The contribution of DNA replication stress marked by high-intensity, pan-nuclear γH2AX staining to chemosensitization by CHK1 and WEE1 inhibitors

<p>Small molecule inhibitors of the checkpoint proteins CHK1 and WEE1 are currently in clinical development in combination with the antimetabolite gemcitabine. It is unclear, however, if there is a therapeutic advantage to CHK1 vs. WEE1 inhibition for chemosensitization. The goals of this study were to directly compare the relative efficacies of the CHK1 inhibitor MK8776 and the WEE1 inhibitor AZD1775 to sensitize pancreatic cancer cell lines to gemcitabine and to identify pharmacodynamic biomarkers predictive of chemosensitization. Cells treated with gemcitabine and either MK8776 or AZD1775 were first assessed for clonogenic survival. With the exception of the homologous recombination-defective Capan1 cells, which were relatively insensitive to MK8776, we found that these cell lines were similarly sensitized to gemcitabine by CHK1 or WEE1 inhibition. The abilities of either the CDK1/2 inhibitor roscovitine or exogenous nucleosides to prevent MK8776 or AZD1775-mediated chemosensitization, however, were both inhibitor-dependent and variable among cell lines. Given the importance of DNA replication stress to gemcitabine chemosensitization, we next assessed high-intensity, pan-nuclear γH2AX staining as a pharmacodynamic marker for sensitization. In contrast to total γH2AX, aberrant mitotic entry or sub-G1 DNA content, high-intensity γH2AX staining correlated with chemosensitization by either MK8776 or AZD1775 (R² 0.83 – 0.53). In summary, we found that MK8776 and AZD1775 sensitize to gemcitabine with similar efficacy. Furthermore, our results suggest that the effects of CHK1 and WEE1 inhibition on gemcitabine-mediated replication stress best predict chemosensitization and support the use of high-intensity or pan-nuclear γH2AX staining as a marker for therapeutic response.</p

Repeated-measures ANOVA of FA changes from pre-RT to end-RT.

<p>Degrees of freedom for within-subject effects corrected for lack of sphericity by Greenhouse-Geisser method, ε = 0.311.</p

Significant changes in AD from pre-RT to one month post-RT.

<p>Arrowheads: Z = +10, right superior longitudinal fasciculus; Z = +35, right superior cingulum; Y = −40, right superior cingulum. Significant results per color chart, blue is TBSS skeleton without significant results. Depicted on MNI ICBM152 standard brain T1-weighted image <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057768#pone.0057768-Mazziotta1" target="_blank">[34]</a>. Units are µm²/s.</p

Fourteen white matter structures.

<p>Fourteen white matter structures.</p

Significant changes in RD from pre-RT to end-RT.

<p>Arrowheads: Z = −5, left inferior cingulum; Z = +10, left fornix crus; Z = +25, corpus callosum body; Y = −40, left inferior cingulum; X = 0, fornix columns. Significant results per color chart, blue is TBSS skeleton without significant results. Depicted on MNI ICBM152 standard brain T1-weighted image <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057768#pone.0057768-Mazziotta1" target="_blank">[34]</a>. Units are µm²/s.</p

Pre-RT to one month post-RT significant voxel overlap.

<p>(a) Color key to significant voxel changes from pre-RT to one month post-RT in AD, RD, and FA with overlapping voxels. Underlying white matter skeleton with no significant changes is gray. (b) Venn diagram depicting proportion of white matter skeleton with significant changes. FA = 82.9%; RD = 37.4%; AD = 12.9%; FA ∩ RD = 33.5%; FA ∩ AD = 10.4%; RD ∩ AD = 0.1%. Labels are MNI coordinates.</p

White matter regions of interest.

<p>ICBM DTI-81 white matter atlas <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057768#pone.0057768-Mori1" target="_blank">[33]</a> depicted on FMRIB58 standard-space FA map <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057768#pone.0057768-Smith2" target="_blank">[35]</a>. Data-derived white matter skeleton mask in white. AnCr, anterior corona radiata; AnIC, anterior internal capsules; PoIC, posterior internal capsules; ReIC, retrolenticular internal capsules; EC, external capsules; FxCr, fornix crura; InCg, inferior cingula; SuCg, superior cingula; SLF, superior longitudinal fasciculi; FxCo, fornix columns; CCs, corpus callosum splenium; CCb, corpus callosum body; CCg, corpus callosum genu. Posterior corona radiata not depicted.</p

Biological processes and pathways significantly enriched in the M-Sig genes.

<p>Biological processes and pathways significantly enriched in the M-Sig genes.</p

Development and Validation of a Novel Platform-Independent Metastasis Signature in Human Breast Cancer

<div><p>Purpose</p><p>The molecular drivers of metastasis in breast cancer are not well understood. Therefore, we sought to identify the biological processes underlying distant progression and define a prognostic signature for metastatic potential in breast cancer.</p><p>Experimental design</p><p><i>In vivo</i> screening for metastases was performed using Chick Chorioallantoic Membrane assays in 21 preclinical breast cancer models. Expressed genes associated with metastatic potential were identified using high-throughput analysis. Correlations with biological function were determined using the Database for Annotation, Visualization and Integrated Discovery.</p><p>Results</p><p>We identified a broad range of metastatic potential that was independent of intrinsic breast cancer subtypes. 146 genes were significantly associated with metastasis progression and were linked to cancer-related biological functions, including cell migration/adhesion, Jak-STAT, TGF-beta, and Wnt signaling. These genes were used to develop a platform-independent gene expression signature (M-Sig), which was trained and subsequently validated on 5 independent cohorts totaling nearly 1800 breast cancer patients with all p-values < 0.005 and hazard ratios ranging from approximately 2.5 to 3. On multivariate analysis accounting for standard clinicopathologic prognostic variables, M-Sig remained the strongest prognostic factor for metastatic progression, with p-values < 0.001 and hazard ratios > 2 in three different cohorts.</p><p>Conclusion</p><p>M-Sig is strongly prognostic for metastatic progression, and may provide clinical utility in combination with treatment prediction tools to better guide patient care. In addition, the platform-independent nature of the signature makes it an excellent research tool as it can be directly applied onto existing, and future, datasets.</p></div