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pmid:32351780

Comparative proteogenomics profiling of non-small and small lung carcinoma cell lines using mass spectrometry.

Jingyu Wu · Zhifang Hao · Chen Ma · Pengfei Li · Liuyi Dang · Shisheng Sun

PeerJ · 2020 doi:10.7717/peerj.8779

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pmid:32351780
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title
Comparative proteogenomics profiling of non-small and small lung carcinoma cell lines using mass spectrometry.
doi
10.7717/peerj.8779
pmid
32351780
authors array · 6 items
[0]
Jingyu Wu
[1]
Zhifang Hao
[2]
Chen Ma
[3]
Pengfei Li
[4]
Liuyi Dang
[5]
Shisheng Sun
journal
PeerJ
year
2020
abstract
BACKGROUND: Evidences indicated that non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) might originate from the same cell type, which however ended up to be two different subtypes of lung carcinoma, requiring different therapeutic regimens. We aimed to identify the differences between these two subtypes of lung cancer by using integrated proteome and genome approaches. METHODS AND MATERIALS: Two representative cell lines for each lung cancer subtype were comparatively analysed by quantitative proteomics, and their corresponding transcriptomics data were obtained from the Gene Expression Omnibus database. The integrated analyses of proteogenomic data were performed to determine key differentially expressed proteins that were positively correlated between proteomic and transcriptomic data. RESULT: The proteomics analysis revealed 147 differentially expressed proteins between SCLC and NSCLC from a total of 3,970 identified proteins. Combined with available transcriptomics data, we further confirmed 14 differentially expressed proteins including six known and eight new lung cancer related proteins that were positively correlated with their transcriptomics data. These proteins are mainly involved in cell migration, proliferation, and invasion. CONCLUSION: The proteogenomic data on both NSCLC and SCLC cell lines presented in this manuscript is complementary to existing genomic and proteomic data related to lung cancers and will be crucial for a systems biology-level understanding of the molecular mechanism of lung cancers. The raw mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD015270.
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Linear Models for Microarray Analysis package in R language was employed to screen DEGs between NSCLC samples and SCLC samples.
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sections[8] "Determination and hierarchical clustering analysis of DEGs" paragraph 2
quote
Linear Models for Microarray Analysis package in R language was employed to screen DEGs between NSCLC samples and SCLC samples.
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The following information was supplied regarding data availability: The proteomic data are available from the PRIDE Archive: PXD015270.
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sections[33] "Data Availability Statement" paragraphs 1-3
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The following information was supplied regarding data availability: The proteomic data are available from the PRIDE Archive: PXD015270.
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[528]
GSM887363
[529]
GSM887364
[530]
GSM887365
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GSM887366
[532]
GSM887367
[533]
GSM887368
[534]
GSM887369
[535]
GSM887370
[536]
GSM887371
[537]
GSM887372
[538]
GSM887373
[539]
GSM887374
[540]
GSM887375
[541]
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[542]
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[543]
GSM887378
[544]
GSM887379
[545]
GSM887380
[546]
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[547]
GSM887382
[548]
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[549]
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[550]
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[551]
GSM887386
[552]
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[553]
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[554]
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[555]
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[556]
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[557]
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[558]
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[559]
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[560]
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[561]
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[562]
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[563]
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[564]
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[565]
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[566]
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[567]
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[568]
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[569]
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[570]
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[571]
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[572]
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[573]
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[574]
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[575]
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[576]
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[577]
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[578]
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[584]
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[586]
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[587]
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[588]
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[589]
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[590]
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[591]
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[592]
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[593]
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[594]
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[595]
GSM887430
[596]
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[597]
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[598]
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[599]
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[600]
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[601]
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GSM887440
[606]
GSM887441
[607]
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[608]
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[609]
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[610]
GSM887445
[611]
GSM887446
[612]
GSM887447
[613]
GSM887448
[614]
GSM887449
[615]
GSM887450
[616]
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[617]
GSM887452
[618]
GSM887453
[619]
GSM887454
[620]
GSM887455
[621]
GSM887456
[622]
GSM887457
[623]
GSM887458
[624]
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[625]
GSM887460
[626]
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[627]
GSM887462
[628]
GSM887463
[629]
GSM887464
[630]
GSM887465
[631]
GSM887466
[632]
GSM887467
[633]
GSM887468
[634]
GSM887469
[635]
GSM887470
[636]
GSM887471
[637]
GSM887472
[638]
GSM887473
[639]
GSM887474
[640]
GSM887475
[641]
GSM887476
[642]
GSM887477
[643]
GSM887478
[644]
GSM887479
[645]
GSM887480
[646]
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[647]
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[648]
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[649]
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[650]
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[651]
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[652]
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[653]
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[654]
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[655]
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[656]
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[657]
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[658]
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[659]
