A Combination Therapy for Non-small Cell Lung Cancer
Advisor: Karen Allendoerfer
Onsite Mentor: Dr. John Santiago
Lung cancer is the leading cause of cancer-related deaths in the United States, with a mortality rate of 51.6 per 100,000 for men and 34.4 per 100,000 for women. Out of these, about 85% of cases are non-small cell lung cancer, a more common and less aggressive type. Yet, treatments for lung cancer are not extremely effective in combating the lung cancer cells. I will be focusing on immunotherapy, a type of treatment used for cancers that essentially activates T-cells to attack cancer cells. The goal of this project is to improve the efficiency of the immunotherapeutic drug, ipilimumab, against lung cancer, by combining it with an anti-cancer vaccine.
Project Blog
Post 1: Becoming a Tumornator!
Hi, I’m Akshaya! Welcome to the first week of my senior project blogs!
Before we start delving deeper into the fascinating world of cancer biology, here is some basic information about myself, my motivations, and my project itself!
Cancer, as many of you may know, is a disease caused by the uncontrolled division of abnormal cells in the body. It can spread to many areas, or it can remain localized in one particular part of the body as well.
I have been interested in cancer research from a young age. My grandfather passed away from bone cancer. In his case, the first round of chemotherapy worked but just as he started his second round, his body didn’t react well and he passed away. From this personal loss, I became curious about how cancer works, and the fatality rate of cancer piqued my interest in wanting to work in cancer research.
In 10th grade, I attended a talk by Dr. Mario Capecchi, a famous Nobel laureate who is known for his work in gene-targeting in mice. He talked about the applications for his work in cancer, which inspired me to start looking for research experiences regarding cancer. By manipulating specific genes within mouse-derived embryonic stem cells, he discovered how to genetically engineer a mouse devoid of a specific gene to analyze the specific function of a particular gene by investigating its absence. This has become important in the analysis of genetic mutations common in cancer patients, and genetics-based cancer research. In 11th grade, I was accepted to an internship at Berkeley Pharma Tech, where I, along with a team, wrote a research paper regarding the tumor microenvironment and immunotherapy. I focused on checkpoint inhibitors and cellular pathways of cancer, learning about the involvement of CTLA-4 and PD-1 (checkpoint inhibitors) in tumor growth. Additionally, I studied signaling pathways involved, like the mTOR and AMPK pathways. Our team also studied how we can use CAR T-cell therapy, a type of cancer immunotherapy treatment that uses genetically altered T-cells to destroy cancer cells more effectively and use CD8+ T cells to fight the spread of tumors. Enzymes, signaling pathways, and molecules involved are very important in cancer research as they could hold the key to unlocking new therapies, especially in immunotherapy.
For my project, I specifically chose lung cancer, as it is the second most common type of cancer in both males and females in the United States. About 80-85% is diagnosed as non-small cell lung cancer (NSCLC) and about 10-15% of lung cancers are diagnosed as small cell lung cancer (SCLC). There has been a lot of research as to how we can cure cancer, and one such field in the modern day is immunotherapy. Immunotherapy is focused on boosting parts of the immune system in order to find and destroy cancer cells, and thus has been termed to be more precise than other cancer therapies, with less side effects.
Unfortunately, many of the current therapies in cancer treatments aren’t very effective at treating late stage lung cancer, which is when most people get diagnosed. Many medications are extremely expensive, meaning that many times people cannot afford to get the treatment they need. With my project, I hope to find a novel potential treatment for non-small cell lung cancer that is also cheaper for people to use. This experiment can help increase the effectiveness of immunotherapy treatment in lung cancer by combining two natural compounds, curcumin and quercetin, that have been known for their immune modulatory effects.
Well then, here comes the end of today’s blurb, and I sincerely hope you will join me on my next blog! Until then!
Post 2: A little more background...
Hey guys! Welcome back to my blog - I'm really glad you're here! Today is going to be more of a info day, with a lot more research about the topics involved in my project! Wear your seatbelts, cuz it's going to be a hectic flight off to the world of cancer biology!
(apologies for the really bad jokes - my sense of humor is broken :))
Lung cancer is the second most common type of cancer in both males and females in the United States. About 80-85% is diagnosed as non-small cell lung cancer (NSCLC) and about 10-15% of lung cancers are diagnosed as small cell lung cancer (SCLC). There has been a lot of research as to how we can cure cancer, and one such field in the modern day is immunotherapy. Immunotherapy is focused on boosting parts of the immune system in order to find and destroy cancer cells, and thus has been termed to be more precise than other cancer therapies, with less side effects.
