1,645
Views
5
CrossRef citations to date
0
Altmetric
Research Paper

Exploration of the prognostic signature reflecting tumor microenvironment of lung adenocarcinoma based on immunologically relevant genes

ORCID Icon, , , , &
Pages 7417-7431 | Received 07 Apr 2021, Accepted 27 Aug 2021, Published online: 06 Oct 2021

References

  • Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021; 10.3322/caac.21660.
  • Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70(1):7–30.
  • Behera M, Owonikoko TK, Gal AA, et al. Lung adenocarcinoma staging using the 2011 IASLC/ATS/ERS classification: a pooled analysis of adenocarcinoma in situ and minimally invasive adenocarcinoma. Clin Lung Cancer. 2016;17(5):e57–e64.
  • Perlikos F, Harrington KJ, Syrigos KN. Key molecular mechanisms in lung cancer invasion and metastasis: a comprehensive review. Crit Rev Oncol Hematol. 2013;87(1):1–11.
  • Rizvi NA, Hellmann MD, Brahmer JR, et al. Nivolumab in combination with platinum-based doublet chemotherapy for first-line treatment of advanced non-small-cell lung cancer. J Clin Oncol. 2016;34(25):2969–2979.
  • Garassino MC, Cho BC, Kim JH, et al. Durvalumab as third-line or later treatment for advanced non-small-cell lung cancer (ATLANTIC): an open-label, single-arm, phase 2 study. Lancet Oncol. 2018;19(4):521–536.
  • Carbone DP, Reck M, Paz-Ares L, et al. First-line nivolumab in stage IV or recurrent non-small-cell lung cancer. N Engl J Med. 2017;376(25):2415–2426.
  • Yost KE, Satpathy AT, Wells DK, et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat Med. 2019;25(8):1251–1259.
  • Shukuya T, Carbone DP. Predictive markers for the efficacy of anti-PD-1/PD-L1 antibodies in lung cancer. J Thorac Oncol. 2016;11(7):976–988.
  • Postow MA, Sidlow R, Hellmann MD. Immune-related adverse events associated with immune checkpoint blockade. N Engl J Med. 2018;378(2):158–168.
  • Kim TK, Herbst RS, Chen L. Defining and understanding adaptive resistance in cancer immunotherapy. Trends Immunol. 2018;39(8):624–631.
  • Wang J, Chmielowski B, Pellissier J, et al. Cost-effectiveness of pembrolizumab versus ipilimumab in ipilimumab-naïve patients with advanced melanoma in the United States. J Manag Care Spec Pharm. 2017;23(2):184–194.
  • Song Q, Shang J, Yang Z, et al. Identification of an immune signature predicting prognosis risk of patients in lung adenocarcinoma. J Transl Med. 2019;17(1):70.
  • Zhang Z, Shi R, Xu S, et al. Identification of small proline-rich protein 1B (SPRR1B) as a prognostically predictive biomarker for lung adenocarcinoma by integrative bioinformatic analysis. Thorac Cancer. 2021;12(6):796–806.
  • Liu Z, Sun D, Zhu Q, et al. The screening of immune-related biomarkers for prognosis of lung adenocarcinoma. Bioengineered. 2021;12(1):1273–1285.
  • Chen D, Wang Y, Zhang X, et al. Characterization of tumor microenvironment in lung adenocarcinoma identifies immune signatures to predict clinical outcomes and therapeutic responses. Front Oncol. 2021;11:581030.
  • Wilkerson MD, Yin X, Walter V, et al. Differential pathogenesis of lung adenocarcinoma subtypes involving sequence mutations, copy number, chromosomal instability, and methylation. PloS One. 2012;7(5):e36530.
  • Shedden K, Taylor JM, Enkemann SA, et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med. 2008;14(8):822–827.
  • Yoshihara K, Shahmoradgoli M, Martínez E, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nature. communications. 2013;4(1):2612.
  • Ritchie ME, Phipson B, Wu D, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.
  • Bhattacharya S, Dunn P, Thomas CG, et al. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Scientific data. 2018;5(1):180015.
  • Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847–2849.
  • Heagerty PJ, Lumley T, Pepe MS. Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics. 2000;56(2):337–344.
  • Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–457.
  • Wei T, Simko V R package “corrplot”: visualization of a Correlation Matrix (Version 0.84). 2017. Available from: https://github.com/taiyun/corrplot
  • Geeleher P, Cox N, Huang RS. pRRophetic: an R package for prediction of clinical chemotherapeutic response from tumor gene expression levels. PloS One. 2014;9(9):e107468.
  • Fu J, Li K, Zhang W, et al. Large-scale public data reuse to model immunotherapy response and resistance. Genome Med. 2020;12(1):21.
  • Jiang P, Gu S, Pan D, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med. 2018;24(10):1550–1558.
  • Wickham H. Ggplot2: elegant graphics for data analysis. New York: Springer. 2016.
  • Pickup MW, Owens P, Moses HL. TGF-β, bone morphogenetic protein, and activin signaling and the tumor microenvironment. Cold Spring Harbor Perspect Biol. 2017;9(5):5.
  • Nagarsheth N, Wicha MS, Zou W. Chemokines in the cancer microenvironment and their relevance in cancer immunotherapy. Nat Rev Immunol. 2017;17(9):559–572.
  • Chew V, Chen J, Lee D, et al. Chemokine-driven lymphocyte infiltration: an early intratumoural event determining long-term survival in resectable hepatocellular carcinoma. Gut. 2012;61(3):427–438.
