Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Prognostic significance of NF-κB expression in non-small cell lung cancer: A meta-analysis

  • Lijun Gu,

    Roles Data curation, Investigation, Methodology, Software, Writing – original draft

    Affiliation Nanlou Respiratory Diseases Department, Chinese PLA General Hospital, Beijing, China

  • Zhiyan Wang,

    Roles Data curation, Validation, Writing – review & editing

    Affiliation Nanlou Respiratory Diseases Department, Chinese PLA General Hospital, Beijing, China

  • Jing Zuo,

    Roles Formal analysis, Resources

    Affiliation Nanlou Health Care Department, Chinese PLA General Hospital, Beijing, China

  • Hongmei Li ,

    Contributed equally to this work with: Hongmei Li, Lin Zha

    Roles Data curation, Methodology, Project administration, Writing – original draft

    hli301hospital@sina.com (HL); lzha306hospital@sina.com (LZ)

    Affiliations Clinical Center of Spaceport, Chinese PLA General Hospital, Beijing, China, Clinical Center of Spaceport, The 309th Hospital of People's Liberation Army, Beijing, China

  • Lin Zha

    Contributed equally to this work with: Hongmei Li, Lin Zha

    Roles Project administration, Writing – review & editing

    hli301hospital@sina.com (HL); lzha306hospital@sina.com (LZ)

    Affiliations Clinical Center of Spaceport, Chinese PLA General Hospital, Beijing, China, Clinical Center of Spaceport, The 309th Hospital of People's Liberation Army, Beijing, China

Abstract

Nuclear factor kappa B (NF-κB), a key nuclear transcription factor, is associated with prognosis in a variety of human cancers. However, the clinical value of NF-κB in non-small cell lung cancer (NSCLC) is still controversial. Therefore, the aim of this meta-analysis was to obtain an accurate evaluation of the relationship between NF-κB expression and survival prognosis of NSCLC patients based on published articles. PubMed, EMBASE and Web of Science databases were systematically searched for potential articles. A total of 1159 patients from 7 eligible studies comparing prognostic significance of NF-κB expression levels in NSCLC were included in our meta-analysis. I2 statistic and P value were performed to evaluate heterogeneity. The results of analysis were presented as hazard ratio (HR) or odds ratios (OR) with 95% confidence interval (95% CI). Subgroup analysis based on ethnicity of NSCLC patients and NF-kB cellular localization within cancer cells were conducted to illustrate the potential discrepancy. Significant heterogeneity was considered at I2>50% and P<0.05, and random-effects model was used. The combined results indicated that higher NF-κB expression was associated with shorter overall survival (OS) of NSCLC patients (HR = 2.78, 95% CI = 1.51–5.12, P = 0.001). Moreover, NF-κB expression was closely associated with tumor stage (HR = 0.32, 95% CI = 0.18–0.57, P<0.0001), lymph node metastasis (HR = 0.56, 95% CI = 0.38–0.83, P = 0.004) and 5-year OS for NSCLC patients (OR = 1.83, 95% CI = 1.02–3.31, P = 0.04). We conclude that NF-κB expression may be a potential unfavorable prognostic marker for NSCLC patients.

Introduction

Non-small cell lung cancer (NSCLC) is a major cause of cancer mortality and is one of the most common cancers worldwide [1]. In spite of recent advances in treatment including targeted therapy, adjuvant therapy and surgery, the overall prognosis of NSCLC is grim and the 5-year survival rate is as low as 15% [2, 3]. Therefore, a more favorable prognostic biomarker that contributes to the improvement of survival situation is crucial for the development of therapeutic strategies against NSCLC.

