Prognostic Influence of Pre-Operative C-Reactive Protein in Node-Negative Breast Cancer Patients

The importance of inflammation is increasingly noticed in cancer. The aim of this study was to analyze the prognostic influence of pre-operative serum C-reactive protein (CRP) in a cohort of 148 lymph node-negative breast cancer patients. The prognostic significance of CRP level for disease-free survival (DFS), metastasis-free survival (MFS) and overall survival (OS) was evaluated using univariate and multivariate Cox regression, also including information on age at diagnosis, tumor size, tumor grade, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) status, proliferation index (Ki67) and molecular subtype, as well as an assessment of the presence of necrosis and inflammation in the tumor tissue. Univariate analysis showed that CRP, as a continuous variable, was significantly associated with DFS (P = 0.002, hazard ratio [HR]  = 1.04, 95% confidence interval [CI]  = 1.02–1.07) and OS (P = 0.036, HR  = 1.03, 95% CI  = 1.00–1.06), whereas a trend was observed for MFS (P = 0.111). In the multivariate analysis, CRP retained its significance for DFS (P = 0.033, HR  = 1.01, 95% CI  = 1.00–1.07) as well as OS (P = 0.023, HR  = 1.03, 95% CI  = 1.00–1.06), independent of established prognostic factors. Furthermore, large-scale gene expression analysis by Affymetrix HG-U133A arrays was performed for 72 (48.6%) patients. The correlations between serum CRP and gene expression levels in the corresponding carcinoma of the breast were assessed using Spearman''s rank correlation, controlled for false-discovery rate. No significant correlation was observed between CRP level and gene expression indicative of an ongoing local inflammatory process. In summary, pre-operatively elevated CRP levels at the time of diagnosis were associated with shorter DFS and OS independent of established prognostic factors in node-negative breast cancer, supporting a possible link between inflammation and prognosis in breast cancer.     

The Proneural Molecular Signature Is Enriched in Oligodendrogliomas and Predicts Improved Survival among Diffuse Gliomas

The Cancer Genome Atlas Project (TCGA) has produced an extensive collection of ‘-omic’ data on glioblastoma (GBM), resulting in several key insights on expression signatures. Despite the richness of TCGA GBM data, the absence of lower grade gliomas in this data set prevents analysis genes related to progression and the uncovering of predictive signatures. A complementary dataset exists in the form of the NCI Repository for Molecular Brain Neoplasia Data (Rembrandt), which contains molecular and clinical data for diffuse gliomas across the full spectrum of histologic class and grade. Here we present an investigation of the significance of the TCGA consortium''s expression classification when applied to Rembrandt gliomas. We demonstrate that the proneural signature predicts improved clinical outcome among 176 Rembrandt gliomas that includes all histologies and grades, including GBMs (log rank test p = 1.16e-6), but also among 75 grade II and grade III samples (p = 2.65e-4). This gene expression signature was enriched in tumors with oligodendroglioma histology and also predicted improved survival in this tumor type (n = 43, p = 1.25e-4). Thus, expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for lower grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy. Integrated DNA and RNA analysis of low-grade and high-grade proneural gliomas identified increased expression and gene amplification of several genes including GLIS3, TGFB2, TNC, AURKA, and VEGFA in proneural GBMs, with corresponding loss of DLL3 and HEY2. Pathway analysis highlights the importance of the Notch and Hedgehog pathways in the proneural subtype. This demonstrates that the expression signatures identified in the TCGA analysis of GBMs also have intrinsic prognostic value for low-grade oligodendrogliomas, and likely represent important differences in tumor biology with implications for treatment and therapy.     

Patient-Specific Metrics of Invasiveness Reveal Significant Prognostic Benefit of Resection in a Predictable Subset of Gliomas

Object

Malignant gliomas are incurable, primary brain neoplasms noted for their potential to extensively invade brain parenchyma. Current methods of clinical imaging do not elucidate the full extent of brain invasion, making it difficult to predict which, if any, patients are likely to benefit from gross total resection. Our goal was to apply a mathematical modeling approach to estimate the overall tumor invasiveness on a patient-by-patient basis and determine whether gross total resection would improve survival in patients with relatively less invasive gliomas.

