Multicenter International Study of the Consensus Immunoscore for the Prediction of Relapse and Survival in Early-Stage Colon Cancer.

Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4−82.6), 88.1% (95%-CI, 85.7−90.4), 93.4% (95%-CI, 91.1−95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18−0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17−0.50); p < 0.0001) of the patient's gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01−0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.

Clinical Categorization Algorithm (CLICAL) and Machine Learning Approach (SRF-CLICAL) to Predict Clinical Benefit to Immunotherapy in Metastatic Melanoma Patients: Real-World Evidence from the Istituto Nazionale Tumori IRCCS Fondazione Pascale, Napoli, Italy.

The real-life application of immune checkpoint inhibitors (ICIs) may yield different outcomes compared to the benefit presented in clinical trials. For this reason, there is a need to define the group of patients that may benefit from treatment. We retrospectively investigated 578 metastatic melanoma patients treated with ICIs at the Istituto Nazionale Tumori IRCCS Fondazione "G. Pascale" of Napoli, Italy (INT-NA). To compare patients' clinical variables (i.e., age, lactate dehydrogenase (LDH), neutrophil-lymphocyte ratio (NLR), eosinophil, BRAF status, previous treatment) and their predictive and prognostic power in a comprehensive, non-hierarchical manner, a clinical categorization algorithm (CLICAL) was defined and validated by the application of a machine learning algorithm-survival random forest (SRF-CLICAL). The comprehensive analysis of the clinical parameters by log risk-based algorithms resulted in predictive signatures that could identify groups of patients with great benefit or not, regardless of the ICI received. From a real-life retrospective analysis of metastatic melanoma patients, we generated and validated an algorithm based on machine learning that could assist with the clinical decision of whether or not to apply ICI therapy by defining five signatures of predictability with 95% accuracy.

Sex Differences in Overall Survival and the Effect of Radiotherapy in Merkel Cell Carcinoma-A Retrospective Analysis of a Swedish Cohort.

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer where Merkel cell Polyomavirus (MCPyV) contributes to the pathogenesis. In an adjuvant setting, radiotherapy (RT) is believed to give a survival benefit. The prognostic impact of sex related to MCPyV-status and adjuvant RT were analyzed in patients referred to Karolinska University Hospital. Data were collected from 113 patients' hospital records and MCPyV analyses were made in 54 patients (48%). We found a significantly better overall survival (OS) for women compared to men and a significant difference in OS in patients receiving adjuvant RT. Furthermore, we found that men with virus negative MCC have an increased risk for earlier death (HR 3.6). This indicates that MCPyV positive and negative MCC act as two different diseases, and it might be due to different mechanism in the immune response between male and female patients. This could have significance in tailoring treatment and follow-up in MCC patients in the future.

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

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

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

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

Multicenter International Society for Immunotherapy of Cancer Study of the Consensus Immunoscore for the Prediction of Survival and Response to Chemotherapy in Stage III Colon Cancer.