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[660]
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[661]
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[662]
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[663]
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[664]
GSM887499
[665]
GSM887500
[666]
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[667]
GSM887502
[668]
GSM887503
[669]
GSM887504
[670]
GSM887505
[671]
GSM887506
[672]
GSM887507
[673]
GSM887508
[674]
GSM887509
[675]
GSM887510
[676]
GSM887511
[677]
GSM887512
[678]
GSM887513
[679]
GSM887514
[680]
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[681]
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[682]
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[683]
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[684]
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[685]
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[686]
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[687]
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[688]
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[689]
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[690]
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[691]
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[692]
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[693]
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[694]
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[695]
GSM887530
[696]
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[697]
GSM887532
[698]
GSM887533
[699]
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[700]
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[701]
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[702]
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[703]
GSM887538
[704]
GSM887539
[705]
GSM887540
[706]
GSM887541
[707]
GSM887542
[708]
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[709]
GSM887544
[710]
GSM887545
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[712]
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[713]
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[714]
GSM887549
[715]
GSM887550
[716]
GSM887551
[717]
GSM887552
[718]
GSM887553
[719]
GSM887554
[720]
GSM887555
[721]
GSM887556
[722]
GSM887557
[723]
GSM887558
[724]
GSM887559
[725]
GSM887560
[726]
GSM887561
[727]
GSM887562
[728]
GSM887563
[729]
GSM887564
[730]
GSM887565
[731]
GSM887566
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GSM887567
[733]
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[734]
GSM887569
[735]
GSM887570
[736]
GSM887571
[737]
GSM887572
[738]
GSM887573
[739]
GSM887574
[740]
GSM887575
[741]
GSM887576
[742]
GSM887577
[743]
GSM887578
[744]
GSM887579
[745]
GSM887580
[746]
GSM887581
[747]
GSM887582
[748]
GSM887583
[749]
GSM887584
[750]
GSM887585
[751]
GSM887586
[752]
GSM887587
[753]
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[754]
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[755]
GSM887590
[756]
GSM887591
[757]
GSM887592
[758]
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[759]
GSM887594
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GSM887595
[761]
GSM887596
[762]
GSM887597
[763]
GSM887598
[764]
GSM887599
[765]
GSM887600
[766]
GSM887601
[767]
GSM887602
[768]
GSM887603
[769]
GSM887604
[770]
GSM887605
[771]
GSM887606
[772]
GSM887607
[773]
GSM887608
[774]
GSM887609
[775]
GSM887610
[776]
GSM887611
[777]
GSM887612
[778]
GSM887613
[779]
GSM887614
[780]
GSM887615
[781]
GSM887616
[782]
GSM887617
[783]
GSM887618
[784]
GSM887619
[785]
GSM887620
[786]
GSM887621
[787]
GSM887622
[788]
GSM887623
[789]
GSM887624
[790]
GSM887625
[791]
GSM887626
[792]
GSM887627
[793]
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[794]
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[795]
GSM887630
[796]
GSM887631
[797]
GSM887632
[798]
GSM887633
[799]
GSM887634
[800]
GSM887635
[801]
GSM887636
[802]
GSM887637
[803]
GSM887638
[804]
GSM887639
[805]
GSM887640
[806]
GSM887641
[807]
GSM887642
[808]
GSM887643
[809]
GSM887644
[810]
GSM887645
[811]
GSM887646
[812]
GSM887647
[813]
GSM887648
[814]
GSM887649
[815]
GSM887650
[816]
GSM887651
[817]
GSM887652
[818]
GSM887653
[819]
GSM887654
[820]
GSM887655
[821]
GSM887656
[822]
GSM887657
[823]
GSM887658
[824]
GSM887659
[825]
GSM887660
[826]
GSM887661
[827]
GSM887662
[828]
GSM887663
[829]
GSM887664
[830]
GSM887665
[831]
GSM887666
[832]
GSM887667
[833]
GSM887668
[834]
GSM887669
[835]
GSM887670
[836]
GSM887671
[837]
GSM887672
[838]
GSM887673
[839]
GSM887674
[840]
GSM887675
[841]
GSM887676
[842]
GSM887677
[843]
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[844]
GSM887679
[845]
GSM887680
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GSM887681
[847]
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[848]
GSM887683
[849]
GSM887684
[850]
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[851]
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[852]
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[855]
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[856]
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[857]
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[858]
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[859]
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[860]
GSM887695
[861]
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[862]
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[863]
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[864]
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[865]
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[866]
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[867]
GSM887702
[868]
GSM887703
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[871]
GSM887706
[872]
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[873]
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[874]
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[875]
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[876]
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[877]
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[878]
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[879]
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[880]
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[881]
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[882]
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[883]
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[885]
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[890]
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[891]
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[892]
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[893]
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[894]
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[898]
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[900]
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[901]
GSM887736
[902]
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[903]
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[904]
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[905]
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[906]
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[907]
GSM887742
[908]
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[909]
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[911]
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[912]
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[913]
GSM887748
[914]
GSM887749
[915]
GSM887750
[916]
GSM887751
sample_count
917
group_sizes
null
group_sizes_basis
null
platform
15308
taxon
Homo sapiens
title
Expression data from the Cancer Cell Line Encyclopedia (CCLE)
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[2] object · 15 fields
id
data:geo:PXD015270
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=PXD015270
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
PXD015270
version
null
note
The following information was supplied regarding data availability: The proteomic data are available from the PRIDE Archive: PXD015270.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The following information was supplied regarding data availability: The proteomic data are available from the PRIDE Archive: PXD015270.
