Literature DB >> 19895223

GUCY2C reverse transcriptase PCR to stage pN0 colorectal cancer patients.

Alex Mejia1, Stephanie Schulz, Terry Hyslop, David S Weinberg, Scott A Waldman.   

Abstract

The most important prognostic marker of survival and predictive marker of response to adjuvant chemotherapy in colon cancer patients is tumor cells in regional lymph nodes. Despite their importance, standard techniques to assess nodal metastases remain imperfect, as approximately 30% of patients with histology-negative lymph nodes (pN0) die of recurrent disease, reflecting occult metastases that escape detection. These observations highlight the clinical need for novel, accurate approaches to detect occult lymph node metastases in patients with colon cancer. GUCY2C is a biomarker whose expression normally is restricted to intestinal cells, but is near universally overexpressed by colorectal cancer cells. Recently, a prospective, multicenter, blinded clinical trial demonstrated for the first time that the prognostic utility of GUCY2C quantitative reverse transcriptase (qRT)-PCR to detect occult lymph node metastases in pN0 colorectal cancer patients. Molecular staging revealed that approximately 13% of pN0 patients were free of tumor cells, while approximately 87% had GUCY2C results that suggested occult metastases. The presence of occult lymph node metastases was the strongest independent predictor of time to recurrence and disease-free survival. These observations establish the utility of molecular detection of occult lymph node metastases for estimating prognostic risk in pN0 colorectal cancer patients. Advancing this molecular diagnostic into staging paradigms in clinical laboratories will require validation in independent patient populations, definition of the relationship between the quantity of occult tumor metastases and risk, and determination of the utility of GUCY2C qRT-PCR to identify pN0 patients who might benefit from adjuvant chemotherapy.

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Year:  2009        PMID: 19895223      PMCID: PMC2810399          DOI: 10.1586/erm.09.67

Source DB:  PubMed          Journal:  Expert Rev Mol Diagn        ISSN: 1473-7159            Impact factor:   5.225


  97 in total

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  8 in total

1.  Molecular staging estimates occult tumor burden in colorectal cancer.

Authors:  Alex Mejia; Stephanie Schulz; Terry Hyslop; David S Weinberg; Scott A Waldman
Journal:  Adv Clin Chem       Date:  2010       Impact factor: 5.394

Review 2.  Molecular staging individualizing cancer management.

Authors:  Alex Mejia; Stephanie Schulz; Terry Hyslop; David S Weinberg; Scott A Waldman
Journal:  J Surg Oncol       Date:  2012-04-01       Impact factor: 3.454

Review 3.  GUCY2C molecular staging personalizes colorectal cancer patient management.

Authors:  Jian P Gong; Stephanie Schulz; Terry Hyslop; Scott A Waldman
Journal:  Biomark Med       Date:  2012-06       Impact factor: 2.851

4.  Current status of gene expression profiling to assist decision making in stage II colon cancer.

Authors:  Cheng E Chee; Neal J Meropol
Journal:  Oncologist       Date:  2014-05-28

5.  GUCY2C as a biomarker to target precision therapies for patients with colorectal cancer.

Authors:  Amanda N Lisby; John C Flickinger; Babar Bashir; Megan Weindorfer; Sanjna Shelukar; Madison Crutcher; Adam E Snook; Scott A Waldman
Journal:  Expert Rev Precis Med Drug Dev       Date:  2021-02-02

Review 6.  Bacterial heat-stable enterotoxins: translation of pathogenic peptides into novel targeted diagnostics and therapeutics.

Authors:  Jieru E Lin; Michael Valentino; Glen Marszalowicz; Michael S Magee; Peng Li; Adam E Snook; Brian A Stoecker; Chang Chang; Scott A Waldman
Journal:  Toxins (Basel)       Date:  2010-08-05       Impact factor: 4.546

Review 7.  Guanylyl cyclase 2C (GUCY2C) in gastrointestinal cancers: recent innovations and therapeutic potential.

Authors:  Ariana A Entezari; Adam E Snook; Scott A Waldman
Journal:  Expert Opin Ther Targets       Date:  2021-06-15       Impact factor: 6.797

8.  Induction of olfaction and cancer-related genes in mice fed a high-fat diet as assessed through the mode-of-action by network identification analysis.

Authors:  Youngshim Choi; Cheol-Goo Hur; Taesun Park
Journal:  PLoS One       Date:  2013-03-26       Impact factor: 3.240

  8 in total

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