Shifting the paradigm: engaging multicellular networks for cancer therapy.

Most anti-cancer modalities are designed to directly kill cancer cells deploying mechanisms of action (MOAs) centered on the presence of a precise target on cancer cells. The efficacy of these approaches is limited because the rapidly evolving genetics of neoplasia swiftly circumvents the MOA generating therapy-resistant cancer cell clones. Other modalities engage endogenous anti-cancer mechanisms by activating the multi-cellular network (MCN) surrounding neoplastic cells in the tumor microenvironment (TME). These modalities hold a better chance of success because they activate numerous types of immune effector cells that deploy distinct cytotoxic MOAs. This in turn decreases the chance of developing treatment-resistance. Engagement of the MCN can be attained through activation of immune effector cells that in turn kill cancer cells or when direct cancer killing is complemented by the production of proinflammatory factors that secondarily recruit and activate immune effector cells. For instance, adoptive cell therapy (ACT) supplements cancer cell killing with the release of homeostatic and pro-inflammatory cytokines by the immune cells and damage associated molecular patterns (DAMPs) by dying cancer cells. The latter phenomenon, referred to as immunogenic cell death (ICD), results in an exponential escalation of anti-cancer MOAs at the tumor site. Other approaches can also induce exponential cancer killing by engaging the MCN of the TME through the release of DAMPs and additional pro-inflammatory factors by dying cancer cells. In this commentary, we will review the basic principles that support emerging paradigms likely to significantly improve the efficacy of anti-cancer therapy.

CD39 and LDHA affects the prognostic role of NLR in metastatic melanoma patients treated with immunotherapy.

BACKGROUND: Identifying response markers is highly needed to guide the treatment strategy in patients with metastatic melanoma. METHODS: A retrospective study was carried out in patients with unresectable/metastatic melanoma (stage IIIb-IV), treated with anti-PD-1 in the first line setting, to better explore the role and the timing of neutrophil/lymphocyte ratio (NLR) as potential biomarker of response. The relationship of NLR with inflammation-immune mediators and the underlying negative effect of raising NLR during immunotherapy, have been investigated with transcriptomic gene analysis. RESULTS: The results confirmed previous findings that a high baseline NLR is associated with a poorer prognosis and with higher serum level of lactate dehydrogenase (LDH), regardless of the presence of brain metastases. The transcriptomic analysis showed that high baseline NLR is associated with a characteristic gene signature CCNA1, LDHA and IL18R1, which correlates with inflammation and tumorigenesis. Conversely, low baseline NLR is associated with the signature CD3, SH2D1A, ZAP70 and CD45RA, linked to the immune-activation. The genes positively associated with NLR (CD39 (ENTPD1), PTEN, MYD88, MMP9 and LDH) are involved in processes of immunosuppression, inflammation and tumor-promoting activity. Increased expression of CD39 correlated with TGFß2, a marker of the N2 neutrophils with immunosuppressive activity. CONCLUSIONS: These results suggest that increasing NLR is associated with an increased neutrophil population, with polarization to the N2 phenotype, and this process may be the basis for the negatively prognostic role of NLR.

The identification of TCF1+ progenitor exhausted T cells in THRLBCL may predict a better response to PD-1/PD-L1 blockade.

