Murray Stackhouse

ATM-mediated Snail Serine 100 phosphorylation regulates cellular radiosensitivity.

PURPOSE Activation of the DNA damage responsive protein kinase ATM is a critical step for cellular survival in response to ionizing irradiation (IR). Direct targets of ATM regulating radiosensitivity remain to be fully investigated. We have recently reported that ATM phosphorylates the transcriptional repressor Snail on Serine 100. We aimed to further study the functional significance of ATM-mediated Snail phosphorylation in response to IR. MATERIAL AND METHODS We transfected vector-only, wild-type, the Serine 100 to alanine (S100A) or to glutamic acid (S100E) substitution of Snail into various cell lines. We assessed colony formation, γ-H2AX focus formation and the invasion index in the cells treated with or without IR. RESULTS We found that over-expression of the S100A mutant Snail in HeLa cells significantly increased radiosensitivity. Meanwhile the expression of S100E, a phospho-mimicking mutation, resulted in enhanced radio-resistance. Interestingly, S100E could rescue the radiosensitive phenotype in ATM-deficient cells. We also found that expression of S100E increased γ-H2AX focus formation and compromised inhibition of invasion in response to IR independent of cell survival. CONCLUSION ATM-mediated Snail Serine 100 phosphorylation in response to IR plays an important part in the regulation of radiosensitivity.

Preclinical Combination Therapy of Clofarabine Plus Radiation

Clofarabine, an approved anticancer drug, was evaluated in combination with radiation in six subcutaneously implanted human tumor xenograft models. Clofarabine had no effect on the growth of SF-295 glioblastoma, which was not enhanced by radiation. There was no difference between clofarabine with and without radiation in the DU-145 prostate model. The combined effect on NCI-H460 lung tumors appeared to be additive. SR475 head and neck, PANC-1 pancreatic, and HCT-116 colon tumors were radiomodified by clofarabine. The radiomodifying capacity of clofarabine was superior to that for gemcitabine in two models (PANC-1 and HCT-116) and was comparable in the other four models.

Abstract 3730: A quick and cost effective 12-cell line panel assay to predict drug activity in human tumor xenograft models

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA The procedure to identify and develop an anti-cancer drug first involves testing drug candidates in cell lines followed by human tumor xenograft models, usually selected based upon the histotype of the cell lines in which the drug showed optimal activity. Many drugs fail at this stage, as activity in cell lines does not often correlate with activity in xenograft models. This is not surprising, as we have previously shown that gene expression in xenograft models does not necessarily correlate with the cell line from which it was derived. In an attempt to improve the success rate of drugs tested in xenograft models, we have developed a fast and cost effective 12-panel human tumor cell line assay that represents the genetic diversity of all our xenograft models and several different cancer histotypes. Affymetrix genomic analysis was performed on 100 human tumor xenograft and cell line models. The genomic profiles obtained underwent Unsupervised Hierarchical Cluster Analysis to group models with similar genetic profiles. This analysis resulted in 12 distinct clusters; a representative cell line was chosen from each cluster. Stocks of each representative cell line were frozen and tested to ensure exponential growth immediately upon thawing, resulting in no waiting time for drug testing. It follows that if a candidate drug shows activity in one or more of these representative cell lines, other cell lines and/or xenograft models in the same cluster can also be tested. As the cell lines and xenograft models within the same cluster will have a similar genetic profile, the chances of success should thus be increased. To test the effectiveness of this approach, we used our database to further develop an internal compound. SRI-20900 had been tested previously in the CCRF-CEM and CAKI-1 xenograft models. The compound showed no activity in CCRF-CEM cells, but excellent activity in CAKI-1 cells. These models were in completely different clusters. So, based on these data, we tested the compound in the SKOV-3 and IGROV-1 xenograft models, as these clustered closely to the CAKI-1 model. The compound showed excellent activity in both SKOV-3 and IGROV-1 models. Although these data provide proof of principle, further work needs to be done by testing targeted compounds in the 12-cell line panel, followed by testing in xenograft models within the same cluster as the cell lines that show optimal activity. In addition, it would follow that a xenograft model within the same cluster as an inactive cell line should also be tested. We hope to start these studies early in 2014. Citation Format: Michael J. Roberts, Tommie A. Gamble, Richard D. May, Murray Stackhouse, Kristy L. Berry, Andrew D. Penman, Robert J. Rooney, Yulia Maxuitenko, Michael S. Koratich. A quick and cost effective 12-cell line panel assay to predict drug activity in human tumor xenograft models. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3730. doi:10.1158/1538-7445.AM2014-3730

