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. 2020 Mar 9;30:105399. doi: 10.1016/j.dib.2020.105399

Dataset of GWAS-identified variants underlying venous thromboembolism susceptibility and linkage to cancer aggressiveness

Valéria Tavares a,b, Ricardo Pinto a, Joana Assis a,c, Deolinda Pereira a,d, Rui Medeiros a,b,c,e,
PMCID: PMC7114903  PMID: 32258274

Abstract

Venous thromboembolism (VTE) is a common cardiovascular disease, for which several single nucleotide polymorphisms (SNPs) underlying susceptibility were identified. Apart from candidate gene approach, genome-wide association studies (GWAS) have contributed to the identification of novel VTE-associated SNPs, including some with no clear role in the haemostatic system. These genetic variants constitute potential cancer-related biomarkers, particularly predictive and prognostic biomarkers, as a two-way association between VTE and cancer is well established. The present dataset comprises the data obtained from GWAS performed to identify genetic variants associated with VTE risk. Furthermore, this dataset also comprises data regarding previously reported candidate gene and validation reports performed in adults of European ancestry that also analysed the VTE GWAS-identified variants. Lastly, to evaluate the impact of these genetic variants in carcinogenesis, a broad search was made, which has let us to establish putative links between several VTE-associated genes and cancer hallmarks in a review article entitled “Venous thromboembolism GWAS reported genetic makeup and the hallmarks of cancer: linkage to ovarian tumour behaviour”.

Keywords: Venous thromboembolism, GWAS, SNPs, Validation reports, Cancer hallmarks


Specifications table

Subject Biochemistry, Genetics and Molecular Biology
Specific subject area Genetics; Molecular biology; Molecular medicine; Cancer Research
Type of data Tables
How data were acquired NHGRI-EBI GWAS catalogue
NCBI database
GeneCards database
Ensembl database
Data format Raw
Filtered
Parameters for data collection The collection of VTE GWAS data (VTE variants’ characterization, study population description and overall risk conferred by each variant in VTE GWAS) was made by screening the NHGRI-EBI GWAS catalogue. Regarding candidate gene and validation reports, data collection was performed by searching the NCBI database. As for the impact of VTE-associated genes in carcinogenesis, putative links with cancer hallmarks were established by searching the NCBI, GeneCards and Ensembl databases.
Description of data collection For VTE GWAS data collection, no restriction was made regarding the origin and age of the population. We gathered only the genetic variants statistically associated with VTE susceptibility in the GWAS´ discovery phase (P < 0.05). For candidate gene and validation reports, we only gathered the reports that analysed incident VTE among adults of European ancestry with no strong risk factors and performed before and after GWAS findings, respectively. In terms of the links between VTE-associated genes and cancer hallmarks, we gathered the information from reports that addressed this topic.
Data source location NHGRI-EBI GWAS catalogue
NCBI database
GeneCards database
Ensembl database
Data accessibility Data is provided in the article
Related review article Tavares V., Pinto R., Assis J., Pereira D., Medeiros R. (2019). Venous thromboembolism GWAS reported genetic makeup and the hallmarks of cancer: Linkage to ovarian tumour behaviour. Biochimica et Biophysica Acta (BBA)-Reviews on Cancer, https://doi.org/10.1016/j.bbcan.2019.188331

Value of the data

  • Given the existence of a tight and bilateral relationship between VTE and cancer, VTE-associated single nucleotide polymorphisms (SNPs) constitute potential cancer-related predictive and prognostic biomarkers that are currently in need.

  • Considering the growing incidence of VTE among cancer patients, with its underlying negative impact on patient prognosis, this dataset can benefit researchers and clinicians that work in the oncology field, who are interested in the genetic susceptibility for VTE, and how VTE-associated SNPs can be linked to cancer progression.

  • This database can be used for the development of several experiments as the majority of VTE genetic variants with a putative role in cancer progression have not been studied among cancer patients, particularly ovarian cancer patients who are frequently diagnosed with VTE and/or present a blood hypercoagulability state in the blood coagulation tests.

1. Data

Table 1 comprises the data obtained from GWAS performed to identify genetic variants that are associated with VTE susceptibility. Table 2 includes the data of a genome-wide search of pairwise SNP interactions associated with VTE risk. Table 3 encompasses data regarding previously reported candidate gene and validation reports of GWAS-identified SNPs that are associated with VTE risk. Table 4 includes putative links between VTE-associated genes and several cancer hallmarks.

Table 1.

SNPs identified by VTE susceptibility GWAS.

