Identification and validation of a gene expression signature that predicts outcome in adult men with germ cell tumors

Decreased expression of p53 is associated with down expression of zyxin in breast cancer

Background and Aims

Breast cancer (BC) is considered one of the most common malignant tumors leading to death in women, and genetic factors have a crucial role in BC pathogenesis. Zyxin (ZYX) is one of these factors that may be important in p53 level and function. Thus, the present work aimed to investigate the ZYX gene and protein expression in tumor tissue and matched margin tissue and its correlation with the p53 expression.

Methods

In a present case-control study, 30 tumors and 30 matched margin tissues were obtained from Iran Tumor Bank/Tehran University of Medical Sciences. Real-time polymerase chain reaction and western blot analysis techniques were applied to evaluate the genes and protein expression, respectively.

Results

The data showed that expression of the ZYX gene in tumor tissues significantly decreased (p = 0.0274) compared to matched margin tissues. In contrast, the p53 gene expression in tumor tissues had no significant difference with matched margin tissues. Additionally, we observed that ZYX and p53 genes expression in tumor tissues of estrogen receptor-positive patients had significant elevation than estrogen receptor-negative patients (p < 0.001, p < 0.001, respectively). The data of the western blot analysis technique showed that protein expression of ZYX (p = 0.0024) and P53 protein (p = 0.0218) in tumor tissues was significantly reduced compared to matched margin tissues. Additionally, our analysis showed a direct and significant correlation between the expression of ZYX and p53 proteins (r = 0.7797, p = 0.0126) and expression of ZYX and p53 genes (r = 0.3079, p = 0.0187).

Conclusion

Based on our observation, ZYX might have a tumor suppressor role and is associated with p53.

Role of Cancer Side Population Stem Cells in Ovarian Cancer Angiogenesis

Ovarian cancer is one of the most common gynecologic malignancies. Recurrence and metastasis often occur after treatment, and it has the highest mortality rate of all gynecological tumors. Cancer stem cells (CSCs) are a small population of cells with the ability of self-renewal, multidirectional differentiation, and infinite proliferation. They have been shown to play an important role in tumor growth, metastasis, drug resistance, and angiogenesis. Ovarian cancer side population (SP) cells, a type of CSC, have been shown to play roles in tumor formation, colony formation, xenograft tumor formation, ascites formation, and tumor metastasis. The rapid progression of tumor angiogenesis is necessary for tumor growth; however, many of the mechanisms driving this process are unclear as is the contribution of CSCs. The aim of this review was to document the current state of knowledge of the molecular mechanism of ovarian cancer stem cells (OCSCs) in regulating tumor angiogenesis.

The role of zyxin in signal transduction and its relationship with diseases

This review highlighted the pivotal role of zyxin, an essential cell focal adhesions protein, in cellular biology and various diseases. Zyxin can orchestrate the restructuring and dynamic alterations of the cellular cytoskeleton, which is involved in cell proliferation, adhesion, motility, and gene transcription. Aberrant zyxin expression is closely correlated with tumor cell activity and cardiac function in both tumorigenesis and cardiovascular diseases. Moreover, in fibrotic and inflammatory conditions, zyxin can modulate cellular functions and inflammatory responses. Therefore, a comprehensive understanding of zyxin is crucial for deciphering signal transduction networks and disease pathogenesis. Investigating its role in diseases holds promise for novel avenues in early diagnosis and therapeutic strategies. Nevertheless, targeting zyxin as a therapeutic focal point presents challenges in terms of specificity, safety, drug delivery, and resistance. Nonetheless, in-depth studies on zyxin and the application of precision medicine could offer new possibilities for personalized treatment modalities.

Integrated genomic analysis reveals aberrations in WNT signaling in germ cell tumors of childhood and adolescence

Germ cell tumors (GCTs) are neoplasms of the testis, ovary and extragonadal sites that occur in infants, children, adolescents and adults. Post-pubertal (type II) malignant GCTs may present as seminoma, non-seminoma or mixed histologies. In contrast, pre-pubertal (type I) GCTs are limited to (benign) teratoma and (malignant) yolk sac tumor (YST). Epidemiologic and molecular data have shown that pre- and post-pubertal GCTs arise by distinct mechanisms. Dedicated studies of the genomic landscape of type I and II GCT in children and adolescents are lacking. Here we present an integrated genomic analysis of extracranial GCTs across the age spectrum from 0-24 years. Activation of the WNT pathway by somatic mutation, copy-number alteration, and differential promoter methylation is a prominent feature of GCTs in children, adolescents and young adults, and is associated with poor clinical outcomes. Significantly, we find that small molecule WNT inhibitors can suppress GCT cells both in vitro and in vivo. These results highlight the importance of WNT pathway signaling in GCTs across all ages and provide a foundation for future efforts to develop targeted therapies for these cancers.

Identification of Core Genes and Prognostic Models of Laryngeal Cancer by Autophagy Related Biomarkers

Background: The aims of our article were to identify the core genes of the autophagy-related genes (ARGs) which abnormally expressed in laryngeal cancer (LC) and constructed a risk prognostic models with these genes. Methods: In this study, we identified genes with abnormally expressed in LC, and they were mainly involved in some cancer-related gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes pathways (KEGG). Statistical analysis were conducted to identify the powerful independent prognostic factors associated with clinical factors and survival. Results: A total of 35 DEGs were identified in our research. The risk prediction model was constructed with three potential prognostic genes (VEGFA, SPNS1 and CCL2) of autophagy by lasso regression analysis that can successfully predict the prognosis in LC. We applied ROC curve to evaluate the effectiveness of the risk prognostic model, and found that AUC was 0.693 below the curve. Risk prediction model was only related to survival status (P < 0.01), and was not related to clinicopathological factors. Furthermore, the genes (VEGFA and CCL2) were considered as core genes not only because they were the highly connected genes but also they were the composed genes of risk prognostic model. Conclusions: Taken together, ARGs were considered as important roles in the progression of LC and the prognostic model can help to identification of new targets to guide the diagnosis and therapy.

