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pmid:33028329

Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma.

Pancheng Wu · Yi Zheng · Yanyu Wang · Yadong Wang · Naixin Liang

Journal of translational medicine · 2020 doi:10.1186/s12967-020-02545-z

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Experiment

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title
Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma.
doi
10.1186/s12967-020-02545-z
pmid
33028329
authors array · 5 items
[0]
Pancheng Wu
[1]
Yi Zheng
[2]
Yanyu Wang
[3]
Yadong Wang
[4]
Naixin Liang
journal
Journal of translational medicine
year
2020
abstract
BACKGROUND: The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD. METHODS: The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan-Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts. RESULTS: A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29-8.11; P = 6.16E-06), GSE31210 (HR = 11.91, 95% CI 4.15-34.19; P = 4.10E-06), GSE50081 (HR = 3.63, 95% CI 1.90-6.95; P = 9.95E-05), the combined data set (HR = 3.15, 95% CI 1.98-5.02; P = 1.26E-06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49-3.13; P = 4.54E-05) and GSE72094 (HR = 2.95, 95% CI 1.86-4.70; P = 4.79E-06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design. CONCLUSIONS: Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.
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Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set).
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GSM773680
[141]
GSM773681
[142]
GSM773682
[143]
GSM773683
[144]
GSM773684
[145]
GSM773685
[146]
GSM773686
[147]
GSM773687
[148]
GSM773688
[149]
GSM773689
[150]
GSM773690
[151]
GSM773691
[152]
GSM773692
[153]
GSM773693
[154]
GSM773694
[155]
GSM773695
[156]
GSM773696
[157]
GSM773697
[158]
GSM773698
[159]
GSM773699
[160]
GSM773700
[161]
GSM773701
[162]
GSM773702
[163]
GSM773703
[164]
GSM773704
[165]
GSM773705
[166]
GSM773706
[167]
GSM773707
[168]
GSM773708
[169]
GSM773709
[170]
GSM773710
[171]
GSM773711
[172]
GSM773712
[173]
GSM773713
[174]
GSM773714
[175]
GSM773715
[176]
GSM773716
[177]
GSM773717
[178]
GSM773718
[179]
GSM773719
[180]
GSM773720
[181]
GSM773721
[182]
GSM773722
[183]
GSM773723
[184]
GSM773724
[185]
GSM773725
[186]
GSM773726
[187]
GSM773727
[188]
GSM773728
[189]
GSM773729
[190]
GSM773730
[191]
GSM773731
[192]
GSM773732
[193]
GSM773733
[194]
GSM773734
[195]
GSM773735
[196]
GSM773736
[197]
GSM773737
[198]
GSM773738
[199]
GSM773739
[200]
GSM773740
[201]
GSM773741
[202]
GSM773742
[203]
GSM773743
[204]
GSM773744
[205]
GSM773745
[206]
GSM773746
[207]
GSM773747
[208]
GSM773748
[209]
GSM773749
[210]
GSM773750
[211]
GSM773751
[212]
GSM773752
[213]
GSM773753
[214]
GSM773754
[215]
GSM773755
[216]
GSM773756
[217]
GSM773757
[218]
GSM773758
[219]
GSM773759
[220]
GSM773760
[221]
GSM773761
[222]
GSM773762
[223]
GSM773763
[224]
GSM773764
[225]
GSM773765
[226]
GSM773766
[227]
GSM773767
[228]
GSM773768
[229]
GSM773769
[230]
GSM773770
[231]
GSM773771
[232]
GSM773772
[233]
GSM773773
[234]
GSM773774
[235]
GSM773775
[236]
GSM773776
[237]
GSM773777
[238]
GSM773778
[239]
GSM773779
[240]
GSM773780
[241]
GSM773781
[242]
GSM773782
[243]
GSM773783
[244]
GSM773784
[245]
GSM773785
sample_count
246
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Gene expression data for pathological stage I-II lung adenocarcinomas
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 15 fields
id
data:geo:GSE50081
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50081
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE50081
version
null
note
The data sets analyzed in this study are available on the public databases.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The data sets analyzed in this study are available on the public databases.
