Neuroendocrine breast carcinomas represent a rare subtype of breast cancer. Their definition, prevalence, and prognosis remain controversial in the literature. The 2012 WHO classification of breast cancer categorizes neuroendocrine carcinomas into three morphologically distinct subtypes: well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation. We aimed to gain insight into the clinical, morphologic, phenotypic, and molecular features of 47 neuroendocrine breast carcinomas. Targeted next-generation sequencing by an AmpliSeq 22 cancer gene hotspot panel and the Prosigna assay were performed on 42/47 and 35/47 cases, respectively. Average age at diagnosis was 69 years. All tumors were estrogen receptor-positive and the large majority expressed progesterone receptor (89%), GATA3 (98%), FOXA1 (96%), and CK8/18 (98%). There was an almost equal distribution of luminal A (52%) and B (48%) carcinomas. Almost half of the cohort (49%) displayed a high risk of recurrence score with the Prosigna test. Patients with a neuroendocrine carcinoma had a shorter disease-free survival compared with those affected by carcinomas of no special type matched for age, size, grade, and estrogen receptor status. No significant differences were observed in terms of overall survival. Stratification of neuroendocrine carcinomas using the 2012 WHO criteria did not reveal statistically significant differences among the distinct categories (well-differentiated neuroendocrine tumors, poorly differentiated neuroendocrine carcinomas, and invasive breast carcinomas with neuroendocrine differentiation), in terms of either progression-free or overall survival. Our targeted sequencing analysis found three cases (7%) harboring a PIK3CA mutation, and in three other cases (7%) TP53 mutations were detected. This study showed that neuroendocrine breast carcinoma is a distinct subtype of luminal carcinoma with a low rate of PIK3CA mutations and with an aggressive clinical behavior. An accurate identification of neuroendocrine differentiation may be useful to better tailor patient adjuvant therapy within luminal carcinomas.

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Background Microsatellite instability (MSI) has recently emerged as a predictive pan-tumor biomarker of immunotherapy efficacy, stimulating the development of diagnostic tools compatible with large-scale screening of patients. In this context, noninvasive detection of MSI from circulating tumor DNA stands as a promising diagnostic and posttreatment monitoring tool. Methods We developed drop-off droplet-digital PCR (ddPCR) assays targeting BAT-26, activin A receptor type 2A (ACVR2A), and defensin beta 105A/B (DEFB105A/B) microsatellite markers. Performances of the assays were measured on reconstitution experiments of various mutant allelic fractions, on 185 tumor samples with known MSI status, and on 72 blood samples collected from 42 patients with advanced colorectal or endometrial cancers before and/or during therapy. Results The 3 ddPCR assays reached analytical sensitivity <0.1% variant allelic frequency and could reliably detect and quantify MSI in both tumor and body fluid samples. High concordance between MSI status determination by the three-marker ddPCR test and the reference pentaplex method were observed (100% for colorectal tumors and 93% for other tumor types). Moreover, the 3 assays showed correlations with r ≥ 0.99 with other circulating tumor DNA markers and their dynamic during treatment correlated well with clinical response. Conclusions This innovative approach for MSI detection provides a noninvasive, cost-effective, and fast diagnostic tool, well suited for large-scale screening of patients that may benefit from immunotherapy agents, as well as for monitoring treatment responses.