Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1
Paul Chiroi
 -- 2433 2022-05-22 20:15:24 |
2 layout
Camila Xu
 -339 word(s) 2094 2022-05-23 04:04:21 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Chiroi, P.; Pirlog, R.; , .; Jurj, A.; Bica-Pop, C.; Crisan, D.; Sabourin, J.; Berindan-Neagoe, I. Tumor Microenvironment and Early-Stage Lung Cancer. Encyclopedia. Available online: https://encyclopedia.pub/entry/23216 (accessed on 27 July 2024).
Chiroi P, Pirlog R,  , Jurj A, Bica-Pop C, Crisan D, et al. Tumor Microenvironment and Early-Stage Lung Cancer. Encyclopedia. Available at: https://encyclopedia.pub/entry/23216. Accessed July 27, 2024.
Chiroi, Paul, Radu Pirlog,  , Ancuta Jurj, Cecilia Bica-Pop, Doinita Crisan, Jean-Christophe Sabourin, Ioana Berindan-Neagoe. "Tumor Microenvironment and Early-Stage Lung Cancer" Encyclopedia, https://encyclopedia.pub/entry/23216 (accessed July 27, 2024).
Chiroi, P., Pirlog, R., , ., Jurj, A., Bica-Pop, C., Crisan, D., Sabourin, J., & Berindan-Neagoe, I. (2022, May 22). Tumor Microenvironment and Early-Stage Lung Cancer. In Encyclopedia. https://encyclopedia.pub/entry/23216
Chiroi, Paul, et al. "Tumor Microenvironment and Early-Stage Lung Cancer." Encyclopedia. Web. 22 May, 2022.
Tumor Microenvironment and Early-Stage Lung Cancer
Edit
This entry is adapted from the peer-reviewed paper 10.3390/ijms23105346

Lung cancer is the leading cause of cancer-related death worldwide, accounting for more than 1.8 million fatalities each year. It is also the second most frequent type of malignancy, with more than 2.2 million cases diagnosed annually. Recent advances in cancer biology and genomics research have the potential of revealing more biomarkers for diagnostic, prognostic, and targeted therapies. A new source of biomarkers are the non-coding RNAs, especially miRNAs.

early-stage lung cancer tumor microenvironment p53 E-cadherin CD4 CD8 hsa-miR-25-3p hsa-miR-29b-3p hsa-miR-181a-5p hsa-miR-205-5p

1. Introduction

Lung cancer is the leading cause of cancer-related death worldwide, accounting for more than 1.8 million fatalities each year. It is also the second most frequent type of malignancy, with more than 2.2 million cases diagnosed annually [1]. Lung cancers are broadly divided into two main histological groups: NSCLC, which accounts for 80–85% of all lung cancer cases, and SCLC, consisting of 10–15%. NSCLC can be further divided into three principal histological subtypes: lung adenocarcinomas (LUADs) (45–60% of cases), squamous cell carcinoma (LUSC) (20–25% of cases), and neuroendocrine carcinomas (NE LC) (10–15%) [1][2]. These histological types differ in terms of treatment approaches and overall survival (OS). NSCLC is the most studied type, with multiple targeted therapies available and with a 5-year OS rate of 23%, while SCLC is treated mainly with platinum-based chemotherapy and has a median survival time of less than 1 year [3][4]. This high mortality is due to late diagnosis and the paucity of effective screening regimens. Lung cancer detected in early-stage has a 5-year OS of up to 70% [5], highlighting the need for better early-stage biomarkers.
Chest X-ray, computed tomography, magnetic resonance imaging, positron emission tomography, sputum analysis, and lung biopsy are all common clinical investigations currently used for identifying lung cancer. However, despite recent advances in cancer screening and diagnosis, 57% of all patients are detected only after the tumor has progressed to the metastatic stage. Under these circumstances, the remission chances are minimal, and the 5-year survival rate for metastatic lung cancer is less than 6% [6]. Therefore, identifying new methods for early-stage lung cancer detection is a central focus of cancer research. In this regard, understanding the alterations in the lung tumor microenvironment (TME) throughout the early stages of cancer evolution could be a viable avenue for biomarker discovery [7][8].
