Genomic Classifier ColoPrint Predicts Recurrence in Stage II Colorectal Cancer Patients More Accurately Than Clinical Factors

Kopetz, Scott; Tabernero, Josep; Rosenberg, Robert D.; Jiang, Zhi Qin; Moreno, Vı́ctor; Bachleitner‐Hofmann, Thomas; Lanza, Giovanni; Stork‐Sloots, Lisette; Maru, Dipen M.; Simón, Iris; Capellà, Gabriel; Salazar, Ramón

doi:10.1634/theoncologist.2014-0325

Cited by 118 publications

(96 citation statements)

References 29 publications

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“…In our study, many of the conventional features appear to have little prognostic impact within the T3, pMMR population. This is consistent with the finding from a recent study in 416 patients comparing the ColoPrint signature and the National Comprehensive Cancer Network (NCCN) clinical risk factors, where additional clinical features in the NCCN guidelines did not correlate with outcome in the T3, pMMR subgroup (HR 1.01, P = 0.9) (48). It is notable that GIV and LVI status were the only two significant predictors of recurrence in our study.…”

Section: Discussionsupporting

confidence: 91%

Girdin (GIV) Expression as a Prognostic Marker of Recurrence in Mismatch Repair–Proficient Stage II Colon Cancer

Ghosh

Tie

Murányi³

et al. 2016

Clinical Cancer Research

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Purpose Prognostic markers that identify patients with stage II colon cancers (CC) who are at risk of recurrence are essential to personalize therapy. We evaluated the potential of GIV/Girdin as a predictor of recurrence risk in such patients. Experimental Design Expression of full-length GIV was evaluated by immunohistochemistry (IHC) using a newly developed monoclonal antibody together with a mismatch repair (MMR)-specific antibody panel in three stage II CC patient cohorts, ie. a training (n=192), test (n=317), and validation (n=181) cohort, with clinical follow-up data. Recurrence risk stratification models were established in the training cohort of T3, proficient MMR (pMMR) patients without chemotherapy and subsequently validated. Results For T3 pMMR tumors, GIV expression and the presence of lymphovascular invasion (LVI) were the only factors predicting recurrence in both training (GIV: HR:2.78, p=0.013; LVI: HR 2.54, p=0.025) and combined test and validation (pooled) cohorts (GIV, HR:1.85, p=0.019; LVI, HR:2.52, p=0.0004). A risk model based on GIV expression and LVI-status classified patients into high- or low-risk groups; 3-year recurrence-free survival was significantly lower in the high-risk versus low-risk group across all cohorts (Training: 52.3% versus 84.8%; HR:3.74, 95%CI: 1.50–9.32; Test: 85.9% versus 97.9%, HR:7.83, 95%CI:1.03–59.54; Validation: 59.4% versus 84.4%, HR:3.71, 95%CI: 1.24–11.12). Conclusions GIV expression status predicts recurrence risk in patients with T3 pMMR stage II CC. A risk model combining GIV expression and LVI-status information further enhances prediction of recurrence. Further validation studies are warranted before GIV status can be routinely included in patient management algorithms.

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Section: Discussionsupporting

confidence: 91%

Girdin (GIV) Expression as a Prognostic Marker of Recurrence in Mismatch Repair–Proficient Stage II Colon Cancer

Ghosh

Tie

Murányi³

et al. 2016

Clinical Cancer Research

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“…The increased availability and reduced costs of microarrays, GWAS and NGS platforms make the pharmacogenetic profiling an appealing area of investigation, as demonstrated by the set up of specific genomic classifiers in breast and CRC patients [128,129]. Hopefully, the future application of results in clinical settings will ensure an efficient and effective stratification of patients while drug use will become more appropriate by adapting doses and combinations to individual genetic signature.…”

Section: Discussionmentioning

confidence: 99%

Methods: for studying pharmacogenetic profiles of combination chemotherapeutic drugs

Paolo

Polillo²,

Lastella³

et al. 2015

Expert Opinion on Drug Metabolism & Toxicology

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Facing the rapid technological evolution for genetic analyses, the most pressing issues are the choice of appropriate strategies (i.e., from gene candidate up to next-generation sequencing) and the possibility to replicate study results for their final validation. It is likely that the latter will be the major obstacle in the future. However, the present landscape is opening up new possibilities, overcoming those hurdles that have limited result translation into clinical settings for years.

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“…This test, known as Oncotype DX, has been used to identify patients who would most benefit from adjuvant chemotherapy (32). This approach has also been used in colon cancer (33).…”

Section: Advanced Technology In Cancer Prevention and Controlmentioning

confidence: 99%

Integration of advances in social media and mHealth technology are pivotal to successful cancer prevention and control

O’Leary

Zaheer

Redmond

et al. 2016

mHealth

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Genomic Classifier ColoPrint Predicts Recurrence in Stage II Colorectal Cancer Patients More Accurately Than Clinical Factors

Abstract: Background. Approximately 20% of patients with stage II colorectal cancer will experience a relapse. Current clinicalpathologic stratification factors do not allow clear identification of these high-risk patients. ColoPrint (Agendia, Amsterdam,The

Cited by 118 publications

References 29 publications

Girdin (GIV) Expression as a Prognostic Marker of Recurrence in Mismatch Repair–Proficient Stage II Colon Cancer

Girdin (GIV) Expression as a Prognostic Marker of Recurrence in Mismatch Repair–Proficient Stage II Colon Cancer

Methods: for studying pharmacogenetic profiles of combination chemotherapeutic drugs

Integration of advances in social media and mHealth technology are pivotal to successful cancer prevention and control

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