Although the first nanomedicine was clinically approved more than two decades ago, nanoparticles’ (NP) in vivo behavior is complex and the immune system’s role in their application remains elusive. At present, only passive-targeting nanoformulations have been clinically approved, while more complicated active-targeting strategies typically fail to advance from the early clinical phase stage. This absence of clinical translation is, among others, due to the very limited understanding for in vivo targeting mechanisms. Dynamic in vivo phenomena such as NPs’ real-time targeting kinetics and phagocytes’ contribution to active NP targeting remain largely unexplored. To better understand in vivo targeting, monitoring NP accumulation and distribution at complementary levels of spatial and temporal resolution is imperative. Here, we integrate in vivo positron emission tomography/computed tomography imaging with intravital microscopy and flow cytometric analyses to study α v β 3 -integrin-targeted cyclic arginine-glycine-aspartate decorated liposomes and oil-in-water nanoemulsions in tumor mouse models. We observed that ligand-mediated accumulation in cancerous lesions is multifaceted and identified “NP hitchhiking” with phagocytes to contribute considerably to this intricate process. We anticipate that this understanding can facilitate rational improvement of nanomedicine applications and that immune cell–NP interactions can be harnessed to develop clinically viable nanomedicine-based immunotherapies.
Background: In breast cancer, activation of bone morphogenetic protein (BMP) signaling and elevated levels of BMP-antagonists have been linked to tumor progression and metastasis. However, the simultaneous upregulation of BMPs and their antagonist, and the fact that both promote tumor aggressiveness seems contradictory and is not fully understood. Methods: We analyzed the transcriptomes of the metastatic 66cl4 and the non-metastatic 67NR cell lines of the 4T1 mouse mammary tumor model to search for factors that promote metastasis. CRISPR/Cas9 gene editing was used for mechanistic studies in the same cell lines. Furthermore, we analyzed gene expression patterns in human breast cancer biopsies obtained from public datasets to evaluate co-expression and possible relations to clinical outcome. Results: We found that mRNA levels of the BMP-antagonist Grem1, encoding gremlin1, and the ligand Bmp4 were both significantly upregulated in cells and primary tumors of 66cl4 compared to 67NR. Depletion of gremlin1 in 66cl4 could impair metastasis to the lungs in this model. Furthermore, we found that expression of Grem1 correlated with upregulation of several stem cell markers in 66cl4 cells compared to 67NR cells. Both in the mouse model and in patients, expression of GREM1 associated with extracellular matrix organization, and formation, biosynthesis and modification of collagen. Importantly, high expression of GREM1 predicted poor prognosis in estrogen receptor negative breast cancer patients. Analyses of large patient cohorts revealed that amplification of genes encoding BMP-antagonists and elevation of the corresponding transcripts is evident in biopsies from more than half of the patients and much more frequent for the secreted BMP-antagonists than the intracellular inhibitors of SMAD signaling. Conclusion: In conclusion, our results show that GREM1 is associated with metastasis and predicts poor prognosis in ER-negative breast cancer patients. Gremlin1 could represent a novel target for therapy.
The purpose of this study was to develop a massive parallel sequencing (MPS) workflow for diagnostic analysis of mismatch repair (MMR) genes using the GS Junior system (Roche). A pathogenic variant in one of four MMR genes, (MLH1, PMS2, MSH6, and MSH2), is the cause of Lynch Syndrome (LS), which mainly predispose to colorectal cancer. We used an amplicon-based sequencing method allowing specific and preferential amplification of the MMR genes including PMS2, of which several pseudogenes exist. The amplicons were pooled at different ratios to obtain coverage uniformity and maximize the throughput of a single-GS Junior run. In total, 60 previously identified and distinct variants (substitutions and indels), were sequenced by MPS and successfully detected. The heterozygote detection range was from 19% to 63% and dependent on sequence context and coverage. We were able to distinguish between false-positive and true-positive calls in homopolymeric regions by cross-sample comparison and evaluation of flow signal distributions. In addition, we filtered variants according to a predefined status, which facilitated variant annotation. Our study shows that implementation of MPS in routine diagnostics of LS can accelerate sample throughput and reduce costs without compromising sensitivity, compared to Sanger sequencing.
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