Dataset Information

Quantum dots based in-vitro co-culture cancer model for identification of rare cancer cell heterogeneity.

ABSTRACT: Cancer cell heterogeneity (CCH) is crucial in understanding cancer progression and metastasis. The CCH is one of the stumbling blocks in modern medicine's therapeutics and diagnostics . An in-vitro model of co-culture systems of MCF-7, HeLa, HEK-293, with THP-1 cells showed the occurrence of EpCAM positive (EpCAM+) and EpCAM negative (EpCAM-) heterogenetic cancer cell types labeled with the Quantum Dot antibody conjugates (QD^Ab). This in-vitro model study could provide insights into the role of rare cancer cells manifestation and their heterogeneity in metastatic progression and risk for severe infections in these patients. We successfully report the presence of CCH based on the fluorescence ratios of the co-cultured cancer cells when treated with the QD^Ab. These short-term mimic co-cultures give a compelling and quite associated model for assessing early treatment responses in various cancers.

SUBMITTER: Vyshnava SS

PROVIDER: S-EPMC8991261 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantum dots based in-vitro co-culture cancer model for identification of rare cancer cell heterogeneity.

Vyshnava Satyanarayana Swamy SS Pandluru Gayathri G Kumar Kanderi Dileep KD Panjala Shiva Prasad SP Banapuram Swathi S Paramasivam Kameshpandian K Devi Kothamunireddy Varalakshmi KV Anupalli Roja Rani RR Dowlatabad Muralidhara Rao MR

Scientific reports 20220407 1

Cancer cell heterogeneity (CCH) is crucial in understanding cancer progression and metastasis. The CCH is one of the stumbling blocks in modern medicine's therapeutics and diagnostics . An in-vitro model of co-culture systems of MCF-7, HeLa, HEK-293, with THP-1 cells showed the occurrence of EpCAM positive (EpCAM+) and EpCAM negative (EpCAM-) heterogenetic cancer cell types labeled with the Quantum Dot antibody conjugates (QD<sup>Ab</sup>). This in-vitro model study could provide insights into t ...[more]

PMID: 35393460

Similar Datasets

Project description:Cancer treatment resistance is a caused by presence of various types of cells and heterogeneity within the tumor. Tumor cell-cell and cell-microenvironment interactions play a significant role in the tumor progression and invasion, which have important implications for diagnosis, and resistance to chemotherapy. In this study, we develop 3D bioprinted in vitro models of the breast cancer tumor microenvironment made of co-cultured cells distributed in a hydrogel matrix with controlled architecture to model tumor heterogeneity. We hypothesize that the tumor could be represented by a cancer cell-laden co-culture hydrogel construct, whereas its microenvironment can be modeled in a microfluidic chip capable of producing a chemical gradient. Breast cancer cells (MCF7 and MDA-MB-231) and non-tumorigenic mammary epithelial cells (MCF10A) were embedded in the alginate-gelatine hydrogels and printed using a multi-cartridge extrusion bioprinter. Our approach allows for precise control over position and arrangements of cells in a co-culture system, enabling the design of various tumor architectures. We created samples with two different types of cells at specific initial locations, where the density of each cell type was carefully controlled. The cells were either randomly mixed or positioned in sequential layers to create cellular heterogeneity. To study cell migration toward chemoattractant, we developed a chemical microenvironment in a chamber with a gradual chemical gradient. As a proof of concept, we studied different migration patterns of MDA-MB-231 cells toward the epithelial growth factor gradient in presence of MCF10A cells in different ratios using this device. Our approach involves the integration of 3D bioprinting and microfluidic devices to create diverse tumor architectures that are representative of those found in various patients. This provides an excellent tool for studying the behavior of cancer cells with high spatial and temporal resolution.

Dataset Information

Quantum dots based in-vitro co-culture cancer model for identification of rare cancer cell heterogeneity.

Publications

Quantum dots based in-vitro co-culture cancer model for identification of rare cancer cell heterogeneity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets