Targeted mutation detection in breast cancer using MammaSeq™.

BACKGROUND: Breast cancer is the most common invasive cancer among women worldwide. Next-generation sequencing (NGS) has revolutionized the study of cancer across research labs around the globe; however, genomic testing in clinical settings remains limited. Advances in sequencing reliability, pipeline analysis, accumulation of relevant data, and the reduction of costs are rapidly increasing the feasibility of NGS-based clinical decision making. METHODS: We report the development of MammaSeq, a breast cancer-specific NGS panel, targeting 79 genes and 1369 mutations, optimized for use in primary and metastatic breast cancer. To validate the panel, 46 solid tumors and 14 plasma circulating tumor DNA (ctDNA) samples were sequenced to a mean depth of 2311× and 1820×, respectively. Variants were called using Ion Torrent Suite 4.0 and annotated with cravat CHASM. CNVKit was used to call copy number variants in the solid tumor cohort. The oncoKB Precision Oncology Database was used to identify clinically actionable variants. Droplet digital PCR was used to validate select ctDNA mutations. RESULTS: In cohorts of 46 solid tumors and 14 ctDNA samples from patients with advanced breast cancer, we identified 592 and 43 protein-coding mutations. Mutations per sample in the solid tumor cohort ranged from 1 to 128 (median 3), and the ctDNA cohort ranged from 0 to 26 (median 2.5). Copy number analysis in the solid tumor cohort identified 46 amplifications and 35 deletions. We identified 26 clinically actionable variants (levels 1-3) annotated by OncoKB, distributed across 20 out of 46 cases (40%), in the solid tumor cohort. Allele frequencies of ESR1 and FOXA1 mutations correlated with CA.27.29 levels in patient-matched blood draws. CONCLUSIONS: In solid tumor biopsies and ctDNA, MammaSeq detects clinically actionable mutations (OncoKB levels 1-3) in 22/46 (48%) solid tumors and in 4/14 (29%) of ctDNA samples. MammaSeq is a targeted panel suitable for clinically actionable mutation detection in breast cancer.

Whole genome amplification of cell-free DNA enables detection of circulating tumor DNA mutations from fingerstick capillary blood.

The ability to measure mutations in plasma cell-free DNA (cfDNA) has the potential to revolutionize cancer surveillance and treatment by enabling longitudinal monitoring not possible with solid tumor biopsies. However, obtaining sufficient quantities of cfDNA remains a challenge for assay development and clinical translation; consequently, large volumes of venous blood are typically required. Here, we test proof-of-concept for using smaller volumes via fingerstick collection. Matched venous and fingerstick blood were obtained from seven patients with metastatic breast cancer. Fingerstick blood was separated at point-of-care using a novel paper-based concept to isolate plasma centrifuge-free. Patient cfDNA was then analyzed with or without a new method for whole genome amplification via rolling-circle amplification (WG-RCA). We identified somatic mutations by targeted sequencing and compared the concordance of mutation detection from venous and amplified capillary samples by droplet-digital PCR. Patient mutations were detected with 100% concordance after WG-RCA, although in some samples, allele frequencies showed greater variation likely due to differential amplification or primer inaccessibility. These pilot findings provide physiological evidence that circulating tumor DNA is accessible by fingerstick and sustains presence/absence of mutation detection after whole-genome amplification. Further refinement may enable simpler and less-invasive methods for longitudinal or theranostic surveillance of metastatic cancer.

Circulating Tumor Cell Phenotyping via High-Throughput Acoustic Separation.

The study of circulating tumor cells (CTCs) offers pathways to develop new diagnostic and prognostic biomarkers that benefit cancer treatments. In order to fully exploit and interpret the information provided by CTCs, the development of a platform is reported that integrates acoustics and microfluidics to isolate rare CTCs from peripheral blood in high throughput while preserving their structural, biological, and functional integrity. Cancer cells are first isolated from leukocytes with a throughput of 7.5 mL h-1 , achieving a recovery rate of at least 86% while maintaining the cells' ability to proliferate. High-throughput acoustic separation enables statistical analysis of isolated CTCs from prostate cancer patients to be performed to determine their size distribution and phenotypic heterogeneity for a range of biomarkers, including the visualization of CTCs with a loss of expression for the prostate specific membrane antigen. The method also enables the isolation of even rarer, but clinically important, CTC clusters.

Detection of ESR1 mutations in circulating cell-free DNA from patients with metastatic breast cancer treated with palbociclib and letrozole.

