Goetz, Matthew P.

Abstract INTRODUCTION: The tumor microenvironment consists of a complicated interplay between a heterogeneous mixture of tumor cells and the surrounding tissue and there is a burgeoning interest in the role of the tissue microbiota within this microenvironment. Our group has investigated the breast tumor microbiome using the unaligned (non-human) reads from 796 RNASequencing data obtained from The Cancer Genome Atlas (TCGA) repository of Breast Cancer. METHODS: Unmapped sequences for 720 TCGA tumor samples and 76 paired normal samples were analyzed with Kraken v0.10.5 using the RefSeq 16S and standard genomes. To minimize false discoveries Kraken results were filtered to species that have bacterial genomic and 16S read support. Cluster analysis of the T-distributed Stochastic Neighbor Embedding (tsne) was performed and consensus voting of 26 maximum scoring metrics identified 3 distinct clusters. Differential abundance analysis was performed with the edgeR package. Covariate association analysis was performed for tumor clinical characteristics, as well as sample heterogeneity characteristics. RESULTS: There were three microbiome clusters we identified using TCGA breast samples. The average silhouette width of the third cluster was deemed statistically insignificant (0.071), suggesting further stratification of this cluster is necessary. The remaining two TCGA clusters (467) shared an average silhouette width of 0.39, using Bray's dissimilarity index. Differential abundance analysis of the two clusters after Bonferroni correction identified 450 significant species. The biomes were represented by 63 triple negative, 93 HER2+, 258 Luminal, and 50 tumor adjacent normals. Concordant cluster assignment was observed in 93.7 +/- 7.3% of the normal-tumor pairings, averaged across clinical subtypes. We observed clear delineation of biome populations at the order taxonomic level, which was not associated with the clinical subtype or the tumor/tumor adjacent pairings. We found enrichment of Burkholderiales in the first biome and enrichment of Bacillales and Lactobacillales within the second biome. The second biome appears to be deplete of representatives from the Asian population (p value 0.005) and survival associations were observed to be significantly reduced for HER2 patients associated with Biome 1 (p value 0.025). Geneset enrichment analysis of the expression signatures indicated drug metabolism and chemical carcinogenesis pathways to be associated with biome 2. CONCLUSIONS: In our study, we observed two significantly different microbiomes among TCGA breast cancer samples that were not associated with the clinical subtypes. Current efforts include validating these biomes, using 16S sequencing on matching fresh frozen paraffin embedded samples. Additionally, we are evaluating the influence of the biomes in independent adjuvant and neo-adjuvant studies with next generation sequencing data. Citation Format: Kevin J. Thompson, Jason Sinnwell, Xiaojia Tang, James N. Ingle, Matthew P. Goetz, Krishna R. Kalari. Distinct microbiome populations within breast cancer microenvironments. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3298.

Abstract Background ER+ BC is associated with activated CDK4/6. The CDK4/6 inhibitor palbociclib (P) markedly improves time to progression in advanced ER+HER2- BC. We conducted a neoadjuvant phase II trial to determine the activity of P in primary breast cancer as a prelude to adjuvant studies. Methods To assess molecular changes induced by anastrozole (A) or P+A, patients (pts) were treated initially with A alone (1mg PO daily) for 28 days in cycle 0 (C0) before the addition of P (125mg PO daily on D1-21 each cycle) on C1D1. P+A was administered for 4 28-day cycles followed by C5 with A alone for 2-4 weeks (wks) before surgery. P was added in C5 for 10-12 days immediately prior to surgery in the last 20 pts enrolled to assess molecular changes induced by A, either alone or in combination with P immediately prior to surgery, in resected tumor. Goserelin was added in premenopausal pts. Research tumor biopsies were obtained at baseline, C1D1, and C1D15. Central Ki67 analysis was performed at all timepoints, those with Ki67 >10% at C1D15 went off study treatment. The primary endpoint was complete cell cycle arrest (CCA), defined as Ki67 <2.7%, at C1D15. Patient stratification was based on PIK3CA mutation status with an initial focus on PIK3CA wild type (WT) disease. Pts with PIK3CA mutant (Mut) tumors enrolled to a separate cohort. A sample size of 33 pts in the PIK3CA WT cohort was chosen based on the Fleming's single-stage phase II design to test the hypothesis that P+A leads to > 50% improvement over A in CCA rate on C1D15 biopsy (44% with A alone based on historical data, vs 66% with P+A, power = 0.8, alpha=0.05). The primary endpoint is met if >20 pts achieved CCA in this cohort. Correlative endpoints included assessment of markers of proliferation, apoptosis, senescence, Rb, gene expression microarray, intrinsic subtype, and next generation sequencing of 83-gene panels, which will be reported at the meeting. Results Between 4/23/2013 and 4/24/2015, 50 pts (33 PIK3CA WT, 11 PIK3CA Mut, 2 pending, 4 tissue quantity or quality not sufficient for sequencing (QNS)) were enrolled to the study. Median age was 57.5 (range: 34.1–79.6) years. Four pts, all with WT PIK3CA, went off study due to Ki67 >10% on C1D15 biopsy, 26 pts completed treatment and surgery, 1 refused surgery, 3 withdrew study treatment in C1, and 16 continued to receive study drug (2 in C0, 3 in C1, 4 in C2, 5 in C3, 1 in C4, and 1 in C5). Among the 40 pts currently evaluable for the primary endpoint (C1D15 Ki67), CCA occurred in 34 (85%) pts, including 9 of 9 (100%) PIK3CA Mut, 22 of 28 (78.5%) WT, and 3 of 3 QNS pts. Preliminary analysis of available data indicated a significantly lower Ki67 value after 2 wks of P+A (C1D15) compared to that on A alone (C1D1) (p=0.034, n=18). Conclusion This study met the primary endpoint demonstrating that P+A is a highly effective anti-proliferative combination. The sequential biopsy design clearly demonstrated that P+A increased cell cycle control over A alone. P+A was effective regardless of PIK3CA mutation status and these results support the evaluation of this combination in the adjuvant setting for ER+HER2- BC. Citation Format: Ma CX, Gao F, Northfelt D, Goetz M, Forero A, Naughton M, Ademuyiwa F, Suresh R, Anderson KS, Margenthaler J, Aft R, Hobday T, Moynihan T, Gillanders W, Cyr A, Eberlein TJ, Hieken T, Krontiras H, Hoog J, Han J, Guo Z, Vij K, Mardis E, Al-Kateb H, Sanati S, Ellis MJ. A phase II trial of neoadjuvant palbociclib, a cyclin-dependent kinase (CDK) 4/6 inhibitor, in combination with anastrozole for clinical stage 2 or 3 estrogen receptor positive HER2 negative (ER+HER2-) breast cancer (BC). [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr S6-05.

Abstract Background: Biomarkers to predict response to platinum-based therapy in early breast cancer are needed. HRD is a promising predictor of response to DNA damaging agents, such as platinums. We hypothesized that HRD (high HRD score ≥ 42 and/or tumor BRCA [tBRCA] mutation) would predict pathological complete response (pCR) in patients with HER2-negative early breast cancer treated with PST comprising a platinum, regardless of estrogen receptor (ER) status. Methods: TBCRC008 was a multicenter placebo-controlled trial that investigated pCR (no invasive cancer in breast/axilla) following 12 weeks of preoperative carboplatin and albumin-bound paclitaxel with or without vorinostat in patients with ER-positive or triple-negative breast cancer (TNBC) (Connolly RM. JNM 2015). The pCR rate was similar in both arms (vorinostat 25.8%, placebo 29%). We performed an exploratory biomarker study correlating baseline tumor biopsy HRD status with pCR. The analysis population included all patients with available HRD and pCR data. We compared the proportion of patients with pCR by HRD status using Fisher's exact test. A subset analysis compared pCR proportions by high (≥42) vs. low (<42) HRD score in those patients who did not have tBRCA mutation. A logistic regression model included HRD status, ER status, treatment arm, tumor grade and use of additional anthracycline-based non-study chemotherapy prior to definitive surgery. Results: HRD status and pCR data were available for 48/62 patients (30 ER-positive, 18 TNBC). Of these, 46% of tumors were HR deficient (n=22/48, 33% ER-positive [10/30], 67% TNBC [12/18]). We observed a significantly higher pCR rate in patients with HR deficiency vs not (50% vs 7.7%, p=0.002) in the overall population. A similar trend was observed in ER-positive (30% vs 5%, p=0.095) and TNBC (66.7% vs 16.7%, p=0.13) patients. There was no significant difference when analyzed by treatment arm (vorinostat vs placebo). In a subgroup analysis (n=40) of patients without tBRCA (25 ER-positive, 15 TNBC), a significantly higher pCR rate was observed in those with high vs low HRD score (64.3% vs 7.7%, p <0.001). After adjusting for ER status, randomized treatment, use of AC treatment, and tumor grade, patients whose tumors exhibited HR deficiency had a greater than 6 fold increase in pCR compared to those without HR deficiency (adjusted odds ratio = 6.76, 95% CI = 0.85-53.99, p=.072). Conclusion: This is the first study to evaluate the predictive role of HRD status in patients with ER-positive, HER2-negative breast cancer treated with platinum-based therapy. Our results also support prior observations that HRD status is a promising predictive biomarker of response to platinum agents in TNBC. Further evaluation of this question is warranted in both TNBC and ER-positive breast cancer. Citation Format: Connolly R, Elkin E, Timms K, Goetz M, Boughey J, Zhang Z, Walsh B, Carpenter J, Storniolo A, Watkins S, Gabrielson E, Hartman A-R, Stearns V. Homologous recombination deficiency (HRD) as a predictive biomarker of response to preoperative systemic therapy (PST) in TBCRC008 comprising a platinum in HER2-negative primary operable breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-13.

