Leukocyte counts

Recently, studies have indicated that early changes in immunological markers may be associated with improved survival. To date, many of these signals have come from single analyte measures tested in some trials and not others, or from common clinical laboratory tests. Increases in ALC and eosinophil count after treatment with ipilimumab 3 mg/kg both correlated with improved survival [35]. Additionally, among 27 patients treated with ipilimumab 10 mg/kg, changes in the number of circulating T cells that expressed ICOS during the early treatment stages and a low ratio between absolute neutrophil count and ALC were also associated with better survival [36]. This is consistent with other analyses of patients treated in the expanded access program, where a high ALC after two doses of ipilimumab or at 6 weeks was significantly associated with survival [4, 37]. The association of changes in ALC with survival was also recently assessed among approximately 2000 patients who had received ipilimumab (at various doses as a monotherapy or in combination with chemotherapy) as part of their treatment regimen. Consistent with its proposed mechanism of action, treatment with ipilimumab resulted in an increase in mean ALC. However, while a positive association was observed between the rate of increase in ALC and survival, absolute changes in ALC were not found to be specifically predictive of improved survival [38]. By contrast, Simeone and co-authors showed that an increase in ALC between baseline and week 12 was significantly associated with disease control and survival in patients treated with intravenous ipilimumab 3 mg/kg every 3 weeks for a total of four doses [14]. Since ALC is a single analyte, further investigations into the utility of ALC as a prognostic biomarker of response to new drug activity are warranted, and it is suggested to combine ALC with other candidate markers.

T cells

It is now established that the infiltration of tumors by T cells can affect tumor growth, invasion, and patient outcome. Several studies have highlighted the correlation between ALC and clinical outcome both in patients with hematological malignancies and in those with solid tumors [39–41]. A conspicuous (“brisk”) lymphocyte infiltrate correlates strongly with a positive outcome in melanoma and in colorectal cancers (CRC). A follow-up study of 2845 patients with invasive primary melanoma has shown that death as a result of melanoma was 30% less with non-brisk tumor infiltrating lymphocyte (TIL) grade and 50% less with brisk TIL grade when compared with the absence of TIL independently of tumor characteristics currently used to define the melanoma stage [42]. In general, TIL express a CD3+CD8+CD45RO+ phenotype [43].

Numbers of CD8+ T cells correlate with improved outcome in various tumor types, including lung cancer and CRC [44, 45]. In contrast, tumor-infiltrating CD4+ T cell numbers may portend both favorable and unfavorable implications for patients’ survival. Regulatory T cells (Treg) express CD4 and reportedly constitute 5-15% of infiltrating CD4+ T cells in tumor samples [46]. The ratio of CD8+ T cells to Treg in TIL has been correlated with aggressive growth and poor response to chemotherapy in several tumor types, including urothelial carcinoma of the bladder [47], serous ovarian cancer [46, 48], squamous cell carcinoma [49], pancreatic cancer [50], breast cancer [47], and colorectal cancer [51, 52], and can separate cancer survivors from non-survivors [53]. In some tumor types, Treg accumulation correlates with a better prognosis. For example, in a large series of 967 stage II and stage III CRC, a high density of FoxP3-expressing intra-tumoral Treg was associated with improved survival and showed stronger prognostic significance than CD8+ T and CD45RO+ T cells [54]. A consensus on the marker set and gating strategy used for enumerating Treg in clinical samples has been recently established [55], with CD3, CD4, CD25, CD127, and FoxP3 markers as the minimally required markers to accurately identify human Treg. Furthermore, staining for Ki67 and CD45RA might provide useful information on the activation status of this cell population. The marker set was validated using PBMC from cancer patients as well as cells from TDLN and fresh tumor samples. A phenotyping panel that is not limited by the constraints of intracellular staining has been proposed by Roederer [56], and it considers Treg markers of activation and suppression. Other activation markers, such as CD39, CTLA-4, LAP, GARP, PD-1, and PD-L1, should be included in the monitoring of Treg for cancer patients as surrogate markers for Treg function and potentially eliminating the need for Treg isolation and in vitro suppression assays [57].

During the expansion phase that follows administration of blinatumomab, a bispecific CD3 and CD19 antibody, to patients with B cell precursor acute lymphoblastic leukemia, bone marrow-infiltrating T cells express a skewed T cell receptor (TCR) repertoire compared with peripheral blood T cells suggesting that clonal expansion occurred within the TME and might affect clinical outcome [58]. Massive parallel sequencing can be used to characterize the complete immune repertoire of patients. ImmunoSEQ (Adaptive Biotechnologies, Seattle, WA) offers a proprietary suite of high-throughput immune profiling assays and powerful online software. Multiplex PCR primers target all possible combinations of the noncontiguous (Vβ), diversity (Dβ), and joining (Jβ) gene segments of the β chain locus. The result of such an assay is millions of sequences per sample – and a quantitative description of the immune cell populations [59].

Myeloid cells

Tumor-associated macrophages (TAM) comprise up to 50% of malignant tumors. Due to their plasticity, it has been challenging to measure and classify these cells. TAM can be reprogrammed to type 2 macrophages (M2) by microenvironmental factors, as a result of alternative activation by Th2-biased cytokines, such as IL-10 [60]. M2 macrophages can be identified based on their expression of CD163 (scavenger receptor) and CD206 (mannose receptor) coupled with traditional monocyte markers such as CD14, HLA-DR, and CD11b. Although tumor infiltration with TAM has been demonstrated to correlate with poor clinical outcome, recent studies have suggested that high TAM densities could also be predictive of better patient survival as shown in prostate cancer [61]. Thus there is an urgent need to harmonize the phenotypic studies to accurately discriminate M1 from M2 macrophages and to correlate the density of macrophage populations with clinical outcome following immunotherapy [62].

