A Tri-Marker Proliferation Index Predicts Biochemical Recurrence after Surgery for Prostate Cancer

Prostate cancer exhibits tremendous variability in clinical behavior, ranging from indolent to lethal disease. Better prognostic markers are needed to stratify patients for appropriately aggressive therapy. By expression profiling, we can identify a proliferation signature variably expressed in prostate cancers. Here, we asked whether one or more tissue biomarkers might capture that information, and provide prognostic utility. We assayed three proliferation signature genes: MKI67 (Ki-67; also a classic proliferation biomarker), TOP2A (DNA topoisomerase II, alpha), and E2F1 (E2F transcription factor 1). Immunohistochemical staining was evaluable on 139 radical prostatectomy cases (in tissue microarray format), with a median clinical follow-up of eight years. Each of the three proliferation markers was by itself prognostic. Notably, combining the three markers together as a “proliferation index” (0 or 1, vs. 2 or 3 positive markers) provided superior prognostic performance (hazard ratio = 2.6 (95% CI: 1.4–4.9); P = 0.001). In a multivariate analysis that included preoperative serum prostate specific antigen (PSA) levels, Gleason grade and pathologic tumor stage, the composite proliferation index remained a significant predictor (P = 0.005). Analysis of receiver-operating characteristic (ROC) curves confirmed the improved prognostication afforded by incorporating the proliferation index (compared to the clinicopathologic data alone). Our findings highlight the potential value of a multi-gene signature-based diagnostic, and define a tri-marker proliferation index with possible utility for improved prognostication and treatment stratification in prostate cancer

Computational prediction and experimental validation associating FABP-1 and pancreatic adenocarcinoma with diabetes

<p/> <p>Background</p> <p>Pancreatic cancer, composed principally of pancreatic adenocarcinoma (PaC), is the fourth leading cause of cancer death in the United States. PaC-associated diabetes may be a marker of early disease. We sought to identify molecules associated with PaC and PaC with diabetes (PaC-DM) using a novel translational bioinformatics approach. We identified fatty acid binding protein-1 (FABP-1) as one of several candidates. The primary aim of this pilot study was to experimentally validate the predicted association between FABP-1 with PaC and PaC with diabetes.</p> <p>Methods</p> <p>We searched public microarray measurements for genes that were specifically highly expressed in PaC. We then filtered for proteins with known involvement in diabetes. Validation of FABP-1 was performed via antibody immunohistochemistry on formalin-fixed paraffin embedded pancreatic tissue microarrays (FFPE TMA). FFPE TMA were constructed using148 cores of pancreatic tissue from 134 patients collected between 1995 and 2002 from patients who underwent pancreatic surgery. Primary analysis was performed on 21 normal and 60 pancreatic adenocarcinoma samples, stratified for diabetes. Clinical data on samples was obtained via retrospective chart review. Serial sections were cut per standard protocol. Antibody staining was graded by an experienced pathologist on a scale of 0-3. Bivariate and multivariate analyses were conducted to assess FABP-1 staining and clinical characteristics.</p> <p>Results</p> <p>Normal samples were significantly more likely to come from younger patients. PaC samples were significantly more likely to stain for FABP-1, when FABP-1 staining was considered a binary variable. Compared to normals, there was significantly increased staining in diabetic PaC samples (p = 0.004) and there was a trend towards increased staining in the non-diabetic PaC group (p = 0.07). In logistic regression modeling, FABP-1 staining was significantly associated with diagnosis of PaC (OR 8.6 95% CI 1.1-68, p = 0.04), though age was a confounder.</p> <p>Conclusions</p> <p>Compared to normal controls, there was a significant positive association between FABP-1 staining and PaC on FFPE-TMA, strengthened by the presence of diabetes. Further studies with closely phenotyped patient samples are required to understand the true relationship between FABP-1, PaC and PaC-associated diabetes. A translational bioinformatics approach has potential to identify novel disease associations and potential biomarkers in gastroenterology.</p

SMURF1 Amplification Promotes Invasiveness in Pancreatic Cancer

Pancreatic cancer is a deadly disease, and new therapeutic targets are urgently needed. We previously identified DNA amplification at 7q21-q22 in pancreatic cancer cell lines. Now, by high-resolution genomic profiling of human pancreatic cancer cell lines and human tumors (engrafted in immunodeficient mice to enrich the cancer epithelial fraction), we define a 325 Kb minimal amplicon spanning SMURF1, an E3 ubiquitin ligase and known negative regulator of transforming growth factor β (TGFβ) growth inhibitory signaling. SMURF1 amplification was confirmed in primary human pancreatic cancers by fluorescence in situ hybridization (FISH), where 4 of 95 cases (4.2%) exhibited amplification. By RNA interference (RNAi), knockdown of SMURF1 in a human pancreatic cancer line with focal amplification (AsPC-1) did not alter cell growth, but led to reduced cell invasion and anchorage-independent growth. Interestingly, this effect was not mediated through altered TGFβ signaling, assayed by transcriptional reporter. Finally, overexpression of SMURF1 (but not a catalytic mutant) led to loss of contact inhibition in NIH-3T3 mouse embryo fibroblast cells. Together, these findings identify SMURF1 as an amplified oncogene driving multiple tumorigenic phenotypes in pancreatic cancer, and provide a new druggable target for molecularly directed therapy

Genomic Profiling Identifies GATA6 as a Candidate Oncogene Amplified in Pancreatobiliary Cancer