A Series of Genes for Predicting Responses to Anti-Tumor Necrosis Factor α Therapy in Crohn's Disease

Background: Patients with Crohn's disease (CD) experience severely reduced quality of life, particularly those who do not respond to conventional therapies. Antitumor necrosis factor (TNF)α is commonly used as first-line therapy; however, many patients remain unresponsive to this treatment, and the identification of response predictors could facilitate the improvement of therapeutic strategies. Methods: We screened Gene Expression Omnibus (GEO) microarray cohorts with different anti-TNFα responses in patients with CD (discovery cohort) and explored the hub genes. The finding was confirmed in independent validation cohorts, and multiple algorithms and in vitro cellular models were performed to further validate the core predictor. Results: We screened four discovery datasets. Differentially expressed genes between anti-TNFα responders and nonresponders were confirmed in each cohort. Gene ontology enrichment revealed that innate immunity was involved in the anti-TNFα response in patients with CD. Prediction analysis of microarrays provided the minimum misclassification of genes, and the constructed network containing the hub genes supported the core status of TLR2. Furthermore, GSEA also supports TLR2 as the core predictor. The top hub genes were then validated in the validation cohort (GSE159034; p < 0.05). Furthermore, ROC analyses demonstrated the significant predictive value of TLR2 (AUC: 0.829), TREM1 (AUC: 0.844), and CXCR1 (AUC: 0.841). Moreover, TLR2 expression in monocytes affected the immune-epithelial inflammatory response and epithelial barrier during lipopolysaccharide-induced inflammation (p < 0.05). Conclusion: Bioinformatics and experimental research identified TLR2, TREM1, CXCR1, FPR1, and FPR2 as promising candidates for predicting the anti-TNFα response in patients with Crohn's disease and especially TLR2 as a core predictor.

Making External Validation Valid for Molecular Classifier Development

PURPOSE

Accurate assessment of a molecular classifier that guides patient care is of paramount importance in precision oncology. Recent years have seen an increasing use of external validation for such assessment. However, little is known about how it is affected by ubiquitous unwanted variations in test data because of disparate experimental handling and by the use of data normalization for alleviating such variations.

METHODS

In this paper, we studied these issues using two microarray data sets for the same set of tumor samples and additional data simulated by resampling under various levels of signal-to-noise ratio and different designs for array-to-sample allocation.

RESULTS

We showed that (1) unwanted variations can lead to biased classifier assessment and (2) data normalization mitigates the bias to varying extents depending on the specific method used. In particular, frozen normalization methods for test data outperform their conventional forms in terms of both reducing the bias in accuracy estimation and increasing robustness to handling effects. We make available our benchmarking tool as an R package on GitHub for performing such evaluation on additional methods for normalization and classification.

CONCLUSION

Our findings thus highlight the importance of proper test-data normalization for valid assessment by external validation and call for caution on the choice of normalization method for molecular classifier development.

Teratomatous Elements in Orchiectomy Specimens Are Associated with a Reduced Relapse-Free Survival in Metastasized Testicular Germ Cell Tumors

INTRODUCTION

The impact of teratomatous elements in orchiectomy specimens of metastasized testicular germ cell tumors (TGCT) regarding oncological outcome is still unclear.

METHODS

We performed a retrospective analysis including 146 patients with metastasized TGCT analysing patient characteristics.

RESULTS

Twenty-six (18%) of all patients showed teratomatous elements in the orchiectomy specimens. TGCT with teratomatous elements showed a significantly higher frequency of clinical-stage 2C-3 disease (73 vs. 49%, p = 0.031), visceral metastases (58 vs. 32%, p = 0.015), and poor prognosis (p = 0.011) than TGCT without teratomatous elements. Teratoma-containing TGCT revealed a significantly higher rate of post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND, 54 vs. 32%, p = 0.041), with teratomatous elements being more often present in the PC-RPLND specimens (43 vs. 11%, p = 0.020) than nonteratoma-containing primaries. In the Kaplan-Meier estimates, the presence of teratomatous elements in orchiectomy specimens was associated with a significantly reduced relapse-free survival (RFS) (p = 0.049) during a median follow-up of 36 months (10-115.5).

CONCLUSIONS

The presence of teratomatous elements in orchiectomy specimens is associated with an advanced tumor stage, worse treatment response as well as a reduced RFS in metastasized TGCT. Consequently, the presence of teratomatous elements might act as a reliable stratification tool for treatment decision in TGCT patients.

Primary intracranial pure endodermal sinus tumor: A retrospective series of 6 cases in a single center and a systematic review of overall survival

BACKGROUND

Primary intracranial pure endodermal sinus tumor (EST) is a rare malignant nongerminomatous germ cell tumor. There is still lack of knowledge about the treatment and prognosis.

METHODS

We studied 6 cases of primary intracranial pure EST patients in Beijing Tiantan Hospital from June 2009 to June 2015. A comprehensive literature search was performed on Pubmed's electronic database using the search terms "primary intracranial endodermal sinus tumor", "primary intracranial yolk sac tumor" and "malignant germ cell tumor". Survival rates based on age, gender, tumor location, treatment, resection degree and metastatis were collected and analyzed.

RESULTS

Total resection was achieved in three patients and subtotal resection was achieved in three patients. Blood AFP level continuously decreased after tumor removal. In our case series, the longest survival time was 99 months; this patient received surgery+adjuvant therapy. Fifty-two cases were eligible and met the inclusion criteria for the review analysis. The majority of the population were in the young child to adolescent age and there is a male predominance in this study. In the Kaplan-Meier survival analysis, age, gender, tumor location and metastasis did not affect patients' OS. Better OS was found in patients who had subtotal and gross total resection of the tumor. Patients who had surgery combined with adjuvant therapy showed better OS compared to those who just had surgery.

CONCLUSION

Total resection of the tumor is necessary and EST is sensitive to adjuvant therapy.