Accumulating evidence has indicated that cancer-related deaths are partially due to activation of inflammatory transcription factors in cancer cells [46]. Inflammatory transcriptional factors, including nuclear factor kappa B (NF-κB), regulate the development of malignant tumor through a wide range of physiologic and pathologic processes including cellular senescence, apoptosis, metabolism, stress responses and tumorigenesis [711]. NF-κB functions through activating diverse downstream signaling cascades, such as TNFα, BCL-2 and STAT 3 pathways [1214]. Due to its tumorigenic characteristics, NF-κB may perform as a target for improving living quality for NSCLC patients. Previous studies have shown that NF-κB performs as a tumor promoter in NSCLC. Elevated NF-κB expression levels were detected in NSCLC tissues in contrast with its corresponding normal tissues [15]. Moreover, NF-κB overexpression is associated with cancer cell metastasis and unfavorable prognosis in NSCLC patients [16, 17]. However, the clinical significance of NF-κB on prognostic value is still controversial. Other studies considered NF-κB as a tumor suppressor for NSCLC since it decreased several oncogenes expression and resulted in a better prognostic outcome [18].

In order to explain the discrepancy on the prognostic significance of NF-κB in NSCLC, we conducted a meta-analysis to systematically evaluate the association between the NF-κB expression and NSCLC prognosis.

Materials and methods

Publication search

All procedures involved in this meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement.

Literatures published before March 1, 2018 were surveyed thoroughly on PubMed, EMBASE and Web of Science databases. No language limitation and publication restriction were applied. Terms were searched as follows: (“NF-κB” OR “NF-kappa B” OR “nuclear factor kappa B”) AND (“Non-Small-Cell Lung Cancer” OR “Non-Small-Cell Lung Carcinoma” OR “NSCLC” OR “Lung cancer” OR “Lung adenocarcinoma” OR “Lung squamous carcinoma”). The references list of all searched articles was also manually reviewed.

Article selection

Articles that met the following criteria were eligible for our meta-analysis: investigate the NF-κB expression in NSCLC patients; evaluate the prognostic significance in NSCLC patients with different NF-κB expression; present the values of hazard ratio (HR) with 95% confidence interval (CI) or survival curves. Articles were excluded according to the following criteria: duplicated or overlapped studies; reviews or case reports; animal or database studies; no sufficient original data or unavailable raw data.

Data extraction

We extracted the following information from qualified studies: names of first author, publication year, country, ethnicity, sample size, values of HR and 95% CI, NF-kB subunit, cellular localization, histology, tumor stage and lymph node metastasis. Two reviewers extracted the data from each of these studies and assessed risk for bias according to the PRISMA recommendations independently.

Statistical analysis

The pooled HR at a 95% CI was analyzed using Review Manager 5.3 to evaluate the association of NF-κB expression with NSCLC patient survival, and pooled odds ratio (OR) with 95% CI was analyzed to assess the association between NF-κB expression and clinical features. Engauge Digitizer version 4.1 was used to get the values of HRs and 95%CI from survival curves. X2-based Q test and I2 test were used to evaluate the heterogeneity among studies. Significant heterogeneity was considered at P<0.05 and I2>50%, and the random-effects model was utilized. Moreover, a sensitivity analysis was conducted to test the consistency of the combined results by Stata13.0. Additionally, publication bias among selected studies was assessed by Begg’s and Egger’s test using Stata13.0. Statistical significance was considered at p<0.05.

Results

Study selection

A total of 1160 literatures accessed for eligibility were obtained from PubMed, EMBASE and Web of Science databases. During further review, 360 articles were excluded from the analysis due to duplicate publications, 13 studies were deleted due to review articles, 759 articles were excluded due to no relevant outcome, 20 articles removed were due to no sufficient data, 1 articles removed were due to unavailable raw data. Eventually, 7 studies were eligible for our meta-analysis [1521]. The selection workflow was illustrated in Fig 1.

