Bioinformatic Analysis of The Prognostic Value of A Panel of Six Amino Acid Transporters in Human Cancers

Document Type : Original Article

Authors

1 Department of Pathology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China

2 National Clinical Research Center for Cancer, Tianjin, China

3 Key Laboratory of Cancer Prevention and Therapy (Tianjin), Tianjin, China

4 Tianjin's Clinical Research Center for Cancer, Tianjin, China

5 Department of Pathology, Tianjin Medical University Cancer Institute & Hospital, Tianjin, China

Abstract

Objective: Solid tumor cells utilize amino acid transporters (AATs) to increase amino acid uptake in response to
nutrient-insufficiency. The upregulation of AATs is therefore critical for tumor development and progression. This study
identifies the upregulated AATs under amino acid deprived conditions, and further determines the clinicopathological
importance of these AATs in evaluating the prognosis of patients with cancers.
Materials and Methods: In this experimental study, the Gene Expression Omnibus (GEO) datasets (GSE62673,
GSE26370, GSE125782 and GSE150874) were downloaded from the NCBI website and utilized for integrated
differential expression and pathway analysis v0.96, Gene Set Enrichment Analysis (GSEA), and REACTOME analyses
to identify the AATs upregulated in response to amino acid deprivation. In addition, The Cancer Genome Atlas (TCGA)
datasets with prognostic information were assessed and employed to evaluate the association of identified AATs with
patients’ prognoses using SurvExpress analysis.
Results: Using analysis of NCBI GEO data, this study shows that amino acid deprivation leads to the upregulation
of six AAT genes; SLC3A2, SLC7A5, SLC7A1, SLC1A4, SLC7A11 and SLC1A5. GSEA and REACTOME analyses
identified altered signaling in cells exposed to amino acid deprivation, such as pathways related to stress responses,
the cell cycle and apoptosis. In addition, Principal Component Analysis showed these six AAT genes to be well divided
into two distinct clusters in relation to TCGA tumor tissues versus normal counterparts. Finally, Log-Rank analysis
confirmed the upregulation of this panel of six AAT genes is correlated with poor prognosis in patients with colorectal,
esophageal, kidney and lung cancers.
Conclusion: The upregulation of a panel of six AATs is common in several human cancers and may provide a valuable
diagnostic tool to evaluate the prognosis of patients with colorectal, esophageal, kidney and lung cancers.

Keywords

Main Subjects

References

  1. Sanchez-Vega F, Mina M, Armenia J, Chatila WK, Luna A, La KC, et al. Oncogenic signaling pathways in the cancer genome atlas. Cell. 2018; 173(2): 321-337. e10.
  2. Batlle R, Andrés E, Gonzalez L, Llonch E, Igea A, Gutierrez-Prat N, et al. Regulation of tumor angiogenesis and mesenchymal-endothelial transition by p38α through TGF-β and JNK signaling. Nat Commun. 2019; 10(1): 3071.
  3. Qie S, Diehl JA. Glutamine addiction: an Achilles heel in esophageal cancers with dysregulation of CDK4/6. Mol Cell Oncol. 2019; 6(4): 1610257.
  4. Qie S, Yoshida A, Parnham S, Oleinik N, Beeson GC, Beeson CC, et al. Targeting glutamine-addiction and overcoming CDK4/6 inhibitor resistance in human esophageal squamous cell carcinoma. Nat Commun. 2019; 10(1): 1296.
  5. Qie S, He D, Sang N. Overview of glutamine dependency and metabolic rescue protocols. Methods Mol Biol. 2019; 1928: 427-439.
  6. Dong M, Miao L, Zhang F, Li S, Han J, Yu R, et al. Nuclear factor-κB p65 regulates glutaminase 1 expression in human hepatocellular carcinoma. Onco Targets Ther. 2018; 11: 3721-3729.
  7. Lee JS, Adler L, Karathia H, Carmel N, Rabinovich S, Auslander N,et al. Urea cycle dysregulation generates clinically relevant genomic and biochemical signatures. Cell. 2018; 174(6): 1559- 1570. e22.
  8. Micaily I, Roche M, Ibrahim MY, Martinez-Outschoorn U, Mallick AB. Metabolic pathways and targets in chondrosarcoma. Front Oncol. 2021; 11: 772263.
  9. Papalazarou V, Maddocks ODK. Supply and demand: cellular nutrient uptake and exchange in cancer. Mol Cell. 2021; 81(18): 3731-3748.
  10. Qie S, Diehl JA. Cyclin D degradation by E3 ligases in cancer progression and treatment. Semin Cancer Biol. 2020; 67(Pt 2): 159- 170.
  11. Xiong G, Stewart RL, Chen J, Gao T, Scott TL, Samayoa LM, et al. Collagen prolyl 4-hydroxylase 1 is essential for HIF-1α stabilization and TNBC chemoresistance. Nat Commun. 2018; 9(1): 4456.
  12. Wei Z, Liu X, Cheng C, Yu W, Yi P. Metabolism of amino acids in cancer. Front Cell Dev Biol. 2021; 8: 603837.
  13. Fultang L, Gneo L, De Santo C, Mussai FJ. Targeting amino acid metabolic vulnerabilities in myeloid malignancies. Front Oncol. 2021; 11: 674720.
  14. Kandasamy P, Gyimesi G, Kanai Y, Hediger MA. Amino acid transporters revisited: new views in health and disease. Trends Biochem Sci. 2018; 43(10): 752-789.
  15. Huang X, Anderle P, Hostettler L, Baumann MU, Surbek DV, Ontsouka EC, et al. Identification of placental nutrient transporters associated with intrauterine growth restriction and pre-eclampsia. BMC Genomics. 2018; 19(1): 173.
  16. Rebsamen M, Girardi E, Sedlyarov V, Scorzoni S, Papakostas K, Vollert M, et al. Gain-of-function genetic screens in human cells identify SLC transporters overcoming environmental nutrient restrictions. Life Sci Alliance. 2022; 5(11): e202201404.
  17. Liu C, Li X, Li C, Zhang Z, Gao X, Jia Z, et al. SLC3A2 is a novel endoplasmic reticulum stress-related signaling protein that regulates the unfolded protein response and apoptosis. PLoS One. 2018; 13(12): e0208993.
  18. Kahlhofer J, Teis D. The human LAT1-4F2hc (SLC7A5-SLC3A2) transporter complex: Physiological and pathophysiological implications. Basic Clin Pharmacol Toxicol. 2022 (ahead of print).
  19. Torrence ME, MacArthur MR, Hosios AM, Valvezan AJ, Asara JM, Mitchell JR, et al. The mTORC1-mediated activation of ATF4 promotes protein and glutathione synthesis downstream of growth signals. Elife. 2021; 10: e63326.
  20. Sikalidis AK, Lee JI, Stipanuk MH. Gene expression and integrated stress response in HepG2/C3A cells cultured in amino acid deficient medium. Amino Acids. 2011; 41(1): 159-171.
  21. Ge SX, Son EW, Yao R. iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. BMC Bioinformatics. 2018; 19(1): 534.
  22. Wu G, Haw R. Functional interaction network construction and analysis for disease discovery. Methods Mol Biol. 2017; 1558: 235- 253.
  23. Jassal B, Matthews L, Viteri G, Gong C, Lorente P, Fabregat A, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2020; 48(D1): D498-D503.
  24. Ge SX, Jung D, Yao R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics. 2020; 36(8): 2628-2629.
  25. Tang Z, Kang B, Li C, Chen T, Zhang Z. GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 2019; 47(W1): W556-W560.
  26. Yuan F, Jiang H, Yin H, Jiang X, Jiao F, Chen S, et al. Activation of GCN2/ATF4 signals in amygdalar PKC-δ neurons promotes WAT browning under leucine deprivation. Nat Commun. 2020; 11(1): 2847.
  27. McFarland JM, Ho ZV, Kugener G, Dempster JM, Montgomery PG, Bryan JG, et al. Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration. Nat Commun. 2018; 9(1): 4610.
  28. Rosario FJ, Dimasuay KG, Kanai Y, Powell TL, Jansson T. Regulation of amino acid transporter trafficking by mTORC1 in primary human trophoblast cells is mediated by the ubiquitin ligase Nedd4-2. Clin Sci (Lond). 2016; 130(7): 499-512.
  29. Honjo H, Kaira K, Miyazaki T, Yokobori T, Kanai Y, Nagamori S, et al. Clinicopathological significance of LAT1 and ASCT2 in patients with surgically resected esophageal squamous cell carcinoma. JSurg Oncol. 2016; 113(4): 381-389.
  30. Oda K, Lee Y, Wiriyasermkul P, Tanaka Y, Takemoto M, Yamashita K, et al. Consensus mutagenesis approach improves the thermal stability of system xc - transporter, xCT, and enables cryo-EM analyses. Protein Sci. 2020; 29(12): 2398-2407.
  31. Badgley MA, Kremer DM, Maurer HC, DelGiorno KE, Lee HJ, Purohit V, et al. Cysteine depletion induces pancreatic tumor ferroptosis in mice. Science. 2020; 368(6486): 85-89.
  32. Ji X, Qian J, Rahman SMJ, Siska PJ, Zou Y, Harris BK, et al. xCT (SLC7A11)-mediated metabolic reprogramming promotes nonsmall cell lung cancer progression. Oncogene. 2018; 37(36): 5007- 5019.
  33. Canup BSB, Song H, Laroui H. Role of CD98 in liver disease. Ann Hepatol. 2020; 19(6): 602-607.
  34. Ip H, Sethi T. CD98 signals controlling tumorigenesis. Int J Biochem Cell Biol. 2016; 81(Pt A): 148-150.
  35. Scalise M, Console L, Cosco J, Pochini L, Galluccio M, Indiveri C. ASCT1 and ASCT2: Brother and Sister? SLAS Discov. 2021; 26(9): 1148-1163.
  36. Yoo HC, Park SJ, Nam M, Kang J, Kim K, Yeo JH, et al. A variant of SLC1A5 Is a mitochondrial glutamine transporter for metabolic reprogramming in cancer cells. Cell Metab. 2020; 31(2): 267-283. e12.
  37. Teixeira E, Silva C, Martel F. The role of the glutamine transporter ASCT2 in antineoplastic therapy. Cancer Chemother Pharmacol. 2021; 87(4): 447-464.
  38. Okita K, Hara Y, Okura H, Hayashi H, Sasaki Y, Masuko S, et al. Antitumor effects of novel mAbs against cationic amino acid transporter 1 (CAT1) on human CRC with amplified CAT1 gene. Cancer Sci. 2021; 112(2): 563-574.
Cell Journal (Yakhteh)
Volume 25, Issue 9 - Serial Number 116
September 2023
Pages 613-624

Files

Share

How to cite

Statistics