Clinical response to primary letrozole therapy in elderly patients with early breast cancer: possible role for p53 as a biomarker

Current Approaches to Diagnosis and Treatment of Ductal Carcinoma In Situ and Future Directions

The presentation and treatment of ductal carcinoma in situ (DCIS) has changed substantially over the years. While previously an incidental pathologic finding in more advanced, palpable tumors, the institution of screening mammography has repositioned this disease entity as one largely diagnosed as a non-palpable lesion, often prior to any invasive disease. As DCIS is a precursor to invasive carcinoma, evolution in the approach to treatment has followed in the footsteps of that for invasive disease, including breast conservation therapy, adjuvant radiation, and use of antihormonal therapy. Survival outcomes for DCIS are very high and more recent literature has investigated tailoring therapeutic approaches to avoid overtreatment. Two important areas of ongoing clinical debate concerning overtreatment include use of preoperative MRI and the role of adjuvant radiation. The heterogeneity of the disease makes it difficult to differentiate lesions that would benefit from more aggressive treatment from those in which overtreatment could be avoided. Clinical characteristics, such as histologic appearance, age at diagnosis, and margin status at tumor excision have been established as moderate predictors of disease recurrence, but none has provided strong enough evidence as to guide consensus decisions on adjuvant therapy. Continuing research seeks to define the genetic and molecular characteristics that can predict disease course and serve as the potential targets for novel therapeutic agents. While several markers have shown promise in differentiating tumor aggressiveness, there is still much to be discovered about the precise mechanisms of disease progression and how this can be applied clinically to optimize treatment.

Rational Manual and Automated Scoring Thresholds for the Immunohistochemical Detection of TP53 Missense Mutations in Human Breast Carcinomas

Missense mutations in TP53 are common in human breast cancer, have been associated with worse prognosis, and may predict therapy effect. TP53 missense mutations are associated with aberrant accumulation of p53 protein in tumor cell nuclei. Previous studies have used relatively arbitrary cutoffs to characterize breast tumors as positive for p53 staining by immunohistochemical assays. This study aimed to objectively determine optimal thresholds for p53 positivity by manual and automated scoring methods using whole tissue sections from the Carolina Breast Cancer Study. p53-immunostained slides were available for 564 breast tumors previously assayed for TP53 mutations. Average nuclear p53 staining intensity was manually scored as negative, borderline, weak, moderate, or strong and percentage of positive tumor cells was estimated. Automated p53 signal intensity was measured using the Aperio nuclear v9 algorithm combined with the Genie histology pattern recognition tool and tuned to achieve optimal nuclear segmentation. Receiver operating characteristic curve analysis was performed to determine optimal cutoffs for average staining intensity and percent cells positive to distinguish between tumors with and without a missense mutation. Receiver operating characteristic curve analysis demonstrated a threshold of moderate average nuclear staining intensity as a good surrogate for TP53 missense mutations in both manual (area under the curve=0.87) and automated (area under the curve=0.84) scoring systems. Both manual and automated immunohistochemical scoring methods predicted missense mutations in breast carcinomas with high accuracy. Validation of the automated intensity scoring threshold suggests a role for such algorithms in detecting TP53 missense mutations in high throughput studies.