LcProt: Proteomics-based identification of plasma biomarkers for lung cancer multievent, a multicentre study

Hengrui Liang , Runchen Wang , Ran Cheng , Zhiming Ye , Na Zhao , Xiaohong Zhao , Ying Huang , Zhanpeng Jiang , Wangzhong Li , Jianqi Zheng , Hongsheng Deng , Yu Jiang , Yuechun Lin , Yun Yan , Lei Song , Jie Li , Xin Xu , Wenhua Liang , Jun Liu , Jianxing He

Clinical and Translational Medicine ›› 2025, Vol. 15 ›› Issue (1) : e70160

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Clinical and Translational Medicine ›› 2025, Vol. 15 ›› Issue (1) : e70160 DOI: 10.1002/ctm2.70160
RESEARCH ARTICLE

LcProt: Proteomics-based identification of plasma biomarkers for lung cancer multievent, a multicentre study

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Abstract

•Our study developed an innovative nanomaterial, Zeolite NaY, which addressed the masking effect and improved the depth of the proteome.

•The performance of NaY-based plasma proteomics as a preclinical diagnostic tool was validated through both internal and external cohort.

•Furthermore, we explored the different patterns of plasma protein changes during the progression of lung cancer and used the explanations method to elucidate the roles of proteins in the multitask predictive model.

Keywords

lung cancer / multitask / plasma proteomics / zeolite NaY

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Hengrui Liang, Runchen Wang, Ran Cheng, Zhiming Ye, Na Zhao, Xiaohong Zhao, Ying Huang, Zhanpeng Jiang, Wangzhong Li, Jianqi Zheng, Hongsheng Deng, Yu Jiang, Yuechun Lin, Yun Yan, Lei Song, Jie Li, Xin Xu, Wenhua Liang, Jun Liu, Jianxing He. LcProt: Proteomics-based identification of plasma biomarkers for lung cancer multievent, a multicentre study. Clinical and Translational Medicine, 2025, 15(1): e70160 DOI:10.1002/ctm2.70160

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References

[1]

MillerKD, Nogueira L, DevasiaT, et al. Cancer treatment and survivorship statistics, 2022. CA Cancer J Clin. 2022;72(5):409-436.

[2]

DaviesMPA, SatoT, AshoorH, et al. Plasma protein biomarkers for early prediction of lung cancer. EBioMedicine. 2023;93:104686.

[3]

FahrmannJF, MarshT, IrajizadE, et al. Blood-based biomarker panel for personalized lung cancer risk assessment. J Clin Oncol. 2022;40(8):876-883.

[4]

IqbalMA, AroraS, PrakasamG, Calin GA, SyedMA. MicroRNA in lung cancer: role, mechanisms, pathways and therapeutic relevance. Mol Aspects Med. 2019;70:3-20.

[5]

MassionPP, HealeyGF, PeekLJ, et al. Autoantibody signature enhances the positive predictive power of computed tomography and nodule-based risk models for detection of lung cancer. J Thorac Oncol. 2017;12(3):578-584.

[6]

LiP, LiuS, DuL, Mohseni G, ZhangY, WangC. Liquid biopsies based on DNA methylation as biomarkers for the detection and prognosis of lung cancer. Clin Epigenetics. 2022;14(1):118.

[7]

HeekeS, GayCM, EstecioMR, et al. Tumor-and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes. Cancer Cell. 2024;42(2):225-237.e5.

[8]

LiangW, ZhaoY, HuangW, et al. Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA). Theranostics. 2019;9(7):2056-2070.

[9]

LiangW, ChenZ, LiC, et al. Accurate diagnosis of pulmonary nodules using a noninvasive DNA methylation test. J Clin Invest. 2021;131(10):e145973.

[10]

HeJ, WangB, TaoJ, et al. Accurate classification of pulmonary nodules by a combined model of clinical, imaging, and cell-free DNA methylation biomarkers: a model development and external validation study. Lancet Digit Health. 2023;5(10):e647-e656.

[11]

ZhaoY, XueQ, WangM, et al. Evolution of mass spectrometry instruments and techniques for blood proteomics. J Proteome Res. 2023;22(4):1009-1023.

[12]

PuF, ChiangS, ZhangW, Ouyang Z. Direct sampling mass spectrometry for clinical analysis. Analyst. 2019;144(4):1034-1051.