The main risk factor associated with lung cancer is tobacco smoking, which is responsible for about 80–90% of all lung cancer cases. It triggers an aggressive mutational burden, an increase in cytosine to adenine nucleotide transversions, and an enhancement in KRAS and TP53 mutations. KRAS mutations are the most common driver mutations, being present in about 35% of NSCLC cases [6]. TP53 is the most important tumor suppressor gene and is the target of multiple mutations early in lung cancer tumorigenesis, its alterations being present in more than 90% of SCLCs and 50% of NSCLCs [9][10][11].
Recent advances in cancer biology and genomics research have allowed to characterize the mutational landscape of lung cancer, and, in recent years, next-generation sequencing (NGS) has become an essential tool for diagnosis and effective therapeutic management [9][10]. Improvements in the understanding of lung cancer genomics have led to the identification of major driver mutations genes, including EGFR, KRAS, ALK, BRAF, HER2, PIK3CA, AKT1, MAP2K1, and MET [12][13]. The identification of these mutations has led to major progress in therapy for LUAD patients, with the introduction of tyrosine kinase inhibitors and, more recently, KRAS G12C inhibitors [14][15][16]. The identification of these mutations changed clinical practice and pathological diagnosis. Nowadays, searching for driver mutations is mandatory for a complete and accurate diagnosis.
From the early development of the lung cancer cellular niche, the tumor starts to organize a complex cellular and molecular habitat that is known as the TME. This entity consists of a complex stromal and cellular network of tumor cells, various normal and immune cell populations, and molecules trafficked in this environment [17]. The principal non-tumoral populations are represented by tumor-infiltrating lymphocytes (TILs), tumor-associated fibroblasts, tumor-associated macrophages, and endothelial progenitor cells [18]. This ecosystem is designed to support the tumor from its early development in acquiring the hallmarks of cancer and support its progression toward more advanced stages [19]. The interest in the research of TME increased with the introduction of anti-PD1/anti-PD-L1 and anti-CTLA4 immunotherapy. The introduction of immunotherapy managed to reactivate the dormant immune population from the environment and became a valuable resource in lung cancer therapy [20]. Currently, all major cellular components of the TME are being intensively studied to identify new targets that can enhance their antitumor activity [21].
Epithelial-to-mesenchymal transition (EMT) is a dynamic process that takes place early in lung cancer tumorigenesis, being an essential step for tumor cells to acquire invasive and metastatic potential [22][23]. The EMT phenotype was identified as early as stage IA in a cohort of LUAD patients. The presence of the mesenchymal phenotype, reduced E-cadherin and high Vimentin expression, was associated with shorter disease-free survival and reduced OS [24]. Additionally, circulating tumor cells, a marker of EMT, were shown to be detected as early as in situ stages of lung cancer in the blood of patients, supporting the early onset of EMT [25]. A better understanding of EMT in the early stages of cancer is essential for understanding tumor progression and for identifying the molecular mechanisms that can be modulated to limit progression and spread to distant sites [26].
NGS, including single-cell analysis, has been used in TME investigation [18][21][27][28]. These methods have shown promising results, highlighting the possible prognostic role of tumor-infiltrating lymphocytes (TILs) in lung cancer. Additionally, approaches that used immunohistochemistry (IHC) for specific TIL subpopulations revealed that the abundance of CD3, CD4, CD8, and FOXP3+ subpopulations can be used as an independent prognostic marker for patient outcome [18][29].
Another conceivable source of biomarkers is represented by the non-coding RNAs (ncRNAs), especially microRNAs (miRNAs); they are short (18–28 nucleotides long) ncRNA sequences found to be involved in the post-transcriptional regulation of gene expression. Thus, miRNAs are potent regulators of cell proliferation, differentiation, development, and apoptosis, among other cellular processes. Furthermore, these ncRNAs were also found involved in various malignancies, including lung cancer [30][31][32]. Moreover, under certain circumstances, miRNAs can act as oncogenes or tumor suppressors. Therefore, different cancer hallmarks, such as sustaining proliferative signals, evading growth suppressors, resisting cell death, activating invasion and metastasis, and initiating angiogenesis, have been linked to dysregulated miRNAs.

