DarwinHealth (United States)

SummaryKRAS is the archetypal oncogenic driver of pancreatic cancer. To identify new modulators of KRAS activity in human pancreatic ductal adenocarcinoma (PDAC), we performed regulatory network analysis on a large collection of expression profiles from laser capture microdissected samples of PDAC and benign controls. We discovered that BMAL2, a member of the PAS family of transcription factors, promotes tumor initiation, progression, and post-resection survival, and is highly correlated with KRAS activity. Functional analysis of BMAL2 target genes suggested a role in regulating the hypoxia response, a hallmark of PDAC. Knockout of BMAL2 in multiple human PDAC cell lines reduced cancer cell viability, invasion, and glycolysis, leading to broad dysregulation of cellular metabolism, particularly under hypoxic conditions. We find that BMAL2 directly regulates hypoxia-responsive target genes and is necessary for the stabilization of HIF1A under low oxygen conditions, while simultaneously destabilizing HIF2A. Notably, in vivo xenograft studies demonstrated that BMAL2 loss significantly impairs tumor growth and reduces tumor volume, underscoring its functional importance in tumor progression. We conclude that BMAL2 is a master transcriptional regulator of hypoxia responses in PDAC that works downstream of KRAS signaling, possibly serving as a long-sought molecular switch that distinguishes HIF1A- and HIF2A-dependent modes of hypoxic metabolism.

Despite extensive research, the gene regulatory architecture governing mammalian cell states remains poorly understood. Here we present an integrative systems biology approach to elucidate the network architecture of primed state pluripotency. Using an unbiased methodology, we identified and experimentally confirmed 132 transcription factors as master regulators (MRs) of mouse epiblast stem cell (EpiSC) pluripotency, many of which were further validated by CRISPR-mediated functional assays. To assemble a comprehensive regulatory network, we silenced each of the 132 MRs to assess their effects on the other MRs and their transcriptional targets, yielding a network of 1273 MR → MR interactions. Network architecture analyses revealed four functionally distinct MR modules (communities), and identified key Speaker and Mediator MRs based on their hierarchical rank and centrality. Our findings elucidate the de-centralized logic of a “communal interaction” model in which the balanced activities of four MR communities maintain primed state pluripotency.

Abstract We employed regulatory network analysis to identify master transcriptional regulators whose activity drives key pancreatic cancer phenotypes. Regulatory network analysis is a systems biology approach that computationally infers the activity of transcriptional regulators based on the integrated expression of their positive and negative target genes. To focus on epithelial cell biology, we performed laser capture microdissection and RNA sequencing on 200 human PDAC samples and 45 low-grade precursors (PanIN and IPMN), generating a rich dataset with clinical, epidemiological, and histopathological annotation. Using a transcriptional regulatory network derived from this dataset, we performed master regulator analysis to identify master regulators of four phenotypes: precursors vs. PDAC (initiation), low-grade vs. high grade histopathology (progression), survival post resection, and association with KRAS activity. Changes in the activity of multiple established PDAC drivers and suppressors were associated with tumor initiation and progression, providing a strong validation from existing biology. Integrating across these phenotypes, the top master regulator of PDAC malignancy was found to be ARNTL2, a member of the PAS family of bHLH transcription factors. The canonical function of ARNTL2 is as the heterodimeric binding partner of the circadian rhythm protein CLOCK. However, functional analysis ARNTL2 inferred transcriptional targets highlighted a potential role in hypoxia response and prior studies have demonstrated the ability of ARNTL2 to heterodimerize with HIF1A. Indeed, ARNTL2 was inferred to directly or indirectly regulate every single hypoxia-responsive protein in a previously published hypoxia signature. We therefore studied the role of ARNTL2 in both normoxic and hypoxic conditions and found that its knockdown in PDAC cells led to a selective decrease in viability and invasion under hypoxic conditions. ARNTL2 activity was induced in response to hypoxia and inhibited following treatment with multiple RAF, MEK, and ERK inhibitors, validating its computationally-ingerred association with RAS activity. Strikingly, we found that ARNTL2 was required in PDAC cells for the stabilization of HIF1A in response to hypoxia. Conversely, HIF2A was further stabilized in response to hypoxia upon ARNTL2 deletion, suggesting that ARNTL2 serves to control the balance between HIF1A- and HIF2A dependent metabolic programs in PDAC. Consistent with this, loss of ARNTL2 had sizeable impacts on profiles in PDAC cells and led to a significant reduction of lactate dehydrogenase A under hypoxic conditions. Together these data demonstrate that ARNTL2 is a previously underappreciated master regulator of hypoxia response in pancreatic ductal adenocarcinoma. Citation Format: H. Carlo Maurer, Alvaro Curiel-Garcia, Pasquale Laise, Carmine F. Palermo, Stephen A. Sastra, Gulam A. Manji, Alina Iuga, Kristen Johnson, Jeanine Genkinger, Costas A. Lyssiotis, Andrea Califano, Kenneth P. Olive. ARNTL2 is a Kras-dependent master regulator of hypoxic response in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B002.

Fimepinostat (CUDC-907), a first-in-class oral small-molecule inhibitor of histone deacetylase and phosphatidylinositol 3-kinase, demonstrated efficacy in a phase 1 study of patients with relapsed/refractory (R/R) diffuse large and high-grade B-cell lymphomas (DLBCL/HGBL), particularly those with increased MYC protein expression and/or MYC gene rearrangement/copy number gain (MYC-altered disease). Therefore, a phase 2 study of fimepinostat was conducted in this patient population with 66 eligible patients treated. The primary end-point of overall response (OR) rate for patients with MYC-IHC ≥40% (n=46) was 15%. Subsequently, exploratory pooled analyses were performed including patients treated on both the phase 1 and 2 studies based upon the presence of MYC-altered disease as well as a biomarker identified by Virtual Inference of Protein activity by Enriched Regulon analysis (VIPER). For these patients with MYC-altered disease (n=63), the overall response (OR) rate was 22% with seven responding patients remaining on treatment for approximately two years or longer, and VIPER yielded a three-protein biomarker classification with positive and negative predictive values of ≥85%. Prolonged durations of response were achieved by patients with MYC-altered R/R DLBCL/HGBL treated with single-agent fimepinostat. Combination therapies and/or biomarker-based patient selection strategies may lead to higher response rates in future clinical trials.

