Frequency of MicroRNA Response Elements Identifies Pathologically Relevant Signaling Pathways in Triple-Negative Breast Cancer

Complex interactions between mRNAs and microRNAs influence cellular functions. The mRNA-microRNA interactions also determine the post-transcriptional availability of mRNAs and unbound microRNAs. MicroRNAs binds to one or more microRNA response elements (MREs) located on the 3′UTR of mRNAs. In this study, we leveraged MREs and their frequencies in cancer and matched normal tissues to obtain insights into disease-specific interactions between mRNAs and microRNAs. We developed a bioinformatics method “ReMIx” that utilizes RNA sequencing (RNA-Seq) data to quantify MRE frequencies across the transcriptome. We applied ReMIx to triple-negative (TN) breast cancer tumor-normal adjacent pairs and identified MREs specific to TN tumors. ReMIx identified candidate mRNAs and microRNAs in the MAPK signaling cascade. Further analysis of MAPK gene regulatory networks revealed microRNA partners that influence and modulate MAPK signaling. In conclusion, we demonstrate a novel method of using MREs in the identification of functionally relevant mRNA-microRNA interactions in TN breast cancer.

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Bioinformatics method ReMIx identify differential microRNA response rlements (MRE)

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Tumor-specific MREs frequency observed in triple-negative breast cancer (TNBC)

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MRE analysis identify MAPK signaling genes as therapeutic target for TNBC

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MREs frequency can be used to identify pathologically relevant pathways

Patient-specific multi-omics models and the application in personalized combination therapy

The rapid advancement of high-throughput technologies and sharp decrease in cost have opened up the possibility to generate large amount of multi-omics data on an individual basis. The development of high-throughput -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, enables the application of multi-omics technologies in the clinical settings. Combination therapy, defined as disease treatment with two or more drugs to achieve efficacy with lower doses or lower drug toxicity, is the basis for the care of diseases like cancer. Patient-specific multi-omics data integration can help the identification and development of combination therapies. In this review, we provide an overview of different -omics platforms, and discuss the methods for multi-omics, high-throughput, data integration, personalized combination therapy.

Liquid biopsy of the immune environment: Evaluation of peripheral blood mononuclear cells (PBMCs) with CyTOF and response to trastuzumab (T)-based neoadjuvant chemotherapy (NAC) in HER2+ breast cancer (BC)

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Background: Immune responses in the tumor microenvironment have prognostic and predictive value in BC. However, the potential of immune responses observed in peripheral blood as biomarkers in BC remains unclear. We have shown that a higher frequency of circulating monocytes and a lower frequency of antigen-experienced memory CD8+ T cells are associated with response to NAC in triple negative BC (Leon-Ferre et al SABCS 2019). Here, we used cytometry by time-of-flight (CyTOF) to evaluate associations between circulating immune cells, clinical features and response to T-based NAC in HER2+ BC. Methods: PBMC suspensions from 36 pts with stage I-III HER2+ BC were prospectively collected prior to initiation of T-based NAC, stained with 29 metal-tagged antibodies optimized to identify major human immune cell subsets, and acquired in the Helios CyTOF instrument. Differential abundance analysis of immune cells by clinical characteristics and by NAC response was evaluated using Wilcoxon rank sum test. % of immune cell subsets is presented as % of all PBMCs. Results: Most pts presented with ER- tumors (56%), measuring > 5cm (64%) and with nodal metastases (78%). After NAC, 16 pts (44%) achieved pathologic complete response (pCR). Analysis of preNAC PBMCs demonstrated a significantly higher number of B cells (8% vs 5%, p = 0.05) and effector memory CD8+ T cells (CD45RA-/CCR7-, 3 vs 1%, p = 0.02) in pts with pCR compared to those with residual disease. Of the B cell subsets, naïve B cells (CD24-/CD27-) were higher in pts who achieved pCR vs not (7% vs 4%, 0 = 0.04). Regarding clinical characteristics, cN+ pts at presentation exhibited a lower number of peripheral blood T cells compared to cN- pts (47% vs 63%, p = 0.03). Of the T cell subsets, overall CD4+ and naïve CD4+ T cells (CD45RA+/CCR7+) were lower in cN+ vs cN- pts (31% vs 45%, p = 0.05; and 11% vs 24%, p = 0.04). We also observed differences in CD56+/CD16- NK cells by ER status (ER- 1% vs ER+ 3%, p = 0.01), and a moderate negative correlation between age and % circulating CD8+ T cells (rho -0.4669, p = 0.004). Conclusions: Distinct peripheral blood immune cell profiles are observed in HER2+ BC at diagnosis, and are associated with response to T-based NAC and initial clinical characteristics. Notably, pts who later achieved pCR had a relative abundance of B cells and effector memory CD8+ T cells at diagnosis. These data suggest that immune cell phenotyping in peripheral blood may have potential as a biomarker to predict response to NAC in BC.

Role of intratumoral NK cells in triple-negative breast cancer in the FinXX trial and Mayo Clinic cohort

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Background: Several studies have established the critical role of preexisting immune response in triple negative breast cancer (TNBC). Most studies evaluated the tumor infiltrating lymphocytes in stroma. However, limited data are available with regards to the importance of specific subtypes and spatial distribution of these immune infiltrates. Methods: NanoString IO360 gene expression analysis and Digital Spatial Profiling (DSP) were used. DSP was used to quantify 39 immune-related proteins in stromal and tumor-enriched segments from 44 TNBC samples from the FinXX trial (NCT00114816) and 335 samples from the Mayo Clinic (MC) cohort of centrally reviewed TNBC (Leon-Ferre BCRT 2018). In FinXX trial, 22 patients with recurrence and 22 patients without recurrence were included. In MC cohort, 217/335 patients received adjuvant chemotherapy while 118 patients had surgery only without adjuvant chemotherapy. Regions were segmented based on pancytokeratin staining. The general linear model was used for statistical analysis of differential expression with recurrence free survival (RFS) as a categorical variable (recur yes or no). Kaplan-Meier estimates and Cox regression models were also used for analysis. Results: In the FinXX trial, using global gene expression analysis with IO360, there was no signature significantly associated with RFS. However, using DSP, high protein expression of CD56 in the tumor-enriched segments was associated with significant improvement in RFS (HR 0.26, 95%CI 0.09-0.78, p 0.01). Nevertheless, CD56 expression in the stroma (HR 0.66, 95%CI 0.29-1.53, p 0.33) and all segments (HR 0.53, 95%CI 0.23-1.25, p 0.14) was not significantly associated with improved outcome. We further validated these findings in the MC TNBC cohort where intratumoral CD56 expression was associated with a significant improvement in RFS (HR 0.23, p 0.002) but not stromal CD56 (p 0.79). Interestingly, when evaluating the MC TNBC cohort according to receipt of chemotherapy, intratumoral CD56 was associated with improved outcome only in patients who received chemotherapy (p 0.02 vs. 0.07). In both cohorts, higher expressions of intratumoral PD-L1, HLA-DR, and CD8 were associated with improved outcome. Conclusions: Using an in-depth analysis with spatially defined context, we identify that intratumoral CD56-positive NK cells are associated with improved outcome in TNBC. Our study highlights the potential role of NK cells in TNBC and future implications for biomarkers and therapeutic targets.Support: W81XWH-15-1-0292, P50CA116201-9, P50CA015083. Clinical trial information: NCT00114816 .

Antitumor activity of Z-endoxifen in aromatase inhibitor-sensitive and aromatase inhibitor-resistant estrogen receptor-positive breast cancer

BACKGROUND

The tamoxifen metabolite, Z-endoxifen, demonstrated promising antitumor activity in endocrine-resistant estrogen receptor-positive (ER+) breast cancer. We compared the antitumor activity of Z-endoxifen with tamoxifen and letrozole in the letrozole-sensitive MCF7 aromatase expressing model (MCF7AC1), as well as with tamoxifen, fulvestrant, exemestane, and exemestane plus everolimus in a letrozole-resistant MCF7 model (MCF7LR).

METHODS

MCF7AC1 tumor-bearing mice were randomized to control (no drug), letrozole (10 μg/day), tamoxifen (500 μg/day), or Z-endoxifen (25 and 75 mg/kg). Treatment in the letrozole arm was continued until resistance developed. MCF7LR tumor-bearing mice were then randomized to Z-endoxifen (50 mg/kg) or tamoxifen for 4 weeks and tumors harvested for microarray and immunohistochemistry analysis. The antitumor activity of Z-endoxifen in the MCF7LR tumors was further compared in a second in vivo study with exemestane, exemestane plus everolimus, and fulvestrant.

RESULTS

In the MCF7AC1 tumors, both Z-endoxifen doses were significantly superior to control and tamoxifen in reducing tumor volumes at 4 weeks. Additionally, the 75 mg/kg Z-endoxifen dose was additionally superior to letrozole. Prolonged letrozole exposure resulted in resistance at 25 weeks. In MCF7LR tumor-bearing mice, Z-endoxifen significantly reduced tumor volumes compared to tamoxifen, letrozole, and exemestane, with no significant differences compared to exemestane plus everolimus and fulvestrant. Additionally, compared to tamoxifen, Z-endoxifen markedly inhibited ERα target genes, Ki67 and Akt expression in vivo.

CONCLUSION

In endocrine-sensitive and letrozole-resistant breast tumors, Z-endoxifen results in robust antitumor and antiestrogenic activity compared to tamoxifen and aromatase inhibitor monotherapy. These data support the ongoing development of Z-endoxifen.

Anastrozole has an Association between Degree of Estrogen Suppression and Outcomes in Early Breast Cancer and is a Ligand for Estrogen Receptor α

PURPOSE

To determine if the degree of estrogen suppression with aromatase inhibitors (AI: anastrozole, exemestane, letrozole) is associated with efficacy in early-stage breast cancer, and to examine for differences in the mechanism of action between the three AIs.

EXPERIMENTAL DESIGN

Matched case-control studies [247 matched sets from MA.27 (anastrozole vs. exemestane) and PreFace (letrozole) trials] were undertaken to assess whether estrone (E1) or estradiol (E2) concentrations after 6 months of adjuvant therapy were associated with risk of an early breast cancer event (EBCE). Preclinical laboratory studies included luciferase activity, cell proliferation, radio-labeled ligand estrogen receptor binding, surface plasmon resonance ligand receptor binding, and nuclear magnetic resonance assays.

RESULTS

Women with E1 ≥1.3 pg/mL and E2 ≥0.5 pg/mL after 6 months of AI treatment had a 2.2-fold increase in risk (P = 0.0005) of an EBCE, and in the anastrozole subgroup, the increase in risk of an EBCE was 3.0-fold (P = 0.001). Preclinical laboratory studies examined mechanisms of action in addition to aromatase inhibition and showed that only anastrozole could directly bind to estrogen receptor α (ERα), activate estrogen response element-dependent transcription, and stimulate growth of an aromatase-deficient CYP19A1^-/- T47D breast cancer cell line.

CONCLUSIONS

This matched case-control clinical study revealed that levels of estrone and estradiol above identified thresholds after 6 months of adjuvant anastrozole treatment were associated with increased risk of an EBCE. Preclinical laboratory studies revealed that anastrozole, but not exemestane or letrozole, is a ligand for ERα. These findings represent potential steps towards individualized anastrozole therapy.

