Targeting dual signalling pathways in concert with immune checkpoints for the treatment of pancreatic cancer.

OBJECTIVE: This study exploits the intersection between molecular-targeted therapies and immune-checkpoint inhibition to define new means to treat pancreatic cancer. DESIGN: Patient-derived cell lines and xenograft models were used to define the response to CDK4/6 and MEK inhibition in the tumour compartment. Impacts relative to immunotherapy were performed using subcutaneous and orthotopic syngeneic models. Single-cell RNA sequencing and multispectral imaging were employed to delineate effects on the immunological milieu in the tumour microenvironment. RESULTS: We found that combination treatment with MEK and CDK4/6 inhibitors was effective across a broad range of PDX models in delaying tumour progression. These effects were associated with stable cell-cycle arrest, as well as the induction of multiple genes associated with interferon response and antigen presentation in an RB-dependent fashion. Using single-cell sequencing and complementary approaches, we found that the combination of CDK4/6 and MEK inhibition had a significant impact on increasing T-cell infiltration and altering myeloid populations, while potently cooperating with immune checkpoint inhibitors. CONCLUSIONS: Together, these data indicate that there are canonical and non-canonical features of CDK4/6 and MEK inhibition that impact on the tumour and immune microenvironment. This combination-targeted treatment can promote robust tumour control in combination with immune checkpoint inhibitor therapy.

Pancreatic cancer cell lines as patient-derived avatars: genetic characterisation and functional utility.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is a therapy recalcitrant disease with the worst survival rate of common solid tumours. Preclinical models that accurately reflect the genetic and biological diversity of PDAC will be important for delineating features of tumour biology and therapeutic vulnerabilities. DESIGN: 27 primary PDAC tumours were employed for genetic analysis and development of tumour models. Tumour tissue was used for derivation of xenografts and cell lines. Exome sequencing was performed on the originating tumour and developed models. RNA sequencing, histological and functional analyses were employed to determine the relationship of the patient-derived models to clinical presentation of PDAC. RESULTS: The cohort employed captured the genetic diversity of PDAC. From most cases, both cell lines and xenograft models were developed. Exome sequencing confirmed preservation of the primary tumour mutations in developed cell lines, which remained stable with extended passaging. The level of genetic conservation in the cell lines was comparable to that observed with patient-derived xenograft (PDX) models. Unlike historically established PDAC cancer cell lines, patient-derived models recapitulated the histological architecture of the primary tumour and exhibited metastatic spread similar to that observed clinically. Detailed genetic analyses of tumours and derived models revealed features of ex vivo evolution and the clonal architecture of PDAC. Functional analysis was used to elucidate therapeutic vulnerabilities of relevance to treatment of PDAC. CONCLUSIONS: These data illustrate that with the appropriate methods it is possible to develop cell lines that maintain genetic features of PDAC. Such models serve as important substrates for analysing the significance of genetic variants and create a unique biorepository of annotated cell lines and xenografts that were established simultaneously from same primary tumour. These models can be used to infer genetic and empirically determined therapeutic sensitivities that would be germane to the patient.

Composite analysis of immunological and metabolic markers defines novel subtypes of triple negative breast cancer.

Cancer biology is influenced by the tumor microenvironment, which impacts disease prognosis and therapeutic interventions. The inter-relationship of tumor-infiltrating lymphocytes, immune response regulators, and a glycolytic tumor environment was evaluated in a cohort of 183 largely consecutive patients with triple negative breast cancer diagnosis. High levels of tumor-infiltrating lymphocytes were associated with improved survival of triple negative breast cancer cases. However, elevated levels of PD-L1, CD163, and FOXP3 were individually associated with significantly decreased overall survival. These three determinants were significantly correlated, and could serve to differentiate the prognostic significance of tumor-infiltrating lymphocytes. Interestingly, a glycolytic tumor environment, as determined by the expression of MCT4 in the tumor stroma, was associated with the immune evasive environment and poor prognosis. Clustering of all markers defined four distinct triple negative breast cancer subtypes that harbored prognostic significance in multivariate analysis. Immune and metabolic markers stratified triple negative breast cancer into subtypes that have prognostic significance and implications for therapies targeting immune checkpoints and tumor metabolism.