Unfortunately, many of the current cancer therapies aren’t very effective at treating late stage lung cancer, which is when most people get diagnosed. Many medications are extremely expensive, meaning that many times people cannot afford to get the treatment they need. With my project, I hope to find a novel potential treatment for non-small cell lung cancer that is also cheaper for people to use. This experiment can help increase the effectiveness of immunotherapy treatment in lung cancer by combining two natural compounds, curcumin and quercetin that have been known for their immune modulatory effects. To test my hypotheses, I will be using dose-response cytotoxicity/migration assays that are useful in measuring cell migration and invasion, especially for cancer cells.
Immune cells consist of T cells, B cells, Natural Killer cells (NK), macrophages (M1 and M2), stromal cells, endothelial cells, and cancer-associated fibroblasts that all function to suppress or promote tumor growth. T cells develop a T-cell receptor that recognizes specific antigens on a tumor cell and consequently kills the tumor cell, putting a halt to angiogenesis, which is the formation of new blood vessels. Angiogenesis is the process that produces all capillaries, and is regulated by a number of substances, including endostatin, adhesion molecules, and growth factors. Dysregulated angiogenesis contributes to tumor growth and metastasis. Tumor angiogenesis depends on interactions between tumor cells and endothelial cells, and VEGF, a signaling protein that promotes the formation of new blood cells plays an important role in the growth and survival of endothelial cells, which are important in cell proliferation and tumor angiogenesis. However, T-cells can also become immune infiltrated and dysfunctional. B cells are responsible for antibody production, antigen presentation, and secretion of cytokines. Furthermore, lymphocytes are made up of both T and B cells where tumor infiltrating lymphocytes (TILs) play a significant role in research. TILs kill tumor cells but are more likely to be recruited by the tumor microenvironment (TME) and cause dysfunction in an immune response. The regulatory T cells (Tregs) act to suppress immune responses to maintain homeostasis, which can be very dangerous once recruited to the TME as they inhibit the formation of T cells. Recruitment to the TME means that the regular functions of the immune system that worked for the body now works in favor of the TME. Already existing immune cell mechanisms now promote TME growth as opposed to inhibiting it. This is one of the biggest problems that many immunotherapeutic treatments aim to solve. The immune system is the natural defense mechanism that the human body uses to combat diseases, mainly using T-cells - which are one of the biggest targets of immunotherapy.
Quercetin and curcumin are both natural compounds that have immune modulatory effects, and thus are currently being explored as potential treatment options in immunotherapy. Quercetin has an anti-angiogenesis, anti-metastasis, and anti-proliferation effect on cancer cells. Quercetin has an anti-tumor effect by reducing development of blood vessels. Tumor angiogenesis and metastasis are caused by the interaction of VEGF and VEGF receptor 2 (VEGFR2). In addition, this natural component decreases tumor growth through targeting the VEGFR-2-mediated angiogenesis pathway and suppressing the downstream regulatory component AKT. Quercetin can also decrease cancer metastasis by suppressing various molecular pathways and angiogenesis. For example, in metastasis and progression of melanoma, the activation of c-Met receptor tyrosine kinase is important. Quercetin showed anti-metastatic activity in melanoma by inhibiting c-Met phosphorylation, reducing its homodimerization, and ultimately suppressing the HGF/c-Met signaling pathway. Additionally, quercetin also exhibits anti-proliferation effects on cancer cells. The p53 protein, as a tumor suppressor, plays an important role in preventing cancer by regulating the cell cycle, apoptosis, and DNA repair. Quercetin can induce cell cycle arrest and apoptosis in hepatocellular carcinoma cells (HCC) by stabilizing or inducing p53. Aurora B, a collection of kinases, is a member of the Aurora kinases family and plays a critical role in chromosomal alignment and segregation, and the inhibition of aurora B kinase resulted in cell-cycle arrest or even death. However, quercetin effectively suppresses anchorage-independent cell growth of lung cancer cells with highly expressed aurora B levels, and suppressed tumor growth of A549 cells by inhibiting aurora B. Quercetin also has a regulatory effect on immune cells and promotes the proliferation of γδ T cells and the differentiation of γδ T cells into Vδ2 T cells, which strengthens their antitumor ability.