The pioneer and differentiation factor FOXA2 is a key driver of yolk-sac tumour formation and a new biomarker for paediatric and adult yolk-sac tumours

Yolk-sac tumours (YSTs), a germ cell tumour subtype, occur in newborns and infants as well as in young adults of age 14-44 years. In clinics, adult patients with YSTs face a poor prognosis, as these tumours are often therapy-resistant and count for many germ cell tumour related deaths. So far, the molecular and (epi)genetic mechanisms that control development of YST are far from being understood. We deciphered the molecular and (epi)genetic mechanisms regulating YST formation by meta-analysing high-throughput data of gene and microRNA expression, DNA methylation and mutational burden. We validated our findings by qRT-PCR and immunohistochemical analyses of paediatric and adult YSTs. On a molecular level, paediatric and adult YSTs were nearly indistinguishable, but were considerably different from embryonal carcinomas, the stem cell precursor of YSTs. We identified FOXA2 as a putative key driver of YST formation, subsequently inducing AFP, GPC3, APOA1/APOB, ALB and GATA3/4/6 expression. In YSTs, WNT-, BMP- and MAPK signalling-related genes were up-regulated, while pluripotency- and (primordial) germ cell-associated genes were down-regulated. Expression of FOXA2 and related key factors seems to be regulated by DNA methylation, histone methylation / acetylation and microRNAs. Additionally, our results highlight FOXA2 as a promising new biomarker for paediatric and adult YSTs.

Potential biomarkers and risk assessment models to enhance the tumor-node-metastasis (TNM) staging classification of urologic cancers

INTRODUCTION

The anatomic-based TNM classification is considered the benchmark in cancer staging and has been regularly updated since its inception. In the current era of precision medicine, the added intention for future TNM modifications is to heighten its impact in the more 'personalized' level of cancer care. In urologic cancers, this goal may be achieved by incorporating 'non-anatomic' factors into TNM, such as biomarkers (e.g. gene alterations, molecular subtypes, genomic classifiers) and risk assessment models (e.g. nomogram, look-up table), while maintaining the anatomic extent as the foundation of staging. These different prognosticators can be combined and integrated, may serve as substratifiers for T, N, or M categories, and perhaps, incorporated as elements in TNM stage groupings to enhance their prognostic capability in urologic cancers.

AREAS COVERED

This review highlights candidate biomarkers and risk assessment models that can be explored to potentially improve TNM prognostication of bladder, prostate, kidney, and testicular cancers.

EXPERT OPINION

Recent advances in molecular analysis have increased the understanding of the genomic, transcriptomic, and epigenetic features for biomarker use in prognostication of urologic cancers, which together with the available risk assessment models, may complement and overcome the limitations of the traditional TNM staging.

Development and Validation of a Gene Signature for Prediction of Relapse in Stage I Testicular Germ Cell Tumors

Background: Testicular germ cell tumors (TGCTs) are commonly diagnosed tumors in young men. However, a satisfactory approach to predict relapse of stage I TGCTs is still lacking. Therefore, this study aimed to develop a robust risk score model for stage I TGCTs. Method: RNA-sequence data of stage I TGCTs and normal testis samples were downloaded and analyzed to identify different expression genes. Gene-based prognostic model was constructed in The Cancer Genome Atlas (TCGA) using least absolute shrinkage and selection operator (LASSO) regression analysis and validated in GSE99420 dataset. Potential biological functions of the genes in prognostic model were determined via Gene Set Enrichment Analysis (GSEA) between high-risk and low-risk patients. Results: A total of 9,391 differentially expressed genes and 84 prognosis-related genes were identified. An eight-gene-based risk score model was constructed to divide patients into high or low risk of relapse. The low-risk patients had a significantly better relapse-free survival (RFS) than high-risk patients in both training and validation cohorts (HR = 0.129, 95% CI = 0.059-0.284, P < 0.001; HR = 0.277, 95% CI = 0.116-0.661, P = 0.004, respectively). The area under the receiver operating characteristic curve (AUC) values at 5 years was 0.805 and 0.724 in the training and validation cohorts, respectively. Functional enrichment analyses showed that DNA replication, ribosome, cell cycle, and TGF-beta signaling pathway may contribute to the relapse process. Conclusion: In summary, our analysis provided a novel eight-gene signature that could predict RFS in stage I TGCT patients.

GCNA Preserves Genome Integrity and Fertility Across Species

The propagation of species depends on the ability of germ cells to protect their genome from numerous exogenous and endogenous threats. While these cells employ ubiquitous repair pathways, specialized mechanisms that ensure high-fidelity replication, chromosome segregation, and repair of germ cell genomes remain incompletely understood. We identified Germ Cell Nuclear Acidic Peptidase (GCNA) as a conserved regulator of genome stability in flies, worms, zebrafish, and human germ cell tumors. GCNA contains an acidic intrinsically disordered region (IDR) and a protease-like SprT domain. In addition to chromosomal instability and replication stress, Gcna mutants accumulate DNA-protein crosslinks (DPCs). GCNA acts in parallel with the SprT domain protein Spartan. Structural analysis reveals that while the SprT domain is needed to limit DNA damage, the IDR imparts significant function. This work shows that GCNA protects germ cells from various sources of damage, providing insights into conserved mechanisms that promote genome integrity across generations.

AYA testis cancer: The unmet challenge

Testis cancer is considered a rare-incidence cancer but comprises the third most common cancer diagnosed within the adolescent and young adult (AYA) years (15-39 years). Most testis cancer patients can anticipate a survival outcome in excess of 95%. However, there are subgroups of AYA patients where outcomes are considerably worse, including younger adolescents, patients with certain histological subtypes, or from certain ethnic backgrounds. For those cured with chemotherapy, the toxicity of treatment and burden of late effects is significant. Newer germ cell tumor-specific biomarkers may identify patients who do not require further treatment interventions or may detect early recurrence, potentially reducing the burden of treatment required for cure. An international collaboration for this rare tumor is creating the forum for trial design, where these biomarker research questions are embedded. Going forward, AYA testis cancer patients could benefit from having a more personalized treatment plan, tailored to risk, that minimizes the overall burden of late effects.

L1TD1 - a prognostic marker for colon cancer

BACKGROUND

Prognostic markers specific to a particular cancer type can assist in the evaluation of survival probability of patients and help clinicians to assess the available treatment modalities.

METHODS

Gene expression data was analyzed from three independent colon cancer microarray gene expression data sets (N = 1052). Survival analysis was performed for the three data sets, stratified by the expression level of the LINE-1 type transposase domain containing 1 (L1TD1). Correlation analysis was performed to investigate the role of the interactome of L1TD1 in colon cancer patients.

RESULTS

We found L1TD1 as a novel positive prognostic marker for colon cancer. Increased expression of L1TD1 associated with longer disease-free survival in all the three data sets. Our results were in contrast to a previous study on medulloblastoma, where high expression of L1TD1 was linked with poor prognosis. Notably, in medulloblastoma L1TD1 was co-expressed with its interaction partners, whereas our analysis revealed lack of co-expression of L1TD1 with its interaction partners in colon cancer.

