Overview of pre-clinical and clinical studies targeting angiogenesis in pancreatic ductal adenocarcinoma

The importance of angiogenesis in pancreatic ductal adenocarcinoma (PDAC) and its therapeutic potential have been explored in both pre-clinical and clinical studies. Human PDACs overexpress a number of angiogenic factors and their cognate high-affinity receptors, and anti-angiogenic agents reduce tumor volume, metastasis, and microvessel density (MVD), and improve survival in subcutaneous and orthotopic pre-clinical models. Nonetheless, clinical trials using anti-angiogenic therapy have been overwhelmingly unsuccessful. This review will focus on these pre-clinical and clinical studies, the potential reasons for failure in the clinical setting, and ways these shortcomings could be addressed in future investigations of angiogenic mechanisms in PDAC

Angiogenic gene signature in human pancreatic cancer correlates with TGF-beta and inflammatory transcriptomes

Indiana University-Purdue University Indianapolis (IUPUI)Pancreatic ductal adenocarcinoma (PDAC), which comprises 85% of pancreatic cancers, is the 4th leading cause of cancer death in the United States with a 5-year survival rate of 8%. While human PDACs (hPDACs) are hypovascular, they also overexpress a number of angiogenic growth factors and receptors. Additionally, the use of anti-angiogenic agents in murine models of PDAC leads to reduced tumor volume, tumor spread, and microvessel density (MVD), and improved survival. Nonetheless, clinical trials using anti-angiogenic therapy have been overwhelmingly unsuccessful in hPDAC. On the other hand, pancreatic neuroendocrine tumors (PNETs) account for only 2% of pancreatic tumors, yet they are very vascular and classically angiogenic, respond to anti-angiogenic therapy, and confer a better prognosis than PDAC even in the metastatic setting. In an effort to compare and contrast the angiogenic transcriptomes of these two tumor types, we analyzed RNA-Sequencing (RNA-Seq) data from The Cancer Genome Atlas (TCGA) and found that a pro-angiogenic gene signature is present in 35% of PDACs and that it is mostly distinct from the angiogenic signature present in PNETs. The pro-angiogenic PDAC subgroup also exhibits a transcriptome that reflects active TGF-β signaling, less frequent SMAD4 inactivation than PDACs without the signature, and up-regulation of several pro-inflammatory genes, including members of JAK signaling pathways. Consequently, targeting the TGF-β receptor type-1 kinase with SB505124 and JAK1/2 with ruxolitinib blocks proliferative crosstalk between human pancreatic cancer cells (PCCs) and human endothelial cells (ECs). Additionally, treatment of the KRC (oncogenic Kras, homozygous deletion of Rb1) and KPC (oncogenic Kras, mutated Trp53) genetically engineered PDAC mouse models with ruxolitinib suppresses murine PDAC (mPDAC) progression only in the KRC model, which shows superior enrichment and differential expression of the human pro-angiogenic gene signature as compared to KPC tumors. These findings suggest that targeting both TGF-β and JAK signaling in the 35% of PDAC patients whose cancers exhibit an pro-angiogenic gene signature should be explored in a clinical trial

Angiogenic gene signature in human pancreatic cancer correlates with TGF-beta and inflammatory transcriptomes

Pancreatic ductal adenocarcinomas (PDACs) are hypovascular, but overexpress pro-angiogenic factors and exhibit regions of microvasculature. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we previously reported that ~12% of PDACs have an angiogenesis gene signature with increased expression of multiple pro-angiogenic genes. By analyzing the recently expanded TCGA dataset, we now report that this signature is present in ~35% of PDACs but that it is mostly distinct from an angiogenesis signature present in pancreatic neuroendocrine tumors (PNETs). These PDACs exhibit a transcriptome that reflects active TGF-β signaling, and up-regulation of several pro-inflammatory genes, and many members of JAK signaling pathways. Moreover, expression of SMAD4 and HDAC9 correlates with endothelial cell abundance in PDAC tissues. Concomitantly targeting the TGF-β type I receptor (TβRI) kinase with SB505124 and JAK1-2 with ruxolitinib suppresses JAK1 phosphorylation and blocks proliferative cross-talk between human pancreatic cancer cells (PCCs) and human endothelial cells (ECs), and these anti-proliferative effects were mimicked by JAK1 silencing in ECs. By contrast, either inhibitor alone does not suppress their enhanced proliferation in 3D co-cultures. These findings suggest that targeting both TGF-β and JAK1 signaling could be explored therapeutically in the 35% of PDAC patients whose cancers exhibit an angiogenesis gene signature

Combined targeting of TGF-beta, EGFR and HER2 suppresses lymphangiogenesis and metastasis in a pancreatic cancer model

