| Literature DB >> 30991686 |
Vito Longo1, Oronzo Brunetti2, Amalia Azzariti3, Domenico Galetta4, Patrizia Nardulli5, Francesco Leonetti6, Nicola Silvestris7.
Abstract
Despite that the impact of immune checkpoint inhibitors on malignancies treatment is unprecedented, a lack of response to these molecules is observed in several cases. Differently from melanoma and non-small cell lung cancer, where the use of immune checkpoint inhibitors results in a high efficacy, the response rate in other tumors, such as gastrointestinal cancers, breast cancer, sarcomas, and part of genitourinary cancers remains low. The first strategy evaluated to improve the response rate to immune checkpoint inhibitors is the use of predictive factors for the response such as PD-L1 expression, tumor mutational burden, and clinical features. In addition to the identification of the patients with a higher expression of immune checkpoint molecules, another approach currently under intensive investigation is the use of therapeutics in a combinatory manner with immune checkpoint inhibitors in order to obtain an enhancement of efficacy through the modification of the tumor immune microenvironment. In addition to the abscopal effect induced by radiotherapy, a lot of studies are evaluating several drugs able to improve the response rate to immune checkpoint inhibitors, including microbiota modifiers, drugs targeting co-inhibitory receptors, anti-angiogenic therapeutics, small molecules, and oncolytic viruses. In view of the rapid and extensive development of this research field, we conducted a systematic review of the literature identifying which of these drugs are closer to achieving validation in the clinical practice.Entities:
Keywords: angiogenesis; chemotherapy; immune checkpoint inhibitors; tyrosine kinase inhibitors
Year: 2019 PMID: 30991686 PMCID: PMC6521062 DOI: 10.3390/cancers11040539
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Figure 1Research strategy with PRISMA flow diagram.
Search terms.
| Immune Therapy | Enhancer |
|---|---|
| ‘immune checkpoint inhibitors’, ‘anti-PD-(L)1’, ‘anti-CTLA-4’. | “microbiote” OR “microbiota” OR “gut microbe” OR “bacteria” |
| ‘immune checkpoint inhibitors’, ‘anti-PD-(L)1’, ‘anti-CTLA-4’. | “chemotherapy” OR“ chemotherapeutics” OR “metronomic chemotherapy” |
| ‘immune checkpoint inhibitors’, ‘anti-PD-(L)1’, ‘anti-CTLA-4’. | “anti-angiogenetic therapies” OR “bevacizumab” OR “nintedanib” OR “Aflibercept” OR “pazopanib” OR “sunitinib” |
| ‘immune checkpoint inhibitors’, ‘anti-PD-(L)1’, ‘anti-CTLA-4’. | “co-inhibitor receptors” OR “TIGIT” OR “LAG3” OR “TIM-3” |
| ‘immune checkpoint inhibitors’, ‘anti-PD-(L)1’, ‘anti-CTLA-4’. | “Oncolytic virus” OR “adenovirus” OR ”vaccinia viruses” OR ”Coxsackieviruses” OR ”Reoviruses” |
| ‘immune checkpoint inhibitors’, ‘anti-PD-(L)1’, ‘anti-CTLA-4’. | “small molecules” OR “tyrosine kinase inhibitor” OR “mTOR inhibitor” OR “cyclin inhibitor” |
Figure 2Summarizes the mechanisms implicated in improving the efficacy of immune checkpoint inhibitors (ICIs): The influence of microbiota on dendritic cell (DC) maturation and activation; the correct trafficking of T cells to the tumor bed due to the normalization of endothelium by anti-angiogenic drugs and the VEGF immunosuppressive activity; the impact of chemotherapy on immunosuppressive cells and on DC maturation; release of damaged molecular patterns after oncolytic viruses induce tumor cell lysis.
Figure 3Summary of the mechanisms involved in improving of ICI efficacy by oncolytic viruses: Release of damage-associated molecular patterns after tumor cell lysis, transfer of genes encoding INF-α, GM-CSF and others cytokines, DC maturation and activation, natural killer (NK) cell activation, and increase in PD-L1 expression. The main studies evaluating the combination of oncolytic viruses are also reported.
