Supplementary Document 3 Comparing Our 6 Genes with Published Hypoxia Gene Signatures

Supplementary Document 3 Comparing our 6 genes with published hypoxia gene signatures

We compared our 6 classifier genes with 6 other published transcriptomic based hypoxia gene signatures which have been derived using approaches involving clinical samples from other tumor types than cervical cancer. Three of the signatures were developed by identifying genes clustering with well‐known hypoxia‐ regulated genes: A 99‐gene HNSCC‐derived signature (1), a 26‐gene signature derived from HNSCC‐ and breast cancer samples (2), and a 70‐gene breast‐cancer derived signature (3). In addition, a 13‐gene breast‐ cancer signature derived to identify biological features associated with distant metastasis (4), a pimonidazole‐associated 32‐gene prostate cancer‐derived signature (5), and a 15‐gene HNSCC‐derived classifier constructed based on the gene expressions of more and less hypoxic tumors, as defined by pO2 electrode measurements in a training cohort (6) was addressed.

Identifying and comparing the genes in the signatures

For identifying the genes in the published signatures, Entrez Gene ID was extracted from the annotations provided and the corresponding official gene symbol was retrieved (see details in Table 1‐6 below, where genes appearing in more than one of the 6 published signatures are marked in red, and genes present among our 6 genes are marked with a green square). When comparing the genes in the 6 published signatures and our 6 genes, there were 209 unique genes, whereas 29 genes (14%) were present in more than one signature (Figure 1). Two out of our signature genes, KCTD11 and P4HA2, were present in three (1, 2, 6) or one (6) other signature, respectively.

Figure 1: The frequency of genes appearing in more than one of the seven hypoxia gene signatures.

Table 1: The Toustrup et al. 2011 signature.

Information in publication Retrieved gene information Illumina probec

SYMBOL ABI probe Entrez Gene IDa HUGO SYMBOL PROBE_ID ADM Hs02562698 133 ADM ILMN_1708934 ALDOA Hs00605108 226 ALDOA ILMN_1681374 ANKRD37 Hs00699181 353322 ANKRD37 ILMN_1756417 BNIP3 Hs00969293 664 BNIP3 ILMN_1724658 BNIP3L Hs00188949 665 BNIP3L ILMN_1718961 C3orf28 Hs01055823 26355 FAM162A ILMN_1803647 EGLN3 Hs00222966 112399 EGLN3 ILMN_1667626 KCTD11 Hs00922550 147040 KCTD11 ILMN_1777513 LOX Hs00184700 4015 LOX ILMN_1695880 NDRG1 Hs00608389 10397 NDRG1 ILMN_1809931 P4HA1 Hs00914594 5033 P4HA1 ILMN_1747442 P4HA2 Hs00989996 8974 P4HA2 ILMN_2381697

PDK1 Hs00326943 5163 PDK1 ILMN_1670256 PFKFB3 Hs00998700 5209 PFKFB3 ILMN_2186061

SLC2A1 Hs185278117b 6513 SLC2A1 ILMN_1659027 aIdentified from ABI probset annotation. bAssay was not found. Entrez Gene ID was found based on HUGO gene symbol. c For genes in which several probes were present on the Illumina‐arrays, the probe with best correlation with ABrix in our training cohort of 42 cervical cancer patients was used.

Table 2: The Eustace et al. 2013 signature.

a b Information in publication Retrieved gene information Illumina probe

SYMBOL Entrez Gene ID HUGO SYMBOL PROBE_ID

ALDOA 226 ALDOA ILMN_1681374

ANGPTL4 51129 ANGPTL4 ILMN_2386444 ANLN 54443 ANLN ILMN_1739645 BNC1 646 BNC1 ILMN_1692748

C20orf20 55257 MRGBP ILMN_1790136

CA9 768 CA9 ILMN_1725139 CDKN3 1033 CDKN3 ILMN_1666305

COL4A6 1288 COL4A6 ILMN_1811289

DCBLD1 285761 DCBLD1 ILMN_1695604 ENO1 2023 ENO1 ILMN_1710756 FAM83B 222584 FAM83B ILMN_1782863

FOSL1 8061 FOSL1 ILMN_1771841

GNAI1 2770 GNAI1 ILMN_1742044 HIG2 29923 HILPDA ILMN_1659990

KCTD11 147040 KCTD11 ILMN_1777513 KRT17 3872 KRT17 ILMN_1666845

LDHA 3939 LDHA ILMN_1807106 MRPS17 51373 MRPS17 ILMN_1804851 P4HA1 5033 P4HA1 ILMN_1747442

PGAM1 5223 PGAM1 ILMN_1661366

PGK1 5230 PGK1 ILMN_2216852

SDC1 6382 SDC1 ILMN_1800038 SLC16A1 6566 SLC16A1 ILMN_1757052 SLC2A1 6513 SLC2A1 ILMN_1659027

TPI1 7167 TPI1 ILMN_2181191

VEGFA 7422 VEGFA ILMN_1693060 aIdentified based on the symbol provided in the publication using the R annotation package org.Hs.eg.db (7). b For genes in which several probes were present on the Illumina‐arrays, the probe with best correlation with ABrix in our training cohort of 42 cervical cancer patients was used.

Table 3: The Winter et al. 2007 signature.

Information in publication Retrieved gene information Illumina probeb Entrez SYMBOL Affy_ID Gene IDa HUGO SYMBOL PROBE_ID ADORA2B 205891_at 136 ADORA2B ILMN_1703946 230630_at, 204348_s_at, AK3 225342_at,204347_at 205 AK4 ILMN_2338038 ALDOA 238996_x_at, 214687_x_at, 200966_x_at 226 ALDOA ILMN_1681374 ANGPTL4 221009_s_at,223333_s_at 51129 ANGPTL4 ILMN_2386444 Lrp2bp 227337_at 353322 ANKRD37 ILMN_1756417 ANKRD9 230972_at 122416 ANKRD9 ILMN_2048607 ANLN 222608_s_at, 1552619_a_at 54443 ANLN ILMN_1739645 B4GALT2 209413_at 8704 B4GALT2 ILMN_1806508 BCAR1 223116_at 9564 BCAR1 ILMN_1672596 BMS1L 203082_at 9790 BMS1 ILMN_1777854 BNIP3 201848_s_at,201849_at 664 BNIP3 ILMN_1724658 MGC17624 227806_at 404550 C16orf74 ILMN_1806149 203963_at, 214164_x_at, 204508_s_at, CA12 210735_s_at 771 CA12 ILMN_2382942 CA9 205199_at 768 CA9 ILMN_1725139

CDCA4 218399_s_at 55038 CDCA4 ILMN_1684045 HSPC163 218728_s_at,223993_s_at 29097 CNIH4 ILMN_1714759 COL4A5 213110_s_at 1287 COL4A5 ILMN_2375360 CORO1C 222409_at 23603 CORO1C ILMN_1745954 IL8 202859_x_at 3576 CXCL8 ILMN_2184373 DPM2 209391_at 8818 DPM2 ILMN_1732049 MGC2408 227103_s_at 9718 ECE2 ILMN_1762883 EIF2S1 201144_s_at 1965 EIF2S1 ILMN_1739821 GAPD AFFX‐HUMGAPDH/M33197_5_at 2597 GAPDH ILMN_1802252 SIP1 211114_x_at 8487 GEMIN2 ILMN_2344002 GMFB 202543_s_at 2764 GMFB ILMN_2093674 MGC14560 218461_at 51184 GPN3 ILMN_1704943 GSS 201415_at 2937 GSS ILMN_1683462 C15orf25 229208_at 55142 HAUS2 ILMN_1738482 HES2 214521_at 54626 HES2 ILMN_2094266 HIG2 1554452_a_at 29923 HILPDA ILMN_1659990 HOMER1 213793_s_at 9456 HOMER1 ILMN_1804568 IMP‐2 218847_at 10644 IGF2BP2 ILMN_1702447

KCTD11 235857_at 147040 KCTD11 ILMN_1777513 KRT17 205157_s_at 3872 KRT17 ILMN_1666845 LDHA 200650_s_at 3939 LDHA ILMN_1807106 LDLR 202068_s_at 3949 LDLR ILMN_2053415 LOC149464 232823_at NA NA NA MGC2654 218945_at 79091 METTL22 ILMN_1658290 MIF 217871_s_at 4282 MIF ILMN_1807074