Curcumin is the other natural compound that has been shown to have immunotherapeutic effects. Curcumin, extracted from ginger, has been shown to effectively inhibit tumor growth, proliferation, invasion, metastasis and angiogenesis in tumors, and can modulate the tumor immune response and the tumor microenvironment. Immune dysfunction usually happens during tumor progression and contributes to tumor immune evasion. CD8+ cytotoxic T lymphocytes (CTLs) are involved in antigen-specific tumor destruction and CD4+ T cells are essential for helping this CD8+ T cell-dependent tumor removal. Tumors often target and inhibit T-cell function to escape from the immune system, which causes the loss of effector and memory T cells, bias towards type 2 cytokines and expansion of T regulatory (Treg) cells.
Tumor cells induce apoptosis, which is induced cell death, of T cells by interfering with the production of NF-κB in T cells, making T cells susceptible to TNF-α-mediated apoptosis. Curcumin neutralizes oxidative stress of tumor cells, restores NF-κB activity and reactivates the TNF-α signal pathway, thereby enhancing the ability of T cells to resist apoptosis. It prevents this loss of T cells, expanded central memory T cell (TCM)/effector memory T cell (TEM) populations, reversed the type 2 immune bias and prevented the tumor-induced inhibition of T-cell proliferation in tumor-bearing hosts. Tumors also upregulates Treg cell populations and stimulates the production of the immunosuppressive cytokines transforming growth factor (TGF)-β and IL-10 in these cells. Curcumin inhibits this suppressive activity of Treg cells by downregulating the production of TGF-β and IL-10 in these cells.
More importantly, curcumin treatment enhanced the ability of effector T cells to kill cancer cells. Curcumin has also been shown to modulate signaling pathways involving Janus kinase (JAK)/signal transducers and activators of transcription (STAT), phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR), Wnt/β-catenin, vascular endothelial growth factor (VEGF)/vascular endothelial growth factor receptor (VEGFR) and genes such as cyclin D1, TP53, BAX, BCL-2, hTERT and MMPs, which modulate the proliferation, migration and invasion, cell cycle and cell apoptosis of tumor cells. In addition, curcumin is a good method to decrease levels of tumor growth factors, like tumor growth-factor β1, which is involved in the epithelial-mesenchymal transition in tumor cells.
In essence, by combining curcumin and quercetin to form a new combination therapy against non-small cell lung cancer, I hope to find an effective treatment against its migration and invasion capacity. Combining curcumin and quercetin can effectively block more pathways that cancer cells use to spread, which is incredibly important in the study of immunotherapy and cancer prevention.
Welp, that brings us to the end of today's blurb. I hope you enjoyed reading, and hopefully it wasn't too much of an info overload! Hope to see you next time!
Post 3: Cell culturing!
Hi y’all! Thanks for joining me again! This week was definitely a lot more interesting than the last two weeks, so I’m hoping this blog will be a lot more intriguing!
This week was my first week actually doing lab work - the last two weeks were mostly remote and full of researching papers and annotating - and I’m super happy for the change. My mentor in the lab and I discussed cell culturing and passaging techniques in order to effectively maintain the cell culture. In a project as long as this, it is incredibly important to ensure that the cells are healthy over a long period of time and have enough nutrients and space to grow - which is essentially what is meant by cell culture maintenance.
The most important parts of cell culture maintenance are feeding, hygiene, and timing. In cell culture growth, there are usually three phases - the lag phase, the log phase, and the stationary phase. Our goal is to keep the cells in the log phase, or growing phase. Since the cells need enough space to grow, we need to take into consideration the confluency, or the percentage of a culture dish or a flask occupied by any type of adherent mammalian cells, to ensure that we split the cells and move them to an empty flask so they have enough space to grow. My mentor and I also discussed aseptic work techniques, or hygienic techniques, in order to prevent any contamination of the cells that could potentially harm them and thus interfere with the experiment.
This week, I, along with my mentor, set up the cell cultures, and started practicing passaging the cells, or moving them to a new flask. Essentially, I will be detailing the steps I followed to maintain the cell cultures. First, I created a medium (basically cell food) for the cells by mixing a 500 mL store bought medium with 50 mL FBS (fetal bovine serum) and 5 mL of penicillin (as an antibiotic to kill any bacteria). Next I learned how to correctly passage cells. First, I needed to suck out the medium that was already in the flask the cells are in by using a vacuum pump. Next, I needed to wash the cells with 2 mL of PBS (phosphate buffered saline) before dissociating the cells (as they are attached to the walls of the plastic - on a side note, since A549 cells, which are the non-small cell lung cancer cells I am using, are adherent, they attach themselves to the walls of the plastic flask). Next, I added 500 microliters of trypsin, which is an enzyme, directly on the cells - this enzyme causes the cells to break away from the plastic and essentially float around. However, trypsin can cause cell death - so it is important to move on quickly after trypsin is added. After incubating the cells for 3-5 minutes afterward, I added 4.5 mL of the medium (which counteracts the effects of trypsin) that I created and resuspended the cells.
To transport some cells into the new flask, I added 4.5 mL of medium into the new flask. I then resuspended the cells from the old flask, and then added 0.5 mL of that into the new flask. To mix up the medium and the cells really well, I resuspended the cells again by repeatedly pipetting the solution in and out (essentially sucking in and spewing out using the pipette). This ratio is 1:10, meaning the cells will last about 3 to 5 days before I need to passage the cells again to ensure they have enough space to continue growing!
My mentor and I also discussed and started seeding for the 96 well, but I’ll explain more on that in the next blog! Although all the pipetting and process for cell culture maintenance seems quite simple, I soon found it to actually be quite difficult. I have to remember to work with aseptic techniques, which required a lot of observation of where my hands were going throughout the whole process. The whole maintenance part took me about an hour and a half - so it definitely is not easy! Surprisingly, pipetting was actually kind of hard - but I think I got used to it by the end of the week!
I had a lot of fun this week, and it was filled with a lot of hands-on activities and learning. I hope you will stay tuned for next week’s blog, where I will detail 96 well seeding as well as the proliferation assay that I will use for my results. Thank you for reading, and see you next time!
Adios! Au revoir! Sayonara!
Post 4: 96-well seeding
Hello all you wonderful people! I hope you had a great week - I certainly did! This week is more of a continuation of the previous week, so I'm hoping you will be just as intrigued as last week!
Before we go into that, I just wanted to show you guys some pictures of my cells!
So this is a picture of the cells at about 70% confluency - they are healthy and they have space for a day or two before they must be passaged.
Now, onto the good stuff! As promised, in this post, I will be going into detail about seeding the 96 well. Taking a step back to the previous blog (before we made the new flask), I mentioned something about adding 4.5 mL of medium to cells after adding trypsin to them (to dissociate them). After this, I resuspended the cells by repeatedly sucking them in and out. Now, here comes the new stuff. After resuspension, I take about 200 microliters of the solution and put it into a small tube.
Next, I have to count the cells - but if I need to count all of them by hand or by eye (which would mean that I have superpower vision that every optometrist dreams of), I would have grey hair by the end of it. Thus, I will be using a machine that simplifies the whole process. So first, I took a strip of parafilm, and then I pipetted 10 microliters of trypan blue (the dye the machine uses) as a drop onto the parafilm. Next, I resuspended the cells again (from the small tube from the previous step) - because cells have a tendency to drop to the bottom, so resuspending will help them be well-dispersed throughout. Next, I took 10 microliters of the cell solution and put it into the drop of dye, and then resuspended it a couple of times. Then, I took 10 microliters of this new mixed drop, and then put it into the machine. Then, all I had to do was press the button that said count - and I was good to go!
The machine gives a whole bunch of numbers - but the ones I really care about are the viability (percentage of healthy cells) and the live cell count. For this particular cell line, A549, anything above a 95% viability is pretty good - and luckily, all of mine have been above 96 when I counted them (which is definitely a good thing 🙂)
Now, onto 96-well seeding! So we use the live cell count number to do some calculations. Essentially, after discussing this with my mentor, we decided that 3000 cells per well (which is 100 microliters per well) is a good number to have - however, the number of cells from the cell count number is way too high. Thus, we need to dilute it, in a sense.