T-cell/histiocyte-rich large B-cell lymphoma (THRLBCL) is a rare and aggressive variant of diffuse large B-cell lymphoma (DLBCL) that usually affects young to middle-aged patients, with disseminated disease at presentation. The tumor microenvironment (TME) plays a key role in THRLBCL due to its peculiar cellular composition (<10% neoplastic B cells interspersed in a cytotoxic T-cell/histiocyte-rich background). A significant percentage of THRLBCL is refractory to rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP)-based regimens and to chimeric antigen receptor T-cell therapy; thus, the development of a specific therapeutic approach for these patients represents an unmet clinical need. To better understand the interaction of immune cells in THRLBCL TME and identify more promising therapeutic strategies, we compared the immune gene expression profiles of 12 THRLBCL and 10 DLBCL samples, and further corroborated our findings in an extended in silico set. Gene coexpression network analysis identified the predominant role of the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) axis in the modulation of the immune response. Furthermore, the PD-1/PD-L1 activation was flanked by the overexpression of 48 genes related to the functional exhaustion of T cells. Globally, THRLBCL TME was highly interferon-inflamed and severely exhausted. The immune gene profiling findings strongly suggest that THRLBCL may be responsive to anti-PD-1 therapy but also allowed us to take a step forward in understanding THRLBCL TME. Of therapeutic relevance, we validated our results by immunohistochemistry, identifying a subset of TCF1+ (T cell-specific transcription factor 1, encoded by the TCF7 gene) progenitor exhausted T cells enriched in patients with THRLBCL. This subset of TCF1+ exhausted T cells correlates with good clinical response to immune checkpoint therapy and may improve prediction of anti-PD-1 response in patients with THRLBCL.

Hallmarks of Resistance to Immune-Checkpoint Inhibitors.

Immune-checkpoint inhibitors (ICI), although revolutionary in improving long-term survival outcomes, are mostly effective in patients with immune-responsive tumors. Most patients with cancer either do not respond to ICIs at all or experience disease progression after an initial period of response. Treatment resistance to ICIs remains a major challenge and defines the biggest unmet medical need in oncology worldwide. In a collaborative workshop, thought leaders from academic, biopharma, and nonprofit sectors convened to outline a resistance framework to support and guide future immune-resistance research. Here, we explore the initial part of our effort by collating seminal discoveries through the lens of known biological processes. We highlight eight biological processes and refer to them as immune resistance nodes. We examine the seminal discoveries that define each immune resistance node and pose critical questions, which, if answered, would greatly expand our notion of immune resistance. Ultimately, the expansion and application of this work calls for the integration of multiomic high-dimensional analyses from patient-level data to produce a map of resistance phenotypes that can be utilized to guide effective drug development and improved patient outcomes.

Contextual reprogramming of CAR-T cells for treatment of HER2+ cancers.

BACKGROUND: Adoptive transfer of chimeric antigen receptor (CAR)-engineered T cells combined with checkpoint inhibition may prevent T cell exhaustion and improve clinical outcomes. However, the approach is limited by cumulative costs and toxicities. METHODS: To overcome this drawback, we created a CAR-T (RB-340-1) that unites in one product the two modalities: a CRISPR interference-(CRISPRi) circuit prevents programmed cell death protein 1 (PD-1) expression upon antigen-encounter. RB-340-1 is engineered to express an anti-human epidermal growth factor receptor 2 (HER2) CAR single chain variable fragment (scFv), with CD28 and CD3ζ co-stimulatory domains linked to the tobacco etch virus (TEV) protease and a single guide RNA (sgRNA) targeting the PD-1 transcription start site (TSS). A second constructs includes linker for activation of T cells (LAT) fused to nuclease-deactivated spCas9 (dCas9)-Kruppel-associated box (KRAB) via a TEV-cleavable sequence (TCS). Upon antigen encounter, the LAT-dCas9-KRAB (LdCK) complex is cleaved by TEV allowing targeting of dCas9-KRAB to the PD-1 gene TSS. RESULTS: Here, we show that RB-340-1 consistently demonstrated higher production of homeostatic cytokines, enhanced expansion of CAR-T cells in vitro, prolonged in vivo persistence and more efficient suppression of HER2+ FaDu oropharyngeal cancer growth compared to the respective conventional CAR-T cell product. CONCLUSIONS: As the first application of CRISPRi toward a clinically relevant product, RB-340-1 with the conditional, non-gene editing and reversible suppression promotes CAR-T cells resilience to checkpoint inhibition, and their persistence and effectiveness against HER2-expressing cancer xenografts.

Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler.

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.