CONCLUSIONS

Our results identify increased expression of L1TD1 as a prognostic marker predicting longer disease-free survival in colon cancer patients.

Impact of Teratoma on the Cumulative Incidence of Disease-Related Death in Patients With Advanced Germ Cell Tumors

PURPOSE

In men with metastatic germ cell tumors (GCTs), risk-directed treatment is determined, in part, by a distinction between seminoma and nonseminomatous GCT (NSGCT). The importance of NSGCT cell type is uncertain. We evaluated the long-term impact of teratoma on survival in patients with NSGCT.

METHODS

Prechemotherapy, primary tumors from patients who received platinum-based chemotherapy were studied, and the histology was confirmed by a genitourinary pathologist. The cumulative incidence of disease-related death (CIDD) was the primary end point, and a competing-risk analysis was performed.

RESULTS

Tumors were available from 232 patients, including 193 with NSGCT. An element of teratoma was present in 82 NSGCT primary tumors (42%). With a median follow-up of 17 years (range, 0.3 to 35 years), 58 patients with NSGCT died, 47 as a result of GCT and 11 as a result of other causes. Most GCT deaths occurred within the first 5 years and were associated with pretreatment risk status (P < .001). Death as a result of other causes rose steadily after 15 years and was not associated with risk status (P = .66). A higher CIDD was observed in patients who had NSGCT with teratoma than those with NSGCT without teratoma and seminoma (5-year CIDD rate, 27.4%, 17.4%, and 10.3%, respectively; P = .03). A higher CIDD was observed in patients who had NSGCT with mature teratoma compared with those with either NSGCT with immature teratoma or NSGCT without teratoma (5-year CIDD rate, 38.1%, 19.9%, and 17.4%, respectively; P = .01).

CONCLUSION

The presence of teratoma, particularly mature teratoma, in an NSGCT primary tumor is associated with a higher CIDD, consistent with the hypothesis that differentiation is associated with adverse outcomes. Death as a result of non-GCT causes is not associated with risk status and must be separated from GCT death when evaluating long-term survival.

Identification of testicular cancer driver genes by a cross-species comparative oncology approach

BACKGROUND

Germ cell tumors arise in the testis, ovary, or extragonadal locations and have a wide range of histopathological and clinical presentations. The relative lack of animal models of germ cell tumors has impeded functional assessment of candidate driver genes. Previously, we described the development of testicular germ cell tumors in zebrafish carrying a mutation in bmpr1bb, a BMP family receptor, and demonstrated that human germ cell tumors have defects in BMP signaling.

OBJECTIVE

To further credential the zebrafish model for studies of human germ cell tumor, and to elucidate conserved genetic programs underlying the development of germ cell tumor.

MATERIALS AND METHODS

We used genetic techniques to ablate the germ cell lineage in developing fish and tested tumors for loss-of-heterozygosity of the wild-type allele of bmpr1bb. We performed comparative gene expression profiling of zebrafish and human germ cell tumors and carried out functional studies of selected genes.

RESULTS

Ablation of germ cells completely prevents testis tumor formation in the fish, definitively establishing the germ cell origin of the tumors. Germ cell tumors in bmpr1bb heterozygous mutants retain the wild-type allele, indicating haploinsufficiency of bmpr1bb as the mechanism of tumor formation. Comparison of RNA-Seq and microarray data from human and zebrafish germ cell tumors revealed a unique overlapping signature shared by the zebrafish tumors with human seminomas, yolk sac tumors, and embryonal carcinomas. The most highly conserved gene set in this cross-species analysis included potential driver genes such as JUP, which we show to be essential for germ cell tumor cell growth.

CONCLUSION

Our findings highlight the value of cross-species comparative oncology for the identification of candidate human cancer genes.

New insights into germ cell tumor genomics

BACKGROUND

Testicular germ cell tumors (GCTs) represent the most common malignancy in young men. While GCTs represent a model for curable solid tumors due to exquisite chemosensitivity, mortality for patients with GCT comprises the most life years lost for non-pediatric malignancies. Given limited options for patients with platinum-resistant disease, improved insight into GCT biology could identify novel therapeutic options for patients with platinum-resistant disease. Recent studies into molecular characteristics of both early stage and advanced germ cell tumors suggest a role for rationally targeted agents and potentially immunotherapy.

RECENT DEVELOPMENTS

Recent GWAS meta-analyses have uncovered additional susceptibility loci for GCT and provide further evidence that GCT risk is polygenic. Chromosome arm level amplifications and reciprocal loss of heterozygosity have been described as significantly enriched in GCT compared to other cancer types. Contemporary analyses confirm ubiquitous gain of isochromosome 12 and mutations in addition to previously described GCT-associated genes such as KIT and KRAS. Alterations within the TP53-MDM2 signal transduction pathway appear to be enriched among patients with platinum-resistant disease. Potentially actionable targets, including alterations in TP53-MDM2, Wnt/β-catenin, PI3K, and MAPK signaling, are present in significant proportions of patients with platinum-resistant disease and may be exploited as therapeutic options. Pre-clinical and early clinical data also suggest a potential role for immunotherapy among patients with GCTs.

CONCLUSION

Molecular characterization of GCT patients may provide biologic rationale for novel treatment options in patients with platinum-resistant disease.

Genitourinary Pathology Reporting Parameters Most Relevant to the Medical Oncologist

Pathologic variables play an important role in prognostication in urologic malignancies. Histologic subtype, histologic grade, and anatomic extent of disease (pathologic tumor and nodal staging) influence treatment decisions in both the adjuvant and metastatic settings. This article discusses treatment paradigms for the most common urologic malignancies, followed by the evidence base to support the relationship between pathologic assessment and decision making by the medical oncologist.