2. Tumor Microenvironment and Early-Stage Lung Cancer

2.1. Study design

Based on bioinformatics analysis using dysregulated genes in early-stage lung cancer, TME analysis, and literature search, researchers were able to identify 4 miRNAs (hsa-miR-29b-3p, hsa-miR-181a-5p, hsa-miR-25-3p, and hsa-miR-205-5p) that target the TP53 gene, modulate EMT pathway in lung cancer and have the potential of being used as a diagnostic panel for early-stage lung cancer.

Researchers investigate a 4-miRNA panel for early-stage lung cancer diagnosis, consisting of two tumor suppressors and two tumor promoter miRNAs known for their roles in essential cancer regulatory processes, such as EMT, angiogenesis, metastasis, and clinical parameters such as response to therapy and OS.

In this research, researchers present a translational approach for biomarker identification in early-stage lung cancer. Researchers used a comprehensive characterization of the selected cases that included morphology, IHC, bioinformatics analysis, and investigation of specific miRNAs expression using qRT-PCR. Researchers included early-stage LUAD, LUSC, and NE LC to better understand lung cancer progression and TME organization in the early stages of carcinogenesis across the different histologic subtypes.

2.2. Discussions

Researchers performed a translational analysis of the tumor and TME in early-stage lung cancer with the aim of identifying the main patterns of TME organization and tumor molecular alterations. The IHC profile of E cadherin and p53 markers allowed to evaluate early phase EMT and the loss of the main tumor suppressor gene.

E-cadherin is a glycoprotein that plays an important morphogenetic role in epithelial cell stabilization by maintaining intercellular connections through calcium-dependent adhesion. Additionally, it regulates cancer cell differentiation and reduces cancer cells’ ability to spread beyond their local site. Thus, reduced or absent E-cadherin expression in several cancers is linked to impaired differentiation and enhanced metastatic capacity. Depletion of E-cadherin expression causes EMT, which enhances the metastatic potential. Deconstruction of cell polarity, cytoskeleton restructuration, and changes in signaling pathways all contribute to EMT, which increases motility and promotes metastasis by increasing cancer cell invasiveness, resulting in a poor prognosis [33]. EMT signature has also been inversely associated with T-cell infiltration in NSCLC [34][35]. In researchers' cohort, the E-cadherin staining was present in all the investigated cases, but a difference in intensity was noted among samples, with 37.3% of cases having high-intensity staining and 62.7% of these samples expressing a moderate staining intensity. This loss of staining intensity can be interpreted as an early sign of EMT, as it was shown in recent years that EMT in lung cancer is a process that starts from the early stages [24].
P53 is a tumor suppressor protein that controls cell division and proliferation that has also been linked to early lung cancer carcinogenesis [36][37]. The presence of p53 IHC staining generally indicates a mutation in the TP53 gene [38]. In researchers' series, p53 IHC was positive in 62.7% of the cases, supporting the importance of p53 mutation as an early-mutational event in early-stage lung cancer. Higher positivity rates were found in groups that included more advanced stages of lung cancer [39].
A critical element in lung cancer initiation and progression is represented by the organization of the TME, which takes place early in tumorigenesis [8][33][40]. Consequently, decoding the lung cancer-associated TME heterogeneity into a collection of prognostic, diagnostic, or predictive biomarkers has become an area of intensive research. Since then, several valuable findings have pinpointed the TME as a potential source for novel early-stage lung cancer biomarkers [8][37][41]. An important constituent at this level is represented by the immune cell populations, which are involved in the immune surveillance and tumor immune escape mechanisms. These two processes are in a dynamic equilibrium, with immune surveillance slowing tumor progression through tumor cell identification and suppression and progressing tumor immune escape by reducing the antitumor activity of the immune compartment as the tumor starts to produce inhibitory molecules and secrete cytokines [42][43]. Moreover, the TME-related immune signature has led to further investigations, especially in LUAD cases, where its diagnostic and prognostic role has been recently proposed [44]. In this regard, TILs play a significant role in the tumor immune milieu and can be a reliable early-stage biomarker [29][45][46]. Two of the most studied TILs that are believed to be associated with the early stages of lung cancer are CD4 and CD8 [47][48][49], commonly known for their important roles in the regulation of both antitumor and protumorigenic processes [50][51]. Using the IHC characterization of TILs, researchers found that CD4 lymphocytes were high and very high within the stromal compartment in 84.4% of the early-stage lung cancer cohort, while the CD8 cells were lower in abundance, showing a moderate and low abundance in 64.7% of the cases. Meanwhile, the intratumor compartment was scarce in TILs, with minor differences between CD4 and CD8 TILs. Therefore, researchers' findings take them a step closer to validating the association between TILs (CD4/CD8) and early-stage tumorigenesis in lung cancer [18][49]. The presence of CD4 cells was correlated with hsa-miR-181a expression, as indicated by the in silico analysis and further validated on the TCGA dataset and researchers' tumor samples. The tumor suppressor hsa-miR-181a was upregulated in the adjacent normal tumoral tissue, which contains the cellular elements of the TME, and downregulated at the tumoral level.
