High Integrin Α3 Expression Is Associated with Poor Prognosis in Patients with Non-Small Cell Lung Cancer

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Original Article

High integrin α3 expression is associated with poor prognosis in patients with non-small cell lung cancer

Qianping Li1#*, Weijie Ma1#, Shuai Chen2, Eddie C. Tian1, Sixi Wei1**, Reggie R. Fan1, Tao Wang3, Chihong Zhou3, Tianhong Li1,4^

1Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis School of Medicine, University of California Davis Comprehensive Cancer Center, Sacramento, California, USA; 2Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, California, USA; 3Department of Pathology and Laboratory Medicine, University of California Davis School of Medicine, Sacramento, CA, USA; 4Department of Internal Medicine, Veterans Affairs Northern California Health Care System, Mather, California, USA Contributions: (I) Conception and design: Q Li, W Ma, T Li; (II) Administrative support: T Li; (III) Provision of study materials or patients: T Li; (IV) Collection and assembly of data: Q Li, W Ma, EC Tian, RR Fan, T Wang, C Zhou; (V) Data analysis and interpretation: Q Li, W Ma, S Chen, T Li; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. #These authors contributed equally to this work. Correspondence to: Tianhong Li, MD, PhD. Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis School of Medicine, University of California Davis Comprehensive Cancer Center, 4501 X Street, Suite 3016, Sacramento, California 95817, USA. Email: [email protected].

Background: We previously showed that α3β1 integrin is a novel cancer biomarker and drug target in non- small cell lung cancer (NSCLC). This study characterized the integrin α3 (ITGA3) expression on patient specimens. Methods: Tissue microarrays (TMAs) were prepared from archival tissue blocks containing 161 patients, which included 91 adenocarcinoma (LUAD), 46 squamous carcinomas (LUSC), and 24 other histology types. TMA sections were stained and scored for ITGA3 expression by immunohistochemistry (IHC). Kaplan- Meier curves and log-rank tests were used to compare overall survival (OS) between IHC score groups. Propensity-score-weighted Kaplan-Meier curves and weighted Cox models were used to adjust for covariate imbalance between IHC score groups. Logistic regression was used to determine ITGA3 transcriptome expression in NSCLC in The Cancer Genome Atlas (TCGA). Results: ITGA3 IHC expression (1+ to 3+) was detected in 107/161 (66.5%) of the NSCLC samples, and was associated with poor prognosis at the edge of significance (HR =1.30, 95% CI: 0.99–1.71, P=0.056), but significant (P<0.05) in subgroups of female patients, smokers and tumors with grade I and II differentiation using propensity-score-weighted survival analysis after adjusting for confounders. Multivariate survival analysis based on multiple imputation for missing variables showed ITGA3 expression, old age and metastasis were associated with poor prognosis (P<0.05). ITGA3 IHC expression was associated with poor prognosis in LUSC (HR =2.27, P<0.05) but not in LUAD (HR =1.49, P=0.16). Median ITGA3 expression was significantly higher in LUAD than LUSC (P<0.0001) in the TCGA transcriptome datasets. Using a higher cutoff than LUSC (70.6 vs. 19.5 FPKM), high ITGA3 RNA expression was also associated with poor prognosis in LUAD (P=0.023). ITGA3 interacted with key genes regulating epithelial to mesenchymal transition, angiogenesis, invasion and metastasis in both LUAD and LUSC. Conclusions: High ITGA3 IHC expression was associated with poor prognosis in NSCLC patients. Further study is warranted for targeting α3β1 integrin in NSCLC.

*Current address: Department of Cardiothoracic Surgery, Shanghai Jiaotong University Affiliated Sixth People’s Hospital, 600 Yi-Shan Road, Shanghai, China. **Current address: Department of Biochemistry, Hospital Affiliated to Guizhou Medical University, Guiyang, China. ^ORCID: 0000-0001-7422-3520.