Diminished cytokine-induced Jak/STAT signaling is associated with rheumatoid arthritis and disease activity.

Rheumatoid arthritis (RA) is a systemic and incurable autoimmune disease characterized by chronic inflammation in synovial lining of joints. To identify the signaling pathways involved in RA, its disease activity, and treatment response, we adapted a systems immunology approach to simultaneously quantify 42 signaling nodes in 21 immune cell subsets (e.g., IFNα→p-STAT5 in B cells) in peripheral blood mononuclear cells (PBMC) from 194 patients with longstanding RA (including 98 patients before and after treatment), and 41 healthy controls (HC). We found multiple differences between patients with RA compared to HC, predominantly in cytokine-induced Jak/STAT signaling in many immune cell subsets, suggesting pathways that may be associated with susceptibility to RA. We also found that high RA disease activity, compared to low disease activity, was associated with decreased (e.g., IFNα→p-STAT5, IL-10→p-STAT1) or increased (e.g., IL-6→STAT3) response to stimuli in multiple cell subsets. Finally, we compared signaling in patients with established, refractory RA before and six months after initiation of methotrexate (MTX) or TNF inhibitors (TNFi). We noted significant changes from pre-treatment to post-treatment in IFNα→p-STAT5 signaling and IL-10→p-STAT1 signaling in multiple cell subsets; these changes brought the aberrant RA signaling profiles toward those of HC. This large, comprehensive functional signaling pathway study provides novel insights into the pathogenesis of RA and shows the potential of quantification of cytokine-induced signaling as a biomarker of disease activity or treatment response.

CTLA-4 blockade and interferon-α induce proinflammatory transcriptional changes in the tumor immune landscape that correlate with pathologic response in melanoma.

Patients with locally/regionally advanced melanoma were treated with neoadjuvant combination immunotherapy with high-dose interferon α-2b (HDI) and ipilimumab in a phase I clinical trial. Tumor specimens were obtained prior to the initiation of neoadjuvant therapy, at the time of surgery and progression if available. In this study, gene expression profiles of tumor specimens (N = 27) were investigated using the NanoString nCounter® platform to evaluate associations with clinical outcomes (pathologic response, radiologic response, relapse-free survival (RFS), and overall survival (OS)) and define biomarkers associated with tumor response. The Tumor Inflammation Signature (TIS), an 18-gene signature that enriches for response to Programmed cell death protein 1 (PD-1) checkpoint blockade, was also evaluated for association with clinical response and survival. It was observed that neoadjuvant ipilimumab-HDI therapy demonstrated an upregulation of immune-related genes, chemokines, and transcription regulator genes involved in immune cell activation, function, or cell proliferation. Importantly, increased expression of baseline pro-inflammatory genes CCL19, CD3D, CD8A, CD22, LY9, IL12RB1, C1S, C7, AMICA1, TIAM1, TIGIT, THY1 was associated with longer OS (p < 0.05). In addition, multiple genes that encode a component or a regulator of the extracellular matrix such as MMP2 and COL1A2 were identified post-treatment as being associated with longer RFS and OS. In all baseline tissues, high TIS scores were associated with longer OS (p = 0.0166). Also, downregulated expression of cell proliferation-related genes such as CUL1, CCND1 and AAMP at baseline was associated with pathological and radiological response (unadjusted p < 0.01). In conclusion, we identified numerous genes that play roles in multiple biological pathways involved in immune activation, immune suppression and cell proliferation correlating with pathological/radiological responses following neoadjuvant immunotherapy highlighting the complexity of immune responses modulated by immunotherapy. Our observations suggest that TIS may be a useful biomarker for predicting survival outcomes with combination immunotherapy.

A three-gene signature based on MYC, BCL-2 and NFKBIA improves risk stratification in diffuse large B-cell lymphoma.