Myeloid-derived suppressor cells (MDSC) consist of immature myeloid progenitor cells with the ability to suppress proliferation and effector functions of T cells [62, 63]. MDSC are expanded in patients with a variety of tumors. In contrast to murine MDSC, the markers used for identification of human MDSC subpopulations are still under discussion. In human PBMC, monocytic and granulocytic MDSC exhibit a CD11b+HLA-DR^neg/lowCD14+CD15- and CD11b+CD14-CD15+ or CD11b+CD14-CD66b+ phenotype, respectively [64]. While monocytic MDSC express the myeloid marker CD33, granulocytic MDSC display CD33^dim staining. Furthermore, HLA-DR-CD33+ cells contain mixed groups of MDSC comprising more immature progenitors. It has been proposed that HLA-DR-CD33+ cells be defined as ‘early-stage’ MDSC [64]. A study analyzing the efficacy of multi-peptide vaccination in patients with renal cell carcinoma (RCC) showed that two out of six phenotypically-defined MDSC populations were of prognostic value for overall patients’ survival [65].

Monocytes and Antibody-Dependent Cellular Cytotoxicity

Intriguingly, in a study of 29 patients with advanced cutaneous melanoma treated with ipilimumab it was shown that ipilimumab can engage ex vivo CD16-expressing, non-classical monocytes (CD14+CD16++), resulting in antibody-dependent cellular cytotoxicity-mediated lysis of Treg [66]. Patients responding to ipilimumab display significantly higher frequencies of non-classical monocytes at baseline compared with non-responder patients.

The diagnostic potential of intermediate CD14++CD16+ monocytes has also been shown in patients with CRC [67]. Intermediate monocytes were significantly elevated in these patients, with the highest frequencies detected in those with localized disease. The frequency of CD14+CD16+ monocytes was negatively associated with tumor size and pathological stage in patients with breast cancer [68]. The expansion of intermediate monocytes could be driven by monocyte chemoattractant protein-1 (MCP-1), which may be inhibited by the addition of neutralizing antibodies against MCP-1 to the monocyte cultures [68]. Finally, vaccination of patients with stage IV melanoma using Melan-A/MART-1:26-35(27 L) and gp100:209-217(210 M) peptides might augment the frequency of CD14+CD16+ monocytes as well as their expression of CD40/CD86 co-stimulatory molecules and antigen-presenting function [69]. Increases in both intra-tumoral and circulating CD14+HLA-DR^low/neg monocytes have been correlated with poor prognosis in RCC patients [70].

Tissue collection and variability

Significant hurdles exist to the use of archival, fresh tumor biopsies, and TDLN samples for correlative studies. In particular, sample quantity, variability in sample handling and processing, and tissue heterogeneity may all impact the pre-analytical variability of tumor-based immune assays. The volume of tumor tissue routinely obtained in diagnostic biopsies is often limiting for the purposes of high-dimensionality immune monitoring and necessitates a rigorous assessment of assay requirements and prioritization of sample workflow. Moreover, the quality of such routinely obtained tissues may be highly variable. Core or needle biopsies taken from different parts of a tumor mass may manifest significant differences in tumor, stromal, and immune cell composition. For surgical or excisional samples, warm and cold ischemia time is a critical parameter impacting the suitability of the tissue for use in complex immunoassays. Similar considerations apply for the handling of core or needle biopsy samples. Procedures for tissue collection, formalin fixation, and paraffin embedding remain non-standardized across institutions, while standardized protocols for other forms of tissue disposition (freezing, preservation in a nucleic acid stabilization medium such as RNAlater™, direct fresh tissue handling) are often not in place.

Despite these limitations, significant insights into tumor immunobiology have been made using archival formalin-fixed, paraffin-embedded (FFPE) samples. However, working with such samples requires rigorous characterization of pre-analytical variability as it impacts the intended set of assays, followed by hypothesis testing in an appropriately sized dataset that takes into account the anticipated pre-analytical variability. Analytical variability may further compound data quality and interpretation, particularly as it impacts the ability to make comparisons across different studies (this is addressed in greater detail by Working Group 1). For example, differences in sensitivity and specificity of detection antibodies for immunohistochemistry (IHC) or flow cytometry, the qualitative and quantitative scoring algorithms (e.g., analysis of whole tissue sections vs fields of view in IHC), and different method-based reaction principles (e.g., NanoString based gene expression profiling [79] and full RNAseq), represent only some parameters that will complicate direct data comparison.