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1362 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

Keywords: Integrin α3 subunit (ITGA3 subunit); ITGA3; non-small cell lung cancer (NSCLC); tissue microarray (TMA); prognosis

Submitted Dec 07, 2019. Accepted for publication Jun 18, 2020. doi: 10.21037/tlcr-19-633 View this article at: http://dx.doi.org/10.21037/tlcr-19-633

Introduction (4,19). Of note, LXY30 has been optimized to bind to live tumor cells but not to live normal cells (4). However, Non-small cell lung cancer (NSCLC) accounts for 80– LXY30 does not bind to tumor cells on the archival, 85% of lung cancer, which is the leading cause of cancer- FFPE specimens. In the current study, we determined the related deaths worldwide (1,2). Despite advances in early expression pattern and prognosis of ITGA3 expression by detection and treatment, the prognosis for patients with immunohistochemistry (IHC) using commercially available NSCLC remains poor (3). Novel therapeutic targets and antibodies on archived NSCLC tumors. treatment strategies are needed to improve the clinical outcomes for NSCLC patients, especially those diagnosed with unresectable, locally advanced or metastatic NSCLC. Methods α3β1 integrin is a promising cancer biomarker and drug Tissue microarrays (TMAs) target in NSCLC (4). Like other integrins, α3β1 integrin is a heterodimeric transmembrane glycoprotein receptor TMAs were prepared from 200 FFPE tissue blocks using without a cytoplasmic kinase domain, and binds to various an IRB approved protocol (IRB 293828, UC Davis Cancer ligands such as fibronectin, laminin, collagen, epiligrin, Center Biorepository) (Figure 1). Three 0.6 mm (diameter) thrombospondin and chondroitin sulfate proteoglycan by 0.4 mm (length) cylindrical cores of tumor and adjacent 4 (CSPG4) (5). α3β1 integrin mediates the adhesion, non-malignant (control) lung tissues were collected from cytoskeleton function, and metastasis of NSCLC via each case and placed in the same block (quick-ray manual cross-talk with EGFR and other receptor tyrosine kinase tissue microarrayer). Three cores of normal liver and kidney (RTK) (4,6-8). The integrin α3 (ITGA3) subunit binds to tissues were also included on the same block as normal the integrin β1 (ITGB1) subunit as its exclusive binding controls. One TMA section was stained with hematoxylin partner. α3β1 integrin is weakly detected in the basement and eosin (H&E) to visualize the presence of tumor and membranes of normal alveolar walls but is highly expressed normal lung tissue. The deidentified database for the TMAs in primary lung cancer cells (9,10) and tumor-derived has been annotated with patient demographics (age at exosomes (4,11). Overexpression of α3β1 integrin has been diagnosis, gender, race/ethnicity), stage, histopathology, and detected in multiple tumor types and is associated with survival outcomes. tumorigenesis, invasion, metastasis, as well as resistance to cancer treatment in several cancer types, including NSCLC IHC stain (4,12), breast cancer (13), cervical cancer (14), glioma (15), and other cancer type metastasis to the lung (16,17). Almost TMA slides were stained by IHC for ITGA3 integrin all these studies were done on preclinical models. Due to expression. 4-μm FFPE tissue sections were cut for each the poor sensitivity and specificity of early commercially TMA. Slides were deparaffinized and pretreated with Heat- available antibodies, limited study has been reported Induced-Epitope-Retrieval solution (pH 9) (DAKO). Slides on the clinical significance of ITGA3 expression using are preincubated in Dual Endogenous Enzyme Block archival formalin fixed, paraffin embedded (FFPE) patient (DEEB) blocking solution in a DAKO Autostainer Link48. samples (14). Furthermore, there are conflicting data on Primary antibody for ITGA3 (ab131055, dilution 1:200; the prognosis of ITGA3 expression in NSCLC (12,18). Abcam) were used for IHC. The slides were incubated We have recently generated and characterized LXY30, a for 30 minutes and then washed, which was followed by high affinity peptide ligand for targeting α3β1 integrin- detection by EDL solution (DAKO EnVision and Dual Link expressing, live tumor cells and tumor-derived exosomes System-HRP). Hematoxylin was used as the counterstain. in NSCLC, regardless of histology and tumor genotypes IHC slides were scored by two readers (QL and WM)

