Tumor-intrinsic metabolic reprogramming and how it drives resistance to anti-PD-1/PD-L1 treatment.

The development of immune checkpoint blockade (ICB) therapies has been instrumental in advancing the field of immunotherapy. Despite the prominence of these treatments, many patients exhibit primary or acquired resistance, rendering them ineffective. For example, anti-programmed cell death protein 1 (anti-PD-1)/anti-programmed cell death ligand 1 (anti-PD-L1) treatments are widely utilized across a range of cancer indications, but the response rate is only 10%-30%. As such, it is necessary for researchers to identify targets and develop drugs that can be used in combination with existing ICB therapies to overcome resistance. The intersection of cancer, metabolism, and the immune system has gained considerable traction in recent years as a way to comprehensively study the mechanisms that drive oncogenesis, immune evasion, and immunotherapy resistance. As a result, new research is continuously emerging in support of targeting metabolic pathways as an adjuvant to ICB to boost patient response and overcome resistance. Due to the plethora of studies in recent years highlighting this notion, this review will integrate the relevant articles that demonstrate how tumor-derived alterations in energy, amino acid, and lipid metabolism dysregulate anti-tumor immune responses and drive resistance to anti-PD-1/PD-L1 therapy.

iBRIDGE: A Data Integration Method to Identify Inflamed Tumors from Single-cell RNA-Seq Data and Differentiate Cell Type-Specific Markers of Immune-Cell Infiltration.

The development of immune checkpoint-based immunotherapies has been a major advancement in the treatment of cancer, with a subset of patients exhibiting durable clinical responses. A predictive biomarker for immunotherapy response is the preexisting T-cell infiltration in the tumor immune microenvironment (TIME). Bulk transcriptomics-based approaches can quantify the degree of T-cell infiltration using deconvolution methods and identify additional markers of inflamed/cold cancers at the bulk level. However, bulk techniques are unable to identify biomarkers of individual cell types. Although single-cell RNA sequencing (scRNA-seq) assays are now being used to profile the TIME, to our knowledge there is no method of identifying patients with a T-cell inflamed TIME from scRNA-seq data. Here, we describe a method, iBRIDGE, which integrates reference bulk RNA-seq data with the malignant subset of scRNA-seq datasets to identify patients with a T-cell inflamed TIME. Using two datasets with matched bulk data, we show iBRIDGE results correlated highly with bulk assessments (0.85 and 0.9 correlation coefficients). Using iBRIDGE, we identified markers of inflamed phenotypes in malignant cells, myeloid cells, and fibroblasts, establishing type I and type II interferon pathways as dominant signals, especially in malignant and myeloid cells, and finding the TGFß-driven mesenchymal phenotype not only in fibroblasts but also in malignant cells. Besides relative classification, per-patient average iBRIDGE scores and independent RNAScope quantifications were used for threshold-based absolute classification. Moreover, iBRIDGE can be applied to in vitro grown cancer cell lines and can identify the cell lines that are adapted from inflamed/cold patient tumors.

CTLA4-Ig-Based Bifunctional Costimulation Inhibitor Blocks CD28 and ICOS Signaling to Prevent T Cell Priming and Effector Function.

CTLA4-Ig/abatacept dampens activation of naive T cells by blocking costimulation via CD28. It is an approved drug for rheumatoid arthritis but failed to deliver efficacy in a number of other autoimmune diseases. One explanation is that activated T cells rely less on CD28 signaling and use alternate coreceptors for effector function. ICOS is critical for activation of T-dependent humoral immune responses, which drives pathophysiology of IgG-mediated autoimmune diseases. In this study, we asked whether CD28 and ICOS play nonredundant roles for maintenance of T-dependent responses in mouse models. Using a hapten-protein immunization model, we show that during an ongoing germinal center response, combination treatment with CTLA4-Ig and ICOS ligand (ICOSL) blocking Ab completely dissolves ongoing germinal center responses, whereas single agents show only partial activity. Next, we took two approaches to engineer a therapeutic molecule that blocks both pathways. First, we engineered CTLA4-Ig to enhance binding to ICOSL while retaining affinity to CD80/CD86. Using a library approach, binding affinity of CTLA4-Ig to human ICOSL was increased significantly from undetectable to 15-42 nM; however, the affinity was still insufficient to completely block binding of ICOSL to ICOS. Second, we designed a bispecific costimulation inhibitor with high-affinity CTLA4 extracellular domains fused to anti-ICOSL Ab termed bifunctional costimulation inhibitor. With this bispecific approach, we achieved complete inhibition of CD80 and CD86 binding to CD28 as well as ICOS binding to ICOSL. Such bispecific molecules may provide greater therapeutic benefit in IgG-mediated inflammatory diseases compared with CTLA4-Ig alone.

A balance score between immune stimulatory and suppressive microenvironments identifies mediators of tumour immunity and predicts pan-cancer survival.

BACKGROUND: The balance between immune-stimulatory and immune-suppressive mechanisms in the tumour microenvironment is associated with tumour rejection and can predict the efficacy of immune checkpoint-inhibition therapies. METHODS: We consider the observed differences between the transcriptional programmes associated with cancer types where the levels of immune infiltration predict a favourable prognosis versus those in which the immune infiltration predicts an unfavourable prognosis and defined a score named Mediators of Immune Response Against Cancer in soLid microEnvironments (MIRACLE). MIRACLE deconvolves T cell infiltration, from inhibitory mechanisms, such as TGFß, EMT and PI3Kγ signatures. RESULTS: Our score outperforms current state-of-the-art immune signatures as a predictive marker of survival in TCGA (n = 9305, HR: 0.043, p value: 6.7 × 10-36). In a validation cohort (n = 7623), MIRACLE predicts better survival compared to other immune metrics (HR: 0.1985, p value: 2.73 × 10-38). MIRACLE also predicts response to checkpoint-inhibitor therapies (n = 333). The tumour-intrinsic factors inversely associated with the reported score such as EGFR, PRKAR1A and MAP3K1 are frequently associated with immune-suppressive phenotypes. CONCLUSIONS: The association of cancer outcome with the level of infiltrating immune cells is mediated by the balance of activatory and suppressive factors. MIRACLE accounts for this balance and predicts favourable cancer outcomes.

Oncogenic states dictate the prognostic and predictive connotations of intratumoral immune response.

BACKGROUND: An immune active cancer phenotype typified by a T helper 1 (Th-1) immune response has been associated with increased responsiveness to immunotherapy and favorable prognosis in some but not all cancer types. The reason of this differential prognostic connotation remains unknown. METHODS: To explore the contextual prognostic value of cancer immune phenotypes, we applied a multimodal pan-cancer analysis among 31 different histologies (9282 patients), encompassing immune and oncogenic transcriptomic analysis, mutational and neoantigen load and copy number variations. RESULTS: We demonstrated that the favorable prognostic connotation conferred by the presence of a Th-1 immune response was abolished in tumors displaying specific tumor-cell intrinsic attributes such as high transforming growth factor-beta (TGF-ß) signaling and low proliferation capacity. This observation was independent of mutation rate. We validated this observation in the context of immune checkpoint inhibition. WNT-ß catenin, barrier molecules, Notch, hedgehog, mismatch repair, telomerase activity and AMPK signaling were the pathways most coherently associated with an immune silent phenotype together with mutations of driver genes including IDH1/2, FOXA2, HDAC3, PSIP1, MAP3K1, KRAS, NRAS, EGFR, FGFR3, WNT5A and IRF7. CONCLUSIONS: This is the first systematic study demonstrating that the prognostic and predictive role of a bona fide favorable intratumoral immune response is dependent on the disposition of specific oncogenic pathways. This information could be used to refine stratification algorithms and prioritize hierarchically relevant targets for combination therapies.

Epitope and Fc-Mediated Cross-linking, but Not High Affinity, Are Critical for Antitumor Activity of CD137 Agonist Antibody with Reduced Liver Toxicity.

CD137 (TNFRSF9, 4-1BB) agonist antibodies (mAb) have demonstrated potent antitumor activity with memory response while causing hepatotoxicity in mouse models. In clinical trials, the degrees of liver toxicity of anti-CD137 vary from grade 4 transaminitis (urelumab) to nonexistent (utomilumab). To exploit the antitumor potential of CD137 signaling, we identified a new class of CD137 agonist mAbs with strong antitumor potency without significant transaminitis in vivo compared with CD137 agonists previously reported. These mAbs are cross-reactive to mouse and cynomolgus monkey and showed cross-linking-dependent T-cell costimulation activity in vitro Antitumor efficacy was maintained in Fc gamma receptor (FcγR) III-deficient mice but diminished in FcγRIIB-deficient mice, suggesting the critical role for FcγRIIB to provide cross-linking in vivo Interestingly, a single dose of an affinity-reduced variant was sufficient to control tumor growth, but a higher affinity variant did not improve efficacy. These observations suggest that binding epitope and FcγR interaction, but not necessarily high affinity, are important for antitumor efficacy and reduced liver toxicity of CD137 mAb. Our study suggests the possibility of CD137 agonist therapy with improved safety profile in humans.

Correction to: Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop.