CDK/cyclin dependencies define extreme cancer cell-cycle heterogeneity and collateral vulnerabilities.

Progression through G1/S phase of the cell cycle is coordinated by cyclin-dependent kinase (CDK) activities. Here, we find that the requirement for different CDK activities and cyclins in driving cancer cell cycles is highly heterogeneous. The differential gene requirements associate with tumor origin and genetic alterations. We define multiple mechanisms for G1/S progression in RB-proficient models, which are CDK4/6 independent and elicit resistance to FDA-approved inhibitors. Conversely, RB-deficient models are intrinsically CDK4/6 independent, but exhibit differential requirements for cyclin E. These dependencies for CDK and cyclins associate with gene expression programs that denote intrinsically different cell-cycle states. Mining therapeutic sensitivities shows that there are reciprocal vulnerabilities associated with RB1 or CCND1 expression versus CCNE1 or CDKN2A. Together, these findings illustrate the complex nature of cancer cell cycles and the relevance for precision therapeutic intervention.

Functional Determinants of Cell Cycle Plasticity and Sensitivity to CDK4/6 Inhibition.

Intrinsic or acquired resistance to clinically approved CDK4/6 inhibitors has emerged as a major obstacle that hinders their utility beyond ER+ breast cancer. In this study, CDK4/6-dependent and -resistant models were employed to identify functional determinants of response to pharmacologic CDK4/6 inhibitors. In all models tested, the activation of RB and inhibition of CDK2 activity emerged as determinants of sensitivity. While depleting CDK4 and 6 was sufficient to limit proliferation in specific resistance settings, RB loss rendered cells completely independent of these kinases. The main downstream target in this context was the activation status of CDK2, which was suppressed with CDK4/6 inhibition in an RB-dependent fashion. Protein levels of p27 were associated with plasticity/rigidity of the cell cycle and correlated with sensitivity to CDK4/6 inhibition. Exogenous overexpression and pharmacologic induction of p27 via inhibition of SKP2 and targeting the MEK/ERK pathway enhanced the cytostatic effect of CDK4/6 inhibitors. Mice bearing ER+ xenografts displayed a durable antitumor response to palbociclib; however, over the course of treatment, few cells retained RB phosphorylation, which was associated with limited p27 protein levels as determined by multispectral imaging. Similarly, combination treatment of palbociclib with a MEK inhibitor in pancreatic cancer PDX models upregulated p27 and further enhanced the in vivo tumor response to palbociclib. Collectively, these results suggest that the cell cycle plasticity, which enables tumor models to evade palbociclib-mediated activation of RB, could be targeted using a clinically applicable CDK2 inhibitor. SIGNIFICANCE: This work provides a mechanistic insight toward understanding the functional roles of multiple cell cycle regulators that drive plasticity and sensitivity to CDK4/6 inhibition.

A Phase I Study of Ribociclib Plus Everolimus in Patients with Metastatic Pancreatic Adenocarcinoma Refractory to Chemotherapy.

Purpose: Metastatic pancreatic adenocarcinoma (mPC) has a poor prognosis. CDK4/6 is often deregulated in mPC due to CDKN2A loss, resulting in the loss of p16INK4a that inhibits CDK4/6. CDK4/6 inhibitor monotherapy is ineffective due to RAS-mediated activation of alternative pathways, including phosphatidylinositol 3-kinase-mammalian target of rapamycin (PI3K-mTOR). We conducted a phase I study combining CDK4/6 and mTOR inhibition in patients with mPC refractory to standard chemotherapy. Materials and Methods: The combination of ribociclib (a CDK4/6 inhibitor) and everolimus (an mTOR inhibitor) was investigated in a phase I study in patients with mPC and progression on 5-fluorouracil- and gemcitabine-based chemotherapy. A 3 + 3 design was used to find the recommended phase II dose (RP2D) of ribociclib (250 or 300 mg daily for days 1-21) in combination with everolimus (2.5 mg daily for days 1-28) every 28 days. Secondary endpoints were median progression-free survival (mPFS), median overall survival (mOS), response rate, safety, and effect on the retinoblastoma pathway. Results: Twelve patients were enrolled, six at each dose level. Only one patient had a dose-limiting toxicity of a grade 3 rash at the 250 mg dose. The RP2D of ribociclib was 300 mg. mPFS was 1.8 months (95% confidence interval [CI] [0.6-2.1]), and mOS was 3.7 months (95% CI [2.3-5.6]). Two patients (17%) had stable disease at 8 weeks. Pharmacodynamic evaluation demonstrated that CDK4/6-regulated gene expression was significantly decreased on treatment (n = 6, p < 0.001). Conclusion: Ribociclib 300 mg daily for days 1-21 plus everolimus 2.5 mg daily was well tolerated and associated with decreased CDK4/6-regulated gene expression. This combination was not effective as a third-line therapy but does pharmacologically target CDK4/6 in mPC, revealing the potential for benefit in other settings.

