CCR5 and CCL5 gene expression in colorectal cancer: comprehensive profiling and clinical value

BACKGROUND

The C-C motif chemokine receptor 5 (CCR5)/C-C motif chemokine ligand 5 (CCL5) axis plays a major role in colorectal cancer (CRC). We aimed to characterize the molecular features associated with CCR5/CCL5 expression in CRC and to determine whether CCR5/CCL5 levels could impact treatment outcomes.

METHODS

7604 CRCs tested with NextGen Sequencing on DNA and RNA were analyzed. Molecular features were evaluated according to CCR5 and CCL5 tumor gene expression quartiles. The impact on treatment outcomes was assessed in two cohorts, including 6341 real-world patients and 429 patients from the Cancer and Leukemia Group B (CALGB)/SWOG 80405 trial.

RESULTS

CCR5/CCL5 expression was higher in right-sided versus left-sided tumors, and positively associated with consensus molecular subtypes 1 and 4. Higher CCR5/CCL5 expression was associated with higher tumor mutational burden, deficiency in mismatch repair and programmed cell death ligand 1 (PD-L1) levels. Additionally, high CCR5/CCL5 were associated with higher immune cell infiltration in the tumor microenvironment (TME) of MMR proficient tumors. Ingenuity pathway analysis revealed upregulation of the programmed cell death protein 1 (PD-1)/PD-L1 cancer immunotherapy pathway, phosphatase and tensin homolog (PTEN) and peroxisome proliferator-activated receptors (PPAR) signaling, and cytotoxic T-lymphocyte antigen 4 (CTLA-4) signaling in cytotoxic T lymphocytes, whereas several inflammation-related pathways were downregulated. Low CCR5/CCL5 expression was associated with increased benefit from cetuximab-FOLFOX treatment in the CALGB/SWOG 80405 trial, where significant treatment interaction was observed with biologic agents and chemotherapy backbone.

CONCLUSIONS

Our data show a strong association between CCR5/CCL5 gene expression and distinct molecular features, gene expression profiles, TME cell infiltration, and treatment benefit in CRC. Targeting the CCR5/CCL5 axis may have clinical applications in selected CRC subgroups and may play a key role in developing and deploying strategies to modulate the immune TME for CRC treatment.

A novel thin plate spline methodology to model tissue surfaces and quantify tumor cell invasion in organ-on-chip models

Organ-on-chip (OOC) models can be useful tools for cancer drug discovery. Advances in OOC technology have led to the development of more complex assays, yet analysis of these systems does not always account for these advancements, resulting in technical challenges. A challenging task in the analysis of these two-channel microfluidic models is to define the boundary between the channels so objects moving within and between channels can be quantified. We propose a novel imaging-based application of a thin plate spline method - a generalized cubic spline that can be used to model coordinate transformations - to model a tissue boundary and define compartments for quantification of invaded objects, representing the early steps in cancer metastasis. To evaluate its performance, we applied our analytical approach to an adapted OOC developed by Emulate, Inc., utilizing a two-channel system with endothelial cells in the bottom channel and colorectal cancer (CRC) patient-derived organoids (PDOs) in the top channel. Initial application and visualization of this method revealed boundary variations due to microscope stage tilt and ridge and valley-like contours in the endothelial tissue surface. The method was functionalized into a reproducible analytical process and web tool - the Chip Invasion and Contour Analysis (ChICA) - to model the endothelial surface and quantify invading tumor cells across multiple chips. To illustrate applicability of the analytical method, we applied the tool to CRC organoid-chips seeded with two different endothelial cell types and measured distinct variations in endothelial surfaces and tumor cell invasion dynamics. Since ChICA utilizes only positional data output from imaging software, the method is applicable to and agnostic of the imaging tool and image analysis system used. The novel thin plate spline method developed in ChICA can account for variation introduced in OOC manufacturing or during the experimental workflow, can quickly and accurately measure tumor cell invasion, and can be used to explore biological mechanisms in drug discovery.

Integration of Patient-Derived Organoids and Organ-on-Chip Systems: Investigating Colorectal Cancer Invasion within the Mechanical and GABAergic Tumor Microenvironment

Three-dimensional (3D) in vitro models are essential in cancer research, but they often neglect physical forces. In our study, we combined patient-derived tumor organoids with a microfluidic organ-on-chip system to investigate colorectal cancer (CRC) invasion in the tumor microenvironment (TME). This allowed us to create patient-specific tumor models and assess the impact of physical forces on cancer biology. Our findings showed that the organoid-on-chip models more closely resembled patient tumors at the transcriptional level, surpassing organoids alone. Using 'omics' methods and live-cell imaging, we observed heightened responsiveness of KRAS mutant tumors to TME mechanical forces. These tumors also utilized the γ-aminobutyric acid (GABA) neurotransmitter as an energy source, increasing their invasiveness. This bioengineered model holds promise for advancing our understanding of cancer progression and improving CRC treatments.

Phosphorylation and stabilization of EZH2 by DCAF1/VprBP trigger aberrant gene silencing in colon cancer

Our recent work has shown that DCAF1 (also known as VprBP) is overexpressed in colon cancer and phosphorylates histone H2AT120 to drive epigenetic gene inactivation and oncogenic transformation. We have extended these observations by investigating whether DCAF1 also phosphorylates non-histone proteins as an additional mechanism linking its kinase activity to colon cancer development. We now demonstrate that DCAF1 phosphorylates EZH2 at T367 to augment its nuclear stabilization and enzymatic activity in colon cancer cells. Consistent with this mechanistic role, DCAF1-mediated EZH2 phosphorylation leads to elevated levels of H3K27me3 and altered expression of growth regulatory genes in cancer cells. Furthermore, our preclinical studies using organoid and xenograft models revealed that EZH2 requires phosphorylation for its oncogenic function, which may have therapeutic implications for gene reactivation in colon cancer cells. Together, our data define a mechanism underlying DCAF1-driven colonic tumorigenesis by linking DCAF1-mediated EZH2 phosphorylation to EZH2 stability that is crucial for establishing H3K27me3 and gene silencing program.

Phenotypic deconvolution in heterogeneous cancer cell populations using drug-screening data

Tumor heterogeneity is an important driver of treatment failure in cancer since therapies often select for drug-tolerant or drug-resistant cellular subpopulations that drive tumor growth and recurrence. Profiling the drug-response heterogeneity of tumor samples using traditional genomic deconvolution methods has yielded limited results, due in part to the imperfect mapping between genomic variation and functional characteristics. Here, we leverage mechanistic population modeling to develop a statistical framework for profiling phenotypic heterogeneity from standard drug-screen data on bulk tumor samples. This method, called PhenoPop, reliably identifies tumor subpopulations exhibiting differential drug responses and estimates their drug sensitivities and frequencies within the bulk population. We apply PhenoPop to synthetically generated cell populations, mixed cell-line experiments, and multiple myeloma patient samples and demonstrate how it can provide individualized predictions of tumor growth under candidate therapies. This methodology can also be applied to deconvolution problems in a variety of biological settings beyond cancer drug response.

Organs-on-chips: a decade of innovation

Recreating 'living organs' with groundbreaking organ-on-a-chip (OOC) technologies is facilitating a new era of drug discovery. Studies by Huh et al. and Ronaldson-Bouchard et al. underscore advances made over a decade, spanning single organ functionality to interconnected organs, that enable examination of drug toxicities and disease pathogenesis in reconstituted tissues.

Breast cancer and neurotransmitters: emerging insights on mechanisms and therapeutic directions

Exploring the relationship between various neurotransmitters and breast cancer cell growth has revealed their likely centrality to improving breast cancer treatment. Neurotransmitters play a key role in breast cancer biology through their effects on the cell cycle, epithelial mesenchymal transition, angiogenesis, inflammation, the tumor microenvironment and other pathways. Neurotransmitters and their receptors are vital to the initiation, progression and drug resistance of cancer and progress in our biological understanding may point the way to lower-cost and lower-risk antitumor therapeutic strategies. This review discusses multiple neurotransmitters in the context of breast cancer. It also discusses risk factors, repurposing of pharmaceuticals impacting neurotransmitter pathways, and the opportunity for better integrated models that encompass exercise, the intestinal microbiome, and other non-pharmacologic considerations. Neurotransmitters' role in breast cancer should no longer be ignored; it may appear to complicate the molecular picture but the ubiquity of neurotransmitters and their wide-ranging impacts provide an organizing framework upon which further understanding and progress against breast cancer can be based.

Abstract A17: Development of a 3D tunable platform to measure the impact of patient-derived organoids on macrophage polarization

There is an increasing need to develop physiologically relevant models that recapitulate the complexity of the human tumor microenvironment (TME) to better understand and treat cancer. Macrophages are a major component of the TME, with high macrophage infiltration linked to poor prognosis in several cancer types. Tumor-associated macrophages have been reported to promote tumor progression, contribute to immune suppression, and limit the efficacy of therapy. Therefore, our goal is to develop a 3D tunable cell culture model that enables the study of macrophage and cancer cell interactions in an environment that more closely mimics the tumor milieu and to serve as a platform for screening therapies that target or reprogram macrophages. Simplistically, macrophages can be polarized into pro-inflammatory (M1) or immune-suppressive (M2) states in response to stimuli from the TME. To examine the crosstalk between cancer cells and macrophages, we first evaluated the signaling pathways and functional metabolic markers of a murine macrophage cell line J774A.1 and a human monocytic cell line THP-1. Treatment of both cell lines with M1 (LPS + IFN-g) and M2 (IL-4) inducers yielded STAT1 and STAT6 activation, respectively. Arginine metabolism by nitric oxide synthase (iNOS) in M1 macrophages and arginase (Arg-1) in M2 macrophages produces nitric oxide and polyamine metabolites. Treatment with M1 and M2 inducers yielded respective iNOS and Arg-1 expressions in J774A.1 cells, but not in THP-1 cells. However, other metabolic markers such as IDO and TGM2 were upregulated by M1 and M2 inducers in THP-1 cells, suggesting that arginine may be metabolized differently in human and mouse macrophages. Furthermore, tumor-conditioned media from murine triple-negative breast cancer 4T1 cells polarized J774A.1 cells toward M2-like macrophages, independent of STAT6 signaling. We extended these studies to co-cultures of macrophages and patient-derived tumor organoids. We established a diverse biobank of patient-derived organoids from breast and colorectal cancer tissues. Using a high-content imaging-based workflow, we examined the inter-patient effect of organoids on the polarization of THP-1 cells by staining and quantifying the expression of M1 and M2 markers. In summary, the methodologies we are employing to interrogate the involvement of macrophages in cancer could provide new insights into critical TME features that contribute to macrophage polarization and offer a venue for evaluating the efficacy of macrophage-targeted therapies.