Pancreatic ductal adenocarcinomas (PDAC) are aggressive with frequent lymphatic spread. By analysis of data from The Cancer Genome Atlas, we determined that ∼35% of PDACs have a pro-angiogenic gene signature. We now show that the same PDACs exhibit increased expression of lymphangiogenic genes and lymphatic endothelial cell (LEC) markers, and that LEC abundance in human PDACs correlates with endothelial cell microvessel density. Lymphangiogenic genes and LECs are also elevated in murine PDACs arising in the KRC (mutated Kras; deleted RB) and KIC (mutated Kras; deleted INK4a) genetic models. Moreover, pancreatic cancer cells (PCCs) derived from KRC tumors express and secrete high levels of lymphangiogenic factors, including the EGF receptor ligand, amphiregulin. Importantly, TGF-β1 increases lymphangiogenic genes and amphiregulin expression in KRC PCCs but not in murine PCCs that lack SMAD4, and combinatorial targeting of the TGF-β type I receptor (TβRI) with LY2157299 and EGFR/HER2 with lapatanib suppresses tumor growth and metastasis in a syngeneic orthotopic model, and attenuates tumor lymphangiogenesis and angiogenesis while reducing lymphangiogenic genes and amphiregulin and enhancing apoptosis. Therefore, this combination could be beneficial in PDACs with lymphangiogenic or angiogenic gene signatures

CIBERSORT analysis of TCGA and METABRIC identifies subgroups with better outcomes in triple negative breast cancer

Studies have shown that the presence of tumor infiltrating lymphocytes (TILs) in Triple Negative Breast Cancer (TNBC) is associated with better prognosis. However, the molecular mechanisms underlying these immune cell differences are not well delineated. In this study, analysis of hematoxylin and eosin images from The Cancer Genome Atlas (TCGA) breast cancer cohort failed to show a prognostic benefit of TILs in TNBC, whereas CIBERSORT analysis, which quantifies the proportion of each immune cell type, demonstrated improved overall survival in TCGA TNBC samples with increased CD8 T cells or CD8 plus CD4 memory activated T cells and in Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) TNBC samples with increased gamma delta T cells. Twenty-five genes showed mutational frequency differences between the TCGA high and low T cell groups, and many play important roles in inflammation or immune evasion (ATG2B, HIST1H2BC, PKD1, PIKFYVE, TLR3, NOTCH3, GOLGB1, CREBBP). Identification of these mutations suggests novel mechanisms by which the cancer cells attract immune cells and by which they evade or dampen the immune system during the cancer immunoediting process. This study suggests that integration of mutations with CIBERSORT analysis could provide better prediction of outcomes and novel therapeutic targets in TNBC cases

Organ-specific adaptive signaling pathway activation in metastatic breast cancer cells

Breast cancer metastasizes to bone, visceral organs, and/or brain depending on the subtype, which may involve activation of a host organ-specific signaling network in metastatic cells. To test this possibility, we determined gene expression patterns in MDA-MB-231 cells and its mammary fat pad tumor (TMD-231), lung-metastasis (LMD-231), bone-metastasis (BMD-231), adrenal-metastasis (ADMD-231) and brain-metastasis (231-BR) variants. When gene expression between metastases was compared, 231-BR cells showed the highest gene expression difference followed by ADMD-231, LMD-231, and BMD-231 cells. Neuronal transmembrane proteins SLITRK2, TMEM47, and LYPD1 were specifically overexpressed in 231-BR cells. Pathway-analyses revealed activation of signaling networks that would enable cancer cells to adapt to organs of metastasis such as drug detoxification/oxidative stress response/semaphorin neuronal pathway in 231-BR, Notch/orphan nuclear receptor signals involved in steroidogenesis in ADMD-231, acute phase response in LMD-231, and cytokine/hematopoietic stem cell signaling in BMD-231 cells. Only NF-κB signaling pathway activation was common to all except BMD-231 cells. We confirmed NF-κB activation in 231-BR and in a brain metastatic variant of 4T1 cells (4T1-BR). Dimethylaminoparthenolide inhibited NF-κB activity, LYPD1 expression, and proliferation of 231-BR and 4T1-BR cells. Thus, transcriptome change enabling adaptation to host organs is likely one of the mechanisms associated with organ-specific metastasis and could potentially be targeted therapeutically

TCGA data and patient-derived orthotopic xenografts highlight pancreatic cancer-associated angiogenesis

