Background
Artificial intelligence in oncology
Genomic medicine
Next generation cancer organoids
Nanoparticles
New chemotherapy delivery system
The references
Further reading
As we move into the future, oncology is experiencing remarkable breakthroughs thanks to cutting-edge technologies and innovative approaches. Five key advances are at the forefront: artificial intelligence (AI), genomic medicine, next-generation cancer organoids, nanoparticles, and pressurized intraperitoneal aerosol chemotherapy (PIPAC).
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Background
Cancer is a non-communicable disease with a significant prevalence worldwide. Every day, groundbreaking advances are made by scientists and researchers around the world, reshaping the landscape of oncology. This progress gives hope to both patients and healthcare professionals.
Chemotherapy, radiotherapy and surgery have characterized the fight against this disease for decades. Cancer research has made significant progress since the rise of personalized treatments and targeted therapies.
We are currently experiencing a transformative era in cancer research, with remarkable innovations paving the way for breakthrough treatments.
Artificial intelligence in oncology
Artificial intelligence (AI) and machine learning (ML) are computer systems designed and trained to help oncology doctors and healthcare professionals treat cancer patients.
These systems are extremely valuable because they can make the diagnosis and treatment process faster and more accurate.
ML has been used to visualize medical images, such as mammograms for breast cancer or CT scans for brain tumors. Evidence has shown that it can be very effective at finding and understanding these images, better than experienced doctors in some cases.
The main benefit of using ML is that it speeds up the time needed to detect and analyze cancer in these images. The results of the ML system are consistent and reliable, so the doctor’s level of experience in using it is irrelevant.
One of the main challenges faced by ML systems is that they require a lot of data to derive insights, which may not be available everywhere in the world. Cancers such as breast and colon cancer are more common, meaning there is a high volume of data, meaning this is a good place to study and improve the use of AI on a global scale, improving patient outcomes.
Using artificial intelligence to help detect breast cancer | Google Health
Genomic medicine
Genomic medicine involves studying and analyzing a patient’s genetic information, particularly their DNA, to better understand the genetic basis of diseases such as cancer.
Next generation sequencing (NGS) was discovered about a decade ago, making reading all the genetic information contained in whole genome sequencing (WGS) of a person’s DNA much easier and less expensive. This advancement made WGS more widely available for research and to help cancer patients.
The 100,000 Genome Project was set up in the UK and is using WGS to look at the DNA of more than 15,000 cancer patients. They compared the patient’s normal genetic information (germline) to the genetic makeup of their tumor.
The project provided detailed information to patients and their families, enabling them to understand the genetic basis of their cancer and how it can be treated.
The success of the 100,000 Genome Project has made it a valuable resource used in cancer research worldwide. Researchers can use this information to improve patient outcomes.
England’s National Health Service (NHS) established the NHS Genomic Medicine Service as a result of the project, offering genetic testing to patients with rare diseases and cancer, making it easier for future patients to benefit from the latest oncogenic advances .
Next generation cancer organoids
Next-generation cancer organoids are advanced 3D models of cancer cells that faithfully replicate the characteristics and behavior of tumors found in the human body. Organoids are created from the patient’s cancer cells and grown in the laboratory.
These models are powerful because they can retain important features of the original tumor, such as its genetics, proteins, and appearance, while allowing scientists to manipulate genes and the environment in ways that were not previously possible. not possible before.
Some challenges are encountered when creating these tumor models because the methods used in the laboratory can vary, leading to inconsistencies and unreliable results. Researchers are working to make these models more reliable and useful for patient care by standardizing the techniques used to create them.
By standardizing methods, researchers can better understand how different tumors behave and respond to treatments, leading to tailored therapies and improved patient outcomes in the future.
Nanoparticles
Nanoparticles are tiny particles designed to deliver drugs or therapeutic agents specifically to cancer cells.
The use of nanoparticles in cancer treatment is part of nanomedicine. This field explores how nanotechnology, including oncology, can improve the diagnosis, treatment and monitoring of diseases.
Thanks to their small size, they are more stable and safer for the body. They may also stay in the cancerous area longer, giving medications time to work. They can be designed to target cancer cells, reducing side effects and making treatment more effective.
Nanoparticle drug delivery has demonstrated its potential to overcome drug resistance observed in cancer treatment. By targeting specific mechanisms responsible for drug resistance, nanoparticles can help reverse multidrug resistance in cancer cells. As we discover more mechanisms of tumor drug resistance, nanoparticles are being refined to address these challenges.
Delivery of nanoparticle-based drugs in the fight against cancer
New chemotherapy delivery system (pressurized intraperitoneal aerosol chemotherapy)
Pressurized intraperitoneal aerosol chemotherapy (PIPAC) is an exciting and hopeful chemotherapy method to treat specific advanced abdominal cancers.
In PIPAC, chemotherapy drugs are delivered directly into the abdominal cavity as an aerosol, targeting and focusing treatment on tumors in that area. This approach holds great promise for improving the effectiveness of abdominal cancer treatment.
PIPAC is still considered a relatively new and evolving technique. Clinical trials and research are underway to determine its long-term effectiveness and safety compared to traditional treatment approaches.
PIPAC is not suitable for all cancer patients and is generally recommended for people with peritoneal metastases who have exhausted other treatment options.
With personalized treatments and targeted therapies, cancer research has evolved considerably. These revolutionary advances have brought us to an era where promising new treatments are now possible.
The references
- LeSavage, BL, Suhar, RA, Broguiere, N., Lutolf, MP, & Heilshorn, SC (2021). Next generation cancer organoids. Natural materials. do I: https://doi.org/10.1038/s41563-021-01057-5.
- Nadiradze, G., Horvath, P., Sautkin, Y., Archid, R., Weinreich, F.-J., Königsrainer, A. and Reymond, MA (2019). Overcoming drug resistance by leveraging physical principles: pressurized intraperitoneal aerosol chemotherapy (PIPAC). Cancers12(1), p.34. do I: https://doi.org/10.3390/cancers12010034.
- Seed, LM (2021). Horizon Scanning in Cancer Genomics: How advances in genomic medicine will change cancer care in the next decade. Current Reports on Genetic Medicine9(3), pp.37-46. do I: https://doi.org/10.1007/s40142-021-00200-7.
- Vobugari, N., Raja, V., Sethi, U., Gandhi, K., Raja, K. and Surani, SR (2022). Advances in oncology using artificial intelligence – A review article. Cancers14(5), p.1349. do I: https://doi.org/10.3390/cancers14051349.
- Yao, Y., Zhou, Y., Liu, L., Xu, Y., Chen, Q., Wang, Y., Wu, S., Deng, Y., Zhang, J. and Shao, A. ( 2020). Nanoparticle drug delivery in cancer treatment and its role in combating drug resistance. Frontiers of molecular biosciences(online) 7(193). doi.org/10.3389/fmolb.2020.00193
