Immunomodulatory effects and improved outcomes with cisplatin- versus carboplatin-based chemotherapy plus atezolizumab in urothelial cancer.

In metastatic urothelial cancer (mUC), cisplatin versus carboplatin leads to durable disease control in a subset of patients. The IMvigor130 trial reveals more favorable effects with atezolizumab combined with gemcitabine and cisplatin (GemCis) versus gemcitabine and carboplatin (GemCarbo). This study investigates the immunomodulatory effects of cisplatin as a potential explanation for these observations. Our findings indicate that improved outcomes with GemCis versus GemCarbo are primarily observed in patients with pretreatment tumors exhibiting features of restrained adaptive immunity. In addition, GemCis versus GemCarbo ± atezolizumab induces transcriptional changes in circulating immune cells, including upregulation of antigen presentation and T cell activation programs. In vitro experiments demonstrate that cisplatin, compared with carboplatin, exerts direct immunomodulatory effects on cancer cells, promoting dendritic cell activation and antigen-specific T cell killing. These results underscore the key role of immune modulation in cisplatin's efficacy in mUC and highlight the importance of specific chemotherapy backbones in immunotherapy combination regimens.

Effective methods for bulk RNA-seq deconvolution using scnRNA-seq transcriptomes.

BACKGROUND: RNA profiling technologies at single-cell resolutions, including single-cell and single-nuclei RNA sequencing (scRNA-seq and snRNA-seq, scnRNA-seq for short), can help characterize the composition of tissues and reveal cells that influence key functions in both healthy and disease tissues. However, the use of these technologies is operationally challenging because of high costs and stringent sample-collection requirements. Computational deconvolution methods that infer the composition of bulk-profiled samples using scnRNA-seq-characterized cell types can broaden scnRNA-seq applications, but their effectiveness remains controversial. RESULTS: We produced the first systematic evaluation of deconvolution methods on datasets with either known or scnRNA-seq-estimated compositions. Our analyses revealed biases that are common to scnRNA-seq 10X Genomics assays and illustrated the importance of accurate and properly controlled data preprocessing and method selection and optimization. Moreover, our results suggested that concurrent RNA-seq and scnRNA-seq profiles can help improve the accuracy of both scnRNA-seq preprocessing and the deconvolution methods that employ them. Indeed, our proposed method, Single-cell RNA Quantity Informed Deconvolution (SQUID), which combines RNA-seq transformation and dampened weighted least-squares deconvolution approaches, consistently outperformed other methods in predicting the composition of cell mixtures and tissue samples. CONCLUSIONS: We showed that analysis of concurrent RNA-seq and scnRNA-seq profiles with SQUID can produce accurate cell-type abundance estimates and that this accuracy improvement was necessary for identifying outcomes-predictive cancer cell subclones in pediatric acute myeloid leukemia and neuroblastoma datasets. These results suggest that deconvolution accuracy improvements are vital to enabling its applications in the life sciences.

Targeting Treg cells with GITR activation alleviates resistance to immunotherapy in murine glioblastomas.

Immune checkpoint blockers (ICBs) have failed in all phase III glioblastoma (GBM) trials. Here, we show that regulatory T (Treg) cells play a key role in GBM resistance to ICBs in experimental gliomas. Targeting glucocorticoid-induced TNFR-related receptor (GITR) in Treg cells using an agonistic antibody (αGITR) promotes CD4 Treg cell differentiation into CD4 effector T cells, alleviates Treg cell-mediated suppression of anti-tumor immune response, and induces potent anti-tumor effector cells in GBM. The reprogrammed GBM-infiltrating Treg cells express genes associated with a Th1 response signature, produce IFNγ, and acquire cytotoxic activity against GBM tumor cells while losing their suppressive function. αGITR and αPD1 antibodies increase survival benefit in three experimental GBM models, with a fraction of cohorts exhibiting complete tumor eradication and immune memory upon tumor re-challenge. Moreover, αGITR and αPD1 synergize with the standard of care treatment for newly-diagnosed GBM, enhancing the cure rates in these GBM models.

Multi-clonal SARS-CoV-2 neutralization by antibodies isolated from severe COVID-19 convalescent donors.

The interactions between antibodies, SARS-CoV-2 and immune cells contribute to the pathogenesis of COVID-19 and protective immunity. To understand the differences between antibody responses in mild versus severe cases of COVID-19, we analyzed the B cell responses in patients 1.5 months post SARS-CoV-2 infection. Severe, and not mild, infection correlated with high titers of IgG against Spike receptor binding domain (RBD) that were capable of ACE2:RBD inhibition. B cell receptor (BCR) sequencing revealed that VH3-53 was enriched during severe infection. Of the 22 antibodies cloned from two severe donors, six exhibited potent neutralization against authentic SARS-CoV-2, and inhibited syncytia formation. Using peptide libraries, competition ELISA and mutagenesis of RBD, we mapped the epitopes of the neutralizing antibodies (nAbs) to three different sites on the Spike. Finally, we used combinations of nAbs targeting different immune-sites to efficiently block SARS-CoV-2 infection. Analysis of 49 healthy BCR repertoires revealed that the nAbs germline VHJH precursors comprise up to 2.7% of all VHJHs. We demonstrate that severe COVID-19 is associated with unique BCR signatures and multi-clonal neutralizing responses that are relatively frequent in the population. Moreover, our data support the use of combination antibody therapy to prevent and treat COVID-19.