access_statement_kind
data_availability_statement
sample_accessions array · 181 items
[0]
GSM1213669
[1]
GSM1213670
[2]
GSM1213671
[3]
GSM1213672
[4]
GSM1213673
[5]
GSM1213674
[6]
GSM1213675
[7]
GSM1213676
[8]
GSM1213677
[9]
GSM1213678
[10]
GSM1213679
[11]
GSM1213680
[12]
GSM1213681
[13]
GSM1213682
[14]
GSM1213683
[15]
GSM1213684
[16]
GSM1213685
[17]
GSM1213686
[18]
GSM1213687
[19]
GSM1213688
[20]
GSM1213689
[21]
GSM1213690
[22]
GSM1213691
[23]
GSM1213692
[24]
GSM1213693
[25]
GSM1213694
[26]
GSM1213695
[27]
GSM1213696
[28]
GSM1213697
[29]
GSM1213698
[30]
GSM1213699
[31]
GSM1213700
[32]
GSM1213701
[33]
GSM1213702
[34]
GSM1213703
[35]
GSM1213704
[36]
GSM1213705
[37]
GSM1213706
[38]
GSM1213707
[39]
GSM1213708
[40]
GSM1213709
[41]
GSM1213710
[42]
GSM1213711
[43]
GSM1213712
[44]
GSM1213713
[45]
GSM1213714
[46]
GSM1213715
[47]
GSM1213716
[48]
GSM1213717
[49]
GSM1213718
[50]
GSM1213719
[51]
GSM1213720
[52]
GSM1213721
[53]
GSM1213722
[54]
GSM1213723
[55]
GSM1213724
[56]
GSM1213725
[57]
GSM1213726
[58]
GSM1213727
[59]
GSM1213728
[60]
GSM1213729
[61]
GSM1213730
[62]
GSM1213731
[63]
GSM1213732
[64]
GSM1213733
[65]
GSM1213734
[66]
GSM1213735
[67]
GSM1213736
[68]
GSM1213737
[69]
GSM1213738
[70]
GSM1213739
[71]
GSM1213740
[72]
GSM1213741
[73]
GSM1213742
[74]
GSM1213743
[75]
GSM1213744
[76]
GSM1213745
[77]
GSM1213746
[78]
GSM1213747
[79]
GSM1213748
[80]
GSM1213749
[81]
GSM1213750
[82]
GSM1213751
[83]
GSM1213752
[84]
GSM1213753
[85]
GSM1213754
[86]
GSM1213755
[87]
GSM1213756
[88]
GSM1213757
[89]
GSM1213758
[90]
GSM1213759
[91]
GSM1213760
[92]
GSM1213761
[93]
GSM1213762
[94]
GSM1213763
[95]
GSM1213764
[96]
GSM1213765
[97]
GSM1213766
[98]
GSM1213767
[99]
GSM1213768
[100]
GSM1213769
[101]
GSM1213770
[102]
GSM1213771
[103]
GSM1213772
[104]
GSM1213773
[105]
GSM1213774
[106]
GSM1213775
[107]
GSM1213776
[108]
GSM1213777
[109]
GSM1213778
[110]
GSM1213779
[111]
GSM1213780
[112]
GSM1213781
[113]
GSM1213782
[114]
GSM1213783
[115]
GSM1213784
[116]
GSM1213785
[117]
GSM1213786
[118]
GSM1213787
[119]
GSM1213788
[120]
GSM1213789
[121]
GSM1213790
[122]
GSM1213791
[123]
GSM1213792
[124]
GSM1213793
[125]
GSM1213794
[126]
GSM1213795
[127]
GSM1213796
[128]
GSM1213797
[129]
GSM1213798
[130]
GSM1213799
[131]
GSM1213800
[132]
GSM1213801
[133]
GSM1213802
[134]
GSM1213803
[135]
GSM1213804
[136]
GSM1213805
[137]
GSM1213806
[138]
GSM1213807
[139]
GSM1213808
[140]
GSM1213809
[141]
GSM1213810
[142]
GSM1213811
[143]
GSM1213812
[144]
GSM1213813
[145]
GSM1213814
[146]
GSM1213815
[147]
GSM1213816
[148]
GSM1213817
[149]
GSM1213818
[150]
GSM1213819
[151]
GSM1213820
[152]
GSM1213821
[153]
GSM1213822
[154]
GSM1213823
[155]
GSM1213824
[156]
GSM1213825
[157]
GSM1213826
[158]
GSM1213827
[159]
GSM1213828
[160]
GSM1213829
[161]
GSM1213830
[162]
GSM1213831
[163]
GSM1213832
[164]
GSM1213833
[165]
GSM1213834
[166]
GSM1213835
[167]
GSM1213836
[168]
GSM1213837
[169]
GSM1213838
[170]
GSM1213839
[171]
GSM1213840
[172]
GSM1213841
[173]
GSM1213842
[174]
GSM1213843
[175]
GSM1213844
[176]
GSM1213845
[177]
GSM1213846
[178]
GSM1213847
[179]
GSM1213848
[180]
GSM1213849
sample_count
181
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Validation of a histology-independent prognostic gene signature for early stage, non-small cell lung cancer including stage IA patients
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 15 fields
id
data:geo:GSE72094
role
raw
format
geo-series
media_type
application/vnd.ncbi.geo-series+json
uri
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE72094
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE72094
version
null
note
The data sets analyzed in this study are available on the public databases.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The data sets analyzed in this study are available on the public databases.
