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BMC Cancer
Published in: BMC Cancer 1/2023

Open Access 01-12-2023 | Research

Lactate dehydrogenase D serves as a novel biomarker for prognosis and immune infiltration in lung adenocarcinoma

Authors: Yu Zhang, Tianyi Zhang, Yingdong Zhao, Hongdi Wu, Qiang Zhen, Suwei Zhu, Shaoshuai Hou

Published in: BMC Cancer | Issue 1/2023

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Abstract

Background

Lung cancer is reported to be the leading cause of death in males and females, globally. Increasing evidence highlights the paramount importance of Lactate dehydrogenase D (LDHD) in different types of cancers, though it’s role in lung adenocarcinoma (LUAD) is still inadequately explored. In this study, we aimed to investigate and determine the relationship between LDHD and LUAD.

Methods

The collection of the samples was guided by The Cancer Genome Atlas (TCGA) datasets and Gene Expression Omnibus (GEO). To ascertain various aspects around LDHD function, we analyzed different expression genes (DEGs), functional enrichment, and protein–protein interaction (PPI) networks. The predictive values for LDHD were collectively determined using the Kaplan–Meier method, Cox regression analysis, and a nomogram. Evaluation of the immune infiltration analysis was completed using Estimate and ssGSEA. The prediction of the immunotherapy response was based on TIDE and IPS. The LDHD expression levels in LUAD were validated through Western blot, qPCR, and immunohistochemistry methods. Wound healing and transwell assays were also performed to illustrate the aggressive features in LUAD cell lines.

Results

The results showed that LDHD was generally downregulated in LUAD patients, with the low LDHD group presenting a decline in OS, DSS, and PFI. Enriched pathways, which include pyruvate metabolism, central carbon metabolism, and oxidative phosphorylation were observed through KEGG analysis. It was also noted that the expression of LDHD expression was inversely related to immune cell infiltration and typical checkpoints. The high LDHD group’s response to immunotherapy was remarkable, particularly in CTAL4 + /PD1- therapy. In vitro studies revealed that the overexpression of LDHD caused tumor migration and invasion to be suppressed.

