Tumor immune evasion mechanisms could be reversed by activating intracellular antiviral immune responses. It has been reported that the use of DNA methyltransferase (DNMT) inhibitors combined with poly(ADP ribose) polymerase (PARP) inhibitors activated stimulator of interferon genes (STING) signaling pathway in a process named pathogen mimicry response.
A group of researchers in China have looked into the role of apolipoprotein B100 (ApoB100) in ovarian cancer following reports of excessive levels of ApoB100 inducing endoplasmic reticulum stress and cell death in liver cancer and of a positive correlation between ApoB100 levels and survival time of patients with high-grade epithelial ovarian cancer.
Chia Tai Tianqing Pharmaceutical Group Co. Ltd. has synthesized kinesin-like protein KIF18A inhibitors reported to be useful for the treatment of cancer.
Eterna Therapeutics Inc. has released promising results from a preclinical study of its lead cell therapy product, ERNA-101, showing it reduced tumor burden and extended survival in mice with ovarian cancer.
CSPC Pharmaceutical Group Ltd. has obtained clinical trial approval from China’s National Medical Products Administration (NMPA) for SYS-6041, an antibody-drug conjugate, for advanced solid tumors.
Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.
Simcere Zaiming Pharmaceutical Co. Ltd. has announced clinical trial approvals in China and the U.S. for its CDH6-targeting antibody-drug conjugate (ADC), SIM-0505, for advanced solid tumors. A global clinical study will evaluate SIM-0505 in various malignant tumors, including ovarian cancer and renal cancer.
Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.
Artificial intelligence (AI)-based models developed by a team of international researchers were able to identify ovarian cancer in ultrasound images more accurately than humans. Results from a study published in Nature Medicine showed that the AI models achieved an accuracy rate of 86.3%, compared to 82.6% for the experts and 77.7% for the non-expert examiners.