Small Molecule Inhibitors and ICIs.
| Small Molecule Enhancer | ICI | Cancer | Study Design | Results/Enhancing | Reference |
|---|---|---|---|---|---|
| BRAFi | Not associated | Melanoma | In vitro | BRAF inhibition enhance melanoma antigen expression | Wilmott, 2013. [ |
| Selective BRAF inhibitors | Not associated | Melanoma | In vitro | Induction of Tcell infiltration into human metastatic melanoma | Wilmott, 2012. [ |
| Dabrafenib and trametinib | (pmel-1 adoptive cell transfer) | BRAFV600E driven melanoma | In vivo—mouse model | Complete tumor regression with increased T cell infiltration into tumors and improved in vivo cytotoxicity | Cooper, 2014. [ |
| Dabrafenib and trametinib | anti-PD1 | SM1 tumors (melanoma) | In vivo—mouse model | Superior anti-tumor effect compared to the results obtained with the only small molecules combination | Hu-Lieskovan, 2015. [ |
| Vemurafenib | Ipilimumab | Melanoma | Phase 1 trial | Stopped after one month due to liver toxicity | Ribas, 2013. [ |
| Dabrafenib, trametinib | Ipilimumab | Melanoma | Phase 1 trial | Stopped due to excessive colon toxicity | Minor, 2015. [ |
| Dabrafenib | Ipilimumab | BRAF-mutated melanoma | Phase 1 trial | ORR of 69% | Puzanov, 2014. [ |
| Dabrafenib and trametinib | pembrolizumab | BRAF-mutated melanoma | KEYNOTE-022, an ongoing phase I/II trial | ORR of 60% ( | NCT02130466, [ |
| Vemurafenib (V) | Atezolizumab (A) | Melanoma | Phase Ib trial (V-run in vs. concurrent V-A) | Higher ORR was seen with V run-in than with concurrent A + V start | Sullivan, 2016. [ |
| Vemurafenib, and cobimetinib | Atezolizumab | BRAFV600-mutant melanoma | Phase I/II trial | Manageable safety profile and promising antitumor activity | NCT01656642. [ |
| imatinib | Not associated | GIST | In vitro study | Reduction of Treg immunosuppressive function | Larmonier, 2008. [ |
| Imatinib | Not associated | GIST | In vivo study | PFS correlated with IFN-γ secretion by NK cells | Ménard, 2009. [ |
| Imatinib | Not associated | GIST | In vivo—mouse model | Activated CD8+ T cells and induced Treg apoptosis in tumor sample | Balachandran, 2011. [ |
| Imatinib | Anti-PD-1 (RMP1-14) or anti-PD-L1 (10F.9G2) | GIST | In vivo—mouse model | Increased antitumor effects by enhancing cytotoxic T cell effector function | Seifert, 2017. [ |
| Imatinib | Ipilimumab | GIST and other c-Kit positive solid cancers | Phase 1 trial | Manageable safety profile in multiple tumor types. | NCT01738139, [ |
| Rapamycin | Not associated | Oral cancer | In vivo—mouse model | Reduction of tumor growth through | Cash, 2015. [ |
| Rapamycin | Not associated | Oral cancer | In vivo—mouse model | Enhancing of IFNγ production by peripheral and tumor-infiltrating CD8 T cells | Moore, 2016. [ |
| Rapamycin | PD-L1 mAb | Oral cancer | In vivo—mouse model | Activation of CD8 T cells in tumor infiltration increased by the addition of rapamycin | Moore, 2016. [ |
| CDK4/6 inhibitor | Not associated | Breast cancer | In vivo—mouse model/blood sample patients | Anti-tumor immunity through proliferation of Tregs | Goel, 2017. [ |
| CDK4/6 inhibitor | anti-PD-1 | Breast cancer | In vivo—mouse model | Enhancing of tumor regression and dramatically improving of OS | Zhang, 2018. [ |
| CDK4/6 inhibitor and PI3K antagonist | Anti PD-1 and anti CTLA-4 | Triple negative breast cancer | In vivo—mouse model | Inhibition induced complete and durable regressions (> one year) of breast tumors in in vivo models. | Teo, 2017. [ |