Report accession on NHGRI-EBI GWAS catalogue Associated SNPs Population No. cases/controls (combined) MAF Locus Gene/Variant Overall risk
Allelic OR (95% Cl) P-value
GCST000354 rs2420371 European ancestry 419/1228 (Discovery phase) 0.15a 1q24.2 F5/intr 2.27 (1.62; 3.18)c 8.08 × 10−10
rs1208134 0.12a 1q24.2 CCDC181/ intr 2.29 (1.58; 3.32)c 3.47 × 10−7
rs657152 0.54a chr9: 133,263,862b ABO/intrb 1.89 (1.51; 2.36)c 2.22 × 10−13
rs505922 0.52a chr9: 133,273,813b ABO/intrb 1.91 (1.53; 2.39)c 1.48 × 10−14
rs630014 0.37a 9q34.2 ABO/intr 0.64 (0.51; 0.80)c 2.00 × 10−7
rs2420371¥ European ancestry 1150/801 (Replication phase I) 0.21a 1q24.2 F5/intr 1.39 (1.17;1.64)c 3.00 × 10−5
rs1208134¥ 0.19a 1q24.2 CCDC181/ intr 1.57 (1.31; 1.88)c 2.89 × 10−7
rs6025 0.01 1q24.2 F5/mis 2.01 (1.63; 2.48)c 9.91 × 10−11
rs657152§ 0.51a chr9: 133,263,862b ABO/intrb 1.75 (1.51; 2.03)c 1.20 × 10−13
rs505922§ 0.49a chr9: 133,273,813b ABO/intrb 1.81 (1.56; 2.11)c 3.72 × 10−15
rs630014§ 0.38a 9q34.2 ABO/intr 0.66 (0.57; 0.76)c 1.21 × 10−8
rs8176719 0.34 9q34.2 ABO/fra 0.33 (0.26; 0.42)c 1.70 × 10−18
rs8176750 0.05 9q34.2 ABO/fra 0.53 (0.38; 0.74)c 2.46 × 10−4
rs2420371¥ European ancestry 607/607 (Replication phase II) 0.10a 1q24.2 F5/intr 1.44 (1.07; 1.93)c 1.80 × 10−3
rs6025 0.01 1q24.2 F5/mis 2.46 (1.55; 3.93)c 1.50 × 10−4
rs657152§ 0.47a chr9: 133,263,862b ABO/intrb 1.58 (1.34; 1.87)c 5.19 × 10−8
rs505922§ 0.46a chr9: 133,273,813b ABO/intrb 1.65 (1.39; 1.95)c 7.25 × 10−9
rs630014§ 0.38a 9q34.2 ABO/intr 0.63 (0.53; 0.74)c 5.01 × 10−8
rs8176719 0.34 9q34.2 ABO/fra 0.53 (0.41; 0.69)c 2.21 × 10−6
GCST000621 rs3813948 European ancestry 419/1228 (in silico GWAS) 0.09a 1q32.1 C4BPB/nc 0.011
rs3813948 1706/1379 (Replication phase) 0.09a 1q32.1 C4BPB/nc 1.24 (1.00; 1.53) 0.046
GCST001253 rs16861990 European ancestry 1542/1110 (Discovery phase) 0.13a 1q24.2 NME7/intr 2.49c- 2.75 × 10−15
rs1208134 0.13a 1q24.2 CCDC181/ intr 2.53c - 3.29 × 10−16
rs2420371 0.15a 1q24.2 F5/intr 2.62c - 8.44 × 10−19
rs2066865 0.28a 4q32.1 FGG/inter 1.55c - 1.17 × 10−10
rs6825454 0.30a 4q31.3 FGA/inter 1.50c- 1.32 × 10−9
rs10029715 0.12a 4q35.2 F11-ASIIintr 3.20 × 10−9
rs2073828 0.32a chr9: 133,261,737b ABO/intrb 3.57 × 10−9
rs657152 0.49a chr9: 133,263,862b ABO/intrb 1.70c 1.10 × 10−18
rs500498 0.33a chr9: 133,273,232b ABO/intrb 1.03 × 10−12
rs505922 0.49a chr9: 133,273,813b ABO/intrb 1.85c 1.06 × 10−23
rs630014 0.38a 9q34.2 ABO/intr 0.63c 4.40 × 10−14
rs495828 0.36a 9q34.2 ABO/rr 1.64c 1.78 × 10−14
rs1018827 European ancestry 1961/2338 (meta-analysis)d 0.07 1q24.2 F5/intr 2.52 2.41 × 10−26
rs7659024 0.30 4q31.3 FGG/inter 1.53 1.93 × 10−13
rs505922 0.35 chr9: 133,273,813b ABO/intrb 1.92 1.39 × 10−34
rs3756008 0.32 4q35.2 F11/inter 1.40 6.46 × 10−11
GCST001557 rs6025 98.64% European ancestry (USA) 1503/1459 (Discovery phase) 0.01 1q24.2 F5/mis 3.75 (2.76; 4.60) 1.68 × 10−22
rs8176719 0.34 9q34.2 ABO/fra 1.47 (1.32; 1.64) 5.68 × 10−12
rs2519093 0.14 chr9: 133,266,456b ABO/intrb 1.69 (1.48; 1.91) 8.08 × 10−16
rs495828 0.16 9q34.2 ABO/rr 1.65 (1.46; 1.86) 2.96 × 10−16
rs7538157¥ <0.01 1q24.2 BLZF1/intr 2.69 (2.09; 3.45) 1.04 × 10−14
rs16861990¥ 0.06 1q24.2 NME7/intr 2.02 (1.66; 2.45) 1.69 × 10−12
rs2038024 0.13 1q24.2 SLC19A2/nc 1.53 (1.32; 1.78) 1.12 × 10−8
rs1799963 <0.01 11p11.2 F2/utr 2.46 (1.70; 3.55) 1.69 × 10−6
rs6025 98.64% European ancestry (USA) 1407/1418 (Replication phase) 0.01 1q24.2 F5/mis 2.56 (1.97; 3.32) 1.40 × 10−12
rs8176719 0.34 9q34.2 ABO/fra 1.58 (1.40; 1.78)e 9.75 × 10−14e
rs2519093 0.14 chr9: 133,266,456b ABO/intrb 1.85 (1.61; 2.13)e 1.37 × 10−17e
rs495828 0.16 9q34.2 ABO/rr 1.76 (1.54; 2.01)e 3.60 × 10−17e
rs1799963 <0.01 11p11.2 F2/utr 1.71 (1.12; 2.63)e 0.01e
rs16861990 0.06 1q24.2 NME7/intr 1.79 (1.47; 2.18) 4.89 × 10−9
1.17 (0.89;1.54)e 0.25e
rs2038024 0.13 1q24.2 SLC19A2/nc 0.77 (0.65;0.92)e 4.00 × 10−3e
GCST002012 rs6427196 European ancestry 1618/44,499 (Discovery phase) 0.09 1q24.2 F5/utr 1.82 (1.58; 2.10)c 1.97 × 10−16
rs687621 0.38 chr9: 133,261,662b ABO/intrb 1.37 (1.26;1.49)c 3.42 × 10−14
rs4253399 0.26 4q35.2 F11/intr 1.15 (1.06; 1.24)c 7.59 × 10−4
rs6536024 0.46 4q32.1 FGG/interg 0.79 (0.73; 0.87)c 4.04 × 10−7
rs6764623 0.35 3p26.3 CNTN6/interg 1.23 (1.11; 1.38)c 9.56 × 10−5
rs4979078 0.33 9q31.3 SUSD1/intr 1.31 (1.17; 1.47)c 2.46 × 10−6
rs7164569 0.33 15q13.3 OTUD7A/syn 0.84 (0.76; 0.92)c 3.54 × 10−4