The role of zyxin in regulation of malignancies

Focal adhesions are highly dynamic multi-protein complexes found at the cell surface and effectively link the cell's internal cytoskeleton to a complex mixture of macromolecules known as the extracellular matrix and mediate transmission of signals from the extracellular matrix to the nucleus. Zyxin is one of the key focal adhesion proteins and is also found to shuttle in the nucleus. Although the mechanism of shuttling to the nucleus unclear, it moves out from the nucleus through a leucine-rich nuclear export signal sequence. It is known to contribute to fundamental cellular activities such as cell migration, adhesion and proliferation by interacting with a variety of cellular proteins. It is also linked with a number of cancers such as melanoma, hepatocellular carcinoma, oral squamous-cell carcinoma, Ewing sarcoma and prostate cancer. However, in many cases, the precise mechanisms by which the absence or presence of zyxin contributes to cancer progression or suppression is unknown. Thus, more work is required to gain insights into how zyxin modulates cellular functions in relationship to cancer. This review summarises the role of zyxin in cancer, with an emphasis on conflicting roles in prostate cancer.

Overexpression of TET dioxygenases in seminomas associates with low levels of DNA methylation and hydroxymethylation

Germ cell tumors and particularly seminomas reflect the epigenomic features of their parental primordial germ cells (PGCs), including genomic DNA hypomethylation and expression of pluripotent cell markers. Because the DNA hypomethylation might be a result of TET dioxygenase activity, we examined expression of TET1-3 enzymes and the level of their product, 5-hydroxymethylcytosine (5hmC), in a panel of histologically characterized seminomas and non-seminomatous germ cell tumors. Expression of TET dioxygenase mRNAs was quantified by real-time PCR. TET1 expression and the level of 5hmC were examined immunohistochemically. Quantitative assessment of 5-methylcytosine (5mC) and 5hmC levels was done by the liquid chromatography-mass spectroscopy technique. We found highly increased expression of TET1 dioxygenase in most seminomas and strong TET1 staining in seminoma cells. Isocitrate dehydrogenase 1 and 2 mutations were not detected, suggesting the enzymatic activity of TET1. The levels of 5mC and 5hmC in seminomas were found decreased in comparison to non-seminomatous germ cell tumors and healthy testicular tissue. We propose that TET1 expression should be studied as a potential marker of seminomas and mixed germ cell tumors and we suggest that elevated expression of TET dioxygenase enzymes is associated with the maintenance of low DNA methylation levels in seminomas. This "anti-methylator" phenotype of seminomas is in contrast to the CpG island methylator phenotype (CIMP) observed in a fraction of tumors of various types.

Testicular germ cell tumor genomics

PURPOSE OF REVIEW

Testicular germ cell tumors (TGCTs) are a model for curable cancer because of exquisite chemosensitivity and incorporation of multimodal therapy. Nevertheless, our ability to predict metastases in early-stage disease and responders to chemotherapy in advanced disease is limited. Treatment options for cisplatin-resistant disease are sparse. A further understanding of TGCT biology may allow for more precise patient counseling and identify novel therapies in patients with cisplatin-resistant disease.

RECENT FINDINGS

Adult TGCTs are characterized by frequent chromosomal anomalies and low rates of somatic mutations. Large-scale integrated molecular analysis of early-stage TGCT patients is actively underway. In addition to ubiquitous gain of isochromosome 12p, current molecular studies have confirmed mutations of previously described genes (i.e., KIT and KRAS) and described novel mutations. Analysis of cisplatin-resistant cases has identified high rates of alterations within the TP53-MDM2 axis and a high proportion of patients with potentially actionable targets, including TP53-MDM2, PI3 kinase, and MAPK signaling pathway alterations. The role of epigenetics in TGCT development and prognosis is also being further characterized.

SUMMARY

Further molecular characterization of TGCT may allow for avoidance of unnecessary treatment in patients with early-stage disease and also provide new treatment options in patients with cisplatin-resistant disease.

Mechanism and Role of SOX2 Repression in Seminoma: Relevance to Human Germline Specification

Human male germ cell tumors (GCTs) are derived from primordial germ cells (PGCs). The master pluripotency regulator and neuroectodermal lineage effector transcription factor SOX2 is repressed in PGCs and the seminoma (SEM) subset of GCTs. The mechanism of SOX2 repression and its significance to GC and GCT development currently are not understood. Here, we show that SOX2 repression in SEM-derived TCam-2 cells is mediated by the Polycomb repressive complex (PcG) and the repressive H3K27me3 chromatin mark that are enriched at its promoter. Furthermore, SOX2 repression in TCam-2 cells can be abrogated by recruitment of the constitutively expressed H3K27 demethylase UTX to the SOX2 promoter through retinoid signaling, leading to expression of neuronal and other lineage genes. SOX17 has been shown to initiate human PGC specification, with its target PRDM1 suppressing mesendodermal genes. Our results are consistent with a role for SOX2 repression in normal germline development by suppressing neuroectodermal genes.

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SOX2 is repressed in hPGC, germ cell neoplasia in situ, and seminoma

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SOX2 repression is mediated by PcG and H3K27me3 enrichment at its promoter

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Retinoid signaling recruits UTX to SOX2 promoter leading to reactivation of SOX2

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These studies shed light on the role of SOX2 in germline development

Paediatric extracranial germ-cell tumours

Management of paediatric extracranial germ-cell tumours carries a unique set of challenges. Germ-cell tumours are a heterogeneous group of neoplasms that present across a wide age range and vary in site, histology, and clinical behaviour. Patients with germ-cell tumours are managed by a diverse array of specialists. Thus, staging, risk stratification, and treatment approaches for germ-cell tumours have evolved disparately along several trajectories. Paediatric germ-cell tumours differ from the adolescent and adult disease in many ways, leading to complexities in applying age-appropriate, evidence-based care. Suboptimal outcomes remain for several groups of patients, including adolescents, and patients with extragonadal tumours, high tumour markers at diagnosis, or platinum-resistant disease. Survivors have significant long-term toxicities. The challenge moving forward will be to translate new insights from molecular studies and collaborative clinical data into improved patient outcomes. Future trials will be characterised by improved risk-stratification systems, biomarkers for response and toxic effects, rational reduction of therapy for low-risk patients and novel approaches for poor-risk patients, and improved international collaboration across paediatric and adult cooperative research groups.

