Abstract
Anchoring filament protein ladinin-1 (LAD1) codes for an anchor filament protein in the basement membrane. Here, we have aimed to determine its potential role in LUAD. According to the comprehensive analyses conducted in this study, we studied the expression, prognostic significance, function, methylation, copy number variations, and the immune cell infiltration of LAD1 in LUAD. A higher level of LAD1 gene expression was observed in the LUAD tumor tissues compared to the normal lung tissues (p < 0.001). Furthermore, the multivariate analysis indicated that a higher LAD1 gene expression level was the independent prognostic factor. Additionally, the DNA methylation level of the LAD1 was inversely linked to its expression (p < 0.001). We noted that the patients affected due to LAD1 hypomethylation showed a very low overall survival rate compared to the patients with a higher LAD1 methylation score (p < 0.05). Moreover, the results of the immunity analysis indicated that the LAD1 expression might be inversely linked to the immune cell infiltration degree, expression of the infiltrated immune cells, and the PD-L1 levels. Lastly, we supplemented some verification to increase the rigor of the study. The results suggested that high expression of LAD1 may be related to cold tumors. Hence, this indirectly reflects that the immunotherapy effect of LUAD patients with high LAD1 expression might be worse. Based on the role played by the LAD1 in the tumor immune microenvironment, it can be considered a potential biomarker for predicting the immunotherapy response to LUAD.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The datasets generated and/or analysed during the current study are available in the public databases, including the UCSC Xena browser (https://xenabrowser.Net/datapages/), the GEO database (https://www.ncbi.nlm.nih.gov/), the Human Protein Atlas (https://www.proteinatlas.org), the TIMER (https://cistrome.shinyapps.io/timer/), the TIMER2.0 software (https://timer.cistrome.org/) the Oncomine database (www.oncomine.org), the cBioPortal (https://www.cbioportal.org/), the MethSurv (https://biit.cs.ut.ee/methsurv/), the UALCAN (http://ualcan.path.uab.edu/), the GEPIA (http://gepia.cancer-pku.cn/index.html), and The TISIDB (http://cis.hku.hk/TISIDB/index.php). The code used for analysis in the manuscript was provided in the Supplementary Information file.
Abbreviations
- LAD1 :
-
Anchoring filament protein ladinin-1
- LUAD:
-
Lung adenocarcinoma
- NSCLC:
-
Non-small cell lung cancer
- LUSC:
-
Lung squamous cell carcinoma
- OS:
-
Overall survival
- TCGA:
-
The Cancer Genome Atlas
- GEO:
-
Gene Expression Omnibus
- ROC:
-
Receiver operating characteristic
- GSEA:
-
Gene set enrichment analysis
- NOS:
-
Not otherwise specified
- MSigDB:
-
Molecular Signatures Database
- NES:
-
Normalized enrichment score
- FDR:
-
False discovery rate
- ssGSEA:
-
Single-sample Gene Set Enrichment Analysis
- DEGs:
-
Differentially expressed genes
- EGFR :
-
Epithelial growth factor receptor
- Mut:
-
Mutation type
- Wt:
-
Wild type
- ALK :
-
Anaplastic lymphoma kinase
- KRAS :
-
Kirsten rat sarcoma viral oncogene
- HR:
-
Hazard ratio
- CI:
-
Confidence interval
- TPR:
-
True positive rate
- FPR:
-
False positive rate
- ICIs:
-
Immune checkpoint inhibitors
References
Aktas ON, Ozturk AB, Erman B, Erus S, Tanju S, Dilege S (2018) Role of natural killer cells in lung cancer. J Cancer Res Clin Oncol 144(6):997–1003. https://doi.org/10.1007/s00432-018-2635-3
Beer DG, Kardia SL, Huang CC, Giordano TJ, Levin AM, Misek DE et al (2002) Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat Med 8(8):816–824. https://doi.org/10.1038/nm733
Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P et al (2001) Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci USA 98(24):13790–13795. https://doi.org/10.1073/pnas.191502998
Bindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC et al (2013) Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity 39(4):782–795. https://doi.org/10.1016/j.immuni.2013.10.003
Brundage MD, Davies D, Mackillop WJ (2002) Prognostic factors in non-small cell lung cancer: a decade of progress. Chest 122(3):1037–1057. https://doi.org/10.1378/chest.122.3.1037
Chandrashekar DS, Bashel B, Balasubramanya SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi B et al (2017) UALCAN: a portal for facilitating tumor subgroup gene expression and survival analyses. Neoplasia 19(8):649–658. https://doi.org/10.1016/j.neo.2017.05.002
Chandrashekar DS, Karthikeyan SK, Korla PK, Patel H, Shovon AR, Athar M et al (2022) UALCAN: an update to the integrated cancer data analysis platform. Neoplasia 25:18–27. https://doi.org/10.1016/j.neo.2022.01.001
Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D et al (2017) Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep 18(1):248–262. https://doi.org/10.1016/j.celrep.2016.12.019
Evison M, AstraZeneca UKL (2020) The current treatment landscape in the UK for stage III NSCLC. Br J Cancer 123(Suppl 1):3–9. https://doi.org/10.1038/s41416-020-01069-z
Faruki H, Mayhew GM, Serody JS, Hayes DN, Perou CM, Lai-Goldman M (2017) Lung adenocarcinoma and squamous cell carcinoma gene expression subtypes demonstrate significant differences in tumor immune landscape. J Thorac Oncol 12(6):943–953. https://doi.org/10.1016/j.jtho.2017.03.010
Forde PM, Kelly RJ, Brahmer JR (2014) New strategies in lung cancer: translating immunotherapy into clinical practice. Clin Cancer Res 20(5):1067–1073. https://doi.org/10.1158/1078-0432.CCR-13-0731
Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO et al (2013) Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 6(269):pl1. https://doi.org/10.1126/scisignal.2004088
Halliday PR, Blakely CM, Bivona TG (2019) Emerging targeted therapies for the treatment of non-small cell lung cancer. Curr Oncol Rep 21(3):21. https://doi.org/10.1007/s11912-019-0770-x
Heuvers ME, Wisnivesky J, Stricker BH, Aerts JG (2012) Generalizability of results from the National Lung Screening Trial. Eur J Epidemiol 27(9):669–672. https://doi.org/10.1007/s10654-012-9720-8
Huang WT, Cen WL, He RQ, Xie Y, Zhang Y, Li P et al (2017) Effect of miR146a5p on tumor growth in NSCLC using chick chorioallantoic membrane assay and bioinformatics investigation. Mol Med Rep 16(6):8781–8792. https://doi.org/10.3892/mmr.2017.7713
Hui L, Chen Y (2015) Tumor microenvironment: sanctuary of the devil. Cancer Lett 368(1):7–13. https://doi.org/10.1016/j.canlet.2015.07.039
Kim J, Bae JS (2016) Tumor-associated macrophages and neutrophils in tumor microenvironment. Mediat Inflamm 2016:6058147. https://doi.org/10.1155/2016/6058147
Klobucar M, Sedic M, Gehrig P, Grossmann J, Bilic M, Kovac-Bilic L et al (2016) Basement membrane protein ladinin-1 and the MIF-CD44-beta1 integrin signaling axis are implicated in laryngeal cancer metastasis. Biochim Biophys Acta 1862(10):1938–1954. https://doi.org/10.1016/j.bbadis.2016.07.014
Li B, Severson E, Pignon JC, Zhao H, Li T, Novak J et al (2016) Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biol 17(1):174. https://doi.org/10.1186/s13059-016-1028-7
Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS et al (2017) TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res 77(21):e108–e110. https://doi.org/10.1158/0008-5472.CAN-17-0307
Li T, Fu J, Zeng Z, Cohen D, Li J, Chen Q et al (2020) TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res 48(W1):W509–W514. https://doi.org/10.1093/nar/gkaa407
