The Society for Immunotherapy of Cancer Biomarkers Task Force recommendations review

Immunotherapy combination approaches: mechanisms, biomarkers and clinical observations

The approval of the first immune checkpoint inhibitors provided a paradigm shift for the treatment of malignancies across a broad range of indications. Whereas initially, single-agent immune checkpoint inhibition was used, increasing numbers of patients are now treated with combination immune checkpoint blockade, where non-redundant mechanisms of action of the individual agents generally lead to higher response rates. Furthermore, immune checkpoint therapy has been combined with various other therapeutic modalities, including chemotherapy, radiotherapy and other immunotherapeutics such as vaccines, adoptive cellular therapies, cytokines and others, in an effort to maximize clinical efficacy. Currently, a large number of clinical trials test combination therapies with an immune checkpoint inhibitor as a backbone. However, proceeding without inclusion of broad, if initially exploratory, biomarker investigations may ultimately slow progress, as so far, few combinations have yielded clinical successes based on clinical data alone. Here, we present the rationale for combination therapies and discuss clinical data from clinical trials across the immuno-oncology spectrum. Moreover, we discuss the evolution of biomarker approaches and highlight the potential new directions that comprehensive biomarker studies can yield.

Deciphering the Dynamic Complexities of the Liver Microenvironment - Toward a Better Understanding of Immune-Mediated liver Injury Caused by Immune Checkpoint Inhibitors (ILICI)

Immune checkpoint inhibitors (ICIs) represent a promising therapy for many types of cancer. However, only a portion of patients respond to this therapy and some patients develop clinically significant immune-mediated liver injury caused by immune checkpoint inhibitors (ILICI), an immune-related adverse event (irAE) that may require the interruption or termination of treatment and administration of systemic corticosteroids or other immunosuppressive agents. Although the incidence of ILICI is lower with monotherapy, the surge in combining ICIs with chemotherapy, targeted therapy, and combination of different ICIs has led to an increase in the incidence and severity of ILICI - a major challenge for development of effective and safe ICI therapy. In this review, we highlight the importance and contribution of the liver microenvironment to ILICI by focusing on the emerging roles of resident liver cells in modulating immune homeostasis and hepatocyte regeneration, two important decisive factors that dictate the initiation, progression, and recovery from ILICI. Based on the proposed contribution of the liver microenvironment on ICILI, we discuss the clinical characteristics of ILICI in patients with preexisting liver diseases, as well as the challenges of identifying prognostic biomarkers to guide the clinical management of severe ILICI. A better understanding of the liver microenvironment may lead to novel strategies and identification of novel biomarkers for effective management of ILICI.

Soluble Sema4D in Plasma of Head and Neck Squamous Cell Carcinoma Patients Is Associated With Underlying Non-Inflamed Tumor Profile

Semaphorin 4D (Sema4D) is a glycoprotein that is expressed by several tumors and immune cells. It can function as a membrane bound protein or as a cleaved soluble protein (sSema4D). We sought to investigate the translational potential of plasma sSema4D as an immune marker in plasma of patients with head and neck squamous cell carcinoma (HNSCC). Paired peripheral blood and tumor tissue samples of 104 patients with HNSCC were collected at the same time point to allow for real time analysis. Scoring of the histological inflammatory subtype (HIS) was carried out using Sema4D immunohistochemistry on the tumor tissue. sSema4D was detected in plasma using direct ELISA assay. Defining elevated sSema4D as values above the 95^th percentile in healthy controls, our data showed that sSema4D levels in plasma were elevated in 25.0% (95% CI, 16.7–34.9%) of the patients with HNSCC and showed significant association with HIS immune excluded (HIS-IE) (p = 0.007), Sema4D^+ve tumor cells (TCs) (p = 0.018) and PD-L1^+ve immune cells (ICs) (p = 0.038). A multi-variable logistic regression analysis showed that HIS was significantly (P = 0.004) associated with elevated sSema4D, an association not explained by available patient-level factors. Using the IO-360 nanoString platform, differential gene expression (DGE) analysis of 10 HNSCC tumor tissues showed that patients with high sSema4D in plasma (HsS4D) clustered as IFN-γ negative tumor immune signature and were mostly HIS-IE. The IC type in the HsS4D paired tumor tissue was predominantly myeloid, while the lymphoid compartment was higher in the low sSema4D (LsS4D). The Wnt signaling pathway was upregulated in the HsS4D group. Further analysis using the IO-360, 770 gene set, showed significant non-inflamed profile of the HsS4D tumors compared to the LsS4D. In conclusion, our data reveals an association between sSema4D and the histological inflammatory subtype.

