Comedications influence immune infiltration and pathological response to neoadjuvant chemotherapy in breast cancer.

Immunosurveillance plays an important role in breast cancer (BC) prognosis and progression, and can be geared by immunogenic chemotherapy. In a cohort of 1023 BC patients treated with neoadjuvant chemotherapy (NAC), 40% of the individuals took comedications mostly linked to aging and comorbidities. We systematically analyzed the off-target effects of 1178 concurrent comedications (classified according to the Anatomical Therapeutic Chemical (ATC) Classification System) on the density of tumor-infiltrating lymphocytes (TILs) and pathological complete responses (pCR). At level 1 of the ATC system, the main anatomical classes of drugs were those targeting the nervous system (class N, 39.1%), cardiovascular disorders (class C, 26.6%), alimentary and metabolism (class A, 16.9%), or hormonal preparations (class H, 6.5%). At level 2, the most frequent therapeutic classes were psycholeptics (N05), analgesics (N02), and psychoanaleptics (N06). Pre-NAC TIL density in triple-negative BC (TNBC) was influenced by medications from class H, N, and A, while TIL density in HER2+ BC was associated with the use of class C. Psycholeptics (N05) and agents acting on the renin-angiotensin system (C09) were independently associated with pCR in the whole population of BC or TNBC, and in HER2-positive BC, respectively. Importantly, level 3 hypnotics (N05C) alone were able to reduce tumor growth in BC bearing mice and increased the anti-cancer activity of cyclophosphamide in a T cell-dependent manner. These findings prompt for further exploration of drugs interactions in cancer, and for prospective drug-repositioning strategies to improve the efficacy of NAC in BC.

Text Mining in Electronic Medical Records Enables Quick and Efficient Identification of Pregnancy Cases Occurring After Breast Cancer.

PURPOSE: To apply text mining (TM) technology on electronic medical records (EMRs) of patients with breast cancer (BC) to retrieve the occurrence of a pregnancy after BC diagnosis and compare its performance to manual curation. MATERIALS AND METHODS: The training cohort (Cohort A) comprised 344 patients with BC age ≤ 40 years old treated at Institut Curie between 2005 and 2007. Manual curation consisted in manually reviewing each EMR to retrieve pregnancies. TM consisted of first applying a keyword filter ("accouch*" or "enceinte," French terms for "deliver*" and "pregnant," respectively) to select a subset of EMRs, and, second, checking manually EMRs to confirm the pregnancy. Then, we applied our TM algorithm on an independent cohort of patients with BC treated between 2008 and 2012 (Cohort B). RESULTS: In Cohort A, 36 pregnancies were identified among 344 patients (10.5%; 2,829 person-years of EMR). Thirty were identified by manual review versus 35 by TM. TM resulted in a lower percentage of manual checking (26.7% v 100%, respectively) and substantial time gains (time to identify a pregnancy: 13 minutes for TM v 244 minutes for manual curation, respectively). Presence of any of the two TM filters showed excellent sensitivity (97%) and negative predictive value (100%). In Cohort B, 67 pregnancies were identified among 1,226 patients (5.5%; 7,349 person-years of EMR). Similarly, for Cohort B, TM spared 904 (73.7%) EMRs from manual review and quickly generated a cohort of 67 pregnancies after BC. Incidence rate of pregnancy after BC was 0.01 pregnancy per person-year of EMR in both cohorts. CONCLUSION: TM is highly efficient to quickly identify rare events and is a promising tool to improve rapidity, efficiency, and costs of medical research.