Lung cancer (N=200)

NSCLC SCLC (N=186) (N=14)

N=25 (Incomplete N=161 (Complete information) information)

LUAD (N=91)

LUSC (N=46)

Others (N=24)

Figure 1 Study flow chart. The distribution of lung cancer types of TMA is illustrated. TMA, tissue microarray. and verified by two pathologists (TW and CZ) blinded tumor characteristics to examine factors associated with to clinicopathologic information. Staining for ITGA3 expression (TPS >5%) versus no (TPS ≤5%) ITGA3 was semi-quantified and assessed using both intensity and expression levels. percentage of positive cells. Staining intensity was graded The Kaplan-Meier method and log-rank test were as 0= negative (no cells stained); 1= weak; 2= moderate; first used to compare survival outcomes between 3= strong. The percentage of positive cells was defined as different ITGA3 expression levels. Univariate survival 0 (0–5%), 1+ (6–20%), 2+ (21–50%), and 3+ (51–100%) analysis and multivariate analysis were performed with (Figure 2A). After the initial analysis, study pathologists Cox proportional hazards models using overall survival recommended to measure the ITGA3 expression by tumor (OS) as outcomes. Factors found to be significant in proportion score (TPS), i.e., the percentage of viable tumor univariate analysis were included and selected by backward cells showing partial or complete membrane staining at any method in multivariate analysis (except ITGA3 IHC intensity. The specimen was considered to have ITGA3 expression which was always included). To ensure the expression if TPS >5% and no ITGA3 expression if TPS proportional hazards assumption holds, the assumption ≤5%. was examined using Schoenfeld residuals. To account for potential confounding and covariate imbalances between different ITGA3 expression groups, we used Statistical analysis propensity score-weighted Kaplan-Meier estimator, All baseline demographics and patient characteristics were incorporating the inverse of the propensity score (20). compared between different ITGA3 expression level groups The propensity score was used to balance the covariate by Pearson chi-square tests except for age, which was distribution between groups for studies with either causal considered a continuous variable and therefore analyzed or non-causal purposes (21). For survival outcomes, this with Kruskal-Wallis test. Multivariate logistic regression method has been shown to produce less biased treatment with backward variable section was applied to patient and effect estimates than stratification or covariate adjustment

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1364 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

A ITGA3 IHC: B Prognosis: 100 TPS =0-5% (0) Intensity Score: 0 1+ 2+ 3+ TPS =6-20% (1) TPS: 0-5% 6-20% 21-50% 51-100% TPS =21-50% (2) 80 TPS =51-100% (3)

10× 60

Survival Percentage (%) Survival Percentage 20 P=0.014 40×

(Month) 0 ITGA3 score: 0 12 24 36 48 60 72 84

0 54 48 40 34 28 25 21 18

1 66 47 42 31 27 22 19 16

2 33 25 22 19 18 15 13 8

3 8 6 5 2 1 1 1 1

Figure 2 Atlas of ITGA3 expression by IHC. (A) Atlas of representative pictures of 0, 1, 2, and 3 IHC scores for ITGA3 expression in NSCLC TMAs. (B) Kaplan-Meier curves of overall survival were stratified by ITGA3 expression score (0, 1, 2, and 3). ITGA3, integrin α3; IHC, immunohistochemistry; NSCLC, non-small cell lung cancer; TMA, tissue microarray. based on the propensity score (22). Significant covariates for the individual patient barcodes matched to these FPKM in univariate and multivariate survival analyses were used values and was used to separate NSCLC subtypes into high in the propensity score model using logistic regression. and low expression groups, on which log-rank tests for We also performed subgroup analyses for different patient significant difference (P<0.05) were conducted. characteristics groups. As there was high proportion of unknown metastasis status (63% of all patients) in the Results database, and the above analyses created an additional level for patients with unknown metastasis status, we performed Patient characteristics additional sensitivity analyses using the multiple imputation Figure 1 illustrates the distribution of the 200 cases of lung method for unknown metastasis based on missing at random cancer on the TMA. Excluding those cases with small cell (MAR) assumption (23). All analyses were performed using lung cancer (SCLC) and NSCLC without complete clinical SAS 9.4 (SAS Institute Inc., Cary, NC, USA) and R 3.6.0 information, the expression of ITGA3 was analyzed in (R Foundation for Statistical Computing, Vienna, Austria). 161 cases. All the statistics for baseline demographics and All P values were two-sided, and a P≤0.05 was considered patient characteristics are summarized in Table 1. statistically significant.

