Mounting evidence suggests that immunotherapies are a promising new class of anticancer therapies. However, the immunosuppressive tumor microenvironment (TME), poor immunogenicity, and off-target toxicity hinder the broader implementation of immunotherapies. Here, we describe a novel strategy combining chemotherapy and immunotherapy to modulate the TME by systemically and concurrently delivering the chemotherapeutic agent SN38 (7-ethyl-10-hydroxycamptothecin) and the STING agonist DMXAA (5,6-dimethylxanthenone-4-acetic acid) into tumors using triblock copolymer nanoparticles, named PS3D1@DMXAA, which enhances antigen cross-presentation and induces the conversion of the immunosuppressive TME to immunogenic TME through the newly found synergistic function between SN38 and STING activation. PS3D1@DMXAA thus shows potent therapeutic efficacy in three mice tumor models and elicits remarkable therapeutic benefit when combined with anti–PD-1 therapy. Our engineered nanosystem offers a rational design of an effective immunotherapy combination regimen to convert uninflamed “cold” tumors into “hot” tumors, addressing the major challenges immunotherapies faced.

Comprehensive integration of structural and functional connectivity data is required to model brain functions accurately. While resources for studying the structural connectivity of non-human primate brains already exist, their integration with functional connectivity data has remained unavailable. Here we present a comprehensive resource that integrates the most extensive awake marmoset resting-state fMRI data available to date (39 marmoset monkeys, 710 runs, 12117 mins) with previously published cellular-level neuronal tracing data (52 marmoset monkeys, 143 injections) and multi-resolution diffusion MRI datasets. The combination of these data allowed us to (1) map the fine-detailed functional brain networks and cortical parcellations, (2) develop a deep-learning-based parcellation generator that preserves the topographical organization of functional connectivity and reflects individual variabilities, and (3) investigate the structural basis underlying functional connectivity by computational modeling. This resource will enable modeling structure-function relationships and facilitate future comparative and translational studies of primate brains.