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Phenotypic Imaging of Nephroblastoma Cancer cells
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Phenotypic Imaging of Nephroblastoma Cancer cells

BioTech Today July 1, 2021June 30, 2021

Nandini Pharasi, Jaypee Institute of Information Technology

Cancer is a disease in which the body cells grow rapidly, uncontrollably and spread to the other parts of the body, cancer makes the body stop its normal mechanism as the old cell do not die instead of that it starts forming new cells, abnormal cells, and sometimes grows out of control. This extra mass of tissue formed by old cells makes a cluster forming a tumor.

To detect cancer we use many imaging techniques are used for the past few years includes CT scan (computerized tomography), MRI (magnetic resonance imaging), PET (positron emission tomography) scan, X-ray, ultrasound, and even Biopsy. In a biopsy, the sample for testing requires cutting off a small piece of tissue from the body, thus sacrificing the important information about how the tissues were organized. Of the different types of tumors, Wilm’s tumor (also called nephroblastoma), is a type of cancer that attacks kidneys primarily of age group 3-4 years. This tumor is one of the most common cancer in children. Nephroblastoma is a malignant embryonal tumor. A digital connection between location activity and people is Spatial information, which can explain the relationship between different types of cells, how the tissue is organized largely, and differentiate between the childhood tumors and healthy tissues thus improving future diagnostic techniques.

To compare Wilm’s tumor cell (nephroblastoma) with healthy developing kidney Ravian van Ineveld and Michiel Kleinnijenhuis put in their microscopic techniques. They found a gene “six2” which in humans decodes a homeobox Protein six2 in a group of cells with a level higher than an ordinary cell. The researchers will further explore six2 Wilm’s tumor (nephroblastoma) cell’s clinical relevance as they could differentiate and distinguish between cell types more precisely because of the new imaging pipeline as it doubles the numbers of colors that can be tagged at the same time from four to eight and can label specific molecules with fluorescent particles in a different color under the microscope to be separated from each other.

The new imaging technique:

Scientists had developed a new imaging computational pipeline technique to study 3D tissues in millions of cells which can tell us about hundreds of unique features from each cell in a small amount of time. This new imaging technique analyses the molecular profile, shape, and position within an organ or a tumor of a particular cell. This technique gives us information into small 3D blocks by cutting out the information about the whole organ and then analyzing the data in parallel, reducing the time to process large data that took multiple days in 2 hours, using deep learning to approach and identify each cell with higher accuracy of data. Sooner the researcher will be using their image pipeline to analyze more samples by linking 3D tissue analysis to a clinical outcome which will lead to a better diagnosis for children’s cancer.

The researchers further added that “this technique will take a step forward in unraveling complexities of the way tumor and organs are organized, this technique will give us in the characterization of an individual cell and large scale of 3D tissue analysis”. Biopsy material was collected from nervous system tumors as well as breast tumor tissue for confirming that this new technique with different molecular tags will help in identifying multiple tissues without sacrificing any tissue.

Also read: Analysis of the interaction sites of SARS-CoV-2

References:

  1. van Ineveld, R. L., Kleinnijenhuis, M., Alieva, M., de Blank, S., Barrera Roman, M., van Vliet, E. J., Martínez Mir, C., Johnson, H. R., Bos, F. L., Heukers, R., Chuva de Sousa Lopes, S. M., Drost, J., Dekkers, J. F., Wehrens, E. J., & Rios, A. C. (2021). Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D. Nature biotechnology, 10.1038/s41587-021-00926-3. Advance online publication. https://doi.org/10.1038/s41587-021-00926-3
  2. The thumbnail image has been extracted from Servier Medical Art.
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Tagged 3D tissue analysis biopsy computerized tomography CT scan Deep Learning magnetic resonance imaging MRI nephroblastoma Nervous system tumor PET positron emission tomography scan Ultrasound wilm’s tumor cell X-ray

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