So this is the excel sheet (thank heavens for excel sheets) I made that details all the calculations. Essentially, the dilution factor is obtained by dividing the total live cells (calculated by the machine) by the cells/ml number (the cell concentration the counted cell concentration needs to be diluted to). For total volume, we need 96 wells x 100 microliter/well = 9600 microliters = 9.6 mL, which rounds up to about 10 mL. To find the amount of cell solution we need, divide total volume needed by the dilution factor, and then to find the amount of medium needed, subtract total volume from the cell volume - and BINGO, you have everything you need to create a seeding solution.
After pipetting the right amounts of medium and cell solutions into a tube, I then resuspended the solutions just to mix it up well to ensure the cells are evenly dispersed. Next, I used a micropipette to pipette 100 microliters of this seeding solution into every single well. It actually takes a lot of concentration and good pipetting technique (which sadly, took a long time for me to even start developing). Then, I incubated the 96 well.
This 96-well is what I will be putting into the proliferation assay to conduct my experiment. But, more on that later! In the next post, I hope to talk more about the treatment and the proliferation as well. I hope you have a great rest of the week!
Post 5: Serial Dilutions
Hey guys! Glad you could join me again! This week was a little all over the place, but I’m happy to know you guys are back here again!
This week, I learned how to do serial dilutions, which are incredibly important in later parts of the experiment regarding treatment. Serial dilutions, as you might have guessed, is essentially a stepwise dilution. So first, I had to do some calculations to figure out how much milliliters or microliters to make with having some extra as well (just for safety purposes). I decided to go with 600 microliters, and I decided to do 8 dilutions (because the 96 well has 8 rows).
Before we delve in, I wanted to go over my positive control, which is important later on in this story. I’m using SDS, which is sodium dodecyl sulfate, and it is known to basically kill all cells. Essentially, I’m using something that can kill cells to compare my combination treatment to. First, I pipetted 600 microliters of SDS into a small tube. Then for the next 6 small tubes, I pipetted 400 microliters of medium. Finally, for the last tube, I pipetted 600 microliters of medium. Then, I took 200 microliters from tube 1 and pipetted it into tube two, and resuspended it to mix it well, and then took 200 microliters of this new solution and pipetted it into tube three, and so forth. The last tube, however, remains only medium, while the first tube remains only SDS.
Now that the serial dilution is complete, we can move forward with treatment. You guys have all seen the 96 well, and hopefully know it has rows and columns. So now, I will pipette 100 microliters per well of tube 1 into row 1, tube 2 into row 2, and so forth, until all the rows are completed. Then, I incubated the well for a day.
Now it's time for the proliferation assay! The assay I am using is called the Alamar blue assay, and essentially it measures the mean fluorescence intensity (MFI). Alamar blue, or resazurin, is broken down by cells, and when it’s broken down, it exhibits fluorescence. Thus, it is a good measure for metabolic activity of cells, and this is what I’ll be using to measure whether the treatment has been working (less fluorescence = less metabolic activity = treatment working). First, I pipetted 20 microliter of Alamar blue into each well, and let it incubate for about an hour and a half. Then, I put the plate into the machine, which gave a reading of the MFI for each well.
In the next update, I will explain how I will analyze this data and plot it, as well as go into details of making solutions for my treatment chemicals! That brings us to the end of today’s blurb, and I hope you enjoyed learning about serial dilutions and the actual assay! Until next time!
Post 6: Making stock solutions!
Hey guys! Welcome back to my blog! I hope you had a great spring break!
Before we go into what I did this week, I promised to go over analyzing the data from last week, so here goes. Essentially, the proliferation assay gives us readings from each well of the mean fluorescent intensity - and we have 3 wells per each concentration of SDS in this case. So, we take the average and plot it, and then we also plot the standard deviation as the error bars.
This is what the graph ended up looking like. For the most part, there is a trend that is quite visible - the lower the SDS concentration, the higher the MFI (which makes sense because it means that there are more cells that didn’t die). However, there are 2 weird points - which probably has to do with either contamination or pipetting errors.
Onto this week’s work, which was all about stock solutions! What are they? They are concentrated solutions prepared ahead of time, and can be used to dilute and obtain solutions of desired concentrations. The compounds I’m using for the experiment, which are curcumin and quercetin, are in powder form, so it is necessary to make a stock solution out of them to be able to use it for treatments in my experiments.