The immune cell populations in the TME were shown to be organized in cellular aggregates that resemble secondary lymphoid organs in morphology and their composition being commonly defined as TLS. Moreover, histologically, these structures were shown to become phenotypically active when they start to develop germinal centers [52]. These structures are partially involved in mediating the host immune response, becoming a subject of interest in the study of TME [53][54]. In early-stage lung cancer, TLS were shown to actively drive the immune response against tumor cells, which is generally considered a sign of active tumor immunity and positive prognosis [49][55][56][57]. In researchers' group, TLS were present in 74.5% of the early-stage lung cancer cases, and among these, 34.2% of cases with TLS showed the presence of active germinal centers. LUADs showed a higher presence of active germinal centers, suggesting they are more immunologically active compared with LUSCs and NE LCs.
In the past decade, the understanding of cancer biology has quantitatively and qualitatively increased, due to the intensive genomic studies, especially regarding the roles of miRNAs in human cancers [58][59]. Different cancers have different miRNA expression levels, distinctive from those within normal tissues. Thus, abnormal miRNA expression patterns have been oftentimes considered a crucial carcinogenesis marker and may have the potential of becoming novel biomarkers for minimally invasive, early-stage lung diagnosis [50][60].

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249.
  2. Schabath, M.B.; Cote, M.L. Cancer Progress and Priorities: Lung Cancer. Cancer Epidemiol. Prev. Biomark. 2019, 28, 1563–1579.
  3. Thandra, K.C.; Barsouk, A.; Saginala, K.; Aluru, J.S.; Barsouk, A. Epidemiology of Lung Cancer. Contemp. Oncol. 2021, 25, 45–52.
  4. Ko, J.; Winslow, M.M.; Sage, J. Mechanisms of Small Cell Lung Cancer Metastasis. EMBO Mol. Med. 2021, 13, e13122.
  5. Gierada, D.S.; Pinsky, P.F. Survival Following Detection of Stage I Lung Cancer by Screening in the National Lung Screening Trial. Chest 2021, 159, 862–869.
  6. Goebel, C.; Louden, C.L.; Mckenna, R.J.; Onugha, O.; Wachtel, A.; Long, T. Diagnosis of Non-Small Cell Lung Cancer for Early Stage Asymptomatic Patients. Cancer Genom. Proteom. 2019, 16, 229–244.
  7. Lim, R.J.; Liu, B.; Krysan, K.; Dubinett, S.M. Lung Cancer and Immunity Markers. Cancer Epidemiol. Biomark. Prev. Publ. Am. Assoc. Cancer Res. Cosponsored Am. Soc. Prev. Oncol. 2020, 29, 2423–2430.
  8. Kim, J.; Xu, Z.; Marignani, P.A. Single-Cell RNA Sequencing for the Identification of Early-Stage Lung Cancer Biomarkers from Circulating Blood. NPJ Genomic Med. 2021, 6, 87.
  9. Hammerman, P.S.; Lawrence, M.S.; Voet, D.; Jing, R.; Cibulskis, K.; Sivachenko, A.; Stojanov, P.; McKenna, A.; Lander, E.S.; Gabriel, S.; et al. Comprehensive Genomic Characterization of Squamous Cell Lung Cancers. Nature 2012, 489, 519–525.
