Plasma Metabolome Signatures to Predict Responsiveness to Neoadjuvant Chemotherapy in Breast Cancer.

BACKGROUND: Neoadjuvant chemotherapy (NACT) has arisen as a treatment option for breast cancer (BC). However, the response to NACT is still unpredictable and dependent on cancer subtype. Metabolomics is a tool for predicting biomarkers and chemotherapy response. We used plasma to verify metabolomic alterations in BC before NACT, relating to clinical data. METHODS: Liquid chromatography coupled to mass spectrometry (LC-MS) was performed on pre-NACT plasma from patients with BC (n = 75). After data filtering, an SVM model for classification was built and validated with 75%/25% of the data, respectively. RESULTS: The model composed of 19 identified metabolites effectively predicted NACT response for training/validation sets with high sensitivity (95.4%/93.3%), specificity (91.6%/100.0%), and accuracy (94.6%/94.7%). In both sets, the panel correctly classified 95% of resistant and 94% of sensitive females. Most compounds identified by the model were lipids and amino acids and revealed pathway alterations related to chemoresistance. CONCLUSION: We developed a model for predicting patient response to NACT. These metabolite panels allow clinical gain by building precision medicine strategies based on tumor stratification.

Gene expression associated with unfavorable vaginal bleeding in women using the etonogestrel subdermal contraceptive implant: a prospective study.

To evaluate gene expression associated with unfavorable vaginal bleeding in users of the Etonogestrel (ENG) contraceptive implant. Prospective study involving 100 women who intended to use the ENG implant. Exclusion criteria included abnormal uterine bleeding, inability to attend a 1-year follow-up, and implant removal for reasons unrelated to vaginal bleeding or loss of follow-up. We obtained endometrial biopsies before implant placement and assessed the expression of 20 selected genes. Users maintained a uterine bleeding diary for 12 months post-implant placement. For statistical analysis, we categorized women into those with or without favorable vaginal bleeding at 3 and 12 months. Women with lower CXCL1 expression had a 6.8-fold increased risk of unfavorable vaginal bleeding at 3 months (OR 6.8, 95% CI 2.21-20.79, p < 0.001), while those with higher BCL6 and BMP6 expression had 6- and 5.1-fold increased risks, respectively. By the 12-month follow-up, women with lower CXCL1 expression had a 5.37-fold increased risk of unfavorable vaginal bleeding (OR 5.37, 95% CI 1.63-17.73, p = 0.006). Women with CXCL1 expression < 0.0675, BCL6 > 0.65, and BMP6 > 3.4 had a higher likelihood of experiencing unfavorable vaginal bleeding at 3 months, and CXCL1 < 0.158 at 12 months. Users of ENG contraceptive implants with elevated BCL6 and BMP6 expression exhibited a higher risk of breakthrough bleeding at the 3-month follow-up. Conversely, reduced CXCL1 expression was associated with an elevated risk of bleeding at both the 3 and 12-month follow-ups.

Gene expression associated with vaginal bleeding in women using the 52-mg levonorgestrel hormonal intrauterine device: A prospective study.

OBJECTIVE: To evaluate gene expression associated with vaginal bleeding in the 52-mg hormonal intrauterine device (IUD) users. MATERIALS AND METHODS: We conducted a prospective study involving 100 women seeking to use the 52-mg hormonal IUD for contraception. We excluded women with a history or current condition of abnormal uterine bleeding and who were unable to attend a 1-year follow up. Women who expelled the device, removed it for reasons unrelated to vaginal bleeding, or were lost to follow up were discontinued. We collected endometrial biopsies immediately before IUD placement and assessed 20 selected genes using reverse transcription quantitative polymerase chain reaction. Users maintained a uterine bleeding diary for 12 months following IUD insertion. For statistical analysis, participants were categorized into groups with or without vaginal bleeding at 3 and 12 months. RESULTS: Women with elevated CXCL9 expression had an 8.15-fold higher likelihood of experiencing vaginal bleeding at 3 months (odds ratio [OR] 8.15, 95% confidence interval [CI] 2.24-29.61, P = 0.001). At 12 months of follow up, women with increased TIMP1 expression had a 2.74-fold higher chance of experiencing vaginal bleeding (OR 2.74, 95% CI 1.08-6.95, P = 0.033). CXCL9 ≥ 1.5 and IL17A ≥ 0.68 were associated with a higher probability of vaginal bleeding at 3 months, while TIMP1 levels ≥0.943 were linked to an increased risk of bleeding at 12 months. CONCLUSION: Users of the 52-mg hormonal IUD with elevated relative CXCL9 expression face an increased risk of vaginal bleeding at 3-month follow up, whereas those with heightened TIMP1 expression are more likely to experience vaginal bleeding at 12 months.

Copy number alterations associated with clinical features in an underrepresented population with breast cancer.

BACKGROUND: As the most incident tumor among women worldwide, breast cancer is a heterogeneous disease. Tremendous efforts have been made to understand how tumor characteristics as histological type, molecular subtype, and tumor microenvironment collectively influence disease diagnosis to treatment, which impact outcomes. Differences between populations and environmental and cultural factors have impacts on the origin and evolution of the disease, as well as the therapeutic challenges that arise due to these factors. We, then, compared copy number variations (CNVs) in mucinous and nonmucinous luminal breast tumors from a Brazilian cohort to investigate major CNV imbalances in mucinous tumors versus non-mucinous luminal tumors, taking into account their clinical and pathological features. METHODS: 48 breast tumor samples and 48 matched control blood samples from Brazilian women were assessed for CNVs by chromosome microarray. Logistic regression and random forest models were used in order to assess CNVs in chromosomal regions from tumors. RESULTS: CNVs that were identified in chromosomes 1, 5, 8, 17, 19, and 21 classify tumors according to their histological type, ethnicity, disease stage, and familial history. CONCLUSION: Copy number alterations described in this study provide a better understanding of the landscape of genomic aberrations in mucinous breast cancers that are associated with clinical features.

Multicenter Study Using Desorption-Electrospray-Ionization-Mass-Spectrometry Imaging for Breast-Cancer Diagnosis.

The histological and molecular subtypes of breast cancer demand distinct therapeutic approaches. Invasive ductal carcinoma (IDC) is subtyped according to estrogen-receptor (ER), progesterone-receptor (PR), and HER2 status, among other markers. Desorption-electrospray-ionization-mass-spectrometry imaging (DESI-MSI) is an ambient-ionization MS technique that has been previously used to diagnose IDC. Aiming to investigate the robustness of ambient-ionization MS for IDC diagnosis and subtyping over diverse patient populations and interlaboratory use, we report a multicenter study using DESI-MSI to analyze samples from 103 patients independently analyzed in the United States and Brazil. The lipid profiles of IDC and normal breast tissues were consistent across different patient races and were unrelated to country of sample collection. Similar experimental parameters used in both laboratories yielded consistent mass-spectral data in mass-to-charge ratios ( m/ z) above 700, where complex lipids are observed. Statistical classifiers built using data acquired in the United States yielded 97.6% sensitivity, 96.7% specificity, and 97.6% accuracy for cancer diagnosis. Equivalent performance was observed for the intralaboratory validation set (99.2% accuracy) and, most remarkably, for the interlaboratory validation set independently acquired in Brazil (95.3% accuracy). Separate classification models built for ER and PR statuses as well as the status of their combined hormone receptor (HR) provided predictive accuracies (>89.0%), although low classification accuracies were achieved for HER2 status. Altogether, our multicenter study demonstrates that DESI-MSI is a robust and reproducible technology for rapid breast-cancer-tissue diagnosis and therefore is of value for clinical use.