Development and Validation of a Gene-Based Model for Outcome Prediction in Germ Cell Tumors Using a Combined Genomic and Expression Profiling Approach

Germ Cell Tumors (GCT) have a high cure rate, but we currently lack the ability to accurately identify the small subset of patients who will die from their disease. We used a combined genomic and expression profiling approach to identify genomic regions and underlying genes that are predictive of outcome in GCT patients. We performed array-based comparative genomic hybridization (CGH) on 53 non-seminomatous GCTs (NSGCTs) treated with cisplatin based chemotherapy and defined altered genomic regions using Circular Binary Segmentation. We identified 14 regions associated with two year disease-free survival (2yDFS) and 16 regions associated with five year disease-specific survival (5yDSS). From corresponding expression data, we identified 101 probe sets that showed significant changes in expression. We built several models based on these differentially expressed genes, then tested them in an independent validation set of 54 NSGCTs. These predictive models correctly classified outcome in 64–79.6% of patients in the validation set, depending on the endpoint utilized. Survival analysis demonstrated a significant separation of patients with good versus poor predicted outcome when using a combined gene set model. Multivariate analysis using clinical risk classification with the combined gene model indicated that they were independent prognostic markers. This novel set of predictive genes from altered genomic regions is almost entirely independent of our previously identified set of predictive genes for patients with NSGCTs. These genes may aid in the identification of the small subset of patients who are at high risk of poor outcome.

Pediatric and Adolescent Extracranial Germ Cell Tumors: The Road to Collaboration

During the past 35 years, survival rates for children with extracranial malignant germ cell tumors (GCTs) have increased significantly. Success has been achieved primarily through the application of platinum-based chemotherapy regimens; however, clinical challenges in GCTs remain. Excellent outcomes are not distributed uniformly across the heterogeneous distribution of age, histologic features, and primary tumor site. Despite good outcomes overall, the likelihood of a cure for certain sites and histologic conditions is less than 50%. In addition, there are considerable long-term treatment-related effects for survivors. Even modest cisplatin dosing can cause significant long-term morbidities. A particular challenge in designing new therapies for GCT is that a variety of specialists use different risk stratifications, staging systems, and treatment approaches for three distinct age groups (childhood, adolescence, and young adulthood). Traditionally, pediatric cancer patients younger than 15 years have been treated by pediatric oncologists in collaboration with their surgical specialty colleagues. Adolescents and young adults with GCTs often are treated by medical oncologists, urologists, or gynecologic oncologists. The therapeutic dilemma for all is how to best define disease risk so that therapy and toxicity can be appropriately reduced for some patients and intensified for others. Further clinical and biologic insights can only be achieved through collaborations that do not set limitations by age, sex, and primary tumor site. Therefore, international collaborations, spanning different cooperative groups and disciplines, have been developed to address these challenges.

Interrogation of a context-specific transcription factor network identifies novel regulators of pluripotency

The predominant view of pluripotency regulation proposes a stable ground state with coordinated expression of key transcription factors (TFs) that prohibit differentiation. Another perspective suggests a more complexly regulated state involving competition between multiple lineage-specifying TFs that define pluripotency. These contrasting views were developed from extensive analyses of TFs in pluripotent cells in vitro. An experimentally validated, genome-wide repertoire of the regulatory interactions that control pluripotency within the in vivo cellular contexts is yet to be developed. To address this limitation, we assembled a TF interactome of adult human male germ cell tumors (GCTs) using the Algorithm for the Accurate Reconstruction of Cellular Pathways (ARACNe) to analyze gene expression profiles of 141 tumors comprising pluripotent and differentiated subsets. The network (GCT(Net)) comprised 1,305 TFs, and its ingenuity pathway analysis identified pluripotency and embryonal development as the top functional pathways. We experimentally validated GCT(Net) by functional (silencing) and biochemical (ChIP-seq) analysis of the core pluripotency regulatory TFs POU5F1, NANOG, and SOX2 in relation to their targets predicted by ARACNe. To define the extent of the in vivo pluripotency network in this system, we ranked all TFs in the GCT(Net) according to sharing of ARACNe-predicted targets with those of POU5F1 and NANOG using an odds-ratio analysis method. To validate this network, we silenced the top 10 TFs in the network in H9 embryonic stem cells. Silencing of each led to downregulation of pluripotency and induction of lineage; 7 of the 10 TFs were identified as pluripotency regulators for the first time.

Germ cell tumors: looking to the future

Our knowledge about the management of men with germ cell tumors (GCTs) and its tumor biology continues to evolve. Vascular disease, metabolic syndrome, second malignant neoplasms, and hypogonadism occur after treatment for GCTs and the latency pattern resembles that seen in patients treated for Hodgkin lymphoma. Patients receiving treatment for GCTs should be informed not only of the near-term toxicity (experienced during or shortly after administration), but also the delayed and late effects of chemotherapy and the need for lifelong surveillance for all late outcomes, including late relapse. Recent data suggest that the treatment outcome of patients with intermediate-risk, poor-risk, and relapsed GCTs can be improved through multicenter trials that include the general oncology community. Finally, GCTs are a malignancy of primordial germ cells. Programmed differentiation is clinically evident in vivo and probably related to chemotherapy resistance. This biology has much clinical relevance, some of which is already in use.

Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker

The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc.) and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.

Biology of childhood germ cell tumours, focussing on the significance of microRNAs

Genomic and protein-coding transcriptomic data have suggested that germ cell tumours (GCTs) of childhood are biologically distinct from those of adulthood. Global messenger RNA profiles segregate malignant GCTs primarily by histology, but then also by age, with numerous transcripts showing age-related differential expression. Such differences are likely to account for the heterogeneous clinico-pathological behaviour of paediatric and adult malignant GCTs. In contrast, as global microRNA signatures of human tumours reflect their developmental lineage, we hypothesized that microRNA profiles would identify common biological abnormalities in all malignant GCTs owing to their presumed shared origin from primordial germ cells. MicroRNAs are short, non-protein-coding RNAs that regulate gene expression via translational repression and/or mRNA degradation. We showed that all malignant GCTs over-express the miR-371-373 and miR-302/367 clusters, regardless of patient age, histological subtype or anatomical tumour site. Furthermore, bioinformatic approaches and subsequent Gene Ontology analysis revealed that these two over-expressed microRNAs clusters co-ordinately down-regulated genes involved in biologically significant pathways in malignant GCTs. The translational potential of this finding has been demonstrated with the detection of elevated serum levels of miR-371-373 and miR-302/367 microRNAs at the time of malignant GCT diagnosis, with levels falling after treatment. The tumour-suppressor let-7 microRNA family has also been shown to be universally down-regulated in malignant GCTs, because of abundant expression of the regulatory gene LIN28. Low let-7 levels resulted in up-regulation of oncogenes including MYCN, AURKB and LIN28 itself, the latter through a direct feedback mechanism. Targeting LIN28, or restoring let-7 levels, both led to effective inhibition of this pathway. In summary, paediatric malignant GCTs show biological differences from their adult counterparts at a genomic and protein-coding transcriptome level, whereas they both display very similar microRNA expression profiles. These similarities and differences may be exploited for diagnostic and/or therapeutic purposes.

