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PAM50 and Risk of Recurrence Scores for Interval Breast Cancers.

ABSTRACT: Breast cancers detected after a negative breast screening examination and prior to the next screening are referred to as interval cancers. These cancers generally have poor clinical characteristics compared with screen-detected cancers, but associations between interval cancer and genomic cancer characteristics are not well understood. Mammographically screened women diagnosed with primary invasive breast cancer from 1993 to 2013 (n = 370) were identified by linking the Carolina Breast Cancer Study and the Carolina Mammography Registry. Among women with a registry-identified screening mammogram 0 to 24 months before diagnosis, cancers were classified as screen-detected (N = 165) or interval-detected (N = 205). Using logistic regression, we examined the association of mode of detection with cancer characteristics (clinical, IHC, and genomic), overall, and in analyses stratified on mammographic density and race. Interval cancer was associated with large tumors [>2 cm; OR, 2.3; 95% confidence interval (CI), 1.5-3.7], positive nodal status (OR, 1.8; 95% CI, 1.1-2.8), and triple-negative subtype (OR, 2.5; 95% CI, 1.1-5.5). Interval cancers were more likely to have non-Luminal A subtype (OR, 2.9; 95% CI, 1.5-5.7), whereas screen-detected cancers tended to be more indolent (96% had low risk of recurrence genomic scores; 71% were PAM50 Luminal A). When stratifying by mammographic density and race, associations between interval detection and poor prognostic features were similar by race and density status. Strong associations between interval cancers and poor-prognosis genomic features (non-Luminal A subtype and high risk of recurrence score) suggest that aggressive tumor biology is an important contributor to interval cancer rates. Cancer Prev Res; 11(6); 327-36. ©2018 AACR.

SUBMITTER: Puvanesarajah S

PROVIDER: S-EPMC5984721 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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PAM50 and Risk of Recurrence Scores for Interval Breast Cancers.

Puvanesarajah Samantha S Nyante Sarah J SJ Kuzmiak Cherie M CM Chen Mengjie M Tse Chiu-Kit CK Sun Xuezheng X Allott Emma H EH Kirk Erin L EL Carey Lisa A LA Perou Charles M CM Olshan Andrew F AF Henderson Louise M LM Troester Melissa A MA

Cancer prevention research (Philadelphia, Pa.) 20180405 6

Breast cancers detected after a negative breast screening examination and prior to the next screening are referred to as interval cancers. These cancers generally have poor clinical characteristics compared with screen-detected cancers, but associations between interval cancer and genomic cancer characteristics are not well understood. Mammographically screened women diagnosed with primary invasive breast cancer from 1993 to 2013 (<i>n</i> = 370) were identified by linking the Carolina Breast Ca ...[more]

PMID: 29622545

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Project description:BackgroundStudies of obesity and survival among patients with breast cancer produce conflicting results, possibly because of heterogeneity by molecular subtype.MethodsThis study examined whether the association of body mass index (BMI) at diagnosis with breast cancer recurrence and survival varied across subtypes defined by PAM50 (Prediction Analysis of Microarray 50) gene expression. Included were 1559 Kaiser Permanente Northern California members ages 18 to 79 years who had PAM50 assays and were diagnosed with American Joint Committee on Cancer stage I through III breast cancer from 1996 to 2013. Patients reported weight and height. Cox regression models were adjusted for age, menopause, race/ethnicity, stage, and chemotherapy.ResultsOver a median of 9 years (maximum, 19 years), 378 women developed recurrent disease, and 312 died from breast cancer. Overall, BMI was not associated with breast cancer recurrence or survival when controlling for subtype (eg, the hazard ratio per 5 kg/m2 of BMI was 1.05 [95% confidence interval, 0.95-1.15] for breast cancer-specific death). However, associations varied by subtype. Among women with luminal A cancers, those who had class II/III obesity, but not class I obesity or overweight, had worse outcomes. When women who had a BMI ≥35 kg/m2 were compared with those who had a BMI from 18.5 to <25 kg/m2 , the hazard ratio was 2.24 (95% confidence interval,1.22-4.11) for breast cancer-specific death and 1.24 (95% confidence interval, 1.00-1.54) for recurrence. There was no association within luminal B, basal-like or human epidermal growth factor over-expressing subtypes.ConclusionsAmong patients who had accurately classified breast cancer subtypes based on gene expression, a BMI ≥35 kg/m2 was adversely associated with outcomes only among those who had luminal A cancers. Research is needed into whether tailoring recommendations for weight management to tumor characteristics will improve outcomes. Cancer 2017;123:2535-42. © 2017 American Cancer Society.

