Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia (ET)-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.

Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and has very few mutations that are shared between different patients. To better understand the intratumoral genetics underlying mutations of ccRCC, we carried out single-cell exome sequencing on a ccRCC tumor and its adjacent kidney tissue. Our data indicate that this tumor was unlikely to have resulted from mutations in VHL and PBRM1. Quantitative population genetic analysis indicates that the tumor did not contain any significant clonal subpopulations and also showed that mutations that had different allele frequencies within the population also had different mutation spectrums. Analyses of these data allowed us to delineate a detailed intratumoral genetic landscape at a single-cell level. Our pilot study demonstrates that ccRCC may be more genetically complex than previously thought and provides information that can lead to new ways to investigate individual tumors, with the aim of developing more effective cellular targeted therapies.

With the unprecedented progresses of biomedical nanotechnology during the past few decades, conventional drug delivery systems (DDSs) have been involved into smart DDSs with stimuli-responsive characteristics. Benefiting from the response to specific internal or external triggers, those well-defined nanoplatforms can increase the drug targeting efficacy, in the meantime, reduce side effects/toxicities of payloads, which are key factors for improving patient compliance. In academic field, variety of smart DDSs have been abundantly demonstrated for various intriguing systems, such as stimuli-responsive polymeric nanoparticles, liposomes, metals/metal oxides, and exosomes. However, these nanoplatforms are lack of standardized manufacturing method, toxicity assessment experience, and clear relevance between the pre-clinical and clinical studies, resulting in the huge difficulties to obtain regulatory and ethics approval. Therefore, such relatively complex stimulus-sensitive nano-DDSs are not currently approved for clinical use. In this review, we highlight the recent advances of smart nanoplatforms for targeting drug delivery. Furthermore, the clinical translation obstacles faced by these smart nanoplatforms have been reviewed and discussed. We also present the future directions and perspectives of stimuli-sensitive DDS in clinical applications.

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