Methods

In 243 patients presenting with contrast-enhancing gliomas, estimates of the relative invasiveness of each patient''s tumor, in terms of the ratio of net proliferation rate of the glioma cells to their net dispersal rate, were derived by applying a patient-specific mathematical model to routine pretreatment MR imaging. The effect of varying degrees of extent of resection on overall survival was assessed for cohorts of patients grouped by tumor invasiveness.

Results

We demonstrate that patients with more diffuse tumors showed no survival benefit (P = 0.532) from gross total resection over subtotal/biopsy, while those with nodular (less diffuse) tumors showed a significant benefit (P = 0.00142) with a striking median survival benefit of over eight months compared to sub-totally resected tumors in the same cohort (an 80% improvement in survival time for GTR only seen for nodular tumors).

Conclusions

These results suggest that our patient-specific, model-based estimates of tumor invasiveness have clinical utility in surgical decision making. Quantification of relative invasiveness assessed from routinely obtained pre-operative imaging provides a practical predictor of the benefit of gross total resection.     

A Comprehensive Comparative Analysis of the Histomorphological Features of ALK-Rearranged Lung Adenocarcinoma Based on Driver Oncogene Mutations: Frequent Expression of Epithelial-Mesenchymal Transition Markers than Other Genotype

Molecular classification of lung cancer correlates well with histomorphological features. However, specific histomorphological features that differentiate anaplastic lymphoma kinase (ALK)-rearranged tumors from ALK-negative tumors have not been fully evaluated. Eighty ALK-rearranged and 213 ALK-negative (91 epidermal growth factor receptor-mutated; 29 K-ras-mutated; 93 triple-negative) resected lung adenocarcinomas were analyzed for several histomorphological parameters and histological subtype. ALK-rearranged tumors were associated with younger age at presentation, frequent nodal metastasis, and higher stage of disease at diagnosis. ALK-rearranged tumors were more likely to show a solid predominant pattern than ALK-negative tumors (43.8%; 35/80; p<0.001). Unlike ALK-negative tumors, a lepidic predominant pattern was not observed in ALK-rearranged tumors (p<0.001). In multivariate analysis, the most significant morphological features that distinguished ALK-rearranged tumors from ALK-negative tumors were cribriform formation (odds ratio [OR], 3.253; p = 0.028), presence of mucin-containing cells (OR, 4.899; p = 0.008), close relationship to adjacent bronchioles (OR, 5.361; p = 0.001), presence of psammoma bodies (OR, 4.026; p = 0.002), and a solid predominant pattern (OR, 13.685; p = 0.023). ALK-rearranged tumors exhibited invasive histomorphological features, aggressive behavior and frequent expression of epithelial-mesenchymal transition markers (loss of E-cadherin and expression of vimentin) compared with other genotype (p = 0.015). Spatial proximity between bronchus and ALK-rearranged tumors and frequent solid histologic subtype with p63 expression may cause diagnostic difficulties to differentiate squamous cell carcinoma in the small biopsy, whereas p40 was rarely expressed in ALK-rearranged adenocarcinoma. Knowledge of these features may improve the diagnostic accuracy and lead to a better understanding of the characteristic behavior of ALK-rearranged tumors.     

Determination of Angptl4 mRNA as a Diagnostic Marker of Primary and Metastatic Clear Cell Renal-Cell Carcinoma

Background

We have previously shown that angiopoietin-like 4 (angptl4) mRNA, a hypoxia-inducible gene, is highly expressed in clear cell renal-cell carcinoma (ccRCC), the most common subtype of RCC for which no specific marker is available. We here investigated whether angptl4 mRNA 1) could be a useful diagnostic and/or prognostic marker of ccRCC in a large and comprehensive retrospective series, 2) induction is dependent on the VHL status of tumors.

