Majority of differentially expressed genes are down-regulated during malignant transformation in a four-stage model

From primary to malignant - what changes? Bridging transcriptomics and proteomics to reveal the molecular changes during malignant transformation in a four-step cancer cell line model

In order to find out more about the changes that occur when a primary cell is transformed into an aggressive cancer cell, integration of biological information has proven to be successful. By bridging transcriptomics and antibody based proteomics data we showed how the major changes during malignant transformation could be scrutinized.

The transformation of normal cells to malignant cancer cells is a complex process that requires a myriad of biological changes that give rise to new capabilities such as a higher rate of cell division, altered metabolism, and the ability of cells to invade into new areas. To get the picture of these changes on a molecular level we used four cell lines that all originate from the same primary fibroblast cell type and that each represent a different stage during malignant transformation, from the primary "slowly growing" cells to highly proliferative cells that are capable of metastasizing and form tumors even in distant organs.

By sequencing the RNA of these cell lines, we observed that about 6% of all human protein coding genes are differentially expressed, and a majority of these are down regulated on the route to cancer. The up regulated genes are mainly involved in progression through the cell cycle and functions needed for the cells to divide at a higher rate. The downregulated genes are mainly encoding proteins that are expressed on the outside of the cells, indicating the ability of cancer cells to shut down many functions in order to fully focus on growth and division.

The large repository of in-house generated antibodies in the Human Protein Atlas enabled us to pursue our investigations with protein analysis using both immunofluorescence and immunohistochemistry. Several interesting candidates with differential protein expression patterns between the different cell lines were found. A subset of these where analyzed in matched sets of cancer tissues with different degree of malignancy where the expression patterns seen in the tissue samples were highly correlated to our observations in the cell lines.

This paper exemplifies well how an integrative approach can be used to profile the molecular changes underlying malignant transformation. The possibility to validate the results generated with RNA sequencing on protein level, both in the same cell lines as well as in matching real cancer tissues, also laid the ground for future studies of cancer related mechanisms using the same cell line model system.

Read the full article about molecular changes in malignant transformation here.

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