As patients are exposed to an ever-increasing repertoire of immunotherapies and other anticancer agents, archival tissue, mostly originating from primary diagnostic biopsies, is less likely to be representative of the immune microenvironment at the time of disease progression or relapse. In these cases, fresh tumor biopsies are warranted to characterize tumor immune status at relapse/progression. More generally, because of the factors cited above that impact the pre-analytical variability of archival tissue, dedicated research biopsies taken in the context of detailed SOP for sample acquisition, annotation, handling, and disposition are preferable to archival tumor specimens whenever feasible, acceptable for study design, and ethically appropriate. Dedicated research personnel should be utilized and given responsibility for tissue acquisition and transport, physician training, and other aspects of sample acquisition and handling. Moreover, surgeons, interventional radiologists, and others obtaining samples should be properly trained and tightly integrated into the research team. Inclusion of patients as well as clinical personnel in the scientific discussion, when feasible, will increase patient willingness to donate tissue specimens and ultimately result in better sample quality. Further, proper annotation of research samples is critical to document the anatomic site (preferably including sub-localization within a given lesion), as well as parameters related to tissue collection and handling, such as time from biopsy/excision to fixation (warm and cold ischemia time), and freezing or other storage/processing steps. Where feasible, samples should be annotated with data related to the location of the lesion on radiographic imaging to allow for appropriate data interpretation in the respective context and the longitudinal resampling of the same anatomic site.

Multi-institutional studies

Special considerations are necessary when performing tumor immune monitoring in the context of multi-institutional studies. Quality control measures and analytical approaches should be put in place to both minimize and quantify site-dependent variability. This can include centralized specimen shipping kit preparation, overnight specimen shipment in temperature controlled containers, and processing upon arrival. For example, standardized approaches to sample processing, fixation and embedding (or alternate tissue preparation approaches appropriate for a given protocol), as well as sample storage and shipping should be used. It is desirable to centralize as many analytical steps as possible, including tissue sectioning and preparation (e.g., nucleic acid extraction) and analytical assay work. Samples received from multiple institutions should be analyzed in batches, and batched (or real-time) analysis should be used to support the early detection of pre-analytical or analytical quality control issues to ensure that these sources of variation are minimized. Any potentially problematic samples should be annotated accordingly to flag them.

Other sources for variability

Pre-analytical variability is influenced not only by technical factors, but also by biological heterogeneity. Where such heterogeneity cannot be fully controlled, it must be well characterized in order to guide the proper design of hypothesis-driven translational research studies [80]. Intra-tumoral heterogeneity of tumor cell clonotypes has been clearly documented through the observation of distinct somatic mutation profiles at different regions within a single lesion [81, 82]. Clonotypic heterogeneity between primary and metastatic lesions and from one metastasis to the next has also been well documented and can directly translate to the heterogeneity of clinical response between lesions within a single patient, which impacts overall disease outcome and treatment opportunities [6, 7]. Likewise, the immune TME may exhibit inter- and intra-lesional heterogeneity. For example, PD-L1 expression has been observed to be discordant between tumor sites in some cases [83]. Preliminary data also show significant intra-patient, inter-lesional diversity in TCR clonality and immune gene expression.

Experimentally, such biological heterogeneity can be controlled for in several ways. At the most basic level, routine morphologic characterization by hematoxylin and eosin (H&E) or cytokeratin staining is critical for confirming the histology of each sample, and SOP that utilize these data to determine sample adequacy and uniformity should be utilized. Where possible two or more cores should be evaluated; multiple cores should be combined for technical approaches that do not preserve geospatial data (e.g., gene expression profiling, whole exome sequencing, TCR deep sequencing, bulk proteomics), in order to compensate for intra-tumor heterogeneity. Where more uniform sampling of specific cell populations is desired, laser capture microdissection can be utilized for cell isolation.

Early insights into the TME and immunotherapy

Regardless of these analytical challenges, significant insights have been made into the biology of the tumor immune microenvironment by direct interrogation of tumor tissue. In particular, methodologies for interrogating the tumor-immune interface have demonstrated both prognostic and predictive values in the setting of checkpoint blockade immunotherapy. As discussed elsewhere, both detailed measures of tumor immune infiltration (the immune contexture) and more streamlined biomarkers representing the same phenomenon (the immunoscore) have shown prognostic value in CRC that may exceed that of traditional TNM staging [44, 84]. These data show that spatial distribution of immune cell infiltrates within the TME will be as important as quantitative assessment toward understanding the underlying biology.

Despite the documented geospatial and temporal heterogeneity of PD-L1 expression, PD-L1 on both tumor cells and immune-infiltrating cells has been shown to be a sensitive and specific biomarker of response to PD-1/PD-L1 directed therapies in tumor types such as non-small cell lung cancer (NSCLC) and urothelial carcinoma [85, 86]. Such insights have been made using archival FFPE samples, often of variable age relative to time of study enrollment. More recently, additional biomarkers have demonstrated predictive value in the setting of CTLA-4 or PD-1-directed immunotherapy, although the performance characteristics of these biomarkers have not yet been fully elucidated. These include measures of non-synonymous mutational load and predicted neoepitopes [87–90], TCR clonal diversity [91], apposition of PD-1 and PD-L1 on adjacent T cells and tumor/stromal cells [91], direct correlation of mutational tumor load and TIL infiltration [92], and expression of cytotoxicity or IFN-γ-associated genes characteristic of a T cell inflamed microenvironment [89, 93].

These data indicate that properly controlled tissue acquisition and analysis, as well as the use of complementary and reinforcing technologies (e.g., orthogonal characterization of biomarkers by multiplex IHC [94] and gene expression profiling), could overcome issues related to pre-analytical and analytical variability, allowing for reproducible assessment of clinically meaningful biomarkers in the TME. Furthermore, additional development and investment in such technologies will allow the use of more effective combinations of tissue analysis tools with limited material that is available in a clinical setting.

