| Literature DB >> 32455666 |
Stefano Frega1, Alessandro Dal Maso2, Giulia Pasello1, Lea Cuppari3, Laura Bonanno1, PierFranco Conte1,2, Laura Evangelista4.
Abstract
The global immuno-oncology pipeline has grown progressively in recent years, leading cancer immunotherapy to become one of the main issues of the healthcare industry. Despite their success in the treatment of several malignancies, immune checkpoint inhibitors (ICIs) perform poorly in others. Again, ICIs action depends on such a multitude of clinico-pathological features, that the attempt to predict responders/long-responders with ad-hoc built immunograms revealed to be quite complex. In this landscape, the role of nuclear medicine might be crucial, with first interesting evidences coming from small case series and pre-clinical studies. Positron-emission tomography (PET) techniques provide functional information having a predictive and/or prognostic value in patients treated with ICIs or adoptive T-cell therapy. Recently, a characterization of the tumor immune microenvironment (TiME) pattern itself has been shown to be feasible through the use of different radioactive tracers or image algorithms, thus adding knowledge about tumor heterogeneity. Finally, nuclear medicine exams permit an early detection of immune-related adverse events (irAEs), with on-going clinical trials investigating their correlation with patients' outcome. This review depicts the recent advances in molecular imaging both in terms of non-invasive diagnosis of TiME properties and benefit prediction from immunotherapeutic agents.Entities:
Keywords: immune checkpoint inhibitors; immunotherapy; nuclear medicine; positron-emission tomography; single-photon emission computed tomography
Year: 2020 PMID: 32455666 PMCID: PMC7281332 DOI: 10.3390/cancers12051303
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Immune checkpoint inhibitor for solid tumors (European Medicines Agency and Food and Drugs Administration approval).
| Immune Checkpoint Inhibitor | Solid Tumor | Reference |
|---|---|---|
| Adjuvant Setting | ||
| Ipilimumab | Malignant melanoma | [ |
| Nivolumab | Malignant melanoma | [ |
| Pembrolizumab | Malignant melanoma | [ |
| Advanced Disease Setting | ||
| Ipilimumab | Malignant melanoma | [ |
| Nivolumab | Malignant melanoma | [ |
| Non-small cell lung cancer | [ | |
| Renal cell carcinoma | [ | |
| Hodgkin’s lymphoma | [ | |
| Head and neck cancer | [ | |
| Urothelial carcinoma | [ | |
| Mismatch-repair deficient/Microsatellite instability-high colorectal carcinoma 1 | [ | |
| Hepatocellular carcinoma 1 | [ | |
| Nivolumab plus Ipilimumab | Malignant melanoma | [ |
| Renal cell carcinoma | [ | |
| Mismatch-repair deficient/Microsatellite instability-high colorectal carcinoma 1 | [ | |
| Pembrolizumab | Malignant melanoma | [ |
| Non-small cell lung cancer (with or without chemotherapy) | [ | |
| Renal cell carcinoma (with axitinib) | [ | |
| Hodgkin’s lymphoma | [ | |
| Head and neck cancer 1 | [ | |
| Urothelial carcinoma | [ | |
| Hepatocellular carcinoma 1 | [ | |
| Gastric cancer 1 | [ | |
| Esophageal cancer 1 | [ | |
| Cervical cancer 1 | [ | |
| Merkel cell carcinoma 1 | [ | |
| Small cell lung cancer 1 | [ | |
| Atezolizumab | Urothelial carcinoma | [ |
| Non-small cell lung cancer (with or without chemotherapy and bevacizumab) | [ | |
