Integrative proteomic characterization of human lung adenocarcinoma with KRAS G12 mutations reveals molecular pathogenesis
Open accessAbstract
INTRODUCTION: Integrated proteogenomic studies of lung adenocarcinoma (LUAD) have provided unique insights with potential clinical effects. Comprehensive proteomic analyses are needed to better understand the molecular landscape of LUAD with KRAS G12 mutations. OBJECTIVES: This study aims to characterize the proteogenomic profile of LUAD with KRAS G12 mutation variants. METHODS: We performed next-generation sequencing (NGS) on 9,479 solid tumors, including 3,523 lung cancers. Proteomic profiling was conducted on 96 LUAD patients with KRAS G12 mutations or wild-type status using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The LUAD tumor immune microenvironment (TIME) was characterized by multiplex immunohistochemistry (mIHC), and protein-protein interactions (PPIs) in KRAS G12-mutant lung cancer cells were mapped using biotin-based proximity labeling. RESULTS: Genomic analysis revealed heterogeneous KRAS-informed mutational profiles across pan-cancer and lung cancer, with allele-specific resolution for KRAS G12 mutations. Proteomic profiling of KRAS G12-mutant LUAD delineated distinct molecular features and tumor progression hallmarks. Unsupervised clustering identified three molecular subtypes, with the immune modulation subtype (S2) characterized by KRAS G12C enrichment, aggressive clinical features, and the greatest potential benefit from immunotherapy. The immune landscape of LUAD showed increased immune cell infiltration in KRAS G12C-mutant tumors. Additionally, proximal proteomics mapped a landscape of gain-of-interactions driven by KRAS G12 mutations, with ion transporter SLC4A7 emerged as a potential effector in immune modulation in the G12C variant. CONCLUSIONS: This comprehensive proteogenomic study provides insights into the molecular features of LUAD harboring KRAS G12 mutations, which may inform patient stratification and potential therapeutic approaches, pending further clinical validation.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Significant interpatient differences exist in molecular characteristics, tumor progression dynamics, and treatment sensitivity in LUAD, posing major challenges to standardized treatment strategies.
“Significant interpatient differences exist in molecular characteristics, tumor progression dynamics, and treatment sensitivity, posing major challenges to standardized treatment strategies (6, 7).”
From Bioinformatics-based identification of glycolysis-related signatures associated with drug resistance and prognosis in lung adenocarcinoma (2026) · cites this paper as [7]
The Results and Discussion describe molecular differences and different rates of progression among KRAS G12-mutant LUAD subtypes, and argue for tailored treatment strategies. The Results associate subtype signatures with immunotherapy response, but the Discussion says treatment responses were not directly assessed. Thus, the paper supports heterogeneity within the studied group, not the claim of established interpatient differences in treatment sensitivity across LUAD generally. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., & Jemal, A. (2024) · CA: a cancer journal for clinicians · doi:10.3322/caac.21834 · Cited by 27,064 · see citing works
Defining a Cancer Dependency Map
Tsherniak, A., Vazquez, F., Montgomery, P. G., Weir, B. A., Kryukov, G., Cowley, G. S., Gill, S., Harrington, W. F., Pantel, S., Krill-Burger, J. M., et al. (2017) · Cell · doi:10.1016/j.cell.2017.06.010 · Cited by 3,276 · see citing works
KRAS Mutation: From Undruggable to Druggable in Cancer
Huang, L., Guo, Z., Wang, F., & Fu, L. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00780-4 · Cited by 1,127 · see citing works
Self-citationDong, Z.-Y., Zhong, W.-Z., Zhang, X.-C., Su, J., Xie, Z., Liu, S.-Y., Tu, H.-Y., Chen, H.-J., Sun, Y.-L., Zhou, Q., et al. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-2554 · Cited by 959 · see citing works
Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma
Gillette, M. A., Satpathy, S., Cao, S., Dhanasekaran, S. M., Vasaikar, S. V., Krug, K., Petralia, F., Li, Y., Liang, W.-W., Reva, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.013 · Cited by 820 · see citing works
Calcinotto, A., Filipazzi, P., Grioni, M., Iero, M., De Milito, A., Ricupito, A., Cova, A., Canese, R., Jachetti, E., Rossetti, M., et al. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-1272 · Cited by 640 · see citing works
Arbour, K. C., Jordan, E., Kim, H. R., Dienstag, J., Yu, H. A., Sanchez-Vega, F., Lito, P., Berger, M., Solit, D. B., Hellmann, M., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-1841 · Cited by 466 · see citing works
Zhou, C., Li, C., Luo, L., Li, X., Jia, K., He, N., Mao, S., Wang, W., Shao, C., Liu, X., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.06.001 · Cited by 102 · see citing works
Flagged first, then by citations
Research works printed but not linked: 49
- [2]Han B. Zheng R. Zeng H. Wang S. Sun K. Chen R. Cancer incidence and mortality in China, 2022 Journal of the National Cancer Center 4 1 2024 47 53 39036382 PMC11256708
- [3]Molina J.R. Yang P. Cassivi S.D. Schild S.E. Adjei A.A. Non-small cell lung cancer: epidemiology, risk factors, treatment, and survivorship Mayo Clin Proc 83 5 2008 584 594 18452692 PMC2718421
- [4]Barta J.A. Powell C.A. Wisnivesky J.P. Global epidemiology of lung cancer Ann Glob Health 2019 PMC6724220 30741509
- [5]Araghi M. Mannani R. Heidarnejadmaleki A. Hamidi A. Rostami S. Safa S.H. Faramarzi F. Khorasani S. Alimohammadi M. Tahmasebi S. Recent advances in non-small cell lung cancer targeted therapy; an update review Cancer Cell Int 23 1 2023 162 37568193 PMC10416536
- [6]Xu J.-Y. Zhang C. Wang X. Zhai L. Ma Y. Mao Y. Integrative proteomic characterization of human lung adenocarcinoma Cell 182 1 2020 245 261.e217 32649877
- [7]Chen Y.-J. Roumeliotis T.I. Chang Y.-H. Chen C.-T. Han C.-L. Lin M.-H. Proteogenomics of non-smoking lung cancer in east Asia delineates molecular signatures of pathogenesis and progression Cell 182 1 2020 226 244.e217 32649875
- [8]Singhal A. Li B.T. O’Reilly E.M. Targeting KRAS in cancer Nat Med 30 4 2024 969 983 38637634 PMC11845254
- [9]Tan Z. Xue H. Sun Y. Zhang C. Song Y. Qi Y. The role of tumor inflammatory microenvironment in lung cancer Front Pharmacol 12 2021 PMC8166205 34079469
- [10]Li Y. Jiang M. Aye L. Luo L. Zhang Y. Xu F. UPP1 promotes lung adenocarcinoma progression through the induction of an immunosuppressive microenvironment Nat Commun 15 1 2024 1200 38331898 PMC10853547
- [11]Genova C. Dellepiane C. Carrega P. Sommariva S. Ferlazzo G. Pronzato P. Therapeutic implications of tumor microenvironment in lung cancer: focus on immune checkpoint blockade Front Immunol 12 2022 PMC8777268 35069581
