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B.W.S. Robinson
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MINI 24 - Epidemiology, Early Detection, Biology (ID 140)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Thymoma, Mesothelioma and Other Thoracic Malignancies
- Presentations: 1
- Moderators:J. Creaney, M. Carbone
- Coordinates: 9/08/2015, 16:45 - 18:15, 102+104+106
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MINI24.14 - Use of Next Generation Sequencing to Improve Lung Tumor Immunotherapy (ID 1749)
18:00 - 18:05 | Author(s): B.W.S. Robinson
- Abstract
- Presentation
Background:
Immunotherapy of pulmonary tumors is now a clinical reality, however most patients do not respond. To convert non-responders into responders one potential approach is to identify the tumor‐specific ‘neo‐antigens’ that arise from DNA mutations in order to follow tumor-specific responses and to design therapeutic vaccines to try to ‘enforce’ a response against these resistant tumors.
Methods:
First, in order to identify tumor neo-antigens we performed RNAseq and exome analysis to identify single nucleotide variants (SNV) in murine pulmonary tumors. An average of 485 SNVs was found. We focused on AB1 and AB1-HA (asbestos-induced mesotheliomas, which mimic human mesothelioma) and Line 1 (lung cancer). We used the NetMHCpan 2.8 algorithm to identify candidate mutation‐carrying peptides and screened them in an interferon‐γ ELISPOT assay. Second, to determine if more neo-antigens could be ‘unmasked’ by therapy, we tested three candidate therapies in our murine model then reanalyzed neo-antigen responses a) Treg depletion using Foxp3-DTR mice, b) gemcitabine, an immunogenic cytotoxic chemotherapy commonly used for pulmonary malignancies, and c) antiCTLA4 (a checkpoint blockade therapy).
Results:
We identified 20 candidate mutation‐carrying peptides in the ELISPOT assay. A strong spontaneous endogenous pre-treatment immune response was demonstrated to DUqcrc2, a component of the respiratory chain protein ubiquinol cytochrome complex. It was found to stimulate a strong response at a similar magnitude to the model neo-antigen viral haemagglutinin (HA). The DUqcrc2 peptide sequence (amino acid 405-413) is predicted to bind the H-2Kd, and the mutant has a proline to alanine substitution mutation at position 408. Treg depletion unmasked a second neo-antigen, DGANAB. GANAB is an alpha glucosidase which cleaves the 2 innermost alpha-1,3-linked glucose residues from the Glc-2-Man-9-GlcNAc-2 oligosaccharide precursor of immature glycoproteins. There is an arginine to glutamine substitution mutation at position 969 of DGANAB (965-972) sequence. This observation supports the theory that removing Treg cells may broaden the immune response to a greater number of neo-antigens, a response presumably otherwise restrained by Treg suppression. Gemcitabine and antiCTLA4 checkpoint blockade did not unmask any additional neo-antigens.
Conclusion:
Thus, removing some immune restraints may expose a greater number of neo-antigens as potential clinical targets. The results from these approaches suggest novel ways to improve the immunotherapy of lung tumor and are the basis for planning current clinical trials.