Citation Format: Chun-Te Chiang, Danielle Hixon, Nevart Mooradian, Seungil Kim, Aaron G. Baugh, Evanthia T. Roussos Torres, Shannon M. Mumenthaler. Development of a 3D tunable platform to measure the impact of patient-derived organoids on macrophage polarization [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr A17.

Neurotransmitter signaling: a new frontier in colorectal cancer biology and treatment

The brain-gut axis, a bidirectional network between the central and enteric nervous system, plays a critical role in modulating the gastrointestinal tract function and homeostasis. Recently, increasing evidence suggests that neuronal signaling molecules can promote gastrointestinal cancers, however, the mechanisms remain unclear. Aberrant expression of neurotransmitter signaling genes in colorectal cancer supports the role of neurotransmitters to stimulate tumor growth and metastatic spread by promoting cell proliferation, migration, invasion, and angiogenesis. In addition, neurotransmitters can interact with immune and endothelial cells in the tumor microenvironment to promote inflammation and tumor progression. As such, pharmacological targeting of neurotransmitter signaling represent a promising novel anticancer approach. Here, we present an overview of the current evidence supporting the role of neurotransmitters in colorectal cancer biology and treatment.

Abstract 3080: A quality-controlled patient-derived tumor organoid biobank facilitates applications such as an integrated database of chemotherapeutic drug response using deep learning-based imaging methods

Patient-derived tumor organoids (PDTOs) have recently been used as an innovative preclinical model to predict patient-specific drug responses. However, it is critical to establish high quality, reproducible, and well-annotated PDTOs that closely recapitulate the original tumors from which they were derived. Here, we established a biobank of over 20 colorectal cancer (CRC) PDTOs representing a racially and ethnically diverse patient population that has been subjected to rigorous quality control (QC) measures. We demonstrate the utility of a well-characterized biobank across several applications including the development of an integrated chemotherapeutic drug response database and image-based phenotypic analyses using deep-learning neural networks (NNs).

To ensure consistency across our biobank, PDTOs were subjected to a meticulous processing pipeline which includes the extensive collection of pertinent culturing metadata (i.e., multi-timepoint brightfield images pre- and post-passaging for consistent size and health of the PDTOs, short tandem repeat sequencing to establish a unique patient barcode, and routine mycoplasma testing results to minimize contamination) and DNA/RNA sequencing to verify the PDTOs reflect the genetic profile of the original tumor. A dashboard is used to manage culturing and characterization tasks across the Cell Line Team and samples are registered in a Lab Information Management System (LIMS) for tracking of data associated with the samples, including detailed patient information.

Our high-quality biobank supports a diverse project portfolio including the creation of a database of PDTO drug responses to clinically-approved chemotherapy treatments 5-Fluorouracil and Irinotecan. This database compares PDTO-specific dose-response curves between ATP-based viability assays and image-based NN analysis and we found the IC50 values from the two analytical methods to be comparable. The NNs were designed to segment and classify organoids as live or dead from brightfield images. The label-free, non-destructive nature of this method enables dynamic imaging and analysis over multiple timepoints. Notably, our biobank and NN analysis work in concert where the biobank provides valuable, consistent datasets that are used to train and validate NNs and the NN is subsequently used to understand phenotypic drug responses of PDTOs. From these results we can show inter-patient heterogeneity in drug responses.

In conclusion, we generated a reliable biobank to support numerous applications including the creation of a PDTO drug response database with deep learning validation. Such a biobank is only feasible through meticulous QC and can serve as a great resource to understand treatment outcomes and identify better therapeutic options for patients in the future.

Citation Format: Scott Valena, Pratiksha Kshetri, Brandon Choi, Ah Young Yoon, Shohei Imamura, Seungil Kim, Michael E. Doche, Shannon M. Mumenthaler. A quality-controlled patient-derived tumor organoid biobank facilitates applications such as an integrated database of chemotherapeutic drug response using deep learning-based imaging methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3080.

Abstract 3858: Peristalsis-like mechanical stimuli in the intestinal milieu promotes colorectal cancer invasion through GABAergic signaling changes in an organ-on-chip platform

Mechanical forces in the tumor microenvironmental milieu are often understudied due to a lack of relevant preclinical model systems. Here we describe a microfluidic organ-on-chip platform that incorporates tissue-tissue interfaces and physical forces to aid in the examination of colorectal cancer (CRC) progression. A major advantage of this model is the ability to mimic peristalsis, a physiological process occurring in the gut. Live-cell imaging with a 3D printed organ-on-chip cradle was used to quantify the number of CRC cells that have invaded from the epithelial channel into the vascular channel over time. We determined that peristalsis-like motions in our organ-on-chip model enhanced the invasion capacity of CRC cells, mimicking intravasation. We subsequently examined the effluent media in stretched compared to non-stretched conditions using mass spectrometry based metabolomics and discovered an increase in the secretion of gamma-aminobutyric acid (GABA) by CRC cells, implicating peristalsis-mediated tumor cell invasion with neurotransmitter release. Inhibitors targeting the GABA-A receptor reversed the observed tumor cell invasion phenotype when cells were subjected to peristalsis-like motions. Interestingly, even in the absence of peristalsis, tumor cell invasion was promoted when GABA agonists were introduced into the organ-on-chip system. This work reveals important interactions between CRC cells and their microenvironment, and that disrupting GABAergic signaling might be an approach to prevent or delay cancer progression.

Citation Format: Carly Strelez, Sujatha Chilakala, Kimya Ghaffarian, Ah Young Yoon, Jonathan Katz, Shannon M. Mumenthaler. Peristalsis-like mechanical stimuli in the intestinal milieu promotes colorectal cancer invasion through GABAergic signaling changes in an organ-on-chip platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3858.

Comprehensive profiling of clock genes expression in colorectal cancer (CRC)

3129

Background: Disruption of the circadian clock has been linked to cancer risk, development and progression. Core clock proteins are emerging as novel therapeutic targets in cancer. We previously showed that polymorphisms in clock genes were associated with anti-VEGF treatment outcome in metastatic CRC. Here we further evaluated the molecular landscape of clock pathway alterations in CRC. Methods: 7591 CRC tested at Caris Life Sciences (Phoenix, AZ) with WTS (Illumina NovaSeq) and NextGen DNA sequencing (NextSeq, 592 Genes and NovaSEQ, WES) were analyzed. Clock gene Score (CS) was determined using expression of core clock genes Z scores (positives of CLOCK, ARNTL, RORA/B/C and negatives of repressors CRY1/2, PER1/2/3, REVERBA/B) stratified by quartiles. xCell was used to quantify cell infiltration in the tumor microenvironment (TME). Consensus molecular subtypes (CMS) were assessed by RNAseq. Significance was determined as P-values adjusted for multiple testing ( q) of <.05. Real world survival was obtained from insurance claims data and Kaplan-Meier estimates were calculated for comparison. Results: CS was higher in primary tumors than metastases and in right- than left-sided CRC ( P <.001). Liver metastases were associated with lower CS (23% Q1 vs 19% Q4, P <.001). CS was positively associated with CMS1 and 3 (21 vs 11% and 23 vs 9%, respectively, Q4 vs Q1) and negatively correlated with CMS2 and 4 (22 vs 32% and 34 vs 48%) (all P <.001). These associations were confirmed in mismatch repair proficient (pMMR) tumors. Overall, TMB-H and dMMR/MSI-H were positively associated with CS (11 vs 6% and 8 vs 4%, Q4 vs Q1, q <.0001) and PD-L1 showed a similar trend ( P <.01, q =.06); the association with TMB-H was not significant in pMMR. High CS was associated with alterations of genes in WNT signaling, RAS, PI3K, TGF-β, and NOTCH pathways, while negatively associated with TP53 mutations, HER2 expression and CDX2 copy numbers, confirmed in pMMR (all q <.05). CS negatively correlated with the angiogenesis pathway signature (Q1 vs Q4 Z score: 6.6 vs -4.6, P <.001). B cells, M1 and M2 macrophages, neutrophils, NK, Tregs, CD4+ and CD8+ T cells, and myeloid dendritic cells were more abundant in the TME of tumors with high CS while cancer associated fibroblasts were lower, regardless of MMR status (all q <.001). Individually, ARNTL tumor expression below median was associated with better OS (overall: HR 0.88, 95% CI [0.82-0.94]; pMMR: HR 0.88 [0.81-0.94]) and longer time on treatment of bevacizumab (overall: HR 0.91 [0.83-0.99]; pMMR: HR 0.91 [0.83-0.99]). Conclusions: This is the most extensive profiling study to investigate the expression of clock genes in CRC. Our data show that clock genes expression is strongly associated with distinct molecular features, immune cell infiltration, angiogenesis pathway enrichment and patient outcomes. These findings support the clock pathway as a therapeutic target in CRC, with a major role in CRC biology and TME modulation.

