| Literature DB >> 35883698 |
Jason Hongting Leung1, Benjamin Ng2,3, Wei-Wen Lim2,3.
Abstract
Non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer and is a fast progressive disease when left untreated. Identification of potential biomarkers in NSCLC is an ongoing area of research that aims to detect, diagnose, and prognosticate patients early to optimize treatment. We review the role of interleukin-11 (IL11), a stromal-cell derived pleiotropic cytokine with profibrotic and cellular remodeling properties, as a potential biomarker in NSCLC. This review identifies the need for biomarkers in NSCLC, the potential sources of IL11, and summarizes the available information leveraging upon published literature, publicly available datasets, and online tools. We identify accumulating evidence suggesting IL11 to be a potential biomarker in NSCLC patients. Further in-depth studies into the pathophysiological effects of IL11 on stromal-tumor interaction in NSCLC are warranted and current available literature highlights the potential value of IL11 detection as a diagnostic and prognostic biomarker in NSCLC.Entities:
Keywords: biomarkers; cytokines; interleukin-11; non-small cell lung cancer
Mesh:
Substances:
Year: 2022 PMID: 35883698 PMCID: PMC9318853 DOI: 10.3390/cells11142257
Source DB: PubMed Journal: Cells ISSN: 2073-4409 Impact factor: 7.666
Other IL6 family cytokines and components of the specific receptors associated with NSCLC.
| Cytokine | Receptors | References |
|---|---|---|
| IL6 | IL6R, gp130/IL6ST | [ |
| IL-31 | IL31Rα, OSMR | [ |
| LIF | LIFR/LIFRα, gp130/IL6ST | [ |
| OSM | OSMR/OSMRβ, gp130/IL6ST, LIFR | [ |
| CLCF1 | CNTFR, LIFR, gp130/IL6ST | [ |
Figure 1Differential expression of IL11 mRNA in lung adenocarcinoma (LUAD) and squamous cell carcinoma (SCC) based on the TCGA TARGET GTEx dataset. Solid tissue normal: adjacent normal tissue from TCGA dataset (n = 109). Normal tissue: tissue from subjects with no lung adenocarcinoma from GTEx dataset (n = 288). Primary tumor: lung tumor tissue (LUAD or SCC) from TCGA dataset (n = 1011). Recurrent tumor: lung tumor tissue from recurrence (n = 2). The results shown here are in whole or part based upon data generated by the TCGA Research Network [75] and GTEx [76] databases using the UCSC Xena online platform [77,78]. https://xenabrowser.net was accessed on 26 April 2022.
Studies identifying IL11 as a diagnostic biomarker.
| Study | Recruited Population | Comparison | Sample Type | Diagnostic Biomarker | Assay | Receiver Operator Curve and Test Metrics | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| AUC | Cutoff (pg/mL) | Sensitivity | Specificity (95% CI) | PPV | NPV | ||||||
| Pastor et al. [ | Age > 40 yrs, current or ex-smokers of 30 pack-years, evaluated for hemoptysis or pulmonary nodule or mass, excluding those with prior diagnosis of malignancy, active tuberculosis, history of drug abuse or other inflammatory disease apart from COPD | LUAD vs. non-LUAD—First validation cohort (n = 149) | BALF | IL11 protein | ELISA | 0.93 (0.90–0.97) | 42.0 | 90.2 (79–95.7) | 88.7 (90.6–93.5) | 80.7 (68.7–88.9) | 94.5 (87.8–97.6) |
| LUAD vs. non-LUAD—Second validation cohort (n = 160) | BALF | IL11 protein | ELISA | 0.95 (0.92–0.98) | 42.0 | 90.6 (79.7–95.9) | 83.0 (86.8–87.7) | 60.8 (49.7–70.8) | 96.8 (92.7–98.6) | ||
| Wu et al. [ | NSCLC patients with no history of radiochemotherapy, immune-targeted therapy or surgery (n = 91 for serum, of which 63 have LUAD and 28 have SCC; 64 for EBC) | Healthy volunteers without acute or chronic infectious diseases, vital organ diseases, or genetic family tumor history (n = 72 for serum; 63 for EBC) | Serum | IL11 protein | ELISA | 0.93 (0.88–0.97) | 126.1 | 75.0 | 100.0 | NR | NR |
| EBC | IL11 protein | ELISA | 0.78 (0.69–0.86) | 21.5 | 78.1 | 79.4 | NR | NR | |||
BALF: bronchoalveolar lavage fluid; EBC: exhaled breath condensate; LUAD: lung adenocarcinoma; SCC: Squamous cell carcinoma; COPD: chronic obstructive pulmonary disease; AUC: Area under curve; PPV: positive predictive value; NPV: negative predictive value; NSCLC: non-small cell lung cancer; NR: not reported.