  • Lin EW, Karakasheva TA, Hicks PD, et al. The tumor microenvironment in esophageal cancer. Oncogene. 2016;35(41):5337–5349.
  • Liu Y, Wu J, Huang W, et al. Development and validation of a hypoxia-immune- based microenvironment gene signature for risk stratification in gastric cancer. J Transl Med. 2020;18(1):201.
  • Mo Z, Yu L, Cao Z, et al. Identification of a hypoxia-associated signature for lung adenocarcinoma. Front Genet. 2020;11:647.
  • Zhang J, Zhang J, Yuan C, et al. Establishment of the prognostic index reflecting tumor immune microenvironment of lung adenocarcinoma based on metabolism-related genes. J Cancer. 2020;11(24):7101–7115.
  • Ramnefjell M, Aamelfot C, Aziz S, et al. Microvascular proliferation is associated with aggressive tumour features and reduced survival in lungadenocarcinoma. The journal of pathology. Clinical research. 2017;3(4):249–257.
  • Mittal D, Gubin MM, Schreiber RD, et al. New insights into cancer immunoediting and its three component phases--elimination, equilibrium and escape. Curr Opin Immunol. 2014;27:16–25.
  • Foubert P, Kaneda MM, Varner JA. PI3Kγ activates integrin α and promotes immune suppressive myeloid cell polarization during tumor progression. Cancer Immunol Res. 2017;5(11):957–968.
  • Kaneda MM, Messer KS, Ralainirina N, et al. PI3Kγ is a molecular switch that controls immune suppression. Nature. 2016;539(7629):437–442.
  • Grosse C, Soltermann A, Rechsteiner M, et al. Oncogenic driver mutations in Swiss never smoker patients with lung adenocarcinoma and correlation with clinicopathologic characteristics and outcome. PloS One. 2019;14(8):e0220691.
  • Liang C, Tian D, Ren X, et al. The development of Bruton’s tyrosine kinase (BTK) inhibitors from 2012 to 2017: a mini-review. Eur J Med Chem. 2018;151:315–326.
  • Haselmayer P, Camps M, Liu-Bujalski L, et al. Efficacy and pharmacodynamic modeling of the BTK inhibitor evobrutinib in autoimmune disease models. Journal of immunology (Baltimore, Md. : 1950). 2019;202(10):2888–2906.
  • Alsadhan A, Cheung J, Gulrajani M, et al. Pharmacodynamic analysis of BTK inhibition in patients with chronic lymphocytic leukemia treated with acalabrutinib. Clin Cancer Res. 2020;26(12):2800–2809.
  • Bi KW, Wei XG, Qin XX, et al. BTK has potential to be a prognostic factor for lung adenocarcinoma and an indicator for tumor microenvironment remodeling: a study based on TCGA data mining. Front Oncol. 2020;10:424.
  • Achen MG, Jeltsch M, Kukk E, et al. Vascular endothelial growth factor D (VEGF-D) is a ligand for the tyrosine kinases VEGF receptor 2 (Flk1) and VEGF receptor 3 (Flt4). Proc Natl Acad Sci U S A. 1998;95(2):548–553.
  • Stacker SA, Achen MG Emerging roles for VEGF-D in human disease.
  • Sanmartín E, Sirera R, Usó M, et al. A gene signature combining the tissue expression of three angiogenic factors is a prognostic marker in early-stage non-small cell lung cancer. Ann Surg Oncol. 2014;21(2):612–620.
  • Rafaqat W, Kayani MR, Fatima T, et al. Association of polymorphism c-124G>A and c.-16 C>T in the promoter region of human INHA gene with altered sperm parameters; A pilot study. Int J Clin Pract. 2020;74(10):e13595.
  • Balanathan P, Williams ED, Wang H, et al. Elevated level of inhibin-alpha subunit is pro-tumourigenic and pro-metastatic and associated with extracapsular spread in advanced prostate cancer. Br J Cancer. 2009;100(11):1784–1793.
  • Singh P, Jenkins LM, Horst B, et al. Inhibin is a novel paracrine factor for tumor angiogenesis and metastasis. Cancer Res. 2018;78(11):2978–2989.
  • Laurent A, Rouillac C, Delezoide AL, et al. Insulin-like 4 (INSL4) gene expression in human embryonic and trophoblastic tissues. Mol Reprod Dev. 1998;51(2):123–129.
  • Brandt B, Kemming D, Packeisen J, et al. Expression of early placenta insulin-like growth factor in breast cancer cells provides an autocrine loop that predominantly enhances invasiveness and motility. Endocr Relat Cancer. 2005;12(4):823–837.
  • Yang R, Li SW, Chen Z, et al. Role of INSL4 signaling in sustaining the growth and viability of LKB1-inactivated lung cancer. J Natl Cancer Inst. 2019;111(7):664–674.
  • Ma C, Luo H, Cao J, et al. Identification of a novel tumor microenvironment-associated eight-gene signature for prognosis prediction in lung adenocarcinoma. Frontiers in molecular biosciences. 2020;7:571641.
  • Hermiston ML, Xu Z, Weiss A. CD45: a critical regulator of signaling thresholds in immune cells. Annu Rev Immunol. 2003;21(1):107–137.
  • Camacho M, Agüero A, Sumarroca A, et al. Prognostic value of CD45 transcriptional expression in head and neck cancer. Eur Arch Otorhinolaryngol. 2018;275(1):225–232.
  • Cheng WY, Ou Yang TH, Anastassiou D. Development of a prognostic model for breast cancer survival in an open challenge environment. Sci Transl Med. 2013;5(181):181ra150.
  • Kilvaer TK, Paulsen EE, Khanehkenari MR, et al. The presence of intraepithelial CD45RO+ cells in resected lymph nodes with metastases from NSCLC patients is an independent predictor of disease-specific survival. Br J Cancer. 2016;114(10):1145–1151.