Increasing incidence of testicular cancer in the United States and Europe between 1992 and 2009

PURPOSE

Increasing in incidence, testicular cancer is the most commonly diagnosed cancer in young men in the USA and in Europe. We sought to determine contemporary trends in testicular cancer incidence in the USA and Europe.

METHODS

Testicular cancer incidence data covering the USA and Europe were extracted from the SEER-13 (SEER*Stat 8.0.1) and the EUREG databases, respectively. Trends were determined using JoinPoint 3.5.3.

RESULTS

Testicular germ cell tumor (TGCT) incidence among US males >15 years increased from 1992 (5.7/100,000) to 2009 (6.8/100,000) with a significant annual percentage change (APC: 1.1%, p < 0.001). Seminomas were 29% of all TGCTs in 15-26 year-olds, increasing to 78% in those 40+ years of age. TGCT rates were highest in White men (1992: 7.5/100,000; 2009: 8.6/100,000) followed by Hispanic men (1992: 4.0/100,000; 2009: 6.3/100,000) and lowest among Asian (1992: 2.0/100,000; 2009: 2.8/100,000) and Black men (1992: 0.7/100,000; 2009: 1.7/100,000). Significantly increasing incidence rates were observed in White men (APC: 1.2%, p < 0.001) and most prominently in Hispanic men, especially from 2002 to 2009 (APC: 5.6%, p < 0.01). Incidence of testicular cancer increased in 15 of 19 (79%) European countries analyzed (p < 0.05). Denmark (13.4/100,000 man-years), Switzerland (12.7/100,000 man-years), and Norway (12.7/100,000 man-years) exhibited the highest age-standardized rates, while Spain had the greatest APC (APC = 5.5, 95% CI 3.9-7.0%, p < 0.001).

CONCLUSIONS

Between 1992 and 2009, testicular cancer incidence in the USA and Europe continued to increase, most notably in US Hispanic, Northern European, Spanish, and younger and older populations.

Pharmacogenomic biomarkers for personalized medicine

Pharmacogenomics examines how the benefits and adverse effects of a drug vary among patients in a target population by analyzing genomic profiles of individual patients. Personalized medicine prescribes specific therapeutics that best suit an individual patient. Much current research focuses on developing genomic biomarkers to identify patients, to identify which patients would benefit from a treatment, have an adverse response, or no response at all, prior to treatment according to relevant differences in risk factors, disease types and/or responses to therapy. This review describes the use of the two personalized medicine biomarkers, prognostic and predictive, to classify patients into subgroups for treatment recommendation.

Unravelling mechanisms of cisplatin sensitivity and resistance in testicular cancer

Testicular cancer is the most frequent solid malignant tumour type in men 20-40 years of age. At the time of diagnosis up to 50% of the patients suffer from metastatic disease. In contrast to most other metastatic solid tumours, the majority of metastatic testicular cancer patients can be cured with highly effective cisplatin-based chemotherapy. This review aims to summarise the current knowledge on response to chemotherapy and the biological basis of cisplatin-induced apoptosis in testicular cancer. The frequent presence of wild-type TP53 and the low levels of p53 in complex with the p53 negative feed-back regulator MDM2 contribute to cisplatin sensitivity. Moreover, the high levels of the pluripotency regulator Oct4 and as a consequence of Oct4 expression high levels of miR-17/106b seed family and pro-apoptotic Noxa and the low levels of cytoplasmic p21 (WAF1/Cip1) appear to be causative for the exquisite sensitivity to cisplatin-based therapy of testicular cancer. However, resistance of testicular cancer to cisplatin-based therapy does occur and can be mediated through aberrant levels of the above mentioned key players. Drugs targeting these key players showed, at least pre-clinically, a sensitising effect to cisplatin treatment. Further clinical development of such treatment strategies will lead to new treatment options for platinum-resistant testicular cancers.

Computational purification of individual tumor gene expression profiles leads to significant improvements in prognostic prediction

Tumor heterogeneity is a limiting factor in cancer treatment and in the discovery of biomarkers to personalize it. We describe a computational purification tool, ISOpure, to directly address the effects of variable normal tissue contamination in clinical tumor specimens. ISOpure uses a set of tumor expression profiles and a panel of healthy tissue expression profiles to generate a purified cancer profile for each tumor sample and an estimate of the proportion of RNA originating from cancerous cells. Applying ISOpure before identifying gene signatures leads to significant improvements in the prediction of prognosis and other clinical variables in lung and prostate cancer.

Assessment of reproducibility of cancer survival risk predictions across medical centers

BACKGROUND

Two most important considerations in evaluation of survival prediction models are 1) predictability - ability to predict survival risks accurately and 2) reproducibility - ability to generalize to predict samples generated from different studies. We present approaches for assessment of reproducibility of survival risk score predictions across medical centers.

METHODS

Reproducibility was evaluated in terms of consistency and transferability. Consistency is the agreement of risk scores predicted between two centers. Transferability from one center to another center is the agreement of the risk scores of the second center predicted by each of the two centers. The transferability can be: 1) model transferability - whether a predictive model developed from one center can be applied to predict the samples generated from other centers and 2) signature transferability - whether signature markers of a predictive model developed from one center can be applied to predict the samples from other centers. We considered eight prediction models, including two clinical models, two gene expression models, and their combinations. Predictive performance of the eight models was evaluated by several common measures. Correlation coefficients between predicted risk scores of different centers were computed to assess reproducibility - consistency and transferability.

