RT Journal Article
SR Electronic
T1 Validation of biomarkers to predict response to immunotherapy in cancer: Volume I — pre-analytical and analytical validation
JF Journal for ImmunoTherapy of Cancer
JO J Immunother Cancer
FD BMJ Publishing Group Ltd
SP 76
DO 10.1186/s40425-016-0178-1
VO 4
IS 1
A1 Giuseppe V. Masucci
A1 Alessandra Cesano
A1 Rachael Hawtin
A1 Sylvia Janetzki
A1 Jenny Zhang
A1 Ilan Kirsch
A1 Kevin K. Dobbin
A1 John Alvarez
A1 Paul B. Robbins
A1 Senthamil R. Selvan
A1 Howard Z. Streicher
A1 Lisa H. Butterfield
A1 Magdalena Thurin
YR 2016
UL http://jitc.bmj.com/content/4/1/76.abstract
AB 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.Abbreviations:AACRAmerican association for cancer researchAECAbsolute eosinophil countsASCOAmerican society of clinical oncologyBCRB cell receptorCAPCollege of American pathologistsCARChimeric antigen receptorCDRComplementarity determining regionCDxCompanion diagnosticcfDNACirculating free DNACLIAClinical laboratory improvement amendmentsCLSIClinical and laboratory standard instituteCNVCopy number valuesCTLA-4Cytotoxic lymphocyte-associated antigen 4CVCoefficient of variationELISAEnzyme-linked immunosorbent assayELISpotEnzyme-linked immunospotEMAEuropean medicines agencyFDAFood and drug administrationFFFreshly-frozenFFPEFormalin-fixed, paraffin-embeddedFISHFluorescent in situ hybridizationGIABGenome in a bottleGM-CSFGranulocyte-macrophage colony-stimulating factorHTSHigh-throughput sequencingICCSInternational clinical cytometry societyIFNInterferonIHCImmunohistochemistryISLHInternational society for laboratory hematologymAbMonoclonal antibodyMDSCMyeloid derived suppressor cellsMIBIMultiplexed ion beam imagingMMRMismatch repairMSIMicrosatellite instabilityNBFNeutral buffered formalinNCINational cancer instituteNGSNext generation sequencingNIBSCNational institute for biological standards and controlsNISTNational institute of standards and technologyNKNatural killer cellNPVNegative predictive valueNSCLCNon-small cell lung cancerOSOverall survivalPBMCPeripheral blood mononuclear cellsPD-1Programmed cell death protein 1PD-L1Programmed cell death ligand 1PPVPositive predictive valueQCQuality controlRCCRenal cell carcinomaRINRNA integrity numberSCNPSingle cell network profilingSITCSociety for immunotherapy of cancerSOPStandard operating procedureTCRT cell receptorTh1T-helper type 1TILsTissue infiltrating lymphocytesTMATissue microarraysTMETumor microenvironmentTNBCTriple negative breast cancerTNFTumor necrosis factorTregsRegulatory T cellsUSPUS Pharmacopeial conventionWESWhole exome sequencingWGWorking groupWGSWhole genome sequencingWHOWorld Health Organization