Methodology/Principal Findings

Using in situ hybridization, we report that angptl4 mRNA is expressed in 100% of both sporadic (n = 102) and inherited (n = 6) primary ccRCCs, without any statistical association with nuclear grade (p = 0.39), tumor size (p = 0.09), stage grouping (p = 0.17), progression-free survival (p = 0.94), and overall survival (p = 0.80). Angptl4 mRNA was also expressed in 26 (87%) of 30 secondary ccRCCs but neither in any other secondary RCCs (n = 7). In contrast, angptl4 mRNA was neither expressed in 94% non-ccRCC renal tumors (papillary RCCs (n = 46), chromophobe RCCs (n = 28), and oncocytomas (n = 9)), nor in non-renal clear cell carcinomas (n = 39). Angptl4 expression was also examined in tumors associated (n = 23) or not associated (n = 66) with VHL disease. 40 (98%) hemangioblastomas expressed angptl4 whereas all pheochromocytomas (n = 23) and pancreatic tumors (n = 25) were angptl4-negative, whatever their VHL status.

Conclusions/Significance

Angptl4 mRNA expression was highly associated with ccRCC (p = 1.5 10⁻⁴⁹, Chi square test) allowing to define its expression as a diagnosis marker for primary ccRCC. Moreover, angptl4 mRNA allows to discriminate the renal origin of metastases of clear-cell carcinomas arising from various organs. Finally, inactivation of VHL gene is neither necessary nor sufficient for angptl4 mRNA induction.     

Prion Protein Is Decreased in Alzheimer's Brain and Inversely Correlates with BACE1 Activity,Amyloid-β Levels and Braak Stage

The cellular prion protein (PrP^C) has been implicated in the development of Alzheimer''s disease (AD). PrP^C decreases amyloid-β (Aβ) production, which is involved in AD pathogenesis, by inhibiting β-secretase (BACE1) activity. Contactin 5 (CNTN5) has also been implicated in the development of AD by a genome-wide association study. Here we measured PrP^C and CNTN5 in frontal cortex samples from 24 sporadic AD and 24 age-matched control brains and correlated the expression of these proteins with markers of AD. PrP^C was decreased in sporadic AD compared to controls (by 49%, p = 0.014) but there was no difference in CNTN5 between sporadic AD and controls (p = 0.217). PrP^C significantly inversely correlated with BACE1 activity (r_s = −0.358, p = 0.006), Aβ load (r_s = −0.456, p = 0.001), soluble Aβ (r_s = −0.283, p = 0.026) and insoluble Aβ (r_s = −0.353, p = 0.007) and PrP^C also significantly inversely correlated with the stage of disease, as indicated by Braak tangle stage (r_s = −0.377, p = 0.007). CNTN5 did not correlate with Aβ load (r_s = 0.040, p = 0.393), soluble Aβ (r_s = 0.113, p = 0.223) or insoluble Aβ (r_s = 0.169, p = 0.125). PrP^C was also measured in frontal cortex samples from 9 Down''s syndrome (DS) and 8 age-matched control brains. In contrast to sporadic AD, there was no difference in PrP^C in the DS brains compared to controls (p = 0.625). These data are consistent with a role for PrP^C in regulating Aβ production and indicate that brain PrP^C level may be important in influencing the onset and progression of sporadic AD.     