High ITGA3 expression was associated with poor prognosis TCGA data access and analysis ITGA3 IHC expression was detected in 107/161 (66.5%) The transcriptome expression data from NSCLC of the NSCLC samples. Weak (1+), moderate (2+) and patients were accessed on September 9th, 2019 in The strong (3+) ITGA3 expression was detected in 66 (41.0%), Cancer Genome Atlas (TCGA) database (http://www. 33 (20.5%), and 8 (5.0%) cases, respectively (Figure 2A). cancergenome.nih.gov) including 500 lung adenocarcinoma Kaplan-Meier curves indicated that weak (1+) and strong (LUAD) and 494 lung squamous cell carcinoma (LUSC) (3+) ITGA3 expression was significantly associated with samples. Fragments per kilobase of exon per million reads poor OS in NSCLC patients (P<0.05) (Figure 2B). Overall, mapped (FPKM) values were chosen as the representative NSCLC patients whose tumors expressed ITGA3 by IHC measure of gene expression (24). Survival data was obtained (1+ to 3+) was associated with poorer prognosis compared

Table 1 Patient characteristics Multivariate survival analysis demonstrated that poor Characteristics N=161 Percentage (%) prognosis is associated with older age and metastasis

Age (mean ± SD; years old) 65.9±10 (Table 2). Propensity-score-weighted survival analysis demonstrated that the significance of association between Range (years old) 32–86 ITGA3 IHC expression (1+ to 3+) and prognosis is near Gender the edge (HR =1.30, 95% CI: 0.99–1.71, P=0.056) for all Female 94 58.3% NSCLC patients after adjusting for confounders (Table 3). Due to a high proportion of unknown metastasis, Male 67 41.6% sensitivity analyses using multiple imputation method for Race/ethnicity unknown metastasis were performed and demonstrated NHW 121 75.2% that ITGA3 IHC expression (1+ to 3+) was significantly Black 7 4.3% associated with poor prognosis (HR =1.67, 95% CI: 1.05– 2.64, P=0.029) for all NSCLC patients after adjusting for Asian 4 2.5% confounders and imputing for unknown metastasis (Table 4). Other 29 18%

Smoking history ITGA3 expression in histology subgroups of NSCLC Smoker 100 62.1% We found the median score of ITGA3 IHC was not Never smoker 61 37.9% significantly higher in LUAD than LUSC (P=0.44) Histology type (Figure 4A), and high ITGA3 IHC score was associated LUAD 91 56.5% with a statistically significant difference in LUSC LUSC 46 28.6% (P<0.05) (Figure 4B) but not LUAD (P=0.16) (Figure 4C). Representative ITGA3 IHC stains on LUAC and LUSC Others 24 14.9% are showed (Figure 4D). After adjusting for confounders, Grade propensity-score-weighted survival analysis demonstrated I 33 20.5% that the association of ITGA3 IHC expression (weak to

