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Pancreatic ductal adenocarcinoma (PDAC) has been classified into classical and basal-like transcriptional subtypes by bulk RNA measurements. However, recent work has uncovered greater complexity to transcriptional subtypes than was initially appreciated using bulk RNA expression profiling. To provide a deeper understanding of PDAC subtypes, we developed a multiplex immunofluorescence (mIF) pipeline that quantifies protein expression of six PDAC subtype markers (CLDN18.2, TFF1, GATA6, KRT17, KRT5, and S100A2) and permits spatially resolved, single-cell interrogation of pancreatic tumors from resection specimens and core needle biopsies. Both primary and metastatic tumors displayed striking intratumoral subtype heterogeneity that was associated with patient outcomes, existed at the scale of individual glands, and was significantly reduced in patient-derived organoid cultures. Tumor cells co-expressing classical and basal markers were present in > 90% of tumors, existed on a basal-classical polarization continuum, and were enriched in tumors containing a greater admixture of basal and classical cell populations. Cell–cell neighbor analyses within tumor glands further suggested that co-expressor cells may represent an intermediate state between expression subtype poles. The extensive intratumoral heterogeneity identified through this clinically applicable mIF pipeline may inform prognosis and treatment selection for patients with PDAC. Significance: A high-throughput pipeline using multiplex immunofluorescence in pancreatic cancer reveals striking expression subtype intratumoral heterogeneity with implications for therapy selection and identifies co-expressor cells that may serve as intermediates during subtype switching.

Resistance to second-generation androgen receptor (AR) antagonists and CYP17 inhibitors in patients with castration-resistant prostate cancer (CRPC) develops rapidly through reactivation of the androgen signaling axis and has been attributed to AR overexpression, production of constitutively active AR splice variants, or the selection for AR mutants with altered ligand-binding specificity. It has been established that androgens induce cell-cycle progression, in part, through upregulation of cyclin D1 (CCND1) expression and subsequent activation of cyclin-dependent kinases 4 and 6 (CDK4/6). Thus, the efficacy of the newly described CDK4/6 inhibitors (G1T28 and G1T38), docetaxel and enzalutamide, was evaluated as single agents in clinically relevant in vitro and in vivo models of hormone-sensitive and treatment-resistant prostate cancer. CDK4/6 inhibition (CDK4/6i) was as effective as docetaxel in animal models of treatment-resistant CRPC but exhibited significantly less toxicity. The in vivo effects were durable and importantly were observed in prostate cancer cells expressing wild-type AR, AR mutants, and those that have lost AR expression. CDK4/6i was also effective in prostate tumor models expressing the AR-V7 variant or the AR F876L mutation, both of which are associated with treatment resistance. Furthermore, CDK4/6i was effective in prostate cancer models where AR expression was lost. It is concluded that CDK4/6 inhibitors are a viable alternative to taxanes as therapeutic interventions in endocrine therapy–refractory CRPC. Implications: The preclinical efficacy of CDK4/6 monotherapy observed here suggests the need for near-term clinical studies of these agents in advanced prostate cancer. Mol Cancer Res; 15(6); 660–9. ©2017 AACR.

Oncogenic KRAS can activate numerous effector pathways to drive malignant progression. However, the relationships between specific effectors and oncogenic phenotypes, and the extent to which these relationships vary across heterogeneous tumors, are incompletely understood. Recently in Cell Reports, a team of scientists described an innovative, combinatorial siRNA-based approach to functionally link KRAS effectors and phenotypes in a large panel of cancer cell lines. Central to this work was the identification of two major subtypes of KRAS-mutant cancers with distinct effector landscapes and tractable therapeutic vulnerabilities.