  10. Collisson, E.A.; Campbell, J.D.; Brooks, A.N.; Berger, A.H.; Lee, W.; Chmielecki, J.; Beer, D.G.; Cope, L.; Creighton, C.J.; Danilova, L.; et al. Comprehensive Molecular Profiling of Lung Adenocarcinoma. Nature 2014, 511, 543–550.
  11. George, J.; Lim, J.S.; Jang, S.J.; Cun, Y.; Ozretić, L.; Kong, G.; Leenders, F.; Lu, X.; Fernández-Cuesta, L.; Bosco, G.; et al. Comprehensive Genomic Profiles of Small Cell Lung Cancer. Nature 2015, 524, 47–53.
  12. Rebuzzi, S.E.; Zullo, L.; Rossi, G.; Grassi, M.; Murianni, V.; Tagliamento, M.; Prelaj, A.; Coco, S.; Longo, L.; Dal Bello, M.G.; et al. Novel Emerging Molecular Targets in Non-Small Cell Lung Cancer. Int. J. Mol. Sci. 2021, 22, 2625.
  13. Pirlog, R.; Piton, N.; Lamy, A.; Guisier, F.; Berindan-Neagoe, I.; Sabourin, J.-C.; Marguet, F. Morphological and Molecular Characterization of KRAS G12C-Mutated Lung Adenocarcinomas. Cancers 2022, 14, 1030.
  14. NEJM. Crizotinib versus Chemotherapy in Advanced ALK-Positive Lung Cancer. Available online: https://www.nejm.org/doi/full/10.1056/nejmoa1214886 (accessed on 10 October 2021).
  15. NEJM. Gefitinib or Chemotherapy for Non–Small-Cell Lung Cancer with Mutated EGFR. Available online: https://www.nejm.org/doi/full/10.1056/nejmoa0909530 (accessed on 10 October 2021).
  16. Hong, D.S.; Fakih, M.G.; Strickler, J.H.; Desai, J.; Durm, G.A.; Shapiro, G.I.; Falchook, G.S.; Price, T.J.; Sacher, A.; Denlinger, C.S.; et al. KRASG12C Inhibition with Sotorasib in Advanced Solid Tumors. N. Engl. J. Med. 2020, 383, 1207–1217.
  17. Tan, Z.; Xue, H.; Sun, Y.; Zhang, C.; Song, Y.; Qi, Y. The Role of Tumor Inflammatory Microenvironment in Lung Cancer. Front. Pharmacol. 2021, 12, 1168.
  18. Mlika, M.; Saidi, A.; Mejri, N.; Abdennadher, M.; Haddouchi, C.; Labidi, S.; Khiari, H.; Boussen, H.; Hsairi, M.; Mezni, F. Prognostic Impact of Tumor-Infiltrating Lymphocytes in Non-Small Cell Lung Carcinomas. Asian Cardiovasc. Thorac. Ann. 2021, 30, 177–184.
  19. Hanahan, D. Hallmarks of Cancer: New Dimensions. Cancer Discov. 2022, 12, 31–46.
  20. Ushio, R.; Murakami, S.; Saito, H. Predictive Markers for Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer. J. Clin. Med. 2022, 11, 1855.
  21. Bejarano, L.; Jordāo, M.J.C.; Joyce, J.A. Therapeutic Targeting of the Tumor Microenvironment. Cancer Discov. 2021, 11, 933–959.
  22. Yang, J.; Antin, P.; Berx, G.; Blanpain, C.; Brabletz, T.; Bronner, M.; Campbell, K.; Cano, A.; Casanova, J.; Christofori, G.; et al. Guidelines and Definitions for Research on Epithelial-Mesenchymal Transition. Nat. Rev. Mol. Cell Biol. 2020, 21, 341–352.
  23. Ribatti, D.; Tamma, R.; Annese, T. Epithelial-Mesenchymal Transition in Cancer: A Historical Overview. Transl. Oncol. 2020, 13, 100773.