Abstract We previously reported, on the basis of a genome-wide association study for aromatase inhibitor-induced musculoskeletal symptoms, that single-nucleotide polymorphisms (SNPs) near the T-cell leukemia/lymphoma 1A (TCL1A) gene were associated with aromatase inhibitor-induced musculoskeletal pain and with estradiol (E2)-induced TCL1A expression. Furthermore, variation in TCL1A expression influenced the downstream expression of proinflammatory cytokines and cytokine receptors. Specifically, the top hit genome-wide association study SNP, rs11849538, created a functional estrogen response element (ERE) that displayed estrogen receptor (ER) binding and increased E2 induction of TCL1A expression only for the variant SNP genotype. In the present study, we pursued mechanisms underlying the E2-SNP-dependent regulation of TCL1A expression and, in parallel, our subsequent observations that SNPs at a distance from EREs can regulate ERα binding and that ER antagonists can reverse phenotypes associated with those SNPs. Specifically, we performed a series of functional genomic studies using a large panel of lymphoblastoid cell lines with dense genomic data that demonstrated that TCL1A SNPs at a distance from EREs can modulate ERα binding and expression of TCL1A as well as the expression of downstream immune mediators. Furthermore, 4-hydroxytamoxifen or fulvestrant could reverse these SNP-genotype effects. Similar results were found for SNPs in the IL17A cytokine and CCR6 chemokine receptor genes. These observations greatly expand our previous results and support the existence of a novel molecular mechanism that contributes to the complex interplay between estrogens and immune systems. They also raise the possibility of the pharmacological manipulation of the expression of proinflammatory cytokines and chemokines in a SNP genotype-dependent fashion.

Abstract Purpose: p38 MAPK regulates the production of cytokines in the tumor microenvironment and enables cancer cells to survive despite oncogenic stress, radiotherapy, chemotherapy, and targeted therapies. Ralimetinib (LY2228820 dimesylate) is a selective small-molecule inhibitor of p38 MAPK. This phase I study aimed to evaluate the safety and tolerability of ralimetinib, as a single agent and in combination with tamoxifen, when administered orally to patients with advanced cancer. Experimental Design: The study design consisted of a dose-escalation phase performed in a 3+3 design (Part A; n = 54), two dose-confirmation phases [Part B at 420 mg (n = 18) and Part C at 300 mg (n = 8)], and a tumor-specific expansion phase in combination with tamoxifen for women with hormone receptor–positive metastatic breast cancer refractory to aromatase inhibitors (Part D; n = 9). Ralimetinib was administered orally every 12 hours on days 1 to 14 of a 28-day cycle. Results: Eighty-nine patients received ralimetinib at 11 dose levels (10, 20, 40, 65, 90, 120, 160, 200, 300, 420, and 560 mg). Plasma exposure of ralimetinib (Cmax and AUC) increased in a dose-dependent manner. After a single dose, ralimetinib inhibited p38 MAPK–induced phosphorylation of MAPKAP-K2 in peripheral blood mononuclear cells. The most common adverse events, possibly drug-related, included rash, fatigue, nausea, constipation, pruritus, and vomiting. The recommended phase II dose was 300 mg every 12 hours as monotherapy or in combination with tamoxifen. Although no patients achieved a complete response or partial response,19 patients (21.3%) achieved stable disease with a median duration of 3.7 months, with 9 of these patients on study for ≥6 cycles. Conclusions: Ralimetinib demonstrated acceptable safety, tolerability, and pharmacokinetics for patients with advanced cancer. Clin Cancer Res; 22(5); 1095–102. ©2015 AACR.