PURPOSE: The purpose of this study was to evaluate the prognostic value of Immunoscore in patients with stage III colon cancer (CC) and to analyze its association with the effect of chemotherapy on time to recurrence (TTR). METHODS: An international study led by the Society for Immunotherapy of Cancer evaluated the predefined consensus Immunoscore in 763 patients with American Joint Committee on Cancer/Union for International Cancer Control TNM stage III CC from cohort 1 (Canada/United States) and cohort 2 (Europe/Asia). CD3+ and cytotoxic CD8+ T lymphocyte densities were quantified in the tumor and invasive margin by digital pathology. The primary end point was TTR. Secondary end points were overall survival (OS), disease-free survival (DFS), prognosis in microsatellite stable (MSS) status, and predictive value of efficacy of chemotherapy. RESULTS: Patients with a high Immunoscore presented with the lowest risk of recurrence, in both cohorts. Recurrence-free rates at 3 years were 56.9% (95% CI, 50.3% to 64.4%), 65.9% (95% CI, 60.8% to 71.4%), and 76.4% (95% CI, 69.3% to 84.3%) in patients with low, intermediate, and high immunoscores, respectively (hazard ratio [HR; high v low], 0.48; 95% CI, 0.32 to 0.71; P = .0003). Patients with high Immunoscore showed significant association with prolonged TTR, OS, and DFS (all P < .001). In Cox multivariable analysis stratified by participating center, Immunoscore association with TTR was independent (HR [high v low], 0.41; 95% CI, 0.25 to 0.67; P = .0003) of patient's sex, T stage, N stage, sidedness, and microsatellite instability status. Significant association of a high Immunoscore with prolonged TTR was also found among MSS patients (HR [high v low], 0.36; 95% CI, 0.21 to 0.62; P = .0003). Immunoscore had the strongest contribution χ2 proportion for influencing survival (TTR and OS). Chemotherapy was significantly associated with survival in the high-Immunoscore group for both low-risk (HR [chemotherapy v no chemotherapy], 0.42; 95% CI, 0.25 to 0.71; P = .0011) and high-risk (HR [chemotherapy v no chemotherapy], 0.5; 95% CI, 0.33 to 0.77; P = .0015) patients, in contrast to the low-Immunoscore group (P > .12). CONCLUSION: This study shows that a high Immunoscore significantly associated with prolonged survival in stage III CC. Our findings suggest that patients with a high Immunoscore will benefit the most from chemotherapy in terms of recurrence risk.

International validation of the consensus Immunoscore for the classification of colon cancer: a prognostic and accuracy study.

BACKGROUND: The estimation of risk of recurrence for patients with colon carcinoma must be improved. A robust immune score quantification is needed to introduce immune parameters into cancer classification. The aim of the study was to assess the prognostic value of total tumour-infiltrating T-cell counts and cytotoxic tumour-infiltrating T-cells counts with the consensus Immunoscore assay in patients with stage I-III colon cancer. METHODS: An international consortium of 14 centres in 13 countries, led by the Society for Immunotherapy of Cancer, assessed the Immunoscore assay in patients with TNM stage I-III colon cancer. Patients were randomly assigned to a training set, an internal validation set, or an external validation set. Paraffin sections of the colon tumour and invasive margin from each patient were processed by immunohistochemistry, and the densities of CD3+ and cytotoxic CD8+ T cells in the tumour and in the invasive margin were quantified by digital pathology. An Immunoscore for each patient was derived from the mean of four density percentiles. The primary endpoint was to evaluate the prognostic value of the Immunoscore for time to recurrence, defined as time from surgery to disease recurrence. Stratified multivariable Cox models were used to assess the associations between Immunoscore and outcomes, adjusting for potential confounders. Harrell's C-statistics was used to assess model performance. FINDINGS: Tissue samples from 3539 patients were processed, and samples from 2681 patients were included in the analyses after quality controls (700 patients in the training set, 636 patients in the internal validation set, and 1345 patients in the external validation set). The Immunoscore assay showed a high level of reproducibility between observers and centres (r=0·97 for colon tumour; r=0·97 for invasive margin; p<0·0001). In the training set, patients with a high Immunoscore had the lowest risk of recurrence at 5 years (14 [8%] patients with a high Immunoscore vs 65 (19%) patients with an intermediate Immunoscore vs 51 (32%) patients with a low Immunoscore; hazard ratio [HR] for high vs low Immunoscore 0·20, 95% CI 0·10-0·38; p<0·0001). The findings were confirmed in the two validation sets (n=1981). In the stratified Cox multivariable analysis, the Immunoscore association with time to recurrence was independent of patient age, sex, T stage, N stage, microsatellite instability, and existing prognostic factors (p<0·0001). Of 1434 patients with stage II cancer, the difference in risk of recurrence at 5 years was significant (HR for high vs low Immunoscore 0·33, 95% CI 0·21-0·52; p<0·0001), including in Cox multivariable analysis (p<0·0001). Immunoscore had the highest relative contribution to the risk of all clinical parameters, including the American Joint Committee on Cancer and Union for International Cancer Control TNM classification system. INTERPRETATION: The Immunoscore provides a reliable estimate of the risk of recurrence in patients with colon cancer. These results support the implementation of the consensus Immunoscore as a new component of a TNM-Immune classification of cancer. FUNDING: French National Institute of Health and Medical Research, the LabEx Immuno-oncology, the Transcan ERAnet Immunoscore European project, Association pour la Recherche contre le Cancer, CARPEM, AP-HP, Institut National du Cancer, Italian Association for Cancer Research, national grants and the Society for Immunotherapy of Cancer.