  24. Matsubara, T.; Tagawa, T.; Takada, K.; Toyokawa, G.; Shimokawa, M.; Kozuma, Y.; Akamine, T.; Haro, A.; Osoegawa, A.; Mori, M. Clinical and Prognostic Significance of the Epithelial-Mesenchymal Transition in Stage IA Lung Adenocarcinoma: A Propensity Score-Matched Analysis. Clin. Lung Cancer 2019, 20, e504–e513.
  25. Duan, G.-C.; Zhang, X.-P.; Wang, H.-E.; Wang, Z.-K.; Zhang, H.; Yu, L.; Xue, W.-F.; Xin, Z.-F.; Hu, Z.-H.; Zhao, Q.-T. Circulating Tumor Cells as a Screening and Diagnostic Marker for Early-Stage Non-Small Cell Lung Cancer. OncoTargets Ther. 2020, 13, 1931–1939.
  26. Ancel, J.; Dewolf, M.; Deslée, G.; Nawrocky-Raby, B.; Dalstein, V.; Gilles, C.; Polette, M. Clinical Impact of the Epithelial-Mesenchymal Transition in Lung Cancer as a Biomarker Assisting in Therapeutic Decisions. Cells Tissues Organs 2022, 211, 91–109.
  27. Zhong, H.; Wang, J.; Zhu, Y.; Shen, Y. Comprehensive Analysis of a Nine-Gene Signature Related to Tumor Microenvironment in Lung Adenocarcinoma. Front. Cell Dev. Biol. 2021, 9, 700607.
  28. Wang, Y.; Li, X.; Peng, S.; Hu, H.; Wang, Y.; Shao, M.; Feng, G.; Liu, Y.; Bai, Y. Single-Cell Analysis Reveals Spatial Heterogeneity of Immune Cells in Lung Adenocarcinoma. Front. Cell Dev. Biol. 2021, 9, 638374.
  29. Geng, Y.; Shao, Y.; He, W.; Hu, W.; Xu, Y.; Chen, J.; Wu, C.; Jiang, J. Prognostic Role of Tumor-Infiltrating Lymphocytes in Lung Cancer: A Meta-Analysis. Cell. Physiol. Biochem. 2015, 37, 1560–1571.
  30. Zhong, S.; Golpon, H.; Zardo, P.; Borlak, J. MiRNAs in Lung Cancer. A Systematic Review Identifies Predictive and Prognostic MiRNA Candidates for Precision Medicine in Lung Cancer. Transl. Res. J. Lab. Clin. Med. 2021, 230, 164–196.
  31. Saliminejad, K.; Khorram Khorshid, H.R.; Soleymani Fard, S.; Ghaffari, S.H. An Overview of MicroRNAs: Biology, Functions, Therapeutics, and Analysis Methods. J. Cell. Physiol. 2019, 234, 5451–5465.
  32. Wu, K.-L.; Tsai, Y.-M.; Lien, C.-T.; Kuo, P.-L.; Hung, A.J.-Y. The Roles of MicroRNA in Lung Cancer. Int. J. Mol. Sci. 2019, 20, 1611.
  33. Gkogkou, P.; Peponi, E.; Ntaskagiannis, D.; Murray, S.; Demou, A.; Sainis, I.; Ioakeim, E.; Briasoulis, E.; Tsekeris, P. E-Cadherin and Syndecan-1 Expression in Patients With Advanced Non-Small Cell Lung Cancer Treated With Chemoradiotherapy. In Vivo 2020, 34, 453–459.
  34. Chae, Y.K.; Chang, S.; Ko, T.; Anker, J.; Agte, S.; Iams, W.; Choi, W.M.; Lee, K.; Cruz, M. Epithelial-Mesenchymal Transition (EMT) Signature Is Inversely Associated with T-Cell Infiltration in Non-Small Cell Lung Cancer (NSCLC). Sci. Rep. 2018, 8, 2918.
  35. Zhou, H.; Liu, T.; Wang, Z. Analysis of Non-Small Cell Lung Cancer Microenvironment Indicates Preponderance of T Cell Exhaustion Marker Expression. Exp. Cell Res. 2017, 360, 205–209.
  36. Wu, C.; Rao, X.; Lin, W. Immune Landscape and a Promising Immune Prognostic Model Associated with TP53 in Early-Stage Lung Adenocarcinoma. Cancer Med. 2021, 10, 806–823.