Background: Pancreatic adenocarcinoma (PDAC) is a rapidly progressive disease, with few molecular markers that stratify patients for survival time or treatment response. Bulk transcriptional analyses of PDAC have identified two major transcriptional subtypes, classical and basal, the latter of which is associated with worse overall survival and limited sensitivity to chemotherapy. However, spatial localization and classical-basal heterogeneity are incompletely understood at the individual cell level within a bulk tumor. Design: We built and validated a multiplex immunofluorescence assay that employs three classical and two basal subtype markers to measure subtype composition at spatially resolved, single cell resolution in a multi-institutional cohort of formalin-fixed paraffin-embedded primary pancreatic cancer resection specimens. Using digital image analysis, supervised machine learning, and Cox proportional hazards regression, we analyzed protein-level classical-basal subtype landscape, cell localization, and outcome associations. Results: Subtyping data were successfully generated for 1.2 million tumor cells across 290 resected tumor specimens (median 3579 cells/tumor). Tumor level analysis of cellular composition revealed that 88% of tumors are “mixed”, harboring any number of both classical and basal cells, whereas tumors composed only of classical or basal cells represented 11% and 1.4% of cases, respectively. In addition to pure classical and basal cells, we identified “hybrid cells” co-expressing basal and classical markers in 79% of cases, ranging in abundance from Citation Format: Hannah L. Williams, Jinming Zhang, Srivatsan Raghavan, Peter S. Winter, Kevin Kapner, Sara Vayrynen, Andressa Dias Costa, Chen Yuan, Mai Chan Lau, Vicente Morales-Oyarvide, Douglas Rubinson, Lauren Brais, Emma Reilly, Margaret Kozak, David Linehan, Richard Dunne, Daniel Chang, Albert Koong, Aram Hezel, William C. Hahn, Alek K. Shalek, Andrew J. Aguirre, Jonathan A. Nowak, Brian M Wolpin. Spatially resolved, single cell assessment of pancreatic ductal adenocarcinoma expression subtypes reveals mixed and hybrid basal-classical marker expression with prognostic significance and discrete spatial localization [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-006.

Metastatic pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal malignancy with few therapeutic options. Tumor transcriptional state is a strong predictor of clinical outcome in PDAC, with two primary cell states, basal-like and classical, identified by bulk transcriptional profiling. Basal-like tumors carry a worse prognosis, but the mechanisms underlying this survival difference, the degree of cellular heterogeneity within a given tumor, and the subtype-specific contributions from the local immune microenvironment are not well understood. In addition, there are ongoing efforts to use patient-derived organoid models as functional surrogates for an individual patient’s disease, but the degree to which patient transcriptional phenotypes are preserved in their matched organoid models remains unclear. Here, we describe a pipeline that enables both direct characterization of the liver metastatic niche via single-cell RNA-sequencing and functional assessment of PDAC tumor biology in patient-matched organoid models. Starting from core needle biopsies of metastatic PDAC lesions, we applied this approach to profile 22 patient samples and their matched organoid models using single-cell RNA-sequencing with Seq-Well. We demonstrate significant heterogeneity at the single-cell level across the basal-like to classical transcriptional spectrum. Basal-like cells expressed more mesenchymal and stem-like features, while classical cells expressed features of epithelial and pancreatic progenitor transcriptional programs. A population of “hybrid” malignant cells co-expressed markers of both basal-like and classical states, suggesting that these phenotypes lie on a continuum rather than as discrete entities. Microenvironmental composition also differed by subtype across T/NK and macrophage populations. Specifically, basal-like tumors exhibited tumor cell crosstalk with specific macrophage subsets, while classical tumors harbored greater immune infiltration and a relatively pro-angiogenic microenvironment, raising important considerations for subtype-specific microenvironmental directed therapy. Finally, we found that matched organoids exhibited transcriptional drift along the basal-like to classical axis relative to their parent tumors, with evidence for selection against basal-like phenotypes in vitro. However, tumor cells in organoid culture exhibited remarkable plasticity and could recover in vivo basal-like phenotypes in response to changes in their growth conditions. Taken together, our work provides a framework for the analysis of human cancers and their matched models using single-cell methods to dissect tumor-intrinsic and extrinsic contributions, and reveals novel insights into the transcriptional heterogeneity and plasticity of PDAC. Citation Format: Srivatsan Raghavan, Peter S. Winter, Andrew W. Navia, Hannah L. Williams, Alan DenAdel, Radha L. Kalekar, Jennyfer Galvez-Reyes, Kristen E. Lowder, Nolawit Mulugeta, Manisha S. Raghavan, Ashir A. Borah, Sara A. Vayrynen, Andressa Dias Costa, Junning Wang, Emma Reilly, Dorisanne Y. Ragon, Lauren K. Brais, Alex M. Jaeger, James M. Cleary, Lorin Crawford, Jonathan A. Nowak, Brian M. Wolpin, William C. Hahn, Andrew J. Aguirre, Alex K. Shalek. Transcriptional subtype-specific microenvironmental crosstalk and tumor cell plasticity in metastatic pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PO-058.