access_statement_kind
data_availability_statement
sample_accessions array · 442 items
[0]
GSM1854797
[1]
GSM1854798
[2]
GSM1854799
[3]
GSM1854800
[4]
GSM1854801
[5]
GSM1854802
[6]
GSM1854803
[7]
GSM1854804
[8]
GSM1854805
[9]
GSM1854806
[10]
GSM1854807
[11]
GSM1854808
[12]
GSM1854809
[13]
GSM1854810
[14]
GSM1854811
[15]
GSM1854812
[16]
GSM1854813
[17]
GSM1854814
[18]
GSM1854815
[19]
GSM1854816
[20]
GSM1854817
[21]
GSM1854818
[22]
GSM1854819
[23]
GSM1854820
[24]
GSM1854821
[25]
GSM1854822
[26]
GSM1854823
[27]
GSM1854824
[28]
GSM1854825
[29]
GSM1854826
[30]
GSM1854827
[31]
GSM1854828
[32]
GSM1854829
[33]
GSM1854830
[34]
GSM1854831
[35]
GSM1854832
[36]
GSM1854833
[37]
GSM1854834
[38]
GSM1854835
[39]
GSM1854836
[40]
GSM1854837
[41]
GSM1854838
[42]
GSM1854839
[43]
GSM1854840
[44]
GSM1854841
[45]
GSM1854842
[46]
GSM1854843
[47]
GSM1854844
[48]
GSM1854845
[49]
GSM1854846
[50]
GSM1854847
[51]
GSM1854848
[52]
GSM1854849
[53]
GSM1854850
[54]
GSM1854851
[55]
GSM1854852
[56]
GSM1854853
[57]
GSM1854854
[58]
GSM1854855
[59]
GSM1854856
[60]
GSM1854857
[61]
GSM1854858
[62]
GSM1854859
[63]
GSM1854860
[64]
GSM1854861
[65]
GSM1854862
[66]
GSM1854863
[67]
GSM1854864
[68]
GSM1854865
[69]
GSM1854866
[70]
GSM1854867
[71]
GSM1854868
[72]
GSM1854869
[73]
GSM1854870
[74]
GSM1854871
[75]
GSM1854872
[76]
GSM1854873
[77]
GSM1854874
[78]
GSM1854875
[79]
GSM1854876
[80]
GSM1854877
[81]
GSM1854878
[82]
GSM1854879
[83]
GSM1854880
[84]
GSM1854881
[85]
GSM1854882
[86]
GSM1854883
[87]
GSM1854884
[88]
GSM1854885
[89]
GSM1854886
[90]
GSM1854887
[91]
GSM1854888
[92]
GSM1854889
[93]
GSM1854890
[94]
GSM1854891
[95]
GSM1854892
[96]
GSM1854893
[97]
GSM1854894
[98]
GSM1854895
[99]
GSM1854896
[100]
GSM1854897
[101]
GSM1854898
[102]
GSM1854899
[103]
GSM1854900
[104]
GSM1854901
[105]
GSM1854902
[106]
GSM1854903
[107]
GSM1854904
[108]
GSM1854905
[109]
GSM1854906
[110]
GSM1854907
[111]
GSM1854908
[112]
GSM1854909
[113]
GSM1854910
[114]
GSM1854911
[115]
GSM1854912
[116]
GSM1854913
[117]
GSM1854914
[118]
GSM1854915
[119]
GSM1854916
[120]
GSM1854917
[121]
GSM1854918
[122]
GSM1854919
[123]
GSM1854920
[124]
GSM1854921
[125]
GSM1854922
[126]
GSM1854923
[127]
GSM1854924
[128]
GSM1854925
[129]
GSM1854926
[130]
GSM1854927
[131]
GSM1854928
[132]
GSM1854929
[133]
GSM1854930
[134]
GSM1854931
[135]
GSM1854932
[136]
GSM1854933
[137]
GSM1854934
[138]
GSM1854935
[139]
GSM1854936
[140]
GSM1854937
[141]
GSM1854938
[142]
GSM1854939
[143]
GSM1854940
[144]
GSM1854941
[145]
GSM1854942
[146]
GSM1854943
[147]
GSM1854944
[148]
GSM1854945
[149]
GSM1854946
[150]
GSM1854947
[151]
GSM1854948
[152]
GSM1854949
[153]
GSM1854950
[154]
GSM1854951
[155]
GSM1854952
[156]
GSM1854953
[157]
GSM1854954
[158]
GSM1854955
[159]
GSM1854956
[160]
GSM1854957
[161]
GSM1854958
[162]
GSM1854959
[163]
GSM1854960
[164]
GSM1854961
[165]
GSM1854962
[166]
GSM1854963
[167]
GSM1854964
[168]
GSM1854965
[169]
GSM1854966
[170]
GSM1854967
[171]
GSM1854968
[172]
GSM1854969
[173]
GSM1854970
[174]
GSM1854971
[175]
GSM1854972
[176]
GSM1854973
[177]
GSM1854974
[178]
GSM1854975
[179]
GSM1854976
[180]
GSM1854977
[181]
GSM1854978
[182]
GSM1854979
[183]
GSM1854980
[184]
GSM1854981