rs3733860 0.17 5q13.3 SV2C/utr 1.22 (1.09; 1.37)c 6.27 × 10−4
rs6427196 European ancestry 3231/3536 (Replication phase) 0.09 1q24.2 F5/utr 2.31 (2.04; 2.62)c 2.56 × 10−38
rs687621 0.38 chr9: 133,261,662b ABO/intrb 1.75 (1.62; 1.89)c 1.20 × 10−44
rs4253399 0.26 4q35.2 F11/intr 1.32 (1.23; 1.43)c 2.07 × 10−13
rs6536024 0.46 4q32.1 FGG/interg 0.81 (0.75; 0.87)c 5.59 × 10−8
rs6764623 0.35 3p26.3 CNTN6/interg 1.14 (1.05; 1.24)c 2.00 × 10−3
rs4979078 0.33 9q31.3 SUSD1/intr 1.11 (1.00; 1.24)c 4.70 × 10−2
rs7164569 0.33 15q13.3 OTUD7A/syn 0.88 (0.82; 0.95)c 2.00 × 10−3
rs3733860 0.17 5q13.3 SV2C/utr 1.17 (1.05; 1.30)c 3.00 × 10−3
rs6427196 European ancestry 4849/48,035 (Combined data of all nine studies) 0.09 1q24.2 F5/utr 2.07 (1.89; 2.28)c 4.47 × 10−51
rs687621 0.38 chr9: 133,261,662b ABO/intrb 1.55 (1.47; 1.64)c 1.55 × 10−52
rs4253399 0.26 4q35.2 F11/intr 1.24 (1.17; 1.31)c 2.78 × 10−14
rs6536024 0.46 4q32.1 FGG/interg 0.80 (0.76; 0.85)c 1.75 × 10−13
rs6764623 0.35 3p26.3 CNTN6/interg 1.18 (1.10; 1.26)c 1.57 × 10−6
rs4979078 0.33 9q31.3 SUSD1/intr 1.21 (1.11; 1.30)c 3.06 × 10−6
rs7164569 0.33 15q13.3 OTUD7A/syn 0.87 (0.81; 0.92)c 3.27 × 10−6
rs3733860 0.17 5q13.3 SV2C/utr 1.19 (1.10; 1.29)c 8.06 × 10−6
GCST002808 rs6025 European ancestry 7507/52,632 (Discovery phase) 0.01 1q24.2 F5/mis 3.25 (2.91; 3.64) 1.10 × 10−96
rs4524 0.27 1q24.2 F5/mis 1.20 (1.14; 1.26) 2.65 × 10−11
rs2066865 0.30 4q32.1 FGG/ inter 1.24 (1.18; 1.31) 1.03 × 10−16
rs4253417 0.30 4q35.2 F11/intr 1.27 (1.22; 1.34) 1.21 × 10−23
rs529565 0.37 chr9: 133,274,084b ABO/intrb 1.55 (1.48; 1.63) 4.23 × 10−75
rs1799963 <0.01 11p11.2 F2/utr 2.29 (1.75; 2.99) 1.73 × 10−9
rs6087685 0.39 20q11.22 PROCR/intr 1.15 (1.10; 1.21) 1.65 × 10−8
rs4602861 0.39 8q23.1 ZFPM2/intr 1.20 (1.13; 1.27) 3.48 × 10−9
rs78707713 0.05 10q22.1 TSPAN15/intr 1.28 (1.19; 1.39) 5.74 × 10−11
rs2288904 0.18 19p13.2 SLC44A2/mis 1.19 (1.12; 1.26) 1.07 × 10−9
rs78707713 European ancestry 3009/2586 (Replication phase) 0.05 10q22.1 TSPAN15/intr 1.42 (1.24; 1.62) 2.21 × 10−7
rs2288904 0.18 19p13.2 SLC44A2/mis 1.28 (1.16; 1.40) 2.64 × 10−7
rs4602861 European ancestry 10,516/55,218 (combined data) 0.39 8q23.1 ZFPM2/intr 5.04 × 10−7
rs78707713 0.05 10q22.1 TSPAN15/intr 1.67 × 10−16
rs2288904 0.18 19p13.2 SLC44A2/mis 2.75 × 10−15
GCST003377 rs62322307# West African Ancestryf (80%) European and Asian ancestry 146/432 (Discovery phase) 0.15a 4q22.2 ATOH1/inter 2.79 (1.80; 4.30) 2.25 × 10−7
rs73692310 0.15a 7p12.3 IGFBP3/inter 3.04 (2.00;4.70) 1.73 × 10−9
rs58952918# 0.17a 18p11.32 AP005230.1/ intr 2.48 (1.70; 3.70) 1.07 × 10−8
rs28496996 0.17a 18p11.32 AP005230.1/ intr 2.44 (1.60; 3.60) 1.13 × 10−8
rs2144940 0.31a 20p11.21 THBD, CD93/inter 2.18 (1.60; 2.90) 3.52 × 10−7
rs2567617# 0.31a 20p11.21 THBD, CD93/inter 2.17 (1.60; 2.90) 4.01 × 10−7
rs1998081 0.27a 20p11.21 THBD, CD93/inter 2.28 (1.60; 3.10) 5.17 × 10−7
rs687621 0.38 chr9: 133,261,662b ABO/intrb 1.55 (1.20; 2.00) 2.00 × 10−3
rs505922 0.35 chr9: 133,273,813b ABO/intrb 1.52 (1.20; 2.00) 2.00 × 10−3
rs657152 0.39 chr9: 133,263,862b ABO/intrb 1.39 (1.10; 1.80) 0.03
rs73692310 West African Ancestryf (77%) European and Asian ancestry 94/65 (Replication phase) 0.09a 7p12.3 IGFBP3/inter 1.27 (0.04; 2.70) 0.60
rs28496996 0.13a 18p11.32 AP005230.1/ intr 1.34 (0.60; 2.60) 0.45
rs2144940 0.35a 20p11.21 THBD, CD93/inter 1.89 (1.10; 3.30) 0.02
rs1998081 0.30a 20p11.21 THBD, CD93/inter 1.94 (1.10; 3.50) 0.02
rs73692310 West African Ancestryf (79%) European and Asian ancestry 240/497 (Combined data) 0.02 7p12.3 IGFBP3/inter 2.48 × 10−8
rs28496996 0.03 18p11.32 AP005230.1/ intr 6.37 × 10−8
rs2144940 0.12 20p11.21 THBD, CD93/inter 1.88 × 10−8
rs1998081 0.11 20p11.21 THBD, CD93/inter 4.62 × 10−8
GCST003390 rs6025 European ancestry 6135/252,827 (Discovery phase) 0.01 1q24.2 F5/mis 2.93 (2.72; 3.15) 3.60 × 10−137
rs7654093 0.31 4q32.1 FGG/inter 1.22 (1.17; 1.27) 2.00 × 10−19
rs4444878 0.32 4q35.2 F11-ASI/intr 0.81 (0.78; 0.84) 7.00 × 10−28
rs1799963 <0.01 11p11.2 F2/utr 0.51 (0.46; 0.58) 1.30 × 10−24
rs34234989 0.39 20q11.22 PROCR/intr 0.89 (0.85; 0.92) 6.70 × 10−9
rs529565 0.37 chr9: 133,274,084b ABO/intrb 0.72 (0.70; 0.75) 7.10 × 10−63
rs9797861 0.21 19p13.2 SLC44A2/ intr 1.15 (1.09; 1.20) 6.10 × 10−9
rs114209171 0.24 Xq28 FUNDC2/nc 1.15 (1.11; 1.20) 7.00 × 10−13
rs72798544 0.01 2p21 COX7A2L/intr 0.73 (0.65; 0.82) 1.90 × 10−7
