Emerging biomarkers for immunomodulatory cancer treatment of upper gastrointestinal, pancreatic and hepatic cancers

Accepted Manuscript Title: Emerging biomarkers for immunomodulatory cancer treatment of upper gastrointestinal, pancreatic and hepatic cancers Authors: Belinda Lee, Ryan Hutchinson, Hui-Li Wong, Jeanne Tie, Tracy Putoczki, Ben Tran, Peter Gibbs, Michael Christie PII: DOI: Reference:

S1044-579X(17)30123-2 https://doi.org/10.1016/j.semcancer.2017.12.009 YSCBI 1429

To appear in:

Seminars in Cancer Biology

Received date: Revised date: Accepted date:

30-6-2017 14-12-2017 15-12-2017

Please cite this article as: Lee Belinda, Hutchinson Ryan, Wong Hui-Li, Tie Jeanne, Putoczki Tracy, Tran Ben, Gibbs Peter, Christie Michael.Emerging biomarkers for immunomodulatory cancer treatment of upper gastrointestinal, pancreatic and hepatic cancers.Seminars in Cancer Biology https://doi.org/10.1016/j.semcancer.2017.12.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Emerging biomarkers for immunomodulatory cancer treatment of upper gastrointestinal, pancreatic and hepatic cancers Belinda Leea,b,f,g,§, Ryan Hutchinsona,e,§, Hui-Li Wonga,§, Jeanne Tiea,c,e, Tracy Putoczkif,g, Ben Trana,c, Peter Gibbsa,b, Michael Christiea,d,* a

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Systems Biology and Personalised Medicine Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia. b

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Department of Medical Oncology, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia. c

Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Victoria 3000, Australia. d

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Department of Pathology, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia. e

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Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia. f

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Inflammation Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia. g

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Department of Medical Biology, University of Melbourne, Parkville, Victoria 3010, Australia.

authors contributed equally to this work.

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*Corresponding author at: Anatomical Pathology Department, Royal Melbourne Hospital, Parkville, Victoria 3050, Australia. Tel. +61393428000. Fax +61393428666. Email: [email protected]

Abstract

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Carcinomas of the oesophagus, stomach, pancreas and liver are common and account for a disproportionately high number of cancer deaths. There is a need for new treatment options for patients with advanced disease. Immunomodulatory treatments including immune checkpoint blockade offer a promising new approach, with efficacy shown in other solid tumour types. However, only a small proportion of patients with carcinomas of the oesophagus, stomach, pancreas and liver have responded to single agent checkpoint inhibitors, and there is a need for markers that are predictive of response to guide treatment of individual patients. Predictive markers may include epidemiological factors such as ethnicity, the genomic status of the tumour, circulating markers, expression of immune checkpoint molecules, and other features

of the stromal/immune response at the site of the tumour. This review will focus on predictive biomarkers for immune checkpoint blockade in oesophageal, gastric, pancreatic and hepatocellular carcinomas, including the genomic context and immune landscape in which they occur. Pancreatic carcinomas are largely resistant to immune checkpoint inhibition in trials to date, therefore emerging immunomodulatory treatments in this tumour type are also reviewed.

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immunotherapy biomarkers hepatocellular pancreas gastric

Introduction Carcinomas of the oesophagus, stomach, pancreas and liver are common globally, and account for a disproportionately high number of cancer deaths [1]. For patients with advanced disease, treatment with conventional chemotherapy and radiotherapy does improve outcome; however, there is significant associated toxicity and prognosis remains very poor. Immunomodulatory therapies offer hope as new, relatively welltolerated treatment approaches for these patients.

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Immunomodulatory therapy for cancer involves alteration of the adaptive immune response in order to improve anti-tumour responses. The main strategy in current clinical use is antibody mediated blockade of immune checkpoints, primarily the cytotoxic T lymphocyte protein 4 (CTLA-4), programmed cell death protein-1 (PD-1) and programmed cell death protein-1 ligand (PD-L1) [2,3]. CTLA-4 is an inhibitory molecule present on T-cells, that is homologous to the CD28 receptor, and prevents the differentiation of naïve T-cells into an active state. By blocking CTLA-4, unrestricted T-cell activation occurs [4]. CTLA-4 is also expressed by numerous epithelial tumours [5]. In contrast, the ligand PD-L1 is expressed by lymphoid, (tumour) epithelial, endothelial and mesenchymal cells and promotes immune tolerance when it interacts with its receptor, PD-1, expressed on activated T-cells [6]. The blockade of the PD-1/PD-L1 interaction can thus boost anti-tumour immunity.

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Reagents in current clinical use include the anti-CTLA-4 antibodies ipilimumab and tremelimumab, anti-PD-1 antibodies nivolumab and pembrolizumab, and anti-PD-L1 antibodies atezolizumab and durvalumab. These agents have shown impressive efficacy in a range of solid tumours including melanoma, non-small cell lung carcinoma, renal cell carcinoma, urothelial cell carcinoma, and squamous cell carcinoma of the head and neck [2,3,7-10]; however many patients do not respond. To date, checkpoint inhibitors have generally been well tolerated; however some patients do suffer significant toxicities including colitis, hepatitis, dermatitis, hypophysitis and thyroiditis. Predictive markers of response have been sought to guide the best use of these agents for individual patients, with some success: established markers predictive of response to checkpoint inhibition include PD-L1 protein expression on tumour cells as shown by immunohistochemistry for pembrolizumab response in non-small cell lung cancer [7], and microsatellite instability (MSI) for pembrolizumab response in colorectal cancer and other solid tumour types [11,12]. The role for predictive markers of response to checkpoint inhibitors in clinical practice is evolving rapidly.

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For carcinomas of the oesophagus, stomach, pancreas and liver, initial trials of immunotherapy agents in unselected patients have reported modest response rates, suggesting the need for selection of recipients on the basis of individual characteristics of the tumour, immune response, and patient. This review will focus on predictive biomarkers for immune checkpoint blockade in upper gastrointestinal, pancreatic and hepatocellular carcinomas, and the immune landscape and genomic context in which they occur. Pancreatic carcinomas appear largely resistant to immune checkpoint inhibition in trials to date, therefore emerging immunomodulatory treatments in this tumour type are also reviewed.

Gastric and oesophageal carcinoma Carcinomas of the oesophagus and stomach, collectively referred to as oesophagogastric carcinomas (OGC), are major causes of cancer death globally, with combined approximately 1,274,600 new cases and 1,123,300 deaths annually attributed to these malignancies [1]. Most patients have late-stage disease at diagnosis, not amenable to surgery, and systemic chemotherapy is the mainstay of treatment for this group. Despite improvements in recent years, the prognosis for advanced OGC patients remains poor [13], and there is an urgent need for new treatments to improve outcomes.