Study characteristics

Among the 7 studies, the overall number of cases was 1159 and the sample size ranged from 45 to 345. Five studies were carried out in China, followed by Norway and the USA. Two studies were performed on the Caucasian population, while other studies were on Asians. All studies used immunohistochemistry (IHC) to detect NF-κB expression levels. Three studies explored the relationship between NF-κB expression and histology classification, and four studies detected the association between NF-κB expression and either tumor stage or lymph node metastasis. The main features of the included studies were summarized in Table 1.

thumbnail
Table 1. Main characteristics of included studies in the meta-analysis.

https://doi.org/10.1371/journal.pone.0198223.t001

Overall analyses

The values of HR and 95% CI from each study were combined to be analyzed (Fig 2). The outcome indicated that higher NF-κB expression was linked to worse overall survival (OS) for NSCLC patients, suggesting a tumor promotive function of NF-κB. (HR = 2.78, 95% CI = 1.51–5.12, P = 0.001). Significant heterogeneity was observed (P = 0.002, I2 = 71%), and a random-effects model was used for statistical analysis (Fig 2A). Studies were regrouped for subset analysis based on the ethnicity of NSCLC patients. Outcome indicated that NF-κB expression was significantly correlated with OS in Asian (n = 5, HR = 2.99, 95% CI = 1.60–5.58, P = 0.0006), but not in Caucasian (n = 2, HR = 2.84, 95% CI = 0.58–13.89, P = 0.20) (Fig 2B).

thumbnail
Fig 2. Forest plot for the association between NF-κB and overall survival in NSCLC patients.

(A) Overall analysis of all NSCLC patients. (B) Subgroup analysis of Asian and Caucasian NSCLC patients. HR, hazard ratio; CI, confidence interval.

https://doi.org/10.1371/journal.pone.0198223.g002

Three studies explored the relationship between NF-κB and histology, and four studies investigated the correlation between NF-κB and either tumor stage or lymph node metastasis. The pooled OR from 137 lung adenocarcinoma (ADC) and 124 squamous cell carcinoma (SCC) revealed that there was no significant difference of NF-κB expression between ADC and SCC (OR = 1.20, 95% CI = 0.71–2.01, P = 0.50) (Fig 3A). NF-κB expression was frequent in patients with T3/T4 tumor stage rather than T1/T2 (OR = 0.32, 95% CI = 0.18–0.57, P<0.0001) (Fig 3B). Moreover, NF-κB expressed more frequently in patients with lymph node metastasis (OR = 0.56, 95% CI = 0.38–0.83, P = 0.004) (Fig 3C).

thumbnail
Fig 3. Forest plot for the association of NF-κB with clinicopathological parameters.

(A) Patients with adenocarcinoma and squamous cell carcinoma. (B) Patients with tumor stage T1/T2 and T3/T4. (C) Patients with or without lymph node metastasis. OR, Odds ratio; CI, confidence interval.

https://doi.org/10.1371/journal.pone.0198223.g003

Sensitivity analysis was performed to evaluate the stability of our results. Fig 4 showed that individual study had little substantial impact on the final outcomes, indicating that our results were stable. Publication bias was investigated by both Begg’s and Egger’s test, indicating there was no publication bias in all groups since P>0.05 (Fig 5).

thumbnail
Fig 4. Sensitivity analyses.

(A) Overall survival in NSCLC patients. (B) Tumor stage. (C) Lymph node metastasis.

https://doi.org/10.1371/journal.pone.0198223.g004

thumbnail
Fig 5. Publication bias estimated by Begg’s and Egger’s test.

(A) Overall survival in NSCLC patients. (B) Tumor stage. (C) Lymph node metastasis.

https://doi.org/10.1371/journal.pone.0198223.g005

We found that high expression of NF-kB correlated with decreased 5-year OS for NSCLC patients (OR = 1.83, 95% CI = 1.02–3.31, P = 0.04) with a significant heterogeneity (P<0.0001, I2 = 81%) (Fig 6). Subgroup analysis was carried out based on the NF-kB expression in either nucleus or cytoplasm. We observed that NF-kB expression in nucleus (activation status) was correlated with decreased 5-year OS (OR = 2.12, 95% CI = 1.40–3.21, P = 0.0004), whereas no significant association was observed between cytoplasmic NF-kB expression (inactivation status) and 5-year OS in NSCLC patients (OR = 1.58, 95% CI = 0.54–4.65, P = 0.40) (Fig 7). In addition, the expression levels of NF-kB subunits (P65, NF-kB1 and RelB) were not associated with deceased 5-year OS of NSCLC (P65 OR = 1.56, 95% CI = 0.91–2.68, P = 0.11; NF-kB1 OR = 1.19, 95% CI = 0.37–3.88, P = 0.77; RelB OR = 8.40, 95% CI = 3.36–20.97, P<0.00001) (Fig 8).