The need for a network to establish and validate predictive biomarkers in cancer immunotherapy.

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, the entire medical oncology field has been revolutionized by the introduction of immune checkpoints inhibitors. Despite success in a variety of malignancies, responses typically only occur in a small percentage of patients for any given histology or treatment regimen. There are also concerns that immunotherapies are associated with immune-related toxicity as well as high costs. As such, identifying biomarkers to determine which patients are likely to derive clinical benefit from which immunotherapy and/or be susceptible to adverse side effects is a compelling clinical and social need. In addition, with several new immunotherapy agents in different phases of development, and approved therapeutics being tested in combination with a variety of different standard of care treatments, there is a requirement to stratify patients and select the most appropriate population in which to assess clinical efficacy. The opportunity to design parallel biomarkers studies that are integrated within key randomized clinical trials could be the ideal solution. Sample collection (fresh and/or archival tissue, PBMC, serum, plasma, stool, etc.) at specific points of treatment is important for evaluating possible biomarkers and studying the mechanisms of responsiveness, resistance, toxicity and relapse. This white paper proposes the creation of a network to facilitate the sharing and coordinating of samples from clinical trials to enable more in-depth analyses of correlative biomarkers than is currently possible and to assess the feasibilities, logistics, and collated interests. We propose a high standard of sample collection and storage as well as exchange of samples and knowledge through collaboration, and envisage how this could move forward using banked samples from completed studies together with prospective planning for ongoing and future clinical trials.

Patient-reported outcomes in KEYNOTE-006, a randomised study of pembrolizumab versus ipilimumab in patients with advanced melanoma.

OBJECTIVE: Report results of patient-reported health-related quality of life (HRQoL) and symptoms from phase III KEYNOTE-006 study of pembrolizumab versus ipilimumab in patients with ipilimumab-naive advanced melanoma. PATIENTS AND METHODS: Patients received pembrolizumab 10 mg/kg every 2 (Q2W) or every 3 weeks (Q3W) for up to 2 years, or four cycles of ipilimumab 3 mg/kg Q3W. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30) was administered at baseline and throughout the study. Patient-reported outcome (PRO) analyses were pre-specified exploratory endpoints; the primary PRO assessment was the score change from baseline to week 12 in EORTC QLQ-C30 global health status (GHS)/HRQoL score between the arms using constrained longitudinal data analysis. RESULTS: The PRO analysis population included 776 patients: pembrolizumab Q2W (n = 270); pembrolizumab Q3W (n = 266); ipilimumab (n = 240). Baseline GHS was similar across arms. QLQ-C30 compliance rates at week 12 were 87% (n = 214), 97% (n = 226), and 96% (n = 178), for the pembrolizumab Q2W, pembrolizumab Q3W, and ipilimumab arms, respectively. From baseline to week 12, GHS/HRQoL scores were better maintained with pembrolizumab than with ipilimumab (decrease of -1.9 and -2.5 for pembrolizumab versus -10.0 for ipilimumab; p < 0.001 for each pembrolizumab arm versus ipilimumab). Fewer patients treated with pembrolizumab experienced deterioration in GHS at week 12 (31% for pembrolizumab Q2W; 29% for Q3W and 44% for ipilimumab), with similar trends observed for individual functioning and symptoms scales. CONCLUSIONS: HRQoL was better maintained with pembrolizumab than with ipilimumab in patients with ipilimumab-naive advanced melanoma. CLINICALTRIALS. GOV IDENTIFIER: NCT01866319.

Ipilimumab treatment decreases monocytic MDSCs and increases CD8 effector memory T cells in long-term survivors with advanced melanoma.

