Abstract
Precision medicine has been utilized for cancer treatments. The principle of precision
medicine study is to collect the molecular differences of tumors that are unique to certain
groups of patients. In order to maximize the treatment efficiency of Thai cancer patients, it is
crucial to select the most appropriate treatments to each patient. This study is a continuation
of our previous precision medicine researches for the past 3 years, which involved developing
patient-derived organoids biobank from colorectal and breast cancers which can be used as
patient avatar model for anti-cancer drug testing. We have also developed an Omics process
in examining biological specimens (blood and tissues) for neoantigen prediction and cancer
vaccine development. Moreover, utilizing multiplex digital pathology for evaluating tumor’s
environment and immune-evasion pathway is also crucial for immune-therapeutic drug
selection for the patients.
In this study, we further established patient-derived organoids from more types of
cancer. We collected 16 more specimens which were 12 ovarian cancer, 2 endometrial cancer,
and 1 Leiomyosarcoma. The organoids from ovarian cancer and endometrial cancer showed
slow growth. We cultured for more than 4 weeks in the subculture of each passage and in the
samples that were subcultured, the organoids grew slower. As a result, it has not been able
to multiply enough to test anti-cancer drugs.
For neoantigen peptide for personalized solid tumor treatment experiment, we
collected specimens from 16 cancer patients, which were 1 rectal cancer, 1 duodenum cancer,
4 melanoma cancer, 1 Renal cell carcinoma (RCC), and 9 breast cancer. Mutation details gained
from DNA sequencing and optimal tumor tumor characteristics showed that each patient had
his/her own unique neoantigens. RCC patient NV029 was the patient undergoing cancer
vaccine treatment. The patient’s white blood cells were collected and tested for immune
activation using ELISpot, and the results showed a high immune activation level with 20
peptide specific reactions. This level of response is reached at 12 weeks after the last dose of
vaccination.
For digital pathology experiment, we stained FFPE-slide sections of 16 cancer patients,
which were 1 Leiomyosarcoma, 1 RCC, and 10 Lung cancers, using 9-Color TLS panel. There
are 8 immune markers provided with this panel for detection of TCF-1, CXCL13, CD20, CD8,
CD4, PD-1, CD21, and PANCK. Our findings showed that all 10 lung cancers had TLS clusters,
which TLS had a good predictive effect on immunotherapy response. The data and process gained from this study can be used for analyzing results and
utilizing treatment planning which, in the future, can be implemented in the clinic so that the
treatments for Thai cancer patients will be towards the precision oncology.
