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328 Validation of 3D Human Tissue Culture Systems that Mimic the Tumor Microenvironment

Fast-Track proposals will be accepted.

Number of anticipated awards: 5–7

Budget (total costs, per award):
Phase I: $225,000 for 9 months;
Phase II: $1,500,000 for 2 years

It is strongly suggested that proposals adhere to the above budget amounts and project periods. Proposals with budgets exceeding the above amounts and project periods may not be funded.

The deadline for receipt of all contract proposals submitted in response to this solicitation has expired. It was: November 25, 2013 by 4:30 p.m. ET.


There is a critical need to improve the accuracy of preclinical drug efficacy screening and testing through the development of in vitro culture systems that more effectively mimic the in vivo environment. Currently, two-dimensional (2D) in vitro culture systems or in vivo animal models are the primary tools used to test cancer cell responses to drugs. However, drug sensitivity data obtained via 2D culture systems can be misrepresentative, while animal models are expensive, time-consuming, and not always predictive of the effects on human tumors in their native environment. Three-dimensional (3D) culture systems using human tissue could be a better tool for drug screening by providing a more accurate, in vivo-like structure and organization than 2D culture systems, and better informing drug efficacy testing in animal models. In addition, culture systems based on human tissue may produce responses more predictive of human cancers than non-human model systems.

Advances in bioengineering, biomaterials, and 3D cell culture models have led to in vitro systems that better replicate the structure, physiology, and function of tissues seen in vivo. 3D models more accurately mimic the in vivo milieu than current 2D in vitro culture systems by recreating the morphology and architecture of cellular relationships, gradients of signaling molecules forces of extracellular matrix (ECM) proteins. The use of 3D systems that recreate the human tumor microenvironment and reflect tumor heterogeneity could improve the development of therapeutic strategies (e.g., treatment combinations, dose, timing) and the feasibility of chemo-sensitivity assays in at least two ways: 1) better inform decision-making for whether a particular therapeutic agent is worth pursuing in an animal model, reducing the time and cost of development; 2) lead to fewer clinical trial failures because of earlier, more relevant results from human tissue.

Properly representing the tumor microenvironment as can be done using 3D systems is particularly critical for testing the effectiveness of anti-cancer therapeutic agents. For example, extravascular transport in solid tumors is a fundamental determinant of the efficacy of both locally and systemically administered cancer agents. Large diffusion distances in tumor tissues, elevated interstitial fluid pressure, and interactions between anti-cancer drugs, tumor tissue, and normal tissue are factors that significantly limit drug diffusion in the extravascular compartment. Additionally, due to rapid proliferation and poor perfusion of tumors, the tumor microenvironment is often acidic and hypoxic, which can lead to the resistance of tumor cells to both drug and radiation therapy. Thus, 3D systems to properly recreate the tumor microenvironment are essential to advance the discovery and development of effective anti-cancer agents.

Project Goals:

The focus of this topic is the validation of 3D human tissue model culture systems that accurately mimic the tumor microenvironment, including factors affecting tumor cell responses such as vascularization, interstitial pressure, physiochemical factors, and interactions with heterogeneous cell types. The project goal is to validate a 3D human tumor culture system against anti-cancer agents with known effects to demonstrate the system's utility as a predictive tool, a pre-clinical screening assay, and/or a chemo-sensitivity assay. It is anticipated that the development of 3D systems representative of human tumor microenvironments will lead to an increase in the quality and accuracy of drug screening, along with reductions in the associated timelines and costs, leading to enhancement in the efficacy of producing information for regulatory decisions.

Essential characteristics of an in vitro tumor microsystem should include all or some of the following features:

  1. multicellular architecture that represents physiologically relevant characteristics of the tumor and tissue of origin;
  2. reproducible and viable operation with simple and clear protocols;
  3. ability to examine multiple aspects of cancer, such as tumor growth, angiogenesis, cell proliferation and cell death, migration, and/or invasion; and
  4. compatibility with high content screening platforms that include multiple molecular read-outs, such as genomic, proteomic, metabolomic, or epigenomic analyses.

System development should permit scale-up production such that the system can be reliably reproduced at a cost with reasonable expectation for market success. An eventual goal for such systems may include the ability to incorporate individual patient tumor biopsies to test patient-specific responses to available agents.