MNAT1 203565_s_at 4331 MNAT1 ILMN_2083243 C20orf20 218586_at 55257 MRGBP ILMN_1790136 MRPL14 225201_s_at 64928 MRPL14 ILMN_2072603 MRPS17 218982_s_at 51373 MRPS17 ILMN_1804851 MTX1 210386_s_at 4580 MTX1 ILMN_1667222 NDRG1 200632_s_at 10397 NDRG1 ILMN_1809931 LOC56901 218484_at 56901 NDUFA4L2 ILMN_1756573 NME1 201577_at 4830 NME1 ILMN_1741133 AD‐003 223368_s_at 28989 NTMT1 ILMN_2170515 NUDT15 219347_at 55270 NUDT15 ILMN_2172202 P4HA1 207543_s_at 5033 P4HA1 ILMN_1747442 PAWR 226231_at 5074 PAWR ILMN_1806907 PDZK11 223037_at 51248 PDZD11 ILMN_1690376 PFKFB4 228499_at 5210 PFKFB4 ILMN_1653292 PGAM1 200886_s_at 5223 PGAM1 ILMN_1661366 PGF 209652_s_at 5228 PGF ILMN_1809813 200738_s_at, PGK1 227068_at,217356_s_at,200737_at 5230 PGK1 ILMN_2216852 PLAU 205479_s_at 5328 PLAU ILMN_1656057 PLEKHG3 212821_at 26030 PLEKHG3 ILMN_1780671 PPARD 37152_at 5467 PPARD ILMN_1674282 PPP2CZ 200885_at 333926 PPM1J ILMN_1799150 PPP4R1 201594_s_at 9989 PPP4R1 ILMN_1724544 PSMA7 201114_x_at 5688 PSMA7 ILMN_1701962 PSMB7 200786_at 5695 PSMB7 ILMN_1814156 PSMD2 200830_at 5708 PSMD2 ILMN_1712432 PTGFRN 224950_at, 224937_at 5738 PTGFRN ILMN_1743130 PVR 212662_at 5817 PVR ILMN_1677305 PYGL 202990_at 5836 PYGL ILMN_1696187 RAN 200750_s_at 5901 RAN ILMN_1757384 RNF24 204669_s_at 11237 RNF24 ILMN_1717809 RNPS1 200060_s_at 10921 RNPS1 ILMN_2375386 RUVBL2 201459_at 10856 RUVBL2 ILMN_2120340 S100A10 200872_at 6281 S100A10 ILMN_2046730 S100A3 206027_at 6274 S100A3 ILMN_1712545 202235_at, AFARP1/SLC16A1 202234_s_at,1557918_s_at/209900_s_at, 6566 SLC16A1 ILMN_1757052 202236_s_at SLC2A1 201250_s_at, 201249_at 6513 SLC2A1 ILMN_1659027 SLC6A10 215812_s_at 386757 SLC6A10P ILMN_1772482 SLC6A8 202219_at,210854_x_at,213843_x_at 6535 SLC6A8 ILMN_1806349 SLCO1B3 206354_at 28234 SLCO1B3 ILMN_1687319 C14orf156 221434_s_at 81892 SLIRP ILMN_1661945 SNX24 222716_s_at 28966 SNX24 ILMN_1795666 SPTB 229952_at 6710 SPTB ILMN_1663106 DKFZP564D166 224952_at 26115 TANC2 NA TEAD4 41037_at, 204281_at 7004 TEAD4 ILMN_1722824

TFAP2C 205286_at 7022 TFAP2C ILMN_1683891 TIMM23 218119_at 100287932 TIMM23 ILMN_1679555 Kua 223186_at 387521 TMEM189 ILMN_1789732 TMEM30B 213285_at 161291 TMEM30B ILMN_1752935 SMILE 1560017_at 160418 TMTC3 ILMN_2119555 CTEN 230398_at 84951 TNS4 ILMN_1716370 TPBG 203476_at 7162 TPBG NA TPD52L2 201379_s_at 7165 TPD52L2 ILMN_1699570 TPI1 213011_s_at, 200822_x_at 7167 TPI1 ILMN_2181191 KIAA1393 227653_at 57570 TRMT5 ILMN_1673872 TUBB2 208977_x_at,213726_x_at 10383 TUBB4B ILMN_1780769 VAPB 202550_s_at 9217 VAPB ILMN_1678459 VEGF 210512_s_at, 212171_x_at,211527_x_at 7422 VEGFA ILMN_1693060 VEZATIN 223675_s_at 55591 VEZT ILMN_2141398 XPO5 223056_s_at 57510 XPO5 ILMN_1759495 aIdentified based on the Affymetrix probe annotations retrieved using the annotation package hgu133plus2.db in R (8). For LOC149464 no Entrez Gene ID was found. For probes mapped to the two genes AFARP1/SLC16A1 in the publication, reannotation of the probes mapped to the same gene, SLC16A, reducing the number of genes in the signature from 99 to 98. b For genes in which several probes were present on the Illumina‐arrays, the probe with best correlation with ABrix in our training cohort of 42 cervical cancer patients was used.