Targeted inhibitors of essential oncogenic kinases induce high rates of clinical response but cure few patients due to the persistence of minimal residual disease (MRD). BCR-ABL mutant leukemias are a classic example of this paradigm where patients usually achieve deep remissions followed by near inevitable relapses. Multiple factors have been shown to influence how an individual patient’s leukemic cells will navigate treatment including differentiation state, mutational background, and communication with the microenvironment. Here, we use BCR-ABL-rearranged acute lymphoblastic leukemia (BCR-ABL ALL) to interrogate cell-autonomous features leading to therapeutic resistance using low-input single-cell assays. Specifically, we use a combination of primary samples and PDX models to dissect aberrant developmental hierarchies and monitor leukemic cell transcriptional and biophysical phenotype at pretreatment, MRD, and relapse. Using machine learning, we relate malignant B cells to normal development, allowing us to define leukemic developmental programs and demonstrate that these have consequences for the time to progression as well as the genetic alterations seen at relapse. Further, we determine that there are unique biophysical features tied to leukemic developmental states and that these integrative properties co-evolve with transcriptional state over the course of treatment. Finally, we demonstrate in PDX studies that it may be possible to intercept relapse by targeting specific features of MRD cells. Together, these data suggest that significant developmental hierarchies exist in ALL, tumor subpopulations can be identified directly within MRD, and their phenotypic and molecular characterization can be exploited to therapeutic effect. Citation Format: Peter S. Winter, Andrew Navia, Haley Strouf, Mahnoor Mirza, Jennyfer Galvez-Reyes, Nolawit Mulugeta, Laura Bilal, Nezha Senhaji, Peter Dennis, Catharine S. Leahy, Kay Shigemori, Foster Powers, Alejandro Gupta, Nicholas Calistri, Alex Van Scoyk, Kristen Jones, Huiyun Liu, Kristen E. Stevenson, Robert Kimmerling, Mark Stevens, David M. Weinstock, Scott R. Manalis, Mark A. Murakami, Alex K. Shalek. Aberrant leukemic developmental hierarchies and MRD-specific targeting informed by single-cell biophysical and molecular profiling [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA20.

The majority of patients with pancreatic ductal adenocarcinoma (PDAC) present with metastatic disease at diagnosis and have median survival times of less than 12 months. Recent studies have demonstrated that PDAC tumors with distinct transcriptional signatures are associated with different clinical outcomes, and that the tumor microenvironment may contribute to PDAC pathogenesis. In parallel, there are ongoing efforts to understand if patient-derived organoid models can be used as functional surrogates for an individual patient’s disease. However, it remains unclear if patient transcriptional phenotypes are preserved in their matched organoid models. Here, we describe a pipeline that permits both direct characterization of the PDAC liver metastatic niche via single-cell RNA-sequencing and functional assessment of PDAC tumor biology in patient-matched organoid models. Starting from core needle biopsies of metastatic PDAC lesions containing 50-100k viable cells, we simultaneously perform (1) low-input single-cell RNA-sequencing using Seq-Well and (2) three-dimensional organoid culture generation. We have applied this approach to profile 21 patients and their matched early passage organoid models. Our pipeline yields high-quality single-cell measurements across diverse cell types—both tumor and nontumor stromal—enabling a principled dissection of tumor intrinsic and extrinsic factors. Evaluation of clinically relevant transcriptional signatures (e.g., basal-like vs. classical) revealed extensive heterogeneity at the single-cell level and identified new, hybrid expression states. We also observed evidence of significant subtype-specific crosstalk between immune populations and tumor cells—specifically between T cells and tumor cells originating from basal-like tumors. Serial sampling at different stages of treatment revealed transcriptional shifts in tumor cells suggestive of significant plasticity. We similarly found that organoids derived from basal-like tumors exhibited considerable plasticity in vitro and had decreased fitness in standard organoid culture conditions, suggesting the need for distinct environments to support specific transcriptional subtypes. Overall, our approach provides actionable insights into the heterogeneity and plasticity of human PDAC, as well as a pipeline and framework for the analysis of PDAC and other cancers. This abstract is also being presented as Poster A50. Citation Format: Peter S. Winter, Srivatsan Raghavan, Andrew W. Navia, Hannah Williams, Jennyfer Galvez-Reyes, Radha Kalekar, Ashir Borah, Alan DenAdel, Manisha Raghavan, Kristen Lowder, Nolawit Mulugeta, Junning Wang, Emma Reilly, Lauren Brais, Lorin Crawford, James McFarland, James M. Cleary, Jonathan Nowak, Brian M. Wolpin, Andrew J. Aguirre, William C. Hahn, Alex K. Shalek. Matched metastatic pancreatic ductal adenocarcinoma biopsies and organoid models reveal tumor cell transcriptional plasticity and subtype-specific microenvironmental crosstalk [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR02.

Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) have few treatment options and continue to have dismal prognoses due to the rapid development of resistance to both standard-of-care and experimental therapies. Several recent studies have demonstrated that patients with distinct PDAC transcriptional subtypes have differing clinical courses, and that the tumor microenvironment can also contribute to patient outcome. However, deep cellular characterization of metastatic PDAC tumors and their stromal microenvironments has been challenging due to limited tissue availability from metastatic liver biopsies. Here, we present a focused assessment of the PDAC liver metastatic niche—encompassing tumor, immune, and stromal cells—via low-input single-cell transcriptional profiling of patient specimens with the goal of developing a deeper understanding of tumor heterogeneity and the tumor microenvironment. Our pipeline accesses core needle biopsies from liver metastases, splitting each core for 1) single-cell RNA sequencing using Seq-Well and 2) organoid generation. Using this pipeline, we have successfully profiled liver metastases from 15 patients along with matched early-passage organoid models. Assessment of clinically relevant transcriptional signatures reveals extensive heterogeneity at the single-cell level and identifies new, hybrid transcriptional states occupied by these metastases. In addition, we observe evidence of significant crosstalk between stromal and immune populations and tumor cells. Serial samples at different stages of therapy show transcriptional shifts in tumor cells suggestive of significant plasticity that likely contributes to therapeutic resistance. Initial analysis of matched organoids at successive passages demonstrates a skew in their clonal composition, as well as evolution of their transcriptional state as compared to their in vivo phenotypes. Overall, our work provides an important window into the biology of metastatic PDAC, as well as some of the first direct comparisons of clonality and transcriptional phenotypes across in vivo specimens and their in vitro organoid counterparts. This abstract is also being presented as Poster C43. Citation Format: Srivatsan Raghavan, Peter S. Winter, Andrew Navia, Radha Kalekar, Jennyfer Galvez-Reyes, Sanjay Prakadan, Junning Wang, Emma Reilly, Lauren Brais, James M. Cleary, Jonathan Nowak, Brian M. Wolpin, Alex K. Shalek, Andrew J. Aguirre, William C. Hahn. Assessment of tumor heterogeneity, clonal evolution, and the stromal microenvironment in metastatic pancreatic ductal adenocarcinoma and matched patient-derived organoids [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr PR15.