rs17490626 0.04 10q22.1 TSPAN15/intr 1.17 (1.10; 1.24) 2.90 × 10−7
rs113092656 0.01 6p24.1 TMEM170B/ADTRP/inter 0.73 (0.65; 0.82) 4.40 × 10−7
rs60942712 0.06 3p11.1 EPHA3/inter 1.21 (1.12; 1.31) 8.00 × 10−7
rs114209171 European ancestry 26,112 participants (Replication phase) 0.24 Xq28 FUNDC2/nc 1.08 (1.02; 1.14) 0.01
GCST004012 rs1304029 European ancestry 212 children with VTE / 424 parents and siblings (Discovery phase) 0.48 6q13 B3GAT2/intr 0.48 (0.36; 0.65) 2.00 × 10−6h
rs9293858 0.26 6q13 RIMS1/intr 0.48 (0.34; 0.67) 8.00 × 10−6h
rs2748331 0.41 6q13 B3GAT2/rr 0.49 (0.36; 0.67) 1.80 × 10−5h
rs10498910 0.12 6q14.1 LOC105377862/intrb 2.21 (1.47; 3.31) 6.89 × 10−5h
rs914958 0.23 1p22.1 ABCA4/intr 0.50 (0.36; 0.70) 1.80 × 10−5h
rs4529013 0.28 4q21.3 MAPK10/intr 0.53 (0.39; 0.72) 2.00 × 10−5h
rs9957519 0.27 18q23 -/inter 0.46 (0.32; 0.68) 2.10 × 10−5h
rs1865590 0.31 2q22.1 THSD7B/intr 1.97 (1.44; 2.68) 2.40 × 10−5h
rs9606534 0.17 chr22: 16,916,985b IGKV2OR22-4/rr 0.43 (0.29; 0.63) 3.30 × 10−5h
rs495828 0.16 9q34.2 ABO/rr 6.44 × 10−4
rs505922 0.35 chr9: 133,273,813b ABO/intrb 4.03 × 10−4
rs657152 0.39 chr9: 133,263,862b ABO/intrb 1.77 (1.34; 2.32) 3.44 × 10−5
rs13146272 0.44 4q35.1 CYP4V2/miss 9.58 × 10−4
rs925451 0.29 4q35.2 F11/intr 2.76 × 10−3
rs11128790 0.06 3p24.3 RFTN1/intr 2.95 (1.78; 4.90) 3.40 × 10−5h
rs4792119 0.21 17p12 SHISA6/Intr 0.51 (0.37; 0.71) 3.50 × 10−5h
rs9399770 0.48 6q16.3 -/inter 0.55 (0.42; 0.74) 4.00 × 10−5h
rs17576372 0.27 1p22.1 TGFBR3/intr 1.84 (1.37; 2.47) 4.57 × 10−5h
rs10247053 0.25 7p15.2 -/inter 0.53 (0.39; 0.72) 5.35 × 10−5h
rs636434 0.34 6q12 EYS/intr 1.79 (1.34; 2.39) 5.35 × 10−5h
rs10190178 0.31 2q22.1 THSD7B/intr 1.91 (1.40; 2.62) 6.15 × 10−5h
rs5014872 0.12 2p16.3 LOC730100/ Intrb 0.46 (0.32; 0.68) 6.21 × 10−5h
rs3823606 0.04 7q11.21 TPST1/intr 6.27 × 10−5h
rs1565242 0.11 15q26.1 LOC105370982/intrb 0.44 (0.29; 0.67) 7.23 × 10−5h
rs1958059 0.31 14q13.1 NPAS3/intr 0.45 (0.31; 0.67) 7.28 × 10−5h
rs1521882 0.23 2q33.1 KIAA2012/intr 2.13 (1.46; 3.11) 7.48 × 10−5h
rs17781793 0.05 12q15 MRPL40P1/ inter 0.38 (0.23; 0.63) 7.81 × 10−5h
rs4775384 0.31 15q22.2 AC104574.2/ intr 0.41 (0.26; 0.65) 8.16 × 10−5h
rs1948650 0.33 15q14 DPH6-DT/intr 1.84 (1.34; 2.51) 8.71 × 10−5h
rs436985 0.34 5q12.1 C5orf64/intr 0.58 (0.44; 0.76) 9.13 × 10−5h
rs4926448 0.47 1q44 SCCPDH/intr 0.57 (0.43; 0.76) 9.38 × 10−5h
rs11153626 0.22 6q22.1 FAM162B/ inter 1.85 (1.34; 2.54) 9.49 × 10−5h
rs2214810 0.26 7p15.2 -/inter 0.54 (0.40; 0.74) 9.62 × 10−5h
rs2748331 European ancestry 413 children/ 826 parents and siblings (combined data of discovery phase and replication phase I) 0.41 6q13 B3GAT2/rr 7.88 × 10−7
rs9446340 0.23 6q13 B3GAT2/ Inter 1.48 × 10−3
rs10498910 0.12 6q14.1 LOC105377862/intrb 5.74 × 10−5
rs2748331 European ancestry 651 adults with VTE/ 1356 controls (Replication phase II) 0.41 6q13 B3GAT2/rr 1.20 (1.02; 1.40) 0.02g
rs1304029 0.48 6q13 B3GAT2/intr 1.18 (1.02; 1.36) 0.03g
GCST004068 rs138916004Ж African ancestry (African-Americans) 393/4941 (Discovery phase) < 0.01 12q14.3 LEMD3/intr 3.17 (2.13; 4.72)j 1.27 × 10−8j
rs3804476Ж 0.28 6p25.1 LY86/intr 1.83 (1.48; 2.26)j 1.97 × 10−8j
rs142143628Ж < 0.01 8q12.2 LOC100130298/intrb 4.97 (2.80; 8.83)j 4.35 × 10−8j
rs6025 0.01 1q24.2 F5/mis 5.00 (2.02; 11.03)j 2.00 × 10−4j
rs8176746 0.15 9q34.2 ABO/mis 1.33 (1.09; 1.62)j 5.00 × 10−3j
rs8176719 0.34 9q34.2 ABO/fra 1.30 (1.11; 1.53)j 2.00 × 10−3j
rs77121243β 0.03 11p15.4 HBB/miss 1.51 (1.11; 2.06) 9.00 × 10−3
GCST004256 rs6025 European ancestry 3290/116,868 (Discovery phase) 0.01 1q24.2 F5/mis 3.49 (2.96; 4.11) 7.10 × 10−50
rs2066865 0.30 4q32.1 FGG/inter 1.21 (1.15; 1.29) 3.10 × 10−11
rs4253416 0.41 4q35.2 F11/intr 1.18 (1.12; 1.24) 2.00 × 10−10
rs2519093 0.14 chr9: 133,266,456b ABO/intrb 1.41 (1.32; 1.50) 6.00 × 10−26
rs8176645 0.38 9q34.2 ABO/intr 1.28 (1.22; 1.35) 4.40 × 10−21
rs1799963 <0.01 11p11.2 F2/utr 2.63 (2.03; 3.40) 4.90 × 10−13
rs3136516 0.28 11p11.2 F2/intr 1.10 (1.04; 1.15)k 3.30 × 10−4k
rs4602861 0.39 8q23.1 ZFPM2/intr 1.08 (1.03; 1.15) 4.50 × 10−3
rs4602861 European ancestry 10,516/55,218 (Replication phase) 0.39 8q23.1 ZFPM2/intr 1.13 (1.08; 1.19) 5.04 × 10−7
rs3136516 0.28 11p11.2 F2/intr 1.10 (1.06; 1.15)k 5.65 × 10−6k
rs4602861 European ancestry 13,806/ 172,086 (combined data) 0.39 8q23.1 ZFPM2/intr 1.11 (1.07; 1.15) 4.88 × 10−10
rs3136516 0.28 11p11.2 F2/intr 1.10 (1.06; 1.13)k 7.60 × 10−9k

The data shown in Table 1 concerning locus, type of genetic variant, as well as MAF values for all populations were obtained on the "Ensembl" database. For intergenic variants, the nearest gene was indicated.

MAF: minor allele frequency; OR: odds ratio; Inter: Intergenic variant, Intr: Intronic variant, Mis: missense variant, Fra: frameshift variant, Nc: non coding transcript exon variant, Syn: synonymous variant, UTR: 3 prime UTR variant, RR: regulatory region variant.

a

MAF values for cases in the Report

b

Data obtained from “NCBI” database

c

OR/RR associated with the minor allele

d

99 SNPs reached genome-wide significant (p < 2 × 10−8), but only the hit SNPs of each locus (F5, FGG, F11 and ABO) were included in the table

e

Data after adjusting for rs6025

f

SNPs predominantly found in populations of African descent

g

After Bonferroni correction, the P-values became insignificant

h

P-values of permutation testing

j

After adjusting for sickle cell risk variant (HBB rs77121243-T allele) and other cofactors

k

After adjusting for rs1799963.

¥

SNPs not significantly associated with VTE risk after adjusting for rs6025

§

SNPs not significantly associated with VTE risk after adjusting for ABO blood group (rs8176719 and rs8176750)

#

SNPs not tested in replication cohort due to high LD or due to failed assay

Ж

SNPs further replicated using parametric bootstrap, internal cross-validation and meta-analysis methods

β

SNP merged into rs334 according to “NCBI” database

Table 2.

Genome-wide search for VTE-associated pairwise SNP interactions.

