1. RNA Sequencing Approaches to Identify Novel Biomarkers for Venous Thromboembolism (VTE) in Lung Cancer
Tamara A. Sussman MD1, Mohamed Abazeed MD PhD1, Keith McCrae MD1, Alok A. Khorana MD1
1Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio
Abstract #554

2. Background
Venous thromboembolism (VTE) significantly contributes to morbidity and a worse overall prognosis in patients with cancer
Although cancer patients have a higher incidence of VTE (5-10%), the majority of patients do not experience VTE
A validated risk tool for general oncology patients exists
Novel biomarkers with greater sensitivity and specificity are needed

3. Objective
Utilize a comprehensive RNA sequencing strategy for lung cancer to identify novel biomarkers of cancer-associated VTE

4. Methods RNA was sequenced using Illumina HiSeq
For gene level analyses, expression values of zero were set to overall minimum value
All data were log2 transformed
Log2 fold-change and adjusted p-values (using Benjamini-Hochberg procedure) were calculated using linear models with moderated t-statistic
Association between single-sample gene set enrichment analysis (GSEA) profiles for each gene set and binary variables were determined using an information-based similarity metric (RNMI)

5. Results Patient Characteristics All Patients N = 12
Age, years (median [range])
67 (48-80)
Gender (n [%])
Male
8 (67%)
Race (n [%])
White
10 (83%)
Stage (n [%])
IA-IIB
IIIA IV
2 (16%)
3 (25%)
7 (58%)
Histology (n [%])
Adenocarcinoma
Squamous Cell Carcinoma
Mixed
Other
1 (8%)
Chemotherapy Received (n [%])
Carboplatin doublet therapy
Immunotherapy
None
Length of Follow Up, months (median [range])
18 (1-69)
Results

6. Results Site of VTE Lung Cancer Patients with VTE N = 6 (%)
Pulmonary Embolism
3 (50%)
Lower Extremity DVT
2 (33%)
Catheter-Associated Thrombus
1 (17%)

7. Differential Gene Expression
Results
Genes over-expressed in patients with VTE
Log2 fold change
Genes under-expressed in patients with VTE
Normalized Counts

8. Genes Over-Expressed in Lung Cancer Patients with VTE
Results
Genes Over-Expressed in Lung Cancer Patients with VTE
Gene
Log (fold-change)
Q value
Mechanism
MIAT
4.8
Myocardial infarction transcript
SHC4
4.6
Ras activating pathway
CR1
4.2
0.0004
Complement receptor
NLRP14
3.8
0.0001
Activates and regulates inflammatory response
IL5RA
3.6
0.006
CLNK
0.004
Regulates inflammatory response

9. Genes Under-Expressed in Lung Cancer Patients with VTE
Results
Genes Under-Expressed in Lung Cancer Patients with VTE
Gene
Log (fold change)
Q value
Mechanism
EN1
-4.12
0.0008
Cell development and differentiation
DSG1
-3.48
0.009
Component of desmosome
TGM1
-3.40
0.005
Cross linking of proteins
IRX4
-3.35
0.01
Cell differentiation, heart development, multicellular organism development
EPHB6
-3.29
0.008
Cell adhesion and migration

10. Results: GSEA Associated Gene Set Pathways Enrichment Score
FDR q Value
IL2-STAT5 Signaling
0.3026
0.4401
Allograft Rejection
0.2752
0.2585
IL6-JAK-STAT3 Signaling
0.2698
0.6826
Interferon-gamma Response
0.2592
0.6489
K-RAS Signaling Up
0.2290
0.6795
Complement
0.2044
0.675
Inflammatory Response
0.2002
0.7792
K-RAS Signaling Down 1
Apoptosis
0.7323

11. Conclusions and Future Directions
To our knowledge, first comprehensive RNA sequencing strategy to identify thrombosis genomic markers in cancer patients
Notably, complement, inflammatory, and KRAS1 pathways are upregulated in lung cancer patients with VTE
Differentially expressed genes and pathways provide novel biologic insight and therapeutic targets for cancer-associated VTE
1Ades et al. Tumor oncogene (KRAS) status and risk of venous thrombosis in patients with metastatic CRC. JTH 2015; 13: