Kalari, Krishna R.

Abstract Background: In phase I/II clinical trials, the tamoxifen metabolite Z-endoxifen (ENDX) demonstrated substantial oral bioavailability and promising antitumor activity in endocrine-refractory estrogen-receptor positive breast cancer (ER+ BC) and other solid tumors, with ENDX plasma concentrations reaching as high as 5 µM, a concentration that far exceeds the ERα-targeting nanomolar concentrations. We previously identified protein kinase C beta 1 (PKCβ1), an oncogenic signaling kinase which regulates cell proliferation and tumorigenic transformation, as a novel ENDX receptor. ENDX-bound PKCβ1 (KD: 100 nM) and inhibited PKCβ1 kinase activity (IC50: 357 nM) in vitro, at concentrations achieved in phase I/II ENDX studies. Given the observations that ENDX induces antitumor activity in breast cancers resistant to endocrine therapies, including AIs, tamoxifen and fulvestrant, we postulated that ENDX may impact additional signaling pathways. Therefore, in this study we performed unbiased mass spectrometry to analyze the effects of ENDX on the phosphoproteome and total proteome. Methods: In estrogen unstimulated aromatase-expressing ER+/human epidermal growth factor 2 receptor negative (HER2-) MCF7AC1 breast cancer cells, the effects of ENDX on the phosphoproteome and total proteome were analyzed using ENDX concentrations achieved in tamoxifen treated patients (0.01 and 0.1 µM) and concentrations observed in the ENDX phase I/II trials (5 µM). NetWorKIN and RoKAI prediction tools were utilized to identify the upstream kinases of ENDX downregulated phosphoproteins. In estrogen unstimulated MCF7AC1 as well as in the ER+/HER2- T47D breast cancer cells, the ability of ENDX, tamoxifen, fulvestrant and PKC kinase inhibitor enzastaurin to block insulin or PKC agonist phorbol 12-myristate 13-acetate (PMA)-stimulated AKTSer473 phosphorylation was analyzed by immunoblot (IB) assay. Additionally, ENDX effects on AKTSer473 phosphorylation in the MCF7AC1 xenograft model in vivo was analyzed by IB assay. Further, the effects of PKCβ1 silencing in MCF7AC1 cells and the effects of AKT inhibitor MK-2206 treatment on growth and AKTSer473 phosphorylation in the MCF7AC1 as well as long-term estrogen deprived T47D (T47D-LTED) cell lines were analyzed by cell proliferation and IB assays. Results: In MCF7AC1 cells unstimulated with estrogen, ENDX at 5 µM but not at 0.01 and 0.1 µM concentrations inhibited growth, and induced apoptosis, suggesting an ERα-independent effect. Further, ENDX at 5 µM displayed three-fold greater effects in downregulating the phosphoproteome compared to the other concentrations, with minimal impact on the total proteome. Protein kinase C beta (PKCβ) and AKT1 were identified as the prevalent upstream kinases for ENDX downregulated protein phosphorylations. Notably, in estrogen unstimulated MCF7AC1 and T47D cells, ENDX at 5 µM attenuated phosphorylation of AKTSer473 and AKT substrates in vitro in the presence of insulin and in vivo. In MCF7AC1 cells, PMA-induced phosphorylation of PKCβ1 as well as AKTSer473 and AKT substrate phosphorylations were blocked by ENDX at 5 µM, with ENDX inducing PKCβ1 protein degradation both in the presence of insulin and PMA. Further, ENDX effects on growth and AKTSer473 phosphorylation were phenocopied by siRNA-mediated PKCβ1 knockdown as well as treatment with the pan-AKT inhibitor, MK-2206. Notably, the potent PKCβ1 kinase inhibitor, enzastaurin, had no effects either on PKCβ1 protein degradation nor on downstream AKT signaling. Conclusion: Taken together, these findings suggest that ENDX may exert anticancer activity via dual effects on blocking ERα as well as by targeting PKCβ1 for degradation, thus suppressing AKT signaling and induction of apoptosis. These preclinical findings will be studied in a planned neoadjuvant trial comparing ENDX with exemestane and ovarian function suppression (EVANGELINE) that will activate in the Fall of 2022. Citation Format: Swaathi Jayaraman, Xinyan Wu, Krishna R. Kalari, Xiaojia Tang, Mary Kuffel, Elizabeth S. Bruinsma, Santosh Renuse, James N. Ingle, Joel Reid, Matthew Schellenberg, John Hawse, Akhilesh Pandey, Matthew P. Goetz. Endoxifen Downregulates AKT Phosphorylation Through Protein Kinase C Beta 1 in ER+/HER2- Breast Cancer. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-11-04.