Report Pairwise SNP interactions++ Population No. cases/controls (combined) MAF Locus Gene/Variant Overall risk
OR P-value
GCST001913 rs493014 European ancestry 1953/2338 (Meta analysis of two previous GWAS) 0.30 9q34.2 SURF6/Inter 1.64 6.00 × 10−11
rs886090 0.32 9q34.2 SURF6/mis
rs1336472 0.40 1p31.3 AK4/utr 1.54 4.24 × 10−10
0.38 6p12.1 HMGCLL1/inter
rs4715555
rs380904 0.29 8q24.3 ZC3H3/intr 1.67 4.51 × 10−10
rs8086028 0.30 18p11.22 PIEZO2/utr
rs6815916 0.09 4q34.3 TENM3-AS1/ inter 2.10 6.84 × 10−10
rs6092326 0.47 20q13.31 FAM209B/inter
rs2282015 0.41 10q26.13 AL160290.2/intr 1.50 8.36 × 10−10
rs13050454 0.42 21q21.3 AP001595.1/ inter
rs7648704 0.33 3p22.3 TRIM71/rr 1.56 9.89 × 10−10
rs4868644 0.49 5q35.2 RNF44/inter
rs1985317 0.41 9q33.1 AL445644.1/inter 0.66 1.32 × 10−9
rs827637 0.46 10p14 AC044784.1/inter
rs2321744 0.10 13q13.2 RFC3/inter 0.49 1.38 × 10−9
rs6497540 0.42 16p13.2 GRIN2A/intr
rs315122 0.30 12q15 YEATS4/intr 2.05 1.42 × 10−9
rs884483 0.12 15q23 TLE3/inter
rs1423386 0.20 5q12.1 LRRC70/inter 1.73 1.63 × 10−9
rs6491679 0.29 13q33.1 FGF14/intr
rs7714670 0.44 5q13.2 ARHGEF28/miss 1.52 1.75 × 10−9
rs12880735 0.35 14q12 AL390334.1/intr
rs9392653 0.28 6p25.1 PPP1R3G/inter 1.74 1.83 × 10−9
rs7780976 0.19 7p21.2 DGKB/inter
rs9804128 0.26 1p36.13 IGSF21/inter 1.71 1.90 × 10−9
rs4784379 0.24 16q12.2 IRX3/inter
rs1364505 0.32 7q32.3 PLXNA4/ intr 1.80 2.10 × 10−9
rs1204660 0.16 20q11.22 UQCC1/intr
rs2288073 0.29 2q23.3 FAM228A/miss 1.60 2.11 × 10−9
rs10771022 0.34 12p12.1 SOX5/intr
rs1367228 0.44 2p16.1 EFEMP1/intr 1.49 2.20 × 10−9
rs3905075 0.40 13q33.3 FAM155AIT1/ intr
rs536477 0.43 1q43 CHRM3/intr 0.63 2.93 × 10−9
rs1937920 0.27 10p15.1 AKR1C2/inter
rs2710201 0.06 7q36.2 ACTR3B /inter 0.40 3.30 × 10−9
rs3780293 0.35 9q21.2 GNA14/intr
rs12541254 0.34 8p22 DLC1/intr 1.65 3.33 × 10−9
0.23 15q23 TLE3/inter
rs305009
rs4507975 0.29 1q25.2 PAPPA2/intr 0.65 3.58 × 10−9
rs9914518 0.47 17p13.1 GSG1L2/intr
rs2771051 0.37 9q33.1 -/inter 0.67 3.82 × 10−9
rs827637 0.46 10p14 -/inter
rs10516089 0.31 5q35.1 SMIM23/inter 0.63 3.86 × 10−9
rs11072930 0.29 15q25.1 ARNT2/inter
rs10504130 0.14 8q11.22 PCMTD1/intr 1.88 4.46 × 10−9
rs2847351 0.31 18p11.22 APCDD1/inter
rs318497 0.49 6p25.2 AL133351.3/nc 0.43 4.54 × 10−9
rs7019259 0.07 9q21.2 PSAT1/inter
rs6695223 0.13 1p22.3 WDR63/intr 1.86 4.70 × 10−9
rs1763510 0.39 6q23.2 SGK1/Intr
rs1336708 0.25 13q33.1 FGF14-IT1/intr 0.58 4.85 × 10−9
rs1423386 0.20 5q12.1 CKS1BP3/inter
rs6771316 0.13 3p13 LINC00877/intr 2.13 5.26 × 10−9
rs10986432 0.17 9q33.3 OLFML2A/intr
rs664910 0.30 3q21.3 MGLL/intr 1.50 6.63 × 10−9
0.46 15q22.2 RORA/intr
rs877228
rs9945428 0.30 18q22.3 FBXO15/intr 0.62 6.88 × 10−9
rs4823535 0.27 22q13.32 FAM19A5/inter
rs1910358 0.23 5q14.2 C5orf17/inter 2.03 7.14 × 10−9
rs9981595 0.11 21q22.2 BRWD1/intr
rs6771725 0.27 3q26.31 NAALADL2/intr 2.22 8.60 × 10−9
rs10507246 0.09 12q24.21 TBX5/intr
rs16865717 0.28 2p25.2 RSAD2/intr 1.56 8.82 × 10−9
rs2009579 0.36 20q12 -/inter
rs2028385 0.16 12q23.1 AC007513.1/intr 1.69 8.82 × 10−9
rs2038227 0.38 16p13.3 RAB11FIP3/intr
rs10476160 0.20 5q35.2 SFXN1/inter 0.62 9.09 × 10−9
rs1707420 0.48 8p23.2 -/inter
rs971572 0.32 1q25.3 TSEN15/intr 0.42 9.30 × 10−9
rs10828151 0.07 10p12.31 NEBL/intr
rs6858430 0.21 4q34.1 ADAM29/intr 1.62 9.67 × 10−9
rs4800250 0.40 18q11.2 TAF4B/intr
rs467650 0.37 5q15 RGMB/inter 0.67 9.91 × 10−9
rs7153749 0.44 14q23.1 LINCO1500/ intr
++

The interactions did not reach the Bonferroni correction for the number of investigated interactions; MAF – minor allele frequency; OR – odds ratio

Table 3.

SNPs reported by VTE GWAS in European populations and their analysis in previously reported candidate gene studies or validation studies also in European populations.

Gene SNP Type of Report No. cases/controls
(combined)
MAF (cases) OR (95% CI) P-value References
F5 rs6025 Candidate gene approach 471/474 0.01* 6.50 (1.80–23.00) (GG vs. AG) <0.05 [1]
rs4524 Candidate gene approach 1488/1439 0.25⁎⁎ 0.77 (0.68–0.87) 2.51 × 10−5 [2]
rs1018827 Validation 1040/16,936 0.07* 1.53 (1.29–1.79) (AA vs. AG) 6.53 × 10−6 [3]
rs6427196 Validation 1040/16,936 0.09* 1.51 (1.28–1.78) (CC vs. CG) 9.21 × 10−6 [3]
rs2420371Ϫ
F2 rs1799963 Candidate gene approach 471/474 <0.01* 2.80 (1.40–5.60) <0.05 [4]
rs3136516 Candidate gene approach 428/795 0.28* 1.50 (1.00–2.20) <0.05 [5]
FGB/FGA/FGG rs2066865 Candidate gene approach 471/471 0.30* 2.40 (1.50–3.90) 0.002 [6]
rs6825454 Candidate gene approach 419/1228 0.31 2.80 × 10−4 [7]
rs7659024 Validation 1040/16,936 0.30* 1.40 (1.09–1.78) (AA vs. GG) 3.03 × 10−2 [3]
rs6536024 Validation 1040/16,936 0.46* 0.23 [3]
rs7654093ф
F11 rs3756008 Candidate gene approach 1837/2204 1.27 (1.16–1.38) <0.05 [8]
rs4253399 Candidate gene approach 1488/1439 0.41⁎⁎ 1.28 (1.15–1.43) 6.33 × 10.6 [2]
rs4253417
rs4444878
rs4253416
ABO rs2519093 Candidate gene approach 1488/1439 0.24⁎⁎ 1.68 (1.48–1.91) 8.08 × 10.16 [2]
rs505922 Validation 1040/16,936 0.35* 1.78 (1.46–2.15) (CC vs. TT) 5.17 × 10−11 [3]
rs630014 Validation 1040/16,936 0.42⁎⁎ 0.75 (0.67–0.84) 2.67 × 10−7 [2]
ABO rs8176719 Validation 1040/16,936 0.42⁎⁎ 1.47 (1.32–1.64) 5.68 × 10−12 [2]
Validation 96/148 0.48 1.62 (1.09–2.38) 0.015 [9]
rs687621 Validation 1040/16,936 0.38* 1.74 (1.43–2.10) (AA vs. GG) 5.45 × 10.10 [3]
rs495828 Validation 1040/16,936 0.16* 2.09 (1.64–2.63) (GG vs. TT) 1.72 × 10.10 [3]
rs8176750
rs657152
rs529565
rs8176645Ж
C4BPB rs3813948 Validation 1433/1402 0.07 0.25 [10]
NME7 rs16861990 Validation 1040/16,936 0.06* 4.11 (2.14–7.33) (CC vs. AA) 2.90 × 10−7 [3]
PROCR rs6087685 Validation 1040/16,936 0.39* 0.92 [3]
rs34234989Ɨ
TSPAN15 rs78707713 Validation 1040/16,936 0.05* 0.77 (0.66–0.91) (TT vs. TC) 6.22 × 10−3 [3]
rs17490626Ʊ
ZFPM2 rs4602861
SLC44A2 rs2288904 Validation 1040/16,936 0.18* 0.63 (0.44–0.89) (AA vs. GG) 2.42 × 10−2 [3]
rs9797861¥
SLC19A2 rs2038024
CCDC181 rs1208134
CNTN6 rs6764623
SUSD1 rs4979078
OTUD7A rs7164569
SV2C rs3733860
FUNDC2 rs114209171
COX7A2L rs72798544
rs113092656
EPHA3 rs60942712