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Classification and genomics of gastric and oesophageal carcinoma

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In common usage there are five subtypes of OGC based on anatomical location and histopathology; (i) oesophageal squamous carcinoma (OSCC) (ii) oesophageal adenocarcinoma (OAC) (iii) adenocarcinoma of the gastro-oesophageal junction (iv) gastric adenocarcinoma intestinal-type and (v) gastric adenocarcinoma diffuse-type [14]. The incidence of OAC has risen rapidly in many Western countries, attributed to increasing rates of obesity and gastro-oesophageal reflux disease [15], whereas rising smoking and alcohol consumption may account for the increasing incidence of OSCC in some Asian countries [16]. Intestinal-type gastric adenocarcinoma is strongly linked to Helicobacter pylori infection and chronic gastritis more generally [17], whereas risk factors for diffuse-type gastric adenocarcinoma are less well defined.

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Integrative genomics studies have reported distinct molecular subtypes of gastric and oesophageal cancer, with features relevant to the potential value of immunotherapy. Four distinct subtypes of gastric cancer were reported; (i) chromosomal instabilitytype (CIN) which is associated with the intestinal subtype of gastric cancer, frequent mutations in TP53 and amplification of receptor tyrosine kinases, (ii) Epstein-Barr virus (EBV)-infected with mutations in PIK3CA, DNA hyper-methylation, amplification of JAK2 and the immune checkpoint genes CD274 (PD-L1) and PDCD1LG2 (PD-L2), and extensive immune cell recruitment and signaling, (iii) a MSI subtype with silencing of MLH1 and deficient DNA mismatch repair (dMMR) causing an increased tumour mutation burden, and (iv) genome stable tumours which are associated with diffuse histology and impaired cell adhesion including CDH1 mutations [18]. Oesophageal squamous cell carcinomas fall into three groups: (i) OSCC1 linked to poor prognosis and resistance to chemo-radiotherapy, (ii) OSCC2 with an abundance of leucocyte infiltration, and relatively increased expression of BST-2 - a gene linked to dendritic cell activation and antigen presentation, and (iii) OSCC3 with PI3K pathway activating mutations. OSCCs more closely resembled squamous cell carcinomas from other sites than they resembled oesophageal adenocarcinoma. Oesophageal adenocarcinomas were more homogeneous, closely resembling CIN-type gastric adenocarcinoma [19,20]. Cancers of the gastrooesophageal junction had characteristics intermediate between gastric and oesophageal adenocarcinomas [19,20]. Despite our improved understanding of the molecular basis of gastric and oesophageal cancers, this has had little influence on clinical practice to date. With the notable exception of trastuzumab in HER2-amplified gastric or gastro-oesophageal carcinoma [21], trials of molecularly targeted agents have generally been underwhelming.

However, several features of OGC suggest immunotherapies might be effective. Major causes of oesophageal and gastric cancer include chronic inflammation: gastrooesophageal reflux associated oesophagitis, and Helicobacter pylori induced gastritis, respectively, and chronic inflammatory states are associated with an immunosuppressive environment [22]. Furthermore, both gastric and oesophageal cancers have a high overall mutation burden [23], and the EBV+ and MSI+ molecular subsets of gastric cancer are associated with an especially high mutation burden, increased immune cell infiltration, or PD-1 pathway activation [18].

The immune landscape of gastric and oesophageal carcinoma

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The immune contexture has been shown to be associated with prognosis in a range of tumour types including oesophageal and gastric cancers [24], however, our understanding of various components of the tumour micro-environment, their relative importance, and potential predictive value for immunotherapies remains limited.

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Tumour infiltrating lymphocytes The density of immune cell infiltration has been positively associated with improved prognosis in many tumour types, including oesophagogastric cancer, presumably reflecting the presence of an anti-tumour immune response. Of the four molecular subtypes of gastric cancer, the EBV-associated cohort has the highest density of immune cell infiltration [25], and accounts for most of those tumours classified as “gastric carcinoma with lymphoid stroma”, which have an undifferentiated appearance, very prominent lymphocytic infiltration in stroma and epithelium [14], and are associated with better prognosis compared to other gastric cancers [26]. The MSI subtype of gastric cancer with a high tumour-mutation burden is also associated with dense immune cell infiltrates and shown to be associated with improved clinical outcomes [25,27].

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There are now standardised guidelines for interpreting tumour infiltrating lymphocytes (TILs) in solid tumours including oesophagogastric cancer [28,29], although there have been limited studies that have assessed TILs on routine H&E sections of OGC, with most reporting that lymphocytic infiltrate has been associated with an improved prognosis [30-32]. Kang and colleagues modified the international TILs working group guidelines for breast cancer [33] and evaluated the prognostic utility of the spatial distribution of TILs (intratumoural (itTILS) or stromal (sTILS)) in EBV-associated gastric cancer, and reported that an increased density of sTILs was independently associated with a prolonged relapse free survival (RFS), whilst itTILs demonstrated no prognostic significance [30]. Giampieri et al. analysed sTILs and dMMR in advanced gastric cancer patients, confirming the association between high stromal lymphocytes and dMMR, but furthermore showed in a multivariable analysis that both sTILs and dMMR were independently associated with better clinical outcome [32]. Jiang and colleagues investigated TILs in OSCC using modified guidelines similar to those reported by Kang, and found in univariate analyses that >20% itTILs and >10% sTILs were both associated with better overall survival (OS), with only sTILs remaining an independent prognostic factor after multivariable analysis, and with a stronger association seen in Stage III-IV [31]. Immune cell and immune checkpoint molecules Following the seminal work carried out by Galon et al. in colorectal carcinoma, [34], focus has shifted from the characterisation of immune cells on H&E sections as described by Virchow in 1863, to immune-phenotyping the tumour microenvironment

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using immunohistochemistry and immune cell specific antibodies. There are a myriad of immune-cell markers which have been associated with prognosis in OGC, singly and in combination, reviewed by Solinas et al. [35], with markers of good prognosis including CD3 [36], CD8 [36], CD45RO [36], CD20 [37], and CD68 [38], and poor prognosis markers including FOXP3 [38], CD66 [38], CTLA-4 [39], PD-L1 [39-41] and PD-L2 [41]. PD-L1 expression was also positively correlated with density of CD8+ lymphocytes [40]. Controversy remains as to the prognostic role of the immunosuppressive regulatory T-cell marker FOXP3 in gastric cancer, with studies reporting high expression as a marker of good prognosis [42,43] and others having found high expression to be associated with a poor prognosis [38,44]. Schlößer and colleagues reported that the expression of PD-L1 and CTLA-4 were associated with an inferior overall survival; however, there was no association with somatic mutations or MSI [39]. Elevated indoleamine 2, 3-dioxygenase (IDO) expression has been reported as a marker of poor prognosis in both OSCC [45] and gastric cancer [46]. IDO has been shown to suppress T-cell function and proliferation by inducing a tryptophan depleted microenvironment, and the production of toxic metabolites [47]. Several studies have reported the prognostic significance of an effector to regulatory phenotype in gastric cancer, namely through the ratio of CD8 to FOXP3 [48]. Interestingly, through the use of quantitative image analysis investigators have shown that the proximity of CD8+ and FOXP3 cells between 30 and 110 um is a prognostic marker in gastric cancer [49].

