Pancreatic cancer is often referred to as the "king of cancers" due to its poor prognosis, with a 5-year survival rate below 10%. Even for localized cancers, the survival rate is only 40%–45%. Recently, a research team led by Professors Zhao Yupei and Liao Quan from Peking Union Medical College Hospital published an article in Molecular Cancer introducing a novel therapy. According to their cellular experiments, this new therapy can inhibit cancer progression and has shown synergistic enhancement when combined with chemotherapy.
In recent years, immune checkpoint inhibitors and CAR-T therapies, which have garnered significant attention, have shown less than ideal efficacy in treating pancreatic cancer. Chimeric Antigen Receptor Macrophages (CAR-M), however, offer particular advantages for solid tumors, especially demonstrating strong infiltration into pancreatic cancer tissue. To this end, the research team has developed CAR-M cells targeting the c-MET receptor to achieve precise targeted destruction of tumors.
Studies have shown that c-MET is significantly upregulated in pancreatic tumor cells compared to normal cells, which also correlates with a shortened overall survival period. The new therapy effectively targets and kills these overexpressing tumor cell lines. When combined with chemotherapy, it significantly enhances the cytotoxic effects of four chemotherapeutic drugs against tumor cells.
In tumor model mouse trials, the new therapy has been shown to reduce tumor burden and extend the lifespan of the mice, with no significant side effects observed. The next step is to proceed to clinical trials to evaluate the actual efficacy of this treatment on solid tumors. Of course, there is still a long and challenging road ahead in the quest to overcome pancreatic cancer.
A recent review in the "Journal of Hematology & Oncology" highlights that, in addition to CAR-M therapies, numerous clinical trials are underway for pancreatic cancer, exploring a range of approaches such as cancer antigen vaccines, therapies targeting the tumor microenvironment, PARP inhibitors, and agents aimed at KRAS mutations. Moreover, as more clinical data accumulates, machine learning and artificial intelligence (AI) are poised to significantly accelerate the development of new drugs.