MAF: minor allele frequency; OR: odds ratio.

MAF values obtained from “Ensembl” database

⁎⁎

Total MAF in the report (cases and controls)

Ϫ

SNP in high LD with rs6427196, particularly for European ancestry populations (r2>0.81), according to “Ensembl” database

ф

SNP in high LD with rs2066865 for all populations according to “Ensembl” database (r2>0.81)

Ж

SNP in high LD with rs8176719, particularly for European ancestry populations (r2>0.90), according to “Ensembl” database

Ɨ

SNP in high LD with rs6087685 for all populations according to “Ensembl” database (r2>0.86, except in Kenya population)

Ʊ

SNP in high LD with rs78707713 for most populations, particularly the European ancestry populations (r2=1), according to “Ensembl” database

¥

SNP in high LD with rs2288904 for most populations, particularly the European ancestry populations (r2>0.90), according to “Ensembl” database.

Table 4.

VTE related-genes reported by GWAS and their putative links with cancer hallmarks.

Genes HUGO nomenclature Molecular processes that promote carcinogenesis Potential cancer hallmarks
F5 Coagulation Factor V Generation of thrombin Metastasis, angiogenesis, immune evasion and apoptosis [11]
CCDC181 (C1orf114) Coiled-Coil Domain Containing 181 Despite the unknown role in carcinogenesis, this gene is frequently methylated in patients with prostate cancer [12] Genome instability and mutation
ABO ABO Blood Group Activation of adhesion molecules [13] Inflammation, immune evasion and metastasis [13, 14]
Regulation of plasmatic levels of von Willebrand factor (vWF) [11] Angiogenesis and apoptosis [15]
C4BPB Complement Component 4 Binding Protein Beta Inactivation of protein S, which is an important cofactor to activated protein C and constitutes a ligand for the Axl family of receptor tyrosine kinases [16, 17] Inflammation and apoptosis [16] Proliferation signalling, invasion and apoptosis through Axl receptor tyrosine kinase signalling [18]
NME7 NME/NM23 Family Member 7 Embryonic Stem Cell Renewal [19] Metastasis
FGB/FGG/FGA Fibrinogen Beta Chain/ Fibrinogen Gamma Chain/ Fibrinogen Alpha Chain Formation of fibrin clot Angiogenesis [11]
Immune response [20] Immune evasion and inflammation
Augmentation of the proliferative effect of fibroblast growth factor‐2 (FGF‐2) [21] Proliferative signalling and angiogenesis [21]
F11 Coagulation Factor XI Generation of Factor Xa Apoptosis [22]
Generation of thrombin Metastasis, angiogenesis, immune evasion and apoptosis [11]
SLC19A2 Solute Carrier Family 19 Member 2 Metabolism Cancer metabolism
F2 Coagulation Factor II, thrombin Generation of thrombin Metastasis, angiogenesis, immune evasion and apoptosis [11]
CNTN6 Contactin 6 Activating of Notch signalling pathway [23] Mediation of cell surface interactions Proliferative signalling and metastasis [11]
OTUD7A OTU Deubiquitinase 7A Modulation of nuclear factor kappa B (NF-κB) expression through interaction with TNF receptor associated factor 6 (TRAF6) Metastasis [24]
SV2C Synaptic Vesicle Glycoprotein 2C Modulation of dopamine release [25] Apoptosis and inflammation [26]
SUSD1 Sushi Domain Containing 1 Unknown role in carcinogenesis unknown
PROCR Protein C Receptor Protein C pathway Proliferative signalling, invasion, metastasis, apoptosis and immune evasion [27] Angiogenesis [28]
ZFPM2 (FOG2) Zinc Finger Protein, FOG Family Member 2 GATA transcriptional network Apoptosis, invasion and inflammation [29]
Angiogenesis [30]
TSPAN15 Tetraspanin 15 Mediates signal transduction events that play a role in the regulation of cell activation, growth, development and motility. Metastasis [31]
SLC44A2 Solute Carrier Family 44 Member 2 Metabolism Cancer metabolism
FUNDC2 FUN14 Domain Containing 2 Modulation of platelet survival [32] Metastasis, angiogenesis and immune evasion [33]
COX7A2L Cytochrome C Oxidase Subunit 7A2 Like Regulation of oxidative phosphorylation Cancer metabolism
EPHA3 EPH Receptor A3 Regulation of developmental events
Regulation of cytoskeletal organization, cell-cell adhesion and cell migration
Invasion and metastasis [34]
Angiogenesis [35]
B3GAT2 Beta-1,3-Glucuronyltransferase 2 Mismatch repair deficiency [36] Genome instability and mutation
THBD Thrombomodulin Protein C pathway
Regulation of adhesion molecules [37]
Angiogenesis [28]
Invasion and metastasis [37]
LEMD3 (MAN1) LEM Domain Containing 3 Regulation of transforming growth factor-beta (TGF-beta) signalling at the inner nuclear membrane Proliferative signalling, invasion and apoptosis [38]
Immune evasion [39]
LY86 (MD-1) Lymphocyte Antigen 86 Innate Immune System Inflammation
LOC100130298 HCG1816373-Like Unknown role in carcinogenesis Unknown

The data shown in Table 4 concerning the HUGO nomenclature and the molecular process involved in carcinogenesis were obtained from "Genecards" database (exceptions are referenced).

2. Experimental design, materials and methods

  • (1)

    GWAS addressing VTE susceptibility:

All SNPs statistically associated (P < 0.05) with susceptibility to VTE (deep vein thrombosis, pulmonary embolism or both) were gathered by screening NHGRI-EBI GWAS catalogue and respective articles. No restriction was made regarding the origin and age of the population. In total, 12 VTE GWAS were collected, including ten in populations of European ancestry (one searching for pairwise SNP interactions associated with disease risk and one performed to determine the genetic factors of paediatric VTE) and two in Afro-American populations (Fig. 1).