Abstract Background: Triple-negative breast cancers (TNBC) exhibit high rates of recurrence and mortality. However, recent studies suggest that a subset of patients (pts) with early-stage TNBC enriched in tumor-infiltrating lymphocytes (TILs) have excellent clinical outcomes even in the absence of systemic therapy. Additional histological biomarkers that could identify pts for future systemic therapy escalation/de-escalation strategies are of great interest. TNBC are frequently highly proliferative with abundant mitoses. However, classic markers of proliferation (manual mitosis counting and Ki-67) appear to offer no prognostic value. Here, we evaluated the prognostic effects of automated mitotic spindle hotspot (AMSH) counting on RFS in independent cohorts of systemically untreated early-stage TNBC. Methods: AMSH counting was conducted with a state-of-the-art deep learning algorithm trained on the detection of mitoses within 2 mm2 areas with the highest mitotic density (i.e. hotspots) in digital H&E images. Details of the development, training and validation of the algorithm were published previously [1] in a cohort of unselected TNBC. We obtained AMSH counts in a centrally confirmed TNBC cohort from Mayo Clinic [2] and focused our analysis on pts who received locoregional therapy but no systemic therapy. Using a fractional polynomial analysis with a multivariable proportional hazards regression model, we confirmed the assumption of linearity in the log hazard for the continuous variable AMSH and evaluated whether AMSH counts were prognostic of RFS. We corroborated our findings in an independent cohort of systemically untreated TNBC pts from the Radboud University Medical Center in the Netherlands (Radboud Cohort). Results are reported at a median follow-up of 8.1 and 6.7 years for the Mayo and Netherlands cohorts, respectively. Results: Among 182 pts with who did not receive systemic therapy in the Mayo Cohort, 140 (77%) with available AMSH counts were included. The mean age was 61 (range: 31-94), 71% were postmenopausal, 67% had tumors ≤ 2cm, and 83% were node-negative. As expected, most tumors were Nottingham grade 3 (84%) and had a high Ki-67 proliferation index (54% with Ki-67 >30%). Most tumors (73%) had stromal TILs ≤ 30%. The median AMSH count was 18 (IQR: 8, 42). AMSH counts were linearly associated with grade and tumor size, with the proportion of pts with grade 3 tumors and size > 2 cm increasing as the AMSH counts increased (p=0.007 and p=0.059, respectively). In a multivariate model controlling for nodal status, tumor size, and stromal TILs, AMSH counts were independently associated with RFS (p< 0.0001). For every 10-point increase in the AMSH count, we observed a 17% increase in the risk of experiencing an RFS event (HR 1.17, 95% CI 1.08-1.26). We corroborated our findings in the Radboud Cohort (n=126). The mean age was 68 (range: 40-96), and 81% were node-negative. While the median AMSH count was 36 (IQR: 16-63), higher than in the Mayo Cohort (p=0.004), the prognostic impact was similar, with a significant association between AMSH count and RFS (p=0.028) in a multivariate model corrected for nodal status, tumor size, and stromal TILs. For every 10-point increase in the AMSH count in the Netherlands cohort, we observed a 9% increase in the risk of experiencing an RFS event (HR 1.09, 95% CI 1.01-1.17). RFS rates according to AMSH counts for both cohorts are shown in the Table. Conclusions: AMSH counting is a new proliferation biomarker that provides prognostic value independent of nodal status, tumor size, and stromal TILs in systemically untreated early-stage TNBC. Plans are underway to evaluate AMSH counts in additional cohorts of systemically untreated TNBC, and in other disease settings such as prior to neoadjuvant systemic therapy. If validated, this biomarker should be prospectively evaluated as a potential selection biomarker in clinical trials of systemic therapy de-escalation. References: 1. PMID: 29994086 2. PMID: 28913760 Table RFS according to AMSH counts in the Mayo and Radboud Cohorts Citation Format: Roberto A. Leon-Ferre, Jodi M. Carter, David Zahrieh, Jason P. Sinnwell, Roberto Salgado, Vera Suman, David Hillman, Judy C. Boughey, Krishna R. Kalari, Fergus J. Couch, James N. Ingle, Maschenka Balkenkohl, Francesco Ciompi, Jeroen van der Laak, Matthew P. Goetz. Mitotic spindle hotspot counting using deep learning networks is highly associated with clinical outcomes in patients with early-stage triple-negative breast cancer who did not receive systemic therapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-11-34.