Ipilimumab has revolutionized malignant melanoma therapy, but a better understanding of the mechanisms behind treatment response and adverse effects is needed. In this work, the immune system of ipilimumab treated patients was monitored to investigate potential mechanisms of action that may correlate with treatment outcome. Blood samples from 43 advanced melanoma patients were taken before, during and at the end of treatment. Hematological parameters were measured and flow cytometry analysis was performed in fresh samples within two hours of sample collection. Strong differences in markers CD45RA, CCR7, HLA-DR and CD15 between fresh and cryopreserved samples were observed. Ipilimumab treatment increased absolute lymphocyte counts, eosinophils, effector T cells and their activation status, whilst diminishing the suppressive side of the immune response, acting on regulatory T cells and myeloid derived suppressor cells (MDSCs). These effects were visible after one ipilimumab infusion and, regarding eosinophil counts, correlated with onset of adverse events. Monocytic MDSCs were decreased in response to treatment only in patients with clinical benefit; additionally, patients with a lower frequency of these cells after the first ipilimumab infusion experienced increased overall survival. CD8 effector memory T cell frequencies at the end of treatment were higher in patients with clinical benefit and positively correlated with survival. These data show that a clinical response to ipilimumab not only requires reshaping T cell populations, but additionally involves a reduction in suppressive cells such as monocytic MDSCs. Our work could provide insight on predicting treatment outcome, assisting clinicians in offering the best personalized therapeutic approach.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume I - pre-analytical and analytical validation.

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, there have been many clinical successes using checkpoint receptor blockade, including T cell inhibitory receptors such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death-1 (PD-1). Despite demonstrated successes in a variety of malignancies, responses only typically occur in a minority of patients in any given histology. Additionally, treatment is associated with inflammatory toxicity and high cost. Therefore, determining which patients would derive clinical benefit from immunotherapy is a compelling clinical question. Although numerous candidate biomarkers have been described, there are currently three FDA-approved assays based on PD-1 ligand expression (PD-L1) that have been clinically validated to identify patients who are more likely to benefit from a single-agent anti-PD-1/PD-L1 therapy. Because of the complexity of the immune response and tumor biology, it is unlikely that a single biomarker will be sufficient to predict clinical outcomes in response to immune-targeted therapy. Rather, the integration of multiple tumor and immune response parameters, such as protein expression, genomics, and transcriptomics, may be necessary for accurate prediction of clinical benefit. Before a candidate biomarker and/or new technology can be used in a clinical setting, several steps are necessary to demonstrate its clinical validity. Although regulatory guidelines provide general roadmaps for the validation process, their applicability to biomarkers in the cancer immunotherapy field is somewhat limited. Thus, Working Group 1 (WG1) of the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force convened to address this need. In this two volume series, we discuss pre-analytical and analytical (Volume I) as well as clinical and regulatory (Volume II) aspects of the validation process as applied to predictive biomarkers for cancer immunotherapy. To illustrate the requirements for validation, we discuss examples of biomarker assays that have shown preliminary evidence of an association with clinical benefit from immunotherapeutic interventions. The scope includes only those assays and technologies that have established a certain level of validation for clinical use (fit-for-purpose). Recommendations to meet challenges and strategies to guide the choice of analytical and clinical validation design for specific assays are also provided.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume II - clinical validation and regulatory considerations.

There is growing recognition that immunotherapy is likely to significantly improve health outcomes for cancer patients in the coming years. Currently, while a subset of patients experience substantial clinical benefit in response to different immunotherapeutic approaches, the majority of patients do not but are still exposed to the significant drug toxicities. Therefore, a growing need for the development and clinical use of predictive biomarkers exists in the field of cancer immunotherapy. Predictive cancer biomarkers can be used to identify the patients who are or who are not likely to derive benefit from specific therapeutic approaches. In order to be applicable in a clinical setting, predictive biomarkers must be carefully shepherded through a step-wise, highly regulated developmental process. Volume I of this two-volume document focused on the pre-analytical and analytical phases of the biomarker development process, by providing background, examples and "good practice" recommendations. In the current Volume II, the focus is on the clinical validation, validation of clinical utility and regulatory considerations for biomarker development. Together, this two volume series is meant to provide guidance on the entire biomarker development process, with a particular focus on the unique aspects of developing immune-based biomarkers. Specifically, knowledge about the challenges to clinical validation of predictive biomarkers, which has been gained from numerous successes and failures in other contexts, will be reviewed together with statistical methodological issues related to bias and overfitting. The different trial designs used for the clinical validation of biomarkers will also be discussed, as the selection of clinical metrics and endpoints becomes critical to establish the clinical utility of the biomarker during the clinical validation phase of the biomarker development. Finally, the regulatory aspects of submission of biomarker assays to the U.S. Food and Drug Administration as well as regulatory considerations in the European Union will be covered.