Conclusion

In conclusion, our study revealed that LDHD might be an effective predictor of prognosis and immune filtration, possibly leading to better choices for immunotherapy.
Appendix
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Literature
1.
Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17–48.PubMed
2.
Cascone T, Fradette J, Pradhan M, Gibbons DL. Tumor Immunology and Immunotherapy of non-small-cell lung cancer. Cold Spring Harb Perspect Med. 2022;12(5):a037895.PubMed
3.
Chen P, Liu Y, Wen Y, Zhou C. Non-small cell lung cancer in China. Cancer Commun (Lond). 2022;42(10):937–70.PubMed
4.
Singh SS, Dahal A, Shrestha L, Jois SD. Genotype driven therapy for non-small cell lung cancer: resistance, pan inhibitors and immunotherapy. Curr Med Chem. 2020;27(32):5274–316.PubMed
5.
Koppenol WH, Bounds PL, Dang CV. Otto Warburg’s contributions to current concepts of cancer metabolism. Nat Rev Cancer. 2011;11(5):325–37.PubMed
6.
7.
San-Millan I, Brooks GA. Reexamining cancer metabolism: lactate production for carcinogenesis could be the purpose and explanation of the Warburg Effect. Carcinogenesis. 2017;38(2):119–33.PubMed
8.
Wang JM, Jiang JY, Zhang DL, Du X, Wu T, Du ZX. HYOU1 facilitates proliferation, invasion and glycolysis of papillary thyroid cancer via stabilizing LDHB mRNA. J Cell Mol Med. 2021;25(10):4814–25.PubMedCentral
9.
Frank AC, Raue R, Fuhrmann DC, Sirait-Fischer E, Reuse C, Weigert A, Lütjohann D, Hiller K, Syed SN, Brüne B. Lactate dehydrogenase B regulates macrophage metabolism in the tumor microenvironment. Theranostics. 2021;11(15):7570–88.PubMedPubMedCentral
10.
Urbańska K, Orzechowski A. Unappreciated role of LDHA and LDHB to control apoptosis and autophagy in tumor cells. Int J Mol Sci. 2019;20(9):2085.PubMedPubMedCentral
11.
Shi L, Yan H, An S, Shen M, Jia W, Zhang R, Zhao L, Huang G, Liu J. SIRT5-mediated deacetylation of LDHB promotes autophagy and tumorigenesis in colorectal cancer. Mol Oncol. 2019;13(2):358–75.PubMed
12.
Liu J, Chen G, Liu Z, Liu S, Cai Z, You P, Ke Y, Lai L, Huang Y, Gao H, et al. Aberrant FGFR tyrosine kinase signaling enhances the Warburg effect by reprogramming LDH isoform expression and activity in prostate cancer. Cancer Res. 2018;78(16):4459–70.PubMedPubMedCentral
13.
Hou X, Shi X, Zhang W, Li D, Hu L, Yang J, Zhao J, Wei S, Wei X, Ruan X, et al. LDHA induces EMT gene transcription and regulates autophagy to promote the metastasis and tumorigenesis of papillary thyroid carcinoma. Cell Death Dis. 2021;12(4):347.PubMedPubMedCentral
14.
Flick MJ, Konieczny SF. Identification of putative mammalian D-lactate dehydrogenase enzymes. Biochem Biophys Res Commun. 2002;295(4):910–6.PubMed
15.
Song KJ, Yu XN, Lv T, Chen YL, Diao YC, Liu SL, Wang YK, Yao Q. Expression and prognostic value of lactate dehydrogenase-A and -D subunits in human uterine myoma and uterine sarcoma. Medicine (Baltimore). 2018;97(14):e0268.PubMed
16.
de Bari L, Moro L, Passarella S. Prostate cancer cells metabolize d-lactate inside mitochondria via a D-lactate dehydrogenase which is more active and highly expressed than in normal cells. FEBS Lett. 2013;587(5):467–73.PubMed
17.
Wang Y, Li G, Wan F, Dai B, Ye D. Prognostic value of D-lactate dehydrogenase in patients with clear cell renal cell carcinoma. Oncol Letters. 2018;16(1):866–74.
18.
Blum A, Wang P, Zenklusen JC. SnapShot: TCGA-Analyzed Tumors. Cell. 2018;173(2):530.PubMed
19.
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.PubMedPubMedCentral
20.
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. Gene Ontol Consortium Nat Genet. 2000;25(1):25–9.
21.
22.
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50.PubMedPubMedCentral
23.
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–7.PubMedPubMedCentral
24.
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607-d613.PubMed
25.
Schober P, Vetter TR. Kaplan-meier curves, log-rank tests, and cox regression for time-to-event data. Anesth Analg. 2021;132(4):969–70.PubMed
26.
Jiang S, Ren X, Liu S, Lu Z, Xu A, Qin C, Wang Z. Integrated analysis of the prognosis-associated RNA-binding protein genes and candidate drugs in renal papillary cell carcinoma. Front Genet. 2021;12:627508.PubMedPubMedCentral
27.