II 43 26.7% strong) and poor prognosis was statistically significant in LUSC patients (HR =1.76, 95% CI: 1.10–2.81, P=0.018) III 51 31.7% but not in LUAD patients (P=0.13). Not known 34 21.11% LUAD, lung adenocarcinoma; LUSC, lung squamous cell Poor prognosis was associated with tumor metastasis carcinoma. We found that ITGA3 expression was significantly higher in the NSCLC tumors from patients with metastatic tumors to those patients whose tumors did not express ITGA3 (N=19) compared to those patients without metastatic (Figure 3A). We also performed propensity-score-weighted tumors (N=41). Due to a high proportion of unknown survival analyses between different ITGA3 expression metastasis status (63% of all patients) in the database, the levels for different patient characteristics groups. We found wide confidence interval of HR for metastasis was observed, that association between ITGA3 IHC expression (weak to although the association is still significant. We performed strong) and poor prognosis is significant in subgroups of additional sensitivity analysis using multiple imputation female patients (HR =1.49, 95% CI: 1.02–2.18, P=0.04) method for unknown metastasis, and the significance of (Figure 3B), smokers (HR =1.77, 95% CI: 1.21–2.57, metastasis on poor prognosis was confirmed by sensitive P=0.003) (Figure 3C) and differentiation grade I & II analysis (HR =2.89, 95% CI: 1.48–5.65, P=0.003) (Table 3). (HR =2.07, 95% CI: 1.39–3.08, P<0.001) (Figure 3D), but not in male patients (P=0.50), non-smokers (P=0.22), ITGA3 expression was associated with no smoking history differentiation grade III (P=0.66) (Table 2). Sensitivity analyses using multiple imputation demonstrated similar Multivariate logistic regression with backward variable conclusions for these subgroups. section was applied to patient and tumor characteristics

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1366 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

Female ITGA3 negative A ITGA3 negative B ITGA3 positive 100 ITGA3 positive 100

HR=1.49

HR=1.67 (95% CI, 1.02-2.18) (95% CI: 1.05-2.64) P=0.04 50 P=0.029 50 Percent survival Percent Survival percentage (%) Survival percentage (Month) 0 0 (Month) 0 12 24 36 48 60 72 84 96 108 120 132 144 156 168 180 192 204 216 0 24 48 72 96 120 144 168 192 216

ITGA3-: 54 49 40 34 29 26 22 19 16 9 7 5 5 4 3 3 3 2 1 ITGA3-: 31 27 20 16 12 5 3 2 2 1

ITGA3+: 107 78 68 51 46 37 34 25 18 12 11 11 11 9 6 3 3 2 1 ITGA3+: 62 43 31 21 12 9 9 5 3 1

Patients with smoking history Grade I & II histology C D 100 100

HR=1.77 HR=2.07 (95% CI, 1.21-2.57) (95% CI, 1.39-3.08) P=0.003 P<0.001 50 50 Percent survival Percent survival Percent

0 (Month) 0 (Month) 0 24 48 72 96 120 144 168 192 216 0 24 48 72 96 120 144 168 192 216

ITGA3-: 42 38 24 20 15 7 5 3 3 1 ITGA3-: 15 14 11 9 6 3 1 1

ITGA3+: 58 41 24 17 11 8 7 4 2 1 ITGA3+: 18 14 10 5 3 3 2 1

Figure 3 High level integrin α3 expression was associated with poor prognosis in NSCLC patients. Kaplan-Meier curves of overall survival were stratified by ITGA3 expression (negative vs. positive) (A), female (B), patients with smoking history (C), and grade I histology (D). ITGA3, integrin α3; NSCLC, non-small cell lung cancer. to examine factors associated with expression (TPS >5%) found that the median RNA expression level of ITGA3 was versus no (TPS ≤5%) ITGA3 expression levels (Table 4). We significantly higher in LUAD than LUSC (43.80 vs. 17.40, found ITGA3 expression was associated with no smoking P<0.0001) (Figure 5A). Similar to our finding in IHC, high history (OR =2.96, 95% CI: 1.40–6.23, P=0.004), but not ITGA3 RNA expression was associated with a statistically significantly associated with other factors. significant poor prognosis in LUSC (P<0.05) (Figure 5B). Using a higher cutoff than LUSC (70.6 vs. 19.5 FPKM), high ITGA3 RNA expression was also associated with High α3 integrin expression by transcriptome sequencing poor prognosis in LUAD (P=0.023) (Figure 5C). ITGA3 was associated with poor prognosis in patients with NSCLC shared many interactive genes mediating cell adhesion and We also validated our findings in an independent cohort motility in both LUSC and LUAD (Figure 6A,B, Table 5), of NSCLC tumors. We analyzed the RNA expression of respectively. Furthermore, ITGA3 interacted with many ITGA3 gene in 494 LUSC and 500 LUAD samples using key genes regulating epithelial to mesenchymal transition, the transcriptome expression data in TCGA database. We angiogenesis, invasion and metastasis in both LUAD and