Project description:BackgroundThe aim of this study was to investigate the prognostic value of the PAM50 intrinsic subtypes and risk of recurrence (ROR) score in patients with early breast cancer and long-term follow-up. A special focus was placed on hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) pN0 patients not treated with chemotherapy.MethodsPatients with early breast cancer (n = 653) enrolled in the observational Oslo1 study (1995-1998) were followed for distant recurrence and breast cancer death. Clinicopathological parameters were collected from hospital records. The primary tumors were analyzed using the Prosigna® PAM50 assay to determine the prognostic value of the intrinsic subtypes and ROR score in comparison with pathological characteristics. The primary endpoints were distant disease-free survival (DDFS) and breast cancer-specific survival (BCSS).ResultsOf 653 tumors, 52.2% were classified as luminal A, 26.5% as luminal B, 10.6% as HER2-enriched, and 10.7% as basal-like. Among the HR+/HER2- patients (n = 476), 37.8% were categorized as low risk by ROR score, 22.7% as intermediate risk, and 39.5% as high risk. Median follow-up durations for BCSS and DDFS were 16.6 and 7.1 years, respectively. Multivariate analysis showed that intrinsic subtypes (all patients) and ROR risk classification (HR+/HER2- patients) yielded strong prognostic information. Among the HR+/HER2- pN0 patients with no adjuvant treatment (n = 231), 53.7% of patients had a low ROR, and their prognosis at 15 years was excellent (15-year BCSS 96.3%). Patients with intermediate risk had reduced survival compared with those with low risk (p = 0.005). In contrast, no difference in survival between the low- and intermediate-risk groups was seen for HR+/HER2- pN0 patients who received tamoxifen only. Ki-67 protein, grade, and ROR score were analyzed in the unselected, untreated pT1pN0 HR+/HER2- population (n = 171). In multivariate analysis, ROR score outperformed both Ki-67 and grade. Furthermore, 55% of patients who according to the PREDICT tool ( http://www.predict.nhs.uk/ ) would be considered chemotherapy candidates were ROR low risk (33%) or luminal A ROR intermediate risk (22%).ConclusionsThe PAM50 intrinsic subtype classification and ROR score improve classification of patients with breast cancer into prognostic groups, allowing for a more precise identification of future recurrence risk and providing an improved basis for adjuvant treatment decisions. Node-negative patients with low ROR scores had an excellent outcome at 15 years even in the absence of adjuvant therapy.

Project description:In the light of the breast density legislation in the USA, it is important to know a woman's breast cancer risk, but particularly her risk of a tumor that is not detected through mammographic screening (interval cancer). Therefore, we examined the associations of automatically measured volumetric breast density with screen-detected and interval cancer risk, separately.Volumetric breast measures were assessed automatically using Volpara version 1.5.0 (Matakina, New Zealand) for the first available digital mammography (DM) examination of 52,814 women (age 50?-?75 years) participating in the Dutch biennial breast cancer screening program between 2003 and 2011. Breast cancer information was obtained from the screening registration system and through linkage with the Netherlands Cancer Registry. We excluded all screen-detected breast cancers diagnosed as a result of the first digital screening examination. During a median follow-up period of 4.2 (IQR 2.0-6.2) years, 523 women were diagnosed with breast cancer of which 299 were screen-detected and 224 were interval breast cancers. The associations between volumetric breast measures and breast cancer risk were determined using Cox proportional hazards analyses.Percentage dense volume was found to be positively associated with both interval and screen-detected breast cancers (hazard ratio (HR) 8.37 (95% CI 4.34-16.17) and HR 1.39 (95% CI 0.82-2.36), respectively, for Volpara density grade category (VDG) 4 compared to VDG1 (p for heterogeneity?<?0.001)). Dense volume (DV) was also found to be positively associated with both interval and screen-detected breast cancers (HR 4.92 (95% CI 2.98-8.12) and HR 2.30 (95% CI 1.39-3.80), respectively, for VDG-like category (C)4 compared to C1 (p for heterogeneity?=?0.041)). The association between percentage dense volume categories and interval breast cancer risk (HR 8.37) was not significantly stronger than the association between absolute dense volume categories and interval breast cancer risk (HR 4.92).Our results suggest that both absolute dense volume and percentage dense volume are strong markers of breast cancer risk, but that they are even stronger markers for predicting the occurrence of tumors that are not detected during mammography breast cancer screening.

Project description:Purpose To investigate relationships between computer-extracted breast magnetic resonance (MR) imaging phenotypes with multigene assays of MammaPrint, Oncotype DX, and PAM50 to assess the role of radiomics in evaluating the risk of breast cancer recurrence. Materials and Methods Analysis was conducted on an institutional review board-approved retrospective data set of 84 deidentified, multi-institutional breast MR examinations from the National Cancer Institute Cancer Imaging Archive, along with clinical, histopathologic, and genomic data from The Cancer Genome Atlas. The data set of biopsy-proven invasive breast cancers included 74 (88%) ductal, eight (10%) lobular, and two (2%) mixed cancers. Of these, 73 (87%) were estrogen receptor positive, 67 (80%) were progesterone receptor positive, and 19 (23%) were human epidermal growth factor receptor 2 positive. For each case, computerized radiomics of the MR images yielded computer-extracted tumor phenotypes of size, shape, margin morphology, enhancement texture, and kinetic assessment. Regression and receiver operating characteristic analysis were conducted to assess the predictive ability of the MR radiomics features relative to the multigene assay classifications. Results Multiple linear regression analyses demonstrated significant associations (R2 = 0.25-0.32, r = 0.5-0.56, P < .0001) between radiomics signatures and multigene assay recurrence scores. Important radiomics features included tumor size and enhancement texture, which indicated tumor heterogeneity. Use of radiomics in the task of distinguishing between good and poor prognosis yielded area under the receiver operating characteristic curve values of 0.88 (standard error, 0.05), 0.76 (standard error, 0.06), 0.68 (standard error, 0.08), and 0.55 (standard error, 0.09) for MammaPrint, Oncotype DX, PAM50 risk of relapse based on subtype, and PAM50 risk of relapse based on subtype and proliferation, respectively, with all but the latter showing statistical difference from chance. Conclusion Quantitative breast MR imaging radiomics shows promise for image-based phenotyping in assessing the risk of breast cancer recurrence. © RSNA, 2016 Online supplemental material is available for this article.

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PAM50 and Risk of Recurrence Scores for Interval Breast Cancers.

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PAM50 and Risk of Recurrence Scores for Interval Breast Cancers.

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