Predictive value of MAOB gene expression for targeted therapy in patients (pts) with metastatic colorectal cancer (mCRC) enrolled in CALGB (Alliance)/SWOG 80405

3580

Background: Monoamine oxidases (MAOs), including MAOA and MAOB, are mitochondrial enzymes responsible for catalyzing monoamine oxidation. Increased expression of MAOs were found in several cancer types and high MAOB was associated with worse disease stage and poorer survival in CRC. Positive and negative correlations of MAOB expression with mesenchymal type and epithelial type gene expressions, respectively, have been reported. Hence, we investigated whether MAOB expression is predictive for targeted therapies in mCRC. Methods: 430 mCRC pts treated with either bevacizumab (BEV, n = 224) or cetuximab (CET, n = 206) in combination with first-line chemotherapy within the CALGB/SWOG 80405 trial were included in the analysis. MAOB RNA was isolated from FFPE tumor samples and sequenced on the HiSeq 2500 (Illumina). Overall survival (OS) and progression-free survival (PFS) were compared between groups of pts categorized by tertiles of MAOB expression into high (H), medium (M) and low (L). Hazard ratios (HR) and 95% confidence intervals (CI) were computed from multivariable Cox proportional hazards model, adjusting for age, sex, location, number of metastases, KRAS, MSI status, and treatment with FOLFOX or FOLFIRI. Sensitivity analyses were conducted after stratifying by sex. Logrank P-values describe differences without adjustment for patient characteristics. Results: In CET-treated pts, MAOB-L showed significantly longer OS (median 39.2 vs 30.9 vs 15.9 months, logrank P = 4.7E-05, L vs H (as reference) adjusted HR 0.42, 95% CI [0.27, 0.65]) and PFS (median 13.2 vs 11.8 vs 7.6 months, logrank P = 0.006, L vs H adjusted HR 0.59 [0.40, 0.88]) compared to MAOB-M and MAOB-H, respectively. Similar results were observed when evaluating MAOB expression as a continuous variable. In BEV-treated pts, no significant differences were observed when comparing MAOB expression tertiles; however, pts with lower MAOB expression had significantly better OS, but not PFS, when evaluating MAOB as a continuous variable (Cox LRT P = 0.015, covariate adjusted). In CET-treated pts, the effect of MAOB expression was observed in male but not female pts (OS: median 40.3 vs 30.9 vs 16.1 months by MAOB-L, M, H, respectively, logrank P = 6.8E-05, L vs H adjusted HR 0.33 [0.19, 0.59]; PFS: median 13.8 vs 12.6 vs 7.9 months, logrank P = 0.001, L vs H adjusted HR 0.46 [0.28, 0.79]). A significant interaction was observed between MAOB expression and treatment for OS ( P = 0.010) in males and females combined, but only in males ( P = 0.018) when stratified by sex. Conclusions: Our results suggest that pts with MAOB-L tumors may have greater benefit from CET-based treatment and that targeting MAOB may be a promising strategy to improve patient outcomes. Further validation studies are warranted to develop a novel personalized approach based on MAOB expression in mCRC pts. Clinical trial information: NCT00265850.

Roadmap on plasticity and epigenetics in cancer

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response

Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, and temporal response dynamics. Here, we present an image-based high-content assay that provides object level information on 3D patient-derived tumor organoids without the need for vital dyes. Leveraging computer vision, we segment and define organoids as independent regions of interest and obtain morphometric and textural information per organoid. By acquiring brightfield images at different timepoints in a robust, non-destructive manner, we can track the dynamic response of individual organoids to various drugs. Furthermore, to simplify the analysis of the resulting large, complex data files, we developed a web-based data visualization tool, the Organoizer, that is available for public use. Our work demonstrates the feasibility and utility of using imaging, computer vision and machine learning to determine the vital status of individual patient-derived organoids without relying upon vital dyes, thus taking advantage of the characteristics offered by this preclinical model system.

Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics

Colorectal cancer (CRC) is a major cause of morbidity and mortality in the United States. Tumor-stromal metabolic crosstalk in the tumor microenvironment promotes CRC development and progression, but exactly how stromal cells, in particular cancer-associated fibroblasts (CAFs), affect the metabolism of tumor cells remains unknown. Here we take a data-driven approach to investigate the metabolic interactions between CRC cells and CAFs, integrating constraint-based modeling and metabolomic profiling. Using metabolomics data, we perform unsteady-state parsimonious flux balance analysis to infer flux distributions for central carbon metabolism in CRC cells treated with or without CAF-conditioned media. We find that CAFs reprogram CRC metabolism through stimulation of glycolysis, the oxidative arm of the pentose phosphate pathway (PPP), and glutaminolysis, as well as inhibition of the tricarboxylic acid cycle. To identify potential therapeutic targets, we simulate enzyme knockouts and find that CAF-treated CRC cells are especially sensitive to inhibitions of hexokinase and glucose-6-phosphate, the rate limiting steps of glycolysis and oxidative PPP. Our work gives mechanistic insights into the metabolic interactions between CRC cells and CAFs and provides a framework for testing hypotheses towards CRC-targeted therapies.

Reprogramming CBX8-PRC1 function with a positive allosteric modulator

Canonical targeting of Polycomb repressive complex 1 (PRC1) to repress developmental genes is mediated by cell-type-specific, paralogous chromobox (CBX) proteins (CBX2, 4, 6, 7, and 8). Based on their central role in silencing and their dysregulation associated with human disease including cancer, CBX proteins are attractive targets for small-molecule chemical probe development. Here, we have used a quantitative and target-specific cellular assay to discover a potent positive allosteric modulator (PAM) of CBX8. The PAM activity of UNC7040 antagonizes H3K27me3 binding by CBX8 while increasing interactions with nucleic acids. We show that treatment with UNC7040 leads to efficient and selective eviction of CBX8-containing PRC1 from chromatin, loss of silencing, and reduced proliferation across different cancer cell lines. Our discovery and characterization of UNC7040 not only reveals the most cellularly potent CBX8-specific chemical probe to date, but also corroborates a mechanism of Polycomb regulation by non-specific CBX nucleotide binding activity.

Immunogenic cell death pathway polymorphisms for predicting oxaliplatin efficacy in metastatic colorectal cancer

Background

Immunogenic cell death (ICD) is a tumor cell death involving both innate and adaptive immune responses. Given published findings that oxaliplatin, but not irinotecan, drives ICD, we investigated whether single nucleotide polymorphisms (SNPs) in the ICD pathway are associated with the efficacy of oxaliplatin-based chemotherapy in metastatic colorectal cancer (mCRC).

Methods

Two randomized clinical trials data were analyzed: discovery cohort, FOLFOX/bevacizumab arm (MAVERICC); validation cohort, FOLFOXIRI/bevacizumab arm (TRIBE); and two control cohorts, FOLFIRI/bevacizumab arms (both trials). Genomic DNA extracted from blood samples was genotyped. Ten SNPs in the ICD pathway were tested for associations with clinical outcomes.

Results

In total, 648 patients were included. In the discovery cohort, three SNPs were significantly associated with clinical outcomes in univariate analysis: CALR rs1010222 with progression-free survival (G/G vs any A, HR=0.61, 95% CI 0.43–0.88), ANXA1 rs1050305 with overall survival (OS) (A/A vs any G, HR=1.87, 95% CI 1.04–3.35), and LRP1 rs1799986 with OS (C/C vs any T, HR=1.69, 95% CI 1.07–2.70). Multivariate analysis confirmed the trend, but statistical significance was not reached. In the validation cohort, ANXA1 rs1050305, and LRP1 rs1799986 were validated to have the significant associations with clinical outcome. No significant associations of these SNPs were observed in the two control cohorts. Treatment-by-SNP interaction test confirmed the predictive values.

Conclusions

The predictive utility of ICD-related SNPs for the efficacy of oxaliplatin-based chemotherapy was demonstrated, warranting further validation studies to be translated into personalized treatment strategies using conventional cytotoxic agents in mCRC.

3D cell culture models: Drug pharmacokinetics, safety assessment, and regulatory consideration

Nonclinical testing has served as a foundation for evaluating potential risks and effectiveness of investigational new drugs in humans. However, the current two-dimensional (2D) in vitro cell culture systems cannot accurately depict and simulate the rich environment and complex processes observed in vivo, whereas animal studies present significant drawbacks with inherited species-specific differences and low throughput for increased demands. To improve the nonclinical prediction of drug safety and efficacy, researchers continue to develop novel models to evaluate and promote the use of improved cell- and organ-based assays for more accurate representation of human susceptibility to drug response. Among others, the three-dimensional (3D) cell culture models present physiologically relevant cellular microenvironment and offer great promise for assessing drug disposition and pharmacokinetics (PKs) that influence drug safety and efficacy from an early stage of drug development. Currently, there are numerous different types of 3D culture systems, from simple spheroids to more complicated organoids and organs-on-chips, and from single-cell type static 3D models to cell co-culture 3D models equipped with microfluidic flow control as well as hybrid 3D systems that combine 2D culture with biomedical microelectromechanical systems. This article reviews the current application and challenges of 3D culture systems in drug PKs, safety, and efficacy assessment, and provides a focused discussion and regulatory perspectives on the liver-, intestine-, kidney-, and neuron-based 3D cellular models.

VprBP directs epigenetic gene silencing through histone H2A phosphorylation in colon cancer

Histone modification is aberrantly regulated in cancer and generates an unbalanced state of gene transcription. VprBP, a recently identified kinase, phosphorylates histone H2A on threonine 120 (T120) and is involved in oncogenic transcriptional dysregulation; however, its specific role in colon cancer is undefined. Here, we show that VprBP is overexpressed in colon cancer and directly contributes to epigenetic gene silencing and cancer pathogenesis. Mechanistically, the observed function of VprBP is mediated through H2AT120 phosphorylation (H2AT120p)‐driven transcriptional repression of growth regulatory genes, resulting in a significantly higher proliferative capacity of colon cancer cells. Our preclinical studies using organoid and xenograft models demonstrate that treatment with the VprBP inhibitor B32B3 impairs colonic tumor growth by blocking H2AT120p and reactivating a transcriptional program resembling that of normal cells. Collectively, our work describes VprBP as a master kinase contributing to the development and progression of colon cancer, making it a new molecular target for novel therapeutic strategies.

Abstract 5: Experimentally-driven mathematical model of tumor angiogenesis mediated by multiple angiogenic factors

Tumor angiogenesis is regulated by multiple pro- and anti-angiogenic factors. Anti-angiogenic drugs target the interconnected network of these angiogenic factors to inhibit neovascularization and tumor growth. However, current anti-angiogenic therapeutics targeting a single angiogenic factor show limited clinical success, prompting the development of combination anti-angiogenic therapy targeting multiple angiogenic factors simultaneously. In cases where anti-angiogenic therapy may be effective, tumors display a wide range of responses, which is not fully understood.

In this work, we use an integrative in vitro imaging and mathematical modeling approach to investigate how tumor angiogenesis is systematically regulated by multiple angiogenic factors and to study the effects of anti-angiogenic therapy. We particularly focus on two pro-angiogenic factors, vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (FGF2), and two anti-angiogenic factors, thrombospondin-1 (TSP1) and platelet factor 4 (PF4). In our in vitro experimental setting human endothelial cells are cultured in a microfluidic organ-on-chip chip platform exposed to angiogenic factors or in the presence of cancer cells to mimic the tumor microenvironment. The cellular responses induced by various concentrations of angiogenic factors are measured through a high content screening (HCS) confocal imaging system to quantify the cell counts, morphological features and vessel characteristics. These data are used to construct a novel mathematical model to capture how the angiogenic factors mediate cross-talk between tumor cells and endothelial cells. By fitting the model to the experimental measurements, we are able to predict the temporal dynamics of cell numbers and concentrations of the angiogenic factors.

Using the model, we generate insights into the effects of angiogenic factors and various anti-angiogenic treatments on tumor cells and endothelial cells. Excitingly, the model can also be applied to investigate how the effect of anti-angiogenic therapy is influenced by inter-tumor heterogeneity. For example, we identified that tumors with lower tumor cell growth rate and higher carrying capacity have a stronger response to anti-VEGF treatment, which indicates that variation in tumor cell growth rates can be a main reason for the observed heterogenous response to anti-VEGF therapy. In addition, we investigate a novel hypothesis regarding synergy between anti-angiogenic and chemotherapeutic agents with the model. Our simulated results suggest a new mechanism in which the chemotherapeutic agent enhances anti-angiogenic therapy simply through reducing the tumor cell growth rate.

Overall, this work generates novel insights into the function of multiple angiogenic factors in tumor angiogenesis, providing a tool that can be further used to test and optimize anticancer therapy.

Citation Format: Ding Li, Danielle D. Hixon, Shannon M. Mumenthaler, Stacey D. Finley. Experimentally-driven mathematical model of tumor angiogenesis mediated by multiple angiogenic factors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 5.

Abstract 2989: Peristalsis-like deformations influence tumor cell intravasation and metabolic reprogramming in a novel colorectal cancer-on-chip model

Colorectal cancer (CRC) is one of the deadliest cancers in the U.S., yet we still understand very little about the mechanisms behind this disease. Therefore, we are developing a CRC-Chip model that recapitulates the complex nature of cancer progression in order to increase our understanding of CRC and accelerate the discovery of new treatments. The organ-on-chip technology developed by Emulate, Inc. maintains physiologically relevant aspects of organ structure and function by incorporating tissue compartments and mechanical forces to mimic in vivo peristalsis and fluid flow. The CRC-Chip consists of two microfluidic compartments separated by a porous membrane, with endothelial cells in the bottom channel and normal colon epithelial cells plus fluorescently-labeled CRC cell lines in the top channel. Via confocal microscopy, We observed monitored cancer cells intravasating from the epithelial compartment into the blood vessel compartment via confocal microscopy, mimicking early metastatic spread. A unique advantage of this system is the ability to interrogate how mechanical forces influence cancer cell intravasation. The presence of peristalsis-like deformations increased the invasion rate of cancer cells. To further investigate the increased aggressiveness, viable tumor cells were collected from the effluent of the blood vessel channel reservoir. These shedded circulating cells, representing the invaded CRC cells, showed markers of epithelial to mesenchymal transition (EMT) induction and changes in adhesive properties. To further understand how peristalsis influences CRC cells, we performed mass-spectrometry based metabolomics on the effluent from the top and bottom channels of CRC-chips in the presence or absence of peristalsis-like motions. The differentially expressed metabolites, when mapped with Ingenuity Pathway Analysis, indicated changes primarily to amino acid/central carbon metabolism in the epithelial channel and differential lipid profiles in the endothelial channel when peristalsis was present. Given a majority of CRC metastases occur in the liver, we optimized the coupling of our CRC-Chip with a normal Liver-Chip model to better understand how intravasated tumor cells from a peristaltic colon environment colonize a healthy liver. This work illuminates the important role of mechanical forces in CRC progression, a currently understudied aspect of the tumor microenvironment. Further insights into a better understanding of how peristalsis increases the metastatic spread of CRC cells may lead to the discovery of novel therapeutic strategies that can halt critical steps in tumor progression.

Citation Format: Carly Strelez, Sujatha Chilakala, Ah Young Yoon, Kimya Ghaffarian, Danielle Hixon, Roy Lau, Jonathan E. Katz, Shannon M. Mumenthaler. Peristalsis-like deformations influence tumor cell intravasation and metabolic reprogramming in a novel colorectal cancer-on-chip model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2989.

Human colorectal cancer-on-chip model to study the microenvironmental influence on early metastatic spread

Colorectal cancer (CRC) progression is a complex process that is not well understood. We describe an in vitro organ-on-chip model that emulates in vivo tissue structure and the tumor microenvironment (TME) to better understand intravasation, an early step in metastasis. The CRC-on-chip incorporates fluid flow and peristalsis-like cyclic stretching and consists of endothelial and epithelial compartments, separated by a porous membrane. On-chip imaging and effluent analyses are used to interrogate CRC progression and the resulting cellular heterogeneity. Mass spectrometry-based metabolite profiles are indicative of a CRC disease state. Tumor cells intravasate from the epithelial channel to the endothelial channel, revealing differences in invasion between aggressive and non-aggressive tumor cells. Tuning the TME by peristalsis-like mechanical forces, the epithelial:endothelial interface, and the addition of fibroblasts influences the invasive capabilities of tumor cells. The CRC-on-chip is a tunable human-relevant model system and a valuable tool to study early invasive events in cancer.

Comprehensive characterization of neurotransmitters and neuronal signaling (NT) pathway alterations in colorectal cancer (CRC)

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Background: Aberrant NT signaling has been shown to activate uncontrolled proliferation and dissemination in several gastrointestinal cancer types. Neurotransmitters have been shown to affect endothelial cells and immune cells in the tumor microenvironment to promote tumor progression. We previously showed that single nucleotide polymorphisms in the dopamine and GABA pathways are associated with outcome in patients with metastatic CRC receiving first-line treatment. Here we further evaluated the distribution and molecular context of NT pathway alterations in CRC. Methods: A total of 7,595 CRC tumors tested at Caris Life Sciences (Phoenix, AZ) with NextGen Sequencing on DNA (Next Seq, 592 genes or NovaSeq, WES) and RNA (NovaSeq, WTS) were analyzed. ssGSEA (single-sample gene set enrichment analysis) was used to calculate pathway enrichment scores (ES) of 7 NT gene sets (GABA, nicotinic, muscarinic, dopamine (DA), reelin, glial cell line-derived neurotrophic factor and neurotrophins). X2/Fisher-Exact was used for comparison and significance was determined as p-value adjusted for multiple comparison of ( q) < 0.05. Results: ES based on sample sites showed a substantial heterogeneity in NT enrichment. Notably, when compared to primary tumors, all 7 gene sets were significantly enriched in brain metastases (mets; ES ratio 1.14-1.55), while abdomen, liver, and peritoneal mets displayed significant decreases in most NT gene sets. DA was enriched in ovarian and lung mets (ES ratio: 1.18 and 1.09, respectively), the latter also showing increased neurotrophins ES (1.06) (all q < 0.05). When investigating primary tumors grouped according to overall ES by unsupervised clustering, right-sided and CMS4 CRCs were more prevalent in the high ES cluster compared to the low ES cluster (32 vs 29%, P = 0.02 and 46 vs 30%, P < 0.001, respectively). In addition, tumors in the high ES cluster showed lower prevalence of TMB-H (≥ 10mt/MB) (7 vs 10%), MSI-H (6 vs 10%) and PD-L1 (2 vs 6%), while higher CNA rates were noted in 9 genes (all q < 0.05). High ES tumors showed significant positive associations with microenvironment infiltration of B cells, T cells (NK, CD4+ and CD8+ T cells, but not Treg), M2 Macrophages, Myeloid Dendritic Cell, Neutrophils, and an inverse association with M1 Macrophages, regardless of MSI status ( q < 0.05). Conclusions: This is the first and most extensive molecular profiling study to investigate NT signaling pathway alterations in CRC. Our data show a distinct distribution of pathway enrichment according to metastatic site, distinct molecular features in high vs low ES clusters in primary tumors (including CMS subtypes, TMB, MSI and PD-L1 rates), and differential immune cell infiltration. These findings support the role of NT signaling in the metastatic spread of CRC and modulation of tumor immune microenvironment.

Germline polymorphisms in genes maintaining replication fork to predict the efficacy of oxaliplatin and irinotecan in metastatic colorectal cancer (mCRC) patients enrolled in MAVERICC trial

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Background: Protection of replication forks is critical for the survival of cancer cells. Chemotherapeutic drugs such as oxaliplatin and irinotecan can impede the progression of replication forks by inducing DNA lesions, which cause fork collapse and generate double-strand breaks. We hypothesized that functional genetic variants in genes involved in the maintenance of replication forks may predict the efficacy of cytotoxic drugs in mCRC patients. Methods: We analyzed genomic and clinical data from MAVERICC, a phase II trial which compared mFOLFOX6 and FOLFIRI in combination with bevacizumab in untreated mCRC patients. Genomic DNA extracted from blood samples was genotyped using an OncoArray (Illumina, Inc., San Diego, CA, USA). Candidate six missense single nucleotide polymorphisms (SNPs) ( SLFN11 rs9898983, SLFN11 rs12453150, RPA1 rs5030749, MCM3 rs2230240, TIMELESS rs2291739, and TIMELESS rs774047) were tested for association with progression-free survival (PFS) and overall survival (OS), using Cox proportional hazards model. To confirm the predictive value, the treatment-by-SNP interaction was tested. Results: A total of 324 patients were available for the SNP analyses (mFOLFOX6 plus bevacizumab arm [OHP arm]: n = 161; FOLFIRI plus bevacizumab arm [IRI arm]: n = 163). In the OHP arm, univariable analysis showed a significantly better PFS in patients with G/G genotype of TIMELESS rs2291739 compared to those with any A allele, and in patients with T/T genotype of TIMELESS rs774047 compared to those with any C allele. However, neither of these SNP’s associations were confirmed by multivariable analysis: TIMELESS rs2291739 (any A allele vs G/G, hazard ratio [HR] = 0.60, 95% confidence interval [CI] = 0.31–1.17, p = 0.12) and TIMELESS rs774047 (any C allele vs T/T, HR = 0.74, 95% CI = 0.41–1.36, p = 0.33). In the IRI arm, univariable analysis showed a significantly worse OS in patients with G/G genotype of TIMELESS rs2291739 compared to those with any A allele, and in patients with T/T genotype of TIMELESS rs774047 compared to those with any C allele. Multivariable analysis confirmed the significant associations in these SNPs: TIMELESS rs2291739 (any A allele vs G/G, HR = 3.06, 95% CI = 1.49–6.25, p < 0.01) and TIMELESS rs774047 (any C allele vs T/T, HR = 2.95, 95% CI = 1.43–6.08, p < 0.01). Treatment-by-SNP interaction test confirmed the significant predictive value of both SNPs, both on PFS and OS. Conclusions: Germline polymorphisms in the TIMELESS gene involved in the protection of replication forks may predict efficacy of oxaliplatin and irinotecan in mCRC patients. Our novel findings warrant further validation studies.

