DNA Replication Licensing Factors and Aneuploidy Are Linked to Tumor Cell Cycle State and Clinical Outcome in Penile Carcinoma

Kayes, Oliver; Loddo, Marco; Patel, Nimish; Patel, Parind; Minhas, Suks; Ambler, Gareth; Freeman, Alex; Wollenschlaeger, Alex; Ralph, David; Stoeber, Kai; Williams, Gareth

doi:10.1158/1078-0432.ccr-09-0882

Cited by 34 publications

(31 citation statements)

References 48 publications

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“…Moreover, Mcm2-7 expression levels are powerful prognostic indicators in diverse tumour types, including cancers of the lung, breast, kidney, bladder, prostate and ovary [71][72][73][74][75][76][77]. This finding is consistent with large-scale meta-analysis of cancer microarray data, which identified up-regulation of the MCM2-6 genes as a component of poor prognostic signatures [78].…”

Section: Dna Replication Licensing and Cancersupporting

confidence: 73%

The cell cycle and cancer

Williams

Stoeber

2011

The Journal of Pathology

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579

406

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Deregulation of the cell cycle underlies the aberrant cell proliferation that characterizes cancer and loss of cell cycle checkpoint control promotes genetic instability. During the past two decades, cancer genetics has shown that hyperactivating mutations in growth signalling networks, coupled to loss of function of tumour suppressor proteins, drives oncogenic proliferation. Gene expression profiling of these complex and redundant mitogenic pathways to identify prognostic and predictive signatures and their therapeutic targeting has, however, proved challenging. The cell cycle machinery, which acts as an integration point for information transduced through upstream signalling networks, represents an alternative target for diagnostic and therapeutic interventions. Analysis of the DNA replication initiation machinery and mitotic engine proteins in human tissues is now leading to the identification of novel biomarkers for cancer detection and prognostication, and is providing target validation for cell cycle-directed therapies.

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Section: Dna Replication Licensing and Cancersupporting

confidence: 73%

The cell cycle and cancer

Williams

Stoeber

2011

The Journal of Pathology

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579

406

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“…It has been suggested that Geminin might provide useful information about tumor proliferation activities that is equal or superior to that of MCM proteins or Ki-67. Moreover, there have been many studies demonstrating that immunohistochemical analysis with the combination of MCM proteins, Ki-67, and Geminin may be useful for predicting tumor proliferating activities or patient prognosis in various malignancies (5,11,14,15,17,37). These findings are consistent with the present study, in which tumors that are positive for all of MCM7, Ki-67, and Geminin possess high proliferation potential, resulting in a high ratio of poorly differentiated and locally invasive tumors in phenotype II.…”

Section: Discussionsupporting

confidence: 92%

“…The cell cycle biomarker proteins, MCM7, Ki-67, Geminin, Aurora A, and H3S10ph, provide information on their specific cell cycle phase distribution: MCM7 protein is expressed throughout the cell cycle (G1-S-G2-M phases) but is tightly downregulated during exit into the out-of-cycle quiescent phase (G0 phase), corresponding to a differentiated or senescent state (11). Ki-67 is expressed during all phases of the cell cycle except for G0, while Geminin is expressed during the S-G2-M phases but not in G0 and G1 phases (17).…”

Section: Resultsmentioning

confidence: 99%

“…After DNA replication is initiated during the cell cycle, Geminin inhibits re-uploading of the MCM proteins onto chromatin, thus preventing DNA re-replication in the same cell cycle (13). It has been confirmed that these proteins are useful biomakers that reflect the proliferative activity of the tumor cells and predict the survival of patients Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma : Prognostic implications TOMOHIRO HARUKI 1,2 , KOHEI SHOMORI 1 , TATSUSHI SHIOMI 1 , YUJI TANIGUCHI 2 , HIROSHIGE NAKAMURA 2 and HISAO ITO 1 1 with various types of cancer (5)(6)(7)(8)(9)(10)(11)(14)(15)(16)(17)(18). Aurora A, known as a member of the serine/threonine kinase family, controls a subset of critical mitotic events including centrosome maturation and separation, as well as chromosome orientation and segregation (19).…”

Section: Introductionmentioning

confidence: 99%

“…However, these have not actually contributed to improving the prognosis of patients with early-stage NSCLC. Although almost all of these previous studies described the prognostic significance of a single biomarker, recent investigations have suggested that prognostic prediction is more reliable when multiparameter analysis with several biomarkers is performed than with analysis with a single one (9)(10)(11).…”

Section: Introductionmentioning

confidence: 99%

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Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma: prognostic implications

et al. 2012

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Abstract. Cell cycle-related molecules play crucial roles in maintaining genomic stability, and can also serve as biomarkers of cell cycle phase distribution at the same time. In this study, we used multiparameter analysis of various biomarkers to investigate their utility for the evaluation of tumor proliferation activities and the prognosis of patients with small-size lung adenocarcinoma. We performed immunohistochemical analysis using five cell cycle-related biomarkers (MCM7, Ki-67, Geminin, Aurora A and H3S10ph) for 102 surgically resected small-size lung adenocarcinomas. We classified them into three phenotypes based on the dominant cell cycle phase distribution of the tumor cell population, and evaluated whether these phenotypes were associated with clinicopathological factors and survival. Phenotype I (MCM7-negative tumors; n=56) was correlated with high or moderate differentiation and reduced local invasiveness (pleural and lymphovascular invasion) compared with phenotype II (MCM7-, Ki-67-and Geminin-positive tumors; n=23) and phenotype III (MCM7-, Aurora A-and H3S10ph-positive tumors; n=17). Five-year survival rates of phenotypes I, II and III were 89.8, 55.4 and 38.6%, respectively, with a significant difference between them (P<0.01). Multivariate analysis revealed that phenotypes II and III were independent prognostic factors in the 79 patients with stage I lung adenocarcinoma. Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma provided novel insights into the cell cycle phase distribution of dynamic tumor cell populations in vivo; it may be possible to evaluate tumor proliferation activities and patient prognosis more precisely if this analytical procedure is used.

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An evaluation of penalised survival methods for developing prognostic models with rare events

Ambler

Seaman

Omar

2011

Statistics in Medicine

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Prognostic models for survival outcomes are often developed by fitting standard survival regression models, such as the Cox proportional hazards model, to representative datasets. However, these models can be unreliable if the datasets contain few events, which may be the case if either the disease or the event of interest is rare. Specific problems include predictions that are too extreme, and poor discrimination between low-risk and high-risk patients. The objective of this paper is to evaluate three existing penalised methods that have been proposed to improve predictive accuracy. In particular, ridge, lasso and the garotte, which use penalised maximum likelihood to shrink coefficient estimates and in some cases omit predictors entirely, are assessed using simulated data derived from two clinical datasets. The predictions obtained using these methods are compared with those from Cox models fitted using standard maximum likelihood. The simulation results suggest that Cox models fitted using maximum likelihood can perform poorly when there are few events, and that significant improvements are possible by taking a penalised modelling approach. The ridge method generally performed the best, although lasso is recommended if variable selection is required.

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DNA Replication Licensing Factors and Aneuploidy Are Linked to Tumor Cell Cycle State and Clinical Outcome in Penile Carcinoma

Cited by 34 publications

References 48 publications

The cell cycle and cancer

The cell cycle and cancer

Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma: prognostic implications

An evaluation of penalised survival methods for developing prognostic models with rare events

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