Table 4: The Ghazoiu et al. 2011 signature.

Information in publication Retrieved gene information Illumina probeb Accession SYMBOL Entrez Gene HUGO number IDa SYMBOL PROBE_ID AK3L1 NM_016282 50808 AK3 ILMN_1778173 ANKRD37 NM_181726 353322 ANKRD37 ILMN_1756417 ATP1B3 NM_001679 483 ATP1B3 ILMN_1654322 ATP5G3 NM_001002256 518 ATP5G3 ILMN_1770466 BNIP3 NM_004052 664 BNIP3 ILMN_1724658 C6ORF129 NM_138493 154467 CCDC167 ILMN_1651987 CHCHD2 NM_016139 51142 CHCHD2 ILMN_2191681 C16ORF61 NM_020188 56942 CMC2 ILMN_1783333 CTSL2 NM_001333 1515 CTSV ILMN_1748352 IL8 NM_000584 3576 CXCL8 ILMN_2184373 DDIT4 NM_019058 54541 DDIT4 ILMN_1661599 EIF2S2 NM_003908 8894 EIF2S2 ILMN_1798014 EIF4EBP1 NM_004095 1978 EIF4EBP1 ILMN_1767324 COX4NB NM_006067 10328 EMC8 ILMN_1722583

ENO1 NM_001428 2023 ENO1 ILMN_1710756 ENY2 NM_020189 56943 ENY2 ILMN_2166865 RBM35A NM_017697 54845 ESRP1 ILMN_1749180 GAPDH NM_002046 2597 GAPDH ILMN_1802252 GARS NM_002047 2617 GARS ILMN_1771026 GMPS NM_003875 8833 GMPS NA GOLT1B NM_016072 51026 GOLT1B ILMN_1767837 GPI NM_000175 2821 GPI ILMN_2173451 HCCS NM_005333 3052 HCCS ILMN_1707236 IMPA2 NM_014214 3613 IMPA2 ILMN_2094061 IMPAD1 NM_017813 54928 IMPAD1 ILMN_1696311 KIF18A NM_031217 81930 KIF18A ILMN_1779153 KIF20A NM_005733 10112 KIF20A ILMN_1695658 LDHA NM_005566 3939 LDHA ILMN_1807106 MGC40489 XM_940001 146880 LOC146880 ILMN_1659110 LRRC59 NM_018509 55379 LRRC59 ILMN_1786259 LSM4 NM_012321 25804 LSM4 ILMN_1788099 MMP1 NM_002421 4312 MMP1 ILMN_1726448

MRPL13 NM_014078 28998 MRPL13 ILMN_1671158 MRPL15 NM_014175 29088 MRPL15 ILMN_2103720 MRPS17 NM_015969 51373 MRPS17 ILMN_1804851 MTCH2 NM_014342 23788 MTCH2 ILMN_1785218 MTFR1 NM_014637 9650 MTFR1 ILMN_1774028 MTHFD2 NM_006636 10797 MTHFD2 ILMN_2293322 NDRG1 NM_006096 10397 NDRG1 ILMN_1809931 NFIL3 NM_005384 4783 NFIL3 ILMN_1707312

NUP93 NM_014669 9688 NUP93 ILMN_2196569 P4HA1 NM_000917 5033 P4HA1 ILMN_1747442 PDIA6 NM_005742 10130 PDIA6 ILMN_1680626 PFKP NM_002627 5214 PFKP ILMN_1805737 PGAM1 NM_002629 5223 PGAM1 ILMN_1661366 PGK1 NM_000291 5230 PGK1 ILMN_2216852 PLOD1 NM_000302 5351 PLOD1 ILMN_1684391 NP NM_000270 4860 PNP ILMN_2172174 PRDX4 NM_006406 10549 PRDX4 ILMN_2222234 PSMA5 NM_002790 5686 PSMA5 ILMN_1759952 PSMB5 NM_002797 5693 PSMB5 ILMN_1744649 PSMD8 NM_002812 5714 PSMD8 ILMN_1733256 DSCR2 NM_203433 8624 PSMG1 ILMN_1779264 RALA NM_005402 5898 RALA ILMN_1755364 RANBP1 NM_002882 5902 RANBP1 ILMN_1721457 RNASEH2A NM_006397 10535 RNASEH2A ILMN_1810901 SEC61G NM_001012456 23480 SEC61G ILMN_2367020 SF3B5 NM_031287 83443 SF3B5 ILMN_1689389 SHMT2 NM_005412 6472 SHMT2 ILMN_1661264 SLC16A3 NM_004207 9123 SLC16A3 ILMN_2364022 SLC2A1 NM_006516 6513 SLC2A1 ILMN_1659027 SLC7A5 NM_003486 8140 SLC7A5 ILMN_1720373 SRD5A1 NM_001047 6715 SRD5A1 ILMN_1793241 TCEB1 NM_005648 6921 TCEB1 ILMN_2066020 RIS1 NM_015444 25907 TMEM158 ILMN_1792455 TMEM70 NM_017866 54968 TMEM70 ILMN_1739032 LOC388642 XM_934933 729708 TPI1P1 NA UBE2S NM_014501 27338 UBE2S ILMN_2217289 VEGF NM_001025366 7422 VEGFA ILMN_1693060 YEATS2 NM_018023 55689 YEATS2 ILMN_1676899 aIdentified based on the accession number provided in the publication using the R annotation package org.Hs.eg.db (7). bFor genes in which several probes were present on the Illumina‐arrays, the probe with best correlation with ABrix in our training cohort of 42 cervical cancer patients was used.

