Literature DB >> 21678471

Multi-biomarker pattern for tumor identification and prognosis.

Sara Rodríguez-Enríquez1, Silvia Cecilia Pacheco-Velázquez, Juan Carlos Gallardo-Pérez, Alvaro Marín-Hernández, José Luis Aguilar-Ponce, Erika Ruiz-García, Luz María Ruizgodoy-Rivera, Abelardo Meneses-García, Rafael Moreno-Sánchez.   

Abstract

In last decades, the basic, clinical, and translational research efforts have been directed to the identification of standard biomarkers associated with the degree of malignancy. There is an increasingly public health concern for earlier detection of cancer development at stages in which successful treatments can be achieved. To meet this urgent clinical demand, early stage cancer biomarkers supported by reliable and robust experimental data that can be readily applicable in the clinical practice, are required. In the current standard protocols, when one or two of the canonical proliferating index biomarkers are analyzed, contradictory results are frequently reached leading to incorrect cancer diagnostic and unsuccessful therapies. Therefore, the identification of other cellular characteristics or signatures present in the tumor cells either alone or in combination with the well-established proliferation markers emerge as an alternative strategy in the improvement of cancer diagnosis and treatment. Because it is well known that several pathways and processes are altered in tumor cells, the concept of "single marker" in cancer results incorrect. Therefore, this review aims to analyze and discuss the proposal that the molecular profile of different genes or proteins in different altered tumor pathways must be established to provide a better global clinical pattern for cancer detection and prognosis.
Copyright © 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21678471     DOI: 10.1002/jcb.23224

Source DB:  PubMed          Journal:  J Cell Biochem        ISSN: 0730-2312            Impact factor:   4.429


  15 in total

Review 1.  Primary and metastatic peritoneal surface malignancies.

Authors:  Delia Cortés-Guiral; Martin Hübner; Mohammad Alyami; Aditi Bhatt; Wim Ceelen; Olivier Glehen; Florian Lordick; Robert Ramsay; Olivia Sgarbura; Kurt Van Der Speeten; Kiran K Turaga; Manish Chand
Journal:  Nat Rev Dis Primers       Date:  2021-12-16       Impact factor: 52.329

2.  Construction of a New Tumor Immunity-Related Signature to Assess and Classify the Prognostic Risk of Colorectal Cancer.

Authors:  Xiaocheng Wu; Tianxing Yang; Liping Qian; Desheng Zhang; Hui Yang
Journal:  Int J Gen Med       Date:  2021-10-12

3.  Increased expression of NuSAP in recurrent prostate cancer is mediated by E2F1.

Authors:  Z G Gulzar; J K McKenney; J D Brooks
Journal:  Oncogene       Date:  2012-02-20       Impact factor: 9.867

4.  Serum protein profiles as potential biomarkers for infectious disease status in pigs.

Authors:  Miriam G J Koene; Han A Mulder; Norbert Stockhofe-Zurwieden; Leo Kruijt; Mari A Smits
Journal:  BMC Vet Res       Date:  2012-03-22       Impact factor: 2.741

5.  Diagnostic and prognostic value of CEA, CA19-9, AFP and CA125 for early gastric cancer.

Authors:  Fan Feng; Yangzi Tian; Guanghui Xu; Zhen Liu; Shushang Liu; Gaozan Zheng; Man Guo; Xiao Lian; Daiming Fan; Hongwei Zhang
Journal:  BMC Cancer       Date:  2017-11-09       Impact factor: 4.430

6.  Isotopic graphene-isolated-Au-nanocrystals with cellular Raman-silent signals for cancer cell pattern recognition.

Authors:  Yuxiu Zou; Siqi Huang; Yixin Liao; Xupeng Zhu; Yiqin Chen; Long Chen; Fang Liu; Xiaoxiao Hu; Haijun Tu; Liang Zhang; Zhangkun Liu; Zhuo Chen; Weihong Tan
Journal:  Chem Sci       Date:  2018-02-12       Impact factor: 9.825

7.  A novel prognostic signature of immune-related genes for patients with colorectal cancer.

Authors:  Jun Wang; Shaojun Yu; Guofeng Chen; Muxing Kang; Xiaoli Jin; Yi Huang; Lele Lin; Dan Wu; Lie Wang; Jian Chen
Journal:  J Cell Mol Med       Date:  2020-06-21       Impact factor: 5.310

8.  Characterization of high- and low-risk hepatocellular adenomas by magnetic resonance imaging in an animal model of glycogen storage disease type 1A.

Authors:  Roberta Resaz; Francesca Rosa; Federica Grillo; Luca Basso; Daniela Segalerba; Andrea Puglisi; Maria Carla Bosco; Luca Mastracci; Carlo E Neumaier; Luigi Varesio; Alessandra Eva
Journal:  Dis Model Mech       Date:  2019-04-05       Impact factor: 5.758

9.  Prediction and diagnosis of renal cell carcinoma using nuclear magnetic resonance-based serum metabolomics and self-organizing maps.

Authors:  Hong Zheng; Jiansong Ji; Liangcai Zhao; Minjiang Chen; An Shi; Linlin Pan; Yiran Huang; Huajie Zhang; Baijun Dong; Hongchang Gao
Journal:  Oncotarget       Date:  2016-09-13

Review 10.  Application of cancer-associated glycoforms and glycan-binding probes to an in vitro diagnostic multivariate index assay for precise diagnoses of cancer.

Authors:  Jeong Gu Kang; Jeong-Heon Ko; Yong-Sam Kim
Journal:  Proteomics       Date:  2016-05-11       Impact factor: 3.984

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