access_statement_kind
data_availability_statement
sample_accessions array · 0 items
sample_count
null
group_sizes
null
group_sizes_basis
null
platform
null
taxon
null
title
comparative proteomics of non-small cell lung cancer and small cell lung cancer
resolution_checked_at
2026-10-31T18:35:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[3] object · 16 fields
id
asset:table:pmid:32351780:1
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table
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jats-table
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application/vnd.jats.table+json
uri
null
sha256
sha256:560c4e8124de4335d7e839ce3c033a99d5d013d812c4efe2cbe490b825b8ce45
bytes
1188
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open
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verified
reader
read_table
reader_status
available
identifier
section[19]/table-wrap[1]#table-1
version
null
note
The profiling of differentially expressed proteins and mRNA.
structure object · 5 fields
pmcid
PMC7183755
section_index
19
section_title
Determination of key proteins by combined use of proteomics and transcriptomics
row_count
15
column_count
5
table object · 8 fields
label
Table 1
caption
The profiling of differentially expressed proteins and mRNA.
rows array · 15 items
[0] array · 5 items
[0]
Protein name
[1]
Description
[2]
Gene name
[3]
Ratio
[4]
PSM
[1] array · 5 items
[0]
P04083
[1]
Annexin A1
[2]
ANXA1
[3]
0.072
[4]
761
[2] array · 5 items
[0]
P07355
[1]
Annexin A2
[2]
ANXA2
[3]
0.314
[4]
1,364
[3] array · 5 items
[0]
O75369
[1]
Filamin-B
[2]
FLNB
[3]
0.106
[4]
1,816
[4] array · 5 items
[0]
Q9BW1
[1]
Acetyl-CoA acetyltransferase 2
[2]
ACAT2
[3]
7.92
[4]
112
[5] array · 5 items
[0]
O75475
[1]
PC4 and SFRS1-interacting protein
[2]
PSIP1
[3]
15.25
[4]
266
[6] array · 5 items
[0]
O14776
[1]
Transcription elongation regulator 1
[2]
TCERG1
[3]
7.166
[4]
101
[7] array · 5 items
[0]
P07741
[1]
Adenine phosphoribosyl transferase
[2]
APRT
[3]
0.262
[4]
160
[8] array · 5 items
[0]
Q9BP6
[1]
Dihydropyrimidinase-related protein 5
[2]
DPYSL5
[3]
3.058
[4]
173
[9] array · 5 items
[0]
Q71U36
[1]
Tubulin alpha-1A
[2]
TUBA1A
[3]
2.969
[4]
244
[10] array · 5 items
[0]
P23368
[1]
NAD-dependent malic enzyme 2
[2]
ME2
[3]
3.614
[4]
252
[11] array · 5 items
[0]
P22626
[1]
Heterogeneous nuclear ribonucleoproteins A2/B1
[2]
HNRNPA21
[3]
2.924
[4]
1,600
[12] array · 5 items
[0]
P15121
[1]
Aldose reductase
[2]
AKR1B1
[3]
0.179
[4]
461
[13] array · 5 items
[0]
Q9BTT0
[1]
Acidic leucine-rich nuclear phosphoprotein 32 family member E
[2]
ANP32E
[3]
3.249
[4]
61
[14] array · 5 items
[0]
Q9BR2
[1]
Thioredoxin domain-containing protein 17
[2]
TXNDC17
[3]
0.294
[4]
109
locator
section[19]/table-wrap[1]#table-1
gaps array · 4 items
[0]
asset:data:geo:GSE36133 not downloaded
[1]
asset:data:geo:GSE36133 licence not read
[2]
asset:data:geo:PXD015270 not downloaded
[3]
asset:data:geo:PXD015270 licence not read
analysis object · 4 fields
state
partial
methods array · 3 items
[0] object · 10 fields
id
method-1
family
clustering
specific
hierarchical
label
Clustering
dsl_operations array · 1 item
[0]
hierarchical_cluster
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
feature_matrix
evidence object · 3 fields
score
0.8
band
high
quote
hierarchical clustering
[1] object · 10 fields
id
method-2
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
[2] object · 10 fields
id
method-3
family
null
specific
null
label
Linear Models for Microarray Analysis
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Linear Models for Microarray Analysis package in R language was employed to screen DEGs between NSCLC samples and SCLC samples.
