RESUMO
Patient-derived tumor organoids (PDTOs) are novel cellular models that maintain the genetic, phenotypic and structural features of patient tumor tissue and are useful for studying tumorigenesis and drug response. When integrated with advanced 3D imaging and analysis techniques, PDTOs can be used to establish physiologically relevant high-throughput and high-content drug screening platforms that support the development of patient-specific treatment strategies. However, in order to effectively leverage high-throughput PDTO observations for clinical predictions, it is critical to establish a quantitative understanding of the basic properties and variability of organoid growth dynamics. In this work, we introduced an innovative workflow for analyzing and understanding PDTO growth dynamics, by integrating a high-throughput imaging deep learning platform with mathematical modeling, incorporating flexible growth laws and variable dormancy times. We applied the workflow to colon cancer organoids and demonstrated that organoid growth is well-described by the Gompertz model of growth. Our analysis showed significant intrapatient heterogeneity in PDTO growth dynamics, with the initial exponential growth rate of an organoid following a lognormal distribution within each dataset. The level of intrapatient heterogeneity varied between patients, as did organoid growth rates and dormancy times of single seeded cells. Our work contributes to an emerging understanding of the basic growth characteristics of PDTOs, and it highlights the heterogeneity in organoid growth both within and between patients. These results pave the way for further modeling efforts aimed at predicting treatment response dynamics and drug resistance timing.
Assuntos
Organoides , Humanos , Organoides/crescimento & desenvolvimento , Organoides/efeitos dos fármacos , Organoides/patologia , Modelos Biológicos , Neoplasias do Colo/diagnóstico por imagem , Neoplasias do Colo/patologia , Neoplasias do Colo/tratamento farmacológico , Biologia Computacional , Aprendizado Profundo , Modelos Teóricos , Imageamento Tridimensional/métodosRESUMO
BACKGROUND: The TIMELESS-TIPIN complex protects the replication fork from replication stress induced by chemotherapeutic drugs. We hypothesised genetic polymorphisms of the TIMELESS-TIPIN complex may affect the response, progression-free survival (PFS), and overall survival (OS) of cytotoxic drugs in patients with metastatic colorectal cancer (mCRC). METHODS: We analysed data from the MAVERICC trial, which compared FOLFOX/bevacizumab and FOLFIRI/bevacizumab in untreated patients with mCRC. Genomic DNA extracted from blood samples was genotyped using an OncoArray. Eight functional single nucleotide polymorphisms (SNPs) in TIMELESS and TIPIN were tested for associations with clinical outcomes. RESULTS: In total, 324 patients were included (FOLFOX/bevacizumab arm, n = 161; FOLFIRI/bevacizumab arm, n = 163). In the FOLFOX/bevacizumab arm, no SNPs displayed confirmed associations with survival outcomes. In the FOLFIRI/bevacizumab arm, TIMELESS rs2291739 was significantly associated with OS in multivariate analysis (G/G vs. any A allele, hazard ratio = 3.06, 95% confidence interval = 1.49-6.25, p = 0.004). TIMELESS rs2291739 displayed significant interactions with treatment regarding both PFS and OS. CONCLUSIONS: TIMELESS rs2291739 might have different effects on therapeutic efficacy between oxaliplatin- and irinotecan-based chemotherapies. Upon further validation, our findings may be useful for personalised approaches in the first-line treatment of mCRC.
Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Biomarcadores Tumorais/genética , Proteínas de Ciclo Celular/genética , Neoplasias do Colo/tratamento farmacológico , Replicação do DNA , Proteínas de Ligação a DNA/genética , Mutação em Linhagem Germinativa , Peptídeos e Proteínas de Sinalização Intracelular/genética , Polimorfismo de Nucleotídeo Único , Idoso , Protocolos de Quimioterapia Combinada Antineoplásica/administração & dosagem , Bevacizumab/administração & dosagem , Camptotecina/administração & dosagem , Camptotecina/análogos & derivados , Neoplasias do Colo/genética , Neoplasias do Colo/patologia , Feminino , Fluoruracila/administração & dosagem , Humanos , Leucovorina/administração & dosagem , Masculino , Metástase Neoplásica , Compostos Organoplatínicos/administração & dosagem , Taxa de SobrevidaRESUMO
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.
Assuntos
Fibroblastos Associados a Câncer , Neoplasias Colorretais , Fibroblastos Associados a Câncer/metabolismo , Fibroblastos Associados a Câncer/patologia , Cromatografia Líquida , Neoplasias Colorretais/genética , Neoplasias Colorretais/metabolismo , Neoplasias Colorretais/patologia , Humanos , Metabolômica , Espectrometria de Massas em Tandem , Microambiente TumoralRESUMO
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?
Assuntos
Epigênese Genética , Neoplasias , Epigenômica , Humanos , Mutação , Neoplasias/tratamento farmacológico , Neoplasias/genética , Microambiente TumoralRESUMO
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.
