Marital status and survival in pancreatic cancer patients: a SEER based analysis.

BACKGROUND: Recent findings suggest that marital status affects survival in patients with different types of cancer. However, its role in the survival of patients with pancreatic ductal adenocarcinoma is unknown. In this study, we investigated whether there was an association between marital status and overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC). METHODS: Adult patients diagnosed with PDAC between 1998 and 2003 with known marital statuses were identified from the Surveillance, Epidemiology, and End Results registry of the National Cancer Institute. OS for these patients was plotted using the Kaplan-Meier method. Comparative risks of mortality were evaluated by using univariate and multivariate-adjusted Cox regression models. RESULTS: Using Kaplan-Meier analysis, we found that the median overall survival of patients was 4 months and 3 months (p CONCLUSIONS: Marital status is an independent prognostic factor of both perioperative and long-term survival in patients with PDAC. This observation may suggest a suboptimally met psychosocial need among PDAC patients that is partially fulfilled by the support system provided by marriage

Associations between Statin/Omega3 Usage and MRI-Based Radiomics Signatures in Prostate Cancer

Prostate cancer is the most common noncutaneous cancer and the second leading cause of cancer deaths among American men. Statins and omega-3 are two medications recently found to correlate with prostate cancer risk and aggressiveness, but the observed associations are complex and controversial. We therefore explore the novel application of radiomics in studying statin and omega-3 usage in prostate cancer patients. On MRIs of 91 prostate cancer patients, two regions of interest (ROIs), the whole prostate and the peripheral region of the prostate, were manually segmented. From each ROI, 944 radiomic features were extracted after field bias correction and normalization. Heatmaps were generated to study the radiomic feature patterns against statin or omega-3 usage. Radiomics models were trained on selected features and evaluated with 500-round threefold cross-validation for each drug/ROI combination. On the 1500 validation datasets, the radiomics model achieved average AUCs of 0.70, 0.74, 0.78, and 0.72 for omega-3/prostate, omega- 3/peripheral, statin/prostate, and statin/peripheral, respectively. As the first study to analyze radiomics in relation to statin and omega-3 uses in prostate cancer patients, our study preliminarily established the existence of imaging-identifiable tissue-level changes in the prostate and illustrated the potential usefulness of radiomics for further exploring these medications’ effects and mechanisms in prostate cancer

Transcriptional Profiling of Peripheral Blood Mononuclear Cells in Pancreatic Cancer Patients Identifies Novel Genes with Potential Diagnostic Utility

Background: It is well known that many malignancies, including pancreatic cancer (PC), possess the ability to evade the immune system by indirectly downregulating the mononuclear cell machinery necessary to launch an effective immune response. This knowledge, in conjunction with the fact that the trancriptome of peripheral blood mononuclear cells has been shown to be altered in the context of many diseases, including renal cell carcinoma, lead us to study if any such alteration in gene expression exists in PC as it may have diagnostic utility. Methods and Findings: PBMC samples from 26 PC patients and 33 matched healthy controls were analyzed by whole genome cDNA microarray. Three hundred eighty-three genes were found to be significantly different between PC and healthy controls, with 65 having at least a 1.5 fold change in expression. Pathway analysis revealed that many of these genes fell into pathways responsible for hematopoietic differentiation, cytokine signaling, and natural killer (NK) cell and CD8+ T-cell cytotoxic response. Unsupervised hierarchical clustering analysis identified an eight-gene predictor set, consisting of SSBP2, Ube2b-rs1, CA5B, F5, TBC1D8, ANXA3, ARG1, and ADAMTS20, that could distinguish PC patients from healthy controls with an accuracy of 79% in a blinded subset of samples from treatment naïve patients, giving a sensitivity of 83% and a specificity of 75%. Conclusions: In summary, we report the first in-depth comparison of global gene expression profiles of PBMCs between PC patients and healthy controls. We have also identified a gene predictor set that can potentially be developed further for use in diagnostic algorithms in PC. Future directions of this research should include analysis of PBMC expression profiles in patients with chronic pancreatitis as well as increasing the number of early-stage patients to assess the utility of PBMCs in the early diagnosis of PC. © 2011 Baine et al

The Potential Use of Radiomics with Pre-Radiation Therapy MR Imaging in Predicting Risk of Pseudoprogression in Glioblastoma Patients

Glioblastoma (GBM) is the most common adult glioma. Differentiating post-treatment effects such as pseudoprogression from true progression is paramount for treatment. Radiomics has been shown to predict overall survival and MGMT (methylguanine-DNA methyltransferase) pro- moter status in those with GBM. A potential application of radiomics is predicting pseudoprogression on pre-radiotherapy (RT) scans for patients with GBM. A retrospective review was performed with radiomic data analyzed using pre-RT MRI scans. Pseudoprogression was defined as post-treatment findings on imaging that resolved with steroids or spontaneously on subsequent imaging. Of the 72 patients identified for the study, 35 were able to be assessed for pseudoprogression, and 8 (22.9%) had pseudoprogression. A total of 841 radiomic features were examined along with clinical features. Receiver operating characteristic (ROC) analyses were performed to determine the AUC (area under ROC curve) of models of clinical features, radiomic features, and combining clinical and radiomic features. Two radiomic features were identified to be the optimal model combination. The ROC analysis found that the predictive ability of this combination was higher than using clini- cal features alone (mean AUC: 0.82 vs. 0.62). Additionally, combining the radiomic features with clinical factors did not improve predictive ability. Our results indicate that radiomics is potentially capable of predicting future development of pseudoprogression in patients with GBM using pre- RT MRIs

Unbiased analysis of pancreatic cancer radiation resistance reveals cholesterol biosynthesis as a novel target for radiosensitisation.

BACKGROUND: Despite its promise as a highly useful therapy for pancreatic cancer (PC), the addition of external beam radiation therapy to PC treatment has shown varying success in clinical trials. Understanding PC radioresistance and discovery of methods to sensitise PC to radiation will increase patient survival and improve quality of life. In this study, we identified PC radioresistance-associated pathways using global, unbiased techniques. METHODS: Radioresistant cells were generated by sequential irradiation and recovery, and global genome cDNA microarray analysis was performed to identify differentially expressed genes in radiosensitive and radioresistant cells. Ingenuity pathway analysis was performed to discover cellular pathways and functions associated with differential radioresponse and identify potential small-molecule inhibitors for radiosensitisation. The expression of FDPS, one of the most differentially expressed genes, was determined in human PC tissues by IHC and the impact of its pharmacological inhibition with zoledronic acid (ZOL, Zometa) on radiosensitivity was determined by colony-forming assays. The radiosensitising effect of Zol in vivo was determined using allograft transplantation mouse model. RESULTS: Microarray analysis indicated that 11 genes (FDPS, ACAT2, AG2, CLDN7, DHCR7, ELFN2, FASN, SC4MOL, SIX6, SLC12A2, and SQLE) were consistently associated with radioresistance in the cell lines, a majority of which are involved in cholesterol biosynthesis. We demonstrated that knockdown of farnesyl diphosphate synthase (FDPS), a branchpoint enzyme of the cholesterol synthesis pathway, radiosensitised PC cells. FDPS was significantly overexpressed in human PC tumour tissues compared with healthy pancreas samples. Also, pharmacologic inhibition of FDPS by ZOL radiosensitised PC cell lines, with a radiation enhancement ratio between 1.26 and 1.5. Further, ZOL treatment resulted in radiosensitisation of PC tumours in an allograft mouse model. CONCLUSIONS: Unbiased pathway analysis of radioresistance allowed for the discovery of novel pathways associated with resistance to ionising radiation in PC. Specifically, our analysis indicates the importance of the cholesterol synthesis pathway in PC radioresistance. Further, a novel radiosensitiser, ZOL, showed promising results and warrants further study into the universality of these findings in PC, as well as the true potential of this drug as a clinical radiosensitiser

Mucin (Muc) expression during pancreatic cancer progression in spontaneous mouse model: potential implications for diagnosis and therapy.