Increased microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas

Glioblastoma (GBM) is a highly malignant brain tumor with a dismal prognosis. Gene expression profiling of GBM has revealed clinically relevant tumor subtypes, and this provides exciting opportunities to better understand disease pathogenesis. Results from an increasing number of studies demonstrate a role for the immune response in cancer progression, yet it is unclear how the immune response differs across tumor subtypes and how it affects outcome. Utilizing gene expression data from The Cancer Genome Atlas Project and the Gene Expression Omnibus database, we demonstrate an enrichment of immune response-related gene expression in the mesenchymal subtype of adult GBM (n = 173) and pediatric high-grade gliomas (n = 53). In an independent cohort of pediatric astrocytomas (n = 24) from UCSF, we stratified tumors into subtypes and confirmed these findings. Using novel immune cell-specific gene signatures we demonstrate selective enrichment of microglia/macrophage-related genes in adult and pediatric GBM tumors of the mesenchymal subtype. Furthermore, immunostaining of adult GBM tumors showed significantly higher cell numbers of microglia/macrophages in mesenchymal versus non-mesenchymal tumors (p = 0.04). Interestingly, adult GBM tumors with the shortest survival had significant enrichment of microglia/macrophage-related genes but this was not true for pediatric GBMs. Consistent with an association with poor outcome, immune response-related genes were highly represented in an adult poor prognosis gene signature, with the expression of genes related to macrophage recruitment and activation being most strongly associated with survival (p<0.05) using CoxBoost multivariate modeling. Using a microglia/macrophage high gene signature derived from quantification of tumor-infiltrating cells in adult GBM, we identified enrichment of genes characteristic of CD4 T cells, granulocytes, and microglia/macrophages (n = 573). These studies support a role for the immune response, particularly the microglia/macrophage response, in the biology of an important subset of GBM. Identification of this subset may be important for future therapeutic stratification.     

Yin Yang Gene Expression Ratio Signature for Lung Cancer Prognosis

Many studies have established gene expression-based prognostic signatures for lung cancer. All of these signatures were built from training data sets by learning the correlation of gene expression with the patients'' survival time. They require all new sample data to be normalized to the training data, ultimately resulting in common problems of low reproducibility and impracticality. To overcome these problems, we propose a new signature model which does not involve data training. We hypothesize that the imbalance of two opposing effects in lung cancer cells, represented by Yin and Yang genes, determines a patient’s prognosis. We selected the Yin and Yang genes by comparing expression data from normal lung and lung cancer tissue samples using both unsupervised clustering and pathways analyses. We calculated the Yin and Yang gene expression mean ratio (YMR) as patient risk scores. Thirty-one Yin and thirty-two Yang genes were identified and selected for the signature development. In normal lung tissues, the YMR is less than 1.0; in lung cancer cases, the YMR is greater than 1.0. The YMR was tested for lung cancer prognosis prediction in four independent data sets and it significantly stratified patients into high- and low-risk survival groups (p = 0.02, HR = 2.72; p = 0.01, HR = 2.70; p = 0.007, HR = 2.73; p = 0.005, HR = 2.63). It also showed prediction of the chemotherapy outcomes for stage II & III. In multivariate analysis, the YMR risk factor was more successful at predicting clinical outcomes than other commonly used clinical factors, with the exception of tumor stage. The YMR can be measured in an individual patient in the clinic independent of gene expression platform. This study provided a novel insight into the biology of lung cancer and shed light on the clinical applicability.     

Is Genetic Background Important in Lung Cancer Survival?

Background

In lung cancer, a patient''s survival is poor with a wide variation in survival within the stage of disease. The aim of this study was to investigate the familial concordance in lung cancer survival by means of analyses of pairs with different degrees of familial relationships.

Methods

Our population-based Swedish family database included three million families and over 58 100 lung cancer patients. We modelled the proband (parent, sibling, spouse) survival utilizing a multivariate proportional hazard (Cox) model adjusting for possible confounders of survival. Subsequently, the survival in proband''s relative (child, sibling, spouse) was analysed with a Cox model.

Findings

By use of Cox modelling with 5 years follow-up, we noted a decreased hazard ratio for death in children with good parental survival (Hazard Ratio [HR] = 0.71, 95% CI = 0.51 to 0.99), compared to those with poor parental survival. Also for siblings, a very strong protective effect was seen (HR = 0.14, 95% CI = 0.030 to 0.65). Finally, in spouses no correlation in survival was found.

Interpretation

Our findings suggest that genetic factors are important in lung cancer survival. In a clinical setting, information on prognosis in a relative may be vital in foreseeing the survival in an individual newly diagnosed with lung cancer. Future molecular studies enhancing the understanding of the underlying mechanisms and pathways are needed.     