targets array · 0 items
gaps array · 1 item
[0]
method.reader_named_unmapped
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]
hierarchical_cluster
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: hierarchical.
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 · 2 items
[0]
GSE36133
[1]
PXD015270
resolved_accessions array · 2 items
[0]
GSE36133
[1]
PXD015270
statements array · 1 item
[0]
The following information was supplied regarding data availability: The proteomic data are available from the PRIDE Archive: PXD015270.
basis
The paper names GSE36133, PXD015270 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]
hierarchical_cluster
assets array · 3 items
[0]
source:pmid:32351780
[1]
data:geo:GSE36133
[2]
asset:table:pmid:32351780:1
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE36133
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:19:34Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
40156
completion_tokens
2072
cached_tokens
520
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:32351780
type
paper
label
pmid:32351780
[1] object · 3 fields
id
source:pmid:32351780
type
manuscript
label
PMID 32351780 full text
[2] object · 3 fields
id
data:geo:GSE36133
type
dataset
label
GEO GSE36133
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:32351780
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PMID 32351780 full text
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ll and small lung carcinoma cell lines using mass spectrometry.
[1]
molecular mechanism of lung cancers. The raw mass spectrometry data have been deposited to the ProteomeXcha
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were comparatively analysed by quantitative proteomics, and their corresponding transcriptomics dat
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eins that were positively correlated between proteomic and transcriptomic data. RESULT: The proteom
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37 °C and 5% CO2. The NSCLC cell lines were cultivated with adherent method and SCLC cell lines wer
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ls Cell culture Two NSCLC cell lines (H1975, A549) and two SCLC cell lines (H69, H446) were ob
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lustering analysis of DEGs Linear Models for Microarray Analysis package in R language was employed
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32351780", "kind": "science-record", "revision": 6, "content_hash": "sha256:8a0d3be46fab9696d39f3d404a6972698b13b60a0969edf2400f50a387ead2a4", "created_at": "2026-11-01T15:41:00Z", "updated_at": "2026-11-01T21:23:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comparative proteogenomics profiling of non-small and small lung carcinoma cell lines using mass spectrometry.", "doi": "10.7717/peerj.8779", "pmid": "32351780", "authors": ["Jingyu Wu", "Zhifang Hao", "Chen Ma", "Pengfei Li", "Liuyi Dang", "Shisheng Sun"], "journal": "PeerJ", "year": 2020, "abstract": "BACKGROUND: Evidences indicated that non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) might originate from the same cell type, which however ended up to be two different subtypes of lung carcinoma, requiring different therapeutic regimens. We aimed to identify the differences between these two subtypes of lung cancer by using integrated proteome and genome approaches.\nMETHODS AND MATERIALS: Two representative cell lines for each lung cancer subtype were comparatively analysed by quantitative proteomics, and their corresponding transcriptomics data were obtained from the Gene Expression Omnibus database. The integrated analyses of proteogenomic data were performed to determine key differentially expressed proteins that were positively correlated between proteomic and transcriptomic data.\nRESULT: The proteomics analysis revealed 147 differentially expressed proteins between SCLC and NSCLC from a total of 3,970 identified proteins. Combined with available transcriptomics data, we further confirmed 14 differentially expressed proteins including six known and eight new lung cancer related proteins that were positively correlated with their transcriptomics data. These proteins are mainly involved in cell migration, proliferation, and invasion.\nCONCLUSION: The proteogenomic data on both NSCLC and SCLC cell lines presented in this manuscript is complementary to existing genomic and proteomic data related to lung cancers and will be crucial for a systems biology-level understanding of the molecular mechanism of lung cancers. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE36133"], "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:GSE36133"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32351780", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.8779", "sha256": 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