  37. Quintanal-Villalonga, Á.; Mediano, M.; Ferrer, I.; Meléndez, R.; Carranza-Carranza, A.; Suárez, R.; Carnero, A.; Molina-Pinelo, S.; Paz-Ares, L. Histology-Dependent Prognostic Role of PERK and P53 Protein Levels in Early-Stage Non-Small Cell Lung Cancer. Oncotarget 2018, 9, 19945–19960.
  38. Iggo, R.; Bartek, J.; Lane, D.; Gatter, K.; Harris, A.L.; Bartek, J. Increased Expression of Mutant Forms of P53 Oncogene in Primary Lung Cancer. Lancet 1990, 335, 675–679.
  39. Kim, C.-H.; Lee, H.S.; Park, J.-H.; Choi, J.-H.; Jang, S.-H.; Park, Y.-B.; Lee, M.G.; Hyun, I.G.; Kim, K.I.; Kim, H.S.; et al. Prognostic Role of P53 and Ki-67 Immunohistochemical Expression in Patients with Surgically Resected Lung Adenocarcinoma: A Retrospective Study. J. Thorac. Dis. 2015, 7, 822–833.
  40. Venhuizen, J.-H.; Jacobs, F.J.C.; Span, P.N.; Zegers, M.M. P120 and E-Cadherin: Double-Edged Swords in Tumor Metastasis. Semin. Cancer Biol. 2020, 60, 107–120.
  41. Aubrey, B.J.; Kelly, G.L.; Janic, A.; Herold, M.J.; Strasser, A. How Does P53 Induce Apoptosis and How Does This Relate to P53-Mediated Tumour Suppression? Cell Death Differ. 2018, 25, 104–113.
  42. Saifi, M.; Maran, A.; Raynaud, P.; Picot, M.C.; Quittet, P.; Cartron, G.; Rossi, J.F.; Costes, V. High Ratio of Interfollicular CD8/FOXP3-Positive Regulatory T Cells Is Associated with a High FLIPI Index and Poor Overall Survival in Follicular Lymphoma. Exp. Ther. Med. 2010, 1, 933–938.
  43. Meng, X.; Gao, Y.; Yang, L.; Jing, H.; Teng, F.; Huang, Z.; Xing, L. Immune Microenvironment Differences Between Squamous and Non-Squamous Non-Small-Cell Lung Cancer and Their Influence on the Prognosis. Clin. Lung Cancer 2019, 20, 48–58.
  44. Qi, X.; Qi, C.; Qin, B.; Kang, X.; Hu, Y.; Han, W. Immune-Stromal Score Signature: Novel Prognostic Tool of the Tumor Microenvironment in Lung Adenocarcinoma. Front. Oncol. 2020, 10, 1816.
  45. Wang, J.; Tian, S.; Sun, J.; Zhang, J.; Lin, L.; Hu, C. The Presence of Tumour-Infiltrating Lymphocytes (TILs) and the Ratios between Different Subsets Serve as Prognostic Factors in Advanced Hypopharyngeal Squamous Cell Carcinoma. BMC Cancer 2020, 20, 731.
  46. Veatch, J.R.; Simon, S.; Riddell, S.R. Tumor-Infiltrating Lymphocytes Make Inroads in Non–Small-Cell Lung Cancer. Nat. Med. 2021, 27, 1339–1341.
  47. Reynders, K.; De Ruysscher, D. Tumor Infiltrating Lymphocytes in Lung Cancer: A New Prognostic Parameter. J. Thorac. Dis. 2016, 8, E833–E835.
  48. Chen, B.; Li, H.; Liu, C.; Xiang, X.; Wang, S.; Wu, A.; Shen, Y.; Li, G. Prognostic Value of the Common Tumour-Infiltrating Lymphocyte Subtypes for Patients with Non-Small Cell Lung Cancer: A Meta-Analysis. PLoS ONE 2020, 15, e0242173.
  49. O’Brien, S.M.; Klampatsa, A.; Thompson, J.C.; Martinez, M.C.; Hwang, W.-T.; Rao, A.S.; Standalick, J.E.; Kim, S.; Cantu, E.; Litzky, L.A.; et al. Function of Human Tumor-Infiltrating Lymphocytes in Early-Stage Non–Small Cell Lung Cancer. Cancer Immunol. Res. 2019, 7, 896–909.
