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D. Djureinovic
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ORAL 41 - Immune Biology, Microenvironment and Novel Targets (ID 159)
- Event: WCLC 2015
- Type: Oral Session
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:S.K. Padda, R. Nemenoff
- Coordinates: 9/09/2015, 18:30 - 20:00, Four Seasons Ballroom F1+F2
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ORAL41.07 - The Identification of Therapeutic Targets in Lung Cancer Based on Transcriptomic and Proteomic Characterization of Cancer-Testis Antigens (ID 1555)
19:35 - 19:46 | Author(s): D. Djureinovic
- Abstract
- Presentation
Background:
Most immunotherapeutic modalities are based on the concept that the immune system can attack targets that are specifically expressed in cancer cells. Cancer testis antigens (CTAs) are a group of genes with a broad expression in cancers including non-small cell lung cancer (NSCLC). In normal tissues the expression of CTAs is restricted to immune privileged organs such as testis and placenta. This limited expression in somatic tissues renders CTAs as a valuable group of genes for the exploration of potential immunotherapeutic targets. The aim of this study was to comprehensively explore the CTA repertoire in NSCLC and to try identifying new CTAs.
Methods:
RNA sequencing (RNAseq) was performed on 202 NSCLC samples from a consecutive clinical cohort of surgically resected patients. For the analysis of the comprehensive CTA expression profile in NSCLC we used Cancer Testis (CT) Database containing all genes reported as CTAs in the literature. The NSCLC transcriptome was compared to the normal transcriptome comprising of 22 paired normal lung tissues as well as to 122 samples from 32 different normal human tissues. Corresponding protein expression was evaluated by using immunohistochemistry (IHC) on tissue microarrays (TMAs) containing tumor tissue from the same patients as used in the RNA sequencing.
Results:
Of the 276 established CTAs, 155 genes (56%) were restricted to testis and placenta among normal tissues and were identified as CTAs. One third (35%) was expressed in at least one of the 202 individual NSCLC cases and 28 of these genes were previously not reported to be expressed as CTAs in NSCLC. Applying stringent analysis criteria on our RNA sequencing data set we identified 61 genes that were expressed in NSCLC and testis or placenta, but not in other normal tissues. Thus, these genes present potential new CTAs. The specific cancer/testis expression of selected genes (ZNF560, TGIF2LX, TFPI2, HMGB3, TKTL1 and STK31) from this group was confirmed on protein level using IHC. Additional analysis revealed that most CTAs were concurrently expressed in adenocarcinoma and squamous cell carcinoma. The expression of a subset of genes was histology dependent, with predominant expression in adenocarcinoma (e.g. XAGE family members) and in squamous cell carcinoma (e.g. MAGE family members).
Conclusion:
Our study provides deep sequencing mRNA expression profiles of the whole CTA repertoire in NSCLC. Several CTAs previously identified in other cancers but not analyzed in NSCLC have been identified on both mRNA and protein level. Additionally, we have identified 61 novel genes as CTAs in NSCLC that previously have not been reported as CTAs and several of these were also confirmed on protein level. This data offers the opportunity to design individual therapy options to target single CTAs or CTA clusters.
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P3.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 235)
- Event: WCLC 2015
- Type: Poster
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P3.04-076 - The Crux of Molecular Prognostications in NSCLC: An Optimized Biomarker Panel Fails to Outperform Clinical Parameters (ID 2586)
09:30 - 09:30 | Author(s): D. Djureinovic
- Abstract
Background:
The best known prognostic factors for non-small cell lung cancer (NSCLC) patients are age, tumor stage and performance status. Numerous proteins have been analyzed to improve the traditional prognostication. Even though some proteins have shown prognostic value, the performance is not sufficient to be introduced in the clinical routine. The aim of this study was to generate a prognostic classifier based on proteins that previously have shown reproducible prognostic value and represent different aspects of tumorigenesis.
Methods:
The selection of proteins was based on literature search, meta-analysis of gene expression data sets and availability of reliable antibodies towards these proteins. Finally, five proteins (Ki67, EZH2, SLC2A1, TTF1 and CADM1) were chosen and analyzed by immunohistochemistry on tissue microarrays comprising NSCLC tissue patients (n=673), divided into a training and a validation cohort. For each patient, one score was obtained for each of the five antibodies, integrating the staining intensity and the fraction of stained tumor cells. Analyses were performed using all possible combinations of proteins and tested with or without clinical parameters. The C-index was used to develop the best prediction model on a training cohort (n=326) and the model was subsequently validated in the validation cohort (n=347).
Results:
All five proteins showed a significant prognostic impact in the univariate and the multivariate Cox analyses. Using a combination of the protein scores, the model was then fitted to provide the best prognostic performance (C-index=0.60). This did, however, not outperform the use of clinical parameters alone (C-index=0.62). The same was true when the analyses were performed separately for the adenocarcinoma (C-index=0.60) and the squamous cell carcinoma subgroup, respectively (C-index=0.60). More importantly, the addition of protein data to the clinical information (C-index=0.62) did not improve the prognostic value of the clinical parameters alone (C-index=0.60). To substantiate the results of our test cohort, we transferred the best prognostic model for all NSCLC, only adenocarcinomas and only squamous cell carcinomas respectively to a validation cohort. Again, all proteins showed prognostic relevance in the univariate analysis but did not perform better, alone or in combination, than the clinical parameters.
Conclusion:
Here we have performed a comprehensive analysis in order to obtain the best survival prediction model by using clinical parameters and the expression of five proteins. Although we chose strict criteria for protein marker selection, the prognostic power of these proteins was inferior to the traditional clinical parameters. Our findings question the general concept of using protein markers for prognostication in NSCLC but stress the value of careful assessment of traditional parameters in clinical practice.