Following publication of the original article [1], the author reported that an author name, Roberta Zappasodi, was missed in the authorship list.

Toward a comprehensive view of cancer immune responsiveness: a synopsis from the SITC workshop.

Tumor immunology has changed the landscape of cancer treatment. Yet, not all patients benefit as cancer immune responsiveness (CIR) remains a limitation in a considerable proportion of cases. The multifactorial determinants of CIR include the genetic makeup of the patient, the genomic instability central to cancer development, the evolutionary emergence of cancer phenotypes under the influence of immune editing, and external modifiers such as demographics, environment, treatment potency, co-morbidities and cancer-independent alterations including immune homeostasis and polymorphisms in the major and minor histocompatibility molecules, cytokines, and chemokines. Based on the premise that cancer is fundamentally a disorder of the genes arising within a cell biologic process, whose deviations from normality determine the rules of engagement with the host's response, the Society for Immunotherapy of Cancer (SITC) convened a task force of experts from various disciplines including, immunology, oncology, biophysics, structural biology, molecular and cellular biology, genetics, and bioinformatics to address the complexity of CIR from a holistic view. The task force was launched by a workshop held in San Francisco on May 14-15, 2018 aimed at two preeminent goals: 1) to identify the fundamental questions related to CIR and 2) to create an interactive community of experts that could guide scientific and research priorities by forming a logical progression supported by multiple perspectives to uncover mechanisms of CIR. This workshop was a first step toward a second meeting where the focus would be to address the actionability of some of the questions identified by working groups. In this event, five working groups aimed at defining a path to test hypotheses according to their relevance to human cancer and identifying experimental models closest to human biology, which include: 1) Germline-Genetic, 2) Somatic-Genetic and 3) Genomic-Transcriptional contributions to CIR, 4) Determinant(s) of Immunogenic Cell Death that modulate CIR, and 5) Experimental Models that best represent CIR and its conversion to an immune responsive state. This manuscript summarizes the contributions from each group and should be considered as a first milestone in the path toward a more contemporary understanding of CIR. We appreciate that this effort is far from comprehensive and that other relevant aspects related to CIR such as the microbiome, the individual's recombined T cell and B cell receptors, and the metabolic status of cancer and immune cells were not fully included. These and other important factors will be included in future activities of the taskforce. The taskforce will focus on prioritization and specific actionable approach to answer the identified questions and implementing the collaborations in the follow-up workshop, which will be held in Houston on September 4-5, 2019.

Pan-cancer adaptive immune resistance as defined by the Tumor Inflammation Signature (TIS): results from The Cancer Genome Atlas (TCGA).

The Tumor Inflammation Signature (TIS) is an investigational use only (IUO) 18-gene signature that measures a pre-existing but suppressed adaptive immune response within tumors. The TIS has been shown to enrich for patients who respond to the anti-PD1 agent pembrolizumab. To explore this immune phenotype within and across tumor types, we applied the TIS algorithm to over 9000 tumor gene expression profiles downloaded from The Cancer Genome Atlas (TCGA). As expected based on prior evidence, tumors with known clinical sensitivity to anti-programmed cell death protein 1 (PD-1) blockade had higher average TIS scores. Furthermore, TIS scores were more variable within than between tumor types, and within each tumor type a subset of patients with elevated scores was identifiable although with different prevalence associated with each tumor type, the latter consistent with the observed clinical responsiveness to anti PD-1 blockade. Notably, TIS scores only minimally correlated with mutation load in most tumors and ranking tumors by median TIS score showed differing association to clinical sensitivity to PD-1/PD-1 ligand 1 (PD-L1) blockade than ranking of the same tumors by mutation load. The expression patterns of the TIS algorithm genes were conserved across tumor types yet appeared to be minimally prognostic in most cancers, consistent with the TIS score serving as a pan-cancer measurement of the inflamed tumor phenotype. Characterization of the prevalence and variability of TIS will lead to increased understanding of the immune status of untreated tumors and may lead to improved indication selection for testing immunotherapy agents.

Immune oncology, immune responsiveness and the theory of everything.