Germ line polymorphisms of genes involved in pluripotency transcription factors predict efficacy of cetuximab in metastatic colorectal cancer

BACKGROUND

Cancer stem cells (CSCs) are primarily maintained by a network of pluripotency transcription factors (PTFs). Given a close relationship of CSC regulation with epidermal growth factor receptor and vascular endothelial growth factor signalling, we investigated whether single-nucleotide polymorphisms (SNPs) in PTF genes are related to the efficacy of cetuximab and/or bevacizumab in patients with metastatic colorectal cancer (mCRC).

PATIENTS AND METHODS

Genomic and clinical data from three independent clinical trial cohorts were tested: cetuximab cohort (FOLFIRI/cetuximab arm in FIRE-3, n = 129), bevacizumab cohort 1 (FOLFIRI/bevacizumab arm in FIRE-3, n = 107) and bevacizumab cohort 2 (FOLFIRI/bevacizumab arm in TRIBE, n = 215). Genomic DNA extracted from blood samples was genotyped, and ten SNPs were tested for association with clinical outcomes.

RESULTS

In the cetuximab cohort, four SNPs were significantly associated with progression-free survival in univariate analysis: NANOG rs11055767 (any A allele vs C/C, hazard ratio [HR] = 0.62, 95% confidence interval [CI] = 0.42-0.94, p = 0.02), NANOG rs10744044 (any A allele vs G/G, HR = 0.59, 95% CI = 0.39-0.90, p = 0.01), NANOGP8 rs2168958 (any C allele vs A/A, HR = 2.12, 95% CI = 1.36-3.29, p < 0.001) and NANOGP8 rs2279066 (any C allele vs T/T, HR = 1.80, 95% CI = 1.06-1.68, p = 0.03). Multivariate analysis confirmed the significant associations for NANOGP8 rs2168958 and NANOGP8 rs2279066. In either bevacizumab cohort, no significant associations were observed in univariate analysis.

CONCLUSIONS

Germ line polymorphisms in the PTF genes could be predictive markers for cetuximab in mCRC.

High-throughput microscopy reveals the impact of multifactorial environmental perturbations on colorectal cancer cell growth

Background

Colorectal cancer (CRC) mortality is principally due to metastatic disease, with the most frequent organ of metastasis being the liver. Biochemical and mechanical factors residing in the tumor microenvironment are considered to play a pivotal role in metastatic growth and response to therapy. However, it is difficult to study the tumor microenvironment systematically owing to a lack of fully controlled model systems that can be investigated in rigorous detail.

Results

We present a quantitative imaging dataset of CRC cell growth dynamics influenced by in vivo–mimicking conditions. They consist of tumor cells grown in various biochemical and biomechanical microenvironmental contexts. These contexts include varying oxygen and drug concentrations, and growth on conventional stiff plastic, softer matrices, and bioengineered acellular liver extracellular matrix. Growth rate analyses under these conditions were performed via the cell phenotype digitizer (CellPD).

Conclusions

Our data indicate that the growth of highly aggressive HCT116 cells is affected by oxygen, substrate stiffness, and liver extracellular matrix. In addition, hypoxia has a protective effect against oxaliplatin-induced cytotoxicity on plastic and liver extracellular matrix. This expansive dataset of CRC cell growth measurements under in situ relevant environmental perturbations provides insights into critical tumor microenvironment features contributing to metastatic seeding and tumor growth. Such insights are essential to dynamical modeling and understanding the multicellular tumor-stroma dynamics that contribute to metastatic colonization. It also establishes a benchmark dataset for training and testing data-driven dynamical models of cancer cell lines and therapeutic response in a variety of microenvironmental conditions.

RNA-Binding Protein Polymorphisms as Novel Biomarkers to Predict Outcomes of Metastatic Colorectal Cancer: A Meta-analysis from TRIBE, FIRE-3, and MAVERICC

RNA-binding proteins (RBPs) regulate many posttranscriptional cellular activities. Accumulating evidence suggests associations between RBPs with colonic tumorigenesis and chemosensitivity. We investigated the prognostic and predictive values of SNPs of genes encoding RBPs in metastatic colorectal cancer (mCRC), using clinical and genomic data from three randomized clinical trials of standard first-line chemotherapy for mCRC (TRIBE, FIRE-3, and MAVERICC). Genomic DNA extracted from blood samples was genotyped using an OncoArray. We tested 30 candidate SNPs of 10 major RBP-related genes with additive models. Prognostic values were estimated by meta-analysis approach. Treatment-by-SNP interactions were tested to estimate predictive values for targeted drugs and cytotoxic backbone chemotherapies. This study included 884 patients. The meta-analysis revealed prognostic values of LIN28B rs314277 [HR, 1.26; 95% confidence interval (CI), 1.06-1.49, P = 0.005, FDR-adjusted P = 0.072 for overall survival (OS)] and LIN28B rs314276 (HR, 1.25; 95% CI, 1.08-1.44, P = 0.002, FDR-adjusted P = 0.062 for OS). Although some SNPs showed potentially predictive values, these associations were not confirmed after FDR adjustment. In conclusion, the results of this study are warranting additional studies to provide the evidence that RBP-related SNPs may be associated with the prognosis of patients with mCRC treated with standard first-line chemotherapies. In addition, further studies are warranted to study the predictive value.

Impact of tumor-parenchyma biomechanics on liver metastatic progression: a multi-model approach

Colorectal cancer and other cancers often metastasize to the liver in later stages of the disease, contributing significantly to patient death. While the biomechanical properties of the liver parenchyma (normal liver tissue) are known to affect tumor cell behavior in primary and metastatic tumors, the role of these properties in driving or inhibiting metastatic inception remains poorly understood, as are the longer-term multicellular dynamics. This study adopts a multi-model approach to study the dynamics of tumor-parenchyma biomechanical interactions during metastatic seeding and growth. We employ a detailed poroviscoelastic model of a liver lobule to study how micrometastases disrupt flow and pressure on short time scales. Results from short-time simulations in detailed single hepatic lobules motivate constitutive relations and biological hypotheses for a minimal agent-based model of metastatic growth in centimeter-scale tissue over months-long time scales. After a parameter space investigation, we find that the balance of basic tumor-parenchyma biomechanical interactions on shorter time scales (adhesion, repulsion, and elastic tissue deformation over minutes) and longer time scales (plastic tissue relaxation over hours) can explain a broad range of behaviors of micrometastases, without the need for complex molecular-scale signaling. These interactions may arrest the growth of micrometastases in a dormant state and prevent newly arriving cancer cells from establishing successful metastatic foci. Moreover, the simulations indicate ways in which dormant tumors could "reawaken" after changes in parenchymal tissue mechanical properties, as may arise during aging or following acute liver illness or injury. We conclude that the proposed modeling approach yields insight into the role of tumor-parenchyma biomechanics in promoting liver metastatic growth, and advances the longer term goal of identifying conditions to clinically arrest and reverse the course of late-stage cancer.

Abstract B15: Metabolic imaging of patient-derived tumor organoids provides a fast and dynamic readout of drug response

Patient-derived tumor organoids are a more physiologically relevant 3D cell culture model system amenable to drug screening. However, several challenges exist with this model system, including the ability to maintain the heterocellular complexity of the original tumor microenvironment (TME) as well as the ability to interrogate this complexity in a quantitative and dynamic manner. To overcome these challenges, we employ fluorescence lifetime imaging microscopy (FLIM) to measure the metabolic activity of unlabeled patient-derived colorectal cancer (CRC) organoids in response to drug perturbations. FLIM relies on the exponential decay rates of fluorescent molecules. By measuring autofluorescent signals from coenzyme NADH, we determined the metabolic state of individual organoids by representing the ratio of free and protein-bound NADH on a 2D phasor plot. Using a confocal microscope, we acquired z-stack images of patient-derived organoids at multiple time points in the presence and absence of clinically relevant chemotherapy and targeted agents (i.e., 5-fluorouracil, SN-38 [active metabolite of irinotecan], and cetuximab). Unlike traditional viability assays that measure the metabolic activity of a population of organoids and provide a single readout at a fixed time point, we can use FLIM to dynamically measure the metabolic activity of individual organoids and capture intra- and interpatient heterogeneity. We were able to detect drug responses in a dose-dependent manner by measuring a shift towards oxidative phosphorylation prior to an increase in fluorescent signal from a vital dye detecting cell death. Thus, FLIM can capture early drug-mediated changes in organoids on the order of hours compared to vital dyes, which are on the order of days. Additionally, cancer cells are in physical and biochemical contact with many different stromal cell types native to the host environment. Cancer-associated fibroblasts (CAFs) are the dominant stromal cell type within the TME and have been linked with increased tumor cell survival and protection against drug-induced apoptosis. When we cocultured organoids with CAFs, we were able to distinguish the metabolic signatures of each cell type without the need for fluorescent labels. Moreover, we quantified the drug-induced metabolic shifts at the IC50 value when CAFs were present. In conclusion, our imaging-based approach has advantages over traditional drug screening methods (e.g., ATP measurements, phototoxic dyes) by capturing the dynamics and heterogeneity of patient-specific drug responses. We are implementing this workflow to better understand the interactions between cancer cells and their microenvironment in the context of drug response.

Citation Format: Emma J. Fong, Seungil Kim, Shannon M. Mumenthaler. Metabolic imaging of patient-derived tumor organoids provides a fast and dynamic readout of drug response [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 B15.