It is important to note that full 3D tumor microenvironment systems will consist of more than an extracellular matrix (ECM) containing tumor cells and will facilitate the inclusion of various cell types to mimic cancer cell interaction and paracrine signaling from surrounding non-malignant cells to model their effects on cancer aggressiveness and response to anti-cancer drugs. Examples include stromal cells that can induce chemoresistance and encourage metastasis, as well as endothelial cells that can carry chemotherapeutics to the tumor. Systems of particular interest will incorporate perfusion, interstitial, and/or immune components.

This topic is not intended to fund microphysiological organ systems for the study of toxicity, though tumor culture systems developed under this topic may be combined as a module with systems such as those being developed through the collaborative program between NIH, FDA, and DARPA:

Phase I Activities and Expected Deliverables:

  • Validate a reproducible 3D culture that mimics the tumor microenvironment and appropriate pre-clinical or chemo-sensitivity assays to screen response to therapeutics.
    • Culture system should include:
      • Incorporation of human tumor cells (cell lines, primary tumor cells, or biopsy tissue) that are readily available and well-characterized in vivo or in a 2D system
      • Multiple cell types (e.g., stromal cells, leukocytes, endothelial cells, etc.)
      • Structural components to mimic ECM topology, mechanical cues/gradients, and/or chemical cues/gradients found in vivo
      • Method to deliver and control necessary growth factors and/or therapeutics
      • Adaptability for use with high-content screening platforms for sample analysis
      • Systems of particular interest will incorporate perfusion, interstitial, and/or immune components
    • Pre-clinical or chemo-sensitivity assay should quantitatively examine at least two of the following aspects of cancer in response to therapeutics: tumor growth, angiogenesis, cell proliferation, cell death, migration, and/or invasion.
    • Quantify reproducibility of culture system SOP and corresponding assay SOP using a statistically relevant number of samples
  • Submit a statement to NCI that specifies metrics used and criteria for prediction of clinical efficacy prior to demonstration of accurate prediction of clinical efficacy.
    • Identify specific biomarkers (e.g. gene expression patterns, cell surface proteins, soluble factors) that characterize cell types and tumors used.
    • Specify criteria for assessing that tumor microenvironment is representative of human physiological environment.
    • Specify markers of tumor activity.
    • Specify metrics that will be used to evaluate efficacy and milestones for desired efficacy.
  • Demonstrate accurate prediction of clinical efficacy or chemo-sensitivity in the culture system.
    • Test at least one anti-cancer agent with a known clinical profile using the validated prototype. For example, agent used may be from the NCI Developmental Therapeutics Program [DTP] Approved Oncology Drugs Set
    • Benchmark performance in developed system against 2D (e.g., NCI-60 Human Tumor Cell Line), and currently available 3D culture systems (e.g., tumor spheroids, hollow-fiber bioreactors).

Phase II Activities and Expected Deliverables:

  • Benchmark performance in developed system against applicable in vivo animal model(s) and known clinical performance.
    • Test multiple agents, at least four, with known clinical profiles in the prototype validated in Phase I.
      • Include at least one agent that demonstrated significant efficacy in animal trials but could not recapitulate that efficacy in clinical trials.
      • Include at least one agent that did not demonstrate significant efficacy in 2D systems and either was not tested in animal trials, or demonstrated efficacy in animal trials.
    • Measure profile of tumor prototype system and applicable in vivo animal model(s) using high content analysis (i.e. at least 6 different measurements per sample). Measurements may include, but are not limited to: genomic, proteomic, morphological, metabolomic, and epigenomic profiles of tumor system.
      • Use validated markers and/or evaluative criteria from in vivo histologic analysis.
      • Genomic data may be compared to that acquired by The Cancer Genome Atlas.
    • Compare dose-response relationships of known anti-cancer agents with available clinical performance data.
  • Demonstrate ability to scale-up system for use in high-throughput therapeutic agent screening assays.
    • Demonstrate ability to perform high-throughput quantitative analysis on samples, such as simple harvesting and/or automated imaging. High throughput assays must still be considered high content (i.e. measurement capabilities of at least 6 different parameters).


  • Demonstrate potential clinical utility of chemo-sensitivity assay.
    • Compare dose-response relationships using high content analysis across a subset of clinical biospecimens to assess sensitivity of assay and relevance to alter standard-of-care treatments on an individual patient basis.


Updated: June 24, 2015

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