Multiomic single cell sequencing identifies stemlike nature of mixed phenotype acute leukemia.

Despite recent work linking mixed phenotype acute leukemia (MPAL) to certain genetic lesions, specific driver mutations remain undefined for a significant proportion of patients and no genetic subtype is predictive of clinical outcomes. Moreover, therapeutic strategy for MPAL remains unclear, and prognosis is overall poor. We performed multiomic single cell profiling of 14 newly diagnosed adult MPAL patients to characterize the inter- and intra-tumoral transcriptional, immunophenotypic, and genetic landscapes of MPAL. We show that neither genetic profile nor transcriptome reliably correlate with specific MPAL immunophenotypes. Despite this, we find that MPAL blasts express a shared stem cell-like transcriptional profile indicative of high differentiation potential. Patients with the highest differentiation potential demonstrate inferior survival in our dataset. A gene set score, MPAL95, derived from genes highly enriched in the most stem-like MPAL cells, is applicable to bulk RNA sequencing data and is predictive of survival in an independent patient cohort, suggesting a potential strategy for clinical risk stratification.

Microfluidics-free single-cell genomics with templated emulsification.

Current single-cell RNA-sequencing approaches have limitations that stem from the microfluidic devices or fluid handling steps required for sample processing. We develop a method that does not require specialized microfluidic devices, expertise or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. Particle-templated instant partition sequencing (PIP-seq) accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multiomics measurements and can accurately characterize cell types in human breast tissue compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq reveals the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible and scalable next-generation workflow that extends single-cell sequencing to new applications.

How and why do gastrointestinal peptides influence food intake?

Despite the ability of some gastrointestinal hormones to reliably reduce meal size when administered prior to a meal, it is not understood why the repeated administration or genetic knockout of these hormones appear largely ineffective in reducing food intake and body weight. Here, we review evidence that the ability of GI peptides such as cholecystokinin (CCK) to elicit satiation is a consequence of prior learning. Evidence includes first, that the ability of some of these signals to modify food intake depends upon past experience and is malleable with new experience. Additionally, the ability of CCK and other gut signals to reduce food intake may not be hard-wired; i.e., any so-called "satiation" signal that reduces food intake in a single-meal situation may not continue to do so over repeated trials. The individual will respond to the signal only so long as it provides reliable information about caloric content. If a particular signal becomes unreliable, the individual will rely on other signals to end meals. Thus, gut peptides/hormones have important metabolic effects such as mediating absorption, digestion, and many aspects of the distribution of ingested nutrients throughout the body; and, if they have been reliably associated with natural stimuli that mediate satiation, they also inform behavior.