Anti-EGFR Therapy Induces EGF Secretion by Cancer-Associated Fibroblasts to Confer Colorectal Cancer Chemoresistance

Targeted agents have improved the efficacy of chemotherapy for cancer patients, however, there remains a lack of understanding of how these therapies affect the unsuspecting bystanders of the stromal microenvironment. Cetuximab, a monoclonal antibody therapy targeting the epidermal growth factor receptor (EGFR), is given in combination with chemotherapy as the standard of care for a subset of metastatic colorectal cancer patients. The overall response to this treatment is underwhelming and, while genetic mutations that confer resistance have been identified, it is still not known why this drug is ineffective for some patients. We discovered that cancer-associated fibroblasts (CAFs), a major cellular subset of the tumor stroma, can provide a source of cancer cell resistance. Specifically, we observed that upon treatment with cetuximab, CAFs increased their secretion of EGF, which was sufficient to render neighboring cancer cells resistant to cetuximab treatment through sustained mitogen-activated protein kinases (MAPK) signaling. Furthermore, we show the cetuximab-induced EGF secretion to be specific to CAFs and not to cancer cells or normal fibroblasts. Altogether, this work emphasizes the importance of the tumor microenvironment and considering the potential unintended consequences of therapeutically targeting cancer-driving proteins on non-tumorigenic cell types.

Comparison of Cell and Organoid-Level Analysis of Patient-Derived 3D Organoids to Evaluate Tumor Cell Growth Dynamics and Drug Response

3D cell culture models have been developed to better mimic the physiological environments that exist in human diseases. As such, these models are advantageous over traditional 2D cultures for screening drug compounds. However, the practicalities of transitioning from 2D to 3D drug treatment studies pose challenges with respect to analysis methods. Patient-derived tumor organoids (PDTOs) possess unique features given their heterogeneity in size, shape, and growth patterns. A detailed assessment of the length scale at which PDTOs should be evaluated (i.e., individual cell or organoid-level analysis) has not been done to our knowledge. Therefore, using dynamic confocal live cell imaging and data analysis methods we examined tumor cell growth rates and drug response behaviors in colorectal cancer (CRC) PDTOs. High-resolution imaging of H2B-GFP-labeled organoids with DRAQ7 vital dye permitted tracking of cellular changes, such as cell birth and death events, in individual organoids. From these same images, we measured morphological features of the 3D objects, including volume, sphericity, and ellipticity. Sphericity and ellipticity were used to evaluate intra- and interpatient tumor organoid heterogeneity. We found a strong correlation between organoid live cell number and volume. Linear growth rate calculations based on volume or live cell counts were used to determine differential responses to therapeutic interventions. We showed that this approach can detect different types of drug effects (cytotoxic vs cytostatic) in PDTO cultures. Overall, our imaging-based quantification workflow results in multiple parameters that can provide patient- and drug-specific information for screening applications.

A Perspective on Expanding Our Understanding of Cancer Treatments by Integrating Approaches from the Biological and Physical Sciences

Multicellular systems such as cancer suffer from immense complexity. It is imperative to capture the heterogeneity of these systems across scales to achieve a deeper understanding of the underlying biology and develop effective treatment strategies. In this perspective article, we will discuss how recent technologies and approaches from the biological and physical sciences have transformed traditional ways of measuring, interpreting, and treating cancer. During the SLAS 2019 Annual Meeting, SBI² hosted a Special Interest Group (SIG) on this topic. Academic and industry leaders engaged in discussions surrounding what biological model systems are appropriate to study cancer complexity, what assays are necessary to interrogate this complexity, and how physical sciences approaches may be useful to detangle this complexity. In particular, we examined the utility of mathematical models in predicting cancer progression and treatment response when tightly integrated with reproducible, quantitative, and dynamic biological measurements achieved using high-content imaging and analysis. The dialogue centered around the impetus for convergent biosciences, bringing new perspectives to cancer research to further understand this complex adaptive system and successfully intervene therapeutically.

Genetic variants in immunogenic cell death (ICD) relating genes to predict outcome in metastatic colorectal cancer (mCRC): Data from FIRE-3, TRIBE and MAVERICC trials

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Background: ICD is an immune response against dead-cell antigens from cancer cells treated with cytotoxic and/or targeted therapies. Oxaliplatin (OHP) and cetuximab (Cet) are distinct drugs to elicit ICD, while most other anticancer agents kill cancer cells in a nonimmunogenic manner. We hypothesized that genetic variants in ICD-related genes could predictive efficacy of OHP and/or Cet in mCRC. Methods: We analyzed data of mCRC patients enrolled in three 1st-line randomized trials [FIRE-3: FOLFIRI+Cet vs FOLFIRI+bevacizumab (Bev), TRIBE: FOLFOXIRI+Bev vs FOLFIRI+Bev and MAVERICC: FOLFOX+Bev vs FOLFIRI+Bev]. Genomic DNA from blood samples was genotyped through the OncoArray, a custom array manufactured by Illumina. Candidate 14 SNPs in five ICD-related genes ( CALR, HMGB1, ANXA1, LRP1 and P2RX7) were tested for association with progression-free survival (PFS) and overall survival (OS), using Cox proportional hazards model. We tested treatment-by-SNP interactions in the following cohorts: combined TRIBE and MAVERICC (OHP-containing treatment vs non-OHP-containing treatment), and FIRE-3 (FOLFIRI+Cet vs FOLFIRI+Bev). An interaction p-value (i p) < 0.05 was considered significant. Results: Totally, 890 patients’ SNPs were available (FIRE-3: n = 236, TRIBE: n = 324, and MAVERICC: n = 330). In the combined TRIBE and MAVERICC cohorts [the reference of hazard ratio (HR) is non-OHP-containing treatment], a significant interaction was observed in ANXA1 rs1050305 (A/A: HR 0.96, Any G: HR 2.62, i p < 0.01), LRP1 rs1466535 (G/G: HR 1.39, Any A: HR 0.91, i p = 0.02), P2RX7 rs2230911 (C/C: HR 0.98, Any G: HR 1.76, i p = 0.03) and P2RX7 rs208294 (C/C: HR 1.82, Any T: HR 0.93, i p < 0.01) on OS. For PFS, that was observed in CALR rs110222 (G/G: HR 1.30, Any A: HR 0.87, i p = 0.02), HMGB1 rs1045411 (C/C: HR 0.85, Any T: HR 1.30, i p = 0.04) and HMGB1 rs1360485 (T/T: HR 0.81, Any C: HR 1.40, i p < 0.01). However, in the FIRE-3 cohort, no significant interactions were observed in any SNPs. Conclusions: Our results showed for the first time that SNPs in ICD-related genes may predict efficacy of OHP-containing treatment in mCRC. But the predictive values for Cet efficacy was not evident.

A truncating mutation in the autophagy gene UVRAG drives inflammation and tumorigenesis in mice

Aberrant autophagy is a major risk factor for inflammatory diseases and cancer. However, the genetic basis and underlying mechanisms are less established. UVRAG is a tumor suppressor candidate involved in autophagy, which is truncated in cancers by a frameshift (FS) mutation and expressed as a shortened UVRAGFS. To investigate the role of UVRAGFS in vivo, we generated mutant mice that inducibly express UVRAGFS (iUVRAGFS). These mice are normal in basal autophagy but deficient in starvation- and LPS-induced autophagy by disruption of the UVRAG-autophagy complex. iUVRAGFS mice display increased inflammatory response in sepsis, intestinal colitis, and colitis-associated cancer development through NLRP3-inflammasome hyperactivation. Moreover, iUVRAGFS mice show enhanced spontaneous tumorigenesis related to age-related autophagy suppression, resultant β-catenin stabilization, and centrosome amplification. Thus, UVRAG is a crucial autophagy regulator in vivo, and autophagy promotion may help prevent/treat inflammatory disease and cancer in susceptible individuals.

AMPK variant, a candidate of novel predictor for chemotherapy in metastatic colorectal cancer: A meta-analysis using TRIBE, MAVERICC and FIRE3

AMP-activated protein kinase (AMPK) is a key sensor of energy homeostasis and regulates cell metabolism, proliferation and chemotherapy/radiotherapy sensitivities. This study aimed to explore the relationship between the AMPK pathway-related single nucleotide polymorphisms (SNPs) and clinical outcomes in patients with metastatic colorectal cancer (mCRC). We analyzed a total of 884 patients with mCRC enrolled in three randomized clinical trials (TRIBE, MAVERICC and FIRE-3: where patients were treated with FOLFIRI, mFOLFOX6 or FOLFOXIRI combined with bevacizumab or cetuximab as the first-line chemotherapy). The association between AMPK pathway-related SNPs and clinical outcomes was analyzed across the six treatment cohorts, using a meta-analysis approach. Our meta-analysis showed that AMPK pathway had significant associations with progression-free survival (PFS; p < 0.001) and overall survival (OS; p < 0.001), but not with tumor response (TR; p = 0.220): PRKAA1 rs13361707 was significantly associated with favorable PFS (log HR = -0.219, SE = 0.073, p = 0.003), as well as PRKAA1 rs10074991 (log HR = -0.215, SE = 0.073, p = 0.003), and there were suggestive associations of PRKAG1 rs1138908 with unfavorable OS (log HR = 0.170, SE = 0.083, p = 0.041), and of UBE2O rs3803739 with unfavorable PFS (log HR = 0.137, SE = 0.068, p = 0.042) and OS (log HR = 0.210, SE = 0.077, p = 0.006), although these results were not significant after false discovery rate adjustment. AMPK pathway-related SNPs may be predictors for chemotherapy in mCRC. Upon validation, our findings would provide novel insight for selecting treatment strategies.