[13]

TamburroD, Fredolini C, EspinaV, et al. Multifunctional core-shell nanoparticles: discovery of previously invisible biomarkers. J Am Chem Soc. 2011;133(47):19178-19188.

[14]

JoshiA, RienksM, TheofilatosK, MayrM. Systems biology in cardiovascular disease: a multiomics approach. Nat Rev Cardiol. 2021;18(5):313-330.

[15]

TognettiM, Sklodowski K, MüllerS, et al. Biomarker candidates for tumors identified from deep-profiled plasma stem predominantly from the low abundant area. J Proteome Res. 2022;21(7):1718-1735.

[16]

MaC, LiY, LiJ, et al. Comprehensive and deep profiling of the plasma proteome with protein corona on zeolite NaY. J Pharm Anal. 2023;13(5):503-513.

[17]

RitchieME, Phipson B, WuD, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.

[18]

BechtE, McInnes L, HealyJ, et al. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2018.

[19]

WuT, HuE, XuS, et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation. 2021;2(3):100141.

[20]

ZhouY, ZhouB, PacheL, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.

[21]

FutschikME, Carlisle B. Noise-robust soft clustering of gene expression time-course data. J Bioinform Comput Biol. 2005;3(04):965-988.

[22]

KumarL, Futschik ME. Mfuzz: a software package for soft clustering of microarray data. Bioinformation. 2007;2(1):5.

[23]

RobinX, TurckN, HainardA, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinform. 2011;12:77.

[24]

BechJM, Terkelsen T, BartelsAS, et al. Proteomic profiling of colorectal adenomas identifies a predictive risk signature for development of metachronous advanced colorectal neoplasia. Gastroenterology. 2023;165(1):121-132.e5.

[25]

AshtonNJ, Nevado-Holgado AJ, BarberIS, et al. A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer’s disease. Sci Adv. 2019;5(2):eaau7220.

[26]

FriedmanJ, HastieT, TibshiraniR. Regularization paths for generalized linear models via coordinate descent. J Stat Software. 2010;33(1):1-22.

[27]

LiawA, WienerM. Classification and regression by randomForest. R News. 2002;2(3):18-22.

[28]

BreimanL. Random forests. Machine Learn. 2001;45:5-32.

[29]

WeiR, WangJ, JiaW, WeiMR. Package ‘multiROC’. 2018, https://CRAN.R-project.org/package=multiROC

[30]

ŠtrumbeljE, Kononenko I. Explaining prediction models and individual predictions with feature contributions. Knowledge and information systems. 2014;41:647-665.

[31]

LundbergSM, LeeS-I. A unified approach to interpreting model predictions. Adv Neural Inform Process Systems. 2017;30

[32]

LundbergSM, ErionG, ChenH, et al. From local explanations to global understanding with explainable AI for trees. Nat Mach Intell. 2020;2(1):56-67.

[33]

Peña-BlancoA, García-Sáez AJ. Bax, Bak and beyond -mitochondrial performance in apoptosis. FEBS J. 2018;285(3):416-431.

[34]

SoneharaK, KimuraY, NakanoY, et al. A common deletion at BAK1 reduces enhancer activity and confers risk of intracranial germ cell tumors. Nat Commun. 2022;13(1):4478.

[35]

WuH, ChenW, ChenZ, Li X, WangM. Novel tumor therapy strategies targeting endoplasmic reticulum-mitochondria signal pathways. Ageing Res Rev. 2023;88:101951.

[36]

PapadimitriouE, Mikelis C, LampropoulouE, et al. Roles of pleiotrophin in tumor growth and angiogenesis. Eur Cytokine Netw. 2009;20(4):180-190.

[37]

ChangY, ZukaM, Perez-PineraP, et al. Secretion of pleiotrophin stimulates breast cancer progression through remodeling of the tumor microenvironment. Proc Natl Acad Sci U S A. 2007;104(26):10888-10893.

[38]

ShiY, PingY-F, ZhouW, et al. Tumour-associated macrophages secrete pleiotrophin to promote PTPRZ1 signalling in glioblastoma stem cells for tumour growth. Nat Commun. 2017;8:15080.

