Redefining breast cancer subtypes to guide treatment prioritization and maximize response: Predictive biomarkers across 10 cancer therapies.

Using pre-treatment gene expression, protein/phosphoprotein, and clinical data from the I-SPY2 neoadjuvant platform trial (NCT01042379), we create alternative breast cancer subtypes incorporating tumor biology beyond clinical hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2) status to better predict drug responses. We assess the predictive performance of mechanism-of-action biomarkers from ∼990 patients treated with 10 regimens targeting diverse biology. We explore >11 subtyping schemas and identify treatment-subtype pairs maximizing the pathologic complete response (pCR) rate over the population. The best performing schemas incorporate Immune, DNA repair, and HER2/Luminal phenotypes. Subsequent treatment allocation increases the overall pCR rate to 63% from 51% using HR/HER2-based treatment selection. pCR gains from reclassification and improved patient selection are highest in HR+ subsets (>15%). As new treatments are introduced, the subtyping schema determines the minimum response needed to show efficacy. This data platform provides an unprecedented resource and supports the usage of response-based subtypes to guide future treatment prioritization.

Global Trend in Artificial Intelligence-Based Publications in Radiology From 2000 to 2018.

OBJECTIVE. The purpose of this study is to evaluate the global trend in artificial intelligence (AI)-based research productivity involving radiology and its subspecialty disciplines. CONCLUSION. The United States is the global leader in AI radiology publication productivity, accounting for almost half of total radiology AI output. Other countries have increased their productivity. Notably, China has increased its productivity exponentially to close to 20% of all AI publications. The top three most productive radiology subspecialties were neuroradiology, body and chest, and nuclear medicine.

Breast Conservation and Negative Margins in Invasive Lobular Carcinoma: The Impact of Oncoplastic Surgery and Shave Margins in 358 Patients.

BACKGROUND: Invasive lobular carcinoma (ILC) of the breast grows in a diffuse pattern, making complete surgical excision difficult. This results in high rates of positive margins and low rates of successful breast-conserving surgery. We hypothesized that utilizing oncoplastic surgical techniques and selective shave margins would be associated with lower positive margin rates and increased breast conservation in women with ILC. METHODS: We performed a retrospective cross-sectional analysis in a large cohort of prospectively collected ILC cases who received surgical treatment at the University of California, San Francisco, between 1992 and 2017. We identified all patients with histologically proven, unilateral or bilateral, stage 1-3 ILC. The primary outcome was positive margin rates, defined as no ink on tumor. RESULTS: We identified 365 tumors in 358 women, with an average age of 61 years, who underwent breast-conserving surgery, and found that the use of oncoplastic techniques (odds ratio [OR] 0.4, 95% confidence interval [CI] 0.21-0.79, p = 0.008) and the selective use of shave margins (OR 0.393, 95% CI 0.22-0.7, p = 0.002) were significantly associated with lower positive margin rates, when adjusted for tumor size and multifocality. The success rate for breast-conservation surgery was 75%, with a 25% conversion rate to mastectomy. CONCLUSIONS: Surgeons should consider routine use of oncoplastic techniques and shave margins when performing breast-conservation surgery for women with ILC as these methods are associated with significantly lower odds of having positive margins and higher breast-conservation rates.

Characterizing the immune microenvironment in high-risk ductal carcinoma in situ of the breast.

PURPOSE: The recent increase in the incidence of ductal carcinoma in situ (DCIS) has sparked debate over the classification and treatment of this disease. Although DCIS is considered a precursor lesion to invasive breast cancer, some DCIS may have more or less risk than is realized. In this study, we characterized the immune microenvironment in DCIS to determine if immune infiltrates are predictive of recurrence. METHODS: Fifty-two cases of high-grade DCIS (HG-DCIS), enriched for large lesions and a history of recurrence, were age matched with 65 cases of non-high-grade DCIS (nHG-DCIS). Immune infiltrates were characterized by single- or dual-color staining of FFPE sections for the following antigens: CD4, CD8, CD20, FoxP3, CD68, CD115, Mac387, MRC1, HLA-DR, and PCNA. Nuance multispectral imaging software was used for image acquisition. Protocols for automated image analysis were developed using CellProfiler. Immune cell populations associated with risk of recurrence were identified using classification and regression tree analysis. RESULTS: HG-DCIS had significantly higher percentages of FoxP3+ cells, CD68+ and CD68+PCNA+ macrophages, HLA-DR+ cells, CD4+ T cells, CD20+ B cells, and total tumor infiltrating lymphocytes compared to nHG-DCIS. A classification tree, generated from 16 immune cell populations and 8 clinical parameters, identified three immune cell populations associated with risk of recurrence: CD8+HLADR+ T cells, CD8+HLADR- T cells, and CD115+ cells. CONCLUSION: These findings suggest that the tumor immune microenvironment is an important factor in identifying DCIS cases with the highest risk for recurrence and that manipulating the immune microenvironment may be an efficacious strategy to alter or prevent disease progression.