Genetic variants in RNA binding protein (RBP) to predict outcome in metastatic colorectal cancer (mCRC): Data from FIRE-3, TRIBE, and MAVERICC trials

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Background: RNA binding proteins (RBPs) post-transcriptionally regulate gene expression by stabilizing or destabilizing target messenger RNA. Although alteration of RBPs affects many steps of cancer development, its clinical implication in mCRC remains unclear. Methods: We analyzed data from mCRC patients (pts) enrolled in three first-line randomized trials (FIRE-3, TRIBE, and MAVERICC). Genomic DNA from blood samples of pts was genotyped through the OncoArray, a custom array manufactured by Illumina. Candidate 30 SNPs in 10 RBP genes (MSI1, MSI2, ELAVL1, RBM3, LIN28A, LIN28B, IGF2BP1, IGF2BP2, IGF2BP3, ZFP36) were tested on association with progression-free survival (PFS) and overall survival (OS). To evaluate prognostic effects and heterogeneities across treatment arms, meta-analysis approach using the METASOFT software was conducted. We also tested interaction between each SNP and treatment within each trial, i.e. FIRE-3 cohort (FOLFIRI+cetuximab (Cet) vs FOLFIRI+bevacizumab (Bev)) and MAVERICC cohort (FOLFIRI+Bev vs FOLFOX6+Bev). For multiple testing, p values were adjusted by the false discovery rate (FDR) method. Results: A total of 884 pts’ SNPs data were available (FIRE-3: n = 236, TRIBE: n = 324, and MAVERICC: n = 324). Meta-analysis combining three trials showed RBM3 rs926152 (adjusted p = 0.045) and RBM3 rs2249585 (adjusted p = 0.016) were significantly prognostic for PFS. Whereas, in terms of OS, only LIN28B rs314277 (adjusted p = 0.045) was significant, and RBM3 rs926152 (adjusted p = 0.057) and RBM3 rs2249585 (adjusted p = 0.059) had a trend. Interaction test showed several SNPs were potentially predictive (raw p < 0.05), although without any significance after FDR adjustment: in FIRE-3 cohort, MSI2 rs1822381, RBM3 rs926152, LIN28B rs221635, IGF2BP1 rs2969 for OS; in MAVERICC cohort, MSI1 rs1179442 and MSI2 rs3826301 for OS, ELAVL1 rs4804244 for PFS. Conclusions: Our results indicate prognostic potential of SNPs in RBP genes, such as RBM3 and LIN28B, in mCRC. However, we find no distinct evidence that these SNPs can predict differential effect between Cet and Bev, or between oxaliplatin- and irinotecan-based chemotherapy.

Impact of polymorphisms within genes involved in regulating DNA methylation in patients with metastatic colorectal cancer enrolled in three independent, randomised, open-label clinical trials: a meta-analysis from TRIBE, MAVERICC and FIRE-3

BACKGROUND

CpG island DNA hypermethylation and global DNA hypomethylation are hallmark characteristics of colorectal cancer (CRC). Therefore, we aim to explore the effect of genetic variations within the genes that regulate the DNA methylation and demethylation pathways on outcomes in patients with metastatic CRC (mCRC) treated with first-line therapy and enrolled in three independent, randomised, open-label clinical trials.

METHODS

A total of 884 patients with mCRC enrolled in TRIBE, MAVERICC and FIRE-3 trials were included. Single-nucleotide polymorphisms (SNPs) within genes involved in DNA methylation and demethylation pathways were analysed. The prognostic value of each SNP across all treatment arms was quantified using the inverse-variance-weighted effect size, a meta-analysis approach implemented in the METASOFT software.

RESULTS

In the meta-analysis, DNMT3A rs11681717 was significantly associated with overall survival (hazard ratio = 1.26; 95% confidence interval [CI] 1.08-1.46; P = 0.002; false discovery rate [FDR] = 0.016), accounting for seven tests in the DNA methylation pathway. In addition, there was suggestive evidence of association for ten-eleven translocation (TET) genes variance with tumour response (TET1 rs3814177, odds ratio [OR] = 0.76, 95% CI 0.59-0.97, P = 0.025, FDR = 0.087; TET3 rs7560668, OR = 1.44; 95% CI 1.10-1.89; P = 0.009; FDR = 0.062).

CONCLUSIONS

We showed that polymorphisms within the genes responsible for the DNA methylation and demethylation machineries are correlated with outcomes in patients with mCRC who were enrolled in three independent, randomised, open-label, phase II/III clinical trials. In addition, we demonstrated the feasibility of a meta-analysis approach to identify stronger and more convincing association between gene polymorphisms and outcome, potentially leading the way to a new method of analysis for similar data set.

Th17 cell pathway-related genetic variants in metastatic colorectal cancer: A meta-analysis using TRIBE, MAVERICC, and FIRE-3

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Background: Th17 cells constitute a subset of T-helper cells, and play a role in immune response to extracellular pathogens in the human intestinal tract. Further, Th17 cells are associated with tumor angiogenesis and enhanced efficacy of 5-FU treatment. We thus investigated associations between the Th17 cell pathway-related SNPs and clinical outcomes in patients with metastatic colorectal cancer (mCRC) treated with conventional chemotherapy. Methods: We analyzed a total of 884 patients with mCRC enrolled in three randomized clinical trials (TRIBE, MAVERICC, and FIRE-3: where patients were treated with FOLFIRI, mFOLFOX6, or FOLFOXIRI combined with bevacizumab or cetuximab as the first-line chemotherapy). Multivariable logistic regression and Cox regression were performed to evaluate the association between candidate SNPs in the Th17 cell pathway and clinical outcomes [tumor response (TR), progression-free survival (PFS), and overall survival (OS)] in each treatment cohort. The meta-analysis approach using the METASOFT software were implemented to quantify the prognostic effect of each SNP using the inverse-variance-weighted effect size, and also to evaluate the heterogeneity across cohorts using the Q statistic. SNPs were coded as additive, dominant, or recessive in the analysis. The Pegasus analysis was also used to identify effects across multiple SNPs and treatment arms. Results: Pathway analysis showed that the Th17 cell pathway was significantly associated with TR ( P = 0.011). There were suggestive associations of IL17F rs763780 with TR (log OR = 0.64, SE = 0.31; P = 0.038), of IL23R rs10889677 with TR (log OR = 0.37, SE = 0.18; P = 0.039), of IRF4 rs872071 with TR (log OR = -0.26, SE = 0.13; P = 0.037), and of IL21 rs2221903 with PFS (log HR = 0.33, SE = 0.15; P = 0.026), although these results were not significant after FDR adjustment. In addition, IL23R rs10889677 had suggestive heterogeneity of effects for PFS across the six cohorts after Cochran’s Q statistic ( P = 0.013). Conclusions: Th17 cell pathway-related SNPs may be predictors for the first-line chemotherapy in mCRC. Upon validation, our findings would provide novel insight for selecting treatment strategies for mCRC.

MALDI-MSI of Immunotherapy: Mapping the EGFR-Targeting Antibody Cetuximab in 3D Colon-Cancer Cell Cultures

Immunotherapies are treatments that use a patient's immune system to combat disease. One important type of immunotherapy employed in cancer treatments is the delivery of monoclonal antibodies to block growth receptors. In this manuscript, we develop a methodology that enables accurate and simple evaluation of antibody-type drug delivery using MALDI-MSI. To overcome the mass-range limitation that prevents the detection of large therapeutic antibodies, we used in situ reduction and alkylation to break disulfide bonds to generate smaller fragments. These smaller fragments are more readily ionized and detected by MALDI-MSI without loss of spatial information on the parent drug. As a proof of concept study, we evaluated the distribution of cetuximab in 3D colon cell cultures. Cetuximab is a monoclonal antibody that binds to the extracellular domain of epidermal-growth-factor receptor (EGFR), which is often overexpressed in colorectal cancer (CRC) and mediates cell differentiation, proliferation, migration, and angiogenesis. Cetuximab directly inhibits tumor growth and metastasis and induces apoptosis. By performing on-tissue reduction followed by MALDI-MSI analysis, we successfully mapped the time-dependent penetration and distribution of cetuximab in spheroids derived from two different colon-cancer cell lines (HT-29 and DLD-1). The localization patterns were further confirmed with IF staining of the drug. Changes in other biomolecules following drug treatment were also observed, including the elevation of ATP in spheroids. The developed method has also been applied to map cetuximab distribution in patient-derived colorectal-tumor organoids (CTOs). Overall, we believe this powerful label-free approach will be useful for visualizing the heterogeneous distribution of antibody drugs in tissues and tumors and will help to monitor and optimize their use in the clinic.

mTORC2 contributes to the metabolic reprogramming in EGFR tyrosine-kinase inhibitor resistant cells in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) patients with activating EGFR mutations are often successfully treated with EGFR tyrosine kinase inhibitor (TKI) such as erlotinib; however, treatment resistance inevitably occurs. Given tumor metabolism of glucose and therapeutic response are intimately linked, we explored the metabolic differences between isogenic erlotinib-sensitive and -resistant NSCLC cell lines. We discovered that the growth of erlotinib-resistant cells is more sensitive to glucose deprivation. Seahorse metabolic assay revealed erlotinib-resistant cells have lower spare respiratory capacity (SRC), an indicator of metabolic flexibility, compared to erlotinib-sensitive cells. Additionally, we found downstream components of mTORC2 signaling to be phosphorylated in erlotinib-resistant cells. Knockdown of an mTORC2 component, Rictor, enhanced the SRC and rescued the growth rate of erlotinib-resistant cells during glucose deprivation. Among NSCLCs with activating EGFR mutations, gene sets involved in glucose metabolism were enriched in patients with high expression of p-NDGR1, a readout of mTORC2 activity. Furthermore, overall survival was negatively correlated with p-NDRG1. Our work uncovers a link between mTORC2 and metabolic reprogramming in EGFR TKI-resistant cells and highlights the significance of mTORC2 in the progression of EGFR-mutated NSCLC.

MALDI Mass Spectrometry Imaging for Evaluation of Therapeutics in Colorectal Tumor Organoids

Patient-derived colorectal tumor organoids (CTOs) closely recapitulate the complex morphological, phenotypic, and genetic features observed in in vivo tumors. Therefore, evaluation of drug distribution and metabolism in this model system can provide valuable information to predict the clinical outcome of a therapeutic response in individual patients. In this report, we applied matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to examine the spatial distribution of the drug irinotecan and its metabolites in CTOs from two patients. Irinotecan is a prodrug and is often prescribed as part of therapeutic regimes for patients with advanced colorectal cancer. Irinotecan shows a time-dependent and concentration-dependent permeability and metabolism in the CTOs. More interestingly, the active metabolite SN-38 does not co-localize well with the parent drug irinotecan and the inactive metabolite SN-38G. The phenotypic effect of irinotecan metabolism was also confirmed by a viability study showing significantly reduced proliferation in the drug treated CTOs. MALDI-MSI can be used to investigate various pharmaceutical compounds in CTOs derived from different patients. By analyzing multiple CTOs from a patient, this method could be used to predict patient-specific drug responses and help to improve personalized dosing regimens. Graphical Abstract ᅟ.

PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems

Many multicellular systems problems can only be understood by studying how cells move, grow, divide, interact, and die. Tissue-scale dynamics emerge from systems of many interacting cells as they respond to and influence their microenvironment. The ideal "virtual laboratory" for such multicellular systems simulates both the biochemical microenvironment (the "stage") and many mechanically and biochemically interacting cells (the "players" upon the stage). PhysiCell-physics-based multicellular simulator-is an open source agent-based simulator that provides both the stage and the players for studying many interacting cells in dynamic tissue microenvironments. It builds upon a multi-substrate biotransport solver to link cell phenotype to multiple diffusing substrates and signaling factors. It includes biologically-driven sub-models for cell cycling, apoptosis, necrosis, solid and fluid volume changes, mechanics, and motility "out of the box." The C++ code has minimal dependencies, making it simple to maintain and deploy across platforms. PhysiCell has been parallelized with OpenMP, and its performance scales linearly with the number of cells. Simulations up to 105-106 cells are feasible on quad-core desktop workstations; larger simulations are attainable on single HPC compute nodes. We demonstrate PhysiCell by simulating the impact of necrotic core biomechanics, 3-D geometry, and stochasticity on the dynamics of hanging drop tumor spheroids and ductal carcinoma in situ (DCIS) of the breast. We demonstrate stochastic motility, chemical and contact-based interaction of multiple cell types, and the extensibility of PhysiCell with examples in synthetic multicellular systems (a "cellular cargo delivery" system, with application to anti-cancer treatments), cancer heterogeneity, and cancer immunology. PhysiCell is a powerful multicellular systems simulator that will be continually improved with new capabilities and performance improvements. It also represents a significant independent code base for replicating results from other simulation platforms. The PhysiCell source code, examples, documentation, and support are available under the BSD license at http://PhysiCell.MathCancer.org and http://PhysiCell.sf.net.

Characterization of the mechanical properties of resected porcine organ tissue using optical fiber photoelastic polarimetry

Characterizing the mechanical behavior of living tissue presents an interesting challenge because the elasticity varies by eight orders of magnitude, from 50Pa to 5GPa. In the present work, a non-destructive optical fiber photoelastic polarimetry system is used to analyze the mechanical properties of resected samples from porcine liver, kidney, and pancreas. Using a quasi-linear viscoelastic fit, the elastic modulus values of the different organ systems are determined. They are in agreement with previous work. In addition, a histological assessment of compressed and uncompressed tissues confirms that the tissue is not damaged during testing.

Abstract 5908: Cancer-associated fibroblast driven drug resistance in colorectal cancer

Drug resistance remains a major problem in the treatment of most cancers. For example, KRAS wild-type colorectal cancers (CRCs) are typically treated with the anti-epidermal growth factor receptor (EGFR) therapy cetuximab in combination with standard chemotherapy; however, of the 40% of patients that do respond, virtually all relapse within 3-12 months. Additionally, around 25% of nonresponders have no identifiable resistance mechanisms. This suggests that it is not just cell-intrinsic mechanisms that result in resistance, but that extrinsic factors play a role. The purpose of this study was to investigate how the dynamics of the tumor microenvironment, specifically cancer-associated fibroblasts (CAFs) and hypoxia, modify the response of CRC cells to cetuximab. We used a novel high-content imaging platform to generate quantitative phenotypic data (i.e. morphology, birth/death rates) of cellular co-cultures perturbed by multiple, co-occurring microenvironmental conditions. Preliminary data demonstrated reduced sensitivity of tumor cells to cetuximab in the presence of CAFs, which was dependent on patient specifics and time scale of co-culture. Additionally, we found that low oxygen conditions altered the effect of CAFs on tumor cell phenotypes, which highlights the importance of studying co-occurring microenvironmental factors. This work underlies the importance of considering not just the genetic makeup of patient tumors, but also the heterogeneity of the surrounding microenvironment when designing personalized treatment strategies.

Citation Format: Colleen M. Garvey, Oscar Chen, Shannon M. Mumenthaler. Cancer-associated fibroblast driven drug resistance in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5908. doi:10.1158/1538-7445.AM2017-5908

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Cellular processes are complex and result from the interplay between multiple cell types and their environment. Existing cell biology techniques often do not allow for accurate interpretation of this interplay. Using a quantitative imaging-based approach, we present a high-content protocol for characterizing the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations to changes in environmental stimuli. We highlight our ability to distinguish between cell types based upon either fluorescence intensity or inherent morphology features depending on the application. This platform allows for a more comprehensive characterization of subpopulation response to perturbation while utilizing shorter time, smaller amounts of reagents, and lower likelihood of error than traditional cell biology assays. However, in some cases, cell populations may be difficult to identify and quantitate based on complex cellular features and will require additional troubleshooting; we highlight some of these circumstances in the protocol. We demonstrate this application using response to drug in a cancer model; however, it can easily be applied more broadly to other physiological processes. This protocol allows one to identify subpopulations within a co-culture system and characterize the particular response of each to external stimuli.

Progress Towards Computational 3-D Multicellular Systems Biology

Tumors cannot be understood in isolation from their microenvironment. Tumor and stromal cells change phenotype based upon biochemical and biophysical inputs from their surroundings, even as they interact with and remodel the microenvironment. Cancer should be investigated as an adaptive, multicellular system in a dynamical microenvironment. Computational modeling offers the potential to detangle this complex system, but the modeling platform must ideally account for tumor heterogeneity, substrate and signaling factor biotransport, cell and tissue biophysics, tissue and vascular remodeling, microvascular and interstitial flow, and links between all these sub-systems. Such a platform should leverage high-throughput experimental data, while using open data standards for reproducibility. In this chapter, we review advances by our groups in these key areas, particularly in advanced models of tissue mechanics and interstitial flow, open source simulation software, high-throughput phenotypic screening, and multicellular data standards. In the future, we expect a transformation of computational cancer biology from individual groups modeling isolated parts of cancer, to coalitions of groups combining compatible tools to simulate the 3-D multicellular systems biology of cancer tissues.

Abstract B13: High-content imaging to quantitate colorectal cancer associated fibroblast heterogeneity

Cancer-associated fibroblasts (CAFs) are an important component of the tumor microenvironment known to influence various aspects of tumor progression, including response to therapy. However, this stromal cell subtype is extremely heterogeneous, both between and within individual tumors. Targeting of the CAF population has not been successful in the clinical setting, which could be due in part to the myriad of functions of different CAF subpopulations. In order to elucidate the overall implications of CAF heterogeneity, we gathered quantitative phenotypic data using a novel high-content imaging platform. Specifically, we calculated several morphological parameter values and estimated birth and death rates of individual populations of CAFs isolated from colorectal cancer patients. We also performed co-culture experiments with tumor cells and characterized the influence of different CAF populations on tumor evolutionary dynamics (i.e. birth and death rates) in response to drug treatment. Further, these features were correlated to molecular analyses (i.e. -smooth muscle actin and fibroblasts activated protein expression) and patient outcome (i.e. sites of metastasis). We observed high levels of heterogeneity in cell area and cell roundness as well as altered rates of growth in response to perturbations in oxygen levels. This quantitative method for investigating multiple cellular phenotypes provides novel insight into patient-level heterogeneity and its possible implications on response to drug.

Citation Format: Colleen M. Garvey, Oscar Chen, Roy Lau, Shannon M. Mumenthaler. High-content imaging to quantitate colorectal cancer associated fibroblast heterogeneity. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr B13.

Abstract A29: Heterogeneity of androgen receptor dynamics and drug response in prostate cancer cells

Background: Recent studies suggest that the spatio-temporal dynamics of critical signaling molecules can mediate heterogeneous response to therapeutic intervention. Here, we set out to apply live cell imaging of single cells in high throughput to correlate the dynamics of androgen receptor (AR) with response to taxane chemotherapy in heterogeneous prostate cancer (PCa) cell populations.

Methods: We previously developed a 3-step high throughput imaging and data analysis workflow to improve measurements of the dynamic phenotype in heterogeneous populations. We treated PCa cells stably expressing GFP-AR with AR ligand and quantified nuclear/cytoplasmic GFP intensity to measure nuclear translocation of AR over a 30 min time course. Then we treated cells with paclitaxel and tracked cells' response for 24h.

Results: Applied to PCa cell lines stably expressing GFP-AR, we measured considerable heterogeneity of AR translocation in response to ligand stimulation. We quantified populations of non-responders and classified responding cells based on the dynamics of AR. Evaluation of cell morphology revealed a fraction of relatively large cells to be exclusively slow responders to AR ligand. We measured heterogeneous response to treatment with paclitaxel that correlated with cell phenotype.

Conclusion: We conclude that cell morphology features in heterogeneous PCa cell populations correlate with AR translocation dynamics and drug response. Future experiments will include expression of the constitutively active AR variant AR-v7 to analyze its effect on the dynamics of wild-type AR and on single cell response to paclitaxel chemotherapy.

Note: This abstract was not presented at the conference.

Citation Format: Katherin Patsch, Anjana Soundararajan, Mark Engeln, Mitchell E. Gross, Shannon M. Mumenthaler, Daniel Ruderman. Heterogeneity of androgen receptor dynamics and drug response in prostate cancer cells. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr A29.

Dual transcript and protein quantification in a massive single cell array

Recently, single-cell molecular analysis has been leveraged to achieve unprecedented levels of biological investigation. However, a lack of simple, high-throughput single-cell methods has hindered in-depth population-wide studies with single-cell resolution. We report a microwell-based cytometric method for simultaneous measurements of gene and protein expression dynamics in thousands of single cells. We quantified the regulatory effects of transcriptional and translational inhibitors on cMET mRNA and cMET protein in cell populations. We studied the dynamic responses of individual cells to drug treatments, by measuring cMET overexpression levels in individual non-small cell lung cancer (NSCLC) cells with induced drug resistance. Across NSCLC cell lines with a given protein expression, distinct patterns of transcript-protein correlation emerged. We believe this platform is applicable for interrogating the dynamics of gene expression, protein expression, and translational kinetics at the single-cell level - a paradigm shift in life science and medicine toward discovering vital cell regulatory mechanisms.