[39]

HoD, QuakeSR, McCabeERB, et al. Enabling technologies for personalized and precision medicine. Trends Biotechnol. 2020;38(5):497-518.

[40]

GuidaF, SunN, BantisLE, et al. Assessment of lung cancer risk on the basis of a biomarker panel of circulating proteins. JAMA Oncol. 2018;4(10):e182078.

[41]

The blood proteome of imminent lung cancer diagnosis. Nat Commun. 2023;14(1):3042.

[42]

FengX, WuWY-Y, OnwukaJU, et al. Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools. J Natl Cancer Inst. 2023;115(9):1050-1059.

[43]

JonesRG, BuiT, WhiteC, et al. The proapoptotic factors Bax and Bak regulate T Cell proliferation through control of endoplasmic reticulum Ca(2+) homeostasis. Immunity. 2007;27(2):268-280.

[44]

NomuraT, Katunuma N. Involvement of cathepsins in the invasion, metastasis and proliferation of cancer cells. J Med Invest. 2005;52(1-2):1-9.

[45]

QinX, LinL, CaoL, et al. Extracellular matrix protein Reelin promotes myeloma progression by facilitating tumor cell proliferation and glycolysis. Sci Rep. 2017;7:45305.

[46]

PapadimitriouE, Pantazaka E, CastanaP, TsaliosT, Polyzos A, BeisD. Pleiotrophin and its receptor protein tyrosine phosphatase beta/zeta as regulators of angiogenesis and cancer. Biochim Biophys Acta. 2016;1866(2):252-265.

[47]

BaeS-Y, ByunS, BaeSH, Min DS, WooHA, LeeK. TPT1 (tumor protein, translationally-controlled 1) negatively regulates autophagy through the BECN1 interactome and an MTORC1-mediated pathway. Autophagy. 2017;13(5):820-833.

[48]

AmsonR, PeceS, MarineJ-C, Di Fiore PP, TelermanA. TPT1/TCTP-regulated pathways in phenotypic reprogramming. Trends Cell Biol. 2013;23(1):37-46.

[49]

WuW, GaoH, LiX, et al. LncRNA TPT1-AS1 promotes tumorigenesis and metastasis in epithelial ovarian cancer by inducing TPT1 expression. Cancer Sci. 2019;110(5):1587-1598.

[50]

ShihAH, Holland EC. Platelet-derived growth factor (PDGF) and glial tumorigenesis. Cancer Lett. 2006;232(2):139-147.

[51]

Santiago-SánchezGS, Pita-GrisantiV, Quiñones-Díaz B, GumpperK, Cruz-MonserrateZ, Vivas-Mejía PE. Biological functions and therapeutic potential of lipocalin 2 in cancer. Int J Mol Sci. 2020;21(12):4365.

[52]

AntonenkoS, Kravchuk I, TelegeevG. Interaction of Bcl-Abl oncoprotein with the Glg1 protein in K562 cells: its role in the pathogenesis of chronic myeloid leukemia. Cytol Genet. 2020;54(1):48-54.

[53]

TrkuljaKL, ManjiF, KuruvillaJ, Laister RC. Nuclear export in non-Hodgkin lymphoma and implications for targeted XPO1 inhibitors. Biomolecules. 2023;13(1):111.

[54]

JariwalaN, Rajasekaran D, SrivastavaJ, et al. Role of the staphylococcal nuclease and tudor domain containing 1 in oncogenesis (review). Int J Oncol. 2015;46(2):465-473.

[55]

ZhouJ-K, FanX, ChengJ, Liu W, PengY. PDLIM1: structure, function and implication in cancer. Cell Stress. 2021;5(8):119-127.

[56]

IslamBN, Sharman SK, HouY, et al. Type-2 cGMP-dependent protein kinase suppresses proliferation and carcinogenesis in the colon epithelium. Carcinogenesis. 2022;43(6):584-593.

[57]

WuM, WuY, QianH, et al. Type II cGMP dependent protein kinase inhibits the migration, invasion and proliferation of several types of human cancer cells. Mol Med Rep. 2017;16(4):5729-5737.

[58]

LiuJ, YuX, YuH, et al. Knockdown of MAPK14 inhibits the proliferation and migration of clear cell renal cell carcinoma by downregulating the expression of CDC25B. Cancer Med. 2020;9(3):1183-1195.

