Pentacyclic triterpene-amino acid derivatives induced apoptosis and autophagy in tumor cells, affected the JNK and PI3K/AKT/mTOR pathway.

A series of pentacyclic triterpene-amino acid derivatives were synthesized and tested for anti-proliferative activity. The results showed that most of the target compounds had good anti-proliferative activity. 2c did not contain protecting groups and hydrochloride, had excellent cytotoxicity, so it had been selected for further study in the mechanism of action in T24 cells. The data from transcriptome sequencing indicated that 2c was found to be closely related to apoptosis and autophagy. Observation of fluorescence staining and analysis from flow cytometry demonstrated that 2c induced apoptosis and cause cell cycle arrest in S/G2 phase in T24 cells. Molecular mechanism studies exhibited that 2c induced apoptosis in the intrinsic and extrinsic pathways. 2c also induced cellular autophagy in T24 cells. Results from Western Blotting showed that 2c could activate JNK pathway and inhibit PI3K/AKT/mTOR pathway. In conclusion, 2c was deserved further investigation in the field of anti-tumor.

(4-Picolylamino)-17ß-Estradiol derivative and analogues induce apoptosis with death receptor trail R2/DR5 in MCF-7.

In order to discover more effective and less toxic drugs in the field of anti-tumor, the backbone structure of 17ß-estradiol was modified, and 11 target compounds were synthesized. Compounds 5 and 10, which exhibited better anti-tumor activity and higher selectivity (more than 10-fold), were chosen for further biological investigation. Flow cytometry results indicated that 5 and 10 could arrest MCF-7 cells in the G2 phase and induce apoptosis. Immunohistochemical analysis revealed that 5 and 10 could bind to the estradiol receptor alpha in MCF-7 cells. Western blotting and real-time PCR assays were performed to detect the effects of compounds on apoptosis-related targets at the protein and gene levels. These results showed that both 5 and 10 could dosed-dependently increase the expression of Apaf-1, Bax, caspase-3,8,9 and reduce the expression levels of the anti-apoptotic factors Bcl-2 and Bcl-xL. Besides, the Human apoptosis array assay demonstrated the expression level of death receptor Trail R2/DR5 was upregulated obviously while the expression of TNF R1, IAPs and Hsp27/60/70 were downregulated. On the whole, 5 induced MCF-7 cell death through the endogenous pathway in mitochondria and the exogenous pathway with death receptor Trail R2/DR5.

Learning Optimal Distributionally Robust Individualized Treatment Rules.

Recent development in the data-driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and outcomes, policy makers best individualized treatment rule (ITR) that maximizes the expected outcome, known as the value function. Many existing methods assume that the training and testing distributions are the same. However, the estimated optimal ITR may have poor generalizability when the training and testing distributions are not identical. In this paper, we consider the problem of finding an optimal ITR from a restricted ITR class where there is some unknown covariate changes between the training and testing distributions. We propose a novel distributionally robust ITR (DR-ITR) framework that maximizes the worst-case value function across the values under a set of underlying distributions that are "close" to the training distribution. The resulting DR-ITR can guarantee the performance among all such distributions reasonably well. We further propose a calibrating procedure that tunes the DR-ITR adaptively to a small amount of calibration data from a target population. In this way, the calibrated DR-ITR can be shown to enjoy better generalizability than the standard ITR based on our numerical studies.

Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules.

We thank the opportunity offered by editors for this discussion and the discussants for their insightful comments and thoughtful contributions. We also want to congratulate Kallus (2020) for his inspiring work in improving the effciency of policy learning by retargeting. Motivated from the discussion in Dukes and Vansteelandt (2020), we first point out interesting connections and distinctions between our work and Kallus (2020) in Section 1. In particular, the assumptions and sources of variation for consideration in these two papers lead to different research problems with different scopes and focuses. In Section 2, following the discussions in Li et al. (2020); Liang and Zhao (2020), we also consider the efficient policy evaluation problem when we have some data from the testing distribution available at the training stage. We show that under the assumption that the sample sizes from training and testing are growing in the same order, efficient value function estimates can deliver competitive performance. We further show some connections of these estimates with existing literature. However, when the growth of testing sample size available for training is in a slower order, efficient value function estimates may not perform well anymore. In contrast, the requirement of the testing sample size for DRITR is not as strong as that of efficient policy evaluation using the combined data. Finally, we highlight the general applicability and usefulness of DRITR in Section 3.

Synthesis of acyl oleanolic acid-uracil conjugates and their anti-tumor activity.

BACKGROUND: Oleanolic acid, which can be isolated from many foods and medicinal plants, has been reported to possess diverse biological activities. It has been found that the acylation of the hydroxyl groups of the A-ring in the triterpene skeleton of oleanolic acid could be favorable for biological activities. The pyrimidinyl group has been constructed in many new compounds in various anti-tumor studies. RESULTS: Five acyl oleanolic acid-uracil conjugates were synthesized. Most of the IC50 values of these conjugates were lower than 10.0 µM, and some of them were even under 0.1 µM. Cytotoxicity selectivity detection revealed that conjugate 4c exhibited low cytotoxicity towards the normal human liver cell line HL-7702. Further studies revealed that 4c clearly possessed apoptosis inducing effects, could arrest the Hep-G2 cell line in the G1 phase, induce late-stage apoptosis, and activate effector caspase-3/9 to trigger apoptosis. CONCLUSIONS: Conjugates of five different acyl OA derivatives with uracil were synthesized and identified as possessing high selectivity toward tumor cell lines. These conjugates could induce apoptosis in Hep-G2 cells by triggering caspase-3/9 activity.Graphical abstractFive acyl oleanolic aicd-uracil conjugates were synthesized. These conjugates exhibited selective cytotoxicity toward tumor cells achieved via inducing apoptosis by activation of caspase-3/9.