- [13]Zdanov S. Mandapathil M. Abu Eid R. Adamson-Fadeyi S. Wilson W. Qian J. Mutant KRAS conversion of conventional t cells into regulatory t cells Cancer Immunol Res 4 4 2016 354 365 26880715 PMC4884020
- [14]Nakamura K. Kitani A. Fuss I. Pedersen A. Harada N. Nawata H. TGF-β1 plays an important role in the mechanism of CD4+CD25+ regulatory t cell activity in both humans and mice J Immunol 172 2 2004 834 842 14707053
- [16]Budczies J. Romanovsky E. Kirchner M. Neumann O. Blasi M. Schnorbach J. KRAS and TP53 co-mutation predicts benefit of immune checkpoint blockade in lung adenocarcinoma Br J Cancer 131 3 2024 524 533 38866964 PMC11300455
- [17]Zehir A. Benayed R. Shah R.H. Syed A. Middha S. Kim H.R. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients Nat Med 23 6 2017 703 713 28481359 PMC5461196
- [18]Wu L. Yao H. Chen H. Wang A. Guo K. Gou W. Landscape of somatic alterations in large-scale solid tumors from an asian population Nat Commun 13 1 2022 4264 35871175 PMC9308789
- [19]Mina M. Raynaud F. Tavernari D. Battistello E. Sungalee S. Saghafinia S. Conditional selection of genomic alterations dictates cancer evolution and oncogenic dependencies Cancer Cell 32 2 2017 155 168.e156 28756993
- [20]Eichner LJ, Curtis SD, Brun SN, McGuire CK, Gushterova I, Baumgart JT, Trefts E, Ross DS, Rymoff TJ, Shaw RJ: HDAC3 is critical in tumor development and therapeutic resistance in Kras-mutant non–small cell lung cancer. Science Adv 9 (11):eadd3243. PMC10022903 36930718
- [21]Kazi A. Chen L. Xiang S. Vangipurapu R. Yang H. Beato F. Global phosphoproteomics reveal CDK suppression as a vulnerability to KRas addiction in pancreatic cancer Clin Cancer Res 27 14 2021 4012 4024 33879459 PMC8493485
- [22]Klomp JE, Diehl JN, Klomp JA, Edwards AC, Yang R, Morales AJ, Taylor KE, Drizyte-Miller K, Bryant KL, Schaefer A, et al. Determining the ERK-regulated phosphoproteome driving KRAS-mutant cancer. Science 384(6700):eadk0850. PMC11301400 38843329
- [23]Najumudeen A.K. Ceteci F. Fey S.K. Hamm G. Steven R.T. Hall H. The amino acid transporter SLC7A5 is required for efficient growth of KRAS-mutant colorectal cancer Nat Genet 53 1 2021 16 26 33414552
- [25]Miyata N. Azuma T. Hozawa S. Higuchi H. Yokoyama A.B.A. Kabashima A.M.S. Transforming growth factor β and Ras/MEK/ERK signaling regulate the expression level of a novel tumor suppressor lefty Pancreas 41 5 2012 22441145
- [26]Streeck H. Kwon D.S. Pyo A. Flanders M. Chevalier M.F. Law K. Epithelial adhesion molecules can inhibit HIV-1–specific CD8+ T-cell functions Blood 117 19 2011 5112 5122 21403126 PMC3109536
- [27]Salerno E.P. Bedognetti D. Mauldin I.S. Deacon D.H. Shea S.M. Pinczewski J. Human melanomas and ovarian cancers overexpressing mechanical barrier molecule genes lack immune signatures and have increased patient mortality risk OncoImmunology 5 12 2016 e1240857 PMC5215363 28123876
- [28]Yu T. Liu Z. Tao Q. Xu X. Li X. Li Y. Targeting tumor-intrinsic SLC16A3 to enhance anti-PD-1 efficacy via tumor immune microenvironment reprogramming Cancer Lett 589 2024 216824 38522774
- [29]Feng R. Liu F. Li R. Zhou Z. Lin Z. Lin S. The rapid proximity labeling system PhastID identifies ATP6AP1 as an unconventional GEF for Rheb Cell Res 34 5 2024 355 369 38448650 PMC11061317
- [30]Polacco B.J. Lobingier B.T. Blythe E.E. Abreu N. Khare P. Howard M.K. Profiling the proximal proteome of the activated μ-opioid receptor Nat Chem Biol 20 9 2024 1133 1143 38528119 PMC11365811