Coordinately Targeting Cell-Cycle Checkpoint Functions in Integrated Models of Pancreatic Cancer.

PURPOSE: Cancer cells often have deficiencies in cell-cycle control mechanisms and could be dependent on specific cell-cycle checkpoints to maintain viability. Because of the documented role of KRAS in driving replication stress, we targeted the checkpoint governing DNA replication using CHK1 kinase inhibitors in pancreatic ductal adenocarcinoma (PDAC) models and examined mechanisms of resistance. EXPERIMENTAL DESIGN: Single-agent efficacy of CHK1 inhibition was investigated in established and primary PDAC lines. Drug screening was performed to identify cooperative agents. In vitro and in vivo studies were employed to interrogate combination treatment efficacy and mechanisms of resistance. RESULTS: Many PDAC models evade single-agent inhibition through mechanisms that allow S-phase progression with CHK1 inhibited. Gene expression analysis revealed FOXM1 as a potential marker of CHK1 sensitivity and defined a form of pancreatic cancer with poor prognosis. Drug screen analysis identified WEE1 as a cooperative agent with CHK1 and was effective in cell culture. In vivo experiments validated the combination efficacy; however, resistance could evolve. Resistance was due to selection of a stable subclone from the original PDX tumor, which harbored high baseline replication stress. In vitro analysis revealed that gemcitabine could eliminate viability in the resistant models. The triplet regimen of gemcitabine, CHK1, and WEE1 inhibition provided strong disease control in all xenograft models interrogated. CONCLUSIONS: These results demonstrate the therapeutic resiliency of pancreatic cancer and indicate that coordinately targeting cell-cycle checkpoints in concert with chemotherapy could be particularly efficacious.

Interrogating Mutant Allele Expression via Customized Reference Genomes to Define Influential Cancer Mutations.

Genetic alterations are essential for cancer initiation and progression. However, differentiating mutations that drive the tumor phenotype from mutations that do not affect tumor fitness remains a fundamental challenge in cancer biology. To better understand the impact of a given mutation within cancer, RNA-sequencing data was used to categorize mutations based on their allelic expression. For this purpose, we developed the MAXX (Mutation Allelic Expression Extractor) software, which is highly effective at delineating the allelic expression of both single nucleotide variants and small insertions and deletions. Results from MAXX demonstrated that mutations can be separated into three groups based on their expression of the mutant allele, lack of expression from both alleles, or expression of only the wild-type allele. By taking into consideration the allelic expression patterns of genes that are mutated in PDAC, it was possible to increase the sensitivity of widely used driver mutation detection methods, as well as identify subtypes that have prognostic significance and are associated with sensitivity to select classes of therapeutic agents in cell culture. Thus, differentiating mutations based on their mutant allele expression via MAXX represents a means to parse somatic variants in tumor genomes, helping to elucidate a gene's respective role in cancer.

Cell cycle plasticity driven by MTOR signaling: integral resistance to CDK4/6 inhibition in patient-derived models of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC), like many KRAS-driven tumors, preferentially loses CDKN2A that encodes an endogenous CDK4/6 inhibitor to bypass the RB-mediated cell cycle suppression. Analysis of a panel of patient-derived cell lines and matched xenografts indicated that many pancreatic cancers have intrinsic resistance to CDK4/6 inhibition that is not due to any established mechanism or published biomarker. Rather, there is a KRAS-dependent rapid adaptive response that leads to the upregulation of cyclin proteins, which participate in functional complexes to mediate resistance. In vivo, the degree of response is associated with the suppression of a gene expression signature that is strongly prognostic in pancreatic cancer. Resistance is associated with an adaptive gene expression signature that is common to multiple kinase inhibitors, but is attenuated with MTOR inhibitors. Combination treatment with MTOR and CDK4/6 inhibitors had potent activity across a large number of patient-derived models of PDAC underscoring the potential clinical efficacy.