Recent randomized trials focused on gene expression-based determination of the cell of origin in diffuse large B-cell lymphoma could not show significant improvements by adding novel agents to standard chemoimmunotherapy. The aim of this study was the identification of a gene signature able to refine current prognostication algorithms and applicable to clinical practice. Here we used a targeted gene expression profiling panel combining the Lymph2Cx signature for cell of origin classification with additional targets including MYC, BCL-2 and NFKBIA, in 186 patients from 2 randomized trials (discovery cohort) (NCT00355199 and NCT00499018). Data were validated in 3 independent series (2 large public datasets and a real-life cohort). By integrating the cell of origin, MYC/BCL-2 double expressor status and NFKBIA expression, we defined a 3-gene signature combining MYC, BCL-2 and NFKBIA (MBN-signature), which outperformed the MYC/BCL-2 double expressor status in multivariate analysis, and allowed further risk stratification within the germinal center B-cell/unclassified subset. The high-risk (MBN Sig-high) subgroup identified the vast majority of double hit cases and a significant fraction of Activated B-Cell-derived diffuse large B-cell lymphomas. These results were validated in 3 independent series including a cohort from the REMoDL-B trial, where, in an exploratory ad hoc analysis, the addition of bortezomib in the MBN Sig-high subgroup provided a progression free survival advantage compared with standard chemoimmunotherapy. These data indicate that a simple 3-gene signature based on MYC, BCL-2 and NFKBIA could refine the prognostic stratification in diffuse large B-cell lymphoma, and might be the basis for future precision-therapy approaches.

Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume II-practical challenges.

The development of strongly predictive validated biomarkers is essential for the field of immuno-oncology (IO) to advance. The highly complex, multifactorial data sets required to develop these biomarkers necessitate effective, responsible data-sharing efforts in order to maximize the scientific knowledge and utility gained from their collection. While the sharing of clinical- and safety-related trial data has already been streamlined to a large extent, the sharing of biomarker-aimed clinical trial derived data and data sets has been met with a number of hurdles that have impaired the progression of biomarkers from hypothesis to clinical use. These hurdles include technical challenges associated with the infrastructure, technology, workforce, and sustainability required for clinical biomarker data sharing. To provide guidance and assist in the navigation of these challenges, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to outline the challenges that researchers currently face, both at the conceptual level (Volume I) and at the technical level (Volume II). The committee also suggests possible solutions to these problems in the form of professional standards and harmonized requirements for data sharing, assisting in continued progress toward effective, clinically relevant biomarkers in the IO setting.

Improving the therapeutic index in adoptive cell therapy: key factors that impact efficacy.

The therapeutic index (TI) is a quantitative assessment of a drug safety proportional to its effectiveness. The estimation is intuitive when the engagement of the product with its target is dependent on stable chemistry and predictable pharmacokinetics as is the case for small molecules or antibodies. But for therapeutics with complex biodistribution and context-dependent potency such as adoptive cell therapy (ACT) products, TI estimations need to consider a broader array of factors. These include product-dependent variability such as functional fitness, unpredictable pharmacokinetics due to non-specific trapping, sequestration and extravasation into normal tissues and variable rates of in vivo expansion. In the case of solid malignancies, additional modifiers dependent on individual tumor immune biology may affect pharmacodynamics, including differential trafficking to benign compared with cancer tissue, hampered engagement with target cells, immune suppression and cellular dysfunction due to unfavorable metabolic conditions. Here, we propose a patient-specific assessment of factors affecting on-tumor from off-tumor activity in disparate immunologic environments that impact ACT's clinical efficacy and may favorably balance the TI. for ACT products.

Society for Immunotherapy of Cancer clinical and biomarkers data sharing resource document: Volume I-conceptual challenges.