  50. Lee, S.S.; Cheah, Y.K. The Interplay between MicroRNAs and Cellular Components of Tumour Microenvironment (TME) on Non-Small-Cell Lung Cancer (NSCLC) Progression. J. Immunol. Res. 2019, 2019, e3046379.
  51. Ogiya, R.; Niikura, N.; Kumaki, N.; Bianchini, G.; Kitano, S.; Iwamoto, T.; Hayashi, N.; Yokoyama, K.; Oshitanai, R.; Terao, M.; et al. Comparison of Tumor-Infiltrating Lymphocytes between Primary and Metastatic Tumors in Breast Cancer Patients. Cancer Sci. 2016, 107, 1730–1735.
  52. Germain, C.; Gnjatic, S.; Tamzalit, F.; Knockaert, S.; Remark, R.; Goc, J.; Lepelley, A.; Becht, E.; Katsahian, S.; Bizouard, G.; et al. Presence of B Cells in Tertiary Lymphoid Structures Is Associated with a Protective Immunity in Patients with Lung Cancer. Am. J. Respir. Crit. Care Med. 2014, 189, 832–844.
  53. Barmpoutis, P.; Capite, M.D.; Kayhanian, H.; Waddingham, W.; Alexander, D.C.; Jansen, M.; Kwong, F.N.K. Tertiary Lymphoid Structures (TLS) Identification and Density Assessment on H&E-Stained Digital Slides of Lung Cancer. PLoS ONE 2021, 16, e0256907.
  54. Jacquelot, N.; Tellier, J.; Nutt, S.I.; Belz, G.T. Tertiary Lymphoid Structures and B Lymphocytes in Cancer Prognosis and Response to Immunotherapies. Oncoimmunology 2021, 10, 1900508.
  55. Goc, J.; Germain, C.; Vo-Bourgais, T.K.D.; Lupo, A.; Klein, C.; Knockaert, S.; de Chaisemartin, L.; Ouakrim, H.; Becht, E.; Alifano, M.; et al. Dendritic Cells in Tumor-Associated Tertiary Lymphoid Structures Signal a Th1 Cytotoxic Immune Contexture and License the Positive Prognostic Value of Infiltrating CD8+ T Cells. Cancer Res. 2014, 74, 705–715.
  56. Munoz-Erazo, L.; Rhodes, J.L.; Marion, V.C.; Kemp, R.A. Tertiary Lymphoid Structures in Cancer—Considerations for Patient Prognosis. Cell. Mol. Immunol. 2020, 17, 570–575.
  57. Tuminello, S.; Veluswamy, R.; Lieberman-Cribbin, W.; Gnjatic, S.; Petralia, F.; Wang, P.; Flores, R.; Taioli, E. Prognostic Value of Immune Cells in the Tumor Microenvironment of Early-Stage Lung Cancer: A Meta-Analysis. Oncotarget 2019, 10, 7142–7155.
  58. Cui, M.; Wang, H.; Yao, X.; Zhang, D.; Xie, Y.; Cui, R.; Zhang, X. Circulating MicroRNAs in Cancer: Potential and Challenge. Front. Genet. 2019, 10, 626.
  59. Yerukala Sathipati, S.; Ho, S.-Y. Identifying the MiRNA Signature Associated with Survival Time in Patients with Lung Adenocarcinoma Using MiRNA Expression Profiles. Sci. Rep. 2017, 7, 7507.
  60. Han, Y.; Li, H. MiRNAs as Biomarkers and for the Early Detection of Non-Small Cell Lung Cancer (NSCLC). J. Thorac. Dis. 2018, 10, 3119–3131.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Oncology
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Paul Chiroi
,
Radu Pirlog
,
,
Ancuta Jurj
,
Cecilia Bica-Pop
,
Doinita Crisan
,
Jean-Christophe Sabourin
,
Ioana Berindan-Neagoe
View Times: 375
Revisions: 2 times (View History)
Update Date: 23 May 2022
Table of Contents
    1000/1000
    Hot Most Recent
    Video Production Service
    Feedback