thumbnail
Fig 6. Forest plot for the association between NF-κB expression levels and 5-year overall survival amoug NSCLC patients.

https://doi.org/10.1371/journal.pone.0198223.g006

thumbnail
Fig 7. Subgroup analysis of nuclear and cytoplasmic NF-kB expression associated with 5-year overall survival.

NF-kB(-), low/negative expression of NF-kB; NF-kB(+), high and moderate/positive expression of NF-kB.

https://doi.org/10.1371/journal.pone.0198223.g007

thumbnail
Fig 8. Forest plot for the expression levels of NF-kB family members and 5-year overall survival in NSCLC patients.

https://doi.org/10.1371/journal.pone.0198223.g008

Discussion

It has been documented that NF-κB, an important inflammatory transcriptional factor, performs a pivotal part in various biological processes and has a dual effect on the progression of cancers [22, 23]. Some researchers have identified high expression levels of NF-κB in variety of solid malignancies, such as breast cancer, renal cell carcinoma and oral squamous cell carcinoma [2426]. Inhibitors targeting at NF-κB expression also inhibited the tumor formation and angiogenesis capacity of lung cancer cells [27]. On the contrary, some studies have shown that NF-κB transactivated the expression of pro-apoptosis genes including Fas and death receptors, and NF-κB performed as a tumor suppressor to facilitate P53-related cancer cell death [2830]. Therefore, NF-κB may act as different roles in diverse types of carcinoma. As to the prognosis of NSCLC, the relationship of NF-κB expression with survival outcome remains uncertain. Previous studies have reported that NSCLC patients are characterized by enhanced NF-κB expression. However, other studies have demonstrated reduced level of NF-κB expression observed in NSCLC cells. Understanding the prognostic value of NF-κB in NSCLC patients may provide insights for the improvement of clinical outcome. Therefore, our meta-analysis exploring the prognostic role of NF-κB in NSCLC patients is clinically significant.

In this study, we showed that high NF-κB expression as a prognostic predictor is positively associated with poor survival outcome of NSCLC patients. The subgroup analysis unveiled that NF-κB expression was more closely associated with OS in Asian but not in Caucasian, indicating that the heterogeneity may be attributed to different ethnicity of patients. We also investigated the association between NF-κB expression and clinicopathological parameters. We found that NF-κB expressed highly in NSCLC patients with T3/T4 tumor stage and lymph node metastasis, indicating that NF-κB may perform tumorigenesis function in NSCLC. Besides, the expression of NF-kB in nucleus is significantly associated with worse 5-year OS for NSCLC, but not in the cytoplasm, suggesting that the relationship between NF-kB expression and 5-year OS was relevant to subcellular localization of NF-kB. Meanwhile, no association of NF-kB subunits expression and 5-year OS was obtained, revealing that individual expression levels of P65, NF-kB1 and RelB were probably not correlated with 5-year OS for NSCLC patients. More multi-center and well-matched cohort studies will be urgently needed in the future to address the specific function of NF-kB family members on NSCLC prognosis.

The mammalian NF-kB family has subunits including RelA (P65), RelB, NF-kB1 (P50/P105), NF-kB2 (P52/P100) and c-Rel. The pathways of NF-kB activation consist of canonical (or classical) pathway mediated by RelA/P50 or c-Rel/P50 dimers and non-canonical (or alternative) pathway mediated by RelB/P52 dimer [31, 32]. Studies have suggested that canonical pathway generally performs as tumor promoting and anti-apoptotic roles, while non-canonical pathway has tumor suppressing and facilitating apoptosis effects within cancer cells. As to the complexity of NF-kB in NSCLC, further studies are needed to clarify the prognostic value of canonical and non-canonical NF-kB activation pathways in NSCLC patients based on multiple clinical studies in the future. Some literatures have reported paradoxical prognosis of NF-kB in different cohort of NSCLC patients. This discrepancy can be explained by the fact that NF-kB functions under regulations of diverse upstream driving mutations, including oncogene gain of function and/or loss of tumor suppressors, which ascertains its effects on regulating various downstream targets to trigger either tumor promoting or tumor suppressing function within cancer cells.

