Genome-wide CRISPR screens identify the YAP/TEAD axis as a driver of persister cells in EGFR mutant lung cancer

Most lung cancer patients with metastatic cancer eventually relapse with drug-resistant disease following treatment and EGFR mutant lung cancer is no exception. Genome-wide CRISPR screens, to either knock out or overexpress all protein-coding genes in cancer cell lines, revealed the landscape of pathways that cause resistance to the EGFR inhibitors osimertinib or gefitinib in EGFR mutant lung cancer. Among the most recurrent resistance genes were those that regulate the Hippo pathway. Following osimertinib treatment a subpopulation of cancer cells are able to survive and over time develop stable resistance. These 'persister' cells can exploit non-genetic (transcriptional) programs that enable cancer cells to survive drug treatment. Using genetic and pharmacologic tools we identified Hippo signalling as an important non-genetic mechanism of cell survival following osimertinib treatment. Further, we show that combinatorial targeting of the Hippo pathway and EGFR is highly effective in EGFR mutant lung cancer cells and patient-derived organoids, suggesting a new therapeutic strategy for EGFR mutant lung cancer patients.

The Next-Generation Oral Selective Estrogen Receptor Degrader Camizestrant (AZD9833) Suppresses ER+ Breast Cancer Growth and Overcomes Endocrine and CDK4/6 Inhibitor Resistance

Oral selective estrogen receptor degraders (SERD) could become the backbone of endocrine therapy (ET) for estrogen receptor-positive (ER+) breast cancer, as they achieve greater inhibition of ER-driven cancers than current ETs and overcome key resistance mechanisms. In this study, we evaluated the preclinical pharmacology and efficacy of the next-generation oral SERD camizestrant (AZD9833) and assessed ER-co-targeting strategies by combining camizestrant with CDK4/6 inhibitors (CDK4/6i) and PI3K/AKT/mTOR-targeted therapy in models of progression on CDK4/6i and/or ET. Camizestrant demonstrated robust and selective ER degradation, modulated ER-regulated gene expression, and induced complete ER antagonism and significant antiproliferation activity in ESR1 wild-type (ESR1wt) and mutant (ESR1m) breast cancer cell lines and patient-derived xenograft (PDX) models. Camizestrant also delivered strong antitumor activity in fulvestrant-resistant ESR1wt and ESR1m PDX models. Evaluation of camizestrant in combination with CDK4/6i (palbociclib or abemaciclib) in CDK4/6-naive and -resistant models, as well as in combination with PI3Kαi (alpelisib), mTORi (everolimus), or AKTi (capivasertib), indicated that camizestrant was active with CDK4/6i or PI3K/AKT/mTORi and that antitumor activity was further increased by the triple combination. The response was observed independently of PI3K pathway mutation status. Overall, camizestrant shows strong and broad antitumor activity in ER+ breast cancer as a monotherapy and when combined with CDK4/6i and PI3K/AKT/mTORi.

SIGNIFICANCE

Camizestrant, a next-generation oral SERD, shows promise in preclinical models of ER+ breast cancer alone and in combination with CDK4/6 and PI3K/AKT/mTOR inhibitors to address endocrine resistance, a current barrier to treatment.

The landscape of therapeutic vulnerabilities in EGFR inhibitor osimertinib drug tolerant persister cells

Third-generation EGFR tyrosine kinase inhibitors (EGFR-TKIs), including osimertinib, an irreversible EGFR-TKI, are important treatments for non-small cell lung cancer with EGFR-TKI sensitizing or EGFR T790M resistance mutations. While patients treated with osimertinib show clinical benefit, disease progression and drug resistance are common. Emergence of de novo acquired resistance from a drug tolerant persister (DTP) cell population is one mechanism proposed to explain progression on osimertinib and other targeted cancer therapies. Here we profiled osimertinib DTPs using RNA-seq and ATAC-seq to characterize the features of these cells and performed drug screens to identify therapeutic vulnerabilities. We identified several vulnerabilities in osimertinib DTPs that were common across models, including sensitivity to MEK, AURKB, BRD4, and TEAD inhibition. We linked several of these vulnerabilities to gene regulatory changes, for example, TEAD vulnerability was consistent with evidence of Hippo pathway turning off in osimertinib DTPs. Last, we used genetic approaches using siRNA knockdown or CRISPR knockout to validate AURKB, BRD4, and TEAD as the direct targets responsible for the vulnerabilities observed in the drug screen.

Resistance to durvalumab and durvalumab plus tremelimumab is associated with functional STK11 mutations in non-small-cell lung cancer patients and is reversed by STAT3 knockdown

Mutations in the STK11 (LKB1) gene regulate resistance to PD-1/PD-L1 blockade. This study evaluated this association in patients with nonsquamous non-small-cell lung cancer enrolled in three Phase 1/2 trials. STK11 mutations were associated with resistance to the anti-PD-L1 antibody durvalumab (alone/with the anti-CTLA-4 antibody tremelimumab) independently of KRAS mutational status, highlighting STK11 as a potential driver of resistance to checkpoint blockade. Retrospective assessments of tumor tissue, whole blood and serum revealed a unique immune phenotype in patients with STK11 mutations, with increased expression of markers associated with neutrophils (i.e. CXCL2, IL6), Th17 contexture (i.e. IL17A) and immune checkpoints. Associated changes were observed in the periphery. Reduction of STAT3 in the tumor microenvironment using an antisense oligonucleotide reversed immunotherapy resistance in preclinical STK11 knockout models. These results suggest that STK11 mutations may hinder response to checkpoint blockade through mechanisms including suppressive myeloid cell biology, which could be reversed by STAT3-targeted therapy.