Targeted inhibitors of oncogenic kinases have transformed cancer therapy by inducing high rates of clinical response across diverse tumor types, yet they cure few patients due to the persistence of minimal residual disease (MRD), which seeds relapse. Characterizing MRD biology would promote development of more effective therapies tailored to relapse-initiating cells. However, these efforts have been complicated by the technical challenges of isolating and profiling low-frequency tumor populations. We overcome these hurdles by measuring the mass and short-term growth rate of single cells ex vivo using a series of suspended microchannel resonators (SMR) followed by single-cell RNA-seq of the same cells. This platform enables measurement of low input samples to facilitate characterization of MRD subpopulations and functionally drug test MRD-specific vulnerabilities. PDX models of BCR-ABL-rearranged acute lymphoblastic leukemia (BCR-ABL ALL) treated with targeted kinase inhibitors provide a tractable experimental system in which to deploy this platform to interrogate in vivo tumor evolution, MRD, and acquired resistance. We conducted a statistically powered 4-arm randomized phase II-like trial combining ponatinib and the novel allosteric BCR-ABL inhibitor ABL001 in a panel of 13 PDX models of BCR-ABL ALL (total evaluable mice: n=10 vehicle, n=14 ABL001, n=30 ponatinib, n=33 combination). Six of 30 animals receiving ponatinib (20% [95% CI, 8-39%]) and a significantly higher proportion receiving combination (10 of 33, 30% [95% CI, 16-49%]) met the primary endpoint of progression-free survival at 120 days on treatment (p=0.030). No mice in the vehicle or ABL001 arms met this endpoint, and all mice eventually progressed or were found to harbor MRD when sacrificed after treatment courses of up to 248 days. These durable remissions prior to relapse allowed us to delineate in vivo tumor evolution, focusing on MRD, via serial bone marrow aspirates. Drug-persistent marrow-resident leukemia cells exhibit strong enrichment for cellular quiescence programs that extend through MRD and into relapse. These programs are driven by expression of genes known to govern quiescence in hematopoietic stem cells (e.g., EGR1, NR4A1), and their expression correlates with a rare subset of biophysically small cells (mass Citation Format: Mark A. Murakami, Peter S. Winter, Andrew W. Navia, Laura L. Bilal, Haley Strouf, Kay Shigemori, Alejandro Gupta, Mahnoor Mirza, Catharine S. Leahy, Nick Calistri, Kristen Jones, Alexandra Van Scoyk, Huiyun Liu, Foster Powers, Robert Kimmerling, Mark Stevens, Kristen E. Stevenson, Scott R. Manalis, David M. Weinstock, Alex K. Shalek. Single-cell profiling reveals programs mediating oncogenic kinase-independence and minimal residual disease in BCR-ABL-rearranged acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2450.

Despite significant advances in the development of cancer treatment in the last 20 years the best available therapies have marginally improved the survival rate of treated pancreatic cancer patients (from 3% to 6% five-year survival), making it still one the deadliest malignancies. Single standard of care cytotoxic and targeted therapies demonstrate little to no effect on patient survival. Even though we now understand some of the main genetic factors that are mutatated in pancreatic tumors, their role in drug response remains poorly understood. To identify drug-sensitizing genetic targets in cancer cells we have developed a high-throughput screening platform. In this methodology, pooled lentiviral libraries containing hundreds of knockout constructs specific for cancer-related genes are used to infect cancer cells. By treating the infected populations with therapeutic agents we are able to identify genetic targets that when inhibited synergize with existing drugs to cause increased cell death. We piloted this type of screening platform in HCT-116 cells, a KRAS mutant, MEK inhibitor resistant colorectal cancer cell line, using the MEK-inhibitor AZD-2644 and a pooled shRNA library. This study identified 4-7 target genes that when knocked down sensitized the previously resistant HCT-116 cells to AZD-2644. To conduct a more robust and representative sensitization screen we developed a lentiviral CRISPR-Cas9 library. By performing screens in a panel of pancreatic cancer cell lines, we have identified both cell line dependencies and sensitizers to targeted and cytotoxic chemotherapies. The findings from these screens provide potential mechanistic insights into the key survival signaling programs in pancreatic cancer as well as new therapeutic strategies. Citation Format: Edgar Ferrer-Lorenzo, Daniel P. Nussbaum, Peter Winter, Kris Wood. Systematic interrogation of druggable pathways in pancreatic adenocarcinomas using pooled gene-knockdown lentiviral libraries. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5465. doi:10.1158/1538-7445.AM2015-5465