Abstract Quantitative metrics to objectively assess the fidelity of cancer models, such as cell lines, organoids, or patient-derived xenografts (PDXs), remain elusive, with histological criteria or the presence of specific mutations often used as driving principles. However, focusing on individual mutations inevitably ignores the effect of a large complement of additional, model-specific genetic and epigenetic events. As a result, effective model fidelity assessment is best performed a posteriori, for instance, by determining whether dependencies identified in a specific tumor model (e.g., a cell line or organoid) are recapitulated in vivo in PDXs or in patients, via pre-clinical or clinical trials. Unfortunately, such an approach is inefficient and time-consuming, creating an urgent need for methodologies capable of effectively and quantitatively assessing model fidelity a priori. This unmet need motivated us to develop and test a quantitative, molecular-level framework (OncoMatch), to assess the fidelity of a given tumor model in the context of a specific biological question, and in particular for addressing issues of drug sensitivity. We addressed this challenge by integrating two independent computational metrics to assess: (a) conservation of regulatory networks inferred from patient-derived samples in a model of interest, and; (b) overlap of master regulator (MR) proteins–i.e., proteins representing the mechanistic determinants of the transcriptional state associated with the phenotype of interest–as inferred from patient-derived and model-derived samples. We show that these molecular-level criteria can effectively identify cell lines that recapitulate patient-specific drug mechanism of action and drug sensitivity, independent of histological consideration. By leveraging gene expression profiles of drug-perturbations in primary cells and explants derived from gastroenteropancreatic-neuroendocrine tumor (GEP-NET) patients, we show that H-STS, an EBV-immortalized lymphoblastoid cell line, represents a high-fidelity model for the assessment of drug mechanism of action and drug sensitivity in these tumors. In particular, our analysis shows highly significant conservation of drug mechanism of action for 60 of 95 profiled drugs (63%, p < 10-10, Bonferroni's corrected), and higher conservation among drugs exhibiting greater bioactivity in this context. This rate is comparable and, in fact higher than what is achieved using tumor-type-matched cell line pairs representative of glioma, pancreatic and prostate carcinoma, and dramatically higher than the conservation observed between unrelated models, which we used as negative controls. Based on this systematic analysis, OncoMatch represents a valuable addition to our repertoire of tools for prioritizing cell lines, organoids and patient-derived xenograft models as high-fidelity human cancer models. We provide comprehensive prioritization of 921 cell lines as potential high-fidelity models for 10,024 human tumor samples in TCGA. This represents an actionable resource to guide selection of cell line models for specific drug mechanism of action and drug sensitivity studies. Citation Format: Mariano J. Alvarez, Yan Pengrong, Mary L. Alpaugh, Michaela Bowden, Ewa T. Sicinska, Chensheng W. Zhou, Charles Karan, Ronald B. Realubit, Prabhjot S. Mundi, Adina Grunn, Jager Dirk, John A. Chabot, Antonio T. Fojo, Paul E. Oberstein, Hanina Hibshoosh, Jeffrey W. Milsom, Matthew H. Kulke, Massimo Loda, Gabriela Chiosis, Diane L. Reidy-Lagunes, Andrea Califano. OncoMatch: Unbiased, quantitative assessment of cancer model fidelity for drug sensitivity and mechanism of action elucidation [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-003.

Eradicating triple-negative breast cancer (TNBC) resistant to neoadjuvant chemotherapy (NACT) is a critical unmet clinical need. In this study, patient-derived xenograft (PDX) models of treatment-naïve TNBC and serial biopsies from TNBC patients undergoing NACT were used to elucidate mechanisms of chemoresistance in the neoadjuvant setting. Barcode-mediated clonal tracking and genomic sequencing of PDX tumors revealed that residual tumors remaining after treatment with standard frontline chemotherapies, doxorubicin (Adriamycin) combined with cyclophosphamide (AC), maintained the subclonal architecture of untreated tumors, yet their transcriptomes, proteomes, and histologic features were distinct from those of untreated tumors. Once treatment was halted, residual tumors gave rise to AC-sensitive tumors with similar transcriptomes, proteomes, and histological features to those of untreated tumors. Together, these results demonstrated that tumors can adopt a reversible drug-tolerant state that does not involve clonal selection as an AC resistance mechanism. Serial biopsies obtained from patients with TNBC undergoing NACT revealed similar histologic changes and maintenance of stable subclonal architecture, demonstrating that AC-treated PDXs capture molecular features characteristic of human TNBC chemoresistance. Last, pharmacologic inhibition of oxidative phosphorylation using an inhibitor currently in phase 1 clinical development delayed residual tumor regrowth. Thus, AC resistance in treatment-naïve TNBC can be mediated by nonselective mechanisms that confer a reversible chemotherapy-tolerant state with targetable vulnerabilities.

Author Affiliation: Distinguished Professor Emerita, College of Nursing, University of Massachusetts, Amherst. The author reports no conflicts of interest. Correspondence: Jeanine Young-Mason, EdD, RN, CS, FAAN, College of Nursing, University of Massachusetts Amherst, 9 Seaview Ln, Newbury, MA 01951 ([email protected]; www.arts4health.org).