Hypoploidy defines patients with poor prognosis in breast cancer

Chavez-Uribe, Elisabet; Cameselle-Teijeiro, José; Viñuela, Juan E.; Castro-Piñeiro, Carmen; Gudé, Francisco; Forteza, Jerónimo; Puente-Domínguez, José Luis

doi:10.3892/or.17.5.1109

Cited by 3 publications

(5 citation statements)

References 24 publications

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“…Given our prior finding of DNA ploidy as an indepdent prognostic factor for overall survival of breast cancer patients [11] , we further classified ER−&PR− tumors by their DNA index and evaluated the association of family history and these tumor subtypes ( Table 5 ). Family history was more pronouncedly associated with diploid/near-diploid ER−&PR− tumors (OR, 2.17; 95% CI, 0.99–4.74) than aneuploid ER−&PR− tumors (OR, 1.23; 95% CI, 0.73–2.08).…”

Section: Resultsmentioning

confidence: 99%

“…The study involved 663 women with operable invasive breast cancer diagnosed and treated between April 1991 and December 2005 at the Clinical University Hospital of Santiago de Compostela (Santiago de Compostela, Spain) [11].…”

Section: Methodsmentioning

confidence: 99%

“…As a part of the Breast Oncology Galician Network (BREOGAN), a population-based study was conducted in the city of Santiago de Compostela, Spain within a geographically defined health region that covers aproximately 500,000 inhabitants. The study involved 663 women with operable invasive breast cancer diagnosed and treated between April 1991 and December 2005 at the Clinical University Hospital of Santiago de Compostela (Santiago de Compostela, Spain) [11] .…”

Section: Methodsmentioning

confidence: 99%

“…Karyometry was carried out at a magnification of ×400 using a light microscope with an eyepiece equipped with a micrometer grid. Details of procedures have been described in a previous publication [11] .…”

Section: Methodsmentioning

confidence: 99%

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Family History and Breast Cancer Hormone Receptor Status in a Spanish Cohort

et al. 2012

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BackgroundBreast cancer is a heterogenous disease that impacts racial/ethnic groups differently. Differences in genetic composition, lifestyles, reproductive factors, or environmental exposures may contribute to the differential presentation of breast cancer among Hispanic women.Materials and MethodsA population-based study was conducted in the city of Santiago de Compostela, Spain. A total of 645 women diagnosed with operable invasive breast cancer between 1992 and 2005 participated in the study. Data on demographics, breast cancer risk factors, and clinico-pathological characteristics of the tumors were collected. Hormone receptor negative tumors were compared with hormone receptor postive tumors on their clinico-pathological characteristics as well as risk factor profiles.ResultsAmong the 645 breast cancer patients, 78% were estrogen receptor-positive (ER+) or progesterone receptor-positive (PR+), and 22% were ER−&PR−. Women with a family history of breast cancer were more likely to have ER−&PR− tumors than women without a family history (Odds ratio, 1.43; 95% confidence interval, 0.91–2.26). This association was limited to cancers diagnosed before age 50 (Odds ratio, 2.79; 95% confidence interval, 1.34–5.81).ConclusionsAn increased proportion of ER−&PR− breast cancer was observed among younger Spanish women with a family history of the disease.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Family History and Breast Cancer Hormone Receptor Status in a Spanish Cohort

et al. 2012

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“…In the original analysis of the dataset (Chavez-Uribe et al, 2007), the authors categorized the variable DI into three groups, i.e., Group I diploid (0.96 ≤ DI ≤ 1.15), Group II hyperploids (DI ≥ 1.16) and Group III hypoploids (DI ≤ 0.95), and they concluded that the patients with hypoploid tumours had a worse prognosis. From the biologic point of view, clinicians expect that tumours with DI values close to 1 will have a better prognosis than those distant from 1.…”

Section: Multi-state Modelling Approachmentioning

confidence: 99%

Flexible hazard ratio curves for continuous predictors in multi-state models

Cadarso‐Suárez

Meira‐Machado

Kneib

et al. 2010

Statistical Modelling

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Multi-state models (MSMs) are very useful for describing complicated event history data. These models may be considered as a generalization of survival analysis where survival is the ultimate outcome of interest but where intermediate (transient) states are identified. One major goal in clinical applications of MSMs is to study the relationship between the different covariates and disease evolution. Usually, MSMs are assumed to be parametric, and the effects of continuous predictors on log-hazards are modelled linearly. In practice, however, the effect of a given continuous predictor can be unknown, and its form may be different in all transitions. In this paper,we propose a P-spline approach that allows for non-linear relationships between continuous predictors and survival in the multi-state framework. To better understand the effects at each transition, results are expressed in terms of hazard ratio curves, taking a specific covariate value as reference. Confidence bands for these curves are also derived. The proposed methodology was applied to a database on breast cancer, using a progressive three-state model. This application revealed hitherto unreported effects: whereas DNA index is only an important non-linear predictor of recurrence, the percentage of cells in phase S is a significant predictor of both recurrence and mortality.

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Revisiting tumour aneuploidy — the place of ploidy assessment in the molecular era

2015

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Chromosome instability (CIN) is gaining increasing interest as a central process in cancer. CIN, either past or present, is indicated whenever tumour cells harbour an abnormal quantity of DNA, termed 'aneuploidy'. At present, the most widely used approach to detecting aneuploidy is DNA cytometry - a well-known research assay that involves staining of DNA in the nuclei of cells from a tissue sample, followed by analysis using quantitative flow cytometry or microscopic imaging. Aneuploidy in cancer tissue has been implicated as a predictor of a poor prognosis. In this Review, we have explored this hypothesis by surveying the current landscape of peer-reviewed research in which DNA cytometry has been applied in studies with disease-appropriate clinical follow up. This area of research is broad, however, and we restricted our survey to results published since 2000 relating to seven common epithelial cancers (those of the breast; endometrium, ovary, and uterine cervix; oesophagus; colon and rectum; lung; prostate; and bladder). We placed particular emphasis on results from multivariate analyses to pinpoint situations in which the prognostic value of aneuploidy as a biomarker is strong compared with that of existing indicators, such as clinical stage, histological grade, and specific molecular markers. We summarize the implications of our findings for the prognostic use of ploidy analysis in the clinic and for the theoretical understanding of the role of CIN in carcinogenesis.

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Hypoploidy defines patients with poor prognosis in breast cancer

Cited by 3 publications

References 24 publications

Family History and Breast Cancer Hormone Receptor Status in a Spanish Cohort

Family History and Breast Cancer Hormone Receptor Status in a Spanish Cohort

Flexible hazard ratio curves for continuous predictors in multi-state models

Revisiting tumour aneuploidy — the place of ploidy assessment in the molecular era

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