Anti-cancer immunotherapy is encountering its own checkpoint. Responses are dramatic and long lasting but occur in a subset of tumors and are largely dependent upon the pre-existing immune contexture of individual cancers. Available data suggest that three landscapes best define the cancer microenvironment: immune-active, immune-deserted and immune-excluded. This trichotomy is observable across most solid tumors (although the frequency of each landscape varies depending on tumor tissue of origin) and is associated with cancer prognosis and response to checkpoint inhibitor therapy (CIT). Various gene signatures (e.g. Immunological Constant of Rejection - ICR and Tumor Inflammation Signature - TIS) that delineate these landscapes have been described by different groups. In an effort to explain the mechanisms of cancer immune responsiveness or resistance to CIT, several models have been proposed that are loosely associated with the three landscapes. Here, we propose a strategy to integrate compelling data from various paradigms into a "Theory of Everything". Founded upon this unified theory, we also propose the creation of a task force led by the Society for Immunotherapy of Cancer (SITC) aimed at systematically addressing salient questions relevant to cancer immune responsiveness and immune evasion. This multidisciplinary effort will encompass aspects of genetics, tumor cell biology, and immunology that are pertinent to the understanding of this multifaceted problem.

LRRC15 Is a Novel Mesenchymal Protein and Stromal Target for Antibody-Drug Conjugates.

Progress in understanding tumor stromal biology has been constrained in part because cancer-associated fibroblasts (CAF) are a heterogeneous population with limited cell-type-specific protein markers. Using RNA expression profiling, we identified the membrane protein leucine-rich repeat containing 15 (LRRC15) as highly expressed in multiple solid tumor indications with limited normal tissue expression. LRRC15 was expressed on stromal fibroblasts in many solid tumors (e.g., breast, head and neck, lung, pancreatic) as well as directly on a subset of cancer cells of mesenchymal origin (e.g., sarcoma, melanoma, glioblastoma). LRRC15 expression was induced by TGFß on activated fibroblasts (αSMA+) and on mesenchymal stem cells. These collective findings suggested LRRC15 as a novel CAF and mesenchymal marker with utility as a therapeutic target for the treatment of cancers with LRRC15-positive stromal desmoplasia or cancers of mesenchymal origin. ABBV-085 is a monomethyl auristatin E (MMAE)-containing antibody-drug conjugate (ADC) directed against LRRC15, and it demonstrated robust preclinical efficacy against LRRC15 stromal-positive/cancer-negative, and LRRC15 cancer-positive models as a monotherapy, or in combination with standard-of-care therapies. ABBV-085's unique mechanism of action relied upon the cell-permeable properties of MMAE to preferentially kill cancer cells over LRRC15-positive CAF while also increasing immune infiltrate (e.g., F4/80+ macrophages) in the tumor microenvironment. In summary, these findings validate LRRC15 as a novel therapeutic target in multiple solid tumor indications and support the ongoing clinical development of the LRRC15-targeted ADC ABBV-085.Significance: These findings identify LRRC15 as a new marker of cancer-associated fibroblasts and cancers of mesenchymal origin and provide preclinical evidence for the efficacy of an antibody-drug conjugate targeting the tumor stroma. Cancer Res; 78(14); 4059-72. ©2018 AACR.

Murinization and H Chain Isotype Matching of the Anti-GITR Antibody DTA-1 Reduces Immunogenicity-Mediated Anaphylaxis in C57BL/6 Mice.

Recent advances in immuno-oncology have shown that the immune system can be activated to induce long-term, durable antitumor responses. For immuno-oncology drug development, immune activation is often explored using rat Abs in immunocompetent mouse models. Although these models can be used to show efficacy, antidrug immune responses to experimental protein-based therapeutics can arise. Immunogenicity of surrogate Abs may therefore represent an important obstacle to the evaluation of the antitumor efficacy of immunomodulator Abs in syngeneic models. A recent publication has shown that anti-glucocorticoid-induced TNFR family-related protein agonistic Ab DTA-1 (rat or murinized IgG2a) can induce the development of anaphylaxis in C57BL/6 mice upon repeated i.p. dosing because of an anti-idiotypic anti-drug Ab immune response. This study was undertaken to address the impact of the immunogenicity derived from the Fc and variable domains. To this end, chimerized (rat V domains/mouse constant regions) and murinized (95% mouse sequence) DTA-1-based surrogate Abs with a murine IgG2c H chain isotype were created. Chimerization and murinization of DTA-1 did not affect receptor binding and glucocorticoid-induced TNFR family-related protein-induced T cell agonistic properties. Similar in vivo antitumor efficacy and intratumoral CD8+/regulatory T cells were also observed. Finally, treatment of C57BL/6 mice with the chimerized and murinized DTA-1 Abs on a C57BL/6-matched IgG2c isotype resulted in reduced development and severity of anaphylaxis as measured by decline of body temperature, behavioral effects, serum IL-4, IgE, and anti-drug Ab levels. These results suggest that careful murinization and selection of a strain-matched H chain isotype are critical to generate ideal surrogate Abs for testing immuno-oncology mechanisms in vivo.

Cancer immune resistance: can theories converge?