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MTE 33 - (Debate on) Prognostic Biomarkers in Mesothelioma (Ticketed Session) (ID 85)
- Event: WCLC 2015
- Type: Meet the Expert (Ticketed Session)
- Track: Thymoma, Mesothelioma and Other Thoracic Malignancies
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2015, 07:00 - 08:00, 201+203
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MTE33.02 - (Debate on) Prognostic Biomarkers in Mesothelioma (ID 2025)
07:30 - 08:00 | Author(s): B.W.S. Robinson
- Abstract
- Presentation
Abstract:
Prognosis for mesothelioma is bleak; median survival for the cohort is generally less than 12 months. However individual patients have been known to survive for many years. From the CARET study 5 year survival rates of 9% have been reported. Our own data shows 5 year survival at less than 5%. The most frequent question of newly diagnosed mesothelioma patients relates to their prognosis. Clinical and laboratory prognostic variables proposed nearly two decades ago from consortium data from the European Organisation for Research and Treatment of Cancer (EORTC) (Curran et al, 1998) and the Cancer and Leukaemia Group B (CALGB) (Herndon et al, 1998) have been validated. Prognostic variables including performance status (PS), age, gender, tumour histology, white blood cell count (WCC), haemoglobin (Hb) level, and the presence or absence of chest pain and weight loss are taken into account when giving the patient their prognosis. Clearly, besides tumour histology and possibly the laboratory variables, most relate to the overall health and fitness of the individual. Non-subjectively determined biomarkers have been proposed as an independent means of providing prognostic information. And indeed several markers have been shown in a research setting to reflect prognosis however few of these studies have taken into account the known clinical prognostic factors. The prognostic value of serum concentrations of soluble mesothelin, the most well studied mesothelioma biomarker, have been inconsistent between studies. Data is compromised by study cohort characteristics, as tumours of sarcomatoid histology tend to have low mesothelin levels and poor survival. Our own data suggests that mesothelin levels in patients with epithelioid tumours are reflective of tumour burden as assessed by chest x-ray, CT or PET scans, which itself is an indicator of survival. Several other serological biomarkers have been reported to have prognostic value, including aquaporin 1 and osteopontin. In addition there has been extensive work on inflammation-based prognostic indices, including the neutrophil to lymphocyte ratio as well as serum albumin levels. Another useful source of prognostic biomarkers is tumour associated antigens. We have shown that serum immunoreactivity to the ATP synthase protein ATP5B is positively correlated with prognosis, and have unpublished data showing a similar significant positive association of immunoreactivity to RAB38, a previously described melanoma associated tumour antigen. In addition to blood based biomarkers, in mesothelioma it is also possible to examine soluble biomarkers in the pleural effusion. There is evidence that pleural effusion concentrations of hyaluronic acid and of fibulin-3 may provide independent prognostic data. In the case of hyaluronic acid, higher concentration of this biomarker is associated with a better prognosis. Fibulin-3 has the potential to be a useful prognostic marker because its interpretation is not confounded by lower concentrations associated with a sarcomatoid histopathology; rather sarcomatoid effusions have higher concentrations of this marker and it has been shown to be markedly superior to effusion mesothelin as a prognostic marker. Other prognostic effusion biomarkers that have been identified are syndecan-1 and osteopontin. Recently, several novel pleural effusion based biomarkers have been reported from discovery studies; these include galectin-1, aldo-keto reductase and apoliproptein C-1. Of these high effusion levels of galectin-1 and aldo-keto reductase were associated with a relatively poor prognosis whereas high effusion levels apoliproptein C-1 were associated with improved prognosis. It is important to realize that these findings remain un-validated in other patient cohorts. These biomarkers that have been identified as having prognostic value were generally not initially investigated as prognostic markers, rather they have been studied for this purpose after their identification as potential diagnostic markers. Typically their initial identification has not been thoroughly investigated in independent cohorts of patients, nor have they been systematically investigated together to determine the degree to which they are independent of each other as prognostic markers. It is possible that more suitable markers could be identified that were initially investigated as prognostic markers. An example of this would be the identification of proteins that were under or over expressed in pleural effusions from patients with longer survival compared to those with a shorter survival time using proteomics discovery methods. This underscores the importance of prospective collection of biological samples with scrupulous recording of clinical details for future evaluation of markers as they are discovered.