Although immunohistochemical method has been extensively used for decades, IHC performed by different laboratories has potential flaws for evaluating candidate prognostic biomarkers due to utilizing different antibodies and/or immunohistochemical protocols [3336]. As to the enrolled articles analyzed in this meta-analysis, all antibodies used were commercially available for IHC assay, and IHC protocols were performed based on standard peroxidase-based staining methods, including streptavidin-peroxidase method and avidin-biotinylated peroxidase complex method. Hence, the immunohistochemical results reported in these included studies are reproducible. Our study, however, found variable factors during IHC staining procedures in these enrolled studies, such as differences of antibodies used, incubation conditions and thresholds for positive immunostaining, which might bring in misleading information. In view of the above shortcomings, we suggest that IHC, at least in some cases, might not be an optimal method for evaluating candidate prognostic biomarkers in cancer tissues. Thus, more standardized protocols such as mining transcriptomic datasets from cancer tissues are vital for improving results reproducibility. And further meta-analysis is warranted to compare IHC to other genetic analysis.

Several limitations of this study might be pointed out. First, the sample size of cases in the selected studies was relatively limited in a range from 45 to 345, which could have resulted in inaccuracy in this meta-analysis. Second, the staining intensity cut-off values of NF-κB expression analyzed by IHC, a semi-quantitative evaluation method, were observer-dependent in these studies, which may affect the heterogeneity in our analyses. Third, the selected studies in our analyses were conducted mainly in Asian countries; little is known about the association of NF-κB expression with NSCLC in other countries. So more multi-center studies are warranted to verify the role of NF-κB in NSCLC prognosis.

In conclusion, we first combine the results of multiple clinical studies to reveal an association of NF-κB expression with OS in patients with NSCLC. The discovery of NF-κB as a predictor for the poor prognosis of NSCLC patients in our study might be important clinically.

Supporting information

Acknowledgments

This study was supported by the National Natural Science Foundation of China (grant number 81602423 to L.Z.).

