James Hackett
Cleveland Clinic
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Featured researches published by James Hackett.
Breast Cancer Research | 2006
Laurel A. Habel; Steven Shak; Marlena K. Jacobs; Angela M. Capra; Claire Alexander; Mylan Pho; Joffre Baker; Michael D. Walker; Drew Watson; James Hackett; Noelle T. Blick; Deborah Greenberg; Louis Fehrenbacher; Bryan Langholz; Charles P. Quesenberry
IntroductionThe Oncotype DX assay was recently reported to predict risk for distant recurrence among a clinical trial population of tamoxifen-treated patients with lymph node-negative, estrogen receptor (ER)-positive breast cancer. To confirm and extend these findings, we evaluated the performance of this 21-gene assay among node-negative patients from a community hospital setting.MethodsA case-control study was conducted among 4,964 Kaiser Permanente patients diagnosed with node-negative invasive breast cancer from 1985 to 1994 and not treated with adjuvant chemotherapy. Cases (n = 220) were patients who died from breast cancer. Controls (n = 570) were breast cancer patients who were individually matched to cases with respect to age, race, adjuvant tamoxifen, medical facility and diagnosis year, and were alive at the date of death of their matched case. Using an RT-PCR assay, archived tumor tissues were analyzed for expression levels of 16 cancer-related and five reference genes, and a summary risk score (the Recurrence Score) was calculated for each patient. Conditional logistic regression methods were used to estimate the association between risk of breast cancer death and Recurrence Score.ResultsAfter adjusting for tumor size and grade, the Recurrence Score was associated with risk of breast cancer death in ER-positive, tamoxifen-treated and -untreated patients (P = 0.003 and P = 0.03, respectively). At 10 years, the risks for breast cancer death in ER-positive, tamoxifen-treated patients were 2.8% (95% confidence interval [CI] 1.7–3.9%), 10.7% (95% CI 6.3–14.9%), and 15.5% (95% CI 7.6–22.8%) for those in the low, intermediate and high risk Recurrence Score groups, respectively. They were 6.2% (95% CI 4.5–7.9%), 17.8% (95% CI 11.8–23.3%), and 19.9% (95% CI 14.2–25.2%) for ER-positive patients not treated with tamoxifen. In both the tamoxifen-treated and -untreated groups, approximately 50% of patients had low risk Recurrence Score values.ConclusionIn this large, population-based study of lymph node-negative patients not treated with chemotherapy, the Recurrence Score was strongly associated with risk of breast cancer death among ER-positive, tamoxifen-treated and -untreated patients.
BMC Genomics | 2007
Kim M. Clark-Langone; Jenny Wu; Chithra Sangli; Angela Chen; James L Snable; Anhthu Nguyen; James Hackett; Joffre Baker; Greg Yothers; Chungyeul Kim; Maureen T. Cronin
BackgroundReverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan® RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco type DX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application.ResultsRNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan® reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery.ConclusionWe have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity, sensitivity and reproducibility that are characteristics of RT-PCR. Biomarkers discovered using this approach can be transferred to a clinical reference laboratory setting without having to re-validate the assay on a second technology platform.
Breast Cancer Research and Treatment | 2008
Jenny Chang; Andreas Makris; M. Carolina Gutierrez; Susan G. Hilsenbeck; James Hackett; Jennie Jeong; Mei Lan Liu; Joffre Baker; Kim M. Clark-Langone; Frederick L. Baehner; Krsytal Sexton; Syed K. Mohsin; Tara Gray; Laura E. Alvarez; Gary C. Chamness; C. Kent Osborne; Steven Shak
Archive | 2009
Wayne Cowens; Joffre B. Baker; Kim Langone; Drew Watson; James Hackett; Soonmyung Paik
Archive | 2007
Wayne Cowens; Joffre B. Baker; Kim Clark; James Hackett; Drew Watson; Soonmyung Paik
Archive | 2007
Michael C. Kiefer; Joffre B. Baker; James Hackett
Cancer Research | 2007
Ming Zhou; Mary P. Bronner; Cristina Magi-Galluzz; Ralph J. Tuthill; Frederick Baehner; Mei-Lan Liu; Debjani Dutta; Jennie Jeong; Ya-Tien Chen; James Hackett; Maureen T. Cronin
Cancer Research | 2006
Michael C. Kiefer; Kenneth W Hoyt; James Hackett; Michael D. Walker; Joffre Baker
Archive | 2010
Wendy J. Fantl; David B. Rosen; Alessandra Cesano; Santosh Putta; James Hackett; Michael D. Walker; Jing Shi
Archive | 2008
Wayne Cowens; Joffre B. Baker; Kim Langone; James Hackett; Drew Watson; Soonmyung Paik