Loss of Somatostatin Receptor Subtype 2 in Prostate Cancer Is Linked to an Aggressive Cancer Phenotype,High Tumor Cell Proliferation and Predicts Early Metastatic and Biochemical Relapse

Somatostatin receptor subtype 2 (SSTR2) is the most frequently expressed SSTR subtype in normal human tissues. SSTR2 expression is differentially regulated in various tumor types and therapeutic somatostatin analogs binding to SSTR2 are in clinical use. In prostate cancers highly contradictory results in terms of SSTR2 expression and its consequences have been published over the past years. The aim of this study was to clarify prevalence and clinical significance of SSTR2 expression in prostate cancer. Therefore, quantitative immunohistochemistry (IHC) using a tissue microarray containing samples from 3,261 prostate cancer patients with extensive clinical and molecular cancer characteristics and oncological follow-up data was performed. IHC data was compared to publicly available Gene Expression Omnibus datasets of human prostate cancer gene expression arrays. While membranous SSTR2 staining was always seen in normal prostate epithelium, SSTR2 staining was absent in more than half (56.1%) of 2,195 interpretable prostate cancer samples. About 13% of all analyzed prostate cancers showed moderate to strong cytoplasmic and membranous SSTR2 staining. Staining intensities were inversely correlated with high Gleason grade, advanced pT category, high tumor cell proliferation (p<0.0001 each), high pre-operative PSA levels, (p = 0.0011) and positive surgical margins (p = 0.006). In silico analysis confirmed lower SSTR2 gene expression in prostate cancers vs. normal adjacent tissue (p = 0.0424), prostate cancer metastases vs. primary cancers (p = 0.0011) and recurrent vs. non-recurrent prostate cancers (p = 0.0438). PSA-free survival gradually declined with SSTR2 staining intensity (p<0.0001). SSTR2-negative cancers were more likely to develop metastases over time (p<0.05). In conclusion, most prostate cancers are indeed SSTR2-negative and loss of SSTR2 strongly predicts an unfavorable tumor phenotype and poor prognosis. Therefore, SSTR2 expression seems an important factor in the pathogenesis of prostate cancer and re-introduction of the receptor in SSTR2-negative prostate cancers may feature a promising target for novel gene therapy approaches.     

The Personalized Advantage Index: Translating Research on Prediction into Individualized Treatment Recommendations. A Demonstration

Background

Advances in personalized medicine require the identification of variables that predict differential response to treatments as well as the development and refinement of methods to transform predictive information into actionable recommendations.

Objective

To illustrate and test a new method for integrating predictive information to aid in treatment selection, using data from a randomized treatment comparison.

Method

Data from a trial of antidepressant medications (N = 104) versus cognitive behavioral therapy (N = 50) for Major Depressive Disorder were used to produce predictions of post-treatment scores on the Hamilton Rating Scale for Depression (HRSD) in each of the two treatments for each of the 154 patients. The patient''s own data were not used in the models that yielded these predictions. Five pre-randomization variables that predicted differential response (marital status, employment status, life events, comorbid personality disorder, and prior medication trials) were included in regression models, permitting the calculation of each patient''s Personalized Advantage Index (PAI), in HRSD units.

Results

For 60% of the sample a clinically meaningful advantage (PAI≥3) was predicted for one of the treatments, relative to the other. When these patients were divided into those randomly assigned to their “Optimal” treatment versus those assigned to their “Non-optimal” treatment, outcomes in the former group were superior (d = 0.58, 95% CI .17—1.01).

Conclusions

This approach to treatment selection, implemented in the context of two equally effective treatments, yielded effects that, if obtained prospectively, would rival those routinely observed in comparisons of active versus control treatments.     

A Fourteen Gene GBM Prognostic Signature Identifies Association of Immune Response Pathway and Mesenchymal Subtype with High Risk Group

Background

Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature.

Methods

Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort.

Results

A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2^.507; B = 0^.919; p<0^.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0^.001) and TCGA cohort (p = 0^.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group.

Conclusion

We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.     