I parsed through a lot of scientific literature about these compounds, and I ended up finding that about 10-100μM was a good amount to use. However, to make a stock solution, it is always better to have a higher molar concentration than a lower molar concentration, so I decided to make a 100mM stock concentration for both curcumin and quercetin.
So first, I found the molecular weight of the compounds through PubChem - curcumin was 368.39 g/mol and quercetin was 338.27 g/mol. So, 1 mM is equal to 0.368 mg/mL for curcumin and 0.338 mg/mL for quercetin, meaning that 100 mM = 36.84 mg/mL (curcumin) and 100mM = 33.83 mg/mL (quercetin).
Now, I went ahead and measured out some curcumin and some quercetin on a scale. Since these were in high dosage powdered form, they were extremely toxic if inhaled. Therefore, I took the necessary precautions by wearing a face mask, a lab coat, and gloves. Since it was impossible to get it to 100 mg exactly, I just measured out some amount, and decided it would be easier to adjust the amount of DMSO to dissolve the compound and make it a 100mM solution instead of chasing the Herculean task of getting it to exactly 100 mg (which would also provide more sources of error).
Here are my compounds after I measured them out.
To find the amount of DMSO needed, I divided the milligrams of the compound I measured out by the 100mM value (36.84 mg/mL (curcumin) and 33.83 mg/mL (quercetin)). I ended up taking 155 mg of curcumin, so I needed 4.21 mL of DMSO for it, and I took 118 mg of quercetin, so I needed 3.49 mL of DMSO for it.
I then mixed it up really well using a microliter pipette and ensured all of the compound was dissolved in the DMSO. However, because the compound was not under the fume hood during the measuring process, it is not sterile anymore, so I needed to make this new solution sterile again. For this, I used a sterilizing syringe, which essentially sucks up the solution using a syringe, and then passes it through a filter into a new bottle, thus sterilizing the solution. It was fairly simple to do, although I almost got poked by the needle 🙂. Now that the solutions were all made, I stored them in the fridge.
I took this picture after I put them in the fridge for like an hour, and because of that the DMSO got a little frozen, which is why the solution don’t look solutiony.
Anyway, I will be doing treatment with curcumin next week, (which I created a plan for and did all the calculations for this week) so that would mean that I needed a lot more cells to seed 6 96-well plates. Thus, I passaged my cells from a T25 flask (which holds 5 mL) to two T75 flasks (which both hold 18 mL each), so I have enough cells by Monday to start a round of the experiment.
Stay tuned for next week, because that’s when things will get a lot more interesting!
Post 7: Curcumin and Quercetin treatment
Hi y’all! I hope you guys all had a good break, and I’m glad you are here with me today! It was a lot of fun, but kind of stressful too, but it was definitely a new experience for me.
This week, I ran the experiments for curcumin and quercetin individually (meaning not the combined experiment). When I went in on Monday though, I received a big shock - there were no more 96-well plates in stock at the lab, and for me to complete the experiment in time, I had to start this week. So essentially, my mentor and I decided to discuss what we could do, and we decided to go with 48 well plates instead. These wells are a bit bigger, so instead of 100 microliters of cells and 100 microliters of treatment, it changed to 200 microliters of cells and 200 microliters of treatment. Thus, the calculations for the seeding and the serial dilutions all became a bit different, but because I already created a template in excel, all I had to do was just type in the new numbers, and I got all the information I needed.
Additionally, we created a new plate map - so instead of 3 wells with the same treatment amount, it became 2 wells with the same treatment amount (for repetition within the 1 assay). The time it takes for the experiment is essentially 5 days. Monday was Day -1, where I trypsinized the cells, and made the seeding solution for them.
Then, I seeded them (200 microliters of the cells) into 3 48 well plates - because I will be taking measurements after 24 hours, 48 hours, and 72 hours - so I needed to seed 1 plate per time stamp. I then put them into the incubator for them to grow.
Tuesday was Day 0, where I treated the cells with quercetin and curcumin. I calculated the amount of microliters of pure quercetin stock solution and curcumin stock solution I need to do the serial dilutions.
I then put two hundred microliters of the treatment into the well according to the plate map design, and then I also placed a negative control (of just medium and the treatment) to make sure that the fluorescence is coming from the cells and not from the color of the chemicals (both quercetin and curcumin are yellowish-orange).
Wednesday was Day 1 - where I measured the MFI using the plate reader Alamar Blue assay for the 24 hour seeded plate.
