Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential—the number of expressed genes per cell—and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied to diverse tissue types and organisms, CytoTRACE outperformed previous methods and nearly 19,000 annotated gene sets for resolving 52 experimentally determined developmental trajectories. Additionally, it facilitated the identification of quiescent stem cells and revealed genes that contribute to breast tumorigenesis. This study thus establishes a key RNA-based feature of developmental potential and a platform for delineation of cellular hierarchies.

Single-cell RNA-sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation without prior knowledge has remained challenging. Here we describe a simple yet robust determinant of developmental potential-the number of detectably expressed genes per celland leverage this measure of transcriptional diversity to develop a new framework for predicting ordered differentiation states from scRNA-seq data. When evaluated on ~150,000 single-cell transcriptomes spanning 53 lineages and five species, our approach, called CytoTRACE, outperformed previous methods and ~19,000 molecular signatures for resolving experimentallyconfirmed developmental trajectories. In addition, it enabled unbiased identification of tissueresident stem cells, including cells with long-term regenerative potential. When used to analyze human breast tumors, we discovered candidate genes associated with less-differentiated luminal progenitor cells and validated GULP1 as a novel gene involved in tumorigenesis. Our study establishes a key RNA-based correlate of developmental potential and provides a new platform for robust delineation of cellular hierarchies (https://cytotrace.stanford.edu).

9503 Background: The immunomodulatory receptor TIGIT is a novel inhibitory immune checkpoint present on activated T cells and NK cells in multiple cancers, including NSCLC. In a phase I study (GO30103), co-inhibition of TIGIT and PD-L1 signaling with tira plus atezo in CIT-naïve PD-L1 positive NSCLC potentially improved overall response rates (ORR) compared to historical ORR with PD-L1/PD-1 inhibitors. We conducted this phase II trial to confirm the efficacy and safety of tira plus atezo (TA) compared to placebo plus atezo (PA) in 1L NSCLC (GO40290, NCT NCT03563716). Methods: This prospective, randomized, double-blind, placebo-controlled trial enrolled patients (pts) with chemotherapy-naïve PD-L1+ (TPS ≥ 1% by 22C3 IHC pharmDx Dako assay) locally advanced or metastatic NSCLC with measurable disease, ECOG PS 0-1, and without EGFR or ALK alterations. Pts were randomized 1:1 to TA (tira 600 mg IV plus atezo 1200 mg IV) or PA (placebo plus atezo 1200 mg IV) on day 1 of every 3-week cycle. Stratification factors were PD-L1 status (TPS ≥ 50% vs TPS 1-49%), histology, and tobacco history. Co-primary endpoints were investigator assessed ORR and PFS, and additional endpoints were duration of response (DOR), OS, and safety. Exploratory endpoints were the effect of PD-L1 status on ORR and PFS. Results: 135 pts were randomized to PA (n = 68) or TA (n = 67). At primary analysis (30 Jun 2019), TA improved ORR and median PFS (mPFS) compared to PA, with median follow-up of 5.9 mo. In the safety population (68 in PA, 67 in TA), treatment-related AEs (TRAEs) occurred in 72% (PA) and 80.6% (TA); Grade ≥3 TRAEs occurred in 19.1% (PA) and 14.9% (TA). AEs leading to treatment withdrawal occurred in 10.3% (PA) and 7.5% (TA). Clinical trial information: NCT03563716 . With an additional six months of follow-up since the primary analysis (2 Dec 2019, median follow-up of 10.9 mo), improvement in ORR and mPFS was maintained in ITT for TA (37.3% [25.0, 49.6] and 5.6 mo [4.2, 10.4]) vs PA (20.6% [10.2, 30.9] and 3.9 mo [2.7, 4.5]). The safety profile remained tolerable. Conclusions: Treatment with TA compared to PA showed clinically meaningful improvement in ORR and PFS in ITT. The safety profile of TA was similar to PA. [Table: see text]