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Emerging biomarkers predicting response to immune checkpoint inhibitors in gastric and oesophageal carcinoma

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What has been readily apparent from the era of targeted therapy clinical trials is that selecting the correct patient population is crucial, although the optimal biomarkers for immunotherapy eligibility in oesophagogastric cancer remain elusive (Table 1).

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Ethnicity Akin to the difference in EGFR mutation rates between Asian and Caucasian lung cancer populations [50], the immune landscape has been reported to be markedly different between Asian and non-Asian patients with gastric cancer: non-Asian gastric cancers have higher expression of T-cell markers CD3, CD8, and CD45RO, and lower expression of FOXP3 by immunohistochemistry, and enriched CTLA-4 signaling on gene-expression analysis [51], suggesting a possible differential response to immunotherapies.

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PD-L1 immunohistochemistry PD-L1 expression as assessed by immunohistochemistry is one of the most promising predictive biomarkers for response to PD-1 inhibition. PD-L1 expression is reported in tumour cells in 12%, and immune cells in 44% of OGC overall [40], with higher rates of tumour cell staining reported in EBV+, and MSI+ gastric adenocarcinomas [52]. It is currently unclear whether staining of PD-L1 on tumour cells, immune cells, or some combination of the two, is most valuable in predicting response to PD-1 inhibition in OGC. PD-L1 staining of >50% tumour cells is currently used to identify non-small cell lung cancer patients who are eligible for pembrolizumab as first line treatment [7]. The KEYNOTE-012 phase 1b trial assessed pembrolizumab in advanced OGC patients who were considered PD-L1 positive by immunohistochemistry, defined as membrane staining in at least 1% of tumour cells or the presence of a distinct interface pattern of staining in immune cells, with 40% of screened cancers meeting the definition of PD-L1 positivity. The toxicity profile was

reported to be manageable with 13% grade 3-4 treatment related adverse events, and encouragingly, 22% of patients had an overall response [53]. There was no association between tumour cell PD-L1 expression level and response, although PDL1 negative tumours were excluded from the study, precluding the possibility of comparing response between PD-L1 positive and PD-L1 negative tumours. The predictive value of PD-L1 expression in OGC, as with other cancer types, is yet to be fully defined. The use of different primary antibodies, different scoring methods, and intra-tumour and temporal heterogeneity confound assessment, and further analyses of large randomized trials are required.

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Mismatch repair deficiency and microsatellite instability dMMR / MSI is a marker of response to pembrolizumab across solid tumour types [11], and is reported in approximately 20% of gastric cancers [18,32]. Deficient mismatch repair leads to increased mutations and neo-antigens in tumour cells, increased immune cell infiltration [32], and in colorectal cancer has been associated with increased expression of immune checkpoint molecules including PD-1, PD-L1, CTLA-4, LAG-3 and IDO [54], all of which point to greater sensitivity to immune checkpoint inhibition. In the KEYNOTE-012 trial, there were four gastric cancer patients with MSI, two of which responded to pembrolizumab [53]. Clearly the MSI+ subtype of gastric cancer should be considered a prime target for investigation of immune checkpoint inhibitors.

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Epstein-Barr virus EBV+ gastric cancers account for approximately 9% of cases [18], and have features suggesting they may respond well to immunomodulatory treatments. These tumours are associated with amplification and overexpression of PD-L1 and PD-L2 [18,52], and the highest density of immune cell infiltration [25]. Unfortunately EBV status was not assessed in KEYNOTE-012 [53].

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Tumour infiltrating lymphocytes Immune cell density has prognostic value in OGC [25,26,30-32], and may also have predictive value for immunotherapies. In the KEYNOTE-012 trial the density of mononuclear inflammatory cells in gastric cancer was scored 0-4. No patients received a score of 4; however, there appeared to be more responses to pembrolizumab in those patients with a score of 3 (4/9, 44%) compared to scores 0-2 (4/26, 15%), although these numbers are too small to be definitive [53].

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Gene expression signatures In KEYNOTE-012 the investigators also assessed expression of a panel of six genes linked to interferon-gamma, with increased expression in gastric cancers showing a trend towards improved response to pembrolizumab, however results were not statistically significant [53]. Gene expression panels appear to be a promising approach to predict response to immunotherapies. There are many ongoing clinical trials of immunomodulatory agents in oesophageal and gastric cancer, including combination studies with other immunotherapy agents, targeted therapies, and cytotoxic chemotherapy, and in the adjuvant setting, reviewed by Kelly [55]. Improved patient selection and stratification by integrative pathology, utilising epidemiological factors, tumour morphology, molecular subtype and immune landscape prior to, or after trial enrolment, will be integral to the success of immunotherapies in OGC. In particular, EBV+ and MSI+ gastric cancers appear to be

highly immunogenic, and are promising targets for checkpoint inhibitors. The predictive value of PD-L1 immunohistochemistry and other features of the immune landscape are the subject of ongoing investigation.

Pancreatic carcinoma

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Outcomes for pancreatic ductal adenocarcinoma (PDAC) have remained stagnant for the last 40 years, with five-year survival statistics remaining at <10% [56,57]. The common use of gemcitabine, 5-fluorouracil, nab-paclitaxel and platinum-based combination chemotherapies, have only led to small incremental improvements in survival by <6 months [58,59]. These gains are likely to be driven by responses in subsets of patients, who cannot currently be identified beforehand with standard molecular makers.

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There remain no reliable prognostic or predictive markers in pancreatic cancer that could help inform treatment decisions, whether for conventional cytotoxics, targeted agents or immunotherapies [60], with the possible exception of MSI status [11]. The results so far for immunotherapies in unselected populations of chemo-refractory pancreatic cancer have been disappointing [61,62]. Future studies of pancreatic cancer need to be more selective by identifying and utilizing biomarkers that characterize patients who may benefit most from a particular novel therapy.

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Understanding the immune response, tumour microenvironment and their interplay with the genomic profile of tumours will drive the identification of biomarkers that will be key to deciphering the optimal immunomodulatory therapies for individual PDAC patients.

Genomics of pancreatic carcinoma

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Large-scale genomic initiatives have mapped the mutational landscape of pancreatic cancer, identifying recurrent genetic damage in >40 genes from 10 core molecular pathways that drive pancreatic cancer [63-65]. The KRAS oncogene is the most frequently mutated gene occurring in >90% of PDAC. Additional somatic alterations commonly present in PDAC include p16/CDKN2A (>95%), BRCA2 (10-14%), TP53 (75%), and TGF-beta pathway components SMAD4 (55%), TGFBR1 and TGFBR2 (<5%). Structural rearrangements disrupting tumour suppressor genes are common, and focal amplifications of oncogenes including ERRB2 and MET are seen occasionally. Inactivation of BRCA1, BRCA2, PALB2, and/or a BRCA-mutational signature are found in a subset of tumours, and may predict response to platinumbased chemotherapy [65]. Integrated genomic analysis identified 4 subtypes of PDAC: (i) squamous-like, (ii) pancreatic progenitor, (iii) immunogenic, and (iv) aberrantly differentiated endocrine exocrine [66]. Notably, the immunogenic subtype showed up-regulated gene expression profiles for CD8+ cytotoxic T-cells, FOXP3+ regulatory T-cells, and B-cells, as well as PD-1 and CTLA-4 signalling pathways. Homologous recombination deficiency and DNA-damaging agent responsiveness Defects in components of the homologous recombination (HR) pathway, such as BRCA1/2 represent potential predictive markers for treatment response. Superior disease control with platinum-based chemotherapies was demonstrated in PDAC patients harbouring germline BRCA1/2 mutations [67-69]. Similarly, results from early phase clinical trials investigating the role of PARP inhibitors (namely olaparib,

veliparib (ABT-888) and rucaparib) in PDAC confirm that knowledge of germline and somatic molecular characteristics of a cancer could help to identify exceptional responders and tailor treatment more effectively [70,71]. Links between HR deficiency, the immune landscape and immunotherapies remain to be explored.

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Microsatellite instability and DNA mutational burden The rate of dMMR / MSI in PDAC is somewhat unclear. Several studies have reported frequencies <5% [72,73], whereas two studies from Japan reported MSI in 13-17% of PDAC patients [74,75]. While outcomes from immunotherapy trials in PDAC have generally been disappointing, results from the pivotal KEYNOTE studies investigating pembrolizumab in the treatment of solid tumours exhibiting dMMR or MSI has led to the accelerated approval of pembrolizumab for this indication, demonstrating 83% objective response rate (ORR) in the six evaluable pancreatic cancer patients [11]. Overall, there was a 39.6% ORR (95% CI, 31.7-47.9) and durable responses of >6 months in 78% of all treated patients. These results indicate that dMMR / MSI predicts for benefit from anti-PD-1/ PD-L1 blockade in PDAC.

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Mutational load and neoantigens Along a similar vein to dMMR / MSI, cancers with higher mutational loads overall are reported to carry more neoantigens presented on HLA molecules [76,77], which are associated with greater infiltration of cytotoxic T-cells into the tumour [78]. High mutational load also appears to correlate with response to checkpoint inhibitors in advanced melanoma and a number of solid tumours, and this appears to be independent of the expression of T-cell activation markers and PD-L1 expression [12,76,77,79]. In PDAC, a relatively low average mutational load has been observed [23,66]. Surprisingly, in contrast to the findings in melanoma and other cancers, a high mutational load in PDAC appears to negatively correlate with T-cell activity, and a significantly better overall survival (OS) (p<0.05) was reported in PDAC patients with fewer mutations [80]. Balachandran et al. reported that the ‘quality’ of neoantigens produced by a tumour may influence immunogenicity in PDAC [81]. They found that long-term survivors (>5 years) with PDAC were enriched in neoantigens with homology to infectious diseases derived proteins, and proposed that this microbial homology was a surrogate marker of antigen non-selfness, and therefore immunogenicity. Neoantigens in MUC16 (CA125) were also overrepresented in long term survivors, suggesting that this protein may be a ‘hot-spot’ for immunogenic neoantigens. Thus neoantigen quality may be more important that quantity for tumour immunogenicity in PDAC.

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KRAS KRAS was one of the first molecular markers to be assessed in PDAC, found in >90% of cases [64]. Oncogenic KRAS mutations are found in most early pancreatic intraepithelial neoplasia (PanIN) lesions, and are presumably responsible for PDAC initiation [82]. Amongst its many consequences, KRAS activation induces IL8 and GM-CSF production which up-regulate inflammation pathways that promote tumour proliferation and angiogenesis [83,84] suggesting that KRAS status might influence response to immunotherapies for PDAC. Despite these advancements in our understanding of PDAC genomics, little headway has been made in improving outcomes. New treatment strategies that look beyond individual mutations and integrate genomic, immune, and other microenvironmental factors need to be explored.

Microenvironment and immune infiltrates in pancreatic carcinoma

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Desmoplastic stroma A characteristic feature of most PDACs is a dense desmoplastic stroma around the tumour cells, which prevents effective delivery of chemotherapy [85-87] and perhaps immune cell migration, and furthermore actively supports tumourigenesis by contributing to invasion, metastasis, and the development of an immunosuppressive, hypoxic and anti-angiogenic tumour microenvironment [88-93]. Hyaluronan has been identified as a key component of the stroma and a novel therapeutic target in PDAC. Reduction in hyaluronan reduces the compactness of the stroma, induces re-expansion of PDAC blood vessels and thereby increases intra-tumoural drug delivery. The phase 2 HALO-202 study investigated PEGPH20, a pegylated form of recombinant human hyaluronidase PH20, reported improved median progression-free survival (PFS) outcomes, 6 months versus 5.3 months (HR 0.73, p=0.048) in the PDAC patients receiving PEGPH20 with gemcitabine and nab-paclitaxel versus gemcitabine and nabpaclitaxel alone [94]. In the secondary endpoint analysis of patients with high levels of hyaluronan, the median PFS increased to 9.2 months from 5.2 months (HR 0.51, p=0.048), in favour of combination PEGPH20 and chemotherapy. Hyaluronan-high status is a potential predictive biomarker of benefit of PEGPH20 in PDAC [94]. The combination of hyaluronidase with immunotherapies is currently under investigation [95].

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Tumour infiltrating lymphocytes There are few published studies examining TILs in PDAC on H&E sections. The presence of intra-tumoural tertiary lymphoid organs (lymphoid follicles), as judged by pathologists, was associated with longer OS and DFS [96]. Hart et al. scored intratumoural lymphocytes as high or low in 63 patients, but found no survival difference [97].

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Immune cell and immune checkpoint molecules Several studies have investigated immunohistochemical markers singly or in combination, and their associations with prognosis in pancreatic adenocarcinoma. Immunohistochemical markers associated with a worse prognosis include FOXP3, CD68, CD163, CD204, and CD66b [98,99]; markers associated with an improved prognosis include CD3, CD8, CD4, CD20 [99-101]. High CD4+/CD8+ tumour infiltrating lymphocytes following PDAC resection is an independent favourable prognostic factor for overall survival (p=0.0098) [100]. High levels of circulating immunosuppressive myeloid-derived suppressor cells (MDSC) and CD4+CD25+ CD127low FOXP3+ regulatory T-cells (Tregs) have been identified in PDAC patients. High MDSC numbers appears to correlate with high Treg levels and is associated with a poor OS [102].

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Emerging data suggests that neoadjuvant therapy may selectively modulate immunosuppressive cells. In a retrospective analysis, significantly lower numbers of Tregs were identified in resected PDAC specimens following neoadjuvant therapy compared with resected tumour specimens from untreated patients [103]. There was no difference in the total CD4+ T-cells or the total T-cells identified, but the CD8+:FOXP3+ ratio was higher in the treated group. It was hypothesized that these observations could be due to direct anti-tumour effects of therapy and resultant adaption of the immune infiltrate, or that the neoadjuvant therapy triggered the

immune activation. Whether this activation could be harnessed by subsequent or concurrent administration of immunotherapies is being explored. PD-1 / PD-L1 PDAC has been largely refractory to single agent checkpoint inhibition [61,62], which may be reliant on the expansion of activated, intra-tumoural, tumour-specific cytotoxic CD8+ T-cells, which is limited in most PDAC. Investigation of checkpoint inhibitor molecules as biomarkers in PDAC has therefore mostly focused on prognosis.

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PD-L1 overexpression is associated with worse prognosis in a range of solid tumours [104], including PDAC [105-107]. Birnbaum and colleagues reported that the “PDL1-up” group demonstrated T-cell exhaustion and up-regulation of CTLA4 and enzyme indoleamine 2,3-dioxygenase-1, molecules that attenuate T-cell immune responses. Up-regulation of interleukin-10 (IL10) and an increased prevalence of immunosuppressive Tregs was also noted in the “PD-L1-up” group, correlating a higher PD-L1 expression in PDAC with a suppressed anti-tumour response [105].

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PD-L1 expression has been evaluated as a predictive biomarker for response to PD-1 pathway inhibitors in a range of tumour types. Most studies are in agreement that higher levels of tumour cell membrane PD-L1 expression correlate with better outcomes with PD-1/PD-L1 blockade [108,109]; however, the relative lack of response to checkpoint inhibitors in PDAC trials reported to date precludes assessment of PD-L1 protein expression as a predictive marker in this tumour type.

Emerging immune modulating strategies in pancreatic carcinoma

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Pancreatic cancers are typically categorized as “cold” tumours lacking both T-cell infiltration and an inflammatory gene signature, which may explain the lack of response to checkpoint inhibitors. To overcome this problem, clinical studies are starting to investigate whether employing additional therapeutic agents in combination with immunotherapies could promote T-cell migration and activation, and this may lead to the development of novel biomarkers for these combination treatments (Table 2).

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CTLA-4 Loos et al. reported increased CTLA-4 levels in PDAC, but found no association with survival [107]. Emerging evidence suggests that chemotherapeutic agents including 5FU, gemcitabine and nab-paclitaxel may have an immune-stimulatory effect [110,111], and that combinations with checkpoint inhibitors may be effective. The combination of CTLA-4 inhibitor ipilimumab with gemcitabine was investigated in a phase 1b study for advanced PDAC (NCT01473940), and reported a partial response in 2 out of 16 patients and stable disease in 5. Patients achieved a median PFS and OS of 2.5 months and 8.5 months respectively [112]. CXC chemokines & CCR2 CXC chemokines are involved in fibroblast migration and recruiting neutrophil and myeloid cell progenitors. Elevated levels of CXCL12 (CXC motif chemokine ligand 12) are commonly found in PDAC, and are partly responsible for stimulating the dense stroma that restricts immune cell migration and the efficacy of chemotherapy and PD-1 blocking antibodies [113]. Inhibition of the CXCL12 interaction with its

receptor CXCR4, restored T-cell function and improved efficacy of anti-PD-L1 immunotherapy in pre-clinical PDAC models [114].

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Preclinical mouse models have demonstrated various strategies of altering immune dynamics in tumours, including antagonizing the CCL2/CCR2 pathway or neutralizing antibodies to block macrophage colony stimulating factor. These strategies inhibit tumour infiltrating macrophages, relieve local immunosuppression thus leading to greater chemotherapy and radiotherapy efficacy [115,116]. Promising early phase clinical trial results report CCR2 inhibition significantly suppresses metastases and improves chemotherapy and immunotherapy efficacy in PDAC [117]. In a phase 1b trial of CCX872-B, a potent, selective oral inhibitor of CCR2, in combination with FOLFIRINOX, 78% tumour control rate at 12 weeks and 57% PFS at 24 weeks was reported in metastatic PDAC patients. This study is ongoing [118] (NCT02345408).

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CD40 CD40 is a member of the tumour necrosis factor (TNF) receptor superfamily. It is expressed by antigen presenting cells such as dendritic cells, B-cells and monocytes, endothelium, platelets and certain tumour cells. CD40 agonists can reverse functional T-cell paralysis in lymphoid structures adjacent to the tumour, thereby restoring Tcell immunosurveillance. CD40 agonists may also have a direct cytotoxic effect on CD40+ tumours as well as induce anti-tumour T-cell responses and activation of macrophages against the tumour and tumour stroma [119]. Results from the phase 1 trial of CP870-893, a selective CD40 agonist, reported synergistic action with gemcitabine on PDAC tumour growth, with partial responses in 4 out of 21 patients, stable disease in 11 patients and a median OS of 7.4 months [120]. Clinical trials investigating several CD40 agonists are underway (Table 2).

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OX40 Preclinical studies report that OX40 co-stimulation induces effector T-cell expansion, activating TILs and overriding Treg suppression, resulting in improved OS in animal models [121]. The co-stimulatory OX40 (CD134) molecule thus offers a nonredundant alternative pathway to increase anti-tumour immunity. This strategy is being evaluated with MEDI0562, an OX40 agonist, in combination with tremelimumab (anti-CTLA4 antibody) or durvalumab (anti-PD-L1 antibody) in advanced solid tumours [122] [NCT02705482] (Table 2).

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IL10 IL10 stimulates intra-tumoural CD8+T-cell expansion and survival [123]. Early phase clinical trial results report durable stable disease and 1 year OS of 22.5% in advanced PDAC patients receiving pegylated IL10 (AM0010) alone. When combined with FOLFOX chemotherapy, in a phase 1b clinical trial, 15.8% ORR was observed in 21 patients, with 2 patients remaining on treatment for >1 year. With a median follow up of 11 months, the median PFS was 3.5 months and median OS 10.0 months. This regimen is being studied in a phase 3 clinical trial [NCT02009449] (Table 2). IDO Indoleamine 2,3-dioxygenase (IDO) degrades tryptophan to kynurenine, which encourages immunosuppression, and is overexpressed in many cancers. Preclinical studies demonstrate that inhibition of IDO1 restores T-cell proliferation and increases dendritic cell numbers whilst lowering levels of immunosuppressive metabolite

kynurenine [124]. To date two selective IDO1 inhibitors have been evaluated in early phase trials – epacadostat (INCB024360) and BMS-986205. Both IDO inhibitors appear to be well tolerated and have been taken forward into phase 2 clinical trials that are underway (NCT01195311) (NCT02658890).