Understanding the mechanisms of resistance to anticancer therapies may improve personalized treatment regimens and responses to therapy. The mitochondrial apoptosis pathway is activated by most targeted and cytotoxic therapies and represents a node that may be modulated for broad therapy resistance. It has been shown that some cancers, especially those of hematopoietic origin, are primed for apoptosis (as measured by BH3 Profiling) and consequently undergo apoptosis readily in response to therapies while others are unprimed and resistant. However, despite the importance of apoptotic priming in governing response to anticancer therapies, the upstream molecular determinants of apoptotic priming are unknown. Prior work has shown that oncogenes, including c-Myc, can sensitize some cells to apoptosis. We therefore hypothesized that lineage programming and activation of oncogenes may modulate apoptotic priming in normal cells undergoing neoplastic transformation. Using numerous in vitro and in vivo ovarian, breast, kidney and liver tumorigenesis models we discovered that the strongest determinant of apoptotic priming and chemosensitivity in a cancer cell is the level of priming measured in the cell of origin. To illustrate, ovarian adenocarcinomas, which originate from primed ovarian or fallopian tube epithelia, are considerably more primed than hepatocellular carcinomas originating from unprimed precursors. Notably, we also found that activation of certain oncogenes can meaningfully increase apoptotic priming and chemosensitivity while others decrease it. For example, transformation of normal epithelial cells via forced expression of the c-Myc oncogene increased priming and chemosensitivity. In contrast, activation of Ras in isogenic cells dramatically decreased both priming and chemosensitivity. We have systematically characterized the effects of 27 oncogenes on apoptotic priming and chemosensitivity including PI3K, Notch, Src, BRAF, β-catenin, Akt, and Aurora B kinase. Certain subsets of oncogenes consistently reduced apoptotic priming in cells undergoing transformation and, in combination with cell lineage programs, established broad resistance to targeted and cytotoxic therapies. Importantly, our experimental findings are complemented by clinical correlates. Overall, this work may aid efforts to deploy personalized and efficacious cancer treatments and enhance our knowledge of how cancers evade cell death, which is a hallmark of cancer. Citation Format: Kristopher A. Sarosiek, Alison Karst, Peter Winter, Antonio Sorrentino, Sourav Bandyopadhyay, Andrei Goga, Kris C. Wood, Ronny Drapkin, Anthony Letai. Broad therapy resistance is induced by suppression of apoptotic priming by lineage programs and oncogenic activation. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 970. doi:10.1158/1538-7445.AM2015-970

Background: MLN2480 is an orally administered, investigational small molecule pan-RAF kinase inhibitor currently in Phase 1 clinical development. Here, we built integrated PK/PD/efficacy models to understand the relationship between MAPK pathway inhibition and efficacy as well as the effect of dose schedule in two melanoma xenograft models, A375 and SKMEL-2. Materials and Methods: We fit a one-compartment PK model to MLN2480 plasma concentration time profiles following a single dose in mice. Tumor pERK levels in xenograft-bearing mice, measured by Western blotting following single (A375) or multiple (SKMEL-2) doses of MLN2480 were fit to a direct or indirect inhibitory Emax model, respectively, to describe the PK/PD relationship between the plasma concentration and %pERK inhibition. Activity in each xenograft was evaluated as the percent growth rate inhibition (%GRI), the percent change between treated and control exponential tumor volume growth rates over the treatment cycle. To connect PK, PD, and efficacy for each xenograft, we simulated the PK and PD profiles over the treatment cycle for each dose group, and estimated the averages of plasma concentration (Cavg) and %pERK inhibition, respectively, using non-compartmental analysis. Results: From a multiple linear regression, schedule-related parameters are not predictive for drug effect demonstrating schedule-independent activity. For a variety of dose schedules, the relationship between total dose and SKMEL-2 xenograft growth rate is approximately linear (R = 0.90, p < 0.0001). A sigmoidal PK/efficacy model captures the relationship between Cavg and %GRI for both xenografts. A375 exhibits greater sensitivity than SKMEL-2 to the same Cavg of MLN2480, with the models predicting tumor regression (Emax = 172% GRI) and stasis (Emax = 102% GRI) as the maximal effects, respectively. Both xenografts have steep, sigmoidal PD/efficacy relationships, which show the same pERK inhibition is associated with greater %GRI in A375, and %GRI saturates with residual pERK (EC90 = 38% in A375, 22% in SKMEL-2). Conclusions: Integrated PK/PD and PK/efficacy modeling for MLN2480 response in A375 and SKMEL-2 xenografts shows a strong relationship between pERK inhibition and preclinical activity, and that maximal effect is achieved without complete inhibition of the MAPK pathway. The findings of pERK inhibition-dependent but not schedule-dependent activity provide translational guidance to clinical dose and schedule selection.