Liu J, Lichtenberg T, Hoadley KA, Poisson LM, Lazar AJ, Cherniack AD, Kovatich AJ, Benz CC, Levine DA, Lee AV, et al. An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics. Cell. 2018;173(2):400-416.e411.PubMedPubMedCentral
28.
Yoshihara K, Shahmoradgoli M, Martínez E, Vegesna R, Kim H, Torres-Garcia W, Treviño V, Shen H, Laird PW, Levine DA, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013;4:2612.PubMed
29.
Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 2013;14:7.PubMedPubMedCentral
30.
De Giglio A, Di Federico A, Nuvola G, Deiana C, Gelsomino F. The Landscape of Immunotherapy in Advanced NSCLC: Driving Beyond PD-1/PD-L1 Inhibitors (CTLA-4, LAG3, IDO, OX40, TIGIT, Vaccines). Curr Oncol Rep. 2021;23(11):126.PubMedPubMedCentral
31.
Jiang P, Gu S, Pan D, Fu J, Sahu A, Hu X, Li Z, Traugh N, Bu X, Li B, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med. 2018;24(10):1550–8.PubMedPubMedCentral
32.
Charoentong P, Finotello F, Angelova M, Mayer C, Efremova M, Rieder D, Hackl H, Trajanoski Z. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep. 2017;18(1):248–62.PubMed
33.
Reck M, Remon J, Hellmann MD. First-line immunotherapy for non-small-cell lung cancer. J Clin Oncol. 2022;40(6):586–97.PubMed
34.
Doroshow DB, Bhalla S, Beasley MB, Sholl LM, Kerr KM, Gnjatic S, Wistuba II, Rimm DL, Tsao MS, Hirsch FR. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol. 2021;18(6):345–62.PubMed
35.
Zhang W, Wang C, Hu X, Lian Y, Ding C, Ming L. Inhibition of LDHA suppresses cell proliferation and increases mitochondrial apoptosis via the JNK signaling pathway in cervical cancer cells. Oncol Rep. 2022;47(4):77.PubMedPubMedCentral
36.
Yoshida GJ. Metabolic reprogramming: the emerging concept and associated therapeutic strategies. J Exp Clin Cancer Res. 2015;34:111.PubMedPubMedCentral
37.
38.
Chen L, Huang L, Gu Y, Cang W, Sun P, Xiang Y. Lactate-lactylation hands between metabolic reprogramming and immunosuppression. Int J Mol Sci. 2022;23(19):11943.PubMedPubMedCentral
39.
Faubert B, Li KY, Cai L, Hensley CT, Kim J, Zacharias LG, Yang C, Do QN, Doucette S, Burguete D, et al. Lactate metabolism in human lung tumors. Cell. 2017;171(2):358-371.e359.PubMedPubMedCentral
40.
Riera-Domingo C, Audigé A, Granja S, Cheng WC, Ho PC, Baltazar F, Stockmann C, Mazzone M. Immunity, hypoxia, and metabolism-the ménage à trois of cancer: implications for immunotherapy. Physiol Rev. 2020;100(1):1–102.PubMed
41.
Bohn T, Rapp S, Luther N, Klein M, Bruehl TJ, Kojima N, Aranda Lopez P, Hahlbrock J, Muth S, Endo S, et al. Tumor immunoevasion via acidosis-dependent induction of regulatory tumor-associated macrophages. Nat Immunol. 2018;19(12):1319–29.PubMed
42.
Watson MJ, Vignali PDA, Mullett SJ, Overacre-Delgoffe AE, Peralta RM, Grebinoski S, Menk AV, Rittenhouse NL, DePeaux K, Whetstone RD, et al. Metabolic support of tumour-infiltrating regulatory T cells by lactic acid. Nature. 2021;591(7851):645–51.PubMedPubMedCentral
43.
Wu D, Yin Z, Ji Y, Li L, Li Y, Meng F, Ren X, Xu M. Identification of novel autophagy-related lncRNAs associated with a poor prognosis of colon adenocarcinoma through bioinformatics analysis. Sci Rep. 2021;11(1):8069.PubMedPubMedCentral
44.
Boutilier AJ, Elsawa SF. Macrophage polarization states in the tumor microenvironment. Int J Mol Sci. 2021;22(13):6995.PubMedPubMedCentral
45.
Petersen RP, Campa MJ, Sperlazza J, Conlon D, Joshi MB, Harpole DH Jr, Patz EF Jr. Tumor infiltrating Foxp3+ regulatory T-cells are associated with recurrence in pathologic stage I NSCLC patients. Cancer. 2006;107(12):2866–72.PubMed
46.
Ito N, Suzuki Y, Taniguchi Y, Ishiguro K, Nakamura H, Ohgi S. Prognostic significance of T helper 1 and 2 and T cytotoxic 1 and 2 cells in patients with non-small cell lung cancer. Anticancer Res. 2005;25(3b):2027–31.PubMed
47.
Su X, Wang G, Zheng S, Ge C, Kong F, Wang C. Comprehensive explorations of CCL28 in lung adenocarcinoma immunotherapy and experimental validation. J Inflamm Res. 2023;16:1325–42.PubMedPubMedCentral
Metadata
Title
Lactate dehydrogenase D serves as a novel biomarker for prognosis and immune infiltration in lung adenocarcinoma
Authors
Yu Zhang
Tianyi Zhang
Yingdong Zhao
Hongdi Wu
Qiang Zhen
Suwei Zhu
Shaoshuai Hou
Publication date
01-12-2023
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2023
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-023-11221-6

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