Immune oncology (IO) is challenged to expand its usefulness to a broader range of cancers. A second generation of IO agents acting beyond the realm of Checkpoint Inhibitor Therapy (CIT) is sought with the intent of turning immune-resistant cancers into appealing IO targets. The published literature proposes a profusion of models to explain cancer immune resistance to CIT that largely outnumber the immune landscapes and corresponding resistance mechanisms. In spite of the complex and contradicting models suggested to explain refractoriness to CIT, the identification of prevailing mechanisms and their targeting may not be as daunting as it at first appears. Here, we suggest that cancer cells go through a conserved evolutionary bottleneck facing a Two-Option Choice to evade recognition by the immune competent host: they can either adopt a clean oncogenic process devoid of immunogenic stimuli (immune-silent tumors) or display an entropic biology prone to immune recognition (immune-active tumors) but resilient to rejection thanks to the recruitment of compensatory immune suppressive processes. Strategies aimed at enhancing the effectiveness of CIT will be different according to the immune landscape targeted.

Identification of prokaryotic small proteins using a comparative genomic approach.

MOTIVATION: Accurate prediction of genes encoding small proteins (on the order of 50 amino acids or less) remains an elusive open problem in bioinformatics. Some of the best methods for gene prediction use either sequence composition analysis or sequence similarity to a known protein coding sequence. These methods often fail for small proteins, however, either due to a lack of experimentally verified small protein coding genes or due to the limited statistical significance of statistics on small sequences. Our approach is based upon the hypothesis that true small proteins will be under selective pressure for encoding the particular amino acid sequence, for ease of translation by the ribosome and for structural stability. This stability can be achieved either independently or as part of a larger protein complex. Given this assumption, it follows that small proteins should display conserved local protein structure properties much like larger proteins. Our method incorporates neural-net predictions for three local structure alphabets within a comparative genomic approach using a genomic alignment of 22 closely related bacteria genomes to generate predictions for whether or not a given open reading frame (ORF) encodes for a small protein. RESULTS: We have applied this method to the complete genome for Escherichia coli strain K12 and looked at how well our method performed on a set of 60 experimentally verified small proteins from this organism. Out of a total of 11 407 possible ORFs, we found that 6 of the top 10 and 27 of the top 100 predictions belonged to the set of 60 experimentally verified small proteins. We found 35 of all the true small proteins within the top 200 predictions. We compared our method to Glimmer, using a default Glimmer protocol and a modified small ORF Glimmer protocol with a lower minimum size cutoff. The default Glimmer protocol identified 16 of the true small proteins (all in the top 200 predictions), but failed to predict on 34 due to size cutoffs. The small ORF Glimmer protocol made predictions for all the experimentally verified small proteins but only contained 9 of the 60 true small proteins within the top 200 predictions. CONTACT: jsamayoa@jhu.edu

The genetic landscape of the childhood cancer medulloblastoma.

Medulloblastoma (MB) is the most common malignant brain tumor of children. To identify the genetic alterations in this tumor type, we searched for copy number alterations using high-density microarrays and sequenced all known protein-coding genes and microRNA genes using Sanger sequencing in a set of 22 MBs. We found that, on average, each tumor had 11 gene alterations, fewer by a factor of 5 to 10 than in the adult solid tumors that have been sequenced to date. In addition to alterations in the Hedgehog and Wnt pathways, our analysis led to the discovery of genes not previously known to be altered in MBs. Most notably, inactivating mutations of the histone-lysine N-methyltransferase genes MLL2 or MLL3 were identified in 16% of MB patients. These results demonstrate key differences between the genetic landscapes of adult and childhood cancers, highlight dysregulation of developmental pathways as an important mechanism underlying MBs, and identify a role for a specific type of histone methylation in human tumorigenesis.

Prioritization of driver mutations in pancreatic cancer using cancer-specific high-throughput annotation of somatic mutations (CHASM).

Over 20,000 genes were recently sequenced in a series of 24 pancreatic cancers. We applied CHASM (Cancer-specific High-throughput Annotation of Somatic Mutations) to 963 of the missense somatic missense mutations discovered in these 24 cancers. CHASM identified putative driver mutations (false discovery rate ≤0.3) in three known pancreatic cancer driver genes (P53, SMAD4, CDKN2A). An additional 15 genes with putative driver mutations include genes coding for kinases (PIK3CG, DGKA, STK33, TTK and PRKCG), for cell cycle related proteins (NEK8), and for proteins involved in cell adhesion (CMAS, PCDHB2). These and other mutations identified by CHASM point to potential "driver genes" in pancreatic cancer that should be prioritized for additional follow-up.