Defining best practices for tissue procurement in immuno-oncology clinical trials: consensus statement from the Society for Immunotherapy of Cancer Surgery Committee

Immunotherapy is now a cornerstone for cancer treatment, and much attention has been placed on the identification of prognostic and predictive biomarkers. The success of biomarker development is dependent on accurate and timely collection of biospecimens and high-quality processing, storage and shipping. Tumors are also increasingly used as source material for the generation of therapeutic T cells. There have been few guidelines or consensus statements on how to optimally collect and manage biospecimens and source material being used for immunotherapy and related research. The Society for Immunotherapy of Cancer Surgery Committee has brought together surgical experts from multiple subspecialty disciplines to identify best practices and to provide consensus on how best to access and manage specific tissues for immuno-oncology treatments and clinical investigation. In addition, the committee recommends early integration of surgeons and other interventional physicians with expertise in biospecimen collection, especially in clinical trials, to optimize the quality of tissue and the validity of correlative clinical studies in cancer immunotherapy.

Clinical biomarkers directing the management of patients with colon and lung cancer (beyond oncogene-addicted NSCLC)

Treatment personalisation plays a key role in the current management of patients with cancer. Several biomarkers have shown clinical utility and may guide therapeutic decisions. Amongst patients with lung cancer, the level of expression of programmed death ligand 1 (PD-L1) has both prognostic and predictive values in terms of response to the inhibition of programmed cell death protein 1 (PD-1). Depending on the clinical setting, the expression of PD-L1 ≥1% or ≥50% has been associated with improved outcomes amongst patients receiving pembrolizumab. Regarding patients with colorectal carcinoma, mutations in the KRAS oncogene predict the responsiveness to the inhibition of epidermal growth factor receptor (EGFR). Only patients with wild-type KRAS tumours derive benefit from cetuximab and panitumumab in terms of response and survival. In conclusion, future research should aim in the optimisation of the use of biomarker in the clinical practice in order to provide the optimal drug combination to each individual patient.

Prediction of therapeutic outcome and survival in a transgenic mouse model of pancreatic ductal adenocarcinoma treated with dendritic cell vaccination or CDK inhibitor using MRI texture: a feasibility study

There is a lack of a well-established approach for assessment of early treatment outcomes for modern therapies for pancreatic ductal adenocarcinoma (PDAC) e.g. dinaciclib or dendritic cell (DC) vaccination. Here, we developed multivariate models using MRI texture features to detect treatment effects following dinaciclib drug or DC vaccine therapy in a transgenic mouse model of PDAC including 21 LSL-KrasG12D ; LSL-Trp53R172H ; Pdx-1-Cre (KPC) mice used as untreated control subjects (n=8) or treated with dinaciclib (n=7) or DC vaccine (n=6). Support vector machines (SVM) technique was performed to build a linear classifier with three variables for detection of tumor tissue changes following drug or vaccine treatments. Besides, multivariate regression models were generated with five variables to predict survival behavior and histopathological tumor markers (Fibrosis, CK19, and Ki67). The diagnostic performance was evaluated using accuracy, area under the receiver operating characteristic curve (AUC) and decision curve analyses. The regression models were evaluated with adjusted r-squared (Radj 2). SVM classifier successfully distinguished changes in tumor tissue with an accuracy of 95.24% and AUC of 0.93. The multivariate models generated with five variables were strongly associated with histopathological tumor markers, fibrosis (Radj 2=0.82, P<0.001), CK19 (Radj 2=0.92, P<0.001) and Ki67 (Radj 2=0.97, P<0.001). Furthermore, the multivariate regression model successfully predicted survival of KPC mice by interpreting tumor characteristics from MRI data (Radj 2=0.91, P<0.001). The results demonstrated that MRI texture features had great potential to generate diagnosis and prognosis models for monitoring early treatment response following dinaciclib drug or DC vaccine treatment and also predicting histopathological tumor markers and long-term clinical outcomes.