- [31]Kotlyar M. Pastrello C. Ahmed Z. Chee J. Varyova Z. Jurisica I. IID 2021: towards context-specific protein interaction analyses by increased coverage, enhanced annotation and enrichment analysis Nucleic Acids Res 50 D1 2022 D640 D647 34755877 PMC8728267
- [33]Yang Y. Bolomsky A. Oellerich T. Chen P. Ceribelli M. Häupl B. Oncogenic RAS commandeers amino acid sensing machinery to aberrantly activate mTORC1 in multiple myeloma Nat Commun 13 1 2022 5469 36115844 PMC9482638
- [34]Pizzagalli M.D. Bensimon A. Superti-Furga G. A guide to plasma membrane solute carrier proteins FEBS J 288 9 2021 2784 2835 32810346 PMC8246967
- [35]Ghandi M. Huang F.W. Jané-Valbuena J. Kryukov G.V. Lo C.C. McDonald E.R. Next-generation characterization of the cancer cell line encyclopedia Nature 569 7757 2019 503 508 31068700 PMC6697103
- [36]Yan H. He Q. Gao Y. He X. Luo H. Shao L. SLC4A7 suppresses lung adenocarcinoma oncogenesis by reducing lactate transport and protein lactylation Int J Oncol 66 5 2025 33 40084702 PMC12002671
- [37]Cho J.-W. Hong M.H. Ha S.-J. Kim Y.-J. Cho B.C. Lee I. Genome-wide identification of differentially methylated promoters and enhancers associated with response to anti-PD-1 therapy in non-small cell lung cancer Exp Mol Med 52 9 2020 1550 1563 32879421 PMC8080767
- [38]Ch'En F.F.T. Villafuerte F.C. Swietach P. Cobden P.M. Vaughan-Jones R.D. S0859, an N-cyanosulphonamide inhibitor of sodium-bicarbonate cotransport in the heart Br J Pharmacol 153 5 2008 972 982 18204485 PMC2267275
- [39]Lee J.K. Sivakumar S. Schrock A.B. Madison R. Fabrizio D. Gjoerup O. Montesion M et al: Comprehensive pan-cancer genomic landscape of KRAS altered cancers and real-world outcomes in solid tumors npj Precis Oncol 6(1):91 2022 PMC9734185 36494601
- [41]Bischoff P. Reck M. Overbeck T. Christopoulos P. Rittmeyer A. Lüders H. Outcome of first-line treatment with pembrolizumab according to KRAS/TP53 mutational status for nonsquamous programmed death-ligand 1–high (≥50%) NSCLC in the German national network genomic medicine lung cancer J Thorac Oncol 19 5 2024 803 817 38096950
- [42]Soula M. Unlu G. Welch R. Chudnovskiy A. Uygur B. Shah V. Glycosphingolipid synthesis mediates immune evasion in KRAS-driven cancer Nature 633 8029 2024 451 458 39112706 PMC11892728
- [43]Gu M. Xu T. Chang P. KRAS/LKB1 and KRAS/TP53 co-mutations create divergent immunesignatures in lung adenocarcinomas Ther Adv Med Oncol 13 2021 PMC8072935 33995590
- [44]Issahaku A.R. Mukelabai N. Agoni C. Rudrapal M. Aldosari S.M. Almalki S.G. Characterization of the binding of MRTX1133 as an avenue for the discovery of potential KRASG12D inhibitors for cancer therapy Sci Rep 12 1 2022 17796 36273239 PMC9588042
- [45]Zheng W, Jiang D, Chen S, Wu M, Yan B, Zhai J, Shi Y, Xie BIN, Xie X, Hu K, et al. Exploring the therapeutic potential of precision T-Cell Receptors (TCRs) in targeting KRAS G12D cancer through in vitro development. Oncol Res 2024; 32(12). PMC11576958 39574477
- [47]Ramirez C. Hauser A.D. Vucic E.A. Bar-Sagi D. Plasma membrane V-ATPase controls oncogenic RAS-induced macropinocytosis Nature 576 7787 2019 477 481 31827278 PMC7048194
- [48]Cheng S.-C. Quintin J. Cramer R.A. Shepardson K.M. Saeed S. Kumar V. mTOR- and HIF-1α–mediated aerobic glycolysis as metabolic basis for trained immunity Science 345 6204 2014 1250684 PMC4226238 25258083