Developmental bifurcation of human T follicular regulatory cells

Germinal centers (GCs) are anatomic structures where B cells undergo affinity maturation, leading to production of high-affinity antibodies. The balance between T follicular helper (T_FH) and regulatory (T_FR) cells is critical for adequate control of GC responses. The study of human T_FH and T_FR cell development has been hampered because of the lack of in vitro assays reproducing in vivo biology, along with difficult access to healthy human lymphoid tissues. We used a single-cell transcriptomics approach to study the maturation of T_FH and T_FR cells isolated from human blood, iliac lymph nodes (LNs), and tonsils. As independent tissues have distinct proportions of follicular T cells in different maturation states, we leveraged the heterogeneity to reconstruct the maturation trajectory for human T_FH and T_FR cells. We found that the dominant maturation of T_FR cells follows a bifurcated trajectory from precursor T_reg cells, with one arm of the bifurcation leading to blood T_FR cells and the other leading to the most mature GC T_FR cells. Overall, our data provide a comprehensive resource for the transcriptomics of different follicular T cell populations and their dynamic relationship across different tissues.

Single-Cell Transcriptomics of Regulatory T Cells Reveals Trajectories of Tissue Adaptation

Non-lymphoid tissues (NLTs) harbor a pool of adaptive immune cells with largely unexplored phenotype and development. We used single-cell RNA-seq to characterize 35,000 CD4+ regulatory (Treg) and memory (Tmem) T cells in mouse skin and colon, their respective draining lymph nodes (LNs) and spleen. In these tissues, we identified Treg cell subpopulations with distinct degrees of NLT phenotype. Subpopulation pseudotime ordering and gene kinetics were consistent in recruitment to skin and colon, yet the initial NLT-priming in LNs and the final stages of NLT functional adaptation reflected tissue-specific differences. Predicted kinetics were recapitulated using an in vivo melanoma-induction model, validating key regulators and receptors. Finally, we profiled human blood and NLT Treg and Tmem cells, and identified cross-mammalian conserved tissue signatures. In summary, we describe the relationship between Treg cell heterogeneity and recruitment to NLTs through the combined use of computational prediction and in vivo validation.

Tissue Handling and Dissociation for Single-Cell RNA-Seq

The starting material for all single-cell protocols is a cell suspension. The particular functions and spatial distribution of immune cells generally make them easy to isolate them from the tissues where they dwell. Here we describe tissue dissociation protocols that have been used to obtain human immune cells from lymphoid and nonlymphoid tissues to be then used as input to single-cell methods. We highlight the main factors that can influence the final quality of single-cell data, namely the stress signatures that can bias its interpretation.

A rapid and robust method for single cell chromatin accessibility profiling

The assay for transposase-accessible chromatin using sequencing (ATAC-seq) is widely used to identify regulatory regions throughout the genome. However, very few studies have been performed at the single cell level (scATAC-seq) due to technical challenges. Here we developed a simple and robust plate-based scATAC-seq method, combining upfront bulk Tn5 tagging with single-nuclei sorting. We demonstrate that our method works robustly across various systems, including fresh and cryopreserved cells from primary tissues. By profiling over 3000 splenocytes, we identify distinct immune cell types and reveal cell type-specific regulatory regions and related transcription factors.

Single-cell RNA-sequencing resolves self-antigen expression during mTEC development

The crucial capability of T cells for discrimination between self and non-self peptides is based on negative selection of developing thymocytes by medullary thymic epithelial cells (mTECs). The mTECs purge autoreactive T cells by expression of cell-type specific genes referred to as tissue-restricted antigens (TRAs). Although the autoimmune regulator (AIRE) protein is known to promote the expression of a subset of TRAs, its mechanism of action is still not fully understood. The expression of TRAs that are not under the control of AIRE also needs further characterization. Furthermore, expression patterns of TRA genes have been suggested to change over the course of mTEC development. Herein we have used single-cell RNA-sequencing to resolve patterns of TRA expression during mTEC development. Our data indicated that mTEC development consists of three distinct stages, correlating with previously described jTEC, mTEChi and mTEClo phenotypes. For each subpopulation, we have identified marker genes useful in future studies. Aire-induced TRAs were switched on during jTEC-mTEC transition and were expressed in genomic clusters, while otherwise the subsets expressed largely overlapping sets of TRAs. Moreover, population-level analysis of TRA expression frequencies suggested that such differences might not be necessary to achieve efficient thymocyte selection.

Power analysis of single-cell RNA-sequencing experiments

Single-cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, thereby revealing new cell types and providing insights into developmental processes and transcriptional stochasticity. A key question is how the variety of available protocols compare in terms of their ability to detect and accurately quantify gene expression. Here, we assessed the protocol sensitivity and accuracy of many published data sets, on the basis of spike-in standards and uniform data processing. For our workflow, we developed a flexible tool for counting the number of unique molecular identifiers (https://github.com/vals/umis/). We compared 15 protocols computationally and 4 protocols experimentally for batch-matched cell populations, in addition to investigating the effects of spike-in molecular degradation. Our analysis provides an integrated framework for comparing scRNA-seq protocols.