Cancer Treatment with Anti-PD-1/PD-L1 Agents: Is PD-L1 Expression a Biomarker for Patient Selection?

Strategies to help improve the efficacy of the immune system against cancer represent an important innovation, with recent attention having focused on anti-programmed death (PD)-1/PD-ligand 1 (L1) monoclonal antibodies. Clinical trials have shown objective clinical activity of these agents (e.g., nivolumab, pembrolizumab) in several malignancies, including melanoma, non-small-cell lung cancer, bladder cancer, squamous head and neck cancer, renal cell cancer, ovarian cancer, microsatellite-unstable colorectal cancer, and Hodgkin's lymphoma. Expression of PD-L1 in the tumor microenvironment appears to be crucial for therapeutic activity, and initial trials suggested positive PD-L1 tumor expression was associated with higher response rates. However, subsequent observations have questioned the prospect of using PD-L1 expression as a biomarker for selecting patients for therapy, especially since many patients considered PD-L1-negative experience a benefit from treatment. Importantly, there is not yet a definitive test for determination of PD-L1 and a cut-off reference for PD-L1-positive status has not been established. Immunohistochemistry with different antibodies and different thresholds has been used to define PD-L1 positivity (1-50 %), with no clear superiority of one threshold over another for identifying which patients respond. Moreover, the type of cells on which PD-L1 expression is most relevant is not yet clear, with immune infiltrate cells and tumor cells both being used. In conclusion, while PD-L1 expression is often a predictive factor for treatment response, it must be complemented by other biomarkers or histopathologic features, such as the composition and amount of inflammatory cells in the tumor microenvironment and their functional status. Multi-parameter quantitative or semi-quantitative algorithms may become useful and reliable tools to guide patient selection.

Non-classical HLA-class I expression in serous ovarian carcinoma: Correlation with the HLA-genotype, tumor infiltrating immune cells and prognosis.

In our previous studies, we have shown that patients with serous ovarian carcinoma in advanced surgical stage disease have a particularly poor prognosis if they carry the HLA-A*02 genotype. This represent a stronger prognostic factor than loss or downregulation of the MHC class I heavy chain (HC) on tumor cells. In this study, we investigated the expression of the non-classical, immune tolerogenic HLA -G and -E on the tumor cells along with the infiltration of immune cells in the tumor microenvironment. FFPE primary tumors from 72 patients with advanced stages of serous adenocarcinoma and metastatic cells present in ascites fluid from 8 additional patients were included in this study. Both expression of HLA-G and aberrant expression of HLA-E were correlated to a significant worse prognosis in patients with HLA-A*02, but not with different HLA genotypes. Focal cell expression of HLA-G correlated to a site-specific downregulation of classical MHC class I HC products and aberrant HLA-E expression, showing a poor survival. HLA-G was more frequently expressed in metastatic cells than in primary tumor lesions and the expression of HLA-G inversely correlated with the frequency of tumor infiltrating immune cells. All these parameters can contribute together to identify and discriminate subpopulations of patients with extremely poor prognosis and can give them the opportunity to receive, and benefit of individually tailored treatments.

Active immunosurveillance in the tumor microenvironment of colorectal cancer is associated with low frequency tumor budding and improved outcome.

