Besca, a single-cell transcriptomics analysis toolkit to accelerate translational research

Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+T cells in the tumor microenvironment and predicts clinical outcome in early-phase and late-phase clinical trials

BACKGROUND

The immune status of a patient's tumor microenvironment (TME) may guide therapeutic interventions with cancer immunotherapy and help identify potential resistance mechanisms. Currently, patients' immune status is mostly classified based on CD8+tumor-infiltrating lymphocytes. An unmet need exists for comparable and reliable precision immunophenotyping tools that would facilitate clinical treatment-relevant decision-making and the understanding of how to overcome resistance mechanisms.

METHODS

We systematically analyzed the CD8 immunophenotype of 2023 patients from 14 phase I-III clinical trials using immunohistochemistry (IHC) and additionally profiled gene expression by RNA-sequencing (RNA-seq). CD8 immunophenotypes were classified by pathologists into CD8-desert, CD8-excluded or CD8-inflamed tumors using CD8 IHC staining in epithelial and stromal areas of the tumor. Using regularized logistic regression, we developed an RNA-seq-based classifier as a surrogate to the IHC-based spatial classification of CD8+tumor-infiltrating lymphocytes in the TME.

RESULTS

The CD8 immunophenotype and associated gene expression patterns varied across indications as well as across primary and metastatic lesions. Melanoma and kidney cancers were among the strongest inflamed indications, while CD8-desert phenotypes were most abundant in liver metastases across all tumor types. A good correspondence between the transcriptome and the IHC-based evaluation enabled us to develop a 92-gene classifier that accurately predicted the IHC-based CD8 immunophenotype in primary and metastatic samples (area under the curve inflamed=0.846; excluded=0.712; desert=0.855). The newly developed classifier was prognostic in The Cancer Genome Atlas (TCGA) data and predictive in lung cancer: patients with predicted CD8-inflamed tumors showed prolonged overall survival (OS) versus patients with CD8-desert tumors (HR 0.88; 95% CI 0.80 to 0.97) across TCGA, and longer OS on immune checkpoint inhibitor administration (phase III OAK study) in non-small-cell lung cancer (HR 0.75; 95% CI 0.58 to 0.97).

CONCLUSIONS

We provide a new precision immunophenotyping tool based on gene expression that reflects the spatial infiltration patterns of CD8+ lymphocytes in tumors. The classifier enables multiplex analyses and is easy to apply for retrospective, reverse translation approaches as well as for prospective patient enrichment to optimize the response to cancer immunotherapy.

Single-cell RNA-sequencing of virus-specific cellular immune responses in chronic hepatitis B patients

Chronic hepatitis B (CHB) is a major global health challenge. CHB can be controlled by antivirals but a therapeutic cure is lacking. CHB is characterized by limited HBV-specific T cell reactivity and functionality and expression of inhibitory receptors. The mechanisms driving these T cell phenotypes are only partially understood. Here, we created a single-cell RNA-sequencing dataset of HBV immune responses in patients to contribute to a better understanding of the dysregulated immunity. Blood samples of a well-defined cohort of 21 CHB and 10 healthy controls, including a subset of 5 matched liver biopsies, were collected. scRNA-seq data of total immune cells (55,825) plus sorted HBV-specific (1,963), non-naive (32,773) and PD1+ T cells (96,631) was generated using the 10X Genomics platform (186,123 cells) or the full-length Smart-seq2 protocol (1,069 cells). The shared transcript count matrices of single-cells serve as a valuable resource describing transcriptional changes underlying dysfunctional HBV-related T cell responses in blood and liver tissue and offers the opportunity to identify targets or biomarkers for HBV-related immune exhaustion.

Myeloid-T cell interplay and cell state transitions associated with checkpoint inhibitor response in melanoma

BACKGROUND

The treatment of melanoma, the deadliest form of skin cancer, has greatly benefited from immunotherapy. However, many patients do not show a durable response, which is only partially explained by known resistance mechanisms.

METHODS

We performed single-cell RNA sequencing of tumor immune infiltrates and matched peripheral blood mononuclear cells of 22 checkpoint inhibitor (CPI)-naive stage III-IV metastatic melanoma patients. After sample collection, the same patients received CPI treatment, and their response was assessed.

FINDINGS

CPI responders showed high levels of classical monocytes in peripheral blood, which preferentially transitioned toward CXCL9-expressing macrophages in tumors. Trajectories of tumor-infiltrating CD8+ T cells diverged at the level of effector memory/stem-like T cells, with non-responder cells progressing into a state characterized by cellular stress and apoptosis-related gene expression. Consistently, predicted non-responder-enriched myeloid-T/natural killer cell interactions were primarily immunosuppressive, while responder-enriched interactions were supportive of T cell priming and effector function.