References

  1. 1. Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30. pmid:28055103
  2. 2. Taverna S, Giallombardo M, Gil-Bazo I, Carreca AP, Castiglia M, Chacartegui J, et al. Exosomes isolation and characterization in serum is feasible in non-small cell lung cancer patients: critical analysis of evidence and potential role in clinical practice. Oncotarget. 2016;7(19):28748–60. pmid:26919248
  3. 3. Schild SE, Tan AD, Wampfler JA, Ross HJ, Yang P, Sloan JA. A new scoring system for predicting survival in patients with non-small cell lung cancer. Cancer Med. 2015;4(9):1334–43. pmid:26108458
  4. 4. Lasry A, Zinger A, Ben-Neriah Y. Inflammatory networks underlying colorectal cancer. Nat Immunol. 2016;17(3):230–40. pmid:26882261
  5. 5. Taniguchi K, Karin M. NF-kappaB, inflammation, immunity and cancer: coming of age. Nat Rev Immunol. 2018. pmid:29379212
  6. 6. Zitvogel L, Pietrocola F, Kroemer G. Nutrition, inflammation and cancer. Nat Immunol. 2017;18(8):843–50. pmid:28722707
  7. 7. Macia A, Vaquero M, Gou-Fabregas M, Castelblanco E, Valdivielso JM, Anerillas C, et al. Sprouty1 induces a senescence-associated secretory phenotype by regulating NFkappaB activity: implications for tumorigenesis. Cell Death Differ. 2014;21(2):333–43. pmid:24270409
  8. 8. Russo A, Saide A, Cagliani R, Cantile M, Botti G, Russo G. rpL3 promotes the apoptosis of p53 mutated lung cancer cells by down-regulating CBS and NFkappaB upon 5-FU treatment. Sci Rep. 2016;6:38369. pmid:27924828
  9. 9. Zha X, Hu Z, Ji S, Jin F, Jiang K, Li C, et al. NFkappaB up-regulation of glucose transporter 3 is essential for hyperactive mammalian target of rapamycin-induced aerobic glycolysis and tumor growth. Cancer Lett. 2015;359(1):97–106. pmid:25578782
  10. 10. Yang G, Wang Y, Feng J, Liu Y, Wang T, Zhao M, et al. Aspirin suppresses the abnormal lipid metabolism in liver cancer cells via disrupting an NFkappaB-ACSL1 signaling. Biochem Biophys Res Commun. 2017;486(3):827–32. pmid:28359761
  11. 11. Shi N, Chen F, Zhang X, Clinton SK, Tang X, Sun Z, et al. Suppression of Oxidative Stress and NFkappaB/MAPK Signaling by Lyophilized Black Raspberries for Esophageal Cancer Prevention in Rats. Nutrients. 2017;9(4). pmid:28441719
  12. 12. Li H, Zhong A, Li S, Meng X, Wang X, Xu F, et al. The integrated pathway of TGFbeta/Snail with TNFalpha/NFkappaB may facilitate the tumor-stroma interaction in the EMT process and colorectal cancer prognosis. Sci Rep. 2017;7(1):4915. pmid:28687755
  13. 13. Alam M, Kashyap T, Pramanik KK, Singh AK, Nagini S, Mishra R. The elevated activation of NFkappaB and AP-1 is correlated with differential regulation of Bcl-2 and associated with oral squamous cell carcinoma progression and resistance. Clin Oral Investig. 2017;21(9):2721–31. pmid:28233171
  14. 14. Santoro A, Ciaglia E, Nicolin V, Pescatore A, Prota L, Capunzo M, et al. The isoprenoid end product N6-isopentenyladenosine reduces inflammatory response through the inhibition of the NFkappaB and STAT3 pathways in cystic fibrosis cells. Inflamm Res. 2017. pmid:29230506
  15. 15. Jin X, Wang Z, Qiu L, Zhang D, Guo Z, Gao Z, et al. Potential biomarkers involving IKK/RelA signal in early stage non-small cell lung cancer. Cancer Sci. 2008;99(3):582–9. pmid:18215193
  16. 16. Nair VS, Gevaert O, Davidzon G, Plevritis SK, West R. NF-kappaB protein expression associates with (18)F-FDG PET tumor uptake in non-small cell lung cancer: a radiogenomics validation study to understand tumor metabolism. Lung Cancer. 2014;83(2):189–96. pmid:24355259
  17. 17. Qin H, Zhou J, Zhou P, Xu J, Tang Z, Ma H, et al. Prognostic significance of RelB overexpression in non-small cell lung cancer patients. Thorac Cancer. 2016;7(4):415–21. pmid:27385983
