Release date: 2016-12-23
Cancer treatment is gradually entering a "precise" era, and research on genetic testing and immunotherapy is endless. However, the concept of precision treatment is rarely reflected in traditional treatments such as radiotherapy. Our impression of radiotherapy is always “indiscriminate attackâ€, and there are also a few people who believe that radiotherapy “does more harm than goodâ€.
Dr. Jacques Bernier
Dr. Javier F. Torres-Roca
But as early as 2004, Dr. Jacques Bernier and his colleagues from Switzerland published an article in the journal Nature Review Cancer. They believe that the development of radiation oncology is now at a turning point. We need to improve our technology, look at molecular biology and genetics, and more accurately 'target the target'."[1]
Today, more than a decade later, a group of scientists from the Moffitt Cancer Center published a study in the Lancet Oncology magazine, which developed a new genomics model that allows for radiation therapy. Become "personalized" [2].
In the early days, the co-author of the study, Dr. Javier F. Torres-Roca, led a team of researchers to develop a gene-based radiosensitivity index (RSI), starting with 10 specific genes (AR, c-Jun, STAT1, PKC). The expression levels of -beta, RelA, cABL, SUMO1, PAK2, HDAC1, and IRF1) were tested and then a mathematical formula was used to derive a value representing the sensitivity of the tumor to radiation therapy.
The researchers performed validation in patients with rectal cancer, esophageal cancer, breast cancer, head and neck cancer, glioblastoma, pancreatic cancer, and metastatic colorectal cancer. They found that patients with high RSI had significantly better radiotherapy. Therefore, the researchers determined that their next step is to use this result to derive a model that can quantify the "radiation treatment effect."
The researchers used the RNI value, the linear quadratic mathematical model, and the standard radiotherapy dose and the time and dose of each patient receiving radiotherapy to derive a genome-based model for adjusting radiotherapy dose (A genome-based model for adjusting radiotherapy dose, GARD), which predicts the efficacy of radiation therapy and directs the radiation dose to match the individual's tumor radiosensitivity. The higher the value of GARD, the better the efficacy of radiotherapy.
They called 8271 clinical samples from 20 tumor sites from the Total Cancer Care protocol. The TCC sample bank is a tumor sample and clinical sample for each cancer patient treated at various institutions since 2006. In addition to the Moffit Cancer Center, there are 17 organizations involved in the treatment. They used these data to calculate the GARD values ​​for each patient and found that they were distributed between 1.66 and 172.4. This range is very broad.
Moffett Cancer Center
Of the 8271 samples, the doses received were 45 Gy (2517), 60 Gy (4877) and 70 Gy and above (877). According to the number and proportion of this dose from low to high, the researchers also divided the GARD value into three corresponding "grades", the low grade is 0-30.40; the mid-range is 30.41-89.40; the high grade is 89.41-100 (GARD value exceeds 100) There are 9 people, classified in high grade).
The lower left corner of the figure is marked with different radiation doses represented by different colors. In Figure A, we can see that the GARD values ​​are from low to high color bands. The distribution of different doses is not well defined, and the dose is not completely proportional to the GARD value. The B, C, and D graphs are the ratios of the different doses of the low, medium, and high GARD values, respectively.
However, they found that the two groups of "bins" did not fully correspond. The data showed that in the group with a radiation dose of 45, the patient's GARD value was from 3.03-56.34; in the group with a dose of 60, the GARD value was 1.66. -122.38,; In the group with a dose of 70, the GARD value was from 9.73-172.4. This result reminds us that the effect of radiotherapy varies from person to person. The high dose does not represent a good effect. The dose of "moderate" may be less harmful to the human body, but it may not bring good therapeutic effect and become optimal. select.
Moreover, the GARD range of different types of cancer is also different. For example, glioma is a very radiation-resistant type of tumor, which occupies the lowest GARD value, while cervical cancer and head and neck cancer are highly sensitive to radiotherapy. The GARD value is also very high. Therefore, this also shows that the simple use of the RSI index can not completely represent the therapeutic effect, we need to combine the tumor type and genetic testing means, that is, using the GARD index, in order to determine the appropriate patient's individual radiation dose.
During the study, the researchers used five clinical tumor cohorts from different institutions (Erasmus Breast Cancer Cohort, 263; Karolinska Breast Cancer Cohort, 77; Moffett Lung Cancer Cohort, 60; Moffett Pancreatic Cancer Cohort, 40 and The GARD model was validated by the data from the Cancer Genome Atlas (TGCA) glioblastoma cohort (98). By analyzing the multivariate Cox model, they determined that GARD values ​​were independently associated with clinical outcomes. The GARD model can be used as a predictor of radiotherapy effects.
5-year non-metastatic survival comparison of Erasmus breast cancer patients (green for patients with high GARD, purple for patients with low GARD)
They also followed a post-radiation follow-up of 263 breast cancer patients from Erasmus in one of five groups of data, and their 5-year non-metastatic survival. In this group of patients, GARD values ​​greater than or equal to 38.9 are those with high GARD values, and those with lower GARD values ​​are lower. The tracking results show that the radiotherapy effect of the high GARD population is indeed better, and the survival rate of patients in the same time. Relatively high.
Dr. Torres-Roca said, "We have seen in the study that even with the same cancer, the GARD values ​​of different patients are very different, which tells us that their sensitivity to radiotherapy is different, which indicates that we Past radiation therapy has a lot of room for improvement and personalization."
For this research, Louis B. Harrison, director of the radiation oncology department at Moffett Cancer Center, gave a high rating. He believes that the GARD model is the first to link genetic testing with radiotherapy doses, providing researchers and physicians with a safe and viable way to "radiate oncology".
Earlier this year, researchers combined chemotherapy with genetic testing (whether or not chemotherapy is needed? Genetic testing is quietly changing the cancer treatment process.) Now, the other one of the "two giants of cancer traditional treatment", radiotherapy, has also begun to change itself with genetic testing. We can foresee that in the future treatment of cancer, we may first use genetic testing to predict the effectiveness of treatment programs, and then choose a solution with good efficacy and small harm to better achieve the "personalization" of cancer treatment.
The construction and verification of a small ps:GARD model involves complex statistical algorithms and needs to be applied to some analysis software. If you are interested in it, if you are interested in how to derive and how to calculate, you can search for the following references. [2], read the original.
references:
[1] Bernier J, Hall EJ, Giaccia A. Radiation oncology: a century of achievements. Nat Rev Cancer 2004; 4: 737–47.
[2] Scott J G, Berglund A, Schell M J, et al. A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study [J]. Lancet Oncol, 2015: 30648-9
Source: Singularity Network
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