Abstract Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying molecular mechanisms is needed to identify effective targets to overcome resistance. Given the complexity of the transcriptional dynamics in cells, differential gene expression analysis of bulk transcriptomics data cannot provide sufficient detailed insights into resistance mechanisms. Incorporating network structures could overcome this limitation to provide a global and functional perspective of Abi resistance in mCRPC. Here, we developed TraRe, a computational method using sparse Bayesian models to examine phenotypically driven transcriptional mechanistic differences at three distinct levels: transcriptional networks, specific regulons, and individual transcription factors (TF). TraRe was applied to transcriptomic data from 46 patients with mCRPC with Abi-response clinical data and uncovered abrogated immune response transcriptional modules that showed strong differential regulation in Abi-responsive compared with Abi-resistant patients. These modules were replicated in an independent mCRPC study. Furthermore, key rewiring predictions and their associated TFs were experimentally validated in two prostate cancer cell lines with different Abi-resistance features. Among them, ELK3, MXD1, and MYB played a differential role in cell survival in Abi-sensitive and Abi-resistant cells. Moreover, ELK3 regulated cell migration capacity, which could have a direct impact on mCRPC. Collectively, these findings shed light on the underlying transcriptional mechanisms driving Abi response, demonstrating that TraRe is a promising tool for generating novel hypotheses based on identified transcriptional network disruptions. Significance: The computational method TraRe built on Bayesian machine learning models for investigating transcriptional network structures shows that disruption of ELK3, MXD1, and MYB signaling cascades impacts abiraterone resistance in prostate cancer.

Prostate cancer (PCa) accounted for more than 34,000 deaths in US males [...]

Abstract We identified resistance mechanisms to abiraterone acetate/prednisone (AA/P) in patients with metastatic castration-resistant prostate cancer (mCRPC) in the Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study. We analyzed whole-exome sequencing (WES) and RNA-sequencing data from 83 patients with metastatic biopsies before (V1) and after 12 weeks of AA/P treatment (V2). Resistance was determined by time to treatment change (TTTC). At V2, 18 and 11 of 58 patients had either short-term (median 3.6 months; range 1.4–4.5) or long-term (median 29 months; range 23.5–41.7) responses, respectively. Nonresponders had low expression of TGFBR3 and increased activation of the Wnt pathway, cell cycle, upregulation of AR variants, both pre- and posttreatment, with further deletion of AR inhibitor CDK11B posttreatment. Deletion of androgen processing genes, HSD17B11, CYP19A1 were observed in nonresponders posttreatment. Genes involved in cell cycle, DNA repair, Wnt-signaling, and Aurora kinase pathways were differentially expressed between the responder and non-responder at V2. Activation of Wnt signaling in nonresponder and deactivation of MYC or its target genes in responders was detected via SCN loss, somatic mutations, and transcriptomics. Upregulation of genes in the AURKA pathway are consistent with the activation of MYC regulated genes in nonresponders. Several genes in the AKT1 axis had increased mutation rate in nonresponders. We also found evidence of resistance via PDCD1 overexpression in responders. Implications: Finally, we identified candidates drugs to reverse AA/P resistance: topoisomerase inhibitors and drugs targeting the cell cycle via the MYC/AURKA/AURKB/TOP2A and/or PI3K_AKT_MTOR pathways.