Table 5: The Ragnum et al. 2014 signature.

Information in publication Retrieved gene information

SYMBOL PROBE_ID Entrez Gene IDa HUGO SYMBOL ADM ILMN_1708934 133 ADM ASF1B ILMN_1695414 55723 ASF1B ASPM ILMN_1815184 259266 ASPM BIRC5 ILMN_2349459 332 BIRC5 BUB3 ILMN_2386100 9184 BUB3 CENPE ILMN_2225718 1062 CENPE MLF1IP ILMN_1679438 79682 CENPU CMTM3 ILMN_2370208 123920 CMTM3 DDIT4 ILMN_1661599 54541 DDIT4 DONSON ILMN_1758629 29980 DONSON DSP ILMN_1655614 1832 DSP DTL ILMN_1779711 51514 DTL FER1L4 ILMN_2206722 80307 FER1L4 FOXM1 ILMN_2344971 2305 FOXM1

G6PD ILMN_2261122 2539 G6PD C7orf68 ILMN_1659990 29923 HILPDA HJURP ILMN_1703906 55355 HJURP MCM2 ILMN_1681503 4171 MCM2 MEP1A ILMN_1659984 4224 MEP1A MTMR2 ILMN_2351029 8898 MTMR2 P4HA1 ILMN_1693334 5033 P4HA1 PGAM4 ILMN_2102515 441531 PGAM4 PKM2 ILMN_1775327 5315 PKM FAM80A ILMN_1706664 284716 RIMKLA RNASE4 ILMN_2239408 6038 RNASE4 SCD ILMN_1689329 6319 SCD SPAG4 ILMN_1684620 6676 SPAG4 TDG ILMN_1777096 6996 TDG TRIP13 ILMN_1796589 9319 TRIP13 UNG ILMN_1683120 7374 UNG XRCC6 ILMN_1743097 2547 XRCC6 ZWINT ILMN_1653209 11130 ZWINT aRetrieved from Illumina annotations.

Table 6: The Hu et al. 2009 signature.

Information in publication Retrieved gene informationa Illumina probeb

SYMBOL Entrez HUGO Gene ID SYMBOL PROBE_ID ADM 133 ADM ILMN_1708934 ANGPTL4 51129 ANGPTL4 ILMN_2386444 DDIT4 54541 DDIT4 ILMN_1661599 FABP5 2171 FABP5 ILMN_2146766 C14orf58 55640 FLVCR2 ILMN_2204876 GAL 51083 GAL ILMN_1682015 NDRG1 10397 NDRG1 ILMN_1809931 PLOD 5351 PLOD1 ILMN_1684391 NP 4860 PNP ILMN_2172174 RRAGD 58528 RRAGD ILMN_1699772 SLC16A3 9123 SLC16A3 ILMN_2364022 UCHL1 7345 UCHL1 ILMN_1757387 VEGF 7422 VEGFA ILMN_1693060 aIdentified the official gene symbol and Entrez Gene ID based on the symbol provided in the publication using the R annotation package org.Hs.eg.db (7). bFor genes in which several probes were present on the Illumina‐arrays, the probe with best correlation with ABrix in our training cohort of 42 cervical cancer patients was used.