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TIM-3 T-cell immunoglobulin and mucin-domain-containing molecule-3 (TIM-3) is a transmembrane protein that acts as an immune inhibitory receptor responsible for regulating Th1 lymphocytes. A study examining the prevalence of TIM-3 gene polymorphisms in a Chinese population reported that TIM-3 polymorphisms appear to be genetic biomarkers for increased susceptibility to pancreatic cancer [125]. Upregulation of TIM-3 has been identified in PD-1 resistant tumours, suggesting that it may mediate acquired resistance to anti-PD-1 antibody therapy [126]. The selective expression of TIM-3 on intra-tumoural T-cells makes it an ideal therapeutic target which could potentially have less non-specific toxicities. Combined anti-TIM-3 and anti-PD-1 antibody therapy has been shown to act synergistically to control tumour proliferation [127]. Phase 1 and 2 clinical trials investigating both anti-TIM-3 antibody monotherapy (MBG453) and combination therapy with anti-PD-1 antibody therapy (PDR001) in advanced malignancies are ongoing [NCT02608268].

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CSF-1 Tumour associated macrophages in PDAC contribute to the immunosuppressive environment, tumour cell proliferation, and metastasis [128]. Tumour-associated macrophages are activated by colony stimulating factor 1 (CSF-1) binding to its receptor CSF-1R, and blocking this interaction is an appealing approach. Zhu et al. reported that CSF-1R blockade enhanced the efficacy of PD-1 and CTLA-4 blockade in a mouse model of PDAC [128], and clinical trials of CSF-1R inhibition and pembrolizumab are underway in PDAC (Table 2).

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Vaccines & adoptive T-cell transfer strategies Several novel vaccine therapies are being trialed against PDAC, exploiting tertiary lymphoid aggregates found in tumour tissue to induce T-cell responses and overcome the innate immune-resistance observed in PDAC. An example of this approach with a dendritic cell vaccine in combination with nivolumab, has demonstrated partial responses in 2 out of 7 PDAC patients treated in the phase 1 trial setting [129]. Another example is the use of neoadjuvant / adjuvant GM-CSF secreting allogeneic pancreatic cancer vaccine (CY/GVAX) with or without nivolumab in resectable pancreatic cancer which is currently being investigated in phase 1 & 2 trials. These studies will utilize IL17 expression in the tumour microenvironment as a biomarker for vaccine induced anti-tumour response (NCT02451982) (Table 2).

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Adoptively transferred chimeric antigen receptor (CAR) T-cells that have been engineered in vitro to recognize mesothelin expressed on the autologous PDAC tumour cell surface are also being investigated. Clinical benefit with this approach to date has been limited but studies are still ongoing (NCT02632019). Pancreatic carcinoma presents a formidable challenge. Its unique microenvironment appears to underpin the lack of response to single agent checkpoint inhibition (with the notable of exception of dMMR/MSI tumours), and new strategies are being investigated. The emerging immunomodulatory treatments for PDAC described here

all present opportunities for biomarker development, which may assist in personalization of treatment for PDAC patients in the future.

Hepatocellular carcinoma

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Hepatocellular carcinoma (HCC) is the fifth most common cancer in men, and the ninth in women worldwide, and is the second leading cause of cancer-related deaths [1]. Over 80% of cases occur in sub-Saharan Africa and eastern Asia, with incidence largely correlated to rates of hepatitis B and C virus infections. Other important causative factors include alcoholic and non-alcoholic steatohepatitis [130]. HCC has one of the highest mortality-to-incidence ratios and lowest 5-year overall survival rates among all cancers [131]. Major factors contributing to the poor prognosis are advanced stage at diagnosis and the lack of effective systemic treatment options. Further, the underlying cause and severity of liver dysfunction are key considerations underlying both prognosis and treatment.

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As in other malignancies, there has been significant interest in exploring the use of anti-cancer immunomodulatory therapies in HCC. One of the first immune checkpoint inhibitors to be investigated was the anti-CTLA-4 antibody, tremelimumab. In a phase II study of 20 patients with advanced HCC and chronic HCV infection, 43% of whom had some degree of liver dysfunction (Child-Pugh stage B7), tumour responses were observed in 18% and most patients had an anti-viral response [132]. Importantly, none of the patients experienced worsening liver function.

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The safety and efficacy of nivolumab, a PD-1 inhibitor, was investigated in the phase I/II CheckMate 040 study, where results from the monotherapy dose escalation (N=48) and expansion (N=214) cohorts were recently published [133]. This was a global study in which 45% of patients were Asian, 48% had viral hepatitis and 69% were previously treated with sorafenib. In the dose expansion cohort, objective responses were observed in 20% of patients regardless of HCC etiology or prior sorafenib treatment. Tumour responses were early (within 3 months of commencing treatment) and appeared to be durable (median duration of response 8.5-10 months), and while OS data are not yet mature, the 9-month OS rates of 63-82% are certainly encouraging.

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Ongoing studies will further define the role of immunomodulatory therapies in HCC. CheckMate 459 (NCT02576509), a phase III randomised trial comparing nivolumab to sorafenib for first-line treatment of advanced HCC, has recently completed accrual and results are eagerly awaited. The safety of combination therapies has been demonstrated, with the combination of dual checkpoint inhibition [134] and tremelimumab with ablation [135] showing no unexpected safety signals, and other combination strategies continue to be pursued.

Genomic and immune landscape of hepatocellular carcinoma The pathogenesis of HCC involves a complex interplay between genetic and environmental factors that in most cases includes the development of chronic inflammation and cirrhosis. The immunological landscape of HCC has been extensively described, and we recommend the excellent review by Prieto et al. [136]. In brief, chronic inflammation in HCC includes a strong element of immune inhibition through a combination of anti-inflammatory and immunosuppressive

cytokines, regulatory T-cells, as well as growth factors that support a wound healinglike environment by stimulating cell proliferation, angiogenesis and stroma formation. Coupled with permanent exposure to tumour-associated antigens (TAAs), this results in T-cell exhaustion and immune tolerance. Indeed, despite the detection of TAAspecific CD8+ T-cell responses in the peripheral blood of over 50% of HCC patients in one series, in vitro experiments suggested that these TAA-specific T-cells were functionally impaired [137].

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The genomic landscape of HCC has been characterized by whole exome sequencing efforts, where an early oncogenic event is up-regulation of TERT, which prolongs cell survival by increasing telomerase activity [138,139]. Other frequently altered oncogenic pathways are the canonical WNT signaling and cell cycle pathways, with CTNNB1 and TP53 mutations present in 25-30% of HCCs (reviewed by ZucmanRossi et al. [140]). HCCs, like most other gastrointestinal tumours, have a modest mutation burden, with 35 to 80 nonsynonymous somatic mutations per tumour [23,141].