Abstract P4-09-03: Phenotypes of breast tumor cells and normal lymphocytes are determined by the integration of minor changes in expression of multiple genes: A new dimension in quantitative inheritance

Breast tumors develop under environmental pressures with phenotypically variant cells generated by mutation and epigenetic changes providing the substrate for clonal selection. Chromosomal mutations are a feature of spontaneous breast tumors in the BALB-neuT mouse model. However, there is little evidence that specific changes in chromosomal structure or ploidy confer selective advantage in these spontaneous tumors. The prominent exception is a consistent loss of chromosome 4, a little understood feature common to several mouse tumors. We previously measured heterozygosity in spontaneous breast tumors from FVB X BALB-neuT F1 mice using Illumina’s Golden Gate assay. In addition to the expected gain and loss of heterozygosity (LOH) evident throughout the genomes of a cohort of spontaneous tumors, the assay also detected wide-spread stochastic pseudo-“LOH” at 600 discrete loci spread throughout the genome in unique patterns among the tumors. Several of these positions were examined by sequence analysis revealing no deviations from the WT sequences, suggesting the detected “LOH” may have been generated by epigenetic modification of DNA which altered sequence detection. While, epigenetically modified DNA templates recapitulated the observed “LOH” signals, no canonical CpG motifs were present in the majority of the 600 loci probed, suggesting that an unusual DNA modification could be responsible for the unexpected wide-spread stochastic structural changes in the breast tumor DNA. We next assessed whether these putative epigenetic changes in DNA structure might impact gene regulation, and have reported that the stochastic pattern observed as “LOH” in DNA was recapitulated in the transcriptomes in unique patterns among the tumors. A direct correlation between the number of “LOH” variants and the down regulation of hundreds of non-polymorphic genes in the transcriptome also was noted. Furthermore, pathway analyses of the genes exhibiting changes in allelic ratios in these tumors revealed significant enrichments within gene networks regulating tissue homeostasis and antigen presentation, providing strong evidence that the perturbations in gene expression translated into selectable tumor cell phenotypes. We now have extended this study to examine the relationship between the magnitude of change in the expression of genes mapping within the pathways regulating tissue homeostasis (Molecular Mechanisms of Cancer). A remarkable feature of the flagged genes is that the magnitude of change in gene expression was not great in each case, yet the biological consequences were strongly reflected in the evolutionary history of the tumors. Importantly, the polymorphisms marking the parental alleles are mostly silent, not altering the structure of the encoded products. Therefore magnitude and timing of gene expression are the likely determinants of phenotypic variation. Each tumor contained several outliers within the pathways regulating tissue homeostasis, suggesting that the integration of multiple small perturbations in the expression of genes comprising functional networks could influence the biology properties of the tumor cells. Overall expression of the loci marked by allelic outliers was significantly below the average expression found among tumors in the cohort highlighting the importance of down regulation of one allele in the establishment of selectable traits. We find a similar direct correlation of multiple small changes in the transcriptome of normal lymphocytes with immune response phenotypes, suggesting this principle of integration of multiple small deviations in gene expression applies widely to the phenotypes of normal cells, tumors, and by extension to organismic traits.

Citation Format: Larry R Pease, Sara J Felts, Adam D Scheid, Xiaojia Tang, Krishna R Kalari. Phenotypes of breast tumor cells and normal lymphocytes are determined by the integration of minor changes in expression of multiple genes: A new dimension in quantitative inheritance [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-09-03.

Abstract P5-04-09: Deep phenotyping using CyTOF identifies peripheral blood immune signatures associated with clinical outcomes and molecular subtypes in patients with early-stage triple negative breast cancer (TNBC)

Background: Local antitumor immunity—as assessed by quantifying tumor-infiltrating immune cells—is increasingly recognized as a critical factor influencing prognosis and therapy response in TNBC. However, an understanding of systemic antitumor immune responses occurring in peripheral blood, and their influence on prognosis and chemotherapy response has not been rigorously studied.

Methods: Cytometry by time-of-flight (CyTOFTM, Fluidigm) was used to examine viably cryopreserved peripheral blood mononuclear cell (PBMC) suspensions prospectively collected from patients with early-stage TNBC prior to initiation of standard neoadjuvant paclitaxel followed by doxorubicin and cyclophosphamide (NACT) as part of the BEAUTY study [1]. Samples were stained using a panel of metal-tagged antibodies, recognizing 30 surface proteins optimized for immune monitoring of human peripheral blood. Differential abundance analysis of immune cell subsets was carried out to evaluate differences between patients who achieved pCR versus those with residual disease after NACT, and between patients with known luminal androgen receptor (LAR) versus basal TNBC subtypes defined by bulk tumor RNA sequencing.

Results: Viably cryopreserved PBMC samples from 40 treatment-naive TNBC patients were available for analysis. The median age was 52 years (range 32 - 73), with 6 (15%) patients having tumors classified as LAR TNBC, and the remaining 34 (85%) as basal TNBC. Overall, 21 (53%) patients achieved pCR after NACT. After acquisition on the mass cytometer, the median yield per sample was 626,815 single-cell events (range 42,786 - 1,035,575), with a median percent debris of 13.7% (range 14 - 58). Across the 40 PBMC samples, the total yield was 23,507,094 single-cell events. The median frequencies of major circulating immune cell subsets across the 40 TNBC patients were: T cells 53.9% (range 25.4 - 71.3), with 33.4% CD4+ T cells (range 11.4 - 46.7) and 10.3% CD8+ T cells (range 5.8 - 19.9); B cells 10.8% (3.3 - 32.6), NK cells 8.6% (1.7 - 17.0) and monocytes 10.6% (2.7 - 29.8). Examining pre-treatment blood samples, patients with residual disease after NACT exhibited a higher median frequency of baseline CD14+CD16- classical monocytes (7.5% vs. 4.1%, p=0.025) and a lower frequency of terminally-differentiated effector memory cytotoxic (CD8+) T cells (0.6% vs. 1.7%, p=0.038) compared to patients who achieved pCR. Patients with LAR TNBC also exhibited a higher frequency of CD14+CD16- classical monocytes (11.5% vs 4.3%, p=0.058), and in addition exhibited a lower frequency of central memory CD4+ T cells (10.4% vs 15.2%, p=0.048). No difference in CD8+ T cells was seen by LAR status. Additional associations of peripheral blood immune cell subsets and classic tumor pathological features will be presented at the meeting.

Conclusion: To our knowledge, this is the first study focused on TNBC to demonstrate variation in peripheral blood immune cell populations by molecular TNBC subtype (LAR vs. basal), and by chemotherapy response. A higher frequency of circulating classical monocytes—which can infiltrate into tissues and give rise to macrophages—appears to be detrimental; whereas a higher frequency of circulating antigen-experienced memory CD8+ T cells seems to be protective, suggesting a putative role of this cell subset in TNBC anti-tumoral immunity.

Reference: [1] Goetz MP et al. JNCI 2017, PMID:28376176

Citation Format: Roberto A Leon-Ferre, Kaitlyn McGrath, Jodi M Carter, Krishna R Kalari, Vera J Suman, Richard Weinshilboum, Liewei Wang, Keith L Knutson, Stephen M Ansell, Judy C Boughey, J C Villasboas, Matthew P Goetz. Deep phenotyping using CyTOF identifies peripheral blood immune signatures associated with clinical outcomes and molecular subtypes in patients with early-stage triple negative breast cancer (TNBC) [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-04-09.

Abstract P2-11-07: Comprehensive tumor sequencing to identify biomarkers of palbociclib response: First report of the PROMISE study

Background: The combination of cyclin dependent 4/6 kinase inhibitors (CDK4/6i) with endocrine therapy (ET) has resulted in clinically significant improvements in progression-free survival (PFS) and overall survival (OS) in hormone-receptor (HR)-positive metastatic breast cancer (MBC). However, most patients’ disease ultimately progresses on CDK4/6i and ET. Therefore, further research is necessary to understand the mechanisms driving primary and secondary resistance. PROMISE is a multicenter prospective cohort study enrolling women with HR-positive MBC commencing treatment with palbociclib + letrozole (1st line) or palbociclib + fulvestrant (2nd Line). The study provides a comprehensive “omic” assessment of blood, tumor, urine and the fecal microbiome to identify molecular or cellular features associated with primary endocrine resistance (e.g. disease progression ≤ 12 months on treatment) and acquired resistance to CDK 4/6i. Additionally, patient derived xenografts and organoids are created to test new drug strategies designed to overcome resistance to CDK 4/6i and ET. Here, we present initial sequencing results from pretreatment biospecimens collected from PROMISE study participants. Methods: On-study tumor biopsies and blood samples were collected for DNA/RNA sequencing (TempusTM). The analyzed biospecimens were all obtained prior to initiation of palbociclib and ET. We correlated patient clinical characteristics (phenotypes) with molecular data and responses to protocol treatment. The data were analyzed using a series of cutting-edge bioinformatics pipelines for somatic and germline mutations in addition to copy number alterations (CNAs). The study database was locked for analysis on 06/20/2019. Results: We analyzed the somatic single nucleotide variants/INDELs (sSNV/INDEL) profiles across the tumor samples to determine the genes that were least likely to occur as a result of background mutation processes. Twenty-six patients had somatic copy number alterations (sCNA) and/or sSNV/INDEL in at least one of 18 genes with the most significant sSNV/INDEL profiles (p < 0.03) which included clinically and biologically relevant genes. The genes with the most statistically significant sSNV/INDEL mutation profiles were GATA3, PIK3CA, CDH1, and ESR1 (p < 0.0009). We observed a high percentage of tumors with somatic alterations in GATA3 (23% sSNV/INDEL, 15% sCNA), PIK3CA (38%, 12%), CDH1 (19%, 50%) and ESR1 (19%, 58%). ESR1 mutations were more frequent in patients receiving 2nd line treatment. Other frequently altered genes included TP53 (15%, 46%), MAP2K4 (8%, 50%), DNAAF1 (8%, 50%), and CDKN1B (8%, 35%). Further, ZNF317 and F3 were altered in 9 and 7 patients, respectively. Twenty-four samples had alterations in at least one of the CDK4/6 pathway genes (RB1, CCNE2, CCND1, CDK6, ESR1, CDKN2A, CCND3, CDK4, CDK2 and CCNE1). Four patients progressed on therapy; three of the four patients had mutations in PIK3CA, and one had a mutation in ESR1. Results of the RNA sequencing data (N=26) will be presented at the SABCS meeting. Conclusions: This is the first report of a prospective study designed to characterize the genomic landscape of ER+/HER2- MBC prior to palbociclib treatment. We observed high frequencies of known targetable alterations in PIK3CA and ESR1, including in patients that progress, which is consistent with previous reports. RNA sequencing data will be presented at the meeting.

Citation Format: Ciara C O Sullivan, Krishna R Kalari, Vera J Suman, Peter T Vedell, Ann Moyer, Erin Carlson, Jason Sinnwell, Tejaswi Alaparthi, Xiaojia Tang, Kevin Thompson, Jaeyun Sung, Alvaro Moreno-Aspitia, Donald Northfelt, Minetta C Liu, Tufia C Haddad, Prema Peethambaram, Saranya Chumsri, Kathryn J Ruddy, Karthik V Giridhar, Roberto A Leon-Ferre, Paula Gill, Mohammad Ranginwala, Asad Javed, Sameer Batoo, Brendan P. McMenomy, Richard Weinshilboum, Liewei Wang, Matthew P Goetz. Comprehensive tumor sequencing to identify biomarkers of palbociclib response: First report of the PROMISE study [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-11-07.

Folate receptor alpha expression associates with improved disease-free survival in triple negative breast cancer patients

Triple negative breast cancer (TNBC) comprises 15-20% of all invasive breast cancer and is associated with a poor prognosis. As therapy options are limited for this subtype, there is a significant need to identify new targeted approaches for TNBC patient management. The expression of the folate receptor alpha (FRα) is significantly increased in patients with TNBC and is therefore a potential biomarker and therapeutic target. We optimized and validated a FRα immunohistochemistry method, specific to TNBC, to measure FRα expression in a centrally confirmed cohort of 384 patients with TNBC in order to determine if expression of the protein is associated with invasive disease-free survival (IDFS) and overall survival (OS). The FRα IHC demonstrated exceptional performance characteristics with low intra- and interassay variability as well as minimal lot-to-lot variation. FRα expression, which varied widely from sample to sample, was detected in 274 (71%) of the TNBC lesions. In a multivariable model adjusted for baseline characteristics, FRα expression was associated with improved IDFS (HR = 0.63, p = 0.01) but not with OS. The results demonstrate the potential of targeting the FRα in the majority of TNBC patients and suggest that variable expression may point to a need to stratify on FRα expression in clinical studies.

Knowledge-guided analysis of "omics" data using the KnowEnG cloud platform

We present Knowledge Engine for Genomics (KnowEnG), a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis, and expression signature analysis. The system specializes in "knowledge-guided" data mining and machine learning algorithms, in which user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge bases and encoded in a massive "Knowledge Network." KnowEnG adheres to "FAIR" principles (findable, accessible, interoperable, and reuseable): its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution, and are interoperable with other computing platforms. The analysis tools are made available through multiple access modes, including a web portal with specialized visualization modules. We demonstrate the KnowEnG system's potential value in democratization of advanced tools for the modern genomics era through several case studies that use its tools to recreate and expand upon the published analysis of cancer data sets.

PANOPLY: Omics-Guided Drug Prioritization Method Tailored to an Individual Patient

PURPOSE

The majority of patients with cancer receive treatments that are minimally informed by omics data. We propose a precision medicine computational framework, PANOPLY (Precision Cancer Genomic Report: Single Sample Inventory), to identify and prioritize drug targets and cancer therapy regimens.

MATERIALS AND METHODS

The PANOPLY approach integrates clinical data with germline and somatic features obtained from multiomics platforms and applies machine learning and network analysis approaches in the context of the individual patient and matched controls. The PANOPLY workflow uses the following four steps: selection of matched controls to the patient of interest; identification of patient-specific genomic events; identification of suitable drugs using the driver-gene network and random forest analyses; and provision of an integrated multiomics case report of the patient with prioritization of anticancer drugs.

RESULTS

The PANOPLY workflow can be executed on a stand-alone virtual machine and is also available for download as an R package. We applied the method to an institutional breast cancer neoadjuvant chemotherapy study that collected clinical and genomic data as well as patient-derived xenografts to investigate the prioritization offered by PANOPLY. In a chemotherapy-resistant patient-derived xenograft model, we found that that the prioritized drug, olaparib, was more effective than placebo in treating the tumor ( P < .05). We also applied PANOPLY to in-house and publicly accessible multiomics tumor data sets with therapeutic response or survival data available.

CONCLUSION

PANOPLY shows promise as a means to prioritize drugs on the basis of clinical and multiomics data for an individual patient with cancer. Additional studies are needed to confirm this approach.

A Transcriptionally Definable Subgroup of Triple-Negative Breast and Ovarian Cancer Samples Shows Sensitivity to HSP90 Inhibition

PURPOSE

We hypothesized that integrated analysis of cancer types from different lineages would reveal novel molecularly defined subgroups with unique therapeutic vulnerabilities. On the basis of the molecular similarities between subgroups of breast and ovarian cancers, we analyzed these cancers as a single cohort to test our hypothesis.

EXPERIMENTAL DESIGN

Identification of transcriptional subgroups of cancers and drug sensitivity analyses were performed using mined data. Cell line sensitivity to Hsp90 inhibitors (Hsp90i) was tested in vitro. The ability of a transcriptional signature to predict Hsp90i sensitivity was validated using cell lines, and cell line- and patient-derived xenograft (PDX) models. Mechanisms of Hsp90i sensitivity were uncovered using immunoblot and RNAi.

RESULTS

Transcriptomic analyses of breast and ovarian cancer cell lines uncovered two mixed subgroups comprised primarily of triple-negative breast and multiple ovarian cancer subtypes. Drug sensitivity analyses revealed that cells of one mixed subgroup are significantly more sensitive to Hsp90i compared with cells from all other cancer lineages evaluated. A gene expression classifier was generated that predicted Hsp90i sensitivity in vitro, and in cell line- and PDXs. Cells from the Hsp90i-sensitive subgroup underwent apoptosis mediated by Hsp90i-induced upregulation of the proapoptotic proteins Bim and PUMA.

CONCLUSIONS

Our findings identify Hsp90i as a potential therapeutic strategy for a transcriptionally defined subgroup of ovarian and breast cancers. This study demonstrates that gene expression profiles may be useful to identify therapeutic vulnerabilities in tumor types with limited targetable genetic alterations, and to identify molecularly definable cancer subgroups that transcend lineage.

Isoform-level gene expression patterns in single-cell RNA-sequencing data

Motivation

RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have focus on characterization of isoform-level expression patterns at the single-cell level. In this study, we propose and apply a novel method, ISOform-Patterns (ISOP), based on mixture modeling, to characterize the expression patterns of isoform pairs from the same gene in single-cell isoform-level expression data.

Results

We define six principal patterns of isoform expression relationships and describe a method for differential-pattern analysis. We demonstrate ISOP through analysis of single-cell RNA-sequencing data from a breast cancer cell line, with replication in three independent datasets. We assigned the pattern types to each of 16 562 isoform-pairs from 4929 genes. Among those, 26% of the discovered patterns were significant (P<0.05), while remaining patterns are possibly effects of transcriptional bursting, drop-out and stochastic biological heterogeneity. Furthermore, 32% of genes discovered through differential-pattern analysis were not detected by differential-expression analysis. Finally, the effects of drop-out events and expression levels of isoforms on ISOP's performances were investigated through simulated datasets. To conclude, ISOP provides a novel approach for characterization of isoform-level preference, commitment and heterogeneity in single-cell RNA-sequencing data.

Availability and implementation

The ISOP method has been implemented as a R package and is available at https://github.com/nghiavtr/ISOP under a GPL-3 license.

Supplementary information

Supplementary data are available at Bioinformatics online.

Alternating EM algorithm for a bilinear model in isoform quantification from RNA-seq data

MOTIVATION

Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform read distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide bias correction step(s), which is based on biological considerations-such as GC content-and applied in single samples separately. The main problem is that not all biases are known.

RESULTS

We have developed a novel method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and is computed based on the simplifying assumptions. In contrast XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by a simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. We use an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes. In a differential-expression analysis of a real single-cell RNA-seq dataset, XAEM achieves substantially better rediscovery rates in independent validation sets.

AVAILABILITY AND IMPLEMENTATION

The method and pipeline are implemented as a tool and freely available for use at http://fafner.meb.ki.se/biostatwiki/xaem/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Gene Expression and Missplicing in the Corneal Endothelium of Patients With a TCF4 Trinucleotide Repeat Expansion Without Fuchs' Endothelial Corneal Dystrophy

Purpose

CTG trinucleotide repeat (TNR) expansion in an intron of the TCF4 gene is the most common genetic variant associated with Fuchs' endothelial corneal dystrophy (FECD). Although several mechanisms have been implicated in the disease process, their exact pathophysiologic importance is unclear. To understand events leading from TCF4 TNR expansion to disease phenotype, we characterized splicing, gene expression, and exon sequence changes in a rare cohort of patients with TNR expansions but no phenotypic FECD (RE+/FECD-).

Methods

Corneal endothelium and blood were collected from patients undergoing endothelial keratoplasty for non-FECD corneal edema. Total RNA was isolated from corneal endothelial tissue (n = 3) and used for RNASeq. Gene splicing and expression was assessed by Mixture of Isoforms (MISO) and MAP-RSeq software. Genomic DNA was isolated from blood mononuclear cells and used for whole genome exome sequencing. Base calling was performed using Illumina's Real-Time Analysis.

Results

Three genes (MBNL1, KIF13A, AKAP13) that were previously identified as misspliced in patients with a CTG TNR expansion and FECD disease (RE+/FECD+) were found normally spliced in RE+/FECD- samples. Gene expression differences in pathways associated with the innate immune response, cell signaling (e.g., TGFβ, WNT), and cell senescence markers were also identified between RE+/FECD- and RE+/FECD+ groups. No consistent genetic variants were identified in RE+/FECD- patient exomes.

Conclusions

Identification of novel splicing patterns and differential gene expression in RE+/FECD- samples provides new insights and more relevant gene targets that may be protective against FECD disease in vulnerable patients with TCF4 CTG TNR expansions.

Abstract 2898: Stochastic variation in gene expression is selected during clonal evolution of spontaneous mouse mammary tumors

Molecular and cellular diversity in cancer cells enables evolutionary processes that govern tumor progression and contributes to treatment failures, but the mechanisms governing this variability remain incompletely understood. We previously described tumor-specific epigenetic alterations in DNA devoid of canonical CpG methylation sites throughout the genomes of spontaneous breast tumors which arise in genetically uniform, yet heterozygous, [FVB X BALB/c MMTV-NeuT+] F1 mice. Those changes were detected in purified tumor DNA using a template-assisted quantitative ligation assay employing locus-specific and SNP-specific oligonucleotide genotyping probes, and the assay was subsequently shown to be sensitive to epigenetic modifications of the templates. We now describe losses of heterozygosity similarly distributed throughout the transcriptomes of tumors in this same model. We quantified expressed alleles across a population of clonal tumors and tested each expressed variant for the occurrence of allelic ratio outliers. The results revealed variegated patterns of expression in hundreds of genes, highly significantly enriched in pathways typically co-opted by tumors (Molecular Mechanisms of Cancer, P &lt; 10-10, IPA analysis). An astounding 87% (2634 of 3044) of expressed genes that could be measured using this approach were represented in at least one tumor. Furthermore, the frequency of these outliers in any one individual tumor was found to correlate strongly with the transcriptional repression of an additional large set of non-polymorphic genes. These findings reveal underappreciated, latent mechanisms driving sporadic errors in epigenetic programming that promote repression of a multiple cis-linked transcripts. This genome-wide molecular chaos presents as dysregulated cellular homeostasis and is the foundation for heritable diversity as tumors evolve.

Citation Format: Sara J. Felts, Xiaojia Tang, Virginia P. Van Keulen, Krishna R. Kalari, Larry R. Pease. Stochastic variation in gene expression is selected during clonal evolution of spontaneous mouse mammary tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2898.

Stochastic changes in gene expression promote chaotic dysregulation of homeostasis in clonal breast tumors

Cells within tumors vary in phenotype as a result of changes in gene expression caused by a variety of mechanisms, permitting cancers to evolve under selective pressures from immune and other homeostatic processes. Earlier, we traced apparent losses in heterozygosity (LOH) of spontaneous breast tumors from first generation (F1) intercrossed mice to atypical epigenetic modifications in the structure of DNA across the tumor genomes. Here, we describe a parallel pattern of LOH in gene expression, revealed through quantitation of parental alleles across a population of clonal tumors. We found variegated patterns of LOH, based on allelic ratio outliers in hundreds of genes, enriched in regulatory pathways typically co-opted by tumors. The frequency of outliers was correlated with transcriptional repression of a large set of homozygous genes. These findings suggest stochastic losses in gene expression across the genome of tumors generate phenotypic variation among cells, allowing clonal selection during tumor development.

