ICG-labeled PD-L1-antagonistic affibody dimer for tumor imaging and enhancement of tumor photothermal-immunotherapy.

In clinical practice, tumor-targeting diagnosis and immunotherapy against programmed death ligand 1 (PD-L1) have a significant impact. In this research, a PD-L1-antagonistic affibody dimer (ZPD-L1) was successfully prepared through Escherichia coli expression system, and conjugated with the photosensitizer of ICG via N-hydroxysuccinimide (NHS) ester to develop a novel tumor-targeting agent (ICG-ZPD-L1) for both tumor imaging diagnosis and photothermal-immunotherapy simultaneously. In vitro, ZPD-L1 could specifically bind to PD-L1-positive LLC and MC38 tumor cells, and ICG-ZPD-L1-mediated photothermal therapy (PTT) also showed excellent phototoxicity to these tumor cells. In vivo, ICG-ZPD-L1 selectively enriched into the PD-L1-positive MC38 tumor tissues, and the high-contrast optical imaging of tumors was obtained. ICG-ZPD-L1-mediated PTT exhibited a potent anti-tumor effect in vivo due to its remarkable photothermal properties. Furthermore, ICG-ZPD-L1-mediated PTT significantly induced the immunogenic cell death (ICD) of primary tumors, promoted maturation of dendritic cells (DCs), up-regulated anti-tumor immune response, enhanced immunotherapy, and superiorly inhibited the growth of metastatic tumors. In addition, ICG-ZPD-L1 showed favorable biosafety throughout the brief duration of treatment. In summary, these results suggest that ICG-ZPD-L1 is a multifunctional tumor-targeting drug integrating tumor imaging diagnosis and photothermal-immunotherapy, and has great guiding significance for the diagnosis and treatment of clinical PD-L1-positive tumor patients.

Targeted co-delivery of resiquimod and a SIRPα variant by liposomes to activate macrophage immune responses for tumor immunotherapy.

Tumor-associated macrophages (TAMs) are the major immune cells infiltrating the tumor microenvironment (TME) and typically exhibit an immunosuppressive M2-like phenotype, which facilitates tumor growth and promotes resistance to immunotherapy. Additionally, tumor cells tend to express high levels of CD47, a "don't eat me" signal, that obstructs macrophage phagocytosis. Consequently, re-educating TAMs in combination with CD47 blockage is promising to trigger intense macrophage immune responses against tumors. As a toll-like receptor 7/8 agonist, resiquimod (R848) possesses the capacity to re-educate TAMs from M2 type to M1 type. We found that intratumoral administration of R848 synergistically improved the antitumor immunotherapeutic effect of CV1 protein (a SIRPα variant with high antagonism to CD47). However, the poor bioavailability and potential toxicity of this combo strategy remain a challenge. Here, a TAMs-targeted liposome (named: R-LS/M/CV1) co-delivering R848 and CV1 protein was constructed via decorating mannose on the liposomal surface. R-LS/M/CV1 exhibited high abilities of targeting, re-education and pro-phagocytosis of tumor cells to M2 macrophages in vitro. Intratumoral administration of R-LS/M/CV1 remarkedly eliminated tumor burden in the MC38 tumor model via repolarization of TAMs to M1 type, pro-phagocytosis of TAMs against tumors, and recruitment of tumor-infiltrating T cells. More encouragingly, due to the double targeting to TAMs and tumor cells of mannose and CV1 protein, R-LS/M/CV1 effectively accumulated at the tumor site, thereby not only remarkedly inhibiting tumors, but also exerting no hematological and histopathological toxicity when administered systemically. Our integrated strategy based on re-educating TAMs and CD47 blockade provides a promising approach to trigger macrophage immune responses against tumors for immunotherapy.

Boundary optimization of inclined coal seam open-pit mine based on the ISSA-LSSVR coal price prediction method.

As an important link in the complex system engineering project of open pit mining, the quality of the boundary determines the performance of the project to a large extent. However, changes in economic indicators may raise doubts about the optimality of mining boundaries. In this article, a coal price time series forecasting model that considers some amount of redundancy is proposed, which combines an improved sparrow search algorithm (ISSA) and a least squares support vector regression machine regression (LSSVR) algorithm. The optimal values of the penalty factor and kernel function parameter of the LSSVR model are selected by ISSA, which improves the prediction accuracy and generalization performance of the forecasting model. A multistep decision optimization method under fluctuating coal price conditions is proposed, and the model prediction results are applied to the boundary optimization design process. Using the widely applied block model as the basis, a set of optimal production nested pits is obtained, allowing the realm design results to fit the coal price fluctuation trend and further enhance enterprise efficiency. The applicability and effectiveness of this method were verified by taking an ideal two-dimensional model and an inclined coal seam open-pit coal mine in Xinjiang as an example.