Cell Cycle Revolution!

Like I’ve mentioned in my previous posts, the cell cycle is far from being a perfect circle. Thinking about it, it’s way too easy to only follow one beautiful shape. It would make sense that the cell would have a variety of replication paths to exploit, particularly in the event that its traditional path becomes obstructed or otherwise modified. Similar to how an animal’s priority is to mate and reproduce, the cell wants to divide into two daughter cells. The cell should do everything in its power to dive into mitosis, and from the looks of my research, it most certainly does.

During my work these past few months, I’ve been staining two tissue microarrays (aka TMA). These microarrays are composed of a variety of tissue slices from different parts of the body, like the bladder, breast, stomach, lung, and pancreas. Within these organs, there are three tissue slices of each. So, for example, I’ll have one core of the pancreas, and the two cores next to it are two versions of adenocarcinoma (cancer of pancreas). This layout (1 normal and 2 cancer) applies to a majority of the remaining organs on the TMA.

You may wonder why I’m looking at normal tissue samples on top of cancerous versions. It’s important, as well as advantageous, to be able to determine the cellular differences between a normal cell and its cancerous counterpart. Let’s say for example that the normal cell has a specific pathway like the following:

Mechanistic Target of Rapamycin (mTOR) Pathway

This is the mTOR pathway, which is necessary for cellular growth, metabolism, and protein synthesis (eventually leading to proliferation). So, if a cell exhibits aberrant mTOR signaling, this activity is linked to hyperproliferative diseases like cancer.

What would be very useful for researchers is to be able to see what specifically changed in this aberrant mTOR pathway (in the cancerous cell). Being able to visualize and determine the mechanistic difference of signaling between the normal cell and this cancer with the altered mTOR pathway would allow the development of drugs to target the modification. Looking in the figure above, notice that when glucose enters the cell, there is an increase in ATP/AMP, which inhibits AMPK. AMPK is necessary for inhibiting cell growth and proliferation. The cancerous cell may have some modification that involves an inhibitory kinase, so when ATP/AMP increases, the new inhibitory kinase may inhibit AMPK, which then allows for more growth and proliferation (which is cancer!).

After analyzing some preliminary data, I can finally say that our lab’s hypothesis is correct: the cell cycles are different among normal and cancer cells.

2D graphs created from three high-dimensional datasets using PHATE algorithm. The normal cells in the normal tissue are colored teal on the left . Cancer cells in the cancerous tissue are colored orange in the middle and blue on the right. Note that pdac1 (pancreatic ductal adenocarcinoma) and pdac2 are different because the tissues are from different people and they may have been exposed to different treatment plans. You may consider them as different cancers.

In the above figure, you can see that the normal and cancerous cells occupy different areas of space, which demonstrates the different cell cycle variants among the normal and cancer tissue. If the cell cycles were near identical, you’d see that pdac1 would be colored in the same region as the normal graph (teal).

Clearly, being able to diagnose cellular mechanisms and determine cellular paths between normal and cancerous cells is vital to understand cancer biology. I’m excited to continue this monumental work that Dr. Wayne Stallaert and I are working on.

I’ll update you as soon as I get more tissue analyzed!

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