Abstract 3943: Affymetrix whole genome microarray analysis of 51 human tumor cell lines representative of 16 different tissues of origin: Unsupervised hierarchical clustering

The total mRNA for each sample of 51 human tumor cell lines representative of 16 different tissues of origin was split into 3 replicates, and analyzed against the entire human genome using standard Affx WT procedures. Approximately 50% of the samples (25 out of the 51 cell lines tested) exhibited low-level clustering related to their tissue of origin. The remaining 50% (26 out of the 51 cell lines tested) did not cluster with other samples of the same tissue of origin. These data reveal the importance of testing potential anticancer agents in multiple models representative of several different tumors of origin, as there is a 50% chance that the model chosen is not actually representative of the intended tissue of origin. This analysis also showed that the pancreatic cancer cell line CFPAC-1 did not cluster with any other cell line tested, revealing the unique genetic profile of this cell line. Interestingly, the reported lung cancer cell lines NCI-H69 and NCI-H82 clustered more closely with leukemic lines than with lung or any other solid tumor. This is particularly interesting as these lines are known to grow/behave more like a suspension culture than a monolayer. The NCI recently published its genetic analysis of their 60-panel, and they revealed that the MDA-MB-435 cell line, traditionally thought to be a breast cancer cell line, more closely resembled a melanoma line; hence, it was re-classified as a melanoma (likely a metastasized melanoma that was taken from the breast site). Our analysis reveals that another traditional breast cancer cell line, UISO-BCA-1, also clusters more closely with the melanomas (including the MDA-MB-435 cell line), suggesting that this cell line also may have been misclassified. Based on these data, we suggest that any potential anticancer agent showing activity in a particular cell line should be tested in other cell lines that cluster with the active line, and not merely in other lines supposedly representative of the same tissue of origin. Furthermore, in early stage testing, it would be more prudent to test several cell lines from different clusters, rather than several cell lines from different tissues of origin. It follows that by testing orphan drugs against several cell lines from each cluster, it would be possible to significantly narrow (and possibly identify), the likely drug target. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3943. doi:10.1158/1538-7445.AM2011-3943

Abstract 4418: Affymetrix whole genome microarray analysis of 24 human tumor xenograft models and the cell lines from which they were developed: Clustering of targets vs tumor tissue of origin

The NCI recently performed microarray expression analysis on its 60-panel of human tumor cell lines. This revealed important information, with some cell lines shown to be from a different tissue of origin than originally believed. Traditionally, potential anti-cancer agents have been evaluated in these in vitro models, and then moved into the corresponding in vivo xenograft model(s) based on the in vitro results. It has been shown that drugs which are effective in vitro are not necessarily effective in vivo and vice versa. Systematic microarray analysis of traditional xenograft models in conjunction with their in vitro counterparts has not been performed. The development of a human tumor xenograft in a mouse might be expected to lead to changes in gene expression, and this could account, in some instances, for the disconnect in results observed between in vitro and in vivo models. Our aim was to perform a genetic analysis against the entire human genome using 24 cell lines from 11 differing tissues of origin that were implanted into immune-deficient mice to establish a xenograft model for each. Once the tumors reached approximately 1 cm3 in size, the tumors were removed, cut into approx. 2-3 mm3 fragments, and an in vivo tumor passage was established. Microarray expression in fragments of those xenografted tumors was compared to microarray expression in the cell line from which they were developed. The total mRNA for each sample was split into 3 replicates, and analyzed against the entire human genome using standard Affx WT procedures. The results showed that over 60% (15 of 24) of the xenograft samples clustered with the cell line from which it was developed, whereas approximately 40% (9 of 24) did not, revealing that major changes in gene expression had occurred in 40% of these xenograft samples. Furthermore, when analyzed alone, these particular 24 cell line samples clustered according to their tissue of origin, whereas the tumor fragment samples did not appear to cluster. On the basis of these data we are currently performing the same analysis on an additional 25 tumor fragments and their corresponding matched cell lines to allow for a more accurate, in-depth cluster analysis. These data strongly suggest that although precedent exists to select in vitro models on the basis of their tissue of origin, no such precedent exists for in vivo models. In vivo models should be more carefully selected to ensure that the model chosen is still representative of the tissue to be tested. It follows that a drug candidate effective in a particular in vitro model might be expected to show activity in other in vitro lines from the same tissue of origin. However, a drug candidate effective in a particular in vivo model representative of a tissue of origin should not be expected to show efficacy in other in vivo models representing the same tissue type. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4418. doi:10.1158/1538-7445.AM2011-4418