[59]

AzmiAS, UddinMH, MohammadRM. The nuclear export protein XPO1-from biology to targeted therapy. Nat Rev Clin Oncol. 2021;18(3):152-169.

[60]

TanX, HeX, JiangZ, et al. Derlin-1 is overexpressed in human colon cancer and promotes cancer cell proliferation. Mol Cell Biochem. 2015;408(1-2):205-213.

[61]

TaoY, HanT, ZhangT, Sun C. Sulfatase-2 promotes the growth and metastasis of colorectal cancer by activating Akt and Erk1/2 pathways. Biomed Pharmacother. 2017;89:1370-1377.

[62]

HongM, TaoS, ZhangL, et al. RNA sequencing: new technologies and applications in cancer research. J Hematol Oncol. 2020;13(1):166.

[63]

XuJ, LiaoK, YangX, Wu C, WuW. Using single-cell sequencing technology to detect circulating tumor cells in solid tumors. Mol Cancer. 2021;20(1):104.

[64]

SongP, WuLR, YanYH, et al. Limitations and opportunities of technologies for the analysis of cell-free DNA in cancer diagnostics. Nat Biomed Eng. 2022;6(3):232-245.

[65]

SankaranVG, Gallagher PG. Applications of high-throughput DNA sequencing to benign hematology. Blood. 2013;122(22):3575-3582.

[66]

ZhangY, Fonslow BR, ShanB, BaekM-C, Yates JR III. Protein analysis by shotgun/bottom-up proteomics. Chem Rev. 2013;113(4):2343-2394.

[67]

MahdaviMA, LinY-H. Prediction of protein-protein interactions using protein signature profiling. Genom Proteom Bioinform. 2007;5(3-4):177-186.

[68]

GeyerPE, KulakNA, PichlerG, Holdt LM, TeupserD, MannM. Plasma proteome profiling to assess human health and disease. Cell Syst. 2016;2(3):185-195.

[69]

OlivierM, AsmisR, HawkinsGA, Howard TD, CoxLA. The need for multi-omics biomarker signatures in precision medicine. Int J Mol Sci. 2019;20(19):4781.

[70]

van der GugtenJG. Tandem mass spectrometry in the clinical laboratory: a tutorial overview. Clin Mass Spectrom. 2020;15:36-43.

[71]

CuiL, LuH, LeeYH. Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases. Mass Spectrom Rev. 2018;37(6):772-792.

[72]

WuL, QuX. Cancer biomarker detection: recent achievements and challenges. Chem Soc Rev. 2015;44(10):2963-2997.

[73]

LundqvistM, Stigler J, CedervallT, et al. The evolution of the protein corona around nanoparticles: a test study. ACS Nano. 2011;5(9):7503-7509.

[74]

LiuY, YangQ, DuZ, et al. Synthesis of surface-functionalized molybdenum disulfide nanomaterials for efficient adsorption and deep profiling of the human plasma proteome by data-independent acquisition. Anal Chem. 2022;94(43):14956-14964.

[75]

MengY, ChenJ, LiuY, et al. A highly efficient protein corona-based proteomic analysis strategy for the discovery of pharmacodynamic biomarkers. J Pharm Anal. 2022;12(6):879-888.

[76]

BlumeJE, Manning WC, TroianoG, et al. Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona. Nat Commun. 2020;11(1):3662.

[77]

Pérez-BotellaE, Valencia S, ReyF. Zeolites in adsorption processes: state of the art and future prospects. Chem Rev. 2022;122(24):17647-17695.

[78]

CormaA. State of the art and future challenges of zeolites as catalysts. J Catal. 2003;216(1-2):298-312.

[79]

WuJ, LiX, YanY, HuY, ZhangY, Tang Y. Protein adsorption onto nanozeolite: effect of micropore openings. J Colloid Interface Sci. 2013;406:130-138.

[80]

RahimiM, NgEP, BakhtiariK, et al. Zeolite nanoparticles for selective sorption of plasma proteins. Sci Rep. 2015;5:17259.

[81]

MatsuiM, Kiyozumi Y, YamamotoT, MizushinaY, Mizukami F, SakaguchiK. Selective adsorption of biopolymers on zeolites. Chemistry. 2001;7(7):1555-1560.

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2025 The Author(s). Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.

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