Reader-free ELISPOT assay for immuno-monitoring in peptide-based cancer vaccine immunotherapy

Cancer vaccine immunotherapy is a therapy that induces cellular immune responses against a target molecule to elicit clinical anti-tumor effects. These cellular immune responses against the target molecule are monitored to evaluate whether the antigen-specific cellular immune responses are induced and maintained during the vaccination period. Enzyme-linked immunospot (ELISPOT) assay is widely performed to analyze not only the frequency of immune cells, but also their effector functions as determined by their cytokine production/secretion. The present study aimed to develop a reader-free ELISPOT assay using a handy membrane-punching device termed ELI 8. With the assistance of particle analysis by ImageJ software, the results of spot counting were reproducible with high inter-assay and inter-examiner concordance. Immune cells that produce and secrete Th1 cytokines without antigen-peptide stimulation of peripheral blood mononuclear cells (PBMCs) were detected, and their frequencies in patients with cancer were significantly higher compared with those in healthy individuals. These frequencies varied between individuals, as well as between time points during the course of cancer vaccine immunotherapy in each patient. Due to the variability in spontaneous cytokine production/secretion by PBMCs, an antigen-specific immune response (IR) index is proposed, which is a ratio of the number of spot-forming cells (SFCs) subjected to antigen-stimulation to that of SFCs with spontaneous cytokine secretion without antigen-stimulation. This index may be used as a marker for antigen-specific cellular immune responses in patients treated with cancer immunotherapy. The IR index successfully detected the induction of Wilms' tumor 1-specific cellular immune responses in patients with cancer treated with cancer vaccine immunotherapy.

Precision cytopathology: expanding opportunities for biomarker testing in cytopathology

Precision cytopathology refers to therapeutically linked biomarker testing in cytopatology, a dynamically growing area of the discipline. This review describes basic steps to expand precision cytopathology services. Focusing exclusively on solid tumors, the review is divided into four sections: Section 1: Overview of precision pathology- opportunities and challenges; Section 2: Basic steps in establishing or expanding a precision cytopathology laboratory; Section 3: Cytopathology specimens suitable for next generation sequencing platforms; and Section 4: Summary. precision cytopathology continues to rapidly evolve in parallel with expanding targeted therapy options. Biomarker assays (companion diagnostics) comprise a multitude of test types including immunohistochemistry, in situ hybridization and molecular genetic tests such as PCR and next generation sequencing all of which are performable on cytology specimens. Best practices for precision cytopathology will incorporate traditional diagnostic approaches allied with careful specimen triage to enable successful biomarker analysis. Beyond triaging, cytopathologists knowledgeable about molecular test options and capabilities have the opportunity to refine diagnoses, prognoses and predictive information thereby assuming a lead role in precision oncology biomarker testing.

The role of automated cytometry in the new era of cancer immunotherapy

The introduction in the clinical practice of several new approaches to cancer immunotherapy has greatly increased the interest in analytical methodologies that can define the immunological profile of patients in the clinical setting. This requires huge effort to obtain reliable monitoring tools that could be used to improve the patient's clinical outcome. The clinical applications of flow cytometry (FCM) in oncology started with the measurement of DNA content for the evaluation of both ploidy and cell cycle profile as potential prognostic parameters in the majority of human solid cancer types. The availability of monoclonal antibodies widely broadened the spectrum of clinical applications of this technique, which rapidly became a fundamental tool for the diagnosis and prognosis of malignant hematological diseases. Among the emerging clinical applications of FCM, the study of minimal residual disease in hematological malignancies, the quantification of blood dendritic cells in various types of tumors, the study of metastatic spread in solid tumors throughout both the analysis of circulating endothelial progenitor cells and the identification and characterization of circulating tumor cells, all appear very promising. More recently, an advanced single cell analysis technique has been developed that combines the precision of mass spectrometry with the unique advantages of FCM. This approach, termed mass cytometry, utilizes antibodies conjugated to heavy metal ions for the analysis of cellular proteins by a mass spectrometer. It provides measurement of over 100 simultaneous cellular parameters in a single sample and has evolved from a promising technology to a high recognized platform for multi-dimensional single-cell analysis. Should a careful standardization of the analytical procedures be reached, both FCM and mass cytometry could effectively become ideal tools for the optimization of new immunotherapeutic approaches in cancer patients.

Single-cell technologies for profiling T cells to enable monitoring of immunotherapies

Immunotherapy relies on the reinvigoration of immune system to combat diseases and has transformed the landscape of cancer treatments. Clinical trials using immune checkpoint inhibitors (ICI), and adoptive transfer of genetically modified T cells have demonstrated durable remissions in subsets of cancer patients. A comprehensive understanding of the polyfunctionality of T lymphocytes in ICI or adoptive cell transfer (ACT), at single-cell resolution, will quantify T-cell properties that are essential for therapeutic benefit. We briefly highlight several emerging integrated single-cell technologies focusing on the profiling of multiple properties/functionalities of T cells. We envision that these tools have the potential to provide valuable experimental and clinical insights on T-cell biology, and eventually pave the road for the discovery of surrogate T-cell biomarkers for immunotherapy.