MRI-based breast cancer radiogenomics using RNA profiling: association with subtypes in a single-center prospective study.

BACKGROUND: There are few prospective studies on the correlations between MRI features and whole RNA-sequencing data in breast cancer according to molecular subtypes. The purpose of our study was to explore the association between genetic profiles and MRI phenotypes of breast cancer and to identify imaging markers that influences the prognosis and treatment according to subtypes. METHODS: From June 2017 to August 2018, MRIs of 95 women with invasive breast cancer were prospectively analyzed, using the breast imaging-reporting and data system and texture analysis. Whole RNA obtained from surgical specimens was analyzed using next-generation sequencing. The association between MRI features and gene expression profiles was analyzed in the entire tumor and subtypes. Gene networks, enriched functions, and canonical pathways were analyzed using Ingenuity Pathway Analysis. The P value for differential expression was obtained using a parametric F test comparing nested linear models and adjusted for multiple testing by reporting Q value. RESULTS: In 95 participants (mean age, 53 years ± 11 [standard deviation]), mass lesion type was associated with upregulation of CCL3L1 (sevenfold) and irregular mass shape was associated with downregulation of MIR421 (sixfold). In estrogen receptor-positive cancer with mass lesion type, CCL3L1 (21-fold), SNHG12 (11-fold), and MIR206 (sevenfold) were upregulated, and MIR597 (265-fold), MIR126 (12-fold), and SOX17 (fivefold) were downregulated. In triple-negative breast cancer with increased standard deviation of texture analysis on precontrast T1-weighted imaging, CLEC3A (23-fold), SRGN (13-fold), HSPG2 (sevenfold), KMT2D (fivefold), and VMP1 (fivefold) were upregulated, and IGLC2 (73-fold) and PRDX4 (sevenfold) were downregulated (all, P < 0.05 and Q < 0.1). Gene network and functional analysis showed that mass type estrogen receptor-positive cancers were associated with cell growth, anti-estrogen resistance, and poor survival. CONCLUSION: MRI characteristics are associated with the different expressions of genes related to metastasis, anti-drug resistance, and prognosis, depending on the molecular subtypes of breast cancer.

Association between vascular ultrasound features and DNA sequencing in breast cancer: a preliminary study.

There are few radiogenomic studies to correlate ultrasound features of breast cancer with genomic changes. We investigated whether vascular ultrasound phenotypes are associated with breast cancer gene profiles for predicting angiogenesis and prognosis. We prospectively correlated quantitative and qualitative features of microvascular ultrasound (vascular index, vessel morphology, distribution, and penetrating vessel) and contrast-enhanced ultrasound (time-intensity curve parameters and enhancement pattern) with genomic characteristics in 31 breast cancers. DNA obtained from breast tumors and normal tissues were analyzed using targeted next-generation sequencing of 105 genes. The single-variant association test was used to identify correlations between vascular ultrasound features and genomic profiles. Chi-square analysis was used to detect single nucleotide polymorphisms (SNPs) associated with ultrasound features by estimating p values and odds ratios (ORs). Eight ultrasound features were significantly associated with 9 SNPs (p < 0.05). Among them, four ultrasound features were positively associated with 5 SNPs: high vascular index with rs1136201 in ERBB2 (p = 0.04, OR = 7.75); large area under the curve on contrast-enhanced ultrasound with rs35597368 in PDGFRA (p = 0.04, OR = 4.07); high peak intensity with rs35597368 in PDGFRA (p = 0.049, OR = 4.05) and rs2305948 in KDR (p = 0.04, OR = 5.10); and long mean transit time with rs2275237 in ARNT (p = 0.02, OR = 10.25) and rs755793 in FGFR2 (p = 0.02, OR = 10.25). We identified 198 non-silent SNPs in 71 various cancer-related genes. Vascular ultrasound features can reflect genomic changes associated with angiogenesis and prognosis in breast cancer.

Whole-Exome Sequencing Reveals Clinical Potential of Circulating Tumor DNA from Peritoneal Fluid and Plasma in Endometrial Cancer.

Endometrial cancer (EC) is the most common type of gynecological cancer. Studies comparing tumor gDNA and ctDNA isolated from the plasma and peritoneal fluid of EC patients are limited. Whole-exome sequencing and P53 immunohistochemistry of 24 paired tissue, plasma, and peritoneal fluid samples from 10 EC patients were performed to analyze somatic mutations, copy number alterations, microsatellite instability, and mutational signatures. Mutations in cancer-related genes (KMT2C, NOTCH2, PRKAR1A, SDHA, and USP6) and genes related to EC (ARID1A, CTNNB1, PIK3CA, and PTEN) were identified with high frequencies among the three samples. TP53 and POLE mutations, which are highly related to the molecular classification of EC, were identified based on several key observations. The ctDNA of two patients with negative peritoneal fluid presented TP53 mutations concordant with those in tissues. ctDNA from the plasma and peritoneal fluid of a patient with positive cytology harbored both TP53 and POLE mutations, although none were detected in tissues. Additionally, the patient presented with wild type P53 immunohistochemistry, with a focal "high" expression in a "low" wild type background. The tissues and peritoneal fluid of 75% EC patients showed concordant microsatellite instability. Furthermore, we observed strong mutational concordance between the peritoneal fluid and tumors. Our data suggest that the ctDNA from peritoneal fluid might be a suitable biomarker for identifying the mutational landscape of EC and could complement tumor heterogeneity.