The sharing of clinical trial data and biomarker data sets among the scientific community, whether the data originates from pharmaceutical companies or academic institutions, is of critical importance to enable the development of new and improved cancer immunotherapy modalities. Through data sharing, a better understanding of current therapies in terms of their efficacy, safety and biomarker data profiles can be achieved. However, the sharing of these data sets involves a number of stakeholder groups including patients, researchers, private industry, scientific journals and professional societies. Each of these stakeholder groups has differing interests in the use and sharing of clinical trial and biomarker data, and the conflicts caused by these differing interests represent significant obstacles to effective, widespread sharing of data. Thus, the Society for Immunotherapy of Cancer (SITC) Biomarkers Committee convened to identify the current barriers to biomarker data sharing in immuno-oncology (IO) and to help in establishing professional standards for the responsible sharing of clinical trial data. The conclusions of the committee are described in two position papers: Volume I-conceptual challenges and Volume II-practical challenges, the first of which is presented in this manuscript. Additionally, the committee suggests actions by key stakeholders in the field (including organizations and professional societies) as the best path forward, encouraging the cultural shift needed to ensure responsible data sharing in the IO research setting.

Immune landscapes predict chemotherapy resistance and immunotherapy response in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous hematological malignancy. Although immunotherapy may be an attractive modality to exploit in patients with AML, the ability to predict the groups of patients and the types of cancer that will respond to immune targeting remains limited. This study dissected the complexity of the immune architecture of AML at high resolution and assessed its influence on therapeutic response. Using 442 primary bone marrow samples from three independent cohorts of children and adults with AML, we defined immune-infiltrated and immune-depleted disease classes and revealed critical differences in immune gene expression across age groups and molecular disease subtypes. Interferon (IFN)-γ-related mRNA profiles were predictive for both chemotherapy resistance and response of primary refractory/relapsed AML to flotetuzumab immunotherapy. Our compendium of microenvironmental gene and protein profiles provides insights into the immuno-biology of AML and could inform the delivery of personalized immunotherapies to IFN-γ-dominant AML subtypes.

The Biology of Immune-Active Cancers and Their Regulatory Mechanisms.

The development of cancer results from the evolutionary balance between the proliferating aptitude of cancer cells and the response of the host's tissues. Some cancers are characterized by genetic instability dependent upon impaired DNA repair mechanisms that lead to the chaotic disruption of multiple cellular functions often in excess of the cancer survival needs and may exert broad effects on surrounding tissues, some beneficial and some detrimental to cancer growth. Among them, inflammatory processes that accompany wound healing may initiate a reaction of the host against the neo-formation. This is possibly triggered by the release by dying cancer cells of molecules known as Damage-Associated Molecular Patterns (DAMPs) following a process termed Immunogenic Cell Death (ICD) that initiates an immune response through innate and adaptive mechanisms. Indeed, analysis of large cancer data sets has shown that ICD is strictly associated with the activation of other immune effector or immune-regulatory pathways. Here, we will describe how immune activation and compensatory immune-regulatory mechanisms balance anti-cancer immune surveillance and the roles that innate and adaptive immunity play including the weight that neo-epitopes may exert as initiators and sculptors of high-affinity memory and effector immune responses against cancer. We will discuss the evolutionary basis for the existence of immune checkpoints and how several theories raised to explain cancer resistance to immunotherapy represent a facet of a similar evolutionary phenomenon that we described in the Theory of Everything. We will show how the biology of immunogenicity and counterbalancing immune regulation is widespread across cancers independent of their ontogenesis while subtle idiosyncratic differences are discernible among them. Finally, we will suggest that overcoming immune resistance implies distinct approaches relevant to the immune context of individual cancers.

The Paradox of Cancer Immune Exclusion: Immune Oncology Next Frontier.