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P1.08 - Poster Session/ Thymoma, Mesothelioma and Other Thoracic Malignancies (ID 224)
- Event: WCLC 2015
- Type: Poster
- Track: Thymoma, Mesothelioma and Other Thoracic Malignancies
- Presentations: 1
- Moderators:
- Coordinates: 9/07/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P1.08-010 - Understanding the Genetic Landscape of Malignant Mesothelioma - A Comparison of Human and Murine Mesothelioma Cell Lines (ID 1641)
09:30 - 09:30 | Author(s): B.W.S. Robinson
- Abstract
Background:
Malignant mesothelioma (MM) is predominantly caused by exposure to asbestos. Next generation sequencing is being used in MM to understand the nature of the genetic lesions that underlie the disease and to identify potential new therapeutic targets. MM has the unusual distinction of having a mouse homologue that largely replicates the human cancer. This provides an opportunity to use murine tumor sequence data to understand mesothelioma pathogenesis, examine asbestos mutational signatures and test potential treatment strategies predicted by the genetic landscape. We have undertaken exome sequencing of asbestos induced murine MM, and compared our findings with human MM.
Methods:
Whole exome sequencing (WES) was performed on the Ion Torrent Proton platform on 15 early passage MM cell lines developed from ascites induced following asbestos exposure and tumour development in three wild-type mouse strains (BALB/c, CBA and C57BL/6 strains). Wild type germline murine normal samples were sequenced concurrently. Somatic single nucleotide variants (SNVs) were identified using publicly available algorithms with a subset being validated using Sanger sequencing. Copy number variation was analysed using GISTIC. Mutation signatures were identified using the Somatic Signatures algorithm in R.
Results:
There were on average 760 SNV identified in mouse MM cell lines (range 212-2234) equivalent to a median of approximately 9 mutations per Mb. There were significantly more SNV detected in the BALB/c strain than the CBA and C57Bl/6 strains. As previously observed there was a tendency for chromosome deletion rather than amplification in MM. Deletions in chromosome 4 in the region of p16 were common. Non-synonymous mutations accounted for 60-80% of all exonic mutations. C>T and G>A transitions were more prevalent than other mutation types across all tumours. Mutation signature analysis showed a higher rate of C>A, C>G and C>T mutations in specific dinucleotide contexts, which was mirrored in the human MM tumours.
Conclusion:
Genetic analysis of murine models of MM enables the identification of candidate mutational changes that can help inform about changes in human tumors. These models also provide excellent opportunities for pre-clinical proof-of-principle therapeutic studies of the use of sequence information in clinical trials.
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P2.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 234)
- Event: WCLC 2015
- Type: Poster
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.04-075 - Network Analysis of Anti-CTLA4-Induced Regressing Tumours Identifies Novel Synergistic Drug Combinations (ID 1113)
09:30 - 09:30 | Author(s): B.W.S. Robinson
- Abstract
Background:
Antibodies blocking immune checkpoint molecules such as CTLA-4 have been shown to be effective in several cancer types, with some patients displaying durable complete regression. However, many patients do not respond to treatment. It is not known what molecular events control the response nor which co-treatments are likely to combine effectively with checkpoint blockade. Current strategies involve empirically testing different combinations of checkpoint blocking antibodies with other immunotherapeutic strategies or conventional anti-cancer drugs. We provide an alternative approach.
Methods:
Through performing network analysis of gene expression data from responding versus non-responding AB1-HA mesothelioma tumours from mice treated with anti-CTLA-4, we identified genetic modules and hub genes within these modules that were associated with responsiveness. We subsequently identified synergistic anti-CTLA-4/drug combinations using two different approaches: first, by pinpointing drugs that modulated hub genes within these response-associated modules, and second, by interrogating overlaps in the modular response patterns and drug-perturbation signatures in drug repurposing databases. The approaches were validated by testing the identified drugs in vivo, in combination with anti-CTLA-4 in murine cancer models.
Results:
We identified and validated several drugs that increased the response rate to anti-CTLA-4 in a highly synergistic manner. We identified four drug classes with the capacity to increase the cure rate from 10% for anti-CTLA-4 alone to 60-80% as combination therapy. These repurposed drugs are normally used in completely unrelated conditions such as cardiovascular or skin diseases.
Conclusion:
Together, our results show that using network analysis of gene expression data from immunotherapy-responsive tumours generates testable hypotheses for the identification of novel synergistic drug combinations.