Neoadjuvant chemotherapy (NAC) remains the cornerstone of the treatment for triple negative breast cancer (TNBC), with the goal of complete eradication of disease. However, for patients with residual disease after NAC, recurrence and mortality rates are high and the identification of novel therapeutic targets is urgently needed. We quantified tyrosine phosphorylation (pTyr)-mediated signaling networks in chemotherapy sensitive (CS) and resistant (CR) TNBC patient-derived xenografts (PDX), to gain novel therapeutic insights. The antitumor activity of SFK inhibition was examined in vivo. Treated tumors were further subjected to phosphoproteomic and RNAseq analysis, to identify the mechanism of actions of the drug. We identified Src Family Kinases (SFKs) as potential therapeutic targets in CR TNBC PDXs. Treatment with dasatinib, an FDA approved SFK inhibitor, led to inhibition of tumor growth in vivo. Further analysis of post-treatment PDXs revealed multiple mechanisms of actions of the drug, confirming the multi-target inhibition of dasatinib. Analysis of pTyr in tumor specimens suggested a low prevalence of SFK-driven tumors, which may provide insight into prior clinical trial results demonstrating a lack of dasatinib antitumor activity in unselected breast cancer patients. Taken together, these results underscore the importance of pTyr characterization of tumors, in identifying new targets, as well as stratifying patients based on their activated signaling networks for therapeutic options. Our data provide a strong rationale for studying SFK inhibitors in biomarker-selected SFK-driven TNBC.

AbstractBackground:Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). Response to NAC is prognostic, with reductions in low overall survival and disease-free survival rates in those patients who do not achieve pathological complete response (pCR). Based on this premise, we focused on patients with residual disease and hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence.Methods and Results: We investigated 24 TNBC tumors from 12 patients with pre- and post-NAC data, including four patients who recurred shortly after surgery(<24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and non-recurrent TNBC tumors; however, post-NAC samples demonstrated a significant alteration in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the paired NAC I-SPY1 trial confirmed 56 genesets. Underlying these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n=392) breast cancer data set with relapse-free survival (RFS) data was used to refine our gene list to a 17 gene signature. A three-fold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine learning models. Due to the limited studies with pre-and post-NAC TNBC tumor data, further validation of the signature is needed.Conclusion:Analysis of multi-omics data from post-NAC TNBC chemoresistant tumors showed downregulation of mismatch repair, purin, and tubulin pathways. Additionally, weidentified a 17 gene signature in TNBC associated with post-NAC recurrence enriched with down-regulation of immune genes.

Abstract A problematic feature of many human cancers is a lack of understanding of mechanisms controlling organ-specific patterns of metastasis, despite recent progress in identifying many mutations and transcriptional programs shown to confer this potential. To address this gap, we developed a methodology that enables different aspects of the metastatic process to be comprehensively characterized at a clonal resolution. Our approach exploits the application of a computational pipeline to analyze and visualize clonal data obtained from transplant experiments in which a cellular DNA barcoding strategy is used to distinguish the separate clonal contributions of two or more competing cell populations. To illustrate the power of this methodology, we demonstrate its ability to discriminate the metastatic behavior in immunodeficient mice of a well-established human metastatic cancer cell line and its co-transplanted LRRC15 knockdown derivative. We also show how the use of machine learning to quantify clone-initiating cell (CIC) numbers and their subsequent metastatic progeny generated in different sites can reveal previously unknown relationships between different cellular genotypes and their initial sites of implantation with their subsequent respective dissemination patterns. These findings underscore the potential of such combined genomic and computational methodologies to identify new clonally-relevant drivers of site-specific patterns of metastasis.

Abstract Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low overall survival rates and high molecular heterogeneity; therefore, few targeted therapies are available. The luminal androgen receptor (LAR) is the most consistently identified TNBC subtype, but the clinical utility has yet to be established. Here, we constructed a novel genomic classifier, LAR-Sig, that distinguishes the LAR subtype from other TNBC subtypes and provide evidence that it is a clinically distinct disease. A meta-analysis of seven TNBC datasets (n = 1086 samples) from neoadjuvant clinical trials demonstrated that LAR patients have significantly reduced response (pCR) rates than non-LAR TNBC patients (odds ratio = 2.11, 95% CI: 1.33, 2.89). Moreover, deconvolution of the tumor microenvironment confirmed an enrichment of luminal epithelium corresponding with a decrease in basal and myoepithelium in LAR TNBC tumors. Increased immunosuppression in LAR patients may lead to a decreased presence of cycling T-cells and plasma cells. While, an increased presence of myofibroblast-like cancer-associated cells may impede drug delivery and treatment. In summary, the lower levels of tumor infiltrating lymphocytes (TILs), reduced immune activity in the micro-environment, and lower pCR rates after NAC, suggest that new therapeutic strategies for the LAR TNBC subtype need to be developed.