| Small cell lung cancer (with carboplatin and etoposide) 1 | [ | |
| Triple-negative breast cancer (with nab-paclitaxel) 1 | [ | |
| Avelumab | Merkel cell carcinoma | [ |
| Urothelial carcinoma 1 | [ | |
| Renal cell carcinoma (with axitinib) 1 | [ | |
| Durvalumab | Non-small cell lung cancer | [ |
| Urothelial carcinoma 1 | [ |
1 Food and Drugs Administration approval only.
Figure 1Overview of computed tomography (CT)-based (upper panel) and positron emission tomography (PET)-based (lower panel) response criteria for solid tumors. On the left side are grouped response criteria designed for chemotherapy, on the right side those specifically designed for immunotherapy. RECIST: Response Evaluation Criteria in Solid Tumors, irRC: Immune Related Response Criteria, irRECIST: Immune-related Response Evaluation Criteria in Solid Tumors, imRECIST: Immune-modified response evaluation criteria in solid tumors, iRECIST: Immune response evaluation criteria in solid tumors. EORTC: European Organization for Research and Treatment of Cancer criteria, PERCIST: PET Response Criteria in Solid Tumors, PERCIMT: PET Response Evaluation Criteria for Immunotherapy, PECRIT: PET/CT Criteria for Early Prediction of Response to Immune Checkpoint Inhibitor Therapy, iPERCIST: immune PET Response Criteria in Solid Tumors.
Tumor immune-microenvironment analysis with nuclear medicine imaging.
| TiME Type | Target | Radionuclide | Cancer Type | Setting | Comment | Reference |
|---|---|---|---|---|---|---|
| PBMCs | CD8 | 89Zr-anti-CD8 | Melanoma cell lines | Preclinical syngeneic tumor | Detecting change in systemic CD8+ T-cells | [ |
| TILs | IL-2 receptor | 123I-IL-2 | SCCHN | Human | – | [ |
| RCC | Human | Identify patients that less likely will benefit from cytokine treatments | [ | |||
| 99mTc-IL-2 | Melanoma | Human | Prognostic information | [ | ||
| Melanoma | Human | – | [ | |||
| CD3 | 89Zr | Bladder cancer lines | Bearing mice | DFO-anti-CD3 had diminished CD4+ T-cell counts and polarization of the CD8+ T-cell pool towards a memory phenotype | [ | |
| CTLA-4 | 64Cu-DOTA-anti-CTLA-4 | Colon cancer cell lines | Bearing mice | – | [ | |
| 64Cu-DOTA-ipilimumab | Lung cancer cell lines | In-vitro and in-vivo (bearing mice) | – | [ | ||
| PD-1 | 89Zr-Df-nivolumab | Lung cancer cell lines | In-vitro and in-vivo (bearing mice) | – | [ | |
| 64Cu-labeled PET | Melanoma cell lines | Bearing mice | Images of FoxP3(+) CD4(+) Tregs | [ | ||
| 64Cu-pembrolizumab | Melanoma cell lines | Bearing mice | – | [ | ||
| 89Zr-pembrolizumab | Melanoma cell lines | Bearing mice | Clinically translatable to monitor cancer response to ICIs | [ | ||
| LAG-3 | 89Zr-REGN3767 | Lymphoma cell lines | Bearing mice | – | [ | |
| Tumor cells | PD-L1 | 89Zr-DFO-PD-L1 mAb | Breast, gastric, lung cancer cell lines | In-vitro and in-vivo (bearing mice) | Uptake increased with escalating dose of avelumab | [ |
| 68Ga-DOTA-Nb109 | Melanoma | Bearing mice | – | [ | ||
| B7-H3 | 89Zr-DS-5573a | Breast, | Bearing mice | Identify tumor responding to therapy, insight into T cell biology | [ | |
| CD-38 | 89Zr-daratumumab | Myeloma cell lines | Bearing mice | Predict effectiveness of daratumumab | [ |
The above table depicts the advancements of NM in the determination of the different TiME features. For each TiME target, it is specified the radionuclide or the antibody-drug conjugates used, the clinical or preclinical setting, the type of cell line. Finally, any other main information in terms of recognition of target, determination of treatment response is reported as comment. CD: cluster of differentiation; CTLA-4: cytotoxic T-lymphocyte antigen 4; Df: p-SCN-deferoxamine; DFO: desferrioxamine B; DOTA: tetra-azacyclododecanetetra-acetic acid; FoxP3: forkhead box P3; ICI: immune checkpoint inhibitors; IL-2: interleukin-2; LAG-3: lymphocyte-activation gene 3; PBMCs: peripheral blood mononuclear cells; PD-1: programmed cell death protein 1; PD-L1: programmed cell death protein-ligand 1; RCC: renal cell carcinoma; SCCHN: squamous cell carcinoma of the head and neck; TILs: tumor-infiltrating lymphocytes; Treg: Regulatory T cell; 64Cu: copper-64; 68Ga: gallium-68; 123I: iodium-123; 99mTc: technetium-99m; 89Zr: zirconium-89.