Yingtian Xie

Abstract Immune checkpoint blockade (ICB) therapy revolutionized cancer treatment, but many patients with impaired MHC-I expression remain refractory. Here, we combined FACS-based genome-wide CRISPR screens with a data-mining approach to identify drugs that can upregulate MHC-I without inducing PD-L1. CRISPR screening identified TRAF3, a suppressor of the NFκB pathway, as a negative regulator of MHC-I but not PD-L1. The Traf3-knockout gene expression signature is associated with better survival in ICB-naïve patients with cancer and better ICB response. We then screened for drugs with similar transcriptional effects as this signature and identified Second Mitochondria-derived Activator of Caspase (SMAC) mimetics. We experimentally validated that the SMAC mimetic birinapant upregulates MHC-I, sensitizes cancer cells to T cell–dependent killing, and adds to ICB efficacy. Our findings provide preclinical rationale for treating tumors expressing low MHC-I expression with SMAC mimetics to enhance sensitivity to immunotherapy. The approach used in this study can be generalized to identify other drugs that enhance immunotherapy efficacy. Significance: MHC-I loss or downregulation in cancer cells is a major mechanism of resistance to T cell–based immunotherapies. Our study reveals that birinapant may be used for patients with low baseline MHC-I to enhance ICB response. This represents promising immunotherapy opportunities given the biosafety profile of birinapant from multiple clinical trials. This article is highlighted in the In This Issue feature, p. 1307

Elevated CO2 and temperature strongly affect crop production, but understanding of the crop response to combined CO2 and temperature increases under field conditions is still limited while data are scarce. We grew wheat (Triticum aestivum L.) and rice (Oryza sativa L.) under two levels of CO2 (ambient and enriched up to 500 μmol mol(-1) ) and two levels of canopy temperature (ambient and increased by 1.5-2.0 °C) in free-air CO2 enrichment (FACE) systems and carried out a detailed growth and yield component analysis during two growing seasons for both crops. An increase in CO2 resulted in higher grain yield, whereas an increase in temperature reduced grain yield, in both crops. An increase in CO2 was unable to compensate for the negative impact of an increase in temperature on biomass and yield of wheat and rice. Yields of wheat and rice were decreased by 10-12% and 17-35%, respectively, under the combination of elevated CO2 and temperature. The number of filled grains per unit area was the most important yield component accounting for the effects of elevated CO2 and temperature in wheat and rice. Our data showed complex treatment effects on the interplay between preheading duration, nitrogen uptake, tillering, leaf area index, and radiation-use efficiency, and thus on yield components and yield. Nitrogen uptake before heading was crucial in minimizing yield loss due to climate change in both crops. For rice, however, a breeding strategy to increase grain number per m(2) and % filled grains (or to reduce spikelet sterility) at high temperature is also required to prevent yield reduction under conditions of global change.

We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses of single-cell RNA-seq (scRNA-seq) and ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions for pre-processing, alignment, quality control, expression and chromatin accessibility quantification, clustering, differential analysis, and annotation. By modeling gene regulatory potential from chromatin accessibilities at the single-cell level, MAESTRO outperforms the existing methods for integrating the cell clusters between scRNA-seq and scATAC-seq. Furthermore, MAESTRO supports automatic cell-type annotation using predefined cell type marker genes and identifies driver regulators from differential scRNA-seq genes and scATAC-seq peaks.

Neuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyze cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single-cell analysis of human clinical samples exhibits a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall, our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy.