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H. Cirenajwis
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Poster Display session (Friday) (ID 65)
- Event: ELCC 2018
- Type: Poster Display session
- Track:
- Presentations: 2
- Moderators:
- Coordinates: 4/13/2018, 12:30 - 13:00, Hall 1
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19P - Single sample predictor of non-small cell lung cancer histology based on gene expression analysis of archival tissue (ID 444)
12:30 - 13:00 | Author(s): H. Cirenajwis
- Abstract
Background:
In non-small cell lung cancer (NSCLC), histological classification dictates choice of patient therapy. In this study, we aimed to establish a gene expression based single-sample predictor (SSP) for histological classification of NSCLC tumors using archival tissue that may be used in parallel with e.g. gene fusion detection as a multicomponent single assay.
Methods:
A NanoString probe set was designed to target 12 genes routinely used as IHC markers for histological subtyping as well as fusion genes known to be frequently active in NSCLC. Gene expression data was derived from NanoString analysis of 78 formalin-fixed paraffin-embedded (FFPE) NSCLCs with known histological subtypes (development cohort). A SSP was trained using AIMS (1) in the development cohort for prediction of adenocarcinoma (AC), squamous cell carcinoma (SqCC), or neuroendocrine tumors (NE). The AIMS model was applied to 11 FFPE tumors classified as large cell carcinomas (LCC) according to the WHO2004 classification (2), and 199 fresh frozen NSCLC tumors analyzed by RNA sequencing (GSE81089)(3). Finally, the SSP will be applied to 11 NSCLC-not otherwise specified (NOS) cases (4) subjected to in-depth pathological re-evaluation.
Results:
The SSP was successfully applied to NanoString data from 11 LCCs re-classified as AC, SqCC and LCC according to the revised WHO2015 guidelines (2). Of reclassified LCC tumors, 100% of AC cases and 75% (3/4) of SqCC tumors were correctly identified. In GSE81089, the SSP was erratically successful depending on histology of the tumor classified, with 97.4% concordance for AC, 97.1% for SqCC, but mismatch for 3 out of 5 NE tumors. In summary, the SSP could successfully classify tumors of AC and SqCC histology in both validation cohorts but could less successfully classify non-AC and non-SqCC tumors respectively.
Conclusions:
Gene expression based SSP can accurately classify AC and SqCC histology. Expanded transcriptional profiling may be required to capture all aspects of lung cancer biology for precise and possibly refined histological subtyping of individual cases. Gene expression-based analysis could serve as a promising complement to existing techniques, providing a useful multicomponent assay for lung cancer diagnostics.
Clinical trial identification:
Legal entity responsible for the study:
Lund University
Funding:
The Swedish Cancer Society, the Mrs Berta Kamprad Foundation, the Gunnar Nilsson Cancer Foundation, the Crafoord Foundation, BioCARE a Strategic Research Program at Lund University, the Gustav V:s Jubilee Foundation, Skane University Hospital Foundation, and governmental funding (ALF)
Disclosure:
All authors have declared no conflicts of interest.
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94P - Lung cancer recurrence in patients with pre-operative circulating tumor DNA and elevated tumor markers (ID 449)
12:30 - 13:00 | Author(s): H. Cirenajwis
- Abstract
Background:
Recurrence after surgically treated non-small cell lung cancer (NSCLC) is frequent. A subset of NSCLCs harbors mutations that are routinely analyzed in tumor tissue but can also be detected in cell-free circulating tumor DNA (ctDNA). We performed mutation analysis of tumors to subsequently quantify corresponding mutated ctDNA in pre-operative plasma. Furthermore, we analyzed five tumor markers in pre-operative serum to study the potential of these blood-based methods to predict lung cancer recurrence.
Methods:
Plasma and serum were collected pre-operatively from 167 patients surgically treated for primary lung adenocarcinoma at the Lund University Hospital 2005–2014. Tumor specimens were analyzed with Next-Generation Sequencing (NGS). 76/167 tumors harbored at least one mutation in either of the EGFR, BRAF or KRAS genes. Cell-free DNA from corresponding plasma (0.6 to 1.4 mL) was analyzed for mutations in these three genes using the IBSAFE method, an innovation upon standard droplet digital PCR. The tumor markers carcinoembryonic antigen, neuron-specific enolase, cancer antigen 125, human epididymis protein 4 and carbohydrate antigen 19–9 were analyzed in serum with electrochemiluminiscence immunoassay.
Results:
So far ctDNA and tumor markers have been analyzed in 41 cases. Twenty-nine patients had ≥1 elevated tumor markers and 10 had detectable ctDNA. Information about recurrence was missing in two patients. Sixteen patients were diagnosed with recurrence. Of these, nine had ≥1 elevated tumor markers, three had detectable ctDNA and two had both ctDNA and ≥1 tumor markers. Of 16 patients without recurrence, 10 had at ≥1 elevated tumor marker, one had detectable ctDNA, and one patient had positive ctDNA in combination with one elevated tumor marker. Four patients had stage IV disease at time of diagnosis, two of them with ctDNA and all four with ≥1 tumor markers.
Conclusions:
In summary, ctDNA and/or tumor markers might be useful to identify NSCLC patients with increased risk of recurrence but it remains to be investigated in larger studies and with greater plasma volumes how these biomarkers may fit into lung cancer management.
Clinical trial identification:
Legal entity responsible for the study:
Lund University
Funding:
The Swedish Cancer Society, Skane University Hospital Foundation, the Mrs Berta Kamprad Foundation, the Gustav V:s Jubilee Foundation, the Gunnar Nilsson Cancer Foundation, BioCARE a Strategic Research Program at Lund University, and governmental funding (ALF)
Disclosure:
A.M. George, L.H. Saal: Named inventor of related intellectual property and shareholder of SAGA Diagnostics. All other authors have declared no conflicts of interest.