[185]
GSM1854982
[186]
GSM1854983
[187]
GSM1854984
[188]
GSM1854985
[189]
GSM1854986
[190]
GSM1854987
[191]
GSM1854988
[192]
GSM1854989
[193]
GSM1854990
[194]
GSM1854991
[195]
GSM1854992
[196]
GSM1854993
[197]
GSM1854994
[198]
GSM1854995
[199]
GSM1854996
[200]
GSM1854997
[201]
GSM1854998
[202]
GSM1854999
[203]
GSM1855000
[204]
GSM1855001
[205]
GSM1855002
[206]
GSM1855003
[207]
GSM1855004
[208]
GSM1855005
[209]
GSM1855006
[210]
GSM1855007
[211]
GSM1855008
[212]
GSM1855009
[213]
GSM1855010
[214]
GSM1855011
[215]
GSM1855012
[216]
GSM1855013
[217]
GSM1855014
[218]
GSM1855015
[219]
GSM1855016
[220]
GSM1855017
[221]
GSM1855018
[222]
GSM1855019
[223]
GSM1855020
[224]
GSM1855021
[225]
GSM1855022
[226]
GSM1855023
[227]
GSM1855024
[228]
GSM1855025
[229]
GSM1855026
[230]
GSM1855027
[231]
GSM1855028
[232]
GSM1855029
[233]
GSM1855030
[234]
GSM1855031
[235]
GSM1855032
[236]
GSM1855033
[237]
GSM1855034
[238]
GSM1855035
[239]
GSM1855036
[240]
GSM1855037
[241]
GSM1855038
[242]
GSM1855039
[243]
GSM1855040
[244]
GSM1855041
[245]
GSM1855042
[246]
GSM1855043
[247]
GSM1855044
[248]
GSM1855045
[249]
GSM1855046
[250]
GSM1855047
[251]
GSM1855048
[252]
GSM1855049
[253]
GSM1855050
[254]
GSM1855051
[255]
GSM1855052
[256]
GSM1855053
[257]
GSM1855054
[258]
GSM1855055
[259]
GSM1855056
[260]
GSM1855057
[261]
GSM1855058
[262]
GSM1855059
[263]
GSM1855060
[264]
GSM1855061
[265]
GSM1855062
[266]
GSM1855063
[267]
GSM1855064
[268]
GSM1855065
[269]
GSM1855066
[270]
GSM1855067
[271]
GSM1855068
[272]
GSM1855069
[273]
GSM1855070
[274]
GSM1855071
[275]
GSM1855072
[276]
GSM1855073
[277]
GSM1855074
[278]
GSM1855075
[279]
GSM1855076
[280]
GSM1855077
[281]
GSM1855078
[282]
GSM1855079
[283]
GSM1855080
[284]
GSM1855081
[285]
GSM1855082
[286]
GSM1855083
[287]
GSM1855084
[288]
GSM1855085
[289]
GSM1855086
[290]
GSM1855087
[291]
GSM1855088
[292]
GSM1855089
[293]
GSM1855090
[294]
GSM1855091
[295]
GSM1855092
[296]
GSM1855093
[297]
GSM1855094
[298]
GSM1855095
[299]
GSM1855096
[300]
GSM1855097
[301]
GSM1855098
[302]
GSM1855099
[303]
GSM1855100
[304]
GSM1855101
[305]
GSM1855102
[306]
GSM1855103
[307]
GSM1855104
[308]
GSM1855105
[309]
GSM1855106
[310]
GSM1855107
[311]
GSM1855108
[312]
GSM1855109
[313]
GSM1855110
[314]
GSM1855111
[315]
GSM1855112
[316]
GSM1855113
[317]
GSM1855114
[318]
GSM1855115
[319]
GSM1855116
[320]
GSM1855117
[321]
GSM1855118
[322]
GSM1855119
[323]
GSM1855120
[324]
GSM1855121
[325]
GSM1855122
[326]
GSM1855123
[327]
GSM1855124
[328]
GSM1855125
[329]
GSM1855126
[330]
GSM1855127
[331]
GSM1855128
[332]
GSM1855129
[333]
GSM1855130
[334]
GSM1855131
[335]
GSM1855132
[336]
GSM1855133
[337]
GSM1855134
[338]
GSM1855135
[339]
GSM1855136
[340]
GSM1855137
[341]
GSM1855138
[342]
GSM1855139
[343]
GSM1855140
[344]
GSM1855141
[345]
GSM1855142
[346]
GSM1855143
[347]
GSM1855144
[348]
GSM1855145
[349]
GSM1855146
[350]
GSM1855147
[351]
GSM1855148
[352]
GSM1855149
[353]
GSM1855150
[354]
GSM1855151
[355]
GSM1855152
[356]
GSM1855153
[357]
GSM1855154
[358]
GSM1855155
[359]
GSM1855156
[360]
GSM1855157
[361]
GSM1855158
[362]
GSM1855159
[363]
GSM1855160
[364]
GSM1855161
[365]
GSM1855162
[366]
GSM1855163
[367]
GSM1855164
[368]
GSM1855165
[369]
GSM1855166
[370]
GSM1855167
[371]
GSM1855168
[372]
GSM1855169
[373]
GSM1855170
[374]
GSM1855171
[375]
GSM1855172
[376]
GSM1855173
[377]
GSM1855174
[378]
GSM1855175
[379]
GSM1855176
[380]
GSM1855177
[381]
GSM1855178
[382]
GSM1855179
[383]
GSM1855180
[384]
GSM1855181
[385]
GSM1855182
[386]
GSM1855183
[387]
GSM1855184
[388]
GSM1855185
[389]
GSM1855186
[390]
GSM1855187
[391]
GSM1855188
[392]
GSM1855189
[393]
GSM1855190
[394]
GSM1855191
[395]
GSM1855192
[396]
GSM1855193
[397]
GSM1855194
[398]
GSM1855195
[399]
GSM1855196
[400]
GSM1855197
[401]
GSM1855198
[402]
GSM1855199
[403]
GSM1855200
[404]
GSM1855201
[405]
GSM1855202
[406]
GSM1855203
[407]
GSM1855204
[408]
GSM1855205
[409]
GSM1855206
[410]
GSM1855207
[411]
GSM1855208
[412]
GSM1855209
[413]
GSM1855210
[414]
GSM1855211
[415]
GSM1855212
[416]
GSM1855213
[417]
GSM1855214
[418]
GSM1855215
[419]
GSM1855216
[420]
GSM1855217
[421]
GSM1855218
[422]
GSM1855219
[423]
GSM1855220
[424]
GSM1855221
[425]
GSM1855222
[426]
GSM1855223
[427]
GSM1855224
[428]
GSM1855225
[429]
GSM1855226
[430]
GSM1855227
[431]
GSM1855228
[432]
GSM1855229
[433]
GSM1855230
[434]
GSM1855231
[435]
GSM1855232
[436]
GSM1855233
[437]
GSM1855234
[438]
GSM1855235
[439]
GSM1855236
[440]
GSM1855237
[441]
GSM1855238
sample_count
442
group_sizes
null
group_sizes_basis
null
platform
15048
taxon
Homo sapiens
title
KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 16 fields
id
asset:table:pmid:33028329:1
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:8983a07500daa7825c84d88cd0c3198750bcd4dec515fa190e5b2e8ba927fcdd
bytes
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open
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verified
reader
read_table
reader_status
available
identifier
section[12]/table-wrap[1]#Tab1
version
null
note
Univariate and multivariate Cox regression analyses of the 21-gene signature and OS in the training set (early-stage LUAD)
structure object · 5 fields
pmcid
PMC7542703
section_index
12
section_title
The 21-gene prognostic signature is an independent prognostic factor
row_count
30
column_count
9
table object · 8 fields
label
Table 1
caption
Univariate and multivariate Cox regression analyses of the 21-gene signature and OS in the training set (early-stage LUAD)
rows array · 30 items
[0] array · 4 items
[0]
Variables
[1]
Patients (N)
[2]
Univariate analysis
[3]
Multivariate analysis
[1] array · 6 items
[0]
HR
[1]
95% CI
[2]
p value
[3]
HR
[4]
95% CI
[5]
p value
[2] array · 1 item
[0]
GSE30219
[3] array · 9 items
[0]
Age
[1]
> 65/ ≤ 65
[2]
23/59
[3]
1.765
[4]
0.946–3.295
[5]
7.42E−02
[6]
2.36
[7]
1.179–4.724
[8]
1.53E−02
[4] array · 9 items
[0]
Gender
[1]
Male/female
[2]
64/18
[3]
1.148
[4]
0.532–2.478
[5]
7.24E−01
[6]
[7]
[8]
[5] array · 9 items
[0]
T stage
[1]
T2/T1
[2]
12/69
[3]
2.046
[4]
1.019–4.107
[5]
4.40E−02
[6]
0.982
[7]
0.352–1.94
[8]
9.63E−01
[6] array · 9 items
[0]
Risk score
[1]
High/low
[2]
34/48
[3]
4.308
[4]
2.287–8.114
[5]
6.16E−06
[6]
5.012
[7]
2.498–10.058
[8]
5.75E−06
[7] array · 1 item
[0]
GSE31210
[8] array · 9 items
[0]
Age
[1]
> 65/ ≤ 65
[2]
47/157
[3]
2.779
[4]
1.349–5.724
[5]
5.59E−03
[6]
3.172