Checkpoint inhibitor therapy (CIT) has revolutionized cancer treatment but it has also reached a standstill when an absent dialog between cancer and immune cells makes it irrelevant. This occurs with high prevalence in the context of "immune silent" and, even perhaps, "immune-excluded" tumors. The latter are characterized by T cells restricted to the periphery of cancer nests. Since in either case T cells do not come in direct contact with most cancer cells, CIT rests immaterial. Adoptive cell therapy (ACT), may also be affected by limited access to antigen-bearing cancer cells. While lack of immunogenicity intuitively explains the immune silent phenotype, immune exclusion is perplexing. The presence of T cells at the periphery suggests that chemo-attraction recruits them and an immunogenic stimulus promotes their persistence. However, what stops the T cells from infiltrating the tumors' nests and reaching the germinal center (GC)? Possibly, a concentric gradient of increased chemo-repulsion or decreased chemo-attraction demarcates an abrupt "do not trespass" warning. Various hypotheses suggest physical or functional barriers but no definitive consensus exists over the weight that each plays in human cancers. On one hand, it could be hypothesized that the intrinsic biology of cancer cells may degenerate from a "cancer stem cell" (CSC)-like phenotype in the GC toward a progressively more immunogenic phenotype prone to immunogenic cell death (ICD) at the periphery. On the other hand, the intrinsic biology of the cancer cells may not change but it is the disorderly architecture of the tumor microenvironment (TME) that alters in a centripetal direction cancer cell metabolism, both directly and indirectly, the function of surrounding stromal cells. In this chapter, we examine whether the paradoxical exclusion of T cells from tumors may serve as a model to understand the requirements for tumor immune infiltration and, correspondingly, we put forth strategies to restore the dialog between immune cells and cancer to enhance the effectiveness of immune oncology (IO) approaches.

Next Generation Imaging Techniques to Define Immune Topographies in Solid Tumors.

In recent years, cancer immunotherapy experienced remarkable developments and it is nowadays considered a promising therapeutic frontier against many types of cancer, especially hematological malignancies. However, in most types of solid tumors, immunotherapy efficacy is modest, partly because of the limited accessibility of lymphocytes to the tumor core. This immune exclusion is mediated by a variety of physical, functional and dynamic barriers, which play a role in shaping the immune infiltrate in the tumor microenvironment. At present there is no unified and integrated understanding about the role played by different postulated models of immune exclusion in human solid tumors. Systematically mapping immune landscapes or "topographies" in cancers of different histology is of pivotal importance to characterize spatial and temporal distribution of lymphocytes in the tumor microenvironment, providing insights into mechanisms of immune exclusion. Spatially mapping immune cells also provides quantitative information, which could be informative in clinical settings, for example for the discovery of new biomarkers that could guide the design of patient-specific immunotherapies. In this review, we aim to summarize current standard and next generation approaches to define Cancer Immune Topographies based on published studies and propose future perspectives.

Status of Immune Oncology: Challenges and Opportunities.

This volume is intended to review the methods used to identify biomarkers predictive of cancer responsiveness to immunotherapy. The successful development of clinically actionable biomarkers depends upon three features: (a) their biological role with respect to malignant transformation and tumor progression; (b) the ability to detect them with robust, reliable, and clinically applicable assays; and (c) their prognostic or predictive value, as validated in clinical trials.Identifying biomarkers that have predictive value for patient selection based on the likelihood of benefiting from anticancer immunotherapy is a lengthy and complex process. To date, few predictive biomarkers for anticancer immunotherapy have been robustly analytically and clinically validated (i.e., PD-L1 expression as measured by IHC assays and microsatellite instability (MSI)/dMMR as measured by PCR or IHC, respectively).This introductory chapter to this book focuses on scientific and technical aspects relevant to the identification and validation of predictive biomarkers for immunotherapy. We emphasize that methods should address both the biology of the tumor and the tumor microenvironment. Moreover, the identification of biomarkers requires highly sensitive, multiplexed, comprehensive techniques, especially for application in clinical care. Thus, in this chapter, we will define the outstanding questions related to the immune biology of cancer as a base for development of the biomarkers and assays using diverse methodologies. These biomarkers will likely be identified through research that integrates conventional immunological approaches along with high-throughput genomic and proteomic screening and the host immune response of individual patients that relates to individual tumor biology and immune drugs' mechanism of action.Checkpoint inhibitor therapy (CIT) is by now an accepted modality of cancer treatment. However, immune resistance is common, and most patients do not benefit from the treatment. The reasons for resistance are diverse, and approaches to circumvent it need to consider genetic, biologic, and environmental factors that affect anticancer immune response. Here, we propose to systematically address fundamental concepts based on the premise that malignant cells orchestrate their surroundings by interacting with innate and adaptive immune sensors. This principle applies to most cancers and governs their evolution in the immune-competent host. Understanding the basic requirement(s) for this evolutionary process will guide biomarker discovery and validation and ultimately guide to effective therapeutic choices. This volume will also discuss novel biomarker approaches aimed at informing an effective assay development from a mechanistic point of view, as well as the clinical implementation (i.e., patient enrichment) for immune therapies.

Development of Gene Expression-Based Biomarkers on the nCounter® Platform for Immuno-Oncology Applications.

Biomarkers based on transcriptional profiling can be useful in the measurement of complex and/or dynamic physiological states where other profiling strategies such as genomic or proteomic characterization are not able to adequately measure the biology. One particular advantage of transcriptional biomarkers is the ease with which they can be measured in the clinical setting using robust platforms such as the NanoString nCounter system. The nCounter platform enables digital quantitation of multiplexed RNA from small amounts of blood, formalin-fixed, paraffin-embedded tumors, or other such biological samples that are readily available from patients, and the chapter uses it as the primary example for diagnostic assay development. However, development of diagnostic assays based on RNA biomarkers on any platform requires careful consideration of all aspects of the final clinical assay a priori, as well as design and execution of the development program in a way that will maximize likelihood of future success. This chapter introduces transcriptional biomarkers and provides an overview of the design and development process that will lead to a locked diagnostic assay that is ready for validation of clinical utility.

The tumor inflammation signature (TIS) is associated with anti-PD-1 treatment benefit in the CERTIM pan-cancer cohort.

BACKGROUND: The 18-gene tumor inflammation signature (TIS) is a clinical research assay that enriches for clinical benefit to immune checkpoint blockade. We evaluated its ability to predict clinical benefit of immunotherapy in cancer patients treated with PD-1 checkpoint inhibitors in routine clinical care. METHODS: The CERTIM cohort is a prospective cohort which includes patients receiving immune checkpoint inhibitors in Cochin University hospital. RNA extracted from 58 archival formalin fixed paraffin embedded tumor blocks (including 38 lung cancers, 5 melanomas, 10 renal carcinomas, 4 urothelial carcinomas and 1 colon carcinoma) was hybridized to a beta version of the NanoString® PanCancer IO360™ CodeSet using nCounter® technology. Gene expression signatures were correlated with tumor responses (by RECIST criteria) and overall survival. PD-L1 immunostaining on tumor cells was assessed in 37 non-small cell lung cancer (NSCLC) samples and tumor mutational burden (TMB) measured by whole exome sequencing in 19 of these. RESULTS: TIS scores were significantly associated with complete or partial response to anti-PD-1 treatment in the whole cohort (odds ratio = 2.64, 95% CI [1.4; 6.0], p = 0.008), as well as in the NSCLC population (odds ratio = 3.27, 95% CI [1.2; 11.6], p = 0.03). Patients whose tumor had a high TIS score (upper tertile) showed prolonged overall survival compared to patients whose tumor had lower TIS scores, both in the whole cohort (hazard ratio = 0.37, 95% CI [0.18, 0.76], p = 0.005) and in the NSCLC population (hazard ratio = 0.36, 95% CI [0.14, 0.90], p = 0.02). In the latter, the TIS score was independent from either PD-L1 staining on tumor cells (spearman coefficient 0.2) and TMB (spearman coefficient - 0.2). CONCLUSIONS: These results indicate that validated gene expression assay measuring the level of tumor microenvironment inflammation such as TIS, are accurate and independent predictive biomarkers and can be easily implemented in the clinical practice.