ESR1 mutations are frequently acquired in hormone-resistant metastatic breast cancer (MBC). CDK4/6 inhibition along with endocrine therapy is a promising strategy in hormone receptor-positive MBC. However, the incidence and impact of ESR1 mutations on clinical outcome in patients treated with CDK4/6 inhibitors have not been defined. In this study, we evaluated the frequency of ESR1 mutations in cfDNA from 16 patients with MBC undergoing palbociclib and letrozole therapy. Four common ESR1 mutations (D538G, Y537C, Y537N, and Y537S) were analyzed in serial blood draws using ddPCR. Mutation rate was 31.3% (5/16) (n=3; de novo, n=2; acquired). D538G was the most frequent mutation (n=3), followed by Y537N and Y537S (n=2). One patient showed multiple ESR1 mutations. Mutations were enriched during therapy. Progression-free survival (PFS) and overall survival (OS) were similar in patients with and without mutation detected at any given time during treatment. However, PFS was significantly shorter in patients with ESR1 mutation at initial blood draw (3.3 versus 9.0 months, P-value=0.038). In conclusion, ESR1 mutation prevalence is consistent with recent studies in hormone-refractory breast cancer. Further, treatment with palbociclib and letrozole does not prevent selection of ESR1 mutations in later lines of therapy. Larger studies are warranted to validate these findings.

Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers.

BACKGROUND: Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME) are key contributors to heterogeneity. METHODS: We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI) and visually represent heterogeneity with a two-dimensional map. RESULTS: We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score. CONCLUSIONS: This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI), which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different components within the TME. We hypothesize that PMI will uncover key spatial interactions in the TME that contribute to disease proliferation and progression.

Intratumor Heterogeneity Affects Gene Expression Profile Test Prognostic Risk Stratification in Early Breast Cancer.

PURPOSE: To examine the effect of intratumor heterogeneity (ITH) on detection of genes within gene expression panels (GEPs) and the subsequent ability to predict prognostic risk. EXPERIMENTAL DESIGN: Multiplexed barcoded RNA analysis was used to measure the expression of 141 genes from five GEPs (Oncotype Dx, MammaPrint, PAM50, EndoPredict, and Breast Cancer Index) in breast cancer tissue sections and tumor-rich cores from 71 estrogen receptor (ER)-positive node-negative tumors, on which clinical Oncotype Dx testing was previously performed. If the tumor had foci of high Ki67 (n = 26), low/negative progesterone receptor (PR; n = 13), or both (n = 5), additional cores were obtained. In total, 181 samples were processed. Oncotype Dx recurrence scores were calculated from NanoString nCounter gene expression data. RESULTS: Hierarchical clustering using all GEP genes showed that majority (61 of 71) of tumor samples clustered by patient, indicating greater interpatient heterogeneity (IPH) than ITH. We found a strikingly high correlation between Oncotype Dx recurrence scores obtained from whole sections versus tumor-rich cores (r = 0.94). However, high Ki67 and low PR cores had slightly higher but not statistically significant recurrence scores. For 18 of 71 (25%) patients, scores were divergent between sections and cores and crossed the boundaries for low, intermediate, and high risk. CONCLUSIONS: Our study indicates that in patients with highly heterogeneous tumors, GEP recurrence scores from a single core could under- or overestimate prognostic risk. Hence, it may be a useful strategy to assess multiple samples (both representative and atypical cores) to fully account for the ITH-driven variation in risk prediction. Clin Cancer Res; 22(21); 5362-9. ©2016 AACR.

Sensitive Detection of Mono- and Polyclonal ESR1 Mutations in Primary Tumors, Metastatic Lesions, and Cell-Free DNA of Breast Cancer Patients.

PURPOSE: Given the clinical relevance of ESR1 mutations as potential drivers of resistance to endocrine therapy, this study used sensitive detection methods to determine the frequency of ESR1 mutations in primary and metastatic breast cancer, and in cell-free DNA (cfDNA). EXPERIMENTAL DESIGN: Six ESR1 mutations (K303R, S463P, Y537C, Y537N, Y537S, D538G) were assessed by digital droplet PCR (ddPCR), with lower limits of detection of 0.05% to 0.16%, in primary tumors (n = 43), bone (n = 12) and brain metastases (n = 38), and cfDNA (n = 29). Correlations between ESR1 mutations in metastatic lesions and single (1 patient) or serial blood draws (4 patients) were assessed. RESULTS: ESR1 mutations were detected for D538G (n = 13), Y537S (n = 3), and Y537C (n = 1), and not for K303R, S463P, or Y537N. Mutation rates were 7.0% (3/43 primary tumors), 9.1% (1/11 bone metastases), 12.5% (3/24 brain metastases), and 24.1% (7/29 cfDNA). Two patients showed polyclonal disease with more than one ESR1 mutation. Mutation allele frequencies were 0.07% to 0.2% in primary tumors, 1.4% in bone metastases, 34.3% to 44.9% in brain metastases, and 0.2% to 13.7% in cfDNA. In cases with both cfDNA and metastatic samples (n = 5), mutations were detected in both (n = 3) or in cfDNA only (n = 2). Treatment was associated with changes in ESR1 mutation detection and allele frequency. CONCLUSIONS: ESR1 mutations were detected at very low allele frequencies in some primary breast cancers, and at high allele frequency in metastases, suggesting that in some tumors rare ESR1-mutant clones are enriched by endocrine therapy. Further studies should address whether sensitive detection of ESR1 mutations in primary breast cancer and in serial blood draws may be predictive for development of resistant disease. See related commentary by Gu and Fuqua, p. 1034.

