| Literature DB >> 29622046 |
Zoë Blake1, Douglas K Marks2, Robyn D Gartrell1, Thomas Hart1, Patti Horton3, Simon K Cheng4, Bret Taback5, Basil A Horst6, Yvonne M Saenger7.
Abstract
BACKGROUND: Immunotherapy, in particular checkpoint blockade, has changed the clinical landscape of metastatic melanoma. Nonetheless, the majority of patients will either be primary refractory or progress over follow up. Management of patients progressing on first-line immunotherapy remains challenging. Expanded treatment options with combination immunotherapy has demonstrated efficacy in patients previously unresponsive to single agent or alternative combination therapy. CASEEntities:
Keywords: Anti-CTLA4; Anti-PD1; Brain metastases; Checkpoint inhibitors; Ipilimumab; Melanoma; Nivolumab; Pembrolizumab; T-Vec; Talimogene laherparepvec
Mesh:
Substances:
Year: 2018 PMID: 29622046 PMCID: PMC5887256 DOI: 10.1186/s40425-018-0338-6
Source DB: PubMed Journal: J Immunother Cancer ISSN: 2051-1426 Impact factor: 13.751
Fig. 1CNS response following radiotherapy and immunotherapy. a CNS lesions following gamma knife surgery (GKS), prior to whole brain radiation therapy (WBRT) and Talimogene laherparepvec (T-Vec). b Three months post WBRT and initiation of T-Vec (c) Six months following T-Vec
Fig. 2Timeline of the patient’s clinical course. GKS = Gamma knife surgery, WBRT = Whole brain radiotherapy. Ipi/Nivo = Concurrent ipilimumab and nivolumab
Fig. 3Representative tissue analysis using Quantitative Multiplex Immunofluorescence (qmIF). a 4 μm tissue section slide is processed using sequential qmIF protocol which uses tyrosine signal amplification following application of secondary antibody. After tissue processing, multispectral tissue images are obtained. b Cellular phenotyping is performed using companion software (inForm) which uses machine learning to perform automated cell phenotyping based on representative cell selection producing a Cartesian map with the X,Y coordinates of each cell in the imaged tissue, along with its assigned phenotype. c Spatial analysis can be performed using a variety of approaches including nearest neighbor calculation. As an example, distance between tumor cells (SOX10+) and nearest neighboring CTL (CD3 + CD8+) is being depicted
Fig. 4Cellular phenotyping of the tumor immune microenvironment (TME). a T Cell infiltration – Total CD3 vs. CTL infiltration in tumor (dark) and stroma (light) (b) Cytotoxic T cell (CTL) activation by tissue location and activation status, HLADR+ active/HLA-DR- inactive. c CD68 distribution by location. d SOX10+ PDL1 expression. Of note, representative tissue images did not include any PDL1+ CD68 cells or PDL1+ tumor (SOX10+) cells