Gut CD4+ T cell phenotypes are a continuum molded by microbes, not by TH archetypes.

CD4+ effector lymphocytes (Teff) are traditionally classified by the cytokines they produce. To determine the states that Teff cells actually adopt in frontline tissues in vivo, we applied single-cell transcriptome and chromatin analyses to colonic Teff cells in germ-free or conventional mice or in mice after challenge with a range of phenotypically biasing microbes. Unexpected subsets were marked by the expression of the interferon (IFN) signature or myeloid-specific transcripts, but transcriptome or chromatin structure could not resolve discrete clusters fitting classic helper T cell (TH) subsets. At baseline or at different times of infection, transcripts encoding cytokines or proteins commonly used as TH markers were distributed in a polarized continuum, which was functionally validated. Clones derived from single progenitors gave rise to both IFN-γ- and interleukin (IL)-17-producing cells. Most of the transcriptional variance was tied to the infecting agent, independent of the cytokines produced, and chromatin variance primarily reflected activities of activator protein (AP)-1 and IFN-regulatory factor (IRF) transcription factor (TF) families, not the canonical subset master regulators T-bet, GATA3 or RORγ.

Multi-Clonal Live SARS-CoV-2 In Vitro Neutralization by Antibodies Isolated from Severe COVID-19 Convalescent Donors.

The interactions between antibodies, SARS-CoV-2 and immune cells contribute to the pathogenesis of COVID-19 and protective immunity. To understand the differences between antibody responses in mild versus severe cases of COVID-19, we analyzed the B cell responses in patients 1.5 months post SARS-CoV-2 infection. Severe and not mild infection correlated with high titers of IgG against Spike receptor binding domain (RBD) that were capable of viral inhibition. B cell receptor (BCR) sequencing revealed two VH genes, VH3-38 and VH3-53, that were enriched during severe infection. Of the 22 antibodies cloned from two severe donors, six exhibited potent neutralization against live SARS-CoV-2, and inhibited syncytia formation. Using peptide libraries, competition ELISA and RBD mutagenesis, we mapped the epitopes of the neutralizing antibodies (nAbs) to three different sites on the Spike. Finally, we used combinations of nAbs targeting different immune-sites to efficiently block SARS-CoV-2 infection. Analysis of 49 healthy BCR repertoires revealed that the nAbs germline VHJH precursors comprise up to 2.7% of all VHJHs. We demonstrate that severe COVID-19 is associated with unique BCR signatures and multi-clonal neutralizing responses that are relatively frequent in the population. Moreover, our data support the use of combination antibody therapy to prevent and treat COVID-19.

CD4+ teff cell heterogeneity: the perspective from single-cell transcriptomics.

Single-cell transcriptomics (scRNAseq) holds the promise to generate definitive atlases of cell types. We review scRNAseq studies of conventional CD4+ αß T cells performed in a variety of challenged contexts (infection, tumor, allergy) that aimed to parse the complexity and representativity of previously defined CD4+ T cell types, lineages, and cosmologies. With a few years' experience, the field has realized the difficulties and pitfalls of scRNAseq. With the very high-dimensionality of scRNAseq data, subset definitions based on low-dimensionality marker combinations tend to fade or blur: cell types prove more complex than expected; transcripts of key defining transcripts (cytokines, chemokines) are distributed as broad and partially overlapping continua; boundaries with innate lymphocytes are blurred. Tissue location and activation, either cytokine-driven or TCR-driven, determine Teff heterogeneity in sometimes unexpected ways. Emerging techniques for lineage and trajectory tracing, and RNA-protein connections, will further help define the space of differentiated CD4+ T cell heterogeneity.

Identification and validation of a tumor-infiltrating Treg transcriptional signature conserved across species and tumor types.

FoxP3+ T regulatory (Treg) cells are central elements of immunologic tolerance. They are abundant in many tumors, where they restrict potentially favorable antitumor responses. We used a three-pronged strategy to identify genes related to the presence and function of Tregs in the tumor microenvironment. Gene expression profiles were generated from tumor-infiltrating Tregs (TITRs) of both human and mouse tumors and were compared with those of Tregs of lymphoid organs or normal tissues from the same individuals. A computational deconvolution of whole-tumor datasets from the Cancer Genome Atlas (TCGA) was performed to identify transcripts specifically associated with Tregs across thousands of tumors from different stages and locations. We identified a set of TITR-differential transcripts with striking reproducibility between tumor types in mice, between mice and humans, and between different human patients spanning tumor stages. Many of the TITR-preferential transcripts were shared with "tissue Tregs" residing in nonlymphoid tissues, but a tumor-preferential segment could be identified. Many of these TITR signature transcripts were confirmed by mining of TCGA datasets, which also brought forth transcript modules likely representing the parenchymal attraction of, or response to, tumor Tregs. Importantly, the TITR signature included several genes encoding effective targets of tumor immunotherapy. A number of other targets were validated by CRISPR-based gene inactivation in mouse Tregs. These results confirm the validity of the signature, generating a wealth of leads for understanding the role of Tregs in tumor progression and identifying potential targets for cancer immunotherapy.