Purpose To provide recommendations on the appropriate use of breast tumor biomarker assay results to guide decisions on systemic therapy for metastatic breast cancer. Methods A literature search and prospectively defined study selection identified systematic reviews, meta-analyses, randomized controlled trials (RCTs), prospective–retrospective studies, and prospective comparative observational studies published from 2006 through September 2014. Results The literature search revealed 17 articles that met criteria for further review: 11 studies reporting discordances between primary tumors and metastases in expression of hormone receptors or human epidermal growth factor receptor 2 (HER2), one RCT that addressed the use of a biomarker to decide whether to change or continue a treatment regimen, and five prospective–retrospective studies that evaluated the clinical utility of biomarkers. Recommendations In patients with accessible metastases, biopsy for confirmation of disease process and retesting of estrogen receptor, progesterone receptor, and HER2 status should be offered, but evidence is lacking to determine whether changing anticancer treatment on the basis of change in receptor status affects clinical outcomes. With discordance of results between primary and metastatic tissues, the Panel consensus is to use preferentially the estrogen receptor, progesterone receptor, and HER2 status of the metastasis to direct therapy if supported by the clinical scenario and patient's goals for care. Carcinoembryonic antigen, cancer antigen 15-3, and cancer antigen 27-29 may be used as adjunctive assessments, but not alone, to contribute to decisions regarding therapy. Recommendations for tumor rebiopsy and use of circulating tumor markers are based on clinical experience and Panel informal consensus in the absence of studies designed to evaluate the clinical utility of the markers. As such, it is also reasonable for clinicians to not use these markers as adjunctive assessments.

Abstract Introduction: Triple negative breast cancers (TNBC) are characterized as lacking estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) expression and TNBC patients have higher rates of recurrence and death compared with other breast cancer subtypes. For TNBC patients who fail standard chemotherapy, there are a lack of novel drug therapies, given the absence of well-defined molecular targets. Recently, a microarray meta-analysis identified 7 triple negative subtypes, including the validation of the luminal androgen receptor (LAR) positive subtype [Lehmann, 2011]. However, microarray technology is dependent on probe-target specificity and the 7 subtypes have yet to be validated using RNA sequencing data, and the presences of recurrent genomic alterations in the 7 subtypes are unknown. METHODS: We obtained 1106 breast cancer RNA-Seq bam files from The Cancer Genome Atlas (TCGA) and aligned with Tophat v1.3. The PAM50 intrinsic gene signature was used to extract a cohort of 128 TNBC samples. Consensus clustering of genes, greater than 75th percentile of variance, was performed using Kmeans clustering in Spearman's correlation space. A nearest centroid prediction model was developed from genes differentially expressed among the clusters. Eighty independent TNBC RNA sequencing samples were obtained (British Colombia; BC) [Shah, 2012] which were calibrated to our TNBC conditional quantile normalized cohort and sub-typed by our model. RESULTS: Using RNA-Seq gene expression count data, we identified 5 clusters, all of which were stable, including the LAR cluster. Signaling pathway impact analysis (SPIA) implicated cytokine-cytokine receptor interaction, leukocyte transendothelial migration, and regulation of actin cytoskeleton pathways commonly altered in the non-LAR TNBC subtypes. In contrast, cell cycle, ECM-receptor interaction, endocrine regulated calcium reabsorption, and insulin signaling pathways were altered in the LAR versus non-LAR subtypes. Neuroactive ligand-receptor interactions were observed to be altered commonly between all sub-types. We then applied our model to the Shah, et al cohort. In this cohort, the LAR subtype was consistent with Shah's classification of ‘other’ TNBC and contained no basal samples by PAM50 intrinsic modeling. Analysis of sub-type specific mutation data from the BC cohort demonstrates an increased mutational load in ECM-related proteins, particularly the myosins, along with increased TP53 clonality in the non-LAR subtypes. CONCLUSIONS: Using