Systemic immune mediators reflect tumour-infiltrating lymphocyte intensity and predict therapeutic response in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer (BC). Neoadjuvant chemotherapy has proven efficacy in its treatment, and a pathological complete response (pCR) to therapy is predictive of improved long-term survival. The immune response is key to successful neoadjuvant chemotherapy, as indicated by the relation between the percentage of stromal tumour-infiltrating lymphocytes (TILs) in pre-treated tumour tissue samples and the likelihood of achieving pCR. Here we studied systemic immune mediators from volunteer TNBC patients before undergoing neoadjuvant chemotherapy to determine the systemic response association with TIL intensity, treatment response and survival. Patients were classified into pCR responder or non-responder at time of surgery. We found higher levels of immune mediators before treatment began in patients that went on to be pCR responders versus non-pCR, with area under the curve (AUC) values of 0.64-0.80. We also observed a positive correlation between inflammatory systemic immune mediators and the percentage of TILs in pCR responder patients. Combining TILs and systemic immune mediator levels provided stronger AUC values (range of 0.72-0.82). Last, performing a progression-free survival analysis with several of the systemic cytokines that predict pCR, segregated the patients into long- and short-survival groups based on high and low production of the cytokines, respectively. Our study demonstrates that circulating cytokines, before treatment begins, predict pCR in TNBC patients treated with neoadjuvant chemotherapy. Moreover, they may act as a surrogate marker of high TILs or together with TILs to better predict pCR and survival.

A Genome-wide Association Study Identifies SERPINB10, CRLF3, STX7, LAMP3, IFNG-AS1, and KRT80 As Risk Loci Contributing to Cutaneous Leishmaniasis in Brazil.

BACKGROUND: Our goal was to identify genetic risk factors for cutaneous leishmaniasis (CL) caused by Leishmania braziliensis. METHODS: Genotyping 2066 CL cases and 2046 controls using Illumina HumanCoreExomeBeadChips provided data for 4 498 586 imputed single-nucleotide variants (SNVs). A genome-wide association study (GWAS) using linear mixed models took account of genetic diversity/ethnicity/admixture. Post-GWAS positional, expression quantitative trait locus (eQTL) and chromatin interaction mapping was performed in Functional Mapping and Annotation (FUMA). Transcriptional data were compared between lesions and normal skin, and cytokines measured using flow cytometry and Bioplex assay. RESULTS: Positional mapping identified 32 genomic loci associated with CL, none achieving genome-wide significance (P < 5 × 10-8). Lead SNVs at 23 loci occurred at protein coding or noncoding RNA genes, 15 with eQTLs for functionally relevant cells/tissues and/or showing differential expression in lesions. Of these, the 6 most plausible genetic risk loci were SERPINB10 (Pimputed_1000G = 2.67 × 10-6), CRLF3 (Pimputed_1000G = 5.12 × 10-6), STX7 (Pimputed_1000G = 6.06 × 10-6), KRT80 (Pimputed_1000G = 6.58 × 10-6), LAMP3 (Pimputed_1000G = 6.54 × 10-6), and IFNG-AS1 (Pimputed_1000G = 1.32 × 10-5). LAMP3 (Padjusted = 9.25 × 10-12; +6-fold), STX7 (Padjusted = 7.62 × 10-3; +1.3-fold), and CRLF3 (Padjusted = 9.19 × 10-9; +1.97-fold) were expressed more highly in CL biopsies compared to normal skin; KRT80 (Padjusted = 3.07 × 10-8; -3-fold) was lower. Multiple cis-eQTLs across SERPINB10 mapped to chromatin interaction regions of transcriptional/enhancer activity in neutrophils, monocytes, B cells, and hematopoietic stem cells. Those at IFNG-AS1 mapped to transcriptional/enhancer regions in T, natural killer, and B cells. The percentage of peripheral blood CD3+ T cells making antigen-specific interferon-γ differed significantly by IFNG-AS1 genotype. CONCLUSIONS: This first GWAS for CL identified multiple genetic risk loci including a novel lead to understanding CL pathogenesis through regulation of interferon-γ by IFNG antisense RNA 1.