Evolution of androgen receptor variant (ARV) profiles in serial metastatic solid and liquid biopsies in metastatic castrate resistant prostate cancer (mCRPC) treated with abiraterone acetate/ prednisone (AA/P)

e16559

Background: ARVs that develop early during treatment with abiraterone acetate/ prednisone (AA/P) may play a role in treatment resistance. We evaluated metastatic site and whole blood mRNA expression of full-length AR (AR-FL) and ARVs to characterize treatment-emergent ARVs (TE-ARVs) from men with mCRPC pre- and post- 12 weeks of AA/P collected in a prospective clinical trial (NCT#01953640). Methods: RNAseq performed on paired metastatic site biopsy (n = 40) and whole blood (n = 25) passed quality control. Reads were aligned to the GRCh38 reference genome with the spliced-alignment TopHat2 package. AR-FL or ARVs were detected if ≥ 2 splice reads aligned to unique splice junctions for AR-FL, AR-8, AR-45, AR-23, AR-V3, AR-V5V6, AR-V7, AR-V8, AR-V9, AR-V10, AR-V12, AR-V13, and AR-V14, and normalized to splice reads per million (SRPM). Cox proportional hazard regression analysis was performed on AR-FL and AR-Vs with ≥1 SRPM for association with time to treatment change (TTTC). Results: In metastatic site biopsies post-AA/P, the average number of splice reads was 27,376,541 (range 7,753,998 to 62,456,773). The median number of ARVs detected was 2 (range 0-8), with a total of total of 110 ARVs identified (Table). Dynamic shifts in ARV profiles were observed post-AAP, with 41 TE-ARVs identified in 17 unique patients. The most common TE-ARV was AR-8 (n = 8), followed by AR-45 (n = 5), AR-23 (n = 5), and AR-V7 (n = 4). The presence of AR-V7 post-AAP was adversely associated with TTTC (hazard ratio 2.46, p = 0.013). The identification of early TE- ARV was not associated with TTTC. In whole blood samples, post-AA/P detection of AR-FL was low (n = 3) and no ARVs were detected. Conclusions: No specific patterns were observed in ARV profiles obtained in the metastatic biopsies after 12 weeks of treatment with AA/P. Clinical trial information: 01953640. [Table: see text]

The lncRNA MIR2052HG regulates ERα levels and aromatase inhibitor resistance through LMTK3 by recruiting EGR1

Background

Our previous genome-wide association study using the MA.27 aromatase inhibitors adjuvant trial identified SNPs in the long noncoding RNA MIR2052HG associated with breast cancer-free interval. MIR2052HG maintained ERα both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated ERα degradation. Our goal was to further elucidate MIR2052HG’s mechanism of action.

Methods

RNA-binding protein immunoprecipitation assays were performed to demonstrate that the transcription factor, early growth response protein 1 (EGR1), worked together with MIR2052HG to regulate that lemur tyrosine kinase-3 (LMTK3) transcription in MCF7/AC1 and CAMA-1 cells. The location of EGR1 on the LMTK3 gene locus was mapped using chromatin immunoprecipitation assays. The co-localization of MIR2052HG RNA and the LMTK3 gene locus was determined using RNA-DNA dual fluorescent in situ hybridization. Single-nucleotide polymorphisms (SNP) effects were evaluated using a panel of human lymphoblastoid cell lines.

Results

MIR2052HG depletion in breast cancer cells results in a decrease in LMTK3 expression and cell growth. Mechanistically, MIR2052HG interacts with EGR1 and facilitates its recruitment to the LMTK3 promoter. LMTK3 sustains ERα levels by reducing protein kinase C (PKC) activity, resulting in increased ESR1 transcription mediated through AKT/FOXO3 and reduced ERα degradation mediated by the PKC/MEK/ERK/RSK1 pathway. MIR2052HG regulated LMTK3 in a SNP- and aromatase inhibitor-dependent fashion: the variant SNP increased EGR1 binding to LMTK3 promoter in response to androstenedione, relative to wild-type genotype, a pattern that can be reversed by aromatase inhibitor treatment. Finally, LMTK3 overexpression abolished the effect of MIR2052HG on PKC activity and ERα levels.

Conclusions

Our findings support a model in which the MIR2052HG regulates LMTK3 via EGR1, and LMTK3 regulates ERα stability via the PKC/MEK/ERK/RSK1 axis. These results reveal a direct role of MIR2052HG in LMTK3 regulation and raise the possibilities of targeting MIR2052HG or LMTK3 in ERα-positive breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1130-3) contains supplementary material, which is available to authorized users.

A prospective genome-wide study of prostate cancer metastases reveals association of wnt pathway activation and increased cell cycle proliferation with primary resistance to abiraterone acetate-prednisone

Background

Genomic aberrations have been identified in metastatic castration-resistant prostate cancer (mCRPC), but molecular predictors of resistance to abiraterone acetate/prednisone (AA/P) treatment are not known.

Patients and methods

In a prospective clinical trial, mCRPC patients underwent whole-exome sequencing (n = 82) and RNA sequencing (n = 75) of metastatic biopsies before initiating AA/P with the objective of identifying genomic alterations associated with resistance to AA/P. Primary resistance was determined at 12 weeks of treatment using criteria for progression that included serum prostate-specific antigen measurement, bone and computerized tomography imaging and symptom assessments. Acquired resistance was determined using the end point of time to treatment change (TTTC), defined as time from enrollment until change in treatment from progressive disease. Associations of genomic and transcriptomic alterations with primary resistance were determined using logistic regression, Fisher's exact test, single and multivariate analyses. Cox regression models were utilized for determining association of genomic and transcriptomic alterations with TTTC.

Results

At 12 weeks, 32 patients in the cohort had progressed (nonresponders). Median study follow-up was 32.1 months by which time 58 patients had switched treatments due to progression. Median TTTC was 10.1 months (interquartile range: 4.4-24.1). Genes in the Wnt/β-catenin pathway were more frequently mutated and negative regulators of Wnt/β-catenin signaling were more frequently deleted or displayed reduced mRNA expression in nonresponders. Additionally, mRNA expression of cell cycle regulatory genes was increased in nonresponders. In multivariate models, increased cell cycle proliferation scores (≥ 50) were associated with shorter TTTC (hazard ratio = 2.11, 95% confidence interval: 1.17-3.80; P = 0.01).

Conclusions

Wnt/β-catenin pathway activation and increased cell cycle progression scores can serve as molecular markers for predicting resistance to AA/P therapy.

Anastrozole Aromatase Inhibitor Plasma Drug Concentration Genome-Wide Association Study: Functional Epistatic Interaction Between SLC38A7 and ALPPL2

Anastrozole is a widely prescribed aromatase inhibitor for the therapy of estrogen receptor positive (ER+) breast cancer. We performed a genome‐wide association study (GWAS) for plasma anastrozole concentrations in 687 postmenopausal women with ER+ breast cancer. The top single‐nucleotide polymorphism (SNP) signal mapped across SLC38A7 (rs11648166, P = 2.3E‐08), which we showed to encode an anastrozole influx transporter. The second most significant signal (rs28845026, P = 5.4E‐08) mapped near ALPPL2 and displayed epistasis with the SLC38A7 signal. Both of these SNPs were cis expression quantitative trait loci (eQTL)s for these genes, and patients homozygous for variant genotypes for both SNPs had the highest drug concentrations, the highest SLC38A7 expression, and the lowest ALPPL2 expression. In summary, our GWAS identified a novel gene encoding an anastrozole transporter, SLC38A7, as well as epistatic interaction between SNPs in that gene and SNPs near ALPPL2 that influenced both the expression of the transporter and anastrozole plasma concentrations.

Abstract P3-08-01: Characteristics, outcomes and prognostic factors of luminal androgen receptor (LAR) triple-negative breast cancer (TNBC)

Background: The LAR subtype is a genomically distinct subset of TNBC. Using a large cohort of non-metastatic TNBC patients (pts) with long term follow-up, we sought to further characterize the clinicopathologic features and outcomes of LAR vs non-LAR TNBC.

Methods: From a cohort of 9982 women with surgically-treated non-metastatic breast cancer, 605 met criteria for TNBC (ER/PR&lt;1% and HER2-negative) by central pathology. RNA extracted from 304 FFPE tumor specimens using the HighPure RNA extraction kit was subjected to TruSeq RNA Access library preparation and sequencing on a HiSeq2500. Adequate RNA was available for 283 pts. Tumors were classified as LAR or non-LAR using a shrunken centroid model, CABAL (Clustering Among BAsal and Luminal androgen receptor). In addition to previously described analyses [Leon-Ferre et al, Breast Cancer Res Treat 2017], immunohistochemical (IHC) androgen receptor (AR) staining was performed and the impact of various parameters on invasive disease-free survival (IDFS) and overall survival (OS) was assessed using Cox proportional hazards models.

Results: 58 (20%) tumors were classified as LAR and 225 (80%) as non-LAR. Compared to non-LAR, LAR pts were older (mean age 65 vs 54) and more often postmenopausal (79%vs53%), both p=0.01. Apocrine histology was more common among LAR tumors (21%vs0%), which were also lower grade (grade3: 69%vs95%) and had lower Ki-67 (Ki-67&gt;15%: 64%vs82%), all p&lt;0.01. Additionally, LAR tumors had lower median stromal tumor infiltrating lymphocytes (TILs, 20%vs25%) and were less frequently lymphocyte-predominant [≥50% stromal or intratumoral TILs (19%vs32%)], although neither reached statistical significance. AR IHC was available for 223 of 283 tumors. Median AR IHC score in LAR was 65% (range 0-100%) vs 0% (range 0-90%) in non-LAR. T/N stage, surgery type, and receipt of adjuvant chemotherapy (AdjCT) or radiotherapy were similar between LAR and non-LAR. LAR pts had shorter IDFS and OS compared to non-LAR (5.6 vs 11.8 yrs and 10.8 vs 20.8 yrs, respectively), although this did not reach statistical significance. Test of proportional hazard assumption was not significant for IDFS or OS (p = 0.30 and 0.09). IDFS estimates were numerically higher in LAR vs non-LAR (80.2%vs70.5%,p = 0.92) at 3yrs post-diagnosis; whereas the opposite was true (40.9%vs55.6%,p = 0.07) after 10yrs. OS estimates at 3 and 5yrs were similar between LAR and non-LAR, but at 10yrs OS was inferior in LAR (40.9%vs66.4%,p = 0.24). In a univariate analysis including both LAR and non-LAR, older age, higher N stage, lower TILs and absence of AdjCT were associated with poorer IDFS and OS. In a multivariate analysis, higher N stage and absence of AdjCT remained associated with both poorer IDFS and OS; while lower stromal TILs were associated with poorer IDFS (p=0.01), and with a trend towards poorer OS (p=0.07).

Conclusions: LAR TNBCs occurred in older women, were lower grade, and had lower TIL density than nonLAR tumors. While significant differences in IDFS or OS were not demonstrated, LAR pts exhibited a numerically lower risk of a disease event at 3yrs, but higher risk by 10yrs compared to nonLAR pts. In the entire cohort, higher N stage, absence of AdjCT and lower TILs were independently associated with poorer outcomes.

Citation Format: Leon-Ferre RA, Polley M-Y, Liu H, Kalari KR, Boughey JC, Liu MC, Cafourek V, Negron V, Ingle JN, Thompson KJ, Tang X, Barman P, Carlson E, Visscher DW, Carter JC, Couch FJ, Goetz MP. Characteristics, outcomes and prognostic factors of luminal androgen receptor (LAR) triple-negative breast cancer (TNBC) [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-08-01.

Abstract P1-03-04: Molecular subtyping of androgen receptor-positive patients using gene expression profiles

Breast cancer is a heterogeneous disease, and unsupervised clustering approaches using gene expression data have identified 3-6 distinct subtypes of triple negative breast cancer (TNBC). A genomically and clinically distinct subtype of TNBC is referred to as LAR (Luminal Androgen Receptor). Tumors with this subtype typically express high levels of the AR and exhibit alterations within genes involved in the PI3K pathway (e.g. PIK3CA mutations). Prospective studies are underway using drugs that target the AR alone or in combination with PI3K and CDK 4/6 inhibitors. Given the importance of accurately identifying this subtype, we sought to develop an online tool that uses submitted gene expression data to confidently characterize LAR samples by corroborating the classification with previously published clustering approaches.