Collection and adequacy of the specimen

Technical considerations for ensuring the collection of adequate specimen are perhaps the most important element for quality control. It is therefore essential that the aspirate be analyzed at the bedside for adequacy of the specimen per the International Council for Standardization in Hematology (ICSH) guidelines [98]. Large volume aspirates from a single site may simply lead to dilution from peripheral blood and should be avoided. Use of needle redirects to access different regions of the bone through a single skin puncture may be useful but still carry the risk of aspiration from a hemorrhagic site. When possible, we recommend obtaining a paired blood sample so that the phenotypic and functional aspects of blood versus marrow mononuclear cells may be directly compared. For example, in contrast to the peripheral blood, T cells in the human marrow are mostly memory T cells and are enriched for CD8+ T cells [99]. Bone marrow samples collected in sodium heparin are sufficient for most immune monitoring assays wherein analysis by flow cytometry or mass cytometry is the focus [99]. However, EDTA may be the preferred anticoagulant in some instances, particularly when concurrent PCR-based molecular studies are desired. When quantitative changes in immune cell populations during immunotherapy are considered important, it is recommended that the sample dedicated for immune monitoring should be the first sample from the collection site [100]. In contrast to the clinical diagnostic samples which typically get prioritized, this often requires a needle redirect. In addition to the aspirate, collection and evaluation of the biopsy specimen is essential to gain insights into the location of immune cells and cell-cell interactions. ICSH guidelines recommend that at least 2 cm cores should be obtained. In settings wherein the amount of aspirate is inadequate, we suggest routinely obtaining touch preparations of the marrow biopsies. Finally, we strongly recommend that immune monitoring protocols for the marrow (at least those intended towards discovery of new targets) routinely include the preparation of “particle clots” using published guidelines [98, 101]. This is because processing of marrow biopsies typically involves decalcification protocols, which cause nucleic acid or protein damage and impact staining for several antigens. Clot sections do not require decalcification. Another approach is to consider snap-freezing a small (e.g., 0.5 cm) portion of the core, which can subsequently be utilized for analysis of gene expression and downstream deconvolution of data [102].

Specimen transport and initial processing

As with peripheral blood, marrow aspirates can be safely transported overnight at room temperature to reference laboratories, and such transport protocols have been successfully utilized in large multicenter studies involving correlative studies on bone marrow specimens [103]. Transport on ice or at lower temperatures leads to loss of mononuclear cell yield. Marrow aspirates also seem to have a greater tendency to clot than blood samples, and it is therefore essential to ensure adequacy of anticoagulant in the tube. Trephine core biopsies are typically added to the fixative at bedside and may be fixed using several different methods. A standard fixative is neutral buffered formalin. Fixation times vary between 1 and 24 h, but are typically 4–6 h. We strongly recommend using a pre-specified fixation time for all specimens in a clinical trial. Fixation longer than 24 h may negatively impact antigen retrieval and should be avoided.

Further processing and downstream applications

In contrast to other tissues, isolation of mononuclear cells from the bone marrow does not require enzymatic digestion steps. However, for samples with particulate appearance, we recommend initial dilution of the aspirate in sample buffer and use of a 0.1 micron filter to remove particulate/bone fragment debris. Ficoll density gradient centrifugation remains the most common approach for the isolation of mononuclear cells from the bone marrow. Mononuclear cells isolated from the marrow aspirate have been successfully utilized for a range of downstream immune monitoring assays including flow cytometry based assays, ELISPOT, MHC tetramers, mass cytometry, TCR sequencing as well as genome wide analyses of sorted cells [99, 100, 104, 105].

Trephine biopsies also require decalcification, which can be achieved by several methods. Decalcification with EDTA results in better preservation of nucleic acids but is slower than other acid reagents [98]. The combination of neutral buffered saline fixation followed by EDTA decalcification is the current format preferred by most investigators, as it provides adequate morphology, preserves nucleic acids for molecular studies, and antigens for IHC.

The microbiome modulates cancer initiation, progression and response to therapy

Similar to all mammalian organisms, the epithelial barrier surfaces in the human body are colonized by commensal microorganisms (the microbiome) with the largest microbial mass present in the lower intestine [106]. Thus, we are meta-organisms, or symbionts, in which our host cells and the microbial cells cohabit and interact with each other [107, 108]. By regulating human physiology and, in particular, inflammation and immunity, the presence and composition of the microbiome can affect cancer initiation, progression, and response to therapy [109–111]. Viruses and bacterial species have been implicated in oncogenesis [112]. Infection with one bacterial species, Helicobacter pylori, has been clearly associated with stomach cancer, and it is recognized as a class 1 human carcinogen [113]. However, several bacterial species have been described that are likely to be involved in the initiation and progression of other cancers such as CRC and gallbladder cancer [109, 114]. In addition, the composition of the microbiome at the epithelial barriers may affect the progression of tumors in sterile tissues not directly colonized by the microbiome [115]. The microbiome composition in cancer patients may be altered due to the presence of the tumor and to a larger extent due to the effect of therapeutic treatments. Use of antibiotics, radiation, and chemotherapy treatments induce persistent changes in the composition of the microbiome, often associated with a reduction in the number of bacterial species present. Following allogeneic bone marrow transplantation, the diversity of the intestinal microbiome at engraftment is an independent predictor of mortality, with higher diversity predicting a more favorable outcome [116]. Recently, experimental evidence as well as initial data in patients have shown that the efficacy of anti-cancer therapy, including adoptive T cell transfer after total body irradiation, immunostimulating oligonucleotides, chemotherapy with cyclophosphamide and platinum compounds as well as immune checkpoint inhibitors, requires the presence of the intestinal microbiome and is affected by the microbial composition [15, 16, 117–119]. The anti-cancer mechanisms of these therapies rely on the ability of the gut microbiome to educate infiltrating immune cells that produce inflammatory mediators required for the direct antitumor effects of therapy and promote the generation of an anti-tumor adaptive immune response [120]. Several microbial genera or species that promote or antagonize the effect of different types of cancer therapy or the anti-tumor host immune response have been identified.