Tumor budding (single tumor cells or small tumor cell clusters) at the invasion front of colorectal cancer (CRC) is an adverse prognostic indicator linked to epithelial-mesenchymal transition. This study characterized the immunogenicity of tumor buds by analyzing the expression of the major histocompatibility complex (MHC) class I in the invasive tumor cell compartment. We hypothesized that maintenance of a functional MHC-I antigen presentation pathway, activation of CD8+ T-cells, and release of antitumoral effector molecules such as cytotoxic granule-associated RNA binding protein (TIA1) in the tumor microenvironment can counter tumor budding and favor prolonged patient outcome. Therefore, a well-characterized multipunch tissue microarray of 220 CRCs was profiled for MHC-I, CD8, and TIA1 by immunohistochemistry. Topographic expression analysis of MHC-I was performed using whole tissue sections (n = 100). Kirsten rat sarcoma viral oncogene homolog (KRAS) and B-Raf proto-oncogene, serine/threonine kinase (BRAF) mutations, mismatch repair (MMR) protein expression, and CpG-island methylator phenotype (CIMP) were investigated. Our results demonstrated that membranous MHC-I expression is frequently down-regulated in the process of invasion. Maintained MHC-I at the invasion front strongly predicted low-grade tumor budding (P = 0.0004). Triple-positive MHC-I/CD8/TIA1 in the tumor microenvironment predicted early T-stage (P = 0.0031), absence of lymph node metastasis (P = 0.0348), lymphatic (P = 0.0119) and venous invasion (P = 0.006), and highly favorable 5-year survival (90.9% vs 39.3% in triple-negative patients; P = 0.0032). MHC-I loss was frequent in KRAS-mutated, CD8+ CRC (P = 0.0228). No relationship was observed with CIMP, MMR, or BRAF mutation. In conclusion, tumor buds may evade immune recognition through downregulation of membranous MHC-I. A combined profile of MHC-I/CD8/TIA1 improves the prognostic value of antitumoral effector cells and should be preferred to a single marker approach.

A phase I clinical trial combining dendritic cell vaccination with adoptive T cell transfer in patients with stage IV melanoma.

Adoptive transfer of in vitro-expanded tumor-infiltrating lymphocytes (TIL) has shown great clinical benefit in patients with malignant melanoma. TIL therapy itself has little side effects, but conditioning chemo- or radiotherapy and postinfusion interleukin 2 (IL-2) injections are associated with severe adverse advents. We reasoned that combining TIL infusion with dendritic cell (DC) vaccination could circumvent the need for conditioning and IL-2 support and thus represent a milder treatment approach. Eight patients with stage IV melanoma were enrolled in the MAT01 study, consisting of vaccination with autologous tumor-lysate-loaded DC, followed by TIL infusion. Six of eight patients were treated according to protocol, while one patient received only TIL and one only DC. Treatments were well tolerated with a single grade 3 adverse event. The small study size precludes analysis of clinical responses, though interestingly one patient showed a complete remission and two had stable disease. Analysis of the infusion products revealed that mature DC were generated in all cases. TIL after expansion were CD3+ T cells, dominated by effector memory CD8+ cytotoxic T cells. Analysis of the T cell receptor repertoire revealed presence of highly dominant clones in most infusion products, and many of these could be detected in the circulation for weeks after T cell transfer. Here, we report the first combination of DC vaccination and TIL infusion in malignant melanoma. This combined treatment was safe and feasible, though after evaluating both clinical and immunological parameters, we expect that administration of lymphodepleting chemotherapy and IL-2 will likely increase treatment efficacy.

A novel approach for HLA-A typing in formalin-fixed paraffin-embedded-derived DNA.