Targeting the Vulnerability of RB Tumor Suppressor Loss in Triple-Negative Breast Cancer.

Approximately 30% of triple-negative breast cancers (TNBCs) exhibit functional loss of the RB tumor suppressor, suggesting a target for precision intervention. Here, we use drug screens to identify agents specifically antagonized by the retinoblastoma tumor suppressor (RB) using CDK4/6 inhibitors. A number of candidate RB-synthetic lethal small molecules were identified, including anti-helmenthics, chemotherapeutic agents, and small-molecule inhibitors targeting DNA-damage checkpoints (e.g., CHK) and chromosome segregation (e.g., PLK1). Counter-screens using isogenic TNBC tumor cell lines and cell panels with varying endogenous RB statuses confirmed that therapeutic effects were robust and selective for RB loss of function. By analyzing TNBC clinical specimens, RB-deficient tumors were found to express high levels of CHK1 and PLK1. Loss of RB specifically resulted in loss of checkpoint functions governing DNA replication, yielding increased drug sensitivity. Xenograft models demonstrated RB-selective efficacy of CHK inhibitors. This study supports the possibility of selectively targeting RB loss in the treatment of TNBC.

Biological specificity of CDK4/6 inhibitors: dose response relationship, in vivo signaling, and composite response signature.

Recently developed potent and selective CDK4/6 inhibitors fall into two classes based on structure and toxicity profiles in clinical studies. One class, exemplified by palbociclib and ribociclib, exhibits neutropenia as a dose-limiting toxicity and requires discontinuous dosing. In contrast, the structurally distinct CDK4/6 inhibitor abemaciclib is dosed continuously, and has diarrhea and fatigue as dose-limiting toxicities. In preclinical models, palbociclib has been extensively studied and induces cell cycle inhibition in an RB-dependent manner. Thus far, abemaciclib has been less extensively evaluated. We found that abemaciclib cell cycle inhibitory activity is RB-dependent at clinically achievable concentrations. Abemaciclib elicited potent suppression of RB/E2F regulated genes associated with prognosis in ER-positive breast cancer. However, unlike palbociclib, at 250nM-1 µM doses abemaciclib induced cell death in RB-deficient cell lines. This response was associated with a rapidly-induced multi-vacuolar phenotype indicative of lysosomal membrane permeabilization that could be ameliorated with chloroquine. This event was not a reflection of inhibition of other CDK family members, but could be recapitulated with CBX4945 that inhibits casein and DYRK/HIPK kinases. To determine if these "off-target" features of abemaciclib were observed in vivo, mice harboring matched RB-positive and negative xenografts were treated with palbociclib and abemaciclib. In vivo, all of the apparent activity of abemaciclib was RB-dependent and strongly elicited suppression of cell cycle regulatory genes in a fashion markedly similar to palbociclib. Using gene expression data from cell lines and tumors treated with abemaciclib and palbociclib a composite signature of response to CDK4/6 inhibition was developed that included many genes that are individually required for tumor cell proliferation or viability. These data indicate that while abemaciclib and palbociclib can exert distinct biological and molecular effects, there are common gene expression features that could be broadly utilized in measuring the response to CDK4/6 inhibition.

Stratification of Pancreatic Ductal Adenocarcinoma: Combinatorial Genetic, Stromal, and Immunologic Markers.