CONCLUSIONS

Our study illustrates that the tumor immune microenvironment prior to CPI treatment can be indicative of response. In perspective, modulating the myeloid and/or effector cell compartment by altering the described cell interactions and transitions could improve immunotherapy response.

FUNDING

This research was funded by Roche Pharma Research and Early Development.

Dissecting the Mechanisms Underlying the Cytokine Release Syndrome (CRS) Mediated by T-Cell Bispecific Antibodies

PURPOSE

Target-dependent TCB activity can result in the strong and systemic release of cytokines that may develop into cytokine release syndrome (CRS), highlighting the need to understand and prevent this complex clinical syndrome.

EXPERIMENTAL DESIGN

We explored the cellular and molecular players involved in TCB-mediated cytokine release by single-cell RNA-sequencing of whole blood treated with CD20-TCB together with bulk RNA-sequencing of endothelial cells exposed to TCB-induced cytokine release. We used the in vitro whole blood assay and an in vivo DLBCL model in immunocompetent humanized mice to assess the effects of dexamethasone, anti-TNFα, anti-IL6R, anti-IL1R, and inflammasome inhibition, on TCB-mediated cytokine release and antitumor activity.

RESULTS

Activated T cells release TNFα, IFNγ, IL2, IL8, and MIP-1β, which rapidly activate monocytes, neutrophils, DCs, and NKs along with surrounding T cells to amplify the cascade further, leading to TNFα, IL8, IL6, IL1β, MCP-1, MIP-1α, MIP-1β, and IP-10 release. Endothelial cells contribute to IL6 and IL1β release and at the same time release several chemokines (MCP-1, IP-10, MIP-1α, and MIP-1β). Dexamethasone and TNFα blockade efficiently reduced CD20-TCB-mediated cytokine release whereas IL6R blockade, inflammasome inhibition, and IL1R blockade induced a less pronounced effect. Dexamethasone, IL6R blockade, IL1R blockade, and the inflammasome inhibitor did not interfere with CD20-TCB activity, in contrast to TNFα blockade, which partially inhibited antitumor activity.

CONCLUSIONS

Our work sheds new light on the cellular and molecular players involved in cytokine release driven by TCBs and provides a rationale for the prevention of CRS in patients treated with TCBs. See related commentary by Luri-Rey et al., p. 4320.

A randomized, double-blind phase 1b study evaluating the safety, tolerability, pharmacokinetics and pharmacodynamics of the NLRP3 inhibitor selnoflast in patients with moderate to severe active ulcerative colitis

BACKGROUND

The NLRP3 inflammasome drives release of pro-inflammatory cytokines including interleukin (IL)-1β and IL-18 and is a potential target for ulcerative colitis (UC). Selnoflast (RO7486967) is an orally active, potent, selective and reversible small molecule NLRP3 inhibitor. We conducted a randomized, placebo-controlled Phase 1b study to assess the safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) of selnoflast.

METHODS

Nineteen adults with previous diagnosis of UC and current active moderate to severe disease were randomized 2:1 to selnoflast or placebo for 7 days. A dose of 450 mg QD (once daily) was selected to achieve 90% IL-1β inhibition in plasma and colon tissue. Consecutive blood, sigmoid colon biopsies and stool samples were analyzed for a variety of PD markers. Safety and PK were also evaluated.

RESULTS

Selnoflast was well-tolerated. Plasma concentrations increased rapidly after oral administration, reaching Tmax 1 h post-dose. Mean plasma concentrations stayed above the IL-1β IC90 level throughout the dosing interval (mean Ctrough on Day 1 and Day 5: 2.55 μg/mL and 2.66 μg/mL, respectively). At steady state, post-dose selnoflast concentrations in sigmoid colon (5-20 μg/g) were above the IC90 . Production of IL-1β was reduced in whole blood following ex vivo stimulation with lipopolysaccharide (LPS) (in the selnoflast arm). No changes were observed in plasma IL-18 levels. There were no meaningful differences in the expression of an IL-1-related gene signature in sigmoid colon tissue, and no differences in the expression of stool biomarkers.

CONCLUSIONS

Selnoflast was safe and well-tolerated. Selnoflast 450 mg QD achieved plasma and tissue exposure predicted to maintain IL-1β IC90 over the dosing interval. However, PD biomarker results showed no robust differences between treatment arms, suggesting no major therapeutic effects are to be expected in UC. The limitations of this study are its small sample size and indirect assessment of the effect on IL-1β in tissue.

TRIAL REGISTRATION

ISRCTN16847938.

Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses

Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.