Pancreatobiliary cancers have among the highest mortality rates of any cancer type. Discovering the full spectrum of molecular genetic alterations may suggest new avenues for therapy. To catalogue genomic alterations, we carried out array-based genomic profiling of 31 exocrine pancreatic cancers and 6 distal bile duct cancers, expanded as xenografts to enrich the tumor cell fraction. We identified numerous focal DNA amplifications and deletions, including in 19% of pancreatobiliary cases gain at cytoband 18q11.2, a locus uncommonly amplified in other tumor types. The smallest shared amplification at 18q11.2 included GATA6, a transcriptional regulator previously linked to normal pancreas development. When amplified, GATA6 was overexpressed at both the mRNA and protein levels, and strong immunostaining was observed in 25 of 54 (46%) primary pancreatic cancers compared to 0 of 33 normal pancreas specimens surveyed. GATA6 expression in xenografts was associated with specific microarray gene-expression patterns, enriched for GATA binding sites and mitochondrial oxidative phosphorylation activity. siRNA mediated knockdown of GATA6 in pancreatic cancer cell lines with amplification led to reduced cell proliferation, cell cycle progression, and colony formation. Our findings indicate that GATA6 amplification and overexpression contribute to the oncogenic phenotypes of pancreatic cancer cells, and identify GATA6 as a candidate lineage-specific oncogene in pancreatobiliary cancer, with implications for novel treatment strategies

Detection of long non-coding RNA in archival tissue: correlation with polycomb protein expression in primary and metastatic breast carcinoma.

A major function of long non-coding RNAs (lncRNAs) is regulating gene expression through changes in chromatin state. Experimental evidence suggests that in cancer, they can influence Polycomb Repressive Complexes (PRC) to retarget to an occupancy pattern resembling that of the embryonic state. We have previously demonstrated that the expression level of lncRNA in the HOX locus, including HOTAIR, is a predictor of breast cancer metastasis. In this current project, RNA in situ hybridization of probes to three different lncRNAs (HOTAIR, ncHoxA1, and ncHoxD4), as well a immunohistochemical staining of EZH2, is undertaken in formalin-fixed paraffin-embedded breast cancer tissues in a high throughput tissue microarray format to correlate expression with clinicopathologic features. Though overall EZH2 and HOTAIR expression levels were highly correlated, the subset of cases with strong HOTAIR expression correlated with ER and PR positivity, while the subset of cases with strong EZH2 expression correlated with an increased proliferation rate, ER and PR negativity, HER2 underexpression, and triple negativity. Co-expression of HOTAIR and EZH2 trended with a worse outcome. In matched primary and metastatic cancers, both HOTAIR and EZH2 had increased expression in the metastatic carcinomas. This is the first study to show that RNA in situ hybridization of formalin fixed paraffin-embedded clinical material can be used to measure levels of long non-coding RNAs. This approach offers a method to make observations on lncRNAs that may influence the cancer epigenome in a tissue-based technique

Assessment of diagnostic accuracy of biomarkers to assess lung consolidation in calves with induced bacterial pneumonia using receiver operating characteristic curves

Abstract Bovine respiratory disease (BRD) is the most economically significant disease for cattle producers in the U.S. Cattle with advanced lung lesions at harvest have reduced average daily gain, yield grades, and carcass quality outcomes. The identification of biomarkers and clinical signs that accurately predict lung lesions could benefit livestock producers in determining a BRD prognosis. Receiver operating characteristic (ROC) curves are graphical plots that illustrate the diagnostic ability of a biomarker or clinical sign. Previously we used the area under the ROC curve (AUC) to identify cortisol, hair cortisol, and infrared thermography imaging as having acceptable (AUC &amp;gt; 0.7) diagnostic accuracy for detecting pain in cattle. Herein, we used ROC curves to assess the sensitivity and specificity of biomarkers and clinical signs associated with lung lesions after experimentally induced BRD. We hypothesized pain biomarkers and clinical signs assessed at specific time points after induction of BRD could be used to predict lung consolidation at necropsy. Lung consolidation of &amp;gt; 10% was retrospectively assigned at necropsy as a true positive indicator of BRD. Calves with a score of &amp;lt; 10% were considered negative for BRD. The biomarkers and clinical signs analyzed were serum cortisol; infrared thermography (IRT); mechanical nociceptive threshold (MNT); substance P; kinematic gait analysis; a visual analog scale (VAS); clinical illness score (CIS); computerized lung score (CLS); average activity levels; prostaglandin E2 metabolite (PGEM); serum amyloid A; and rectal temperature. A total of 5,122 biomarkers and clinical signs were collected from 26 calves, of which 18 were inoculated with M. haemolytica. All statistics were performed using JMP Pro 14.0. Results comparing calves with significant lung lesions to those without yielded the best diagnostic accuracy (AUC &amp;gt; 0.75) for right front stride length at 0 h; gait velocity at 32 h; VAS, CIS, average activity and rumination levels, step count, and rectal temperature, all at 48 h; PGEM at 72 h; gait distance at 120 h; cortisol at 168 h; and IRT, right front force and serum amyloid A, all at 192 h. These results show ROC analysis can be a useful indicator of the predictive value of pain biomarkers and clinical signs in cattle with induced bacterial pneumonia. AUC values for VAS score, average activity levels, step count, and rectal temperature seemed to yield good diagnostic accuracy (AUC &amp;gt; 0.75) at multiple time points, while MNT values, substance P concentrations, and CLS did not (all AUC values &amp;lt; 0.75).</jats:p

Summary of lncRNA and EZH2 associations with clinicopathologic data.

<p>NS = not significant.</p><p>− = negative.</p><p>+ = weak positive.</p><p>++ = strong positive.</p