BACKGROUND: Pancreatic cancer (PC) is a lethal malignancy primarily driven by activated Kras mutations and characterized by the deregulation of several genes including mucins. Previous studies on mucins have identified their significant role in both benign and malignant human diseases including PC progression and metastasis. However, the initiation of MUC expression during PC remains unknown because of lack of early stage tumor tissues from PC patients. METHODS: In the present study, we have evaluated stage specific expression patterns of mucins during mouse PC progression in (Kras(G12D);Pdx1-Cre (KC)) murine PC model from pancreatic intraepithelial neoplasia (PanIN) to pancreatic ductal adenocarcinoma (PDAC) by immunohistochemistry and quantitative real-time PCR. RESULTS: In agreement with previous studies on human PC, we observed a progressive increase in the expression of mucins particularly Muc1, Muc4 and Muc5AC in the pancreas of KC (as early as PanIN I) mice with advancement of PanIN lesions and PDAC both at mRNA and protein levels. Additionally, mucin expression correlated with the increased expression of inflammatory cytokines IFN-γ (p \u3c 0.0062), CXCL1 (p \u3c 0.00014) and CXCL2 (p \u3c 0.08) in the pancreas of KC mice, which are known to induce mucin expression. Further, we also observed progressive increase in inflammation in pancreas of KC mice from 10 to 50 weeks of age as indicated by the increase in the macrophage infiltration. Overall, this study corroborates with previous human studies that indicated the aberrant overexpression of MUC1, MUC4 and MUC5AC mucins during the progression of PC. CONCLUSIONS: Our study reinforces the potential utility of the KC murine model for determining the functional role of mucins in PC pathogenesis by crossing KC mice with corresponding mucin knockout mice and evaluating mucin based diagnostic and therapeutic approaches for lethal PC

Potentials of Plasma NGAL and MIC-1 as Biomarker(s) in the Diagnosis of Lethal Pancreatic Cancer

Pancreatic cancer (PC) is lethal malignancy with very high mortality rate. Absence of sensitive and specific marker(s) is one of the major factors for poor prognosis of PC patients. In pilot studies using small set of patients, secreted acute phase proteins neutrophil gelatinase associated lipocalin (NGAL) and TGF-β family member macrophage inhibitory cytokine-1 (MIC-1) are proposed as most potential biomarkers specifically elevated in the blood of PC patients. However, their performance as diagnostic markers for PC, particularly in pre-treatment patients, remains unknown. In order to evaluate the diagnostic efficacy of NGAL and MIC-1, their levels were measured in plasma samples from patients with pre-treatment PC patients (n = 91) and compared it with those in healthy control (HC) individuals (n = 24) and patients with chronic pancreatitis (CP, n = 23). The diagnostic performance of these two proteins was further compared with that of CA19-9, a tumor marker commonly used to follow PC progression. The levels of all three biomarkers were significantly higher in PC compared to HCs. The mean (± standard deviation, SD) plasma NGAL, CA19-9 and MIC-1 levels in PC patients was 111.1 ng/mL (2.2), 219.2 U/mL (7.8) and 4.5 ng/mL (4.1), respectively. In comparing resectable PC to healthy patients, all three biomarkers were found to have comparable sensitivities (between 64%-81%) but CA19-9 and NGAL had a higher specificity (92% and 88%, respectively). For distinguishing resectable PC from CP patients, CA19-9 and MIC-1 were most specific (74% and 78% respectively). CA19-9 at an optimal cut-off of 54.1 U/ml is highly specific in differentiating resectable (stage 1/2) pancreatic cancer patients from controls in comparison to its clinical cut-off (37.1 U/ml). Notably, the addition of MIC-1 to CA19-9 significantly improved the ability to distinguish resectable PC cases from CP (p = 0.029). Overall, MIC-1 in combination with CA19-9 improved the diagnostic accuracy of differentiating PC from CP and HCs