Methods: We have investigated TNBC RNA-Seq data from The Cancer Genome Atlas (TCGA) breast cancer study (N=123 samples) by cluster analysis. Analysis of the average silhouette width in both biased and unbiased K-means clustering approaches demonstrated LAR and basal as two distinct and significant clusters. A shrunken centroid model of 426 differentially expressed genes, named as CABAL (Clustering Among BAsal and Luminal androgen receptor), was constructed by comparing LAR and basal subtypes.

Results: We applied the CABAL model to classify the four TNBC microarray datasets that were previously used in clustering experiments as well as an independent RNA-Seq data cohort. Non-negative matrix factorization (NMF) and fuzzy clustering were applied to the samples (N=1046). Clustering similarity among the methods was assessed with the adjusted rand index, and CABAL demonstrated significant similarity with both fuzzy and NMF clustering methods. Similarly, hierarchical clustering analysis performed on the pooled cohort of 1046 samples recapitulated the CABAL classification with an area under the receiver operating curve of 0.91.

Conclusions: Confident and robust identification of samples with the LAR phenotype is paramount in the assessment of clinical associations and therapeutic efficacy. To facilitate LAR identification, we have provided a web-based prediction tool of the CABAL classification, integrated with the NMF and fuzzy clustering results to identify candidate LAR samples. The end user is provided with the pair-wise adjusted rand indexes, thus reinforcing in the clustering characterizations. Further, our online LAR depiction tool provides a set of graphical and tabular summaries, which will be illustrated, while providing additional molecular characterizations of the PAM50 and Metabric classifications. The availability of this tool could advance the genomic research and treatment of TNBC patients.

Citation Format: Thompson KJ, Alaparthi T, Sinnwell JP, Carlson EE, Tang X, Bockol M, Vedell PT, Ingle JN, Suman V, Weinshilboum RM, Wang L, Boughey JC, Kalari KR, Goetz MP. Molecular subtyping of androgen receptor-positive patients using gene expression profiles [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P1-03-04.

Abstract P3-06-10: Multiscale modeling of omics data for precision breast cancer treatment

Introduction: The vast majority of cancer patients continue to receive treatments that are minimally informed by omics data. In the case of breast cancer, only ER and HER2 are routinely used for treatment selection. There is a particular need for personalized treatment in individuals with primary and secondary drug resistance or aggressive breast cancers. Emerging bioinformatics and statistical methods have made a fundamental impact on cancer research. However, challenges remains with regard to patient-centric data analysis and providing genomic data guidance to oncologists. There exists a large number of FDA approved anti-neoplastic drugs used to treat cancers other than breast and the development of innovative informatics methods and algorithms to repurpose those drugs should benefit breast cancer patients.

Methods and Results: We have developed precision care systems (such as PANOPLY and CORPUS) to identify personalized therapies for an individual patient and to deliver genomic reports in a standard, searchable format so that a researcher or an oncologist can quickly navigate through molecular data and obtain prioritized drugs and targets.The PANOPLY (Precision cancer genomics report: single sample inventory) algorithm applies machine learning and topology-based network analysis methods to integrate multi-omics profiles and clinical data; individual-specific molecular alterations are identified and compared with a set of matched-controls having similar clinical data. Since there is a lack of a “gold standard” dataset to test such algorithms, we simulated 500 case-control sets and evaluated drug predictions across multiple simulation scenarios. We applied the PANOPLY algorithm to The Cancer Genome Atlas (TCGA) breast cancer cohort, which consists of multi-omics data and clinical data. In addition, PANOPLY was also applied to an in-house neoadjuvant breast cancer study (BEAUTY) that consists of multi-omics data, clinical data, and patient-derived xenografts (PDXs). In the TCGA breast cancer study we obtained survival data to determine the cases and matched-controls; and in the BEAUTY, we used pathologic complete response (pCR) as an outcome to determine responders and non-responders. Recurrent targetable alterations were not enriched in patients without pCR in the BEAUTY study. We have applied the PANOPLY to non-responder patients to identify individual specific alterations, dysregulated networks, drug targets, and drugs for each patient and stored them as case reports in CORPUS (Computational Oncology Reports and Precision therapeUticS), a web-based repository that allows clinicians to review genomic reports. Using comprehensive “omic” data derived from a triple negative breast cancer patient who had pre and post-neoadjuvant chemotherapy PDXs, PANOPLY prioritized the PARP inhibitors as the top class of drug. Using the PDX models available from this patient, we tested olaparib and confirmed the in vivo antitumor activity (more effective than vehicle with a p-value &lt; 0.05 in the PDXs). Further studies to confirm PANOPLY findings are currently underway.

Conclusions: In summary, the PANOPLY and CORPUS systems incorporate molecular data together with clinical data to provide genomic reports with proposed drug targets to advance or enable precision breast cancer care.

Citation Format: Kalari KR, Sinnwell JP, Thompson KJ, Tang X, Carlson EE, Alaparthi T, Yu J, Vedell PT, Kalmbach MT, Bockol MA, Hossain A, Weinshilboum RM, Boughey JC, Wang L, Suman VJ, Goetz MP. Multiscale modeling of omics data for precision breast cancer treatment [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-06-10.

Single Nucleotide Polymorphisms (SNPs) Distant from Xenobiotic Response Elements Can Modulate Aryl Hydrocarbon Receptor Function: SNP-Dependent CYP1A1 Induction

CYP1A1 expression can be upregulated by the ligand-activated aryl hydrocarbon receptor (AHR). Based on prior observations with estrogen receptors and estrogen response elements, we tested the hypothesis that single-nucleotide polymorphisms (SNPs) mapping hundreds of base pairs (bp) from xenobiotic response elements (XREs) might influence AHR binding and subsequent gene expression. Specifically, we analyzed DNA sequences 5 kb upstream and downstream of the CYP1A1 gene for putative XREs. SNPs located ±500 bp of these putative XREs were studied using a genomic data-rich human lymphoblastoid cell line (LCL) model system. CYP1A1 mRNA levels were determined after treatment with varying concentrations of 3-methylcholanthrene (3MC). The rs2470893 (-1694G>A) SNP, located 196 bp from an XRE in the CYP1A1 promoter, was associated with 2-fold variation in AHR-XRE binding in a SNP-dependent fashion. LCLs with the AA genotype displayed significantly higher AHR-XRE binding and CYP1A1 mRNA expression after 3MC treatment than did those with the GG genotype. Electrophoretic mobility shift assay (EMSA) showed that oligonucleotides with the AA genotype displayed higher LCL nuclear extract binding after 3MC treatment than did those with the GG genotype, and mass spectrometric analysis of EMSA protein-DNA complex bands identified three candidate proteins, two of which were co-immunoprecipitated with AHR. In conclusion, we have demonstrated that the rs2470893 SNP, which maps 196 bp from a CYP1A1 promoter XRE, is associated with variations in 3MC-dependent AHR binding and CYP1A1 expression. Similar "distant SNP effects" on AHR binding to an XRE motif and subsequent gene expression might occur for additional AHR-regulated genes.

ATR Inhibition Is a Promising Radiosensitizing Strategy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by elevated locoregional recurrence risk despite aggressive local therapies. New tumor-specific radiosensitizers are needed. We hypothesized that the ATR inhibitor, VX-970 (now known as M6620), would preferentially radiosensitize TNBC. Noncancerous breast epithelial and TNBC cell lines were investigated in clonogenic survival, cell cycle, and DNA damage signaling and repair assays. In addition, patient-derived xenograft (PDX) models generated prospectively as part of a neoadjuvant chemotherapy study from either baseline tumor biopsies or surgical specimens with chemoresistant residual disease were assessed for sensitivity to fractionated radiotherapy, VX-970, or the combination. To explore potential response biomarkers, exome sequencing was assessed for germline and/or somatic alterations in homologous recombination (HR) genes and other alterations associated with ATR inhibitor sensitivity. VX-970 preferentially inhibited ATR-Chk1-CDC25a signaling, abrogated the radiotherapy-induced G₂-M checkpoint, delayed resolution of DNA double-strand breaks, and reduced colony formation after radiotherapy in TNBC cells relative to normal-like breast epithelial cells. In vivo, VX-970 did not exhibit significant single-agent activity at the dose administered even in the context of genomic alterations predictive of ATR inhibitor responsiveness, but significantly sensitized TNBC PDXs to radiotherapy. Exome sequencing and functional testing demonstrated that combination therapy was effective in both HR-proficient and -deficient models. PDXs established from patients with chemoresistant TNBC were also highly radiosensitized. In conclusion, VX-970 is a tumor-specific radiosensitizer for TNBC. Patients with residual TNBC after neoadjuvant chemotherapy, a subset at particularly high risk of relapse, may be ideally suited for this treatment intensification strategy. Mol Cancer Ther; 17(11); 2462-72. ©2018 AACR.

HGT-ID: an efficient and sensitive workflow to detect human-viral insertion sites using next-generation sequencing data

Background

Transfer of genetic material from microbes or viruses into the host genome is known as horizontal gene transfer (HGT). The integration of viruses into the human genome is associated with multiple cancers, and these can now be detected using next-generation sequencing methods such as whole genome sequencing and RNA-sequencing.

Results

We designed a novel computational workflow, HGT-ID, to identify the integration of viruses into the human genome using the sequencing data. The HGT-ID workflow primarily follows a four-step procedure: i) pre-processing of unaligned reads, ii) virus detection using subtraction approach, iii) identification of virus integration site using discordant and soft-clipped reads and iv) HGT candidates prioritization through a scoring function. Annotation and visualization of the events, as well as primer design for experimental validation, are also provided in the final report. We evaluated the tool performance with the well-understood cervical cancer samples. The HGT-ID workflow accurately detected known human papillomavirus (HPV) integration sites with high sensitivity and specificity compared to previous HGT methods. We applied HGT-ID to The Cancer Genome Atlas (TCGA) whole-genome sequencing data (WGS) from liver tumor-normal pairs. Multiple hepatitis B virus (HBV) integration sites were identified in TCGA liver samples and confirmed by HGT-ID using the RNA-Seq data from the matched liver pairs. This shows the applicability of the method in both the data types and cross-validation of the HGT events in liver samples. We also processed 220 breast tumor WGS data through the workflow; however, there were no HGT events detected in those samples.

Conclusions

HGT-ID is a novel computational workflow to detect the integration of viruses in the human genome using the sequencing data. It is fast and accurate with functions such as prioritization, annotation, visualization and primer design for future validation of HGTs. The HGT-ID workflow is released under the MIT License and available at http://kalarikrlab.org/Software/HGT-ID.html.

Machine Learning Helps Identify New Drug Mechanisms in Triple-Negative Breast Cancer

This paper demonstrates the ability of mach- ine learning approaches to identify a few genes among the 23,398 genes of the human genome to experiment on in the laboratory to establish new drug mechanisms. As a case study, this paper uses MDA-MB-231 breast cancer single-cells treated with the antidiabetic drug metformin. We show that mixture-model-based unsupervised methods with validation from hierarchical clustering can identify single-cell subpopulations (clusters). These clusters are characterized by a small set of genes (1% of the genome) that have significant differential expression across the clusters and are also highly correlated with pathways with anticancer effects driven by metformin. Among the identified small set of genes associated with reduced breast cancer incidence, laboratory experiments on one of the genes, CDC42, showed that its downregulation by metformin inhibited cancer cell migration and proliferation, thus validating the ability of machine learning approaches to identify biologically relevant candidates for laboratory experiments. Given the large size of the human genome and limitations in cost and skilled resources, the broader impact of this work in identifying a small set of differentially expressed genes after drug treatment lies in augmenting the drug-disease knowledge of pharmacogenomics experts in laboratory investigations, which could help establish novel biological mechanisms associated with drug response in diseases beyond breast cancer.

