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Tumor cells, inflammatory cells and chemical factors work together to mediate complex signaling networks, which forms inflammatory tumor microenvironment (TME). The development of breast cancer is closely related to the functional activities of TME. This review introduces the origins of cancer-related chronic inflammation and the main constituents of inflammatory microenvironment. Inflammatory microenvironment plays an important role in breast cancer growth, metastasis, drug resistance and angiogenesis through multifactorial mechanisms. It is suggested that inflammatory microenvironment contributes to providing possible mechanisms of drug action and modes of drug transport for anti-cancer treatment. Nano-drug delivery system (NDDS) becomes a popular topic for optimizing the design of tumor targeting drugs. It is seen that with the development of therapeutic approaches, NDDS can be used to achieve drug-targeted delivery well across the biological barriers and into cells, resulting in superior bioavailability, drug dose reduction as well as off-target side effect elimination. This paper focuses on the review of modulation mechanisms of inflammatory microenvironment and combination with nano-targeted therapeutic strategies, providing a comprehensive basis for further research on breast cancer prevention and control.

Funder: National Nature Science Foundation of China 81922058 National Science and Technology Major Project 2019YFC1315702 Guangdong Province Key Research and Development Program 2019B020226002 National Youth Top-Notch Talent Support Program 283812 Peking University Clinical Medicine plus X Youth Project PKU2019LCXQ012, Cutaneous T cell lymphoma (CTCL) represents a heterogeneous group of non-Hodgkin lymphoma distinguished by the presence of clonal malignant T cells. The heterogeneity of malignant T cells and the complex tumor microenvironment remain poorly characterized. With single-cell RNA analysis and bulk whole-exome sequencing on 19 skin lesions from 15 CTCL patients, we decipher the intra-tumor and inter-lesion diversity of CTCL patients and propose a multi-step tumor evolution model. We further establish a subtyping scheme based on the molecular features of malignant T cells and their pro-tumorigenic microenvironments: the TCyEM group, demonstrating a cytotoxic effector memory T cell phenotype, shows more M2 macrophages infiltration, while the TCM group, featured by a central memory T cell phenotype and adverse patient outcome, is infiltrated by highly exhausted CD8+ reactive T cells, B cells and Tregs with suppressive activities. Our results establish a solid basis for understanding the nature of CTCL and pave the way for future precision medicine for CTCL patients.

Background Breast cancer is the most frequently occurring cancer among women. Baicalin has been shown to inhibit breast cancer proliferation, but poor aqueous solubility and unknown mechanism of action limit its application. This study aimed to investigate the antiproliferative effects of baicalin-loaded folic acid-modified albumin nanoparticles (FA-BSANPs/BA) in breast cancer MCF-7 cells and its relationship with autophagy and ROS-mediated p38 MAPK and Akt/mTOR signaling pathways. Cell viability was detected by MTT assay. Flow cytometry and fluorescence microscopy were used to detect cell cycle, apoptosis and autophagy. Western blot was used to detect protein expression. Results Compared with the control and free baicalin groups, FA-BSANPs/BA inhibited viability of MCF-7 cells and increased cells in S phase, apoptotic bodies, pro-apoptotic proteins, autophagy markers and autophagosomes. These effects could be reversed when combined with the autophagy inhibitor 3-methyladenine. FA-BSANPs/BA increased the levels of phosphorylated p38 MAPK, inhibited the levels of phosphorylated Akt and mTOR, and increased the level of ROS in MCF-7 cells. The effects of FA-BSANPs/BA could be reversed or enhanced using inhibitors of Akt, mTOR, p38 MAPK and ROS scavengers. Conclusions Encapsulation in folate albumin nanoparticles improved the antiproliferative activity of baicalin. FA-BSANPs/BA induced autophagy and apoptosis via ROS-mediated p38 MAPK and Akt/mTOR signaling pathways in human breast cancer cells.

Background Brain image segmentation is the basis and key to brain disease diagnosis, treatment planning and tissue 3D reconstruction. The accuracy of segmentation directly affects the therapeutic effect. Manual segmentation of these images is time-consuming and subjective. Therefore, it is important to research semi-automatic and automatic image segmentation methods. In this paper, we propose a semi-automatic image segmentation method combined with a multi-atlas registration method and an active contour model (ACM). Method We propose a multi-atlas active contour segmentation method using a template optimization algorithm. First, a multi-atlas registration method is used to obtain the prior shape information of the target tissue, and then a label fusion algorithm is used to generate the initial template. Second, a template optimization algorithm is used to reduce the multi-atlas registration errors and generate the initial active contour (IAC). Finally, a ACM is used to segment the target tissue. Results The proposed method was applied to the challenging publicly available MR datasets IBSR and MRBrainS13. In the MRBrainS13 datasets, we obtained an average thalamus Dice similarity coefficient of 0.927 ± 0.014 and an average Hausdorff distance (HD) of 2.92 ± 0.53. In the IBSR datasets, we obtained a white matter (WM) average Dice similarity coefficient of 0.827 ± 0.04 and a gray gray matter (GM) average Dice similarity coefficient of 0.853 ± 0.03. Conclusion In this paper, we propose a semi-automatic brain image segmentation method. The main contributions of this paper are as follows: 1) Our method uses a multi-atlas registration method based on affine transformation, which effectively reduces the multi-atlas registration time compared to the complex nonlinear registration method. The average registration time of each target image in the IBSR datasets is 255 s, and the average registration time of each target image in the MRBrainS13 datasets is 409 s. 2) We used a template optimization algorithm to improve registration error and generate a continuous IAC. 3) Finally, we used a ACM to segment the target tissue and obtain a smooth continuous target contour.

Positive root response to metals may enhance metal accumulation for greater requirement in hyperaccumulators. The effects of spatially heterogeneous Zn/Cd addition on root allocation, metal accumulation, and growth of the Zn/Cd hyperaccumulator Sedum alfredii were assessed in a pot experiment. Young shoots of S. alfredii were grown with or without supplied Zn/Cd. Two concentrations were used of each metal, and each metal concentration had one homogeneous and two heterogeneous treatments. Growth increased by 1.6–3.2 times with the increasing overall dose of Zn/Cd addition, and shoot biomass was positively correlated with shoot Zn/Cd concentration (P < 0.001). In all heterogeneous treatments, the plants consistently allocated approximately 90% of root biomass to the metal-enriched patches, and shoot Zn/Cd contents were greater than or similar to those in the homogeneous treatment at each metal concentration. Plants in the control treatment showed symptoms of Zn deficiency, although their shoots had Zn concentrations 100-fold higher than the critical deficiency value for most plants. We conclude that S. alfredii has evolved root foraging mechanisms associated with its greater requirements for Zn/Cd. These results could have important implications both for phytoremediation and for investigation of positive role of Cd in higher plants.