Comparative analysis of Bcl-2 family protein overexpression in CAR T cells alone and in combination with BH3 mimetics.

Approximately 50% of patients with hematologic malignancies relapse after chimeric antigen receptor (CAR) T cell treatment; mechanisms of failure include loss of CAR T persistence and tumor resistance to apoptosis. We hypothesized that both of these challenges could potentially be overcome by overexpressing one or more of the Bcl-2 family proteins in CAR T cells to reduce their susceptibility to apoptosis, both alone and in the presence of BH3 mimetics, which can be used to activate apoptotic machinery in malignant cells. We comprehensively investigated overexpression of different Bcl-2 family proteins in CAR T cells with different signaling domains as well as in different tumor types. We found that Bcl-xL and Bcl-2 overexpression in CAR T cells bearing a 4-1BB costimulatory domain resulted in increased expansion and antitumor activity, reduced exhaustion, and decreased apoptotic priming. In addition, CAR T cells expressing either Bcl-xL or a venetoclax-resistant Bcl-2 variant led to enhanced antitumor efficacy and survival in murine xenograft models of lymphoma and leukemia in the presence or absence of the BH3 mimetic venetoclax, a clinically approved BH3 mimetic. In this setting, Bcl-xL overexpression had stronger effects than overexpression of Bcl-2 or the Bcl-2(G101V) variant. These findings suggest that CAR T cells could be optimally engineered by overexpressing Bcl-xL to enhance their persistence while opening a therapeutic window for combination with BH3 mimetics to prime tumors for apoptosis.

Phase 1 study of CAR-37 T cells in patients with relapsed or refractory CD37+ lymphoid malignancies.

We report on the first-in-human clinical trial using chimeric antigen receptor (CAR) T-cells targeting CD37, an antigen highly expressed in B- and T-cell malignancies (clinicaltrials.gov NCT04136275). Five patients with relapsed or refractory CD37+ lymphoid malignancies were enrolled and infused with autologous CAR-37 T-cells. CAR-37 T-cells expanded in the peripheral blood of all patients and, at peak, comprised >94% of the total lymphocytes in 4/5 patients. Tumor responses were observed in 4/5 patients, with 3 complete responses, 1 mixed response, and 1 patient whose disease progressed rapidly and with relative loss of CD37 expression. Three patients experienced prolonged and severe pancytopenia, and in two of these patients, efforts to ablate CAR-37 T-cells (which were engineered to co-express truncated EGFR) with cetuximab, were unsuccessful. Hematopoiesis was restored in these two patients following allogeneic hematopoietic stem cell transplantation. No other severe, non-hematopoietic toxicities occurred. We investigated the mechanisms of profound pancytopenia and did not observe activation of CAR-37 T-cells in response to hematopoietic stem cells in vitro or hematotoxicity in humanized models. Patients with pancytopenia had sustained high levels of IL-18, with low levels of IL-18 binding protein in their peripheral blood. IL-18 levels were significantly higher in CAR-37-treated patients relative to both cytopenic and non-cytopenic cohorts of CAR-19-treated cohorts of patients. In conclusion, CAR-37 T-cells exhibited anti-tumor activity, with significant CAR expansion and cytokine production. CAR-37 T-cells may be an effective therapy in hematologic malignancies as a bridge to hematopoietic stem cell transplant.

Understanding Mechanisms of Response to CAR T-cell Therapy through Single-Cell Sequencing: Insights and Challenges.

SUMMARY: Single-cell RNA sequencing has emerged as a powerful technique to understand the molecular features of chimeric antigen receptor (CAR) T cells that associate with clinical outcomes. Here we discuss the common themes that have emerged from across single-cell studies of CAR T-cell therapy, and summarize the challenges in interpreting this complex data type.

Latent human herpesvirus 6 is reactivated in CAR T cells.