Gene expression in the corneal endothelium of Fuchs endothelial corneal dystrophy patients with and without expansion of a trinucleotide repeat in TCF4

Fuchs Endothelial Corneal Dystrophy (FECD) is a late onset, autosomal dominant eye disease that can lead to loss of vision. Expansion of a CTG trinucleotide repeat in the third intron of the transcription factor 4 (TCF4) gene is highly associated with FECD. However, only about 75% of FECD patients in the northern European population possess an expansion of this repeat. The remaining FECD cases appear to be associated with variants in other genes. To better understand the pathophysiology of this disease, we compared gene expression profiles of corneal endothelium from FECD patients with an expanded trinucleotide repeat (RE+) to those that do not have a repeat expansion (RE-). Comparative analysis of these two cohorts showed widespread RNA mis-splicing in RE+, but not in RE- samples. Quantitatively, we identified 39 genes in which expression was significantly different between RE+ and RE- samples. Examination of the mutation profiles in the RE- samples did not find any mutations in genes previously associated with FECD, but did reveal one sample with a rare variant of laminin subunit gamma 1 (LAMC1) and three samples with rare variants in the gene coding for the mitochondrial protein peripheral-type benzodiazepine receptor-associated protein 1 (TSPOAP1).

Abstract 840: ATR inhibition is a promising radiosensitizing strategy for chemotherapy-resistant triple negative breast cancer (TNBC)

Purpose: TNBC represents an aggressive subtype characterized by earlier relapse and worse survival compared to non-TNBC. Patients with residual TNBC after neoadjuvant chemotherapy (NAC) have a high risk of locoregional recurrence despite aggressive subsequent local therapies, including RT. Thus, new radiosensitizers that address chemoresistant TNBC (i.e residual disease after NAC) are needed. ATR plays a key role in the cellular response to replication stress and DNA damage. TNBC is characterized by G1 checkpoint loss, homologous recombination deficiency (HRD), and other features which increase dependence on ATR pathway signaling. We hypothesized that VX-970, a selective inhibitor of ATR, would effectively radiosensitize TNBC.

Methods: Cell lines representing varying subtypes of TNBC (MDA-MB-231, HCC1806, and BT-549) and the normal breast epithelial cell line MCF10a were investigated in clonogenic survival, cell cycle, and DNA damage signaling and repair assays. In addition, Mayo Clinic (MC)TNBC1 and MCTNBC2, patient derived xenograft models (PDXs) generated prospectively from baseline and chemoresistant residual disease surgical specimens after NAC, respectively, of unique patients in the Breast Cancer Genome Guided Therapy Study were analyzed. Tumors were injected into hind-legs of athymic nude mice and animals were randomized to: 1) Vehicle 2) RT 3) VX-970 4) RT + VX-970. RT was delivered in 5 daily fractions of 2 Gy. VX-970 was administered daily 1 hour prior to RT at a dose of 60 mg/kg. Exome sequencing was assessed for germ-line and/or somatic alterations in HR genes and an ex-vivo RAD51 foci formation assay was applied to confirm the functional status of HR in each PDX model.

Results: In vitro, VX-970 preferentially inhibited ATR-Chk1-CDC25a signaling, abrogated the RT-induced G2/M checkpoint, delayed resolution of γH2AX and 53BP1 foci and reduced colony formation after RT in MDA-MB-231, HCC1806, and BT-549 relative to MCF10a. In vivo, VX-970 did not exhibit single agent activity at the dose administered but markedly sensitized both MCTNBC1 and MCTNBC2 to RT, suggesting that VX-970 could overcome chemoresistant TNBC biology. For MCTNBC1 and MCTNBC2, the median time to tumor tripling was 26 vs 49 days (p=0.002) and 25 vs 43 days (p=0.006) for the RT and RT + VX-970 groups, respectively. Ex-vivo RAD51 foci formation was robust in MCTNBC1, a PDX without HR gene alterations. In contrast, there was no RT-induced RAD51 foci formation in MCTNBC2, suggesting a BRCA1 mutation in the corresponding human tumor resulted in loss of HR function in that model.

Conclusion: VX-970 + RT effectively radiosensitized TNBC PDXs established from both pre-treatment biopsy specimens and chemoresistant residual tumor samples and in both HR deficient and HR proficient settings. ATR inhibition should be investigated in the clinic in combination with RT for patients with residual TNBC after NAC.

Citation Format: Robert W. Mutter, Mohamed M. Kahila, Xinyi Tu, Qin Zhou, Jia Yu, Krishna R. Kalari, Liewei Wang, Judy C. Boughey, Matthew P. Goetz, Jann N. Sarkaria, Zhenkun Lou. ATR inhibition is a promising radiosensitizing strategy for chemotherapy-resistant triple negative breast cancer (TNBC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 840.

DNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor prognosis that lacks targeted therapies, especially in patients with chemotherapy-resistant disease. Since DNA methylation-induced silencing of tumor suppressors is common in cancer, reversal of promoter DNA hypermethylation by 5-aza-2'-deoxycytidine (decitabine), an FDA-approved DNA methyltransferase (DNMT) inhibitor, has proven effective in treating hematological neoplasms. However, its antitumor effect varies in solid tumors, stressing the importance of identifying biomarkers predictive of therapeutic response. Here, we focused on the identification of biomarkers to select decitabine-sensitive TNBC through increasing our understanding of the mechanism of decitabine action. We showed that protein levels of DNMTs correlated with response to decitabine in patient-derived xenograft (PDX) organoids originating from chemotherapy-sensitive and -resistant TNBCs, suggesting DNMT levels as potential biomarkers of response. Furthermore, all 3 methytransferases, DNMT1, DNMT3A, and DNMT3B, were degraded following low-concentration, long-term decitabine treatment both in vitro and in vivo. The DNMT proteins could be ubiquitinated by the E3 ligase, TNF receptor-associated factor 6 (TRAF6), leading to lysosome-dependent protein degradation. Depletion of TRAF6 blocked decitabine-induced DNMT degradation, conferring resistance to decitabine. Our study suggests a potential mechanism of regulating DNMT protein degradation and DNMT levels as response biomarkers for DNMT inhibitors in TNBCs.

Discovery of a Glucocorticoid Receptor (GR) Activity Signature Using Selective GR Antagonism in ER-Negative Breast Cancer

Purpose: Although high glucocorticoid receptor (GR) expression in early-stage estrogen receptor (ER)-negative breast cancer is associated with shortened relapse-free survival (RFS), how associated GR transcriptional activity contributes to aggressive breast cancer behavior is not well understood. Using potent GR antagonists and primary tumor gene expression data, we sought to identify a tumor-relevant gene signature based on GR activity that would be more predictive than GR expression alone.Experimental Design: Global gene expression and GR ChIP-sequencing were performed to identify GR-regulated genes inhibited by two chemically distinct GR antagonists, mifepristone and CORT108297. Differentially expressed genes from MDA-MB-231 cells were cross-evaluated with significantly expressed genes in GR-high versus GR-low ER-negative primary breast cancers. The resulting subset of GR-targeted genes was analyzed in two independent ER-negative breast cancer cohorts to derive and then validate the GR activity signature (GRsig).Results: Gene expression pathway analysis of glucocorticoid-regulated genes (inhibited by GR antagonism) revealed cell survival and invasion functions. GR ChIP-seq analysis demonstrated that GR antagonists decreased GR chromatin association for a subset of genes. A GRsig that comprised n = 74 GR activation-associated genes (also reversed by GR antagonists) was derived from an adjuvant chemotherapy-treated Discovery cohort and found to predict probability of relapse in a separate Validation cohort (HR = 1.9; P = 0.012).Conclusions: The GRsig discovered herein identifies high-risk ER-negative/GR-positive breast cancers most likely to relapse despite administration of adjuvant chemotherapy. Because GR antagonism can reverse expression of these genes, we propose that addition of a GR antagonist to chemotherapy may improve outcome for these high-risk patients. Clin Cancer Res; 24(14); 3433-46. ©2018 AACR.

Pathway-Based Analysis of Genome-Wide Association Data Identified SNPs in HMMR as Biomarker for Chemotherapy- Induced Neutropenia in Breast Cancer Patients

Neutropenia secondary to chemotherapy in breast cancer patients can be life-threatening and there are no biomarkers available to predict the risk of drug-induced neutropenia in those patients. We previously performed a genome-wide association study (GWAS) for neutropenia events in women with breast cancer who were treated with 5-fluorouracil, epirubicin and cyclophosphamide and recruited to the SUCCESS-A trial. A genome-wide significant single-nucleotide polymorphism (SNP) signal in the tumor necrosis factor superfamily member 13B (TNFSF13B) gene, encoding the cytokine B-cell activating factor (BAFF), was identified in that GWAS. Taking advantage of these existing GWAS data, in the present study we utilized a pathway-based analysis approach by leveraging knowledge of the pharmacokinetics and pharmacodynamics of drugs and breast cancer pathophysiology to identify additional SNPs/genes associated with the underlying etiology of chemotherapy-induced neutropenia. We identified three SNPs in the hyaluronan mediated motility receptor (HMMR) gene that were significantly associated with neutropenia (p < 1.0E-04). Those three SNPs were trans-expression quantitative trait loci for the expression of TNFSF13B (p < 1.0E-04). The minor allele of these HMMR SNPs was associated with a decreased TNFSF13B mRNA level. Additional functional studies performed with lymphoblastoid cell lines (LCLs) demonstrated that LCLs possessing the minor allele for the HMMR SNPs were more sensitive to drug treatment. Knock-down of TNFSF13B in LCLs and HL-60 promyelocytic cells and treatment of those cells with BAFF modulated the cell sensitivity to chemotherapy treatment. These results demonstrate that HMMR SNP-dependent cytotoxicity of these chemotherapeutic agents might be related to TNFSF13B expression level. In summary, utilizing a pathway-based approach for the analysis of GWAS data, we identified additional SNPs in the HMMR gene that were associated with neutropenia and also were correlated with TNFSF13B expression.

Abstract P5-07-01: LncRNA MIR2052HG regulates ERα level and endocrine resistance through LMTK3 by recruiting early growth response protein 1

BACKGROUND: A GWAS for the MA.27 aromatase inhibitors (AIs) adjuvant trial (4,406 controls and 252 cases) identified variant (V) SNPs in a long noncoding (lnc) RNA, MIR2052HG, that were associated with longer breast cancer free interval (HR= 0.37, P= 2.15E-07). V SNPs (MAF= 0.32 to 0.42) were associated with lower MIR2052HG and ERα expression in the presence of AIs. MIR2052HG maintained ERα both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated ERα degradation. (Cancer Res 76:7012-23, 2016). Our goal was to further elucidate MIR2052HG's mechanism of action.

METHODS: RNA-Binding Protein Immunoprecipitation (RBPI) assays were performed to demonstrate that the transcription factor, early growth response protein 1 (EGR1), worked together with MIR2052HG to regulate lemur tyrosine kinase-3 (LMTK3) transcription in MCF7/AC1 and CAMA-1 cells. The location of EGR1 on the LMTK3 gene locus was mapped using chromatin immunoprecipitation (ChIP) assays. The co-localization of MIR2052HG RNA and the LMTK3 gene locus was determined using RNA-DNA dual fluorescent in situ hybridization (FISH). SNP effects were evaluated using a panel of human lymphoblastoid cell lines.

