Towards new horizons: characterization, classification and implications of the tumour antigenic repertoire

Abstract

Immune-checkpoint inhibition provides an unmatched level of durable clinical efficacy in various malignancies. Such therapies promote the activation of antigen-specific T cells, although the precise targets of these T cells remain unknown. Exploiting these targets holds great potential to amplify responses to treatment, such as by combining immune-checkpoint inhibition with therapeutic vaccination or other antigen-directed treatments. In this scenario, the pivotal hurdle remains the definition of valid HLA-restricted tumour antigens, which requires several levels of evidence before targets can be established with sufficient confidence. Suitable antigens might include tumour-specific antigens with alternative or wild-type sequences, tumour-associated antigens and cryptic antigens that exceed exome boundaries. Comprehensive antigen classification is required to enable future clinical development and the definition of innovative treatment strategies. Furthermore, clinical development remains challenging with regard to drug manufacturing and regulation, as well as treatment feasibility. Despite these challenges, treatments based on diligently curated antigens combined with a suitable therapeutic platform have the potential to enable optimal antitumour efficacy in patients, either as monotherapies or in combination with other established immunotherapies. In this Review, we summarize the current state-of-the-art approaches for the identification of candidate tumour antigens and provide a structured terminology based on their underlying characteristics.

Fig. 1. Adjustment of patient-adapted and tumour-directed drug products and therapies for clinical use.

Three levels of biomarker-driven adaptation of drug products for (immuno)therapies directed against given malignancies for clinical application can be achieved via different strategies. a | Stratification. The allocation of patients to specific therapies is directed by the assessment of established predefined biomarkers. In the absence of a respective selection criterion, therapy is not administered (represented by Ø in the figure). Usually, the active pharmaceutical ingredients (APIs) used and also the resulting stratified drug product (SPD) are manufactured and shelved. Such therapies are employed either as a defined pharmaceutical product or as an API used in combination with autologous or allogeneic cells for release as a drug product. In this scenario, the principle of either antigen-aware therapy or antigen-unaware therapy may apply. b | Warehousing. A pre-characterized set of APIs (coloured squares) is manufactured and stored as separate components that may be individually assembled (active adaptation), for example, representing a selection of APIs defined by biomarkers assessed in autologous tumour tissues (coloured circles under ‘theranostics’; colouring reflects the biomarker-defined components of the warehouse represented below). The combination of individually selected API components results in a uniquely assembled drug product (UADP), which consists of a defined number of APIs from the warehouse (represented as colours in each vial under drug product reflecting the components selected from the warehouse; respective components from the warehouse are labelled with checkmarks). The resulting drug product can be considered a UADP, which can be administered either directly as a pharmacologically defined drug product or using autologous or allogeneic cellular drug products. For this strategy, the applied therapeutic principle has to be generally antigen aware. c | Individualization. Here, active ingredients are adapted according to patient-individual biomarkers (represented by colours in different shadings in accordance with the colouring of the silhouettes) and therefore per se cannot be pre-manufactured and stored. Hence, individualization requires de novo identification, characterization, selection and manufacturing of APIs for every given patient, based on analysis of autologous tumour (and non-malignant) tissues. The individual compilation of APIs and their formulation results in a uniquely designed drug product (UDDP). When administered as a pharmacologically defined product, the resulting therapy is antigen-aware (for example, for vaccines targeting individual specified mutated HLA ligands), or, if UDDPs are generated using autologous or allogeneic cell products, these therapies may be either characterized as antigen-aware (for example, when T cells are primed with known antigens) or antigen-unaware (for example, when T cells are primed with undefined tumour lysates). SDP, standardized drug product.

Fig. 2. Cancer-related cellular alterations and characterization of HLA-presented tumour-specific and tumour-associated peptides.

a | Schematic overview of cellular processes involved in emergence, processing and HLA class I presentation of antigens. Respective changes in cellular processes (for example, modifications during translation or post-transcriptional modifications) that are altered leading to the formation of respective antigen classes are marked. b | Overview of different classes of HLA-presented antigens. Blue bars indicate whether antigens comprise alternative and/or wild-type sequences (or both). Other specific characteristics of the different tumour-specific antigens (TSAs) and tumour-associated antigens (TAAs) described in this Review are provided as a table labelled with traffic light colours: green indicates that the antigen characteristics are in accordance with the respective criteria; red indicates that the antigen characteristics are discordant with the respective criteria; and orange indicates that the respective criteria are not a defining property of this antigen class. For cryptic antigens, question marks indicate missing experimental evidence. CA, cryptic antigen; mut., mutated; oex, overexpressed; ptm, post-translational modification; roe, reactivated ontogenetic expression; spl., spliced; TAP, transporter-associated with antigen processing; TCR, T cell receptor; wt, wild-type.

Fig. 3. Current levels of scientific evidence for discovery and characterization of different classes of MHC-presented antigens.

The confidence in experimental evidence for alternative sequence antigens as well as tumour-specific antigens (TSAs) with wild-type sequence, tumour-associated antigens (TAAs) and cryptic antigens is represented by the lines of different colours. These represent light of different wavelengths combined to yield white light when transitioning through the prisms (here representing triangulation integrating different lines of evidence). The lengths of the coloured lines represent the experimental evidence graded into experimental multi-omic evidence (long lines; multiple congruent lines of evidence available), experimental evidence (medium-length lines; some merging lines of evidence available) and experimental evidence with allocation (short lines; one single line of evidence available). The colours of the lines represent exome sequencing (red), transcriptome sequencing (yellow) and MS/MS techniques, including proteomics (green) and HLA ligandomics (blue). The current situation, where the majority of tumour antigens cannot be characterized with multiple congruent lines of evidence (that is, triangulation), using both multi-omics approaches as well as indirect evidence, is symbolized by the dark side of the Moon, which exists but remains invisible to the eye. For cryptic antigens the prism and respective rays of light are inverted, as observations from MS/MS made at the HLA ligand level are attributed to a space beyond the exome, excluding exome-templated sequences. In contrast to most other antigen classes, cryptic antigens are identified using a bottom-up approach, thereby allocating HLA ligand level evidence to an ample search space comprising sequences deemed non-coding in the genome. Credit for moon image: Historical/Contributor/Getty. Adapted with permission from NASA.

Fig. 4. Antigen identification and selection for patient-adapted therapy.

Autologous tumour and/or non-malignant tissues are analysed using several methods complementing each other (whole-exome sequencing (WES), transcriptome sequencing and MS/MS). Suitable tumour-specific antigens (TSAs) and tumour-associated antigens (TAAs) are prioritized using (automated) bioinformatics approaches, but results may additionally be manually curated. This is performed by an interdisciplinary team of professionals, assessing limitations and potential issues of sample acquisition and preparation, antigen detection and bioinformatics, as well as active pharmaceutical ingredient (API) and drug product manufacturing, thereby potentially introducing bias but also improving safety owing to thorough target review. The identified antigens could be used therapeutically utilizing different platforms, comprising chimeric antigen receptor (CAR) T cells, TCR-mimic antibodies, bispecific TCR molecules and different vaccination approaches. The resulting drug product can either be standardized or individually assembled as an uniquely assembled drug product (UADP) or uniquely designed drug product (UDDP). αCD3, anti-CD3; scTCR, single-chain TCR; SDP, stratified drug product; TCR, T cell receptor.