Table 2 Univariate, multivariate, and propensity score-weighted survival analysis for overall survival using Cox proportional hazards models Univariate Multivariate Factors HR 95% CI P value Adjusted HR 95% CI P value

ITGA3 IHC score

TPS ≤5% 1.00 1.00

TPS >5% 1.68 1.09–2.57 0.018 1.39 0.90–2.14 0.137

Age (in year) 1.03 1.01–1.05 0.003 1.03 1.01–1.05 0.009

Sex

Male 1.00

Female 0.65 0.44–0.95 0.027

Race

Non-white 1.00

White 1.96 1.27–3.02 0.003

Smoke

No 1.00

Yes 0.67 0.46–0.99 0.042

COPD

No 1.00

Yes 0.71 0.46–1.09 0.116

Histology

LUAD 1.00

LUSC 1.16 0.76–1.76 0.502

Other/unknown 0.70 0.38–1.29 0.256

Differentiation grade

Well (I) 1.00

Moderate (II) 1.66 0.91–3.02 0.098

Poor (III) 1.67 0.90–3.09 0.105

Unknown 1.25 0.64–2.41 0.514

Metastasis

No 1.00 1.00

Yes 60.95 8.01–463.74 <0.001 58.8 7.74–447.01 <0.001

Unknown 78.40 10.85–566.76 <0.001 73.3 10.15–529.46 <0.001

ITGA3 IHC score*

All

TPS ≤5% 1.00

TPS >5% 1.30 0.99 –1.71 0.056

Table 2 (continued)

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1368 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

Table 2 (continued) Univariate Multivariate Factors HR 95% CI P value Adjusted HR 95% CI P value

Subset analysis of smokers

TPS ≤5% 1.00

TPS >5% 1.77 1.21–2.57 0.003

Subset analysis of non-smokers

TPS ≤5% 1.00

TPS >5% 0.78 0.52–1.17 0.223

Subset analysis of LUSC

TPS ≤5% 1.00

TPS >5% 1.76 1.10–2.81 0.018

Subset analysis of LUAD

TPS ≤5% 1.00

TPS >5% 1.34 0.91–1.95 0.134

Subset analysis of Female

TPS ≤5% 1.00

TPS >5% 1.49 1.02–2.18 0.040

Subset analysis of LUSC

TPS ≤5% 1.00

TPS >5% 1.14 0.78–1.68 0.501

Subset analysis of differentiation grade I&II

TPS ≤5% 1.00

TPS >5% 2.07 1.39–3.08 <0.001

Subset analysis of differentiation grade III

TPS ≤5% 1.00

TPS >5% 1.12 0.69–1.81 0.656 Variables significant in univariate analyses were included in multivariate analysis and further selected by backward method. *, data are collected by propensity score-weighted survival analysis. ITGA3, integrin α3; IHC, immunohistochemistry; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

LUSC as illustrated in Figure 7. on tumor cells mediating metastasis and treatment resistance (6). Using a novel peptide ligand LXY30 that has higher affinity and longer half-life than natural integrin Discussion (4,19), we recently showed that ITGA3 was expressed in α3β1 integrin is a promising biomarker for lung cancer about 90% of live tumor cells and exosomes isolated from detection and a potential drug target, being one of the patients with metastatic NSCLC (4). However, LXY30 does most commonly expressed integrin subtypes found not work in FFPE specimens. We have screened several