Cell therapies have yielded durable clinical benefits for patients with cancer, but the risks associated with the development of therapies from manipulated human cells are understudied. For example, we lack a comprehensive understanding of the mechanisms of toxicities observed in patients receiving T cell therapies, including recent reports of encephalitis caused by reactivation of human herpesvirus 6 (HHV-6)1. Here, through petabase-scale viral genomics mining, we examine the landscape of human latent viral reactivation and demonstrate that HHV-6B can become reactivated in cultures of human CD4+ T cells. Using single-cell sequencing, we identify a rare population of HHV-6 'super-expressors' (about 1 in 300-10,000 cells) that possess high viral transcriptional activity, among research-grade allogeneic chimeric antigen receptor (CAR) T cells. By analysing single-cell sequencing data from patients receiving cell therapy products that are approved by the US Food and Drug Administration2 or are in clinical studies3-5, we identify the presence of HHV-6-super-expressor CAR T cells in patients in vivo. Together, the findings of our study demonstrate the utility of comprehensive genomics analyses in implicating cell therapy products as a potential source contributing to the lytic HHV-6 infection that has been reported in clinical trials1,6-8 and may influence the design and production of autologous and allogeneic cell therapies.

Pan-cancer analysis of post-translational modifications reveals shared patterns of protein regulation.

Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.

Systematic characterization of therapeutic vulnerabilities in Multiple Myeloma with Amp1q reveals increased sensitivity to the combination of MCL1 and PI3K inhibitors.

The development of targeted therapy for patients with Multiple Myeloma (MM) is hampered by the low frequency of actionable genetic abnormalities. Gain or amplification of chr1q (Amp1q) is the most frequent arm-level copy number gain in patients with MM, and it is associated with higher risk of progression and death despite recent advances in therapeutics. Thus, developing targeted therapy for patients with MM and Amp1q stands to benefit a large portion of patients in need of more effective management. Here, we employed large-scale dependency screens and drug screens to systematically characterize the therapeutic vulnerabilities of MM with Amp1q and showed increased sensitivity to the combination of MCL1 and PI3K inhibitors. Using single-cell RNA sequencing, we compared subclones with and without Amp1q within the same patient tumors and showed that Amp1q is associated with higher levels of MCL1 and the PI3K pathway. Furthermore, by isolating isogenic clones with different copy number for part of the chr1q arm, we showed increased sensitivity to MCL1 and PI3K inhibitors with arm-level gain. Lastly, we demonstrated synergy between MCL1 and PI3K inhibitors and dissected their mechanism of action in MM with Amp1q.

Single cell characterization of myeloma and its precursor conditions reveals transcriptional signatures of early tumorigenesis.

Multiple myeloma is a plasma cell malignancy almost always preceded by precursor conditions, but low tumor burden of these early stages has hindered the study of their molecular programs through bulk sequencing technologies. Here, we generate and analyze single cell RNA-sequencing of plasma cells from 26 patients at varying disease stages and 9 healthy donors. In silico dissection and comparison of normal and transformed plasma cells from the same bone marrow biopsy enables discovery of patient-specific transcriptional changes. Using Non-Negative Matrix Factorization, we discover 15 gene expression signatures which represent transcriptional modules relevant to myeloma biology, and identify a signature that is uniformly lost in abnormal cells across disease stages. Finally, we demonstrate that tumors contain heterogeneous subpopulations expressing distinct transcriptional patterns. Our findings characterize transcriptomic alterations present at the earliest stages of myeloma, providing insight into the molecular underpinnings of disease initiation.

Immune biomarkers of response to immunotherapy in patients with high-risk smoldering myeloma.

Patients with smoldering multiple myeloma (SMM) are observed until progression, but early treatment may improve outcomes. We conducted a phase II trial of elotuzumab, lenalidomide, and dexamethasone (EloLenDex) in patients with high-risk SMM and performed single-cell RNA and T cell receptor (TCR) sequencing on 149 bone marrow (BM) and peripheral blood (PB) samples from patients and healthy donors (HDs). We find that early treatment with EloLenDex is safe and effective and provide a comprehensive characterization of alterations in immune cell composition and TCR repertoire diversity in patients. We show that the similarity of a patient's immune cell composition to that of HDs may have prognostic relevance at diagnosis and after treatment and that the abundance of granzyme K (GZMK)+ CD8+ effector memory T (TEM) cells may be associated with treatment response. Last, we uncover similarities between immune alterations observed in the BM and PB, suggesting that PB-based immune profiling may have diagnostic and prognostic utility.