RESULTS: TCGA analysis revealed LMTK3 and MIR2052HG expression were highly correlated in ERα-positive breast cancer patients. We found that the MIR2052HG transcript was located in the LMTK3 gene locus by RNA-DNA FISH. Among all of the 12 potential LMTK3 transcription factors identified in the Encode database that were examined by RBPI, only EGR1 showed an interaction with MIR2052HG. CHIP assays confirmed EGR1 binding to the two putative EGR1 binding sites in LMTK3 gene.Depletion of MIR2052HG reduced the binding of EGR1 to the LMTK3 promoter and decreased LMTK3 expression, suggesting that it might function as a scaffold. Mechanistically, decreased LMTK3 levels further increased protein kinase C (PKC) activity and downstream AKT activity, leading to reduced ESR1 mRNA levels via increased pFOXO3. At the protein level, in MIR2052HG depleted cells, increased PKC activity increased the phosphorylation of MEK, ERK, and RSK1, leading to increased ERα phosphorylation at Ser167 and increased ERα degradation. Conversely, overexpression of LMTK3 in MIR2052HG depleted cells reversed these phenotypes. MIR2052HG regulated LMTK3 and ERα expression in a SNP- dependent fashion: the MIR2052HG V SNP, relative to wild-type (WT) genotype, increased LMTK3/ERα expression in response to androstenedione due to increased binding between EGR1 and the LMTK3 promoter in LCLs. However, AI treatment reduced this binding in MIR2052HG variant cells but increased binding in WT cells, resulting in decreased LMTK3/ERα in V cells and increased expression in WT cells.

CONCLUSIONS: Our findings support a model in which the protective MIR2052HG variant genotype regulates LMTK3 via MIR2052HG/EGR1, and LMTK3 regulates ERα stability via the PKC/MEK/ERK/RSK1 axis. This regulation may explain the effect of the MIR2052HG variant genotype on cell proliferation and response to AIs in MA.27. These findings provide new insight into the mechanism of action of MIR2052HG and suggest that LMTK3 may be a new therapeutic target in ERα-positive breast cancer patients treated with AIs.

Citation Format: Cairns J, Ingle JN, Shepherd LE, Kubo M, Goetz MP, Weinshilboum RM, Kalari KR, Wang L. LncRNA MIR2052HG regulates ERα level and endocrine resistance through LMTK3 by recruiting early growth response protein 1 [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-07-01.

Tumor-infiltrating lymphocytes in androgen receptor-positive, triple-negative breast cancer

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Background: Triple-negative breast cancer (TNBC) is an immunogenic breast cancer subtype, with a greater percentage of tumors containing tumor-infiltrating lymphocytes (TILs) compared to non-TNBC. TILs are prognostic for recurrence and predictive for chemotherapy benefit in TNBC, but not in estrogen receptor (ER)-positive tumors. A subset of TNBC expresses the androgen receptor (AR), and resembles ER-positive breast cancer in terms of demographics (older age) and clinical course (later recurrences that tend to involve bone). However, little is known regarding the association between TILs and AR expression in TNBC. Methods: From a cohort of 9982 women with surgically-treated non-metastatic breast cancer, patients who met criteria for TNBC (ER/PR < 1% and HER2-negative) by centralized-pathology review were included as previously published [Leon-Ferre et al, Breast Cancer Res Treat 2017]. Stromal TILs in these tumors were quantified on full-face hematoxylin and eosin sections from the surgical specimen, following the 2014 TIL Working Group recommendations [Salgado et al, Ann Oncol 2014]. The expression of AR [EPR1535(2), Abcam] was scored as a continuous variable (1% increments), and categorized as absent (0%), low (1-25% ), low-moderate (26-50%) moderate (51-75%) and high (> 75%) and correlated with TIL density. Results: 605 patients met criteria for TNBC. The median age was 56 years. Most tumors were T1-2 (95%), N0-1 (86%), and high grade (88%). The median stromal TIL content was 20% (0-90%). Tumor tissue was available for AR staining in 509/605 patients. 165 (32%) tumors expressed AR as follows: low: 12%, low-moderate: 7%, moderate: 5%, and high: 8%. Apocrine tumors (n = 30) expressed AR most frequently (86%) and at higher levels (AR high: 50%). For all 509 tumors, the median stromal TIL content according to AR expression was AR absent: 20%, AR low: 20%, AR low-moderate: 15%, AR high: 10%. AR and stromal TILs (both as continuous variables) demonstrated a weak inverse correlation (correlation coefficient -0.1064, p = 0.017). Conclusions: AR expression in TNBC is associated with lower levels of stromal TILs. Additional data correlating the AR, stromal TILs and outcomes in this cohort will be presented at the meeting.

Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines

Metformin is currently considered as a promising anticancer agent in addition to its anti-diabetic effect. To better individualize metformin therapy and explore novel molecular mechanisms in cancer treatment, we conducted a pharmacogenomic study using 266 lymphoblastoid cell lines (LCLs). Metformin cytotoxicity assay was performed using the MTS assay. Genome-wide association (GWA) analyses were performed in LCLs using 1.3 million SNPs, 485k DNA methylation probes, 54k mRNA expression probe sets, and metformin cytotoxicity (IC50s). Top candidate genes were functionally validated using siRNA screening, followed by MTS assay in breast cancer cell lines. Further study of one top candidate, STUB1, was performed to elucidate the mechanisms by which STUB1 might contribute to metformin action. GWA analyses in LCLs identified 198 mRNA expression probe sets, 12 SNP loci, and 5 DNA methylation loci associated with metformin IC50 with P-values <10−4 or <10−5. Integrated SNP/methylation loci-expression-IC50 analyses found 3 SNP loci or 5 DNA methylation loci associated with metformin IC50 through trans-regulation of expression of 11 or 26 genes with P-value <10−4. Functional validation of top 61 candidate genes in 4 IPA networks indicated down regulation of 14 genes significantly altered metformin sensitivity in two breast cancer cell lines. Mechanistic studies revealed that the E3 ubiquitin ligase, STUB1, could influence metformin response by facilitating proteasome-mediated degradation of cyclin A. GWAS using a genomic data-enriched LCL model system, together with functional and mechanistic studies using cancer cell lines, help us to identify novel genetic and epigenetic biomarkers involved in metformin anticancer response.

Establishing and characterizing patient-derived xenografts using pre-chemotherapy percutaneous biopsy and post-chemotherapy surgical samples from a prospective neoadjuvant breast cancer study

Background

Patient-derived xenografts (PDXs) are increasingly used in cancer research as a tool to inform cancer biology and drug response. Most available breast cancer PDXs have been generated in the metastatic setting. However, in the setting of operable breast cancer, PDX models both sensitive and resistant to chemotherapy are needed for drug development and prospective data are lacking regarding the clinical and molecular characteristics associated with PDX take rate in this setting.

Methods

The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant chemotherapy (NAC) trial of stage I-III breast cancer patients treated with neoadjuvant weekly taxane+/-trastuzumab followed by anthracycline-based chemotherapy. Using percutaneous tumor biopsies (PTB), we established and characterized PDXs from both primary (untreated) and residual (treated) tumors. Tumor take rate was defined as percent of patients with the development of at least one stably transplantable (passed at least for four generations) xenograft that was pathologically confirmed as breast cancer.

Results

Baseline PTB samples from 113 women were implanted with an overall take rate of 27.4% (31/113). By clinical subtype, the take rate was 51.3% (20/39) in triple negative (TN) breast cancer, 26.5% (9/34) in HER2+, 5.0% (2/40) in luminal B and 0% (0/3) in luminal A. The take rate for those with pCR did not differ from those with residual disease in TN (p = 0.999) and HER2+ (p = 0.2401) tumors. The xenografts from 28 of these 31 patients were such that at least one of the xenografts generated had the same molecular subtype as the patient. Among the 35 patients with residual tumor after NAC adequate for implantation, the take rate was 17.1%. PDX response to paclitaxel mirrored the patients’ clinical response in all eight PDX tested.

Conclusions

The generation of PDX models both sensitive and resistant to standard NAC is feasible and these models exhibit similar biological and drug response characteristics as the patients’ primary tumors. Taken together, these models may be useful for biomarker discovery and future drug development.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0920-8) contains supplementary material, which is available to authorized users.

A comprehensive analysis of breast cancer microbiota and host gene expression

The inflammatory tumoral-immune response alters the physiology of the tumor microenvironment, which may attenuate genomic instability. In addition to inducing inflammatory immune responses, several pathogenic bacteria produce genotoxins. However the extent of microbial contribution to the tumor microenvironment biology remains unknown. We utilized The Cancer Genome Atlas, (TCGA) breast cancer data to perform a novel experiment utilizing unmapped and mapped RNA sequencing read evidence to minimize laboratory costs and effort. Our objective was to characterize the microbiota and associate the microbiota with the tumor expression profiles, for 668 breast tumor tissues and 72 non-cancerous adjacent tissues. The prominent presence of Proteobacteria was increased in the tumor tissues and conversely Actinobacteria abundance increase in non-cancerous adjacent tissues. Further, geneset enrichment suggests Listeria spp to be associated with the expression profiles of genes involved with epithelial to mesenchymal transitions. Moreover, evidence suggests H. influenza may reside in the surrounding stromal material and was significantly associated with the proliferative pathways: G2M checkpoint, E2F transcription factors, and mitotic spindle assembly. In summary, further unraveling this complicated interplay should enable us to better diagnose and treat breast cancer patients.

Vitamin D Levels, Vitamin D Receptor Polymorphisms, and Inflammatory Cytokines in Aromatase Inhibitor-Induced Arthralgias: An Analysis of CCTG MA.27

BACKGROUND

Approximately half of women taking aromatase inhibitor (AI) therapy develop AI-induced arthralgia (AIA), and many might discontinue AI therapy because of the pain. Using plasma samples from the MA.27 study, we assessed several factors potentially associated with AIA.

PATIENTS AND METHODS

MA.27 is a phase III adjuvant trial comparing 2 AIs, exemestane versus anastrozole. Within an 893-participant nested case-control AIA genome-wide association study, we nested a 72 AIA case-144 control assessment of vitamin D plasma concentrations, corrected for seasonal and geographic variation. We also examined 9 baseline inflammatory cytokines: interleukin (IL)-1β, IL-6, tumor necrosis factor-α, interferon (IFN)γ, IL-10, IL-12p70, IL-17, IL-23, and chemokine ligand (CCL)-20. Finally, we analyzed the multivariate effects of baseline factors: vitamin D level, previously identified musculoskeletal single nucleotide polymorphisms, age, body mass index, and vitamin D receptor (VDR) Fok-I variant genotype on AIA development.

RESULTS

Changes in vitamin D from baseline to 6 months were not significantly different between cases and controls. Elevated inflammatory cytokine levels were not associated with development of AIA. The multivariate model included no clinical factors associated with AIA. However, women with the VDR Fok-I variant genotype were more likely to have a lower IL-1β level (P = .0091) and less likely to develop AIA after 6 months of AI compared with those with the wild type VDR (P < .0001).

CONCLUSION

In this nested case-control correlative study, vitamin D levels were not significantly associated with development of AIA; however, patients with the Fok-I VDR variant genotype were more likely to have a significant reduction in IL-1β level, and less likely to develop AIA.

Knowledge-guided gene prioritization reveals new insights into the mechanisms of chemoresistance

BACKGROUND

Identification of genes whose basal mRNA expression predicts the sensitivity of tumor cells to cytotoxic treatments can play an important role in individualized cancer medicine. It enables detailed characterization of the mechanism of action of drugs. Furthermore, screening the expression of these genes in the tumor tissue may suggest the best course of chemotherapy or a combination of drugs to overcome drug resistance.