TCGA RNASeq data, we have confirmed the presence of 5 major TNBC subtypes, including the LAR; which was negligible in basal composition by PAM50 intrinsic modeling. SPIA pathway analysis indicates a core set of pathways demonstrating altered expression across the TNBC sub-types and the identification of molecular targets within each subtype is ongoing. Citation Format: Kevin J. Thompson, Xiaojia Tang, Zhifu Sun, Jason P. Sinnwell, Hugues Sicotte, Douglas W. Mahoney, Steven Hart, Peter T. Vedell, Poulami Barman, Jeanette E. Eckel Passow, Eric D. Wieben, James N. Ingle, Judy C. Boughey, Liewei Wang, Richard Weinshilboum, Krishna R. Kalari, Matthew P. Goetz. Molecular classification of triple negative breast cancer via RNA-sequencing data. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5592. doi:10.1158/1538-7445.AM2014-5592

Abstract INTRODUCTION Next generation sequencing (NGS) of patients has significantly changed our ways to study cancer genomics as it provides precise estimates of gene expression, fusion transcripts, expressed single nucleotide variants (eSNVs), splice variants and copy number variants. The Breast Cancer Genome Guided Therapy (BEAUTY) is an ongoing clinical study in which RNA sequencing (RNAseq) and whole exome sequencing (WES) are performed prior to, during and after neoadjuvant chemotherapy. Here we report the use of these sequencing technologies to investigate gene expression levels and mutational profiles in a triple negative breast cancer (TNBC) patient enrolled in BEAUTY whose disease did not respond to neoadjuvant paclitaxel and anthracycline/cycphosphamide. METHODS Computational approaches were used to integrate WES and RNAseq data obtained before therapy (V1T), after 12 weekly paclitaxel treatments (V2T) and after anthracycline-based regimen at surgical resection (V3T) to study a single patient with persistent TNBC disease after neoadjuvant chemotherapy. RESULTS Using RNA-Seq data, we identified an inter-chromosomal fusion transcript between chromosome 20 and 22 (GNAS-TTC38) that was highly expressed at V1T, V2T and V3T. We also identified intra-chromosomal fusion transcripts that were expressed at two time points, such as fusion transcript (KANSL1-ARL17A) on chromosome 17 for V1T and V2T and fusion transcript (RBM12B-LINC00535) on chromosome 8 for V2T and V3T time points. Several gene expression changes were also observed. Gene expression analysis of V1T, V2T and V3T tumors was performed. Differential temporal gene expression profiles of 9884 genes that were significant and varying at different time points were obtained for pathway analysis. Pathway analysis of 9884 genes identified up regulation and down regulation of several transcription factors with a fold change of 2x or more. When compared to blood, DNA tumor and RNA-Seq data, we identified 81 common somatic eSNVs that were expressed in both V1T and V2T time points and we are in the process of investigating V3T data. We found alterations of key transporter domains (CD225, Coatamer_beta_C, DUF2435, Dynamitin, EI24, GLTP, LMF1, Porin_3, V-ATPase_C) in our V1T and V2T SNV data. Similar to gene expression analysis, we are in the process of obtaining the list of mutations at various time points to identify driver and passenger mutation candidate genes for this specific TNBC patient. CONCLUSIONS Our initial time-series analysis of eSNV, fusion transcripts and gene expression data demonstrate that intensive analysis for individual patients is feasible. Further investigation of drug transporters and transcription regulators may help develop personalized treatment strategies for patients with disease resistant to current regimens. Citation Format: Krishna R. Kalari, Xiaojia Tang, Kevin J. Thompson, Douglas W. Mahoney, Poulami Barman, Jason P. Sinnwell, Hugues Sicotte, Peter Vedell, Steven N. Hart, Travis J. Dockter, Katie N. Jones, Amy L. Conners, Ann M. Moyer, Daniel W. Visscher, Jia Yu, Bowen Gao, Sarah A. McLaughlin, John A. Copland, Alvaro Moreno-Aspitia, Donald W. Northfelt, Richard J. Gray, Vera J. Suman, Jeanette E. Eckel Passow, Jean-Pierre A. Kocher, Eric D. Wieben, Gianrico Farrugia, Cloann G. Schultz, James N. Ingle, Richard Weinshilboum, Matthew P. Goetz, Liewei Wang, Judy C. Boughey. Analysis of sequencing data to identify potential drug targets for an individual newly diagnosed with basal breast cancer who failed to respond to current standard neoadjuvant chemotherapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4185. doi:10.1158/1538-7445.AM2014-4185