Emerging biomarkers for immunomodulatory therapies of hepatocellular carcinoma

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Immune cell and immune checkpoint molecules The rationale for using immunomodulatory therapies in HCC was supported by clinical observations of spontaneous regressions in HCC, which have been partly attributed to the host immune response [142,143]. Further, the presence of lymphocytic infiltration in tumour specimens by morphologic examination was associated with lower relapse rates after surgical resection [144], lending further evidence to the importance of the host immune response in tumour control. Immunohistochemical markers further define the role of lymphocyte subpopulations, with high densities of total CD3+ and cytotoxic CD8+ T-cells associated with improved outcomes after resection [145]. Conversely, tumour infiltration with FOXP3+ regulatory T-cells is associated with worse prognosis, particularly in combination with a low proportion of granzyme-B positive activated cytotoxic T-cells [146]. More recently, tumour infiltrating B-cells have also been associated with improved survival, suggesting important functional interactions between B- and Tcells in local tumour control [147].

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The immunosuppressive environment of HCC is contributed to, at least in part, by the up-regulation of immune checkpoint molecules, such as CTLA-4, PD-1, TIM-3, LAG-3 and BTLA. Overexpression of the PD-1 ligands, PD-L1 and PD-L2, has been associated with worse survival in patients with resected HCC [148,149]. High PD-L1 expression in tumour and peri-tumoural inflammatory cells has also been related to aggressive phenotypic features, such as vascular invasion and poor differentiation [150]. PD-L1 expression continues to be investigated as a predictive biomarker for anti-PD-1/PD-L1 antibodies but its clinical utility in HCC remains limited due to technical challenges and biological variation [151]. In the CheckMate 040 study described above, PD-L1 positivity was defined as membrane expression in at least 1% of tumour cells, and was not predictive for response to nivolumab; objective responses were observed in 26% and 19% of patients with PD-L1 positive and negative tumours, respectively [133].

Mismatch repair deficiency / microsatellite instability dMMR / MSI is emerging as one of the most useful biomarkers predicting for benefit to anti-PD-1 pathway antibodies for all solid tumours [11]. The role of dMMR in HCC carcinogenesis and progression remains uncertain. While MSI has been reported in 16-18% of HCCs [152,153], and MSI tumours arising from non-cirrhotic livers have been associated with aggressive tumour features and shorter time to recurrence [152], other studies have failed to identify any HCC cases with MSI [154]. Further, there were no HCC cases among the 149 dMMR or MSI cancers in the KEYNOTE studies upon which pembrolizumab was approved [11].

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Gene expression signatures Other genomic-driven approaches to defining biomarkers of immunotherapy response continue to be investigated in HCC. For example, gene expression signatures reflecting anti-tumour immunity, e.g. overexpression of genes involved in cytotoxic T lymphocyte activation and interferon-gamma pathways, have been reported in melanoma and non-small cell lung cancer, and may correlate with immunotherapy treatment outcomes [155]. In HCC, gene expression profiling of resected tumours have revealed molecular subtypes that correlate with clinicopathologic features and outcomes [140]; however, these have not yet been prospectively validated.

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Neutrophil to lymphocyte ratio There is considerable interest in exploring the role of circulating biomarkers that may predict for response to immunomodulatory treatments [156]. A high neutrophil to lymphocyte ratio (NLR) is thought to reflect systemic inflammation and has been shown to be associated with worse survival in HCC [157] and other cancers [158]. NLR has also been associated with outcomes among patients treated with immunotherapy [159,160] although it is uncertain if this is related to the prognostic, rather than a predictive, impact of NLR.

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The role of immunomodulatory therapies in HCC is likely to expand in the near future, with promising efficacy and safety results reported so far. The major role of immune tolerance in the pathogenesis of HCC supports an immune-based treatment approach, and other strategies under investigation include cell-based therapies [161,162] and oncolytic viruses (NCT02562755). Defining predictive biomarkers for these immune-based therapies continues to be an important challenge (Table 3).

Conclusion

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For cancers of the oesophagus, stomach, pancreas and liver, response rates to monotherapy with checkpoint inhibitors in unselected patients have been modest to date, suggesting that combination therapies and predictive biomarkers will be required. Three main features appear promising across multiple tumour types, when considering response to checkpoint inhibitors: dMMR/MSI status, PD-L1 protein expression on tumour cells, and T-cell infiltration. Of these, dMMR testing offers an immediate marker to identify the subset of oesophagogastric, pancreatic and hepatocellular carcinoma patients who are more likely to respond to pembrolizumab. PD-L1 immunohistochemistry is a promising biomarker for response to PD-1/PD-L1 inhibitors in carcinomas of the gastrointestinal tract, and indeed for all tumour types, notwithstanding the known difficulties in methods and interpretation. Assessment of

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TILs has already shown prognostic value in multiple tumour types, highlighting their importance to the anti-tumour immune response, and further studies may show predictive value. A standardized method for the assessment of TILs in solid tumours was recently published [28,29]. These three predictive markers; dMMR/MSI status, PD-L1 protein expression, and TILs, appear to suggest one alternative way forward for anti-cancer therapy biomarker development: rather than each therapeutic agent having its own companion diagnostic test, these markers reflect underlying biology, relevant to broad groups of treatments, and across tumour types. This integrative approach to biomarkers may be prescient, given the large number of new immunotherapies currently on the horizon.

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The highest priority biomarkers for immunotherapies remain the key molecular targets, with the clearest underlying biological rationale for success. However, the complexity of tumour and immune system interactions suggests that future predictive assays for immunotherapies will be more complicated than the single oncogene tests that have accounted for the majority of companion tests to date. Tissue based assays will likely assess multiple markers in combination, taking different tissue compartments (tumour cells, tumour stroma, invasive front, tumour core, etc.) into account. This may require development of multiplex immunohistochemistry assays and digital image analysis algorithms. Predictive genomic assays will likely include large-scale interrogation of the cancer genome, assessment of neo-antigens, as well as analysis of germline variants. Analysis of the gut microbiota is a promising potential biomarker for response to immunotherapies for gastrointestinal cancers: response to anti-CTLA4 and anti-PD-L1 therapies have been shown to be influenced by the presence of specific gut bacteria in mouse models of melanoma, and furthermore, manipulation of the gut microbiota augmented the response to these agents [163,164].

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The need to integrate large volumes of complex data from multiple sources has led to the development of “Network Science” (see review in this issue). An appreciation of the interplay between biological systems including genomics, the tumour microenvironment, inflammation, the immune system and the microbiome is gaining ground and will be of value in the discovery and development of immunological biomarkers in gastrointestinal cancers. With ever increasing amounts of data from sources including high throughput spatial Omics to single cell RNA sequencing, an integrated network-based approach will be imperative. Attempts to link translational data have already begun with initiatives like the “PURPLE-Pancreatic Cancer Translational registry” which will link and combine translational and clinical data across 27 cancer and research centres in Australia, New Zealand and Singapore.