Deciphering molecular and cellular ex vivo responses to bispecific antibodies PD1-TIM3 and PD1-LAG3 in human tumors

BACKGROUND

Next-generation cancer immunotherapies are designed to broaden the therapeutic repertoire by targeting new immune checkpoints including lymphocyte-activation gene 3 (LAG-3) and T cell immunoglobulin and mucin-domain containing-3 (TIM-3). Yet, the molecular and cellular mechanisms by which either receptor functions to mediate its inhibitory effects are still poorly understood. Similarly, little is known on the differential effects of dual, compared with single, checkpoint inhibition.

METHODS

We here performed in-depth characterization, including multicolor flow cytometry, single cell RNA sequencing and multiplex supernatant analysis, using tumor single cell suspensions from patients with cancer treated ex vivo with novel bispecific antibodies targeting programmed cell death protein 1 (PD-1) and TIM-3 (PD1-TIM3), PD-1 and LAG-3 (PD1-LAG3), or with anti-PD-1.

RESULTS

We identified patient samples which were responsive to PD1-TIM3, PD1-LAG3 or anti-PD-1 using an in vitro approach, validated by the analysis of 659 soluble proteins and enrichment for an anti-PD-1 responder signature. We found increased abundance of an activated (HLA-DR⁺CD25⁺GranzymeB⁺) CD8⁺ T cell subset and of proliferating CD8⁺ T cells, in response to bispecific antibody or anti-PD-1 treatment. Bispecific antibodies, but not anti-PD-1, significantly increased the abundance of a proliferating natural killer cell subset, which exhibited enrichment for a tissue-residency signature. Key phenotypic and transcriptional changes occurred in a PD-1⁺CXCL13⁺CD4⁺ T cell subset, in response to all treatments, including increased interleukin-17 secretion and signaling toward plasma cells. Interestingly, LAG-3 protein upregulation was detected as a unique pharmacodynamic effect mediated by PD1-LAG3, but not by PD1-TIM3 or anti-PD-1.

CONCLUSIONS

Our in vitro system reliably assessed responses to bispecific antibodies co-targeting PD-1 together with LAG-3 or TIM-3 using patients' tumor infiltrating immune cells and revealed transcriptional and phenotypic imprinting by bispecific antibody formats currently tested in early clinical trials.

Single Cell RNA Sequencing: A New Frontier in Pancreatic Ductal Adenocarcinoma

Simple Summary

Pancreatic cancer has a very low survival rate for several reasons. One of those is primarily due to the difficulty in diagnosing it at an early stage. For this reason, it is important to refine our understanding of this disease to guide the development of new diagnostic and therapeutic modalities to combat this fatal illness. Here we attempt to provide a review of current progress in utilizing single-cell RNA sequencing (scRNA-seq) techniques in the molecular profiling of pancreatic ductal adenocarcinoma.

Abstract

Pancreatic ductal adenocarcinoma is a malignancy with a high mortality rate. It exhibits significant heterogeneity in metabolic pathways which are associated with its progression. In this review, we discuss the role of single cell RNA sequencing in unraveling the metabolic and clinical features of these highly malignant tumors.

PD-1-cis IL-2R agonism yields better effectors from stem-like CD8+ T cells

Expansion and differentiation of antigen-experienced PD-1⁺TCF-1⁺ stem-like CD8⁺ T cells into effector cells is critical for the success of immunotherapies based on PD-1 blockade^1-4. Hashimoto et al. have shown that, in chronic infections, administration of the cytokine interleukin (IL)-2 triggers an alternative differentiation path of stem-like T cells towards a distinct population of 'better effector' CD8⁺ T cells similar to those generated in an acute infection⁵. IL-2 binding to the IL-2 receptor α-chain (CD25) was essential in triggering this alternative differentiation path and expanding better effectors with distinct transcriptional and epigenetic profiles. However, constitutive expression of CD25 on regulatory T cells and some endothelial cells also contributes to unwanted systemic effects from IL-2 therapy. Therefore, engineered IL-2 receptor β- and γ-chain (IL-2Rβγ)-biased agonists are currently being developed^6-10. Here we show that IL-2Rβγ-biased agonists are unable to preferentially expand better effector T cells in cancer models and describe PD1-IL2v, a new immunocytokine that overcomes the need for CD25 binding by docking in cis to PD-1. Cis binding of PD1-IL2v to PD-1 and IL-2Rβγ on the same cell recovers the ability to differentiate stem-like CD8⁺ T cells into better effectors in the absence of CD25 binding in both chronic infection and cancer models and provides superior efficacy. By contrast, PD-1- or PD-L1-blocking antibodies alone, or their combination with clinically relevant doses of non-PD-1-targeted IL2v, cannot expand this unique subset of better effector T cells and instead lead to the accumulation of terminally differentiated, exhausted T cells. These findings provide the basis for the development of a new generation of PD-1 cis-targeted IL-2R agonists with enhanced therapeutic potential for the treatment of cancer and chronic infections.