Mutant POLQ and POLZ/REV3L DNA polymerases may contribute to the favorable survival of patients with tumors with POLE mutations outside the exonuclease domain.

BACKGROUND: Mutations in the exonuclease domain of POLE, a DNA polymerase associated with DNA replication and repair, lead to cancers with ultra-high mutation rates. Most studies focus on intestinal and uterine cancers with POLE mutations. These cancers exhibit a significant immune cell infiltrate and favorable prognosis. We questioned whether loss of function of other DNA polymerases can cooperate to POLE to generate the ultramutator phenotype. METHODS: We used cases and data from 15 cancer types in The Cancer Genome Atlas to investigate mutation frequencies of 14 different DNA polymerases. We tested whether tumor mutation burden, patient outcome (disease-free survival) and immune cell infiltration measured by ESTIMATE can be attributed to mutations in POLQ and POLZ/REV3L. RESULTS: Thirty six percent of colorectal, stomach and endometrial cancers with POLE mutations carried additional mutations in POLQ (E/Q), POLZ/REV3L (E/Z) or both DNA polymerases (E/Z/Q). The mutation burden in these tumors was significantly greater compared to POLE-only (E) mutant tumors (p < 0.001). In addition, E/Q, E/Z, and E/Q/Z mutant tumors possessed an increased frequency of mutations in the POLE exonuclease domain (p = 0.013). Colorectal, stomach and endometrial E/Q, E/Z, and E/Q/Z mutant tumors within TCGA demonstrated 100% disease-free survival, even if the POLE mutations occurred outside the exonuclease domain (p = 0.003). However, immune scores in these tumors were related to microsatellite instability (MSI) and not POLE mutation status. This suggests that the host immune response may not be the sole mechanism for prolonged disease-free survival of ultramutated tumors in this cohort. CONCLUSION: Results in this study demonstrate that mutations in POLQ and REV3L in POLE mutant tumors should undergo further investigation to determine whether POLQ and REV3L mutations contribute to the ultramutator phenotype and favorable outcome of patients with POLE mutant tumors.

Spatial Mapping of Myeloid Cells and Macrophages by Multiplexed Tissue Staining.

An array of phenotypically diverse myeloid cells and macrophages (MC&M) resides in the tumor microenvironment, requiring multiplexed detection systems for visualization. Here we report an automated, multiplexed staining approach, named PLEXODY, that consists of five MC&M-related fluorescently-tagged antibodies (anti - CD68, - CD163, - CD206, - CD11b, and - CD11c), and three chromogenic antibodies, reactive with high- and low-molecular weight cytokeratins and CD3, highlighting tumor regions, benign glands and T cells. The staining prototype and image analysis methods which include a pixel/area-based quantification were developed using tissues from inflamed colon and tonsil and revealed a unique tissue-specific composition of 14 MC&M-associated pixel classes. As a proof-of-principle, PLEXODY was applied to three cases of pancreatic, prostate and renal cancers. Across digital images from these cancer types we observed 10 MC&M-associated pixel classes at frequencies greater than 3%. Cases revealed higher frequencies of single positive compared to multi-color pixels and a high abundance of CD68+/CD163+ and CD68+/CD163+/CD206+ pixels. Significantly more CD68+ and CD163+ vs. CD11b+ and CD11c+ pixels were in direct contact with tumor cells and T cells. While the greatest percentage (~70%) of CD68+ and CD163+ pixels was 0-20 microns away from tumor and T cell borders, CD11b+ and CD11c+ pixels were detected up to 240 microns away from tumor/T cell masks. Together, these data demonstrate significant differences in densities and spatial organization of MC&M-associated pixel classes, but surprising similarities between the three cancer types.

Regulation of inside-out ß1-integrin activation by CDCP1.