A proangiogenic signature is revealed in FGF-mediated bevacizumab-resistant head and neck squamous cell carcinoma.

UNLABELLED: Resistance to antiangiogenic therapies is a critical problem that has limited the utility of antiangiogenic agents in clinical settings. However, the molecular mechanisms underlying this resistance have yet to be fully elucidated. In this study, we established a novel xenograft model of acquired resistance to bevacizumab. To identify molecular changes initiated by the tumor cells, we performed human-specific microarray analysis on bevacizumab-sensitive and -resistant tumors. Efficiency analysis identified 150 genes upregulated and 31 genes downregulated in the resistant tumors. Among angiogenesis-related genes, we found upregulation of fibroblast growth factor-2 (FGF2) and fibroblast growth factor receptor-3 (FGFR3) in the resistant tumors. Inhibition of the FGFR in the resistant tumors led to the restoration of sensitivity to bevacizumab. Furthermore, increased FGF2 production in the resistant cells was found to be mediated by overexpression of upstream genes phospholipase C (PLCg2), frizzled receptor-4 (FZD4), chemokine [C-X3-C motif] (CX3CL1), and chemokine [C-C motif] ligand 5 (CCL5) via extracellular signal-regulated kinase (ERK). In summary, our work has identified an upregulation of a proangiogenic signature in bevacizumab-refractory HNSCC tumors that converges on ERK signaling to upregulate FGF2, which then mediates evasion of anti-VEGF therapy. These findings provide a new strategy on how to enhance the therapeutic efficacy of antiangiogenic therapy. IMPLICATIONS: Novel xenograft model leads to the discovery of FGF as a promising therapeutic target in overcoming the resistance of antiangiogenic therapy in HNSCC.

Interleukin-8 as a modulator of response to bevacizumab in preclinical models of head and neck squamous cell carcinoma.

OBJECTIVES: Bevacizumab, a monoclonal antibody to VEGF-A, is under active clinical evaluation in head and neck squamous cell carcinoma (HNSCC) and appears to be a promising therapy in at least a subset of patients. However, there are no reliable predictive biomarkers to identify those patients most likely to benefit. In this study, we assessed the efficacy of bevacizumab in HNSCC xenograft models to characterize escape mechanisms underlying intrinsic resistance and identify potential biomarkers of drug response. MATERIALS AND METHODS: We evaluated the angiogenic profile of HNSCC cells from sensitive and resistant cell lines using antibody array. We further examined the role of interleukin-8 (IL-8) in contributing to resistance both in vitro and in vivo, using a loss- and gain-of-function approach. RESULTS: Angiogenic profiling indicated that resistant cells expressed higher levels of proangiogenic factors including IL-8, interleukin-1α (IL-1α), vascular endothelial growth factor (VEGF), fibroblast growth factor-a (FGF-a), and tumor necrosis factor-α (TNF-α). IL-8 was the most differentially expressed protein. IL-8 signaling compensated for VEGF inhibition in endothelial cells. Downregulation of IL-8 resulted in sensitization of resistant tumors to bevacizumab by disrupting angiogenesis and enhancing endothelial cell apoptosis. Overexpression of IL-8 in sensitive tumors conferred resistance to bevacizumab. Serum analysis of HNSCC patients treated with a bevacizumab-containing regime revealed high baseline IL-8 levels in a subset of patients refractory to treatment but not in responders. CONCLUSIONS: These results implicate IL-8 in mediating intrinsic resistance to bevacizumab in HNSCC. Hence, co-targeting of VEGF and IL-8 may help overcome resistance and enhance therapeutic efficacy.

Predictive biomarkers to anti-VEGF therapy: progress toward an elusive goal.

The search for reliable biomarkers predictive of response to anti-VEGF therapy has been elusive. VEGF-A, the therapeutic target of bevacizumab, is an intuitive candidate as a predictive biomarker to bevacizumab-based anticancer therapy. However, there remains much controversy in the use of VEGF-A as a predictor of response to bevacizumab.