Purpose: Pancreatic ductal adenocarcinoma (PDAC) is associated with an immunosuppressive milieu that supports immune system evasion and disease progression. Here, we interrogated genetic, stromal, and immunologic features of PDAC to delineate impact on prognosis and means to more effectively employ immunotherapy.Experimental Design: A cohort of 109 PDAC cases annotated for overall survival was utilized as a primary discovery cohort. Gene expression analysis defined immunologic subtypes of PDAC that were confirmed in the Cancer Genome Atlas dataset. Stromal and metabolic characteristics of PDAC cases were evaluated by histologic analysis and immunostaining. Enumeration of lymphocytes, as well as staining for CD8, FOXP3, CD68, CD163, PDL1, and CTLA4 characterized immune infiltrate. Neoantigens were determined by analysis of whole-exome sequencing data. Random-forest clustering was employed to define multimarker subtypes, with univariate and multivariate analyses interrogating prognostic significance.Results: PDAC cases exhibited distinct stromal phenotypes that were associated with prognosis, glycolytic and hypoxic biomarkers, and immune infiltrate composition. Immune infiltrate was diverse among PDAC cases and enrichment for M2 macrophages and select immune checkpoints regulators were specifically associated with survival. Composite analysis with neoantigen burden, immunologic, and stromal features defined novel subtypes of PDAC that could have bearing on sensitivity to immunologic therapy approaches. In addition, a subtype with low levels of neoantigens and minimal lymphocyte infiltrate was associated with improved overall survival.Conclusions: The mutational burden of PDAC is associated with distinct immunosuppressive mechanisms that are conditioned by the tumor stromal environment. The defined subtypes have significance for utilizing immunotherapy in the treatment of PDAC. Clin Cancer Res; 23(15); 4429-40. ©2017 AACR.

Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes.

Missense variants represent a significant proportion of variants identified in clinical genetic testing. In the absence of strong clinical or functional evidence, the American College of Medical Genetics recommends that these findings be classified as variants of uncertain significance (VUS). VUSs may be reclassified to better inform patient care when new evidence is available. It is critical that the methods used for reclassification are robust in order to prevent inappropriate medical management strategies and unnecessary, life-altering surgeries. In an effort to provide evidence for classification, several in silico algorithms have been developed that attempt to predict the functional impact of missense variants through amino acid sequence conservation analysis. We report an analysis comparing internally derived, evidence-based classifications with the results obtained from six commonly used algorithms. We compiled a dataset of 1118 variants in BRCA1, BRCA2, MLH1, and MSH2 previously classified by our laboratory's evidence-based variant classification program. We compared internally derived classifications with those obtained from the following in silico tools: Align-GVGD, CONDEL, Grantham Analysis, MAPP-MMR, PolyPhen-2, and SIFT. Despite being based on similar underlying principles, all algorithms displayed marked divergence in accuracy, specificity, and sensitivity. Overall, accuracy ranged from 58.7 to 90.8% while the Matthews Correlation Coefficient ranged from 0.26-0.65. CONDEL, a weighted average of multiple algorithms, did not perform significantly better than its individual components evaluated here. These results suggest that the in silico algorithms evaluated here do not provide reliable evidence regarding the clinical significance of missense variants in genes associated with hereditary cancer.

Comparison of locus-specific databases for BRCA1 and BRCA2 variants reveals disparity in variant classification within and among databases.

Genetic variants of uncertain clinical significance (VUSs) are a common outcome of clinical genetic testing. Locus-specific variant databases (LSDBs) have been established for numerous disease-associated genes as a research tool for the interpretation of genetic sequence variants to facilitate variant interpretation via aggregated data. If LSDBs are to be used for clinical practice, consistent and transparent criteria regarding the deposition and interpretation of variants are vital, as variant classifications are often used to make important and irreversible clinical decisions. In this study, we performed a retrospective analysis of 2017 consecutive BRCA1 and BRCA2 genetic variants identified from 24,650 consecutive patient samples referred to our laboratory to establish an unbiased dataset representative of the types of variants seen in the US patient population, submitted by clinicians and researchers for BRCA1 and BRCA2 testing. We compared the clinical classifications of these variants among five publicly accessible BRCA1 and BRCA2 variant databases: BIC, ClinVar, HGMD (paid version), LOVD, and the UMD databases. Our results show substantial disparity of variant classifications among publicly accessible databases. Furthermore, it appears that discrepant classifications are not the result of a single outlier but widespread disagreement among databases. This study also shows that databases sometimes favor a clinical classification when current best practice guidelines (ACMG/AMP/CAP) would suggest an uncertain classification. Although LSDBs have been well established for research applications, our results suggest several challenges preclude their wider use in clinical practice.