Tumor metastasis depends on the dynamic regulation of cell adhesion through ß1-integrin. The Cub-Domain Containing Protein-1, CDCP1, is a transmembrane glycoprotein which regulates cell adhesion. Overexpression and loss of CDCP1 have been observed in the same cancer types to promote metastatic progression. Here, we demonstrate reduced CDCP1 expression in high-grade, primary prostate cancers, circulating tumor cells and tumor metastases of patients with castrate-resistant prostate cancer. CDCP1 is expressed in epithelial and not mesenchymal cells, and its cell surface and mRNA expression declines upon stimulation with TGFß1 and epithelial-to-mesenchymal transition. Silencing of CDCP1 in DU145 and PC3 cells resulted in 3.4-fold higher proliferation of non-adherent cells and 4.4-fold greater anchorage independent growth. CDCP1-silenced tumors grew in 100% of mice, compared to 30% growth of CDCP1-expressing tumors. After CDCP1 silencing, cell adhesion and migration diminished 2.1-fold, caused by loss of inside-out activation of ß1-integrin. We determined that the loss of CDCP1 reduces CDK5 kinase activity due to the phosphorylation of its regulatory subunit, CDK5R1/p35, by c-SRC on Y234. This generates a binding site for the C2 domain of PKCδ, which in turn phosphorylates CDK5 on T77. The resulting dissociation of the CDK5R1/CDK5 complex abolishes the activity of CDK5. Mutations of CDK5-T77 and CDK5R1-Y234 phosphorylation sites re-establish the CDK5/CDKR1 complex and the inside-out activity of ß1-integrin. Altogether, we discovered a new mechanism of regulation of CDK5 through loss of CDCP1, which dynamically regulates ß1-integrin in non-adherent cells and which may promote vascular dissemination in patients with advanced prostate cancer.

ONECUT2 is a targetable master regulator of lethal prostate cancer that suppresses the androgen axis.

Treatment of prostate cancer (PC) by androgen suppression promotes the emergence of aggressive variants that are androgen receptor (AR) independent. Here we identify the transcription factor ONECUT2 (OC2) as a master regulator of AR networks in metastatic castration-resistant prostate cancer (mCRPC). OC2 acts as a survival factor in mCRPC models, suppresses the AR transcriptional program by direct regulation of AR target genes and the AR licensing factor FOXA1, and activates genes associated with neural differentiation and progression to lethal disease. OC2 appears active in a substantial subset of human prostate adenocarcinoma and neuroendocrine tumors. Inhibition of OC2 by a newly identified small molecule suppresses metastasis in mice. These findings suggest that OC2 displaces AR-dependent growth and survival mechanisms in many cases where AR remains expressed, but where its activity is bypassed. OC2 is also a potential drug target in the metastatic phase of aggressive PC.

PARP-1 regulates DNA repair factor availability.

PARP-1 holds major functions on chromatin, DNA damage repair and transcriptional regulation, both of which are relevant in the context of cancer. Here, unbiased transcriptional profiling revealed the downstream transcriptional profile of PARP-1 enzymatic activity. Further investigation of the PARP-1-regulated transcriptome and secondary strategies for assessing PARP-1 activity in patient tissues revealed that PARP-1 activity was unexpectedly enriched as a function of disease progression and was associated with poor outcome independent of DNA double-strand breaks, suggesting that enhanced PARP-1 activity may promote aggressive phenotypes. Mechanistic investigation revealed that active PARP-1 served to enhance E2F1 transcription factor activity, and specifically promoted E2F1-mediated induction of DNA repair factors involved in homologous recombination (HR). Conversely, PARP-1 inhibition reduced HR factor availability and thus acted to induce or enhance "BRCA-ness". These observations bring new understanding of PARP-1 function in cancer and have significant ramifications on predicting PARP-1 inhibitor function in the clinical setting.

Data integration from pathology slides for quantitative imaging of multiple cell types within the tumor immune cell infiltrate.

BACKGROUND: Immune cell infiltrates (ICI) of tumors are scored by pathologists around tumor glands. To obtain a better understanding of the immune infiltrate, individual immune cell types, their activation states and location relative to tumor cells need to be determined. This process requires precise identification of the tumor area and enumeration of immune cell subtypes separately in the stroma and inside tumor nests. Such measurements can be accomplished by a multiplex format using immunohistochemistry (IHC). METHOD: We developed a pipeline that combines immunohistochemistry (IHC) and digital image analysis. One slide was stained with pan-cytokeratin and CD45 and the other slide with CD8, CD4 and CD68. The tumor mask generated through pan-cytokeratin staining was transferred from one slide to the other using affine image co-registration. Bland-Altman plots and Pearson correlation were used to investigate differences between densities and counts of immune cell underneath the transferred versus manually annotated tumor masks. One-way ANOVA was used to compare the mask transfer error for tissues with solid and glandular tumor architecture. RESULTS: The overlap between manual and transferred tumor masks ranged from 20%-90% across all cases. The error of transferring the mask was 2- to 4-fold greater in tumor regions with glandular compared to solid growth pattern (p < 10-6). Analyzing data from a single slide, the Pearson correlation coefficients of cell type densities outside and inside tumor regions were highest for CD4 + T-cells (r = 0.8), CD8 + T-cells (r = 0.68) or CD68+ macrophages (r = 0.79). The correlation coefficient for CD45+ T- and B-cells was only 0.45. The transfer of the mask generated an error in the measurement of intra- and extra- tumoral CD68+, CD8+ or CD4+ counts (p < 10-10). CONCLUSIONS: In summary, we developed a general method to integrate data from IHC stained slides into a single dataset. Because of the transfer error between slides, we recommend applying the antibody for demarcation of the tumor on the same slide as the ICI antibodies.