Thursday was Day 2 - where I measured the MFI using the plate reader Alamar Blue assay for the 48 hour seeded plate.
Friday was Day 2 - where I measured the MFI using the plate reader Alamar Blue assay for the 72 hour seeded plate.
Results seem to be looking good, although I will graph them next week.
Post 8: New Week, New Trials
Hey! Welcome back to the next edition of my blog! This week was quite similar to last week, so there isn’t too much information this week.
This is a graph of the curcumin data that I got from last week - as you can see, the 48 h data set has the best curve.
I will be doing the graphs for the quercetin next week, as well as create some more graphs for the combination treatments!
I did a rerun of the trials regarding the curcumin and the quercetin, essentially following the same steps of seeding the cells, treating them with the compounds, and measuring the MFI through the alamar blue assay. Since we found the best results from last week to be the 48h plate, I decided to seed another trial for just the 48 hour plate for both curcumin and quercetin individually.
This week, I also ran the combination treatment. Since the calculations for the 48 well require 200 microliters of cells and then 200 microliters of treatment, I had to put 100 microliters of curcumin and 100 microliters of quercetin in per well. This meant that the calculations for the serial dilutions would be different, so I once again used my handy dandy excel sheet to do the necessary calculations for the serial dilutions. I have also attached a picture of all the calculations for this trial below, as well as the plate map, so you guys get a better picture of what exactly I'm doing. Also, on a side note, the colors look so pretty!
Welp that's all for this week! Hope to see you again next week!
Post 9: Combination Treatment Trial
Hey guys! Welcome back to the next edition of my blog! This week was also quite similar to last week, so there isn’t too much information this week.
This week, I ran a combination treatment trial once again, which started off kind of chaotically. When I went to count and collect my cells to make the seeding solution, I realized that I didn’t have enough cells to do the experiment, which was surprising because I was sure I passaged them and gave them enough time to grow before Monday. (Even now, I’m still not too sure about what actually happened).
So, instead of Monday, I started the trials on Thursday, and today, I collected my 48 hour data points. I also got started on graphing my data points from the previous week(s), which I will show you down below.
Here is the combination treatment graph:
Here is the quercetin graph:
As you can see, the numbers for the combination are definitely lower than those for the quercetin, which is a good thing! I didn’t include the 24h graph for quercetin here because there was some error in it (it might have been something to do with my pipetting 😣)
Anyway, like I mentioned before, I did another trial of the combination treatment, and so far, the numbers seem to be looking good. I used the same calculations as last time for the serial dilutions, so all I had to really do this week was make sure to follow the excel sheets and pipette very carefully (which is nice because I really don’t like doing the calculations for the serial dilutions). The plate map also remains the same, so no major changes there!
Welp, that’s it for this week’s blog - I’ll see you next time!
Post 10: Some data, some graphs
Hey guys! Glad you could join me again! This week was again pretty similar to the last couple of weeks.
I finished taking the data for the combination trial this week, and I started plotting and analyzing the data.
Based on the graphs (and you can see this from last week too), the 48h curves look the nicest (both in terms of the curve itself and the R-squared value), so I will be comparing the 48h data curves for each the combination, the curcumin, and the quercetin trials.
This is what the graph looks like.
Although it might not look too different towards the higher concentrations (especially with the curcumin vs the combination), the combination treatment has a slightly lower MFI in higher concentrations as well. However, the key part is the IC50, which is the concentration needed to kill half the cells. The IC50 for quercetin is 32.33, for curcumin is 29.73, and for the combo is 17.72.
This shows that the combination is definitely much stronger than the two compounds individually, because less of it is required to kill the same amount of cells.
So that basically brings me to the end of the lab work, and now begins the less interesting parts of the project - the analysis, making the presentations, and writing up the final report.
Thank you for reading this week! I’ll see you again next week!
Post 11: Preparations for Senior Project
Hey guys! Glad you're back here again!
This week was not too different from the previous week. I finished making my presentation, finalized all the graphs, and also *GASP* animated my slides! I went over my presentations with my advisors, made some adjustments and new graphics, and just kept practicing over and revising my presentation.
I also started working on my final report, which takes the format of a research paper. This week was kind of less interesting than usual because it was a whole lot of busy work.
Thanks for tuning in this week, and see you next week for my final blog post! See ya soon :)!