Abstract While epoxyeicosatrienoic acids (EETs) have been implicated in breast cancer growth and progression, less is known about their effects on oncogene transcription. We have previously found that the oncogenic regioisomer (±)14,15-EET drives mitochondrial respiration, ATP synthesis, and proliferation of ER+/HER2- breast cancer cells [Cell Chem Biol. 2017 Oct 19;24(10):1259-1275]. RNAseq analysis was performed (5 replicates per condition) on serum starved (16 hours) MCF-7 cells which were then treated with (±)14,15-EET or vehicle (2 hours; serum and phenol red free medium without estradiol). Using gene set enrichment analysis (GSEA), we found that (±)14,15-EET activated an estrogen receptor alpha (ER) hallmark early response gene set and synchronously activated a MYC hallmark gene set. With activation of the MYC hallmark gene set, c-Myc gene expression was also induced at 2 hours (3.99-fold; P=2.3 x 10-17; FDR=2.8 x 10-14). These data suggest an alternative pathway for activation of estrogen and MYC regulated genes in the absence of estradiol. The 15 genes most transcriptionally activated by (±)14,15-EET at 2 hours were: VMP1, ZFP36, JUNB, FOS, IER3, EGR1, IER5L, ELF3, JUN, NR4A1, HES1, DUSP1, MYC, TOB1, and CITED2 [fold change range: 3.25 (CITED2) to 90.5 (FOS); all P&lt; 2.86 x 10-17; all FDR &lt; 3.03 x 10-14]. The ER regulated genes most transcriptionally activated (&gt;1.5 fold) were: IER3, TOB1, AREG, CISH, KCNMB3, and PDK4 (fold change range: 1.77 to 4.35; P= 1.74 x 10-18 to 1.35 x 10-5; FDR=5.54 x 10-15 to 6.4 x 10-4). The MYC regulated genes most transcriptionally activated (&gt; 1.5-fold change) were EIF4A1 (fold change= 2.37; P=1.0 x 10-7; FDR=1.33 x 10-5), IRF9 (fold change=1.58; P=0.0044; FDR= 0.026), and FOSL1 (fold change=1.51; P=0.008; FDR=0.04). Supporting the hypothesis of (±)14,15-EET activation of ER-regulated transcription, (±)14,15-EET promoted nuclear translocation of ER at 1 hour measured by DAPI normalized immunofluorescence [MCF-7 nuclear ER increase of 1.66-fold (P=0.031); ZR75-1 nuclear ER increase of 1.77-fold (P=0.015)]. Supporting the hypothesis of (±)14,15-EET activation of MYC-regulated transcription, (±)14,15-EET treatment promoted nuclear translocation of c-Myc with MCF-7 cells exhibiting a 1.22-fold increase at 2 hours (P=0.002). (±)14,15-EET also promoted nuclear translocation of FITC-70 kDa dextran with MCF-7 cells exhibiting an increase of 1.35-fold at 1 hour (P=0.029). These data suggest that (±)14,15-EET can induce an estradiol-like immediate early gene response in ER+/HER2- breast cancer cells correlating with c-Myc activation. In summary, while the effect of (±)14,15-EET on nuclear translocation may be partially cargo agnostic, (±)14,15-EET promotes ER and c-Myc nuclear translocation and associated transcription, mimicking a tandem hormonal and growth factor response. Citation Format: Jianxun Lei, Zhijun Guo, Julissa Molina-Vega, Paloma Cervantes, Swaathi Jayaraman, John R. Hawse, Carlos Perez, Juan Abrahante, Xiaojia Tang, Krishna Kalari, Jinhua Wang, John R. Falck, Carol Lange, Matthew P. Goetz, David Potter. (±) 14,15-epoxyeicosatrienoic acid induces hallmark ER and MYC gene expression and associated ER and c-Myc nuclear translocation in ER+/HER2- breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB564.