Table 3 Sensitivity analyses with multivariate survival analysis for Table 4 Association between covariates and positive (TPS >5%) vs. overall survival using Cox proportional hazards models negative (TPS ≤5%) ITGA3 expression levels in NSCLC patients Multivariate analysis HR 95% CI P value Smoking history Odds ratio (95% CI) P value

IHC score of ITGA3 Yes 1.00

TPS ≤5% (negative) 1.00 No 2.96 (1.40–6.23) 0.004

TPS >5% (positive) 1.67 1.05–2.64 0.029 Multivariate logistic regression was applied to model the event of high ITGA3 expression, and variables were selected by Age (in year) 1.03 1.00–1.06 0.014 backward method. ITGA3, integrin α3; NSCLC, non-small cell Metastasis (N=60) lung cancer.

No (N=41) 1.00

Yes (N=19) 2.89 1.48–5.65 0.003 Multiple imputation method was used for unknown metastasis based on missing at random (MAR) assumption. ITGA3, integrin α3; IHC, immunohistochemistry.

A B LUSC C LUAD

4.0 100 P=0.44 ITGA3 negative ITGA3 negative 3.5 ITGA3 positive 100 ITGA3 positive

3.0 mOS (mos): 67.0 vs. 22.0 mOS (mos): 76.0 vs. 55.0 2.5 Logrank HR=0.44 Logrank HR=0.67 (95% CI, 0.23-0.89) (95% CI, 0.40-1.16) 2.0 50 P<0.05 P=0.16 50 1.5 IHC scores

1.0 survival Percent survival Percent

0.5

0.0 LUSC LUAD 0 0 0 12 24 36 48 60 72 84 96 108 120 0 12 24 36 48 60 72 84 96 108 120 132 (N=46) (N=91) ITGA3-: 18 15 13 10 10 9 7 6 5 3 1 ITGA3-: 28 26 21 18 14 13 11 8 7 3 3 2

ITGA3+: 28 15 11 10 9 8 8 7 5 3 1 ITGA3+: 61 51 45 33 28 21 16 10 7 4 4 4

Intensity Score: 0 1+ 2+ 3+ D TPS: 0-5% 6-20% 21-50% 51-100%

LUAD

LUSC

Figure 4 ITGA3 expression by histology subtypes. (A) The median ITGA3 expression was higher in LUAD than LUSC. Kaplan- Meier curves of overall survival were stratified by ITGA3 expression (negative vs. positive) in LUSC (B) and LUAD (C), respectively. (D) Representative ITGA3 IHC stains on LUAC and LUSC (×10). ITGA3, integrin α3; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1370 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

A B LUSC C LUAD LUSC LUAD 100 300 P<0.0001 100 ITGA3 low expression (N=272) ITGA3 low expression (N=361) ITGA3 high expression (N=222) ITGA3 high expression (N=139)

200 Cut off: 19.5 Cut off: 70.6 P value: 0.00017 P value: 0.023 50 50 FPKM Level 100 Survival percentage Survival percentage (%) Survival percentage

0 LUSC LUAD 0 0 (N=494) (N=500) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Time after diagnosis (Year) Time after diagnosis (Year)

Figure 5 ITGA3 expression by RNA in LUSC and LUAD in TCGA RNA seq database. The transcriptome expression data from lung cancer patients were analyzed in TCGA database (http://www.cancergenome.nih.gov) including 499 LUSC and 500 LUAD samples. (A) The median RNA expression of ITGA3 was significantly higher in LUAD than LUSC. Kaplan-Meier curves of overall survival were stratified by ITGA3 RNA expression (low vs. high at different cutoffs) in LUSC (B) and LUAD (C), respectively. ITGA3, integrin α3; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

A LUSC B LUAD

Figure 6 Interactive networks of ITGA3 expression in TCGA RNA sