Citations

Abstract Background: Cancer is usually treated with a combination of drugs rather than a single agent. Treating cancer with a drug combination decreases the likelihood of the cancer acquiring resistance to therapy. It also allows for lower dosages of individual drugs, which reduces the occurrence and severity of side effects. Using public datasets, we investigated potential anti-cancer drug combinations using a novel framework, ReCorDE (Recurrent Correlation of Drugs with Enrichment), which identifies correlated drug response patterns for drugs with different primary mechanisms of action. Methods: 250 drugs from CTRPv2, GDSCv2, and PRISM datasets were examined using normalized logIC50 or AUC measurements. ReCorDE consists of a correlation and an enrichment step. For each dataset, we constructed pairwise drug-drug relationships using Spearman’s correlation. Combinations significant (p < 0.05) in less than two datasets after Benjamini-Hochberg (BH) correction were pruned. To turn each drug combination into a drug class combination, all drugs were mapped to their corresponding fourth-level Anatomical Therapeutic Chemical (ATC) codes. Then, using a hypergeometric test, for each class combination in the subset of significant drug combinations (the “inside” set), we tested for enrichment of that class combination in the inside set compared to the class combination universe, the distribution of class combinations for all unique pairwise drug-drug associations (250 unique drugs; 31,125 distinct drug combinations mapped to 1596 distinct class combinations). Multiple testing during enrichment was corrected using the BH method with a significance cutoff of p< 0.05. Results: We found 2764 pairs to be significant at a = 0.05 using the AUC measure. With a correlation coefficient of 0.77, vincristine and YK-4-279, an EWS-FLI1/RNA Helicase A inhibitor, had the lowest computed p-value of of 1.39 × 10−120 Adjusted p-values for >15% of these combinations had p-values < 5 × 10−6. Class combination enrichment on the same set showed 132 class pairs were enriched in the inside set compared to the class combination universe after BH correction. Taxanes/Plk1 inhibitors (OR = 69.5, adjusted p = 5.6 × 10−11); Aurora Kinase inhibitors/histone modifying agents (OR=9.2, adjusted p = 6.13 × 10−11); and pyrimidine analogues/CDK inhibitors (OR=3.43, adjusted p = 0.02) are a few notable enriched class combinations. The enrichment of these class combinations in the inside set suggests that combinations of drugs from these classes may be particularly effective in treating cancer compared to other drug combinations. Conclusions: Our framework, ReCorDE, demonstrates that finding potential drug combinations and characterizing novel, frequently perturbed pathways outside of a drug's primary mechanisms of action can be accomplished by identifying correlated drug-drug pairs from large, publicly accessible databases. Citation Format: Emily T. Ghose, August John, Huanyao Gao, Krishna R. Kalari, Liewei Wang. ReCorDE: A novel computational framework to discover potential combinations of anti-cancer drugs. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4290.

Abstract Background: Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer-related death among women worldwide. Triple negative breast cancer (TNBC) represents 15-20% of all breast cancers and is an aggressive subtype. Chemotherapy-based treatments remain the standard of care for TNBC. Unfortunately, chemotherapy resistance is common, and for these patients, outcomes are poor and alternative treatment strategies remain an unmet need. circRNAs are a newly identified class of noncoding RNA molecules with covalently closed circular structures. An increasing number of recent studies including ours have indicated that circRNAs play crucial roles in regulating tumor development and chemoresistance. However, the role of circRNAs in the process of chemotherapy resistance and TNBC progression is not clear. Materials and Methods: As a first step towards identifying circRNAs that participate in the development of chemoresistance in TNBC cells, and to determine if targeting such circRNAs is a novel and efficacious therapeutic strategy, doxorubicin-resistant (Doxo-R), paclitaxel-resistant (PTX-R), and double-resistant (DP-R) cell lines were generated from MDA-MB-231. Human circRNA microarrays were utilized to profile the expression of approximately 14,000 known circRNAs in normal breast tissue, matched patient-derived xenografts (PDX) generated prior to and following neoadjuvant chemotherapy (NAC), and TNBC chemosensitive and chemoresistant cell lines. Top hits were validated using RT-PCR. Results: circRNA microarray profiling identified 429 and 310 transcripts differentially expressed in doxorubicin and paclitaxel resistant cells, respectively, compared to parental chemosensitive cell lines (|FC| ≥ 1.5; p value < 0.05). In comparison to pre-NAC derived xenografts, 1,396 circRNAs were dysregulated among post-NAC PDX models. Further, three circRNAs (hsa_circ_001388, hsa_circ_104652, and hsa_circ_061260) were upregulated in Doxo-R, PTX-R, and post-NAC PDX samples compared to their respective controls. Among these three circRNAs, hsa_circ_001388 (also known as circNSD2) was the only transcript also predicted to be translated into a novel and uncharacterized protein given the presence of a high confidence translation initiation site and IRES sequence. Ongoing studies are aimed at determining the role of circNSD2 protein in breast cancer carcinogenesis, progression, and response to standard of care chemotherapeutics and the mechanistic process by which this protein functions. Additionally, the efficacy of specifically targeting this circRNA as a novel therapeutic approach is being explored. Conclusions: Increasing knowledge of the important functions of circRNAs underlying drug resistance will provide new opportunities for developing efficacious therapeutic strategies and prognostic/predictive biomarkers for TNBC. Citation Format: Xiyin Wang, Michael J. Emch, Xiaojia Tang, Jia Yu, Krishna R. Kalari, Liewei Wang, Matthew P. Goetz, John R. Hawse. The role of circular RNAs in triple negative breast cancer and chemotherapy resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1689.

AbstractObjectiveElevated serum chromogranin A (CGA) is associated with intrinsic or treatment‐related neuroendocrine differentiation (NED) in men with metastatic castration‐resistant prostate cancer (mCRPC). Fluctuations in serum CGA during treatment of mCRPC have had conflicting results. We analyzed the impact of (i) rising serum CGA and (ii) baseline CGA/PSA ratio during treatment to identify associations with abiraterone acetate (AA) therapy.MethodsBetween June 2013 and August 2015, 92 men with mCRPC were enrolled in a prospective trial with uniform serum CGA processing performed before initiating abiraterone acetate/prednisone (AA/P) and serially after 12 weeks of AA/P treatments. Serum CGA was measured using a homogenous automated immunofluorescent assay. Patients receiving proton pump inhibitors or with abnormal renal function were excluded due to possible false elevations of serum CGA (n = 21 excluded), therefore 71 patients were analyzed. All patients underwent a composite response assessment at 12‐weeks. Kaplan–Meier estimates and Cox Regression models were used to calculate the association with time‐to‐treatment failure analyses and overall survival.ResultsAn increase in chromogranin was associated with a lower risk of treatment failure (hazard ratio [HR]: 0.52, p = 0.0181). The median CGA/PSA ratio was 7.8 (2.6–16.0) and an elevated pretreatment CGA/PSA ratio above the median was associated with a lower risk of treatment failure (HR: 0.54 p value = 0.0185). An increase in CGA was not found to be associated with OS (HR: 0.71, 95% CI: 0.42–1.21, p = 0.207). An elevated baseline CGA/PSA ratio was not associated with OS (HR: 0.62, 95% CI: 0.37–1.03, p = 0.062). An increase in PSA after 12 weeks of treatment was associated with an increased risk of treatment failure (HR: 4.14, CI: 2.21–7.73, p = < 0.0001) and worse OS (HR: 2.93, CI: 1.57–4.45, p = < 0.0001).ConclusionsWe show that an increasing chromogranin on AA/P and an elevated baseline CGA/PSA in patients with mCRPC were associated with a favorable response to AA/P with no changes in survival. There may be limited clinical utility in serum CGA testing to evaluate for lethal NED as AA/P did not induce lethal NED in this cohort. This highlights that not all patients with an increasing CGA have a worse OS.

201 Background: Previous studies have evaluated peripheral whole blood mRNA to identify prognostic biomarkers in metastatic prostate cancer, with no consistent genes of prognostic significance between studies and sample collection done at various points of therapy. We aim to identify the prognostic value of 20 previously identified genes in patients mCRPC from a prospective clinical trial. Methods: Between June 2013 and August 2015, whole blood was prospectively collected in PAXgene RNA tubes from 92 men with mCRPC (NCT01953640). Gene expression from samples with RIN > 4.0 were quantified using a customized NanoString CodeSet of 20 candidate genes (C1QA, MCM2, STOM, GABARAPL2, R10K3, HMBS, TFDP1, CDKN1A, ITGAL, TMCC2, TERF2IP, MMP9, SNCA, TIMP1, SLC4A1, SELENBP1, TMEM66, SEMA4D, PROS1, CD22). The raw data from the nCounter Analysis system were normalized to the positive controls and log2 transformed. Univariable Cox proportional hazards models were performed on each target gene sufficiently above negative control (5 times the maximum value of the negative control) to evaluate associations with overall survival (OS). For each gene we considered a linear, quadratic, or categorical model with quantile cutpoints. Categorical models with cutpoints at the 25th percentile for the genes CD22, GABARAPL2, R10K3, and STOM were used as there was a nonlinear relationship between gene expression and death hazard. The remaining genes were modeled with a linear model. Findings were considered statistically significant based on p-values adjusted using the Holm-Bonferroni correction. Results: 18/20 genes were identified and passed quality control (QC) measures, which excluded C1QA and MCM2. 72/92 men had an evaluable pretreatment specimen that passed QC. The median age was 72 years. The study cohort was evenly balanced in terms of Gleason score ( < = 7 v. > 7) and 60% had high volume disease. The median follow-up time was 5.73 years (IQR: 5.39, 6.49) and 58 patients had died. Of the 18 genes evaluated, STOM (Stomatin) [hazard ratio (HR) 3.00, adjusted p = 0.007] and GABARAPL2 (GABA Type A Receptor Associated Protein Like 2) [HR 2.62, adjusted p = 0.033] were significantly associated with overall survival in univariate analysis. In multivariate analysis, after adjusting for volume of metastatic disease and Gleason score, STOM [HR 2.89, adjusted p = 0.014] was significantly associated with overall survival. Conclusions: Elevated whole blood mRNA expression of STOM is adversely associated with OS in mCRPC. Further studies investigating elucidating the molecular significance of STOM in mCRPC are planned. Clinical trial information: NCT01953640 .

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 &gt;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 &gt; 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&lt; 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.