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Drug development, biomarker discovery, and clinical trial designs have been rethought in the era of immunotherapy, with the large number of new agents and potential biomarkers proving a challenge. Seamless phase I/II trials across tumour types, with paired biopsies and assessment of pharmacodynamics markers allows activity to be determined earlier, and in a range of tumour types [165]. Given the lack of effective adjuvant treatment options and increasing use of neoadjuvant therapy for PDAC [166], the expansion of neoadjuvant therapy trials including immunotherapies, should be considered in this tumour type. Such trials may rapidly determine if a drug has activity, and residual tumour tissue may give insight into resistance mechanisms.

Biomarkers for immunomodulatory therapies may not be as strongly predictive of response as single oncogene markers are for genotype-targeted therapies; however, they may still be crucial for decision making when faced with an individual patient. Although predictive biomarkers are not always a priority for pharmaceutical companies, they benefit cancer patients, and should be pursued in the analyses of immunotherapy trials.

Conflict of interest statement

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BT has advisory roles for Bristol-Myers Squibb and MSD. PG has had honoraria for advisory boards from Roche, Amgen, Merck, SIRTEX and MSD, and been a paid consultant for Servier. JT has honoraria for advisory boards from Amgen and Merck.

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Tables Table 1. Biomarkers for immunomodulatory therapies in oesophagogastric carcinoma

IP T

Biomarker Value Stromal tumour infiltrating lymphocytes Prognostic (sTILs) High sTILs associated with improved prognosis Immunohistochemistry markers Prognostic CD3 CD8 High expression associated with better CD45RO prognosis CD20 CD68

High ratio associated with better prognosis High expression associated with worse prognosis

SC R

CD8:FOXP3

A

N

U

CD66 CTLA-4 PD-L1 PD-L2 Microsatellite instability (MSI) or deficient Predictive of pembrolizumab response across mismatch repair (dMMR) multiple tumour types, probably including oesophagogastric carcinoma Epstein-Barr virus Prognostic May be associated with better prognosis

A

CC

EP

Ethnicity

TE D

Gene expression signatures

M

Uncertain predictive value for checkpoint inhibitors Uncertain; immune signatures under investigation. Uncertain; Asian patients have different immune infiltrates in gastric carcinoma

I N U SC R

Table 2. Active clinical trials of immunomodulatory therapies in pancreatic carcinoma Trial Description

CC E

PT

ED

M

A

FOLFIRINOX followed by Ipilimumab with allogenic GM-CSF transfected Pancreatic tumour vaccine in metastatic pancreatic cancer Tremelimumab and/or MEDI4736 in combination with stereotactic radiation therapy (SBRT) in unresectable pancreatic cancer Tremelimumab and MEDI4736 in combination with hypofractionated radiotherapy Nivolumab in combination with CAPIRI in advanced pancreatic cancer Pembrolizumab in combination with gemcitabine and nab-paclitaxel in metastatic pancreatic cancer Neoadjuvant chemoradiation in combination with Pembrolizumab in borderline resectable pancreatic cancer compared to chemoradiation therapy alone AMG820 and Pembrolizumab combination in advanced solid tumours

A

BL8040 as a single agent or in combination with Pembrolizumab in metastatic pancreatic cancer (COMBACT/KEYNOTE-202) Neoadjuvant/ Adjuvant GM-CSF secreting allogeneic pancreatic cancer vaccine (CY/GVAX) with or without Nivolumab before and after surgery in resectable pancreatic cancer BMS-986205 in combination with Nivolumab and in combination with both Nivolumab and Ipilimumab in advanced cancers Indoximod in combination with gemcitabine and nab-paclitaxel in metastatic pancreatic cancer Neoadjuvant RO7009789 alone or in combination with nab-paclitaxel and gemcitabine followed by adjuvant RO7009789 plus nab-paclitaxel and gemcitabine in resectable pancreatic cancer

Target

Target Agent(s)

Phase

CTLA-4

Ipilimumab

2

Active Clinical Trial NCT01896869

CTLA-4 PD-1 CTLA-4 PD-1 PD-1 PD-1

Tremelimumab MEDI4736 Tremelimumab MEDI4736 Nivolumab Pembrolizumab

1

NCT02311361

1

NCT02639026

1&2 1&2

NCT02423954 NCT02331251

PD-1

Pembrolizumab

1&2

NCT02305186

CSF-1R PD-1 CXCR4 PD-1 GVAX PD-1

AMG820 Pembrolizumab BL-8040 Pembrolizumab GVAX Nivolumab

1

NCT02713529

2

NCT02826486

1&2

NCT02451982

IDO PD-1 CTLA-4 IDO

BMS-986205 Nivolumab Ipilimumab Indoximod

1&2

NCT02658890

1&2

NCT02077881

CD40

RO7009789

1

NCT02588443

I N U SC R CD40 PDL1

MEDI5083 Durvalumab

LOAd703 Oncolytic virus therapy for pancreatic cancer

CD40 4-188L CCR2

A

MEDI5083 alone or in combination with durvalumab in advanced solid tumours (with pancreatic cancer cohort)

A

CC E

PT

ED

M

CCX872-B in combination with FOLFIRINOX in pancreatic cancer patients MEDI0562, an OX40 agonist, in combination with tremelimumab (antiCTLA4 antibody) or durvalumab (anti-PDL1 antibody) in advanced solid tumours AM0010 with FOLFOX compared to FOLFOX alone in 2nd line treatment of metastatic pancreatic cancer MBG453 alone or in combination with PDR001 in advanced malignancies

1

NCT03089645

LOAd703

1&2

NCT02705196

CCX872-B

1

NCT02345408

OX40 CTLA-4 PDL1 IL10

MEDI0562 Tremelimumab Durvalumab AM0010

1

NCT02705482

3

NCT02923921

TIM-3 PD-1

MBG453 PDR001

1&2

NCT02608268

I N U SC R

Table 3. Biomarkers for immunomodulatory therapies in hepatocellular carcinoma (HCC) Value Prognostic; high TILs associated with improved RFS after surgical resection or transplantation Lymphocytic subpopulations defined by Prognostic immunohistochemistry CD3 High expression associated with better OS CD8 Granzyme B High expression associated with worse OS

ED

M

A

Biomarker Tumour infiltrating lymphocytes (TILs)

FOXP3 PD-L1

A

CC E

PT

High expression associated with worse overall survival Not predictive of response to nivolumab Microsatellite instability (MSI) or deficient Predictive of pembrolizumab response across mismatch repair (dMMR) multiple tumour types but role in HCC is uncertain Gene expression signatures Uncertain; prognostic signatures have been described but not prospectively validated. Immune signatures under investigation. Neutrophil to lymphocyte ratio (NLR) Prognostic; high baseline NLR associated with worse OS