RESULTS

We developed a computational method called ProGENI to identify genes most associated with the variation of drug response across different individuals, based on gene expression data. In contrast to existing methods, ProGENI also utilizes prior knowledge of protein-protein and genetic interactions, using random walk techniques. Analysis of two relatively new and large datasets including gene expression data on hundreds of cell lines and their cytotoxic responses to a large compendium of drugs reveals a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compared to other methods. Our siRNA knockdown experiments on ProGENI-identified genes confirmed the role of many new genes in sensitivity to three chemotherapy drugs: cisplatin, docetaxel, and doxorubicin. Based on such experiments and extensive literature survey, we demonstrate that about 73% of our top predicted genes modulate drug response in selected cancer cell lines. In addition, global analysis of genes associated with groups of drugs uncovered pathways of cytotoxic response shared by each group.

CONCLUSIONS

Our results suggest that knowledge-guided prioritization of genes using ProGENI gives new insight into mechanisms of drug resistance and identifies genes that may be targeted to overcome this phenomenon.

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer

Background

Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown.

Methods

We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient-derived xenografts (PDXs) using core needle biopsies. Chemotherapy response was assessed at surgery.

Results

Recurrent "targetable" alterations were not enriched in patients without pathologic complete response (pCR); however, upregulation of steroid receptor signaling and lower pCR rates (16.7%, 1/6) were observed in triple-negative breast cancer (TNBC) patients with luminal androgen receptor (LAR) vs basal subtypes (60.0%, 21/35). Within TNBC, TP53 mutation frequency (75.6%, 31/41) did not differ comparing basal (74.3%, 26/35) and LAR (83.3%, 5/6); however, TP53 stop-gain mutations were more common in basal (22.9%, 8/35) vs LAR (0.0%, 0/6), which was confirmed in The Cancer Genome Atlas and British Columbia data sets. In luminal B tumors, Ki-67 responses were observed in tumors that harbored mutations conferring endocrine resistance ( p53, AKT, and IKBKE ). PDX take rate (27.4%, 31/113) varied according to tumor subtype, and in a patient with progression on NAC, sequencing data informed drug selection (olaparib) with in vivo antitumor activity observed in the primary and resistant (postchemotherapy) PDXs.

Conclusions

In this study, we demonstrate the feasibility of tumor sequencing and PDX generation in the NAC setting. "Targetable" alterations were not enriched in chemotherapy-resistant tumors; however, prioritization of drug testing based on sequence data may accelerate drug development.

Trinucleotide Repeat Expansion in the Transcription Factor 4 (TCF4) Gene Leads to Widespread mRNA Splicing Changes in Fuchs' Endothelial Corneal Dystrophy

Purpose

To identify RNA missplicing events in human corneal endothelial tissue isolated from Fuchs' endothelial corneal dystrophy (FECD).

Methods

Total RNA was isolated and sequenced from corneal endothelial tissue obtained during keratoplasty from 12 patients with FECD and 4 patients undergoing keratoplasty or enucleation for other indications. The length of the trinucleotide repeat (TNR) CTG in the transcription factor 4 (TCF4) gene was determined using leukocyte-derived DNA analyzed by a combination of Southern blotting and Genescan analysis. Commercial statistical software was used to quantify expression of alternatively spliced genes. Validation of selected alternative splicing events was performed by using RT-PCR. Gene sets identified were analyzed for overrepresentation using Web-based analysis system.

Results

Corneal endothelial tissue from FECD patients containing a CTG TNR expansion sequence in the TCF4 gene revealed widespread changes in mRNA splicing, including a novel splicing event involving FGFR2. Differential splicing of NUMA1, PPFIBP1, MBNL1, and MBNL2 transcripts were identified in all FECD samples containing a TNR expansion. The differentially spliced genes were enriched for products that localize to the cell cortex and bind cytoskeletal and cell adhesion proteins.

Conclusions

Corneal endothelium from FECD patients harbors a unique signature of mis-splicing events due to CTG TNR expansion in the TCF4 gene, consistent with the hypothesis that RNA toxicity contributes to the pathogenesis of FECD. Changes to the endothelial barrier function, a known event in the development of FECD, was identified as a key biological process influenced by the missplicing events.

TCL1A Single-Nucleotide Polymorphisms and Estrogen-Mediated Toll-Like Receptor-MYD88-Dependent Nuclear Factor-κB Activation: Single-Nucleotide Polymorphism- and Selective Estrogen Receptor Modulator-Dependent Modification of Inflammation and Immune Response

In a previous genome-wide association study (GWAS) for musculoskeletal adverse events during aromatase inhibitor therapy for breast cancer, we reported that single nucleotide polymorphisms (SNPs) near the TCL1A gene were associated with this adverse drug reaction. Functional genomic studies showed that TCL1A expression was induced by estradiol, but only in cells with the variant sequence for the top GWAS SNP (rs11849538), a SNP that created a functional estrogen response element. In addition, TCL1A genotype influenced the downstream expression of a series of cytokines and chemokines and had a striking effect on nuclear factor κB (NF-κB) transcriptional activity. Furthermore, this SNP-dependent regulation could be reversed by selective ER modulators (SERMs). The present study was designed to pursue mechanisms underlying TCL1A SNP-mediated, estrogen-dependent NF-κB activation. Functional genomic studies were performed using a panel of 300 lymphoblastoid cell lines for which we had generated genome-wide SNP and gene expression data. It is known that toll-like receptors (TLRs) can regulate NF-κB signaling by a process that requires the adaptor protein MYD88. We found that TLR2, TLR7, TLR9, and TLR10 expression, as well as that of MYD88, could be modulated by TCL1A in a SNP and estrogen-dependent fashion and that these effects were reversed in the presence of SERMs. Furthermore, MYD88 inhibition blocked the TCL1A SNP and estrogen-dependent NF-κB activation, as well as protein-protein interaction between TCL1A and MYD88. These observations greatly expand the range of pathways influenced by TCL1A genotype and raise the possibility that this estrogen- and SNP-dependent regulation might be altered pharmacologically by SERMs.

Prognostic value of histopathology, stromal tumor infiltrating lymphocytes (sTILs) and adjuvant chemotherapy (AdjCT) in early stage triple negative breast cancer (TNBC)

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Background: Current guidelines define TNBC as complete absence of estrogen (ER) and progesterone receptor (PR), without HER2 amplification. However, the prognostic impact of clinical and histopathological factors, sTILs, and AdjCT in TNBC meeting these strict criteria is unknown. Methods: From a cohort of 9985 women who underwent upfront surgery for M0 breast cancer (BC) at Mayo Clinic Rochester from 1985-2012, 1159 pts with ER negative or low (≤10%) BC were identified for central ER/PR/HER2 staining and HER2 FISH (IHC2+ only) to select those with TNBC by modern definitions. Cox proportional hazards models were used to assess the impact of clinicopathological variables on invasive disease-free (IDFS) and overall survival (OS). Results: Tumors from 605 pts (median age 56.3 yrs) met criteria for TNBC (ER < 1%, PR < 1% and HER2 0, 1 or 2+ and FISH negative). 51% were T1, 65% N0, 88% grade 3, and 75% had Ki67 > 15%. Histologically, 39% were anaplastic, 26% invasive ductal, 16% medullary, 8% metaplastic, 6% apocrine and 5% others. Median sTILs was 20% (0-90%). 55% pts received AdjCT [21% anthracycline (A), 19% A + taxane, and 15% other]. Median follow-up for IDFS and OS were 7.4 and 10.6 yrs, respectively. Multivariate analyses demonstrated that higher N stage (p < 0.01), lower sTILs (p = 0.01) and no AdjCT (p < 0.01) were independently associated with worse IDFS and OS. Histology (medullary subtype) was associated with better IDFS in univariate (HR 0.56, 95% CI, 0.35-0.89) but not in multivariate analyses, once sTILs were accounted for. Among systemically untreated pts (n = 182), higher N (p < 0.01) and lower sTILs (p = 0.04) were associated with worse IDFS. For systemically untreated T1N0 pts (n = 111), the 5-yr IDFS was 70% (95% CI, 61-81) [T1a: 83% (95% CI, 63-100), T1b: 68% (95% CI, 52-88) and T1c: 67% (95% CI, 55-83)], compared to 78% (95% CI, 68-84) for T1N0 pts treated with AdjCT. Conclusions: In TNBC pts, N stage, sTILs and receipt of AdjCT were independently prognostic for IDFS and OS. sTILs remained prognostic for IDFS in systemically untreated TNBC. In N0 TNBC, the risk of recurrence or death was substantial in the absence of chemotherapy, even for those with T1 tumors.

SLCO1B1 polymorphisms and plasma estrone conjugates in postmenopausal women with ER+ breast cancer: genome-wide association studies of the estrone pathway

BACKGROUND

Estrone (E1), the major circulating estrogen in postmenopausal women, promotes estrogen-receptor positive (ER+) breast tumor growth and proliferation. Two major reactions contribute to E1 plasma concentrations, aromatase (CYP19A1) catalyzed E1 synthesis from androstenedione and steroid sulfatase (STS) catalyzed hydrolysis of estrone conjugates (E1Cs). E1Cs have been associated with breast cancer risk and may contribute to tumor progression since STS is expressed in breast cancer where its activity exceeds that of aromatase.

METHODS

We performed genome-wide association studies (GWAS) to identify SNPs associated with variation in plasma concentrations of E1Cs, E1, and androstenedione in 774 postmenopausal women with resected early-stage ER+ breast cancer. Hormone concentrations were measured prior to aromatase inhibitor therapy.

RESULTS

Multiple SNPs in SLCO1B1, a gene encoding a hepatic influx transporter, displayed genome-wide significant associations with E1C plasma concentrations and with the E1C/E1 ratio. The top SNP for E1C concentrations, rs4149056 (p = 3.74E-11), was a missense variant that results in reduced transporter activity. Patients homozygous for the variant allele had significantly higher average E1C plasma concentrations than did other patients. Furthermore, three other SLCO1B1 SNPs, not in LD with rs4149056, were associated with both E1C concentrations and the E1C/E1 ratio and were cis-eQTLs for SLCO1B3. GWAS signals of suggestive significance were also observed for E1, androstenedione, and the E1/androstenedione ratio.

CONCLUSION

These results suggest a mechanism for genetic variation in E1C plasma concentrations as well as possible SNP biomarkers to identify ER+ breast cancer patients for whom STS inhibitors might be of clinical value.

Model-based unsupervised learning informs metformin-induced cell-migration inhibition through an AMPK-independent mechanism in breast cancer

We demonstrate that model-based unsupervised learning can uniquely discriminate single-cell subpopulations by their gene expression distributions, which in turn allow us to identify specific genes for focused functional studies. This method was applied to MDA-MB-231 breast cancer cells treated with the antidiabetic drug metformin, which is being repurposed for treatment of triple-negative breast cancer. Unsupervised learning identified a cluster of metformin-treated cells characterized by a significant suppression of 230 genes (p-value < 2E-16). This analysis corroborates known studies of metformin action: a) pathway analysis indicated known mechanisms related to metformin action, including the citric acid (TCA) cycle, oxidative phosphorylation, and mitochondrial dysfunction (p-value < 1E-9); b) 70% of these 230 genes were functionally implicated in metformin response; c) among remaining lesser functionally-studied genes for metformin-response was CDC42, down-regulated in breast cancer treated with metformin. However, CDC42's mechanisms in metformin response remained unclear. Our functional studies showed that CDC42 was involved in metformin-induced inhibition of cell proliferation and cell migration mediated through an AMPK-independent mechanism. Our results points to 230 genes that might serve as metformin response signatures, which needs to be tested in patients treated with metformin and, further investigation of CDC42 and AMPK-independence's role in metformin's anticancer mechanisms.