[7]
1.445–6.964
[8]
4.01E−03
[9] array · 9 items
[0]
Gender
[1]
Male/female
[2]
95/109
[3]
1.686
[4]
0.818–3.476
[5]
1.57E−01
[6]
1.033
[7]
0.347–3.078
[8]
9.54E−01
[10] array · 9 items
[0]
Stage
[1]
II/I
[2]
42/462
[3]
4.297
[4]
2.092–8.828
[5]
7.21E−05
[6]
2.444
[7]
1.152–5.186
[8]
1.99E−02
[11] array · 9 items
[0]
Smoking
[1]
Yes/no
[2]
99/105
[3]
1.908
[4]
0.918–3.966
[5]
8.35E−02
[6]
1.726
[7]
0.565–5.271
[8]
3.38E−01
[12] array · 9 items
[0]
ALK fusion
[1]
±
[2]
7/197
[3]
1.057
[4]
0.144–7.777
[5]
9.56E−01
[6]
[7]
[8]
[13] array · 9 items
[0]
EGFR mutation
[1]
±
[2]
116/88
[3]
0.46
[4]
0.222–0.956
[5]
3.76E−02
[6]
1.658
[7]
0.512–5.375
[8]
3.99E−01
[14] array · 9 items
[0]
KRAS mutation
[1]
±
[2]
19/185
[3]
0.992
[4]
0.3–3.282
[5]
9.89E−01
[6]
[7]
[8]
[15] array · 9 items
[0]
Triple negative
[1]
Yes/no
[2]
62/142
[3]
0.436
[4]
0.212–0.894
[5]
2.34E−02
[6]
0.543
[7]
0.174–1.698
[8]
2.94E−01
[16] array · 9 items
[0]
MYC copy
[1]
High/low
[2]
16/187
[3]
0.767
[4]
0.183–3.22
[5]
0.716942752
[6]
[7]
[8]
[17] array · 9 items
[0]
Risk score
[1]
High/low
[2]
81/123
[3]
11.914
[4]
4.151–34.193
[5]
4.10E−06
[6]
8.817
[7]
2.864–27.14
[8]
1.48E−04
[18] array · 1 item
[0]
GSE50081
[19] array · 9 items
[0]
Age
[1]
> 65/ ≤ 65
[2]
87/40
[3]
1.455
[4]
0.774–2.735
[5]
2.44E−01
[6]
[7]
[8]
[20] array · 9 items
[0]
Gender
[1]
Male/female
[2]
65/62
[3]
1.41
[4]
0.807–2.463
[5]
2.28E−01
[6]
[7]
[8]
[21] array · 9 items
[0]
Stage
[1]
II/I
[2]
35/92
[3]
2.443
[4]
1.383–4.316
[5]
2.10E−03
[6]
1.905
[7]
1.068–3.399
[8]
2.90E−02
[22] array · 9 items
[0]
T stage
[1]
T2/T1
[2]
82/30
[3]
2.435
[4]
1.214–4.883
[5]
1.22E−02
[6]
1.625
[7]
0.785–3.365
[8]
1.91E−01
[23] array · 9 items
[0]
Smoking
[1]
Yes/no
[2]
92/23
[3]
1.682
[4]
0.75–3.776
[5]
2.07E−01
[6]
[7]
[8]
[24] array · 9 items
[0]
Risk score
[1]
High/low
[2]
72/55
[3]
3.632
[4]
1.897–6.953
[5]
9.95E−05
[6]
2.736
[7]
1.373–5.455
[8]
4.24E−03
[25] array · 1 item
[0]
Combined data set
[26] array · 9 items
[0]
Age
[1]
> 65/ ≤ 65
[2]
157/256
[3]
2.314
[4]
1.621–3.304
[5]
3.82E−06
[6]
2.414
[7]
1.686–3.456
[8]
1.49E−06
[27] array · 9 items
[0]
Gender
[1]
Male/female
[2]
224/189
[3]
1.574
[4]
1.081–2.291
[5]
1.80E−02
[6]
1.582
[7]
1.084–2.307
[8]
1.73E−02
[28] array · 9 items
[0]
Stage
[1]
II/I
[2]
90/323
[3]
2.79
[4]
1.934–4.026
[5]
4.08E−08
[6]
2.065
[7]
1.42–3.004
[8]
1.49E−04
[29] array · 9 items
[0]
Risk score
[1]
High/low
[2]
270/143
[3]
3.153
[4]
1.981–5.016
[5]
1.26E−06
[6]
3.005
[7]
1.863–4.846
[8]
6.44E−06
locator
section[12]/table-wrap[1]#Tab1
[6] object · 16 fields
id
asset:table:pmid:33028329:2
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table
format
jats-table
media_type
application/vnd.jats.table+json
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null
sha256
sha256:1999b3171e9a08b0b7dd0debcac5a110249e8b4e52d2cb7f92be32ba2f103858
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read_table
reader_status
available
identifier
section[12]/table-wrap[2]#Tab2
version
null
note
Univariate and multivariate Cox regression analyses of the 21-gene signature and OS in the validation set (early-stage LUAD)