The aim of this study was to establish a novel approach for human leukocyte antigen (HLA)-typing from formalin-fixed paraffin-embedded-derived DNA. HLAs can be a prognostic factor in cancer and have an extensive polymorphism. This polymorphism is predominantly restricted to exons, which encode the peptide-binding domain of the protein. Formalin-fixed paraffin-embedded material is routinely collected in the clinic and therefore a great source of DNA for genetic analyses. However, its low quality due to fragmentation and nucleotide changes has often created obstacles in designing genetic assays. In this study, we amplified the most polymorphic exons of the HLA-A gene, exons 2, 3, and 4, in 16 formalin-fixed paraffin-embedded samples >10 years old. These tissue samples belonged to patients already HLA-typed by peripheral blood samples at the routine laboratory. Acquired amplification products were used for sequencing, which provided enough information to establish an HLA allele. The same method was applied to DNA extracted from peripheral blood from a healthy volunteer with known HLA type. Of the samples, 14/16 (88%) were successfully typed, in one sample only one of the alleles could be determined, and in one sample no allele could be determined. The amplification of the most polymorphic exons of HLA-A was a successful alternative when DNA quality prevented positive results with previously described methods. The method is usable when an HLA type is needed but the patients are deceased and/or no whole blood samples can be collected. It has thus potential to be used in several fields such as the clinic, research, and forensic science.

Towards the introduction of the 'Immunoscore' in the classification of malignant tumours.

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) TNM staging system provides the most reliable guidelines for the routine prognostication and treatment of colorectal carcinoma. This traditional tumour staging summarizes data on tumour burden (T), the presence of cancer cells in draining and regional lymph nodes (N) and evidence for distant metastases (M). However, it is now recognized that the clinical outcome can vary significantly among patients within the same stage. The current classification provides limited prognostic information and does not predict response to therapy. Multiple ways to classify cancer and to distinguish different subtypes of colorectal cancer have been proposed, including morphology, cell origin, molecular pathways, mutation status and gene expression-based stratification. These parameters rely on tumour-cell characteristics. Extensive literature has investigated the host immune response against cancer and demonstrated the prognostic impact of the in situ immune cell infiltrate in tumours. A methodology named 'Immunoscore' has been defined to quantify the in situ immune infiltrate. In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC/UICC TNM classification. An international consortium has been initiated to validate and promote the Immunoscore in routine clinical settings. The results of this international consortium may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Genotyping of human leukocyte antigen (HLA) ancestral haplotypes as prognostic marker in cancer using PCR analysis.

The major histocompatibility complex (MHC) comprises a set of genes that are essential to immunity and surveillance against neoplastic transformation. MHC antigens not only regulate antitumor immune responses in experimental animal models but also directly correlate with survival and prognosis of patients with various types of cancers. Effective recognition of tumor cells by effector T cells may be affected by the genotype and the extent of expression of human leukocyte antigen (HLA)-peptide complexes. Therefore, MHC antigens may serve as potential biomarkers for prognosis and allow selection of cancer patients for specific therapy. We describe PCR-based method to determine the HLA genotype in healthy individuals and patients using blood and tumor tissue as DNA source.

HLA class I and II expression in oropharyngeal squamous cell carcinoma in relation to tumor HPV status and clinical outcome.

HPV-DNA positive (HPVDNA+) oropharyngeal squamous cell carcinoma (OSCC) has better clinical outcome than HPV-DNA negative (HPVDNA-) OSCC. Current treatment may be unnecessarily extensive for most HPV+ OSCC, but before de-escalation, additional markers are needed together with HPV status to better predict treatment response. Here the influence of HLA class I/HLA class II expression was explored. Pre-treatment biopsies, from 439/484 OSCC patients diagnosed 2000-2009 and treated curatively, were analyzed for HLA I and II expression, p16(INK4a) and HPV DNA. Absent/weak as compared to high HLA class I intensity correlated to a very favorable disease-free survival (DFS), disease-specific survival (DSS) and overall survival (OS) in HPVDNA+ OSCC, both in univariate and multivariate analysis, while HLA class II had no impact. Notably, HPVDNA+ OSCC with absent/weak HLA class I responded equally well when treated with induction-chemo-radiotherapy (CRT) or radiotherapy (RT) alone. In patients with HPVDNA- OSCC, high HLA class I/class II expression correlated in general to a better clinical outcome. p16(INK4a) overexpression correlated to a better clinical outcome in HPVDNA+ OSCC. Absence of HLA class I intensity in HPVDNA+ OSCC suggests a very high survival independent of treatment and could possibly be used clinically to select patients for randomized trials de-escalating therapy.