Pancreatic ductal adenocarcinomas (PDACs) overexpress pro-angiogenic factors but are not viewed as vascular. Using data from The Cancer Genome Atlas we demonstrate that a subset of PDACs exhibits a strong pro-angiogenic signature that includes 37 genes, such as HDAC9, that are overexpressed in PDAC arising in KRC mice, which express mutated Kras and lack RB. Moreover, patient-derived orthotopic xenografts can exhibit tumor angiogenesis, whereas conditioned media (CM) from KRC-derived pancreatic cancer cells (PCCs) enhance endothelial cell (EC) growth and migration, and activate canonical TGF-β signaling and STAT3. Inhibition of the type I TGF-β receptor with SB505124 does not alter endothelial activation in vitro, but decreases pro-angiogenic gene expression and suppresses angiogenesis in vivo. Conversely, STAT3 silencing or JAK1-2 inhibition with ruxolitinib blocks CM-enhanced EC proliferation. STAT3 disruption also suppresses endothelial HDAC9 and blocks CM-induced HDAC9 expression, whereas HDAC9 re-expression restores CM-enhanced endothelial proliferation. Moreover, ruxolitinib blocks mitogenic EC/PCC cross-talk, and suppresses endothelial p-STAT3 and HDAC9, and PDAC progression and angiogenesis in vivo, while markedly prolonging survival of KRC mice. Thus, targeting JAK1-2 with ruxolitinib blocks a final pathway that is common to multiple pro-angiogenic factors, suppresses EC-mediated PCC proliferation, and may be useful in PDACs with a strong pro-angiogenic signature

Identification of a novel type of spacer element required for imprinting in fission yeast

Asymmetrical segregation of differentiated sister chromatids is thought to be important for cellular differentiation in higher eukaryotes. Similarly, in fission yeast, cellular differentiation involves the asymmetrical segregation of a chromosomal imprint. This imprint has been shown to consist of two ribonucleotides that are incorporated into the DNA during laggingstrand synthesis in response to a replication pause, but the underlying mechanism remains unknown. Here we present key novel discoveries important for unravelling this process. Our data show that cis-acting sequences within the mat1 cassette mediate pausing of replication forks at the proximity of the imprinting site, and the results suggest that this pause dictates specific priming at the position of imprinting in a sequence-independent manner. Also, we identify a novel type of cis-acting spacer region important for the imprinting process that affects where subsequent primers are put down after the replication fork is released from the pause. Thus, our data suggest that the imprint is formed by ligation of a not-fullyprocessed Okazaki fragment to the subsequent fragment. The presented work addresses how differentiated sister chromatids are established during DNA replication through the involvement of replication barriers

Insight Into Myocardial Microstructure of Athletes and Hypertrophic Cardiomyopathy Patients Using Diffusion Tensor Imaging

Background Hypertrophic cardiomyopathy (HCM) remains the commonest cause of sudden cardiac death among young athletes. Differentiating between physiologically adaptive left ventricular (LV) hypertrophy observed in athletes' hearts and pathological HCM remains challenging. By quantifying the diffusion of water molecules, diffusion tensor imaging (DTI) MRI allows voxelwise characterization of myocardial microstructure. Purpose To explore microstructural differences between healthy volunteers, athletes, and HCM patients using DTI. Study Type Prospective cohort. Population Twenty healthy volunteers, 20 athletes, and 20 HCM patients. Field Strength/Sequence 3T/DTI spin echo. Assessment In‐house MatLab software was used to derive mean diffusivity (MD) and fractional anisotropy (FA) as markers of amplitude and anisotropy of the diffusion of water molecules, and secondary eigenvector angles (E2A)—reflecting the orientations of laminar sheetlets. Statistical Tests Independent samples t‐tests were used to detect statistical significance between any two cohorts. Analysis of variance was utilized for detecting the statistical difference between the three cohorts. Statistical tests were two‐tailed. A result was considered statistically significant at P ≤ 0.05. Results DTI markers were significantly different between HCM, athletes, and volunteers. HCM patients had significantly higher global MD and E2A, and significantly lower FA than athletes and volunteers. (MDHCM = 1.52 ± 0.06 × 10−3 mm2/s, MDAthletes = 1.49 ± 0.03 × 10−3 mm2/s, MDvolunteers = 1.47 ± 0.02 × 10−3 mm2/s, P < 0.05; E2AHCM = 58.8 ± 4°, E2Aathletes = 47 ± 5°, E2Avolunteers = 38.5 ± 7°, P < 0.05; FAHCM = 0.30 ± 0.02, FAAthletes = 0.35 ± 0.02, FAvolunteers = 0.36 ± 0.03, P < 0.05). HCM patients had significantly higher E2A in their thickest segments compared to the remote (E2Athickest = 66.8 ± 7, E2Aremote = 51.2 ± 9, P < 0.05). Data Conclusion DTI depicts an increase in amplitude and isotropy of diffusion in the myocardium of HCM compared to athletes and volunteers as reflected by increased MD and decreased FA values. While significantly higher E2A values in HCM and athletes reflect steeper configurations of the myocardial sheetlets than in volunteers, HCM patients demonstrated an eccentric rise in E2A in their thickest segments, while athletes demonstrated a concentric rise. Further studies are required to determine the diagnostic capabilities of DTI. Evidence Level 1 Technical Efficacy Stage

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell