 80 years of focus on the problems created by hypoxia in solid tumours, we still largely lack methods to deal efficiently with these treatment-resistant cells. The consequences of this lack may be serious for many patients: Not only is there a negative correlation between the hypoxic fraction in tumours and the outcome of radiotherapy as well as many types of chemotherapy, a correlation has been shown between the hypoxic fraction in tumours and cancer metastasis. Thus, on a fundamental basis the great variety of problems related to hypoxia in cancer treatment has to do with the broad range of functions oxygen (and lack of oxygen) have in cells and tissues. Therefore, activation-deactivation of oxygen-regulated cascades related to metabolism or external signalling are important areas for the identification of mechanisms as potential targets for hypoxia-specific treatment. Also the chemistry related to reactive oxygen radicals (ROS) and the biological handling of ROS are part of the problem complex. The problem is further complicated by the great variety in oxygen concentrations found in tissues. For tumour hypoxia to be used as a marker for individualisation of treatment there is a need for non-invasive methods to measure oxygen routinely in patient tumours. A large-scale collaborative EU-financed project 2009-2014 denoted METOXIA has studied all the mentioned aspects of hypoxia with the aim of selecting potential targets for new hypoxia-specific therapy and develop the first stage of tests for this therapy. A new non-invasive PET-imaging method based on the 2-nitroimidazole [(18)F]-HX4 was found to be promising in a clinical trial on NSCLC patients. New preclinical models for testing of the metastatic potential of cells were developed, both in vitro (2D as well as 3D models) and in mice (orthotopic grafting). Low density quantitative real-time polymerase chain reaction (qPCR)-based assays were developed measuring multiple hypoxia-responsive markers in parallel to identify tumour hypoxia-related patterns of gene expression. As possible targets for new therapy two main regulatory cascades were prioritised: The hypoxia-inducible-factor (HIF)-regulated cascades operating at moderate to weak hypoxia (<1% O(2)), and the unfolded protein response (UPR) activated by endoplasmatic reticulum (ER) stress and operating at more severe hypoxia (<0.2%). The prioritised targets were the HIF-regulated proteins carbonic anhydrase IX (CAIX), the lactate transporter MCT4 and the PERK/eIF2α/ATF4-arm of the UPR. The METOXIA project has developed patented compounds targeting CAIX with a preclinical documented effect. Since hypoxia-specific treatments alone are not curative they will have to be combined with traditional anti-cancer therapy to eradicate the aerobic cancer cell population as well.

Cancer subclonal genetic architecture as a key to personalized medicine

The future of personalized oncological therapy will likely rely on evidence-based medicine to integrate all of the available evidence to delineate the most efficacious treatment option for the patient. To undertake evidence-based medicine through use of targeted therapy regimens, identification of the specific underlying causative mutation(s) driving growth and progression of a patient's tumor is imperative. Although molecular subtyping is important for planning and treatment, intraclonal genetic diversity has been recently highlighted as having significant implications for biopsy-based prognosis. Overall, delineation of the clonal architecture of a patient's cancer and how this will impact on the selection of the most efficacious therapy remain a topic of intense interest.

Patient-derived tumor xenografts: transforming clinical samples into mouse models

Tumor graft models (also known as patient-derived xenografts or PDX) are based on the transfer of primary tumors directly from the patient into an immunodeficient mouse. Because PDX mice are derived from human tumors, they offer a tool for developing anticancer therapies and personalized medicine for patients with cancer. In addition, these models can be used to study metastasis and tumor genetic evolution. This review examines the development, challenges, and broad use of these attractive preclinical models.