  18. 18. Al-Saad S, Al-Shibli K, Donnem T, Persson M, Bremnes RM, Busund LT. The prognostic impact of NF-kappaB p105, vimentin, E-cadherin and Par6 expression in epithelial and stromal compartment in non-small-cell lung cancer. Br J Cancer. 2008;99(9):1476–83. pmid:18854838
  19. 19. Yu J, Wang L, Zhang T, Shen H, Dong W, Ni Y, et al. Co-expression of beta-arrestin1 and NF-small ka, CyrillicB is associated with cancer progression and poor prognosis in lung adenocarcinoma. Tumour Biol. 2015;36(8):6551–8. pmid:25820700
  20. 20. Zhang Z, Ma J, Li N, Sun N, Wang C. Expression of nuclear factor-kappaB and its clinical significance in nonsmall-cell lung cancer. Ann Thorac Surg. 2006;82(1):243–8. pmid:16798222
  21. 21. Zhang D, Jin X, Wang F, Wang S, Deng C, Gao Z, et al. Combined prognostic value of both RelA and IkappaB-alpha expression in human non-small cell lung cancer. Ann Surg Oncol. 2007;14(12):3581–92. pmid:17899287
  22. 22. Bentires M. [Kappa-B nuclear factor and apoptosis of cancerous cells]. Bull Mem Acad R Med Belg. 2001;156(6 Pt 2):329–37. pmid:11928223
  23. 23. Coward WR, Sagara H, Wilson SJ, Holgate ST, Church MK. Allergen activates peripheral blood eosinophil nuclear factor-kappaB to generate granulocyte macrophage-colony stimulating factor, tumour necrosis factor-alpha and interleukin-8. Clin Exp Allergy. 2004;34(7):1071–8. pmid:15248852
  24. 24. Zhou XL, Fan W, Yang G, Yu MX. The clinical significance of PR, ER, NF- kappa B, and TNF- alpha in breast cancer. Dis Markers. 2014;2014:494581. pmid:24864130
  25. 25. Kankaya D, Kiremitci S, Tulunay O, Baltaci S. Gelsolin, NF-kappaB, and p53 expression in clear cell renal cell carcinoma: Impact on outcome. Pathol Res Pract. 2015;211(7):505–12. pmid:25908108
  26. 26. Jiang LL, Zhao YJ, Li Y. [Expressions and clinical significance of TGF-betaRII and NF-kappaB in oral squamous cell carcinoma]. Shanghai Kou Qiang Yi Xue. 2016;25(6):729–33. pmid:28275800
  27. 27. Gao P, Gao YJ, Liang HL. Effect of NF- kappa B inhibitor PDTC on VEGF and endostatin expression of mice with Lewis lung cancer. Asian Pac J Trop Med. 2015;8(3):220–4. pmid:25902165
  28. 28. Perkins ND. NF-kappaB: tumor promoter or suppressor? Trends Cell Biol. 2004;14(2):64–9. pmid:15102437
  29. 29. Ryan KM, Ernst MK, Rice NR, Vousden KH. Role of NF-kappaB in p53-mediated programmed cell death. Nature. 2000;404(6780):892–7. pmid:10786798
  30. 30. Disis ML. Immune regulation of cancer. J Clin Oncol. 2010;28(29):4531–8. pmid:20516428
  31. 31. Giopanou I, Lilis I, Papaleonidopoulos V, Marazioti A, Spella M, Vreka M, et al. Comprehensive Evaluation of Nuclear Factor-kappaBeta Expression Patterns in Non-Small Cell Lung Cancer. PLoS One. 2015;10(7):e0132527. pmid:26147201; PubMed Central PMCID: PMCPMC4493092.
  32. 32. Vreka M, Lilis I, Papageorgopoulou M, Giotopoulou GA, Lianou M, Giopanou I, et al. IotakappaBeta kinase alpha is required for development and progression of KRAS-mutant lung adenocarcinoma. Cancer Res. 2018. pmid:29588349.
  33. 33. Gown AM. Current issues in ER and HER2 testing by IHC in breast cancer. Mod Pathol. 2008;21 Suppl 2:S8–S15. pmid:18437174.
  34. 34. Soo RA, Yun Lim JS, Asuncion BR, Fazreen Z, Herrera MC, Mohd Omar MF, et al. Determinants of variability of five programmed death ligand-1 immunohistochemistry assays in non-small cell lung cancer samples. Oncotarget. 2018;9(6):6841–51. pmid:29467933; PubMed Central PMCID: PMCPMC5805519.
  35. 35. Rimm D, Schalper K, Pusztai L. Unvalidated antibodies and misleading results. Breast Cancer Res Treat. 2014;147(2):457–8. pmid:25086631; PubMed Central PMCID: PMCPMC4216678.
  36. 36. Anagnostou VK, Welsh AW, Giltnane JM, Siddiqui S, Liceaga C, Gustavson M, et al. Analytic variability in immunohistochemistry biomarker studies. Cancer Epidemiol Biomarkers Prev. 2010;19(4):982–91. pmid:20332259; PubMed Central PMCID: PMCPMC3891912.