- [49]Wang Z.-H. Peng W.-B. Zhang P. Yang X.-P. Zhou Q. Lactate in the tumour microenvironment: from immune modulation to therapy eBioMedicine 73 2021 PMC8524104 34656878
- [51]Angelin A. Gil-de-Gómez L. Dahiya S. Jiao J. Guo L. Levine M.H. Foxp3 reprograms T cell metabolism to function in low-glucose, high-lactate environments Cell Metabolism 25 6 2017 1282 1293.e1287 28416194 PMC5462872
- [52]Renner K. Bruss C. Schnell A. Koehl G. Becker H.M. Fante M. Restricting glycolysis preserves T cell effector functions and augments checkpoint therapy Cell Rep 29 1 2019 135 150.e139 31577944
- [53]Cappellesso F. Orban M.-P. Shirgaonkar N. Berardi E. Serneels J. Neveu M.-A. Targeting the bicarbonate transporter SLC4A4 overcomes immunosuppression and immunotherapy resistance in pancreatic cancer Nature Cancer 3 12 2022 1464 1483 36522548 PMC9767871
- [54]Mina M. Iyer A. Tavernari D. Raynaud F. Ciriello G. Discovering functional evolutionary dependencies in human cancers Nat Genet 52 11 2020 1198 1207 32989323
- [55]Cotto K.C. Wagner A.H. Feng Y.-Y. Kiwala S. Coffman A.C. Spies G. DGIdb 3.0: a redesign and expansion of the drug–gene interaction database Nucleic Acids Res 46 D1 2018 D1068 D1073 29156001 PMC5888642
- [56]Connor A.A. Denroche R.E. Jang G.H. Lemire M. Zhang A. Chan-Seng-Yue M. Integration of genomic and transcriptional features in pancreatic cancer reveals increased cell cycle progression in metastases Cancer Cell 35 2 2019 267 282.e267 30686769 PMC6398439
- [57]Lu X. Meng J. Zhou Y. Jiang L. Yan F. MOVICS: an R package for multi-omics integration and visualization in cancer subtyping Bioinformatics 36 22–23 2021 5539 5541 33315104
Cited by
Sorted by citations
Zheng, Q., Liu, Y., Li, T., Zhang, X., Geng, Y., Chen, Z., Zhou, J., Fan, W., Wang, Y., Zhang, L., et al. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1871582
- Authors
- Shi, X., Hu, L., Huang, Y., Zhang, M.-F., Ying, X., Yuan, X., Wen, N., Lu, J., Zou, H., Tan, X., He, Q.-Y., Wang, F., Yang, H., & Zhang, C. Z.
- Affiliations
- Jinan University (CN)
- Sun Yat-sen University Cancer Center (CN)
- Sun Yat-sen University (CN)
- Corresponding author
- Zhang, Mei-Fang
- Wang, Fang
- Yang, Hong
- Zhang, Chris Zhiyi
- ORCID
- Venue
- Journal of Advanced Research
- Publisher
- Elsevier BV
- Published
- 2026-06
- Volume
- 84
- Pages
- 675-693
- ISSN
- 2090-1224 (ISSN-L)
- 2090-1232
- PMC
- PMC13227296
- OpenAlex
- W4414189878
- Cited by
- 6
- References
- 8
- Citations by year
- 2026: 4 · 2025: 2
- FWCI
- 3.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Advanced Research (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- Funders
- Fundamental Research Funds for the Central Universities (21624109)
- National Key Research and Development Program of China (2022YFA1304604)
- National Natural Science Foundation of China (82273110, 82273032)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Health Sciences › Medicine › Oncology › Lung Cancer Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- lung adenocarcinoma, KRAS G12C, proteogenomics, tumor immune microenvironment, immune cell infiltration, protein-protein interaction, SLC4A7, molecular subtypes, immunotherapy response, patient stratification
- MeSH terms
- Adenocarcinoma of Lung, Female, Humans, Lung Neoplasms, Male, Mutation, Proto-Oncogene Proteins p21(ras), Proteomics, Tandem Mass Spectrometry, High-Throughput Nucleotide Sequencing, Tumor Microenvironment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review