Failure to Find a Cure for Cancer May Be Due to the Difference between Laboratory Cultured Cancer Cells and Those in the Human Body

Cancer has long fascinated the science world. what is it? What are the triggers? Why does it behave the way it does?

Scientists the world over have been interested in understudying cancer cell lines in the hopes of unraveling a key to possibly putting an end to the cancer menace or at least slowing the progression. Cancer

To meet these ends, scientists research different models of cancer, chiefly cancer cells extracted from the host [humans] and cultured on a laboratory disk. However, recent evidence, from John Hopkins, says that research based on a cancer model cultured in the laboratory could be faulted as these malignancies do not bear sufficient semblance with the original cancer cells that grow in the host.

CancerNetCells

Table of Contents

1 CancerNetCells
2 Clinical significance
3 Conclusion
- - 3.0.1 References

John Hopkins Scientists developed a computational technique that revealed that RNA sequences of cancer cells cultured in the laboratory and those that grew in humans were dissimilar. The scientists called this computational technique the CancerCellNet.

The bottom line is that for us to continue meaningful studies on a cancer cell, a new model has to be developed.

Furthermore, the scientists of John Hopkins hospital discovered that, unlike the cultured cancer cells, tumoroids (tumor-like organoids), and genetically engineered mice bear close genetic semblance, to cancer cells when you compare their RNA sequences. The computer tool CancerCellNet was used to confirm this.

To put this to perspective, an average of 4 out of 5 different tumors in genetically engineered mice or tumoroids have a similar RNA sequence to the tumors they tested. These show that human interacts with a tumor in complex ways that differ from the laboratory environment.

That said, we must shift our focus if we aim to correctly evaluate genetic aberrations that offset cancer growth and progress and devise a possible treatment.

Dr. Cahan Patrick, One of the lead investigators and associate professors of biomedical engineering described the exercise by saying, “It may not be a surprise to scientists that cancer cell lines are genetically inferior to other models, but we were surprised that genetically engineered mice and tumoroids performed so very well by comparison… once you take tumors out of their natural environment, cell lines start to change”

Before the advent of CancerCellNet, researchers had implanted cancer cells from humans to mice [xenograft], they checked if they displayed classical features of cancer. But this method was time and cost-prohibitive, and even difficult to achieve.

The researchers evaluated their novel tool by applying it to already known tumor types from the International Human Genome Sequencing Consortium.

They further supported this evidence when they carried out more experiments on 22 different tumors selected from a list of 657 cancer cell lines in labs all over the world–415 xenografts, 26 genetically engineered mice, and 131 tumoroids.

Clinical significance

It is not enough to study cancer cells with the hope of finding a cure, it has to be done right! As we have discussed, studies have shown that the knowledge we have garnered thus far using the laboratory cultured model of cancer might be all wrong and can lead to more confusion in the science. As such, we have to start all over with cancer cell constructs that reflect the events ongoing in cancer cells.

Conclusion

Hundreds of billions of dollars have already been spent on cancer research yet a cure for this scourge keeps eluding us. Would we have already found a cure if we were using laboratory cancer cells that actually reflect the cells within the body? Only time will tell as there is still a need for more improvement according to Dr. Cahan whose team is uploading more RNA sequencing data to boost the reliability of CancerCellNet.