Distinct cellular dynamics associated with response to CAR-T therapy for refractory B cell lymphoma.

Chimeric antigen receptor (CAR)-T cell therapy has revolutionized the treatment of hematologic malignancies. Approximately half of patients with refractory large B cell lymphomas achieve durable responses from CD19-targeting CAR-T treatment; however, failure mechanisms are identified in only a fraction of cases. To gain new insights into the basis of clinical response, we performed single-cell transcriptome sequencing of 105 pretreatment and post-treatment peripheral blood mononuclear cell samples, and infusion products collected from 32 individuals with large B cell lymphoma treated with either of two CD19 CAR-T products: axicabtagene ciloleucel (axi-cel) or tisagenlecleucel (tisa-cel). Expansion of proliferative memory-like CD8 clones was a hallmark of tisa-cel response, whereas axi-cel responders displayed more heterogeneous populations. Elevations in CAR-T regulatory cells among nonresponders to axi-cel were detected, and these populations were capable of suppressing conventional CAR-T cell expansion and driving late relapses in an in vivo model. Our analyses reveal the temporal dynamics of effective responses to CAR-T therapy, the distinct molecular phenotypes of CAR-T cells with differing designs, and the capacity for even small increases in CAR-T regulatory cells to drive relapse.

CAR T cell killing requires the IFNγR pathway in solid but not liquid tumours.

Chimeric antigen receptor (CAR) therapy has had a transformative effect on the treatment of haematologic malignancies1-6, but it has shown limited efficacy against solid tumours. Solid tumours may have cell-intrinsic resistance mechanisms to CAR T cell cytotoxicity. Here, to systematically identify potential resistance pathways in an unbiased manner, we conducted a genome-wide CRISPR knockout screen in glioblastoma, a disease in which CAR T cells have had limited efficacy7,8. We found that the loss of genes in the interferon-γ receptor (IFNγR) signalling pathway (IFNGR1, JAK1 or JAK2) rendered glioblastoma and other solid tumours more resistant to killing by CAR T cells both in vitro and in vivo. However, loss of this pathway did not render leukaemia or lymphoma cell lines insensitive to CAR T cells. Using transcriptional profiling, we determined that glioblastoma cells lacking IFNγR1 had lower upregulation of cell-adhesion pathways after exposure to CAR T cells. We found that loss of IFNγR1 in glioblastoma cells reduced overall CAR T cell binding duration and avidity. The critical role of IFNγR signalling in susceptibility of solid tumours to CAR T cells is surprising, given that CAR T cells do not require traditional antigen-presentation pathways. Instead, in glioblastoma tumours, IFNγR signalling was required for sufficient adhesion of CAR T cells to mediate productive cytotoxicity. Our work demonstrates that liquid and solid tumours differ in their interactions with CAR T cells and suggests that enhancing binding interactions between T cells and tumour cells may yield improved responses in solid tumours.

Designing sensitive viral diagnostics with machine learning.

Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome's conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants. Toward that goal, we screen 19,209 diagnostic-target pairs, concentrated on CRISPR-based diagnostics, and train a deep neural network to accurately predict diagnostic readout. We join this model with combinatorial optimization to maximize sensitivity over the full spectrum of a virus's genomic variation. We introduce Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT), a system for automated design, and use it to design diagnostics for 1,933 vertebrate-infecting viral species within 2 hours for most species and within 24 hours for all but three. We experimentally show that ADAPT's designs are sensitive and specific to the lineage level and permit lower limits of detection, across a virus's variation, than the outputs of standard design techniques. Our strategy could facilitate a proactive resource of assays for detecting pathogens.

DNA Polymerase and Mismatch Repair Exert Distinct Microsatellite Instability Signatures in Normal and Malignant Human Cells.