Publisher Correction: Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

In the version of this article initially published, the Supplementary Note was missing. The Supplementary Note has now been provided online and is cited in the Methods section of the article. The error has been corrected in the HTML and PDF version of the article.

Single-cell gene expression reveals a landscape of regulatory T cell phenotypes shaped by the TCR.

CD4+ T regulatory cells (Treg) are central to immune homeostasis, their phenotypic heterogeneity reflecting the diverse environments and target cells that they regulate. To understand this heterogeneity, we combined single-cell RNA-seq, activation reporter and T cell receptor (TCR) analysis to profile thousands of Treg or conventional CD4+FoxP3- T cells (Tconv) from mouse lymphoid organs and human blood. Treg and Tconv pools showed areas of overlap, as resting 'furtive' Tregs with overall similarity to Tconvs or as a convergence of activated states. All Tregs expressed a small core of FoxP3-dependent transcripts, onto which additional programs were added less uniformly. Among suppressive functions, Il2ra and Ctla4 were quasiconstant, inhibitory cytokines being more sparsely distributed. TCR signal intensity did not affect resting/activated Treg proportions but molded activated Treg programs. The main lines of Treg heterogeneity in mice were strikingly conserved in human blood. These results reveal unexpected TCR-shaped states of activation, providing a framework to synthesize previous observations of Treg heterogeneity.

The PARP1 inhibitor BMN 673 exhibits immunoregulatory effects in a Brca1(-/-) murine model of ovarian cancer.

Familial breast and ovarian cancer are often caused by inherited mutations of BRCA1. While current prognoses for such patients are rather poor, inhibition of poly-ADP ribose polymerase 1 (PARP1) induces synthetic lethality in cells that are defective in homologous recombination. BMN 673 is a potent PARP1 inhibitor that is being clinically evaluated for treatment of BRCA-mutant cancers. Using the Brca1-deficient murine epithelial ovarian cancer cell line BR5FVB1-Akt, we investigated whether the antitumor effects of BMN 673 extend beyond its known pro-apoptotic function. Administration of modest amounts of BMN 673 greatly improved the survival of mice bearing subcutaneous or intraperitoneal tumors. We thus hypothesized that BMN 673 may influence the composition and function of immune cells in the tumor microenvironment. Indeed, BMN 673 significantly increases the number of peritoneal CD8(+) T cells and NK cells as well as their production of IFN-γ and TNF-α. These data suggest that the cell stress caused by BMN 673 induces not only cancer cell-intrinsic apoptosis but also cancer cell-extrinsic antitumor immune effects in a syngeneic murine model of ovarian cancer. BMN 673 may therefore serve as a promising adjuvant therapy to immunotherapy to achieve durable responses among patients whose tumors harbor defects in homologous recombination.

Efficient and specific gene knockdown by small interfering RNAs produced in bacteria.

Synthetic small interfering RNAs (siRNAs) are an indispensable tool to investigate gene function in eukaryotic cells and may be used for therapeutic purposes to knock down genes implicated in disease. Thus far, most synthetic siRNAs have been produced by chemical synthesis. Here we present a method to produce highly potent siRNAs in Escherichia coli. This method relies on ectopic expression of p19, an siRNA-binding protein found in a plant RNA virus. When expressed in E. coli, p19 stabilizes an ∼21-nt siRNA-like species produced by bacterial RNase III. When mammalian cells are transfected by them, siRNAs that were generated in bacteria expressing p19 and a hairpin RNA encoding 200 or more nucleotides of a target gene reproducibly knock down target gene expression by ∼90% without immunogenicity or off-target effects. Because bacterially produced siRNAs contain multiple sequences against a target gene, they may be especially useful for suppressing polymorphic cellular or viral genes.

GenomeRNAi: a database for cell-based RNAi phenotypes. 2009 update.

The GenomeRNAi database (http://www.genomernai.org/) contains phenotypes from published cell-based RNA interference (RNAi) screens in Drosophila and Homo sapiens. The database connects observed phenotypes with annotations of targeted genes and information about the RNAi reagent used for the perturbation experiment. The availability of phenotypes from Drosophila and human screens also allows for phenotype searches across species. Besides reporting quantitative data from genome-scale screens, the new release of GenomeRNAi also enables reporting of data from microscopy experiments and curated phenotypes from published screens. In addition, the database provides an updated resource of RNAi reagents and their predicted quality that are available for the Drosophila and the human genome. The new version also facilitates the integration with other genomic data sets and contains expression profiling (RNA-Seq) data for several cell lines commonly used in RNAi experiments.