Calculation of a continuous hypoxia score for each signature

Different methods were used in the published studies to calculate a continuous hypoxia score based on the signatures (1‐5). In addition, Toustrup et al. (6) constructed a classifier similar to our 6‐gene classifier without any continuous hypoxia measure. To compare our 6 classifier genes with the published signatures in our cervical cancer data set of 281 patients, we first calculated a continuous hypoxia score for each patient by three methods using data from our Illumina expression arrays:

1. Mean of median‐centered, log2‐transformed values as in (4, 5).

2. Median of log2 expression values as in (2, 3).

3. Fractional rank (0‐1) of median of log2 expression values as in (1).

The Illumina probes used in the calculations are listed in Table 1‐6. For four of the signatures, data were available for all genes (2, 4‐6), while for the Winter et al. signature (1), data were not found for three of the 98 genes (two of the genes was found to be the same gene after reannotation of the provided probes in the original publication, see Table 3), and for Ghazoui et al. (3) data were not found for two of the 70 genes.

Univariate COX PH analysis and ABrix‐correlation of the signatures in cervical cancer

To compare the prognostic values of the hypoxia gene signatures, univariate COX PH analysis of the continuous hypoxia score of each signature was performed in our cervical cancer data set. The signature of our six classifier genes was found to be the most prognostic signature (Table 7).

To evaluate the hypoxia gene signatures’ ability to reflect an ABrix‐associated hypoxic phenotype in cervical cancer, Spearman’s rank correlation analysis was performed using data for all the 59 squamous cell carcinomas with available ABrix‐data included in our study (Table 7). Several signatures showed a significant correlation to ABrix, however, the correlation was much stronger for the signature of our six classifier genes.

Table 7: Univariate COX PH analysis for progression‐free survival and correlation to ABrix for the hypoxia gene signatures.

b c Univariate COX PH analysis Correlation with ABrix 95% CI 95% CI Signaturea P HR P ρ lower upper Fjeldbo 6 genes 0.008 2.12 1.22 3.68 1.30E‐06 ‐0.59 Hu et al. 2009 0.026 2.56 1.12 5.89 0.004 ‐0.38 Eustace et al. 2013 0.061 1.61 0.98 2.64 0.029 ‐0.28 Winter et al. 2007 0.191 1.69 0.77 3.69 0.101 ‐0.22 Toustrup et al. 2011 0.248 1.42 0.78 2.59 0.036 ‐0.27 Ragnum et al. 2014 0.637 1.39 0.35 5.54 0.900 ‐0.02 Ghazoui et al. 2011 0.694 1.15 0.57 2.35 0.041 ‐0.27 aBased on 281 squamous cell carcinomas of the uterine cervix. All three methods for hypoxia score calculation were tested for all signatures. Results applying the method used in the original publications are shown. For the Toustrup et al. 2011 signature, results using method 1 for hypoxia score calculation are shown. bFor signatures without statistical significant association to recurrence (P > 0.05), application of one of the other methods for hypoxia score calculation did not lead to statistically significant results. Continuous hypoxia scores were used in the analysis. c Spearman’s rank correlation analysis based on 59 squamous cell carcinomas of the uterine cervix with available ABrix data. P‐values and correlation coefficients (ρ) are listed. Abbreviations: HR, hazard ratio; CI, confidence interval.

Cumulative incidence in cervical cancer patients stratified by the signatures A competing risk model was used to further compare the prognostic value of the hypoxia gene signatures in our cervical cancer data set. After stratifying the patients based on each signature, a significant difference in disease progression between the two groups was found only for the signature of our six classifier genes (Figure2).

Figure 2: Cumulative incidence of disease progression for 281 patients classified by seven different hypoxia gene signatures; six classifier genes in this work (Fjeldbo) and six published signatures: Ragnum et al. (5), Toustrup et al. (6), Winter et al. (1), Eustace et al. (2), Ghazoui et al. (3), and Hu et al. (4). The hypoxia score was calculated as in the original publication, and for Toustrup et al. (6) we used method 1. The patients were stratified as in the original publications: Fjeldbo and Toustrup: 65% low, 35% high; Ragnum: 40% low, 60% high; Winter: 75% low, 25% high; Eustace and Hu: low score for ≤ median, high score for > median. For Ghazoui, no stratification was found in the original publication, and the stratification with the largest separation among those tested is shown, i.e. 65% low and 35% high. For all signatures, other stratifications were also tested without achieving statistically significant separation of the groups. 60 months recurrence probability, 95% confidence intervals for hazard ratio (HR), P‐values from Gray’s test and number of patients at risk are indicated; death from other causes than cervical cancer was included as a competing event (n=14).

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