The study of the composition of the microbial communities in the stool or at other anatomical sites of cancer patients before and after therapy could provide information about the immune status of the patients and contribute to the identification of future biomarkers for prediction of disease progression and response to therapy. The presently available information has been largely obtained in experimental animals, so it will be necessary to collect a wide range of information from clinical studies before being able to evaluate the prognostic significance of the findings and the identification of biomarkers. However, this type of analysis has great potential to provide clinically significant information. In addition, there has been important progress in the development of new methodologies to modify the composition of the microbiome, suggesting the possibility that the microbiome could be targeted to slow tumor progression, prevent cancer co-morbidities, enhance cancer therapy efficacy, and to attenuate treatment toxicity.

Development of microbiome studies

Until recently, the study of microbes in human samples relied on labor-intensive microbiology techniques for growing and collecting individual isolates, the data from which were influenced by cultivation conditions. These methods did not allow for complete profiling of the microbial communities present in the samples; however, the advent of next generation DNA sequencing methods has advanced microbial investigations. The most common approach for microbiome studies is the amplification and sequencing of variable regions in the bacterial genes encoding 16S ribosomal RNA to determine the taxonomic composition of the microbiome by comparing them to existing databases. Thus, 16S rRNA gene sequencing permits a more comprehensive assessment of the bacterial communities present in a clinical sample. When incorporating microbiome approaches to cancer studies, each element of a microbiome study is critically important [121].

Collection of specimens

The collection of specimens and metadata significantly influences the ability to derive clinically relevant downstream analyses. Many factors are important to consider, including determining the body site(s) of interest, e.g., stool, skin, oral mucosa, vaginal mucosa; selection of cases and controls; frequency of sampling; and method of collection. Because sites with little spatial separation can harbor distinct bacterial communities, consistency in sample collection is important [122, 123]. Predominant bacterial taxa and the microbial biomass are body site-dependent and location identity will determine the methods for collecting specimens and relevant metadata [124]. Most oncology studies that have included microbiome approaches have focused on stool [15, 118, 119]. While various stool sampling and storage methods have been studied, feasibility (e.g., accessibility to storage freezers) and patient participation (e.g., self-collection) may guide selection of optimal collection methods [125–127]. Depending on the clinical study, tumor type, and/or therapeutic intervention, the other commonly studied body sites of skin, oral mucosa, and vaginal mucosa may provide distinct and informative microbiome data. Identifying appropriate controls for oncology patients may be challenging; alternatively, repeat samplings of the same patients can provide internal controls, particularly if specimens are collected both prior to and after a clinical intervention.

Sequencing and analysis

Given the potential sources of variation in microbiome studies, standardization is crucial for study quality and reproducibility [128]. After collection and processing of specimens, regions of bacterial 16S ribosomal RNA gene are amplified and sequenced. Because newer sequencing platforms do not sequence the complete 16S rRNA genes, only some of the variable regions can be selected and sequenced, which allows effective identification of the genera present but can reduce the ability to identify bacteria at the species level. Primer selection is usually based on the source of the clinical biospecimens, e.g., V4 primers for stool samples and V1-3 primers for skin samples, to optimize species-level identification of sequences [129]. Different platforms can be used for amplicon sequencing. At present, the Illumina’s MiSeq is the most commonly used.

Various pipelines and tools are available to facilitate analyses of amplicon sequencing data. Most popular are Quantitative Insights Into Microbial Ecology [130] and mothur [131]. Alternatively, all genes in all microorganisms in a given sample can be analyzed by shotgun metagenomic sequencing. Metagenomic analysis allows identification not only of bacteria, fungi, and viruses present in a sample but also which genes and gene functions are present in the community. More recently, metatranscriptome analysis has been used to sequence the RNA in a sample and to evaluate which genes are transcribed, and to what extent. Metagenomic and metatranscriptomic analyses require a much higher depth of sequencing (and higher costs) to obtain sufficient coverage of the different microorganisms, and the bioinformatics analysis of the data is more challenging than for amplicon sequencing [132].

SEREX

SEREX has been developed primarily for the determination of humoral immunity to TAA by using tumor cDNA libraries in lambda vectors expressed in E. coli, which are then transferred to nitrocellulose membranes and incubated with sera from cancer patients and respective control donors. The clones reactive to sera are identified by sequencing [142].

Using this method >1000 TAA have been identified, including NY-ESO-1, which was discovered from an esophageal cancer cDNA library. Next to the use in human patients and clinical trials, SEREX has been also employed in murine transgenic models to predict TAA. Furthermore, a sera database has been established, which is for public access and allows the addition of data from other centers. However, one major limitation of this technology is the failure to detect post-translational modifications.

PROTEOMEX/SERPA

In addition to SEREX, PROTEOMEX also termed SERPA was developed using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) followed by Western blot analysis of the gels followed by their incubation with sera of patients and healthy volunteers [143, 144]. In addition, two-dimensional immune affinity chromatography followed by proteolysis and mass spectrometry has been used to identify novel TAA or respective biomarkers. Although these tools are very robust, the disadvantages of these proteome-based technologies are their labor intensity with limitations in sample capacity, while the mapping could be automated in the future.

Protein arrays

Other proteome-based high-throughput analyses include automated protein microarrays of serum antibodies from cancer patients versus healthy controls. With this technology, a large series of proteins can be evaluated, which are either derived from cDNA or peptide phage display libraries [145]. By using protein arrays with a known panel of proteins, an induction of antibody responses against TAA has been recently demonstrated in a study using ipilimumab associated with GM-CSF treatment [146]. The development of antibodies to NY-ESO-1 post-treatment was identified in one clinical responder and one non-responder, suggesting that immunotherapy can induce immune responses to other known TAA. Other sources for immune genomic arrays apart from libraries include recombinant proteins or tumor lysates. The implementations of recombinant proteins for the array are multiple, but also more costly and may not account for post-translational modifications like SEREX. In order to take into account the effects of post-translational modifications on epitope recognition with respect to aberrant glycosylation of the tumor protein, high-throughput analysis using a glycopeptide discovery platform for proteomics profiling has been developed [147]. Although this glycopeptide platform allows high-throughput analyses, it has yet to be validated in particular regarding reproducibility and stability of this technique.

SomaScan

Aptamer-based protein array monitoring has recently become available. A particular form of modified aptamers with slow off-rate (SOMAmers) allows for the comparative evaluation of proteins in as low as 70 μl of serum or plasma (or other biological fluids). The SOMAscan assay is highly multiplexed, sensitive and quantitative. This assay is based on the use of a new generation of protein-capture SOMAmer reagent [148]. Native proteins contained in biological samples are captured by SOMAmers immobilized on streptavidin-agarose beads via a photo-cleavable biotin linker. Unbound proteins are washed away. The proteins captured are then biotinylated, the complex biotinylated protein/SOMAmer is released from the capture beads by the UV-induced photocleavage of the photosensitive linker. Magnetic-streptavidin beads capture the freed protein-SOMAmer complexes while the SOMAmers that did not bind to a protein are washed away. Captured SOMAmer-protein complexes are then denatured and the SOMAmers (each containing a unique 40-nucleotide tag) are hybridized onto a high-density array of complementary probes. The hybridized SOMAmers are detected on a DNA array reader, which quantifies the presence of each SOMAmer using classic DNA detection methods. By transforming each individual protein concentration into a corresponding SOMAmer reagent concentration, the SOMAscan assay is not limited by variation between lots of protein standards. The SOMAscan assay measures over 1300 protein analytes that cover a diverse set of molecular functions. Targets to date extensively cover major gene families including receptors, kinases, growth factors, and hormones, and span a diverse collection of secreted proteins, including cytokines and their soluble receptors, and intracellular and extracellular proteins or domains. The assay covers a wide concentration range by using a systematic dilution scheme based on the normal abundance of the protein measured. The analysis of the SOMAscan is performed using classic DNA array data analysis and is based on bioinformatics tools that have been developed for gene array analysis.

Multiplexed ELISA-type assays

Chemokines and cytokines are small molecules, which play an important role in an array of physiologic, but also pathophysiologic acute (e.g. infections) and chronic (e.g. cancer) immune responses. Therefore the measurement of chemokines and cytokines can be used to monitor the immune system, as the composition of these small molecules yields insights into the immune cell repertoire and functions both in the disease state as well as in response to immunotherapy [149]. In addition, soluble adhesion molecules and MMP are also suitable biomarkers for clinical trials [22].

Historically, the assessment of cytokines and chemokines has been performed with the single-plex ELISA. Despite the accuracy and value of this technology, it has a limited scope, since determination of the cytokine network interaction is precluded. Furthermore, this method is costly, time consuming, requires a relatively large sample size, and can only measure one analyte per sample. Multiplex immunoassays measuring multiple biomarkers have since been developed and represent an important tool to monitor immune responses [150]. Using the luminex technology, it is possible to evaluate >100 cytokines/chemokines simultaneously with a minimal amount (approximately 50 μl) of sample thus avoiding sample pooling [151, 152]. For the implementation of this assay in clinical trials it is important to determine the accuracy and reliability (including potential antibody cross-reactivity) of the detection method for each analyte. Furthermore pre-analytical variables, such as the anti-coagulant used for the collection of blood, sample preparation, time and temperature storage of samples as well as gender and age of the donor also have an impact on the cytokine/chemokine measurement using luminex and ELISA [152–154]. However, no single method of specimen preparation was clearly superior for the measurement of cytokines. Although there exist anti-coagulant-dependent differences in analyte concentrations, the relative concentrations of the various analytes remain similar for a given anti-coagulant [154].

Mismatch repair deficiency and anti-tumor immunity

One notable exception to this disappointing preliminary experience has been in mismatch repair-deficient CRC where significant responses to PD-1 pathway inhibition have been observed [184]. The defective mismatch repair system results in a marked increase in the non-synonymous mutagenic burden within tumors, increasing the likelihood that a tumor-specific neoantigen, capable of recognition by the immune system, is generated [185]. This is certainly relevant for any tumor type that happens to have a high mutagenic burden because of either inherited or acquired mismatch repair deficiency – resulting in a degree of microsatellite instability (MSI) – or other factors. Various tumors of the GI tract have been shown to occur in patients with inherited mismatch repair deficiency. MSI is present in 10–20% of sporadic colorectal [186], gastric [186], and ampullary cancers [187]. Between 0.3 and 13% of pancreatic cancers are reported to have MSI as well [188] and recently a small proportion (5.9%) of biliary cancer have been identified to have a high mutational load [189]. Consequently, immune monitoring has become important for GI malignancies (Table 2).

Anti-viral responses as surrogate markers for an active immunotherapy

A number of GI cancer types are typical inflammation associated tumors. Almost 90% of all patients with hepatocellular carcinoma (HCC) also show an underlying liver disease. Chronic viral hepatitis (hepatitis B virus [HBV] and hepatitis C virus [HCV]) is a major risk factor for the development of liver cirrhosis and HCC. Immune checkpoint inhibitors are currently being evaluated in HCC patients with underlying chronic HBV and HCV infection. Interestingly, not only did tremelimumab show early signs of anti-tumor efficacy, but it also induced a decrease in HCV viral load from 3.78 x 10⁵ IU/ml at day 0 to 1.69 x 10³ IU/ml. In parallel, the investigators observed a general trend to increased number of virus-specific IFN-γ-producing lymphocytes post-treatment [38]. We have observed similar effects in HCC patients with chronic HBV or HCV infection [190]. In summary, anti-viral responses can be used to track the effect of those approaches aiming to enhance antigen-specific T cell immunity.

Liver toxicity

Immune-stimulatory mAbs are currently being evaluated as antitumor agents. Although overall toxicity from immunotherapy drugs such as anti-CTLA-4, anti-PD-L1/PD-1, and anti-CD40 appears to be moderate, liver toxicities have been reported and are not completely understood.

Transient dose-related elevations in serum liver transaminases and total bilirubin were observed after infusion of anti-CD40 [191]. It was thought that this effect was due to CD40+ hepatocytes, which underwent apoptosis upon CD40 activation. We have been able to show that agonistic CD40 antibody caused liver damage within 24 h after injection in a variety of different murine tumor models. Here, liver damage was induced by the generation of reactive oxygen species produced by intrahepatic myeloid cells, which accumulate in the liver of tumor-bearing individuals [192]. Therefore, liver toxicity may be mediated by anti-CD40 activated intrahepatic myeloid cells rather than a direct effect of anti-CD40 on hepatocytes [193]. Transient transaminitis has also been observed in patients with HCC treated with tremelimumab [38]. A remarkable rise in serum transaminases was observed after the first dose in more than half of the patients. However, it was not associated with a parallel decline in liver function and did not recur in the following treatment cycles.

This observation was unexpected since inflammatory hepatic adverse events (AE) related to anti-CTLA-4 were uncommon in clinical studies. Of any grade, these AE were reported in 3.8% (5/131) of patients treated with ipilimumab monotherapy at 3 mg/kg in a phase III trial [194]. Kleiner and Berman studied 5 patients in which a liver biopsy was taken to rule out drug-induced autoimmune hepatitis.

The histologic changes observed with ipilimumab-related hepatitis were similar to those with acute viral and autoimmune hepatitis and it was not possible to make a definite diagnosis of a drug-induced hepatitis. Hepatic inflammation in the five patients reported resolved with appropriate immuno-suppressive therapy, and the authors suggest that patients who receive immune checkpoint inhibitor therapy should be monitored at regular intervals for biochemical and pathological evidence of hepatitis so that appropriate treatment can be promptly administered [195].

Endoscopy

Patients undergoing immune checkpoint therapy could develop enterocolitis as an adverse event [195]. A common side effect in such instances is diarrhea, which warrants endoscopic procedures such as upper endoscopy and colonoscopy. It should be noted that these tests can also be used to obtain tumor biopsies and monitor progress during the course of treatment.

Characteristics of adoptively transferred cells associated with better clinical outcomes

The adoptive transfer of TIL for the treatment of patients with metastatic melanoma has produced promising clinical results. More favorable clinical results have been associated with greater in vivo persistence of infused TIL one month after therapy [196]. Characteristics of TIL that correlate with more favorable outcomes include longer telomeres and the administration of larger numbers of TIL, CD8+ cells, and CD8+CD27+ T cells [196, 197]. TIL that spend less time in culture, so-called “young” TIL, have a phenotype consistent with an earlier differentiation state including longer telomeres and higher levels of CD27 and CD28 expression [198–200] and these cells may be more effective clinically [197]. Analysis of TIL cells obtained from patients with metastatic melanoma has shown that reduced expression of the chemokine receptors CXCR3 and CCR5 and the presence of the CCR5-Δ32 polymorphisms, which encodes a protein that is not expressed, were associated with better response to TIL therapy [201].

Preclinical models have shown that the phenotype of adoptively transferred T cells can influence their effectiveness. Antigen-specific central memory T (T_CM) cells are more effective for adoptive T cell therapy than effector memory T cells; transferred T_CM survive longer in vivo [202]. Adoptively transferred memory T cells that have stem cell-like qualities, stem memory T cells (T_SCM), result in greater in vivo expansion, longer persistence and better anti-tumor activity [203, 204]. T_SCM are characterized as CD45RA+, CD62L+, CCR7+, and CD95+. Some investigators are developing methods to enrich adoptively transferred T cells with T_SCM or T_CM characteristics [205].

Clinical studies of adoptively transferred T cells engineered to express CAR have found that the in vivo expansion of these cells also been associated with favorable clinical outcomes [206]. When CD19 CAR T cells are used to treat children and young adults with acute lymphoblastic leukemia, the transferred T cells can expand several-fold. Peak expansion of CD19 CAR T cells occurred at 14 days post-infusion and the cells persisted up to two years [206, 207]. Peak expansion was associated with disappearance of circulating leukemic blasts in responding patients. Patients responding to the therapy had higher levels of circulating CD19 CAR T cells than those that did not respond [206].

Tumor-trafficking potential of adoptively infused T cells

The trafficking of effector T cells to tumor sites is a prerequisite for their antitumor activity. Tumor irradiation has been shown to shape a pro-inflammatory microenvironment that permits the extravasation of T cells and promotes their effector function [208].

CD19-targeted T cells may be more rapidly cleared from the circulation in the presence of a higher peripheral blood tumor burden, likely as a result of tumor infiltration and disappearance from the circulation [209]. However, in a patient with chronic lymphocytic leukemia who died 44 h after CAR T cell infusion, staining of autopsy tissues with anti-CAR antibodies showed rapid T cell trafficking to tumor sites, including lymph nodes, bone marrow, and liver [209]. Studies of autologous anti-LeY CAR immunotherapy in patients with acute myeloid leukemia have shown migration of the adoptively infused T cells to the bone marrow and the skin, as well as persistence for up to 10 months [210].

CAR T cells containing the CD28 endodomain may be endowed with enhanced expansion potential and persistence compared with CAR T cells lacking this endodomain [211]. The analysis of skin biopsies from a patient with non-Hodgkin lymphoma showed that 20% of the gated CD3+ lymphocytes co-expressed the CAR. This study clearly demonstrates that one of the incremental benefits of incorporating critical costimulatory components into CARs is the ability of T cells to infiltrate and mediate anti-tumor effects in tissues.

The tumor trafficking potential of activated T cells bearing a CAR specific for the tumor antigen GD2 can be enhanced by forced co-expression of the chemokine receptor CCR2b, which directs migration towards CCL2, a chemokine produced by several tumors. This strategy translated into improved homing (>10 fold) to CCL2-secreting neuroblastoma compared to CCR2-negative T cells, as well as greater in vivo anti-tumor activity [212]. Forced expression of CCR4 by effector T cells has been shown to enhance their migration to the Reed-Sternberg cells of Hodgkin lymphoma (HL) [213], which predominantly produce TARC/CCL17 and MDC/CCL22. Furthermore, T cells expressing both CCR4 and the HL-associated antigen CD30 manifested greater cytotoxic function and in vitro cytokine secretion, and mediated better tumor control in mice engrafted with human HL [213].

Monitoring the levels of adoptively transferred T cells

Monitoring the circulating levels of adoptively transferred TIL and lymphocytes engineered to express CAR or high affinity TCR is important for improving the effectiveness of these therapies. The survival of T cells can be monitored by labeling a fraction of the cells with radionuclides such as chromium-51 or indium-111, however radiolabeling requires dedicated space, highly trained staff, and it is not widely available. The intravascular persistence of T cell clones prepared from TIL can be measured by TCR-specific PCR [214]. T cell clone persistence can be monitored by amplification of the TCR beta-chain region gene and the relative expression of the TCRBV gene products can be determined using a panel of monoclonal antibodies and flow cytometry [215]. This method has been used to show that the degree of persistence in the peripheral blood of adoptively transferred T cell clones was associated with melanoma regression [215]. Another study found that the persistence for one month of adoptively transferred T cell clones prepared from TIL was associated with clinical responses [196]. While this technique has provided important insights, it is limited by the need to isolate and characterize clones. In addition, the quantitative ability of this assay is limited.

Monitoring the levels of CAR T cells in the peripheral blood is easier and has yielded important information. The percent of T cells expressing CARs can be measured using flow cytometry. If the scFV region of the monoclonal antibody used in the CAR is of mouse origin, then goat antibodies directed to mouse F(ab)2 can be used to quantitate CAR T cells. To detect CD19 CAR T cells by flow cytometry, anti-Fab antibody staining and labeled CD19 protein have been used [216]. Flow cytometry using anti-idiotype monoclonal antibody has been used to detect CD19 CAR T cells derived from CD19 mouse monoclonal antibody clone FMC63, [206, 217, 218]. CAR T cell expansion can also be detected by quantitative qPCR [219, 220].

Cytokine release following cell infusion

The rapid expansion of adoptively transferred CD19 CAR T cells and the disappearance of leukemic cells is associated with clinical toxicity due to cytokine storm [221]. Cytokine release syndrome (CRS) is a non-antigen specific toxicity that occurs as a result of high levels of activation of lymphocytes or myeloid cells. It is associated with elevated circulating levels of several cytokines including IL-6, IFN-γ, and TNF-α. Clinically, patients with CRS may experience fever, tachycardia, and hypotension. It can result in cardiac dysfunction, adult respiratory distress syndrome, renal failure, hepatic failure, or neurotoxicity [221]. It is more likely to occur in patients with higher tumor burdens and greater T cell expansion [207, 221]. IL-6 appears to play an important role in the pathogenesis of CRS and the anti-IL-6 receptor antibody, tocilizumab, is often an effective therapy. The clinical use of tocilizumab has also been explored in patients with acute lymphoblastic leukemia who develop CRS after blinatumomab immunotherapy [222].

CRP has been found to be an effective biomarker for CRS [221]. CRP is an acute phase reactant produced by the liver. Its production is largely dependent on IL-6. In patients with ALL treated with CAR T cells, CRP levels have been found to be associated with the IL-6 levels and CRS severity [206].