RESULTS

Two public datasets, the lung cancer data generated from four medical centers and colon cancer data generated from two medical centers, were analyzed. The risk score estimates for lung cancer patients predicted by three of four centers agree reasonably well. In general, a good prediction model showed better cross-center consistency and transferability. The risk scores for the colon cancer patients from one (Moffitt) medical center that were predicted by the clinical models developed from the another (Vanderbilt) medical center were shown to have excellent model transferability and signature transferability.

CONCLUSIONS

This study illustrates an analytical approach to assessing reproducibility of predictive models and signatures. Based on the analyses of the two cancer datasets, we conclude that the models with clinical variables appear to perform reasonable well with high degree of consistency and transferability. There should have more investigations on the reproducibility of prediction models including gene expression data across studies.

Network information improves cancer outcome prediction

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression.

Identification and validation of gene expression models that predict clinical outcome in patients with early-stage laryngeal cancer

BACKGROUND

Despite improvement in therapeutic techniques, patients with early-stage laryngeal cancer still recur after treatment. Gene expression prognostic models could suggest which of these patients would be more appropriate for testing adjuvant strategies.

MATERIALS AND METHODS

Expression profiling using whole-genome DASL arrays was carried out on 56 formalin-fixed paraffin-embedded tumor samples of patients with early-stage laryngeal cancer. We split the samples into a training and a validation set. Using the supervised principal components survival analysis in the first cohort, we identified gene expression profiles that predict the risk of recurrence. These profiles were then validated in an independent cohort.

RESULTS

Gene models comprising different number of genes identified a subgroup of patients who were at high risk of recurrence. Of these, the best prognostic model distinguished between a high- and a low-risk group (log-rank P<0.005). The prognostic value of this model was reproduced in the validation cohort (median disease-free survival: 38 versus 161 months, log-rank P=0.018), hazard ratio=5.19 (95% confidence interval 1.14-23.57, P<0.05).

CONCLUSIONS

We have identified gene expression prognostic models that can refine the estimation of a patient's risk of recurrence. These findings, if further validated, should aid in patient stratification for testing adjuvant treatment strategies.

Assessment of performance of survival prediction models for cancer prognosis

BACKGROUND

Cancer survival studies are commonly analyzed using survival-time prediction models for cancer prognosis. A number of different performance metrics are used to ascertain the concordance between the predicted risk score of each patient and the actual survival time, but these metrics can sometimes conflict. Alternatively, patients are sometimes divided into two classes according to a survival-time threshold, and binary classifiers are applied to predict each patient's class. Although this approach has several drawbacks, it does provide natural performance metrics such as positive and negative predictive values to enable unambiguous assessments.

METHODS

We compare the survival-time prediction and survival-time threshold approaches to analyzing cancer survival studies. We review and compare common performance metrics for the two approaches. We present new randomization tests and cross-validation methods to enable unambiguous statistical inferences for several performance metrics used with the survival-time prediction approach. We consider five survival prediction models consisting of one clinical model, two gene expression models, and two models from combinations of clinical and gene expression models.

RESULTS

A public breast cancer dataset was used to compare several performance metrics using five prediction models. 1) For some prediction models, the hazard ratio from fitting a Cox proportional hazards model was significant, but the two-group comparison was insignificant, and vice versa. 2) The randomization test and cross-validation were generally consistent with the p-values obtained from the standard performance metrics. 3) Binary classifiers highly depended on how the risk groups were defined; a slight change of the survival threshold for assignment of classes led to very different prediction results.

CONCLUSIONS

1) Different performance metrics for evaluation of a survival prediction model may give different conclusions in its discriminatory ability. 2) Evaluation using a high-risk versus low-risk group comparison depends on the selected risk-score threshold; a plot of p-values from all possible thresholds can show the sensitivity of the threshold selection. 3) A randomization test of the significance of Somers' rank correlation can be used for further evaluation of performance of a prediction model. 4) The cross-validated power of survival prediction models decreases as the training and test sets become less balanced.

Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

Why do some people with the same type of cancer die early and some live long? Apart from influences from the environment and personal lifestyle, we believe that differences in the individual tumor genome account for different survival times. Recently, powerful methods have become available to systematically read genomic information of patient samples. The major remaining challenge is how to spot, among the thousands of changes, those few that are relevant for tumor aggressiveness and thereby affecting patient survival. Here, we make use of the fact that genes and proteins in a cell never act alone, but form a network of interactions. Finding the relevant information in big networks of web documents and hyperlinks has been mastered by Google with their PageRank algorithm. Similar to PageRank, we have developed an algorithm that can identify genes that are better indicators for survival than genes found by traditional algorithms. Our method can aid the clinician in deciding if a patient should receive chemotherapy or not. Reliable prediction of survival and response to therapy based on molecular markers bears a great potential to improve and personalize patient therapies in the future.

Using gene expression information obtained by quantitative real-time PCR to evaluate Angus bulls divergently selected for feed efficiency

Residual feed intake (RFI) is a measure of feed efficiency in beef cattle. Young Angus bulls from lines of cattle divergently selected for RFI were used in a gene expression profiling study of the liver. Quantitative real-time PCR (qPCR) assay was used to quantify the differentially expressed genes and the information was used to examine the relationships between the genes and RFI and to classify the bulls into their respective RFI group. Gene expression of 21 genes in liver biopsies from 22 low RFI and 22 high RFI bulls were measured by qPCR. Gene expressions of 14 of the 21 genes were significantly correlated with RFI. The expression of the genes was used in a principal component analysis from which five components were extracted. The five principal components explained 70% of the variation in the dependency structure. The first component was highly correlated (correlation coefficient of 0.69) with RFI. The genes of the glutathione S-transferase Mu family (GSTM1, GSTM2, GSTM4), protocadherin 19 (PCDH19), ATP-binding cassette transporter C4 (ABCC4) and superoxide dismutase 3 (SOD3) are in the xenobiotic pathway and were the key factors in the first principal component. This highlights the important relationship between this pathway and variation in RFI. The second and third principal components were also correlated with RFI, with correlation coefficients of –0.28 and –0.20, respectively. Two of the four important genes of the second principal component work coordinately in the signalling pathways that inhibit the insulin-stimulated insulin receptor and regulate energy metabolism. This is consistent with the observation that a positive genetic correlation exists between RFI and fatness. The important genes in the third principal component are related to the extracellular matrix activity, with low RFI bulls showing high extracellular matrix activity.