structure object · 5 fields
pmcid
PMC7542703
section_index
12
section_title
The 21-gene prognostic signature is an independent prognostic factor
row_count
19
column_count
9
table object · 8 fields
label
Table 2
caption
Univariate and multivariate Cox regression analyses of the 21-gene signature and OS in the validation set (early-stage LUAD)
rows array · 19 items
[0] array · 4 items
[0]
Variables
[1]
Patients (N)
[2]
Univariate analysis
[3]
Multivariate analysis
[1] array · 6 items
[0]
HR
[1]
95% CI
[2]
p value
[3]
HR
[4]
95% CI
[5]
p value
[2] array · 1 item
[0]
GSE72094
[3] array · 9 items
[0]
Age
[1]
> 65/ ≤ 65
[2]
219/92
[3]
1.638
[4]
0.952–2.817
[5]
7.47E−02
[6]
1.807
[7]
1.042–3.135
[8]
3.52E−02
[4] array · 9 items
[0]
Gender
[1]
Male/female
[2]
141/170
[3]
1.449
[4]
0.917–2.289
[5]
1.12E−01
[6]
1.386
[7]
0.871–2.207
[8]
1.69E−01
[5] array · 9 items
[0]
Stage
[1]
II/I
[2]
65/246
[3]
2.137
[4]
1.313–3.479
[5]
2.24E−03
[6]
2.258
[7]
1.38–3.695
[8]
1.20E−03
[6] array · 9 items
[0]
Smoking
[1]
Yes/no
[2]
237/26
[3]
1.334
[4]
0.482–3.696
[5]
5.79E−01
[6]
[7]
[8]
[7] array · 9 items
[0]
EGFR mutation
[1]
Yes/no
[2]
35/276
[3]
0.092
[4]
0.013–0.659
[5]
1.76E−02
[6]
0.137
[7]
0.019–1.004
[8]
5.05E−02
[8] array · 9 items
[0]
KRAS mutation
[1]
Yes/no
[2]
105/206
[3]
1.701
[4]
1.075–2.691
[5]
2.33E−02
[6]
1.554
[7]
0.976–2.475
[8]
6.33E−02
[9] array · 9 items
[0]
TP53 mutation
[1]
Yes/no
[2]
77/234
[3]
1.461
[4]
0.893–2.392
[5]
1.31E−01
[6]
1.154
[7]
0.69–1.932
[8]
5.86E−01
[10] array · 9 items
[0]
STK11 mutation
[1]
Yes/no
[2]
48/263
[3]
0.799
[4]
0.41–1.559
[5]
5.11E−01
[6]
[7]
[8]
[11] array · 9 items
[0]
Risk score
[1]
High/low
[2]
89/222
[3]
2.952
[4]
1.857–4.695
[5]
4.79E−06
[6]
2.942
[7]
1.806–4.793
[8]
1.47E−05
[12] array · 1 item
[0]
TCGA-LUAD
[13] array · 9 items
[0]
Age
[1]
> 65/ ≤ 65
[2]
190/168
[3]
1.308
[4]
0.897–1.907
[5]
1.62E−01
[6]
1.513
[7]
1.018–2.249
[8]
4.05E−02
[14] array · 9 items
[0]
Gender
[1]
Male/female
[2]
168/199
[3]
1.069
[4]
0.739–1.546
[5]
7.25E−01
[6]
[7]
[8]
[15] array · 9 items
[0]
Stage
[1]
II/I
[2]
113/254
[3]
2.607
[4]
1.795–3.785
[5]
4.84E−07
[6]
2.186
[7]
1.444–3.309
[8]
2.19E−04
[16] array · 9 items
[0]
T stage
[1]
T2/T1
[2]
201/141
[3]
1.423
[4]
0.942–2.147
[5]
9.35E−02
[6]
1.131
[7]
0.775–1.813
[8]
4.34E−01
[17] array · 9 items
[0]
Smoking
[1]
Yes/no
[2]
273/49
[3]
0.923
[4]
0.54–1.579
[5]
7.70E−01
[6]
[7]
[8]
[18] array · 9 items
[0]
Risk score
[1]
High/low
[2]
141/226
[3]
2.16
[4]
1.492–3.128
[5]
4.54E−05
[6]
1.909
[7]
1.279–2.849
[8]
1.55E−03
locator
section[12]/table-wrap[2]#Tab2
gaps array · 8 items
[0]
asset:data:geo:GSE30219 not downloaded
[1]
asset:data:geo:GSE30219 licence not read
[2]
asset:data:geo:GSE31210 not downloaded
[3]
asset:data:geo:GSE31210 licence not read
[4]
asset:data:geo:GSE50081 not downloaded
[5]
asset:data:geo:GSE50081 licence not read
[6]
asset:data:geo:GSE72094 not downloaded
[7]
asset:data:geo:GSE72094 licence not read
analysis object · 4 fields
state
complete
methods array · 5 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
1
band
verbatim
quote
Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set).
