Ductal Carcinoma in Situ: State of the Science and Roadmap to Advance the Field

Kuerer, Henry Mark; Albarracin, Constance T.; Yang, Wei Tse; Cardiff, Robert D.; Brewster, Abenaa M.; Symmans, W. Fraser; Hylton, Nola M.; Middleton, Lavinia P.; Krishnamurthy, Savitri; Perkins, George H.; Babiera, Gildy; Edgerton, Mary E.; Czerniecki, Brian J.; Arun, Banu K.; Hortobágyi, Gabriel N.

doi:10.1200/jco.2008.18.3103

Cited by 149 publications

(103 citation statements)

References 72 publications

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“…2 We apply herein a reduced version of a general agent-based cell model [24,30,33,34] (preprint of [24] at: http://www. MathCancer.org/Publications.php#macklin11 jtb) that improves over a previous cellular automaton approach [35,36]. Accordingly, we only determine averaged tumor population dynamics of mitosis and death, where these phenotypic states are governed by stochastic processes which depend upon the cells' internal machinery and its sampling of the heterogeneous microenvironment (nutrient concentrations σ).…”

Section: Patient-specific Calibration Of Eqs (1) and (2) From Cell-smentioning

confidence: 99%

A Novel, Patient-Specific Mathematical Pathology Approach for Assessment of Surgical Volume: Application to Ductal Carcinomain situof The Breast

Edgerton

Chuang

Macklin

et al. 2011

Analytical Cellular Pathology

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Abstract. We introduce a novel "mathematical pathology" approach, founded on a biophysical model, to identify robust patientspecific predictors of tumor growth useful in clinical practice to improve the accuracy of diagnosis/prognosis and intervention. In accordance with biological observations, our model simulates the diffusion-limited in-situ tumors with a relatively short phase of fast initial growth, followed by a prolonged slow-growth phase where tumor size is constrained primarily by the relative weight of cell mitosis and death. The former phase may only last for a few months, so that at the time of diagnosis, we may assume that most tumors will have entered the phase where their size is changing slowly. Based on this prediction, we hypothesize that the volume of breast with ducts affected by in-situ tumors at the time of diagnosis will be closely approximated by a modelderived mathematical function based on the ratio of tumor cell proliferation-to-apoptosis indices and on the extent of diffusion of cell nutrients (diffusion penetration length), which can be measured from immunohistochemical and morphometric analysis of patient histopathology specimens without the need for multiple-time measurements. We tested this idea in a retrospective study of 17 patients by staining breast tumor specimens containing ductal carcinoma in situ for mitosis with Ki-67 and for apoptosis with cleaved caspase-3 and counting cells positive for each marker. We also determined diffusion penetration by measuring the thickness of viable rims of tumor cells within ducts. Using the ensuing ratios, we applied the model to determine a predicted surgical volume or tumor size. We then corroborated our hypothesis by comparing the predicted size of each tumor based on our model with the actual size of the pathological specimen after tumor excision (R 2 = 0.74-0.88). In addition, for the 17 cases studied, both histological grade and mammography were not found to correlate with tumor size (R 2 = 0.08-0.47). We conclude that our mathematical pathology approach yields a high degree of accuracy in predicting the size of tumors based on the mitotic/apoptotic index and on diffusion penetration. By obtaining these ratios at the time of initial biopsy, pathologists can employ our model to predict the size of the tumor and thereby inform surgeons how much tissue to remove (surgical volume). We discuss how results from the model have implications concerning the current debate on recommendations for screening mammography, while the model itself may contribute to better planning of breast conservation surgery.

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Section: Patient-specific Calibration Of Eqs (1) and (2) From Cell-smentioning

confidence: 99%

A Novel, Patient-Specific Mathematical Pathology Approach for Assessment of Surgical Volume: Application to Ductal Carcinomain situof The Breast

Edgerton

Chuang

Macklin

et al. 2011

Analytical Cellular Pathology

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“…The earliest recognised breast cancers (in situ malignancies) already harbour many of the genomic aberrations that are characteristic of invasive disease (Allred et al, 2008;Tamimi et al, 2008;Kuerer et al, 2009). Attention has focused recently on alterations in earlier cancer precursors, including hyperplastic lesions and even histologically normal (HN) epithelium (reviewed in Simpson et al, 2005;Mastracci et al, 2007;Heaphy et al, 2009).…”

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confidence: 99%

Gene expression in histologically normal epithelium from breast cancer patients and from cancer-free prophylactic mastectomy patients shares a similar profile

et al. 2010

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INTRODUCTION:We hypothesised that gene expression in histologically normal (HN) epithelium (NlEpi) would differ between breast cancer patients and usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomy (PM) samples from high-risk women would resemble HN gene expression. METHODS: We analysed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 samples, we used microarrays to compare gene expression between 18 RM patients and 18 age-matched HN (9 oestrogen receptor (ER) þ , 9 ERÀ) and 6 PM patients. Data were analysed using a Bayesian approach (BADGE), and validated with quantitative real-time PCR (qPCR) in 31 independent NlEpi samples from 8 RM, 17 HN, and 6 PM patients. RESULTS: A total of 98 probe sets (86 genes) were differentially expressed between RM and HN samples. Performing hierarchical analysis with these 98 probe sets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM compared with HN patients, and lower (58%), but more heterogeneous, in RM compared with PM patients. The 86 genes were implicated in many processes including transcription and the MAPK pathway. CONCLUSION: Gene expression differs between the NlEpi of breast cancer cases and controls. The profile of cancer cases can be discerned in high-risk NlEpi from cancer-free breasts. This suggests that the profile is not an effect of the tumour, but may mark increased risk and reveal the earliest genomic changes of breast cancer.

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“…Women with DCIS were almost all treated and a 35.8% were mastectomized, resulting in a possible overtreatment. However, DCIS treatment was necessary to obtain a low percentage of subsequent IBC if we considered the estimation that 14-50% of DCIS would progress to IBC if left untreated (16).…”

Section: Discussionmentioning

confidence: 99%

Rapid increase in incidence of breast ductal carcinoma in situ in Girona, Spain 1983–2007

et al. 2012

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Ductal Carcinoma in Situ: State of the Science and Roadmap to Advance the Field

Abstract: There is a critical need for a concerted international effort among patients with DCIS, clinicians, and basic scientists to conduct the research necessary to improve fundamental understanding of the biology and clinical behavior of DCIS and prevent development of invasive breast cancer.

Cited by 149 publications

References 72 publications

A Novel, Patient-Specific Mathematical Pathology Approach for Assessment of Surgical Volume: Application to Ductal Carcinomain situof The Breast

A Novel, Patient-Specific Mathematical Pathology Approach for Assessment of Surgical Volume: Application to Ductal Carcinomain situof The Breast

Gene expression in histologically normal epithelium from breast cancer patients and from cancer-free prophylactic mastectomy patients shares a similar profile

Rapid increase in incidence of breast ductal carcinoma in situ in Girona, Spain 1983–2007

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