BackgroundSeveral prognostic factors affect the recurrence of breast cancer in patients who undergo mastectomy. Assays of the expression profiles of multiple genes increase the probability of overexpression of certain genes and thus can potentially characterize the risk of metastasis.MethodsWe propose a 20-gene classifier for predicting patients with high/low risk of recurrence within 5 years. Gene expression levels from a quantitative PCR assay were used to screen 473 luminal breast cancer patients treated at Taiwan Hospital (positive for estrogen and progesterone receptors, negative for human epidermal growth factor receptor 2). Gene expression scores, along with clinical information (age, tumor stage, and nodal stage), were evaluated for risk prediction. The classifier could correctly predict patients with and without relapse (logistic regression, P<0.05).ResultsA Cox proportional hazards regression analysis showed that the 20-gene panel was prognostic with hazard ratios of 5.63 (95% confidence interval 2.77-11.5, univariate) and 5.56 (2.62-11.8, multivariate) for the “genetic” model, and of 8.02 (3.52-18.3, univariate) and 19.8 (5.96-65.87, multivariate) for the “clinicogenetic” model during a 5-year follow-up.ConclusionsThe proposed 20-gene classifier can successfully separate the patients into two risk groups, and the two risk group had significantly different relapse rate and prognosis. This 20-gene classifier can provide better estimation of prognosis, which can help physicians to make better personalized treatment plans.
BackgroundThe information of Oncotype DX applied in Asian breast cancer patients is limited. A recurrence index for distant recurrence (RI-DR) has been developed for early-stage breast cancer (EBC) from tumor samples in Chinese patients. In this study, we compared the prognostic performance of the Oncotype DX (ODx) recurrence score (RS) with the RI-DR for any recurrence risk type.Materials and methodsOne hundred thirty-eight (138) patients with hormone receptor-positive and human epidermal growth factor receptor 2-negative EBC who were previously tested with ODx were included for testing with the RI-DR. The cutoff score to partition the low- and high-risk patients was 26 for RS and 36 for RI-DR. The primary endpoint was recurrence-free survival (RFS).ResultsThe concordance between the RI-DR and RS was 83% in N0 patients and 81% in node-positive patients when the RS score cutoff was set at 26. With a median follow-up interval of 36.8 months, the 4-year RFS for the high- and low-risk groups categorized by the RS were 61.9% and 95.0%, respectively (hazard ratio: 10.6, 95.0% confidence interval [CI]: 1.8–62.9). The 4-year RFS in the high- and low-risk groups categorized by the RI-DR were 72.6% and 98.5%, respectively (hazard ratio: 18.9, 95% CI: 1.8–138.8).ConclusionThis paper illustrated the performance of RI-DR and ODx RS in breast cancer women in Taiwan. There was high concordance between the RI-DR and RS. The RI-DR is not inferior to the RS in predicting RFS in EBC patients. This study will fill the gap between the current and best practice in Chinese patients.
The application of optical absorption spectra in prognostic prediction has hardly been investigated. We developed and evaluated a novel two dimensional absorption spectrum measurement system (TDAS) for use in early diagnosis, evaluating response to chemoradiation, and making prognostic prediction. The absorption spectra of 120 sets of normal and tumor tissues from esophageal cancer patients were analyzed with TDAS ex-vivo. We demonstrated the cancerous tissue, the tissue from patients with a poor concurrent chemoradiotherapy (CCRT) response, and the tissue from patients with an early disease progression each had a readily identifiable common spectral signature. Principal component analysis (PCA) classified tissue spectra into distinct groups, demonstrating the feasibility of using absorption spectra in differentiating normal and tumor tissues, and in predicting CCRT response, poor survival and tumor recurrence (efficiencies of 75%, 100% and 85.7% respectively). Multivariate analysis revealed that patients identified as having poor-response, poor-survival and recurrence spectral signatures were correlated with increased risk of poor response to CCRT (P = 0.012), increased risk of death (P = 0.111) and increased risk of recurrence (P = 0.030) respectively. Our findings suggest that optical absorption microscopy has great potential to be a useful tool for pre-operative diagnosis and prognostic prediction of esophageal cancer.
We report a 23- gene-classifier profiled from Asian women, with the primary purpose of assessing its clinical utility towards improved risk stratification for relapse for breast cancer patients from Asian cohorts within 10 years’ following mastectomy. Four hundred and twenty-two breast cancer patients underwent mastectomy and were used to train the classifier on a logistic regression model. A subset of 197 patients were chosen to be entered into the follow-up studies post mastectomy who were examined to determine the patterns of recurrence and survival analysis based on gene expression of the gene classifier, age at diagnosis, tumor stage and lymph node status, over a 5 and 10 years follow-up period. Metastasis to lymph node (N2-N3) with N0 as the reference (N2 vs. N0 hazard ratio: 2.02 (1.05–8.70), N3 vs. N0 hazard ratio: 4.32 (1.41–13.22) for 5 years) and gene expression of the 23-gene panel (P=0.06, 5 years and 0.02, 10 years, log-rank test) were found to have significant discriminatory effects on the risk of relapse (HR (95%CI):2.50 (0.95–6.50)). Furthermore, survival curves for subgroup analysis with N0-N1 and T1-T2 predicted patients with higher risk scores. The study provides robust evidence of the effectiveness of the 23-gene-classifier and could be used to determine the risk of relapse event (locoregional and distant recurrence) in Asian patients, leading to a meaningful reduction in chemotherapy recommendations.
Breast cancer is the most common cancer and the leading cause of cancer-related death in women. The estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) are important biomarkers in the prognosis of breast cancer, and their expression is used to categorize breast cancer into subtypes. We aimed to analyze the concordance between ER, PR, and HER2 expression levels and breast cancer subtyping results obtained by immunohistochemistry (IHC, for protein) and reverse transcriptase-polymerase chain reaction (RT-PCR, for mRNA) and to assess the recurrence-free survival (RFS) of the different subtypes as determined by the two methods. We compared biomarker expression by IHC and RT-PCR in 397 operable breast cancer patients and categorized all patients into luminal, HER2, and triple-negative (TN) subtypes. The concordance of biomarker expression between the two methods was 81.6% (kappa = 0.4075) for ER, 87.2% (kappa = 0.5647) for PR, and 79.1% (kappa = 0.2767) for HER2. The kappa statistic was 0.3624 for the resulting luminal, HER2, and TN subtypes. The probability of a 5-year RFS was 0.78 for the luminal subtype versus 0.77 for HER2 and 0.51 for TN, when determined by IHC (p = 0.007); and 0.80, 0.71, and 0.61, respectively, when determined by the RT-PCR method (p = 0.008). Based on the current evidence, subtyping by RT-PCR performs similarly to conventional IHC with regard to the 5-year prognosis. The PCR method may thus provide a complementary means of subtyping when IHC results are ambiguous.
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