  • (2)

    Other reports reporting VTE-associated SNPs:

Fig. 1.

Fig. 1

Schematic diagram of data collection.

After gathering all GWAS-identified SNPs associated with VTE risk, data regarding validation and candidate gene reports that stated the same associations were also collected, using the NCBI database, in order to confirm the GWAS findings (Fig. 1). Only SNPs reported by VTE GWAS among adults of European ancestry were considered. Hence, only validation and candidate gene reports with adults of European ancestry with incident VTE and with no strong risk factors were taken into account. To our best knowledge, the majority of VTE GWAS-reported SNPs are currently lacking validation.

  • (3)

    Putative links between VTE-associated genes and cancer hallmarks:

A vast search using NCBI, GeneCards and Ensembl databases (Fig. 1) was made to collect data concerning VTE-associated genes and how they may be implicated in many cancer-related processes that contribute to cancer growth and progression.

Acknowledgements

We would like to thank the Liga Portuguesa Contra o Cancro-Centro Regional do Norte, Ministério da Saúde de Portugal (CFICS-45/2007), IPO-Porto Projects CI-IPOP-91-2015 and CI-IPOP-22-2015, and Fundação para a Ciência e Tecnologia (FCT).

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  • 1.Rosendaal F., Koster T., Vandenbroucke J., Reitsma P. High risk of thrombosis in patients homozygous for factor V Leiden (activated protein C resistance)[see comments] Blood. 1995;85:1504–1508. [PubMed] [Google Scholar]
  • 2.Heit J.A., Cunningham J.M., Petterson T.M., Armasu S.M., Rider D.N., de Andrade M. Genetic variation within the anticoagulant, procoagulant, fibrinolytic and innate immunity pathways as risk factors for venous thromboembolism. J. Thromb. Haemost. 2011;9:1133–1142. doi: 10.1111/j.1538-7836.2011.04272.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Crous-Bou M., De Vivo I., Camargo Jr C.A., Varraso R., Grodstein F., Jensen M.K., Kraft P., Goldhaber S.Z., Lindström S., Kabrhel C. Interactions of established risk factors and a GWAS-based genetic risk score on the risk of venous thromboembolism. Thromb. Haemost. 2016;116:705–713. doi: 10.1160/TH16-02-0172. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Poort S.R., Rosendaal F.R., Reitsma P.H., Bertina R.M. A common genetic variation in the 3′-untranslated region of the prothrombin gene is associated with elevated plasma prothrombin levels and an increase in venous thrombosis. Blood. 1996;88:3698–3703. [PubMed] [Google Scholar]
  • 5.Martinelli I., Battaglioli T., Tosetto A., Legnani C., Sottile L., Ghiotto R., Mannucci P. Prothrombin A19911G polymorphism and the risk of venous thromboembolism. J. Thromb. Haemost. 2006;4:2582–2586. doi: 10.1111/j.1538-7836.2006.02216.x. [DOI] [PubMed] [Google Scholar]
  • 6.de Willige S.U., de Visser M.C., Houwing-Duistermaat J.J., Rosendaal F.R., Vos H.L., Bertina R.M. Genetic variation in the fibrinogen gamma gene increases the risk for deep venous thrombosis by reducing plasma fibrinogen γ′ levels. Blood. 2005;106:4176–4183. doi: 10.1182/blood-2005-05-2180. [DOI] [PubMed] [Google Scholar]
  • 7.Trégouët D.-A., Heath S., Saut N., Biron-Andreani C., Schved J.-F., Pernod G., Galan P., Drouet L., Zelenika D., Juhan-Vague I. Common susceptibility alleles are unlikely to contribute as strongly as the FV and ABO loci to VTE risk: results from a GWAS approach. Blood. 2009;113:5298–5303. doi: 10.1182/blood-2008-11-190389. [DOI] [PubMed] [Google Scholar]
  • 8.Bezemer I.D., Bare L.A., Doggen C.J., Arellano A.R., Tong C., Rowland C.M., Catanese J., Young B.A., Reitsma P.H., Devlin J.J. Gene variants associated with deep vein thrombosis. JAMA. 2008;299:1306–1314. doi: 10.1001/jama.299.11.1306. [DOI] [PubMed] [Google Scholar]
  • 9.Manco L., Silva C., Fidalgo T., Martinho P., Sarmento A.B., Ribeiro M.L. Venous thromboembolism risk associated with ABO, F11 and FGG loci. Blood Coagul. Fibrinolysis. 2018;29:528–532. doi: 10.1097/MBC.0000000000000753. [DOI] [PubMed] [Google Scholar]
  • 10.Bruzelius M., Bottai M., Sabater‐Lleal M., Strawbridge R., Bergendal A., Silveira A., Sundström A., Kieler H., Hamsten A., Odeberg J. Predicting venous thrombosis in women using a combination of genetic markers and clinical risk factors. J. Thromb. Haemost. 2015;13:219–227. doi: 10.1111/jth.12808. [DOI] [PubMed] [Google Scholar]
  • 11.Tavares V., Pinto R., Assis J., Pereira D., Medeiros R. Venous thromboembolism GWAS reported genetic makeup and the hallmarks of cancer: linkage to ovarian tumour behaviour. Biochim. Biophys. Acta Rev. Cancer. 2020;1873 doi: 10.1016/j.bbcan.2019.188331. [DOI] [PubMed] [Google Scholar]
  • 12.Strand S., Orntoft T., Sorensen K. Prognostic DNA methylation markers for prostate cancer. Int. J. Mol. Sci. 2014;15:16544–16576. doi: 10.3390/ijms150916544. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Kiechl S., Paré G., Barbalic M., Qi L., Dupuis J., Dehghan A., Bis J.C., Laxton R.C., Xiao Q., Bonora E. Association of variation at the ABO locus with circulating levels of soluble intercellular adhesion molecule-1, soluble P-selectin, and soluble E-selectin: a meta-analysis. Circ. Cardiovasc. Genet. 2011;4:681–686. doi: 10.1161/CIRCGENETICS.111.960682. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Franchini M., Liumbruno G.M., Lippi G. The prognostic value of ABO blood group in cancer patients. Blood Transfus. 2016;14:434. doi: 10.2450/2015.0164-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Franchini M., Frattini F., Crestani S., Bonfanti C., Lippi G. von Willebrand factor and cancer: a renewed interest. Thromb. Res. 2013;131:290–292. doi: 10.1016/j.thromres.2013.01.015. [DOI] [PubMed] [Google Scholar]
  • 16.Rezende S.M., Simmonds R.E., Lane D.A. Coagulation, inflammation, and apoptosis: different roles for protein S and the protein S–C4b binding protein complex. Blood. 2004;103:1192–1201. doi: 10.1182/blood-2003-05-1551. [DOI] [PubMed] [Google Scholar]
  • 17.Stitt T.N., Conn G., Goret M., Lai C., Bruno J., Radzlejewski C., Mattsson K., Fisher J., Gies D.R., Jones P.F. The anticoagulation factor protein S and its relative, Gas6, are ligands for the Tyro 3/Axl family of receptor tyrosine kinases. Cell. 1995;80:661–670. doi: 10.1016/0092-8674(95)90520-0. [DOI] [PubMed] [Google Scholar]
  • 18.Paccez J.D., Vogelsang M., Parker M.I., Zerbini L.F. The receptor tyrosine kinase Axl in cancer: biological functions and therapeutic implications. Int. J. Cancer. 2014;134:1024–1033. doi: 10.1002/ijc.28246. [DOI] [PubMed] [Google Scholar]
  • 19.Wang C.H., Ma N., Lin Y.T., Wu C.C., Hsiao M., Lu F.L., Yu C.C., Chen S.Y., Lu J. A shRNA functional screen reveals Nme6 and Nme7 are crucial for embryonic stem cell renewal. Stem Cells. 2012;30:2199–2211. doi: 10.1002/stem.1203. [DOI] [PubMed] [Google Scholar]
  • 20.Girmann G., Pees H., Schwarze G., Scheurlen P. Immunosuppression by micromolecular fibrinogen degradation products in cancer. Nature. 1976;259:399. doi: 10.1038/259399a0. [DOI] [PubMed] [Google Scholar]
  • 21.Sahni A., Simpson‐Haidaris P., Sahni S., Vaday G., Francis C. Fibrinogen synthesized by cancer cells augments the proliferative effect of fibroblast growth factor‐2 (FGF‐2) J. Thromb. Haemost. 2008;6:176–183. doi: 10.1111/j.1538-7836.2007.02808.x. [DOI] [PubMed] [Google Scholar]
  • 22.Versteeg H.H., Spek C.A., Richel D.J., Peppelenbosch M.P. Coagulation factors VIIa and Xa inhibit apoptosis and anoikis. Oncogene. 2004;23:410. doi: 10.1038/sj.onc.1207066. [DOI] [PubMed] [Google Scholar]
  • 23.Cui X.-Y., Hu Q.-D., Tekaya M., Shimoda Y., Ang B.-T., Nie D.-Y., Sun L., Hu W.-P., Karsak M., Duka T. NB-3/Notch1 pathway via Deltex1 promotes neural progenitor cell differentiation into oligodendrocytes. J. Biol. Chem. 2004;279:25858–25865. doi: 10.1074/jbc.M313505200. [DOI] [PubMed] [Google Scholar]
  • 24.Xu Z., Pei L., Wang L., Zhang F., Hu X., Gui Y. Snail1-dependent transcriptional repression of Cezanne2 in hepatocellular carcinoma. Oncogene. 2014;33:2836. doi: 10.1038/onc.2013.243. [DOI] [PubMed] [Google Scholar]
  • 25.Dunn A.R., Stout K.A., Ozawa M., Lohr K.M., Hoffman C.A., Bernstein A.I., Li Y., Wang M., Sgobio C., Sastry N. Synaptic vesicle glycoprotein 2C (SV2C) modulates dopamine release and is disrupted in Parkinson disease. Proc. Natl. Acad. Sci. 2017;114:E2253–E2262. doi: 10.1073/pnas.1616892114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Lan Y.-L., Wang X., Xing J.-S., Yu Z.-L., Lou J.-C., Ma X.-C., Zhang B. Anti-cancer effects of dopamine in human glioma: involvement of mitochondrial apoptotic and anti-inflammatory pathways. Oncotarget. 2017;8:88488. doi: 10.18632/oncotarget.19691. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Ducros E., Mirshahi S., Azzazene D., Camilleri-Broët S., Mery E., Al Farsi H., Althawadi H., Besbess S., Chidiac J., Pujade-Lauraine E. Endothelial protein C receptor expressed by ovarian cancer cells as a possible biomarker of cancer onset. Int. J. Oncol. 2012;41:433–440. doi: 10.3892/ijo.2012.1492. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Uchiba M., Okajima K., Oike Y., Ito Y., Fukudome K., Isobe H., Suda T. Activated protein C induces endothelial cell proliferation by mitogen-activated protein kinase activation in vitro and angiogenesis in vivo. Circ. Res. 2004;95:34–41. doi: 10.1161/01.RES.0000133680.87668.FA. [DOI] [PubMed] [Google Scholar]
  • 29.Kumar M.S., Hancock D.C., Molina-Arcas M., Steckel M., East P., Diefenbacher M., Armenteros-Monterroso E., Lassailly F., Matthews N., Nye E. The GATA2 transcriptional network is requisite for RAS oncogene-driven non-small cell lung cancer. Cell. 2012;149:642–655. doi: 10.1016/j.cell.2012.02.059. [DOI] [PubMed] [Google Scholar]
  • 30.Choi S.H., Ruggiero D., Sorice R., Song C., Nutile T., Smith A.V., Concas M.P., Traglia M., Barbieri C., Ndiaye N.C. Six novel loci associated with circulating VEGF levels identified by a meta-analysis of genome-wide association studies. PLoS Genet. 2016;12 doi: 10.1371/journal.pgen.1005874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Zhang B., Zhang Z., Li L., Qin Y.-R., Liu H., Jiang C., Zeng T.-T., Li M.-Q., Xie D., Li Y. TSPAN15 interacts with BTRC to promote oesophageal squamous cell carcinoma metastasis via activating NF-κB signaling. Nat. Commun. 2018;9:1423. doi: 10.1038/s41467-018-03716-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Ma Q., Zhu C., Zhang W., Ta N., Zhang R., Liu L., Feng D., Cheng H., Liu J., Chen Q. Mitochondrial PIP3-binding protein FUNDC2 supports platelet survival via AKT signaling pathway. Cell Death Differ. 2019;26:321. doi: 10.1038/s41418-018-0121-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Jain S., Harris J., Ware J. Platelets: linking hemostasis and cancer. Arterioscler. Thromb. Vasc. Biol. 2010;30:2362–2367. doi: 10.1161/ATVBAHA.110.207514. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Chen X., Lu B., Ma Q., Ji C.D., Li J.Z. EphA3 inhibits migration and invasion of esophageal cancer cells by activating the mesenchymal-epithelial transition process. Int. J. Oncol. 2019;54:722–732. doi: 10.3892/ijo.2018.4639. [DOI] [PubMed] [Google Scholar]
  • 35.Lv X.Y., Wang J., Huang F., Wang P., Zhou J.G., Wei B., Li S.H. EphA3 contributes to tumor growth and angiogenesis in human gastric cancer cells. Oncol. Rep. 2018;40:2408–2416. doi: 10.3892/or.2018.6586. [DOI] [PubMed] [Google Scholar]
  • 36.Noda M., Okayama H., Tachibana K., Sakamoto W., Saito K., Min A.K.T., Ashizawa M., Nakajima T., Aoto K., Momma T. Glycosyltransferase gene expression identifies a poor prognostic colorectal cancer subtype associated with mismatch repair deficiency and incomplete glycan synthesis. Clin. Cancer Res. 2018;24:4468–4481. doi: 10.1158/1078-0432.CCR-17-3533. [DOI] [PubMed] [Google Scholar]
  • 37.Zheng N., Huo Z., Zhang B., Meng M., Cao Z., Wang Z., Zhou Q. Thrombomodulin reduces tumorigenic and metastatic potential of lung cancer cells by up-regulation of E-cadherin and down-regulation of N-cadherin expression. Biochem. Biophys. Res. Commun. 2016;476:252–259. doi: 10.1016/j.bbrc.2016.05.105. [DOI] [PubMed] [Google Scholar]
  • 38.Kaminska B., Wesolowska A., Danilkiewicz M. TGF beta signalling and its role in tumour pathogenesis. Acta Biochim. Pol. Engl. Ed. 2005;52:329. [PubMed] [Google Scholar]
  • 39.Gorelik L., Flavell R.A. Transforming growth factor-β in T-cell biology. Nat. Rev. Immunol. 2002;2:46. doi: 10.1038/nri704. [DOI] [PubMed] [Google Scholar]

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