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There is also the issue of robustness of data acquired by different researchers for a single experiment, as user-to-user variability in technique leads to deviation in data. Success of the experiment depends on user experience, and most methods require learning new skills to ensure uniformity, robustness, and reproducibility. Often these skills become so specific to a subject that crossing the technological hurdles between biological and engineering fields becomes extremely difficult at a time when interdisciplinary research is essential for progress.

This limitation highlights the need for detailed documentation of the methodologies discussed above. Often times, method sections will omit key experimental details that leave the reader extrapolating to fill in the gaps, which could lead to improper technique, unsuccessful experiments, and incongruent results, especially when interpreted by a less experienced researcher.


  1. Journal Papers.
  2. Sambanis Laboratory | Publications.
  3. Fisher Edits Two Works on Tissue Engineering | Fischell Department of Bioengineering;
  4. The Practitioners Handbook to the Social Services.
  5. Charlie Nuttelman - Publications!
  6. Charlie Nuttelman.

As such, great care should be taken in drafting detailed methods that provide step-by-step instructions that researchers in different fields can follow. Such detailed methods will also help minimize experimental variation between researchers probing the same question. In addition, comprehensive reporting of model characterization will help to identify potential sources of variation between models from different research labs and thus aide in the accurate interpretation of results. Furthermore, interdisciplinary efforts between dissimilar fields will help ensure a more seamless translation of model and analysis techniques between disciplines.

For example, many physiologic models of cancers have been designed in engineering, physics, and chemistry labs with the intention of being widely adopted by the biology and clinical labs. However, the engineering parameters such as fluid flow, ECM mechanics, etc.

mod01lec02 - Introduction to Tissue Engineering - Part 2

Evidence of this synergy between disciplines is already seen in collaborative grants, conferences, and publications that are being led by increasingly integrative teams in cancer biology, engineering, and oncology. One way to promote collaboration is through the promotion and development of more multidisciplinary conferences, which focus specifically on the inclusion of other fields to improve current models and techniques. These cross-disciplinary interactions are essential for the progress of the field and the improved design of experiments.

The power of interdisciplinary research in precision medicine is further evident in the development of advanced analytical techniques, which utilize concepts from physics, chemistry, and engineering to improve biological analysis of the more complex 3D in vitro tumor models present in research today.

One such technique is live cell imaging performed with light sheet microscopy, which enables real-time live cell tracking and complete 3D imaging of the culture environment with minimal photobleaching, phototoxicity, and imaging time[ ].

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The information gleaned from such a technique may provide insight into key cell-cell interactions involved in tumor development and differentiation pathways and may help to explain experimental variation attributable to differences in 3D architecture[ ], which would not otherwise be easily obtainable. Mass spectrometry-based proteomics is another advanced analytical technique that is becoming more widely implemented due to improvements in the mass spectrometry workflow and is now considered an irreplaceable molecular and cellular biology tool[ ].

Finally, increased development and utilization of mathematical models across subjects may serve as a common language through which biology, engineering, and chemistry can collaborate remotely, implement data to make predictions, and accelerate progress. The use of mathematical models in all fields is beneficial, as they can be created to analyze complex variables not easily studied experimentally, to determine which experiments are most promising, and to improve our understanding of biological mechanisms.

These models could also decrease the use of scarce patient samples in experiments that can be determined in situ to not work and decrease the time needed to devise patient specific treatment plans.

Reducing beam hardening effects and metal artefacts in spectral CT using Medipix3RX - INSPIRE-HEP

Integration will also be facilitated by the ease of sharing of codes used to generate mathematical models, effectively minimizing variance attributed to user differences and experience. Overall, cancer can be considered a complex and interconnected organ system that colludes with its host in order to progress and maintain function. In order to complete this task, cancer bioengineering models should consider the three dimensionalities of the tumor, the mechanical stimuli that continuously provoke response, the multicellular interactions innate to the environment, and the variety of sources that can provide signaling to a heterogeneous tumor.

Understandably, each of these aspects encompasses numerous degrees of freedom, complicating the overarching picture. To remedy these challenges, we propose: 1 Enhancing physiological reproducibility through development of more comprehensive in vitro models, 2 Improving experimental reproducibility via reporting standards and sharing of negative results, 3 Sharing of knowledge and expertise across fields through collaboration, and 4 Improvement of analysis techniques to reduce technological hurdles.

Moreover, as a result of this work, we will gain significant understanding regarding the complex ways in which cancer cells interact with their surroundings. This has direct implications for both effective cancer prevention and individualized therapies and achieving better patient survival. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Tumors are not merely cancerous cells that undergo mindless proliferation. Data Availability: All relevant data are within the paper. Introduction Tumors have long been viewed as the accumulation of a mass of aberrant cancer cells.

Download: PPT. Fig 2. Table 1. Summary of 3-dimensional cancer bioengineering methods and their respective benefits and limitations. Fig 3. Various cell-cell interactions within the cancer-organ system. Table 2. Examples of 3-dimensional cancer bioengineering models that emphasize cell-cell interactions. Fig 4. The immune microenvironment of tumors contains cellular components from both the innate and adaptive immune systems, with functional immuno-modulation between all the different cell types.

Conclusion Overall, cancer can be considered a complex and interconnected organ system that colludes with its host in order to progress and maintain function. References 1. Hanahan D, Weinberg RA.

Hallmarks of Cancer: The Next Generation. The Hallmarks of Cancer. Tumor heterogeneity: biological implications and therapeutic consequences. Cancer Metastasis Rev. Plasticity of tumour and immune cells: a source of heterogeneity and a cause for therapy resistance? Nat Rev Cancer. Tumors as organs: complex tissues that interface with the entire organism.

Dev Cell. Bioengineered 3D platform to explore cell—ECM interactions and drug resistance of epithelial ovarian cancer cells. Stemness and chemoresistance in epithelial ovarian carcinoma cells under shear stress. Sci Rep. Molecular analysis of chondrocytes cultured in agarose in response to dynamic compression. BMC Biotechnol. Mechanical compression drives cancer cells toward invasive phenotype. Proc Natl Acad Sci.

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Mechanotransduction in cancer. Curr Opin Chem Eng. Involvement of M2-polarized macrophages in the ascites from advanced epithelial ovarian carcinoma in tumor progression via Stat3 activation. Cancer Sci. Tumor-associated macrophages drive spheroid formation during early transcoelomic metastasis of ovarian cancer. J Clin Invest. Colvin EK. Front Oncol. A 3D tension bioreactor platform to study the interplay between ECM stiffness and tumor phenotype. J Biotechnol. The influence of soluble fragments of extracellular matrix ECM on tumor growth and morphology.

Math Biosci. Bioengineering 3D environments for cancer models. Adv Drug Deliv Rev. Culturing substrates influence the morphological, mechanical and biochemical features of lung adenocarcinoma cells cultured in 2D or 3D. Tissue Cell. Nanomater Basel. Analysis of sensitivity and cell death pathways mediated by anti-cancer drugs using three-dimensional culture system. Int J Cancer Res. View Article Google Scholar Three-dimensional tissue culture model of human breast cancer for the evaluation of multidrug resistance. J Tissue Eng Regen Med. Dual-degradable and injectable hyaluronic acid hydrogel mimicking extracellular matrix for 3D culture of breast cancer MCF-7 cells.

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