Although replication repair deficiency, either by mismatch repair deficiency (MMRD) and/or loss of DNA polymerase proofreading, can cause hypermutation in cancer, microsatellite instability (MSI) is considered a hallmark of MMRD alone. By genome-wide analysis of tumors with germline and somatic deficiencies in replication repair, we reveal a novel association between loss of polymerase proofreading and MSI, especially when both components are lost. Analysis of indels in microsatellites (MS-indels) identified five distinct signatures (MS-sigs). MMRD MS-sigs are dominated by multibase losses, whereas mutant-polymerase MS-sigs contain primarily single-base gains. MS deletions in MMRD tumors depend on the original size of the MS and converge to a preferred length, providing mechanistic insight. Finally, we demonstrate that MS-sigs can be a powerful clinical tool for managing individuals with germline MMRD and replication repair-deficient cancers, as they can detect the replication repair deficiency in normal cells and predict their response to immunotherapy. SIGNIFICANCE: Exome- and genome-wide MSI analysis reveals novel signatures that are uniquely attributed to mismatch repair and DNA polymerase. This provides new mechanistic insight into MS maintenance and can be applied clinically for diagnosis of replication repair deficiency and immunotherapy response prediction.This article is highlighted in the In This Issue feature, p. 995.

A post-transcriptional program of chemoresistance by AU-rich elements and TTP in quiescent leukemic cells.

BACKGROUND: Quiescence (G0) is a transient, cell cycle-arrested state. By entering G0, cancer cells survive unfavorable conditions such as chemotherapy and cause relapse. While G0 cells have been studied at the transcriptome level, how post-transcriptional regulation contributes to their chemoresistance remains unknown. RESULTS: We induce chemoresistant and G0 leukemic cells by serum starvation or chemotherapy treatment. To study post-transcriptional regulation in G0 leukemic cells, we systematically analyzed their transcriptome, translatome, and proteome. We find that our resistant G0 cells recapitulate gene expression profiles of in vivo chemoresistant leukemic and G0 models. In G0 cells, canonical translation initiation is inhibited; yet we find that inflammatory genes are highly translated, indicating alternative post-transcriptional regulation. Importantly, AU-rich elements (AREs) are significantly enriched in the upregulated G0 translatome and transcriptome. Mechanistically, we find the stress-responsive p38 MAPK-MK2 signaling pathway stabilizes ARE mRNAs by phosphorylation and inactivation of mRNA decay factor, Tristetraprolin (TTP) in G0. This permits expression of ARE mRNAs that promote chemoresistance. Conversely, inhibition of TTP phosphorylation by p38 MAPK inhibitors and non-phosphorylatable TTP mutant decreases ARE-bearing TNFα and DUSP1 mRNAs and sensitizes leukemic cells to chemotherapy. Furthermore, co-inhibiting p38 MAPK and TNFα prior to or along with chemotherapy substantially reduces chemoresistance in primary leukemic cells ex vivo and in vivo. CONCLUSIONS: These studies uncover post-transcriptional regulation underlying chemoresistance in leukemia. Our data reveal the p38 MAPK-MK2-TTP axis as a key regulator of expression of ARE-bearing mRNAs that promote chemoresistance. By disrupting this pathway, we develop an effective combination therapy against chemosurvival.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

The repertoire of mutational signatures in human cancer.

Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature1. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses3-15, enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated-but distinct-DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.

Single-cell RNA sequencing reveals compromised immune microenvironment in precursor stages of multiple myeloma.

Precursor states of Multiple Myeloma (MM) and its native tumor microenvironment need in-depth molecular characterization to better stratify and treat patients at risk. Using single-cell RNA sequencing of bone marrow cells from precursor stages, MGUS and smoldering myeloma (SMM), to full-blown MM alongside healthy donors, we demonstrate early immune changes during patient progression. We find NK cell abundance is frequently increased in early stages, and associated with altered chemokine receptor expression. As early as SMM, we show loss of GrK+ memory cytotoxic T-cells, and show their critical role in MM immunosurveillance in mouse models. Finally, we report MHC class II dysregulation in CD14+ monocytes, which results in T cell suppression in vitro. These results provide a comprehensive map of immune changes at play over the evolution of pre-malignant MM, which will help develop strategies for immune-based patient stratification.

Scaling computational genomics to millions of individuals with GPUs.

Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we show that high efficiency at low cost can be achieved by leveraging general-purpose libraries for computing using graphics processing units (GPUs), such as PyTorch and TensorFlow. We demonstrate > 200-fold decreases in runtime and ~ 5-10-fold reductions in cost relative to CPUs. We anticipate that the accessibility of these libraries will lead to a widespread adoption of GPUs in computational genomics.