[1] object · 10 fields
id
method-2
family
survival_analysis
specific
kaplan_meier
label
Survival analysis
dsl_operations array · 1 item
[0]
survival_km
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.7
band
medium
quote
Kaplan-Meier
[2] object · 10 fields
id
method-3
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.7
band
medium
quote
log-rank
[3] object · 10 fields
id
method-4
family
network_analysis
specific
pathway_enrichment
label
Network / pathway analysis
dsl_operations array · 1 item
[0]
pathway_enrich
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
edge_list
evidence object · 3 fields
score
0.8
band
high
quote
GO enrichment
[4] object · 10 fields
id
method-5
family
diagnostic_evaluation
specific
roc
label
Diagnostic test evaluation
dsl_operations array · 6 items
[0]
confusion_counts
[1]
roc_curve
[2]
sensitivity_specificity
[3]
solve_confusion_matrix
[4]
classification_metrics
[5]
published_precision_envelope
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
reference_standard_and_test
evidence object · 3 fields
score
0.8
band
high
quote
ROC analysis
targets array · 0 items
gaps array · 0 items
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 4 items
[0]
GSE30219
[1]
GSE31210
[2]
GSE50081
[3]
GSE72094
resolved_accessions array · 4 items
[0]
GSE30219
[1]
GSE31210
[2]
GSE50081
[3]
GSE72094
statements array · 1 item
[0]
The data sets analyzed in this study are available on the public databases.
basis
The paper names GSE30219, GSE31210, GSE50081, GSE72094 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
cox_ph
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asset:table:pmid:33028329:1
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steps array · 1 item
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run_analysis
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data_gaps array · 1 item
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data:geo:GSE30219
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review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
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minimax
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independence
single_reader
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verbatim
availability
verbatim
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40500
completion_tokens
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PMID 33028329 full text
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GEO GSE30219
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agent:corpus-assay-engine
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asset:data:geo:GSE50081 licence not read
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from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA)
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cox_ph
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Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set).
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33028329", "kind": "science-record", "revision": 7, "content_hash": "sha256:428d50b55670a64da826f256fe103980dfe6b72de2baeacf47824f9aa76f84a0", "created_at": "2026-11-01T15:41:12Z", "updated_at": "2026-11-01T22:02:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma.", "doi": "10.1186/s12967-020-02545-z", "pmid": "33028329", "authors": ["Pancheng Wu", "Yi Zheng", "Yanyu Wang", "Yadong Wang", "Naixin Liang"], "journal": "Journal of translational medicine", "year": 2020, "abstract": "BACKGROUND: The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD.\nMETHODS: The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan-Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts.\nRESULTS: A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29-8.11; P = 6.16E-06), GSE31210 (HR = 11.91, 95% CI 4.15-34.19; P = 4.10E-06), GSE50081 (HR = 3.63, 95% CI 1.90-6.95; P = 9.95E-05), the combined data set (HR = 3.15, 95% CI 1.98-5.02; P = 1.26E-06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49-3.13; P = 4.54E-05) and GSE72094 (HR = 2.95, 95% CI 1.86-4.70; P = 4.79E-06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design.\nCONCLUSIONS: Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.", "claims": [{"id": "claim-method", "statement": "Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33028329", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data sets analyzed in this study are available on the public databases.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33028329", "locator": "sections[23] \"Availability of data and materials\" paragraph 2", "quote": "The data sets analyzed in this study are available on the public databases."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33028329"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE30219"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE30219"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33028329", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12967-020-02545-z", "sha256": 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21-gene signature and OS in the validation set (early-stage LUAD)", "structure": {"pmcid": "PMC7542703", "section_index": 12, "section_title": "The 21-gene prognostic signature is an independent prognostic factor", "row_count": 19, "column_count": 9}, "table": {"label": "Table 2", "caption": "Univariate and multivariate Cox regression analyses of the 21-gene signature and OS in the validation set (early-stage LUAD)", "rows": [["Variables", "Patients (N)", "Univariate analysis", "Multivariate analysis"], ["HR", "95% CI", "p value", "HR", "95% CI", "p value"], ["GSE72094"], ["Age", "> 65/ ≤ 65", "219/92", "1.638", "0.952–2.817", "7.47E−02", "1.807", "1.042–3.135", "3.52E−02"], ["Gender", "Male/female", "141/170", "1.449", "0.917–2.289", "1.12E−01", "1.386", "0.871–2.207", "1.69E−01"], ["Stage", "II/I", "65/246", "2.137", "1.313–3.479", "2.24E−03", "2.258", "1.38–3.695", "1.20E−03"], ["Smoking", "Yes/no", "237/26", "1.334", "0.482–3.696", "5.79E−01", "", "", ""], ["EGFR mutation", 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