Genetic Characterizations of Giardia duodenalis in Sheep and Goats in Heilongjiang Province,China and Possibility of Zoonotic Transmission

Background

Giardia duodenalis is a widespread intestinal protozoan of both humans and mammals. To date, few epidemiological studies have assessed the potential and importance of zoonotic transmission; and the human giardiasis burden attributable to G. duodenalis of animal origin is unclear. No information about occurrence and genotyping data of sheep and goat giardiasis is available in China. The aim of the present study was to determine prevalence and distribution of G. duodenalis in sheep and goats in Heilongjiang Province, China, and to characterize G. duodenalis isolates and assess the possibility of zoonotic transmission.

Methodology/Principal Findings

A total of 678 fecal specimens were collected from sheep and goats on six farms ranging in age from one month to four years in Heilongjiang Province, China. The average prevalence of G. duodenalis infection was 5.0% (34/678) by microscopy after Lugol''s iodine staining, with 5.6% (30/539) for the sheep versus 2.9% (4/139) for the goats. Molecular analysis was conducted on 34 G. duodenalis isolates based on the triosephosphate isomerase (tpi) gene. 29 tpi gene sequences were successfully obtained and identified as assemblages A (n = 4), B (n = 2) and E (n = 23). High heterogeneity was observed within assemblage E at the tpi locus, with five novel subtypes found out of seven subtypes. Two subtypes of assemblage A were detected, including subtype AI (n = 3) and a novel subtype (designated as subtype AIV) (n = 1). Two assemblage B isolates were identical to each other in the tpi gene sequences.

Conclusions/Significance

This is the first report of G. duodenalis infections in sheep and goats in China. The present data revealed the unique endemicity on prevalence, distribution and genetic characterization of G. duodenalis in sheep and goats in Heilongjiang Province. The findings of assemblages A and B in sheep and goats implied the potential of zoonotic transmission.     

Impact of Gene Dosage on Gene Expression,Biological Processes and Survival in Cervical Cancer: A Genome-Wide Follow-Up Study

We investigated the role of tumor copy number (CN)–altered genome (CN-AG) in the carcinogenesis of cervical cancer (CC), especially its effect on gene expression, biological processes, and patient survival. Fifty-nine human papillomavirus 16 (HPV16)-positive CCs were investigated with microarrays–31 for mapping CN-AG and 55 for global gene expression, with 27 CCs in common. Five-year survival was investigated in 55 patients. Deletions and amplifications >2.5 Mb were defined as CN alterations. The %CN-AG varied from 0 to 32.2% (mean = 8.1±8.9). Tumors were classified as low (mean = 0.5±0.6, n = 11), medium (mean = 5.4±2.4, n = 10), or high (mean = 19.2±6.6, n = 10) CN. The highest %CN-AG was found in 3q, which contributed an average of 55% of all CN alterations. Genome-wide, only 5.3% of CN-altered genes were deregulated directly by gene dosage. In contrast, the rate in fully duplicated 3q was twice as high. Amplification of 3q explained 23.2% of deregulated genes in whole tumors (r² = 0.232, p = 0.006; analysis of variance), including genes located in 3q and other chromosomes. A total of 862 genes were deregulated exclusively in high-CN tumors, but only 22.9% were CN altered. This suggests that the remaining genes are not deregulated directly by gene dosage, but by mechanisms induced in trans by CN-altered genes. Anaphase-promoting complex/cyclosome (APC/C)-dependent proteasome proteolysis, glycolysis, and apoptosis were upregulated, whereas cell adhesion and angiogenesis were downregulated exclusively in high-CN tumors. The high %CN-AG and upregulated gene expression profile of APC/C-dependent proteasome proteolysis were associated with poor patient survival (p<0.05, log-rank test). Along with glycolysis, they were linearly associated with FIGO stage (r>0.38, p<0.01, Spearman test). Therefore, inhibition of APC/C-dependent proteasome proteolysis and glycolysis could be useful for CC treatment. However, whether they are indispensable for tumor growth remains to be demonstrated.