Assuntos
Proteínas Quinases Ativadas por AMP/genética , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Neoplasias Colorretais/tratamento farmacológico , Polimorfismo de Nucleotídeo Único , Bevacizumab/administração & dosagem , Biomarcadores Tumorais/genética , Camptotecina/administração & dosagem , Cetuximab/administração & dosagem , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Fluoruracila , Humanos , Leucovorina/administração & dosagem , Metástase Neoplásica , Prognóstico , Intervalo Livre de Progressão , Ensaios Clínicos Controlados Aleatórios como Assunto , Transdução de Sinais/genéticaRESUMO
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.
Assuntos
Biologia Computacional/métodos , Simulação por Computador , Biologia de Sistemas , Apoptose , Transporte Biológico , Fenômenos Biomecânicos , Neoplasias da Mama/metabolismo , Carcinoma Intraductal não Infiltrante/metabolismo , Comunicação Celular , Ciclo Celular , Feminino , Humanos , Sistema Imunitário , Modelos Biológicos , Necrose , Fenótipo , Reprodutibilidade dos Testes , Transdução de Sinais , Software , Esferoides Celulares , Processos EstocásticosRESUMO
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.
Assuntos
Cetuximab/imunologia , Receptores ErbB/imunologia , Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz , Trifosfato de Adenosina/metabolismo , Área Sob a Curva , Técnicas de Cultura de Células , Linhagem Celular Tumoral , Proliferação de Células/efeitos dos fármacos , Cetuximab/análise , Cetuximab/farmacologia , Neoplasias do Colo/metabolismo , Neoplasias do Colo/patologia , Neoplasias do Colo/terapia , Humanos , Imunoterapia , Microscopia de Fluorescência , Curva ROC , Esferoides Celulares/efeitos dos fármacosRESUMO
Experimental studies have shown that one key factor in driving the emergence of drug resistance in solid tumors is tumor hypoxia, which leads to the formation of localized environmental niches where drug-resistant cell populations can evolve and survive. Hypoxia-activated prodrugs (HAPs) are compounds designed to penetrate to hypoxic regions of a tumor and release cytotoxic or cytostatic agents; several of these HAPs are currently in clinical trial. However, preliminary results have not shown a survival benefit in several of these trials. We hypothesize that the efficacy of treatments involving these prodrugs depends heavily on identifying the correct treatment schedule, and that mathematical modeling can be used to help design potential therapeutic strategies combining HAPs with standard therapies to achieve long-term tumor control or eradication. We develop this framework in the specific context of EGFR-driven non-small cell lung cancer, which is commonly treated with the tyrosine kinase inhibitor erlotinib. We develop a stochastic mathematical model, parametrized using clinical and experimental data, to explore a spectrum of treatment regimens combining a HAP, evofosfamide, with erlotinib. We design combination toxicity constraint models and optimize treatment strategies over the space of tolerated schedules to identify specific combination schedules that lead to optimal tumor control. We find that (i) combining these therapies delays resistance longer than any monotherapy schedule with either evofosfamide or erlotinib alone, (ii) sequentially alternating single doses of each drug leads to minimal tumor burden and maximal reduction in probability of developing resistance, and (iii) strategies minimizing the length of time after an evofosfamide dose and before erlotinib confer further benefits in reduction of tumor burden. These results provide insights into how hypoxia-activated prodrugs may be used to enhance therapeutic effectiveness in the clinic.
Assuntos
Antineoplásicos/farmacologia , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Hipóxia/metabolismo , Neoplasias Pulmonares/tratamento farmacológico , Pró-Fármacos/farmacologia , Antineoplásicos/uso terapêutico , Linhagem Celular Tumoral , Biologia Computacional , Cloridrato de Erlotinib/farmacologia , Cloridrato de Erlotinib/uso terapêutico , Humanos , Pró-Fármacos/uso terapêutico , Microambiente Tumoral/efeitos dos fármacosRESUMO
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.
Assuntos
Líquido Extracelular/diagnóstico por imagem , Modelos Biológicos , Neoplasias/diagnóstico por imagem , Neovascularização Patológica/diagnóstico por imagem , Biologia de Sistemas/métodos , Remodelação Vascular , Simulação por Computador , Células Endoteliais/patologia , Células Endoteliais/ultraestrutura , Hemodinâmica , Humanos , Imageamento Tridimensional/estatística & dados numéricos , Neoplasias/irrigação sanguínea , Neoplasias/patologia , Neoplasias/ultraestrutura , Neovascularização Patológica/patologia , Reprodutibilidade dos Testes , Software , Microambiente TumoralRESUMO
OBJECTIVE: To identify clinically relevant predictive biomarkers of trastuzumab resistance. MATERIAL AND METHODS: MTT, FACS assays, immunoblotting and immunocytochemistry were used to phenotypically characterize drug responses of two cell models BT474R and SKBR3R. Student's t-test and Spearman's correlation were applied for statistic analysis. RESULTS: The activity of a downstream effector of the HER2 pathway phosphorylated ribosomal protein S6 (p-rpS6), was suppressed by trastuzumab in the parental cell lines yet remained unchanged in the resistant cells following treatment. The level of p-rpS6 was inversely correlated to the drug induced growth inhibition of trastuzumab-resistant cells when they are treated with selected HER2 targeting drugs. CONCLUSION: p-rpS6 is a robust post-treatment indicator of HER2 pathway-targeted therapy resistance.
