Genomic signatures to guide the use of chemotherapeutics

Potti, Anil; Dressman, Holly K.; Bild, Andrea; Riedel, Richard F.; Chan, Gina; Sayer, Robyn; Cragun, Janiel M.; Cottrill, Hope M.; Kelley, Michael J.; Petersen, Rebecca P.; Harpole, David; Marks, Jeffrey R.; Berchuck, Andrew; Ginsburg, Geoffrey S.; Febbo, Phillip G.; Lancaster, Johnathan M.; Nevins, Joseph R.

doi:10.1038/nm1491

Cited by 544 publications

(395 citation statements)

References 23 publications

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“…First, it suggests that molecular profiling using genome-wide assays can be a powerful and valid means of identifying biomarkers predictive of clinical response. This has been shown even for less selective agents, such as molecular profiles that predict for taxane activity in the treatment of breast cancer (31). Second, genome-wide profiles could point to additional genetic aberrations that further influence the efficacy of an agent in the absence of (or in conjunction with) primary markers; the fact that clinical responses may occur in only f25% of an already-enriched population (32) highlights the potential existence of additional predictive markers.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines

Greshock

Cheng

Rusnak

et al. 2008

Molecular Cancer Therapeutics

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A common aim of pharmacogenomic studies that use genome-wide assays on panels of cancers is the unbiased discovery of genomic alterations that are associated with clinical outcome and drug response. Previous studies of lapatinib, a selective dual-kinase inhibitor of epidermal growth factor receptor (EGFR) and HER2 tyrosine kinases, have shown predictable relationships between the activity of these target genes and response. Under the hypothesis that additional genes may play a role in drug sensitivity, a predictive model for lapatinib response was constructed from genome-wide DNA copy number data from 24 cancer cell lines. An optimal predictive model which consists of aberrations at nine distinct genetic loci, includes gains of HER2, EGFR, and loss of CDKN2A. This model achieved an area under the receiver operating characteristic curve of f0.85 (80% confidence interval, 0.70 -0.98; P < 0.01), and correctly classified the sensitivity status of 8 of 10 head and neck cancer cell lines. This study shows that biomarkers predictive for lapatinib sensitivity, including the previously described copy number gains of EGFR and HER2, can be discovered using novel genomic assays in an unbiased manner. Furthermore, these results show the utility of DNA copy number profiles in pharmacogenomic studies. [Mol Cancer Ther 2008;7(4):935 -43]

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Section: Discussionmentioning

confidence: 99%

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines

Greshock

Cheng

Rusnak

et al. 2008

Molecular Cancer Therapeutics

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“…(ii) Statistical approaches-linear combinations of known input-output relations and desired phenotype are developed, neglecting the nonlinearity in biological networks. In these models, the system is treated as a black box, and it does not require a complete characterization of the biological networks 37,38 . (iii) Model-based combinations in which biological measurements are used to build explicit models of a target network using simulations 39,40 .…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

Optimization of drug combinations using Feedback System Control

Nowak-Śliwińska¹,

Weiss²,

et al. 2016

Nat Protoc

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“…38 The currently most widely used such assay in the United States is Oncotype DX (Genomic Health, Redwood City, CA, USA), an RT-PCR-based assay, which analyzes 16 cancer-related and 5 reference genes to provide a Recurrence Score. The Recurrence Score is based on the assumption that patients will receive adjuvant hormonal manipulation and predicts a 10-year distant recurrence risk as a continuous variable.…”

mentioning

confidence: 99%

A mitotically active, cellular tumor stroma and/or inflammatory cells associated with tumor cells may contribute to intermediate or high Oncotype DX Recurrence Scores in low-grade invasive breast carcinomas

et al. 2012

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Oncotype DX is an RT-PCR-based 21-gene assay validated to provide prognostic and predictive information in the form of a Recurrence Score in patients with estrogen receptor-positive, lymph node-negative breast cancer. Although the Recurrence Score was shown to correlate with several histopathological tumor features, there is a significant proportion of cases showing an apparent discrepancy between Recurrence Score and risk estimates based on the traditional clinicopathological tumor features. In this study, we tested whether a proliferating, cellular stroma and/or admixed inflammatory cells may result in an artificially increased Recurrence Score in low-grade invasive breast cancers. We analyzed the histopathological features in 141 low-grade invasive breast carcinomas, including 41 special type (tubular, cribriform and mucinous) carcinomas, with available Recurrence Score. The tumor stroma was evaluated for increased cellularity and presence of inflammatory cells. Double immunohistochemical stains for pancytokeratin and Ki-67 was performed to assess the cell proliferation in tumor vs stromal/inflammatory cells. The clinicopathological features of tumors with Recurrence Score o18 (low risk) were compared with those with Recurrence Score Z18 (intermediate/high risk). Carcinomas associated with Recurrence Score Z18 showed lower progesterone receptor immunoreactivity, increased stromal cellularity and presence of inflammatory cells associated with the tumor. Double immunohistochemical stains showed significantly increased proliferation in stromal/inflammatory cells compared with carcinoma cells in cases associated with Recurrence Score Z18. A Ki-67-positive stromal/ tumor cells ratio of 41 predicted Recurrence Score Z18 with an area under the curve of 0.8967 on receiver operator curve analysis (Po0.0001). Our results suggest that the presence of increased stromal cellularity and/ or associated inflammatory cells in low-grade invasive breast carcinomas may contribute to an apparently increased risk of recurrence according to Oncotype DX Recurrence Score. Careful assessment and correlation with histopathological features in such cases may help in determining the appropriate patient management.

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Genomic signatures to guide the use of chemotherapeutics

Cited by 544 publications

References 23 publications

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines

Genome-wide DNA copy number predictors of lapatinib sensitivity in tumor-derived cell lines

Optimization of drug combinations using Feedback System Control

A mitotically active, cellular tumor stroma and/or inflammatory cells associated with tumor cells may contribute to intermediate or high Oncotype DX Recurrence Scores in low-grade invasive breast carcinomas

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