Pathologies where IL11 from peripheral blood has been reported to be increased in human subjects.
| Pathology | Comparison | Source | Findings | Reference |
|---|---|---|---|---|
| Polycythemia vera | Healthy | Plasma | Increased | [ |
| Rheumatoid arthritis with or without interstitial lung disease | Healthy | Serum | Increased in rheumatoid arthritis, more so with concomitant interstitial lung disease | [ |
| Congestive heart failure | Healthy | Plasma | Increased | [ |
| Severe pancreatitis | Mild pancreatitis | Serum | Increased | [ |
| Breast cancer metastatic to bone | Primary breast cancer and healthy controls | Serum | Increased compared to healthy controlsCorrelated with shorter disease-free survival | [ |
| Pancreatic cancer | Healthy | Plasma | Increased | [ |
| Gastric cancer | Chronic superficial gastritis and | Serum | Increased in gastric cancer > chronic atrophic gastritis > chronic superficial gastritis | [ |
| Preeclampsia | Normal pregnant gestation-matched control | Serum | Increased | [ |
| Thoracic aortic dissection | Non-aortic dissection patients presenting with chest pain | Plasma | Increased | [ |
Studies identifying IL11 as a prognostic biomarker.
| Study | Year | Training Cohort | Validation Cohort (s) | Cancer Type | Prognostic Signature | Findings |
|---|---|---|---|---|---|---|
| Kratz et al. [ | 2012 | Non-squamous NSCLC (n = 361) | Stage I non-squamous NSCLC (n = 433), and stage I-III non-squamous NSCLC (n = 1006) | Non-squamous NSCLC | 11 Target genes ( |
Risk as identified by the 14 gene-expression assay was a statistically significant predictor of overall survival. |
| Watza et al. [ | 2018 | NSCLC patients without history of bronchiectasis or cystic fibrosis (n = 280) | TCGA Lung SCC and TCGA LUAD datasets (n = 1026) | NSCLC | 23 genes involved in the interleukin signaling pathway, including |
Interleukin signaling pathway was one of three pathways that was significantly associated with survival out of 48 immune-centric pathways evaluated. 23 genes were identified as drivers of the interleukin pathway enrichment, which included Higher expression of |
| Wang et al. [ | 2020 | TCGA LUAD dataset (497 LUAD tissues, 54 normal lung tissues) | n/a | LUAD | 6 genes ( |
Cytokine-cytokine receptor pathways, JAK-STAT signaling pathways were among the top 5 most significantly enriched pathways by differentially expressed immune-related genes. |
| Fan et al. [ | 2021 | TGCA LUAD dataset (n = 464)(majority stage I and II) | GSE13213 (n = 117), GSE30219 (n = 85), GSE31210 (n = 226), GSE72094 (n = 420)(majority stage I and II) | LUAD | 5 genes ( |
These 5 genes were selected as they were differentially expressed and prognostic and thought to play the most important role in LUAD |
| Chen et al. [ | 2021 | TCGA LUAD (535 LUAD tissues, 59 normal lung tissues)GSE161116 (9 LUAD tissues, 9 LUAD brain metastasis tissues) | n/a | LUAD | 6 genes ( |
|
| Peng et al. [ | 2021 | GSE161116 (13 lung tumor tissues, 15 brain tissues), GSE747706 (18 lung tumor tissues, 18 normal tissues), GSE21933 (21 lung tumor tissues, 21 normal tissues) datasets | n/a | NSCLC andBrain tumor | n/a |
20 genes (including High |
Figure 2Kaplan–Meier curves for overall survival in patients with either high or low tumor IL11 mRNA expression in the TCGA PanCancer Atlas datasets for (A) LUAD (n = 501) and (B) SCC (n = 478). A cutoff of z > 0 was used for high expression and z ≤ 0 as low expression. Logrank tests show statistically significant differences between the high and low expression groups. The results shown here are based upon data generated by the TCGA Research Network [75,116], generated with cbioportal (https://www.cbioportal.org) [113,117] that was last accessed on 26 April 2022.