Macheleidt IF, Dalvi PS, Lim SY, Meemboor S, Meder L, Kasgen O et al (2018) Preclinical studies reveal that LSD1 inhibition results in tumor growth arrest in lung adenocarcinoma independently of driver mutations. Mol Oncol 12(11):1965–1979. https://doi.org/10.1002/1878-0261.12382
Modhukur V, Iljasenko T, Metsalu T, Lokk K, Laisk-Podar T, Vilo J (2018) MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data. Epigenomics 10(3):277–288. https://doi.org/10.2217/epi-2017-0118
Montano-Samaniego M, Bravo-Estupinan DM, Mendez-Guerrero O, Alarcon-Hernandez E, Ibanez-Hernandez M (2020) Strategies for targeting gene therapy in cancer cells with tumor-specific promoters. Front Oncol 10:605380. https://doi.org/10.3389/fonc.2020.605380
Moon B, Yang SJ, Park SM, Lee SH, Song KS, Jeong EJ et al (2020) LAD1 expression is associated with the metastatic potential of colorectal cancer cells. BMC Cancer 20(1):1180. https://doi.org/10.1186/s12885-020-07660-0
Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J et al (2003) PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet 34(3):267–273. https://doi.org/10.1038/ng1180
Motoki K, Megahed M, LaForgia S, Uitto J (1997) Cloning and chromosomal mapping of mouse ladinin, a novel basement membrane zone component. Genomics 39(3):323–330. https://doi.org/10.1006/geno.1996.4507
Ohaegbulam KC, Assal A, Lazar-Molnar E, Yao Y, Zang X (2015) Human cancer immunotherapy with antibodies to the PD-1 and PD-L1 pathway. Trends Mol Med 21(1):24–33. https://doi.org/10.1016/j.molmed.2014.10.009
Okayama H, Kohno T, Ishii Y, Shimada Y, Shiraishi K, Iwakawa R et al (2012) Identification of genes upregulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. Cancer Res 72(1):100–111. https://doi.org/10.1158/0008-5472.CAN-11-1403
Peters I, Dubrowinskaja N, Abbas M, Seidel C, Kogosov M, Scherer R et al (2014) DNA methylation biomarkers predict progression-free and overall survival of metastatic renal cell cancer (mRCC) treated with antiangiogenic therapies. PLoS ONE 9(3):e91440. https://doi.org/10.1371/journal.pone.0091440
Ponten F, Jirstrom K, Uhlen M (2008) The Human Protein Atlas—a tool for pathology. J Pathol 216(4):387–393. https://doi.org/10.1002/path.2440
Remark R, Becker C, Gomez JE, Damotte D, Dieu-Nosjean MC, Sautes-Fridman C et al (2015) The non-small cell lung cancer immune contexture. A major determinant of tumor characteristics and patient outcome. Am J Respir Crit Care Med 191(4):377–390. https://doi.org/10.1164/rccm.201409-1671PP
Roth L, Srivastava S, Lindzen M, Sas-Chen A, Sheffer M, Lauriola M et al (2018) SILAC identifies LAD1 as a filamin-binding regulator of actin dynamics in response to EGF and a marker of aggressive breast tumors. Sci Signal 11(515):eaan0949. https://doi.org/10.1126/scisignal.aan0949
Ru B, Wong CN, Tong Y, Zhong JY, Zhong SSW, Wu WC et al (2019) TISIDB: an integrated repository portal for tumor-immune system interactions. Bioinformatics 35(20):4200–4202. https://doi.org/10.1093/bioinformatics/btz210
Rusinek D, Swierniak M, Chmielik E, Kowal M, Kowalska M, Cyplinska R et al (2015) BRAFV600E-associated gene expression profile: early changes in the transcriptome, based on a transgenic mouse model of papillary thyroid carcinoma. PLoS ONE 10(12):e0143688. https://doi.org/10.1371/journal.pone.0143688
Selamat SA, Chung BS, Girard L, Zhang W, Zhang Y, Campan M et al (2012) Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression. Genome Res 22(7):1197–1211. https://doi.org/10.1101/gr.132662.111
Shoji F, Morodomi Y, Akamine T, Takamori S, Katsura M, Takada K et al (2016) Predictive impact for postoperative recurrence using the preoperative prognostic nutritional index in pathological stage I non-small cell lung cancer. Lung Cancer 98:15–21. https://doi.org/10.1016/j.lungcan.2016.05.010
Siegel Y, Kuker R, Danton G, Gonzalez J (2016) Occult lung cancer occluding a pulmonary vein with suspected venous Infarction, mimicking pneumonia and a pulmonary embolus. J Emerg Med 51(2):e11–e14. https://doi.org/10.1016/j.jemermed.2015.12.019
Siegel RL, Miller KD, Jemal A (2020) Cancer statistics, 2020. CA Cancer J Clin 70(1):7–30. https://doi.org/10.3322/caac.21590
Stearman RS, Dwyer-Nield L, Zerbe L, Blaine SA, Chan Z, Bunn PA Jr et al (2005) Analysis of orthologous gene expression between human pulmonary adenocarcinoma and a carcinogen-induced murine model. Am J Pathol 167(6):1763–1775. https://doi.org/10.1016/S0002-9440(10)61257-6
Stewart GD, Powles T, Van Neste C, Meynert A, O’Mahony F, Laird A et al (2016) Dynamic epigenetic changes to VHL occur with sunitinib in metastatic clear cell renal cancer. Oncotarget 7(18):25241–25250. https://doi.org/10.18632/oncotarget.8308
Su LJ, Chang CW, Wu YC, Chen KC, Lin CJ, Liang SC et al (2007) Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme. BMC Genomics 8:140. https://doi.org/10.1186/1471-2164-8-140
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102(43):15545–15550. https://doi.org/10.1073/pnas.0506580102
Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z (2017) GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res 45(W1):W98–W102. https://doi.org/10.1093/nar/gkx247
Teixeira JC, de Filippo C, Weihmann A, Meneu JR, Racimo F, Dannemann M et al (2015) Long-term balancing selection in LAD1 maintains a missense trans-species polymorphism in humans, chimpanzees, and bonobos. Mol Biol Evol 32(5):1186–1196. https://doi.org/10.1093/molbev/msv007
Testa U, Castelli G, Pelosi E (2018) Lung cancers: molecular characterization, clonal heterogeneity and evolution, and cancer stem cells. Cancers 10(8):248. https://doi.org/10.3390/cancers10080248
van Vlodrop IJH, Joosten SC, De Meyer T, Smits KM, Van Neste L, Melotte V et al (2017) A four-gene promoter methylation marker panel consisting of GREM1, NEURL, LAD1, and NEFH predicts survival of clear cell renal cell cancer patients. Clin Cancer Res 23(8):2006–2018. https://doi.org/10.1158/1078-0432.CCR-16-1236
Wang SS, Liu W, Ly D, Xu H, Qu L, Zhang L (2019) Tumor-infiltrating B cells: their role and application in anti-tumor immunity in lung cancer. Cell Mol Immunol 16(1):6–18. https://doi.org/10.1038/s41423-018-0027-x
Wu F, Wang L, Zhou C (2021) Lung cancer in China: current and prospect. Curr Opin Oncol 33(1):40–46. https://doi.org/10.1097/CCO.0000000000000703
Zhang Y, Zhang Z (2020) The history and advances in cancer immunotherapy: understanding the characteristics of tumor-infiltrating immune cells and their therapeutic implications. Cell Mol Immunol 17(8):807–821. https://doi.org/10.1038/s41423-020-0488-6
Acknowledgements
We sincerely thank the public databases, including TCGA, UCSC Xena, GEO, Oncomine, HPA, TIMER, TIMER2.0, cBioPortal, GEPIA, UALCAN, TISIDB, and MethSurv for providing open access.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. KY, YPZ and SX designed this study. KY, YPZ, YLY and YJX contributed to the data collection. KY, YPZ and YLY analyzed the data. SX supervised the study. KY, YPZ, YLY and YJX wrote the manuscript. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors have no relevant financial or non-financial interests to disclose.
Ethical Approval and Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Yuan, K., Zhang, Y., Yu, Y. et al. Anchoring Filament Protein Ladinin-1 is an Immunosuppressive Microenvironment and Cold Tumor Correlated Prognosticator in Lung Adenocarcinoma. Biochem Genet 61, 2173–2202 (2023). https://doi.org/10.1007/s10528-023-10370-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10528-023-10370-4