A novel machine learning approach reveals latent vascular phenotypes predictive of renal cancer outcome.

Gene expression signatures are commonly used as predictive biomarkers, but do not capture structural features within the tissue architecture. Here we apply a 2-step machine learning framework for quantitative imaging of tumor vasculature to derive a spatially informed, prognostic gene signature. The trained algorithms classify endothelial cells and generate a vascular area mask (VAM) in H&E micrographs of clear cell renal cell carcinoma (ccRCC) cases from The Cancer Genome Atlas (TCGA). Quantification of VAMs led to the discovery of 9 vascular features (9VF) that predicted disease-free-survival in a discovery cohort (n = 64, HR = 2.3). Correlation analysis and information gain identified a 14 gene expression signature related to the 9VF's. Two generalized linear models with elastic net regularization (14VF and 14GT), based on the 14 genes, separated independent cohorts of up to 301 cases into good and poor disease-free survival groups (14VF HR = 2.4, 14GT HR = 3.33). For the first time, we successfully applied digital image analysis and targeted machine learning to develop prognostic, morphology-based, gene expression signatures from the vascular architecture. This novel morphogenomic approach has the potential to improve previous methods for biomarker development.

Neoadjuvant dasatinib for muscle-invasive bladder cancer with tissue analysis of biologic activity.

OBJECTIVES: Preclinical urothelial carcinoma models suggest activity of dasatinib, an oral SRC-family kinase (SFK) inhibitor. We sought to determine the feasibility and biologic activity of neoadjuvant dasatinib (Neo-D) in patients with muscle-invasive urothelial carcinoma of the bladder (miUCB) preceding radical cystectomy (RC). MATERIALS AND METHODS: A prospective multisite phase II trial was conducted. Key eligibility criteria included: resectable miUCB (T2-T4a, N0, M0), and Eastern Cooperative Oncology Group performance status 0 to 1. Patients received oral Neo-D 100mg once daily for 28±7 days followed by RC 8 to 24 hours after the last dose. The primary end point was feasibility, defined as≥60% of patients with miUCB completing therapy without treatment-related dose-limiting toxicity (DLT). Pre- and posttreatment tumor immunohistochemistry of phosphorylated SFK (pSFK), Ki-67, and cleaved caspase (Cas)-3 results were analyzed by paired t test. RESULTS: The study completed full accrual with enrollment of 25 patients of whom 23 were evaluable for feasibility. The study achieved its primary end point with 15 patients (65%) completing therapy without treatment-related DLTs. DLTs included: fatigue (n = 2), pulmonary embolism, abdominal pain, supraventricular tachycardia, enteric fistula, hematuria, and dyspnea (n = 1 each). At RC, 5 patients (23%) had

Quantitative imaging for development of companion diagnostics to drugs targeting HGF/MET.

The limited clinical success of anti-HGF/MET drugs can be attributed to the lack of predictive biomarkers that adequately select patients for treatment. We demonstrate here that quantitative digital imaging of formalin fixed paraffin embedded tissues stained by immunohistochemistry can be used to measure signals from weakly staining antibodies and provides new opportunities to develop assays for detection of MET receptor activity. To establish a biomarker panel of MET activation, we employed seven antibodies measuring protein expression in the HGF/MET pathway in 20 cases and up to 80 cores from 18 human cancer types. The antibodies bind to epitopes in the extra (EC)- and intracellular (IC) domains of MET (MET4EC, SP44_METIC, D1C2_METIC), to MET-pY1234/pY1235, a marker of MET kinase activation, as well as to HGF, pSFK or pMAPK. Expression of HGF was determined in tumour cells (T_HGF) as well as in stroma surrounding cancer (St_HGF). Remarkably, MET4EC correlated more strongly with pMET (r = 0.47) than SP44_METIC (r = 0.21) or D1C2_METIC (r = 0.08) across 18 cancer types. In addition, correlation coefficients of pMET and T_HGF (r = 0.38) and pMET and pSFK (r = 0.56) were high. Prediction models of MET activation reveal cancer-type specific differences in performance of MET4EC, SP44_METIC and anti-HGF antibodies. Thus, we conclude that assays to predict the response to HGF/MET inhibitors require a cancer-type specific antibody selection and should be developed in those cancer types in which they are employed clinically.