Assuntos
Antineoplásicos/farmacologia , Biomarcadores/metabolismo , Receptor ErbB-2/metabolismo , Proteína S6 Ribossômica/metabolismo , Transdução de Sinais , Trastuzumab/farmacologia , Linhagem Celular Tumoral , Resistencia a Medicamentos Antineoplásicos , Humanos , Concentração Inibidora 50 , FosforilaçãoRESUMO
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.
Assuntos
Dispositivos Lab-On-A-Chip , Invasividade Neoplásica , Humanos , Organoides/patologia , Neoplasias Colorretais/patologia , Células Endoteliais/patologia , Células Endoteliais/metabolismo , Microfluídica/métodosRESUMO
Circadian clock genes are emerging targets in many types of cancer, but their mechanistic contributions to tumor progression are still largely unknown. This makes it challenging to stratify patient populations and develop corresponding treatments. In this work, we show that in breast cancer, the disrupted expression of circadian genes has the potential to serve as biomarkers. We also show that the master circadian transcription factors (TFs) BMAL1 and CLOCK are required for the proliferation of metastatic mesenchymal stem-like (mMSL) triple-negative breast cancer (TNBC) cells. Using currently available small molecule modulators, we found that a stabilizer of cryptochrome 2 (CRY2), the direct repressor of BMAL1 and CLOCK transcriptional activity, synergizes with inhibitors of proteasome, which is required for BMAL1 and CLOCK function, to repress a transcriptional program comprising circadian cycling genes in mMSL TNBC cells. Omics analyses on drug-treated cells implied that this repression of transcription is mediated by the transcription factor binding sites (TFBSs) features in the cis-regulatory elements (CRE) of clock-controlled genes. Through a massive parallel reporter assay, we defined a set of CRE features that are potentially repressed by the specific drug combination. The identification of cis -element enrichment may serve as a new way of defining and targeting tumor types through the modulation of cis -regulatory programs, and ultimately provide a new paradigm of therapy design for cancer types with unclear drivers like TNBC.
RESUMO
Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved high-throughput computational screening to investigate the effects of enzyme perturbations predicted by a computational model of CRC metabolism to understand system-wide effects efficiently. Our results highlighted hexokinase (HK) as one of the crucial targets, which subsequently became our focus for experimental validation using patient-derived tumor organoids (PDTOs). Through metabolic imaging and viability assays, we found that PDTOs cultured in CAF conditioned media exhibited increased sensitivity to HK inhibition. Our approach emphasizes the critical role of integrating computational and experimental techniques in exploring and exploiting CRC-CAF crosstalk.
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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.
Assuntos
Neoplasias Colorretais , Receptores de Quimiocinas , Humanos , Antígeno B7-H1/genética , Ligantes , Quimiocina CCL5/genética , Quimiocina CCL5/metabolismo , Quimiocinas/genética , Neoplasias Colorretais/tratamento farmacológico , Neoplasias Colorretais/genética , Neoplasias Colorretais/patologia , Expressão Gênica , Microambiente Tumoral , Receptores CCR5/genética , Receptores CCR5/metabolismoRESUMO
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.
Assuntos
Descoberta de Drogas , Dispositivos Lab-On-A-Chip , Sistemas MicrofisiológicosRESUMO
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.
RESUMO
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.
Assuntos
Neoplasias do Colo , Proteína Potenciadora do Homólogo 2 de Zeste , Histonas , Proteínas Serina-Treonina Quinases , Ubiquitina-Proteína Ligases , Humanos , Neoplasias do Colo/genética , Proteína Potenciadora do Homólogo 2 de Zeste/genética , Proteína Potenciadora do Homólogo 2 de Zeste/metabolismo , Inativação Gênica , Genes Reguladores , Histonas/genética , Histonas/metabolismo , Fosforilação , Proteínas Serina-Treonina Quinases/metabolismo , Ubiquitina-Proteína Ligases/metabolismoRESUMO
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.
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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.
Assuntos
Antineoplásicos , Neoplasias , Humanos , Detecção Precoce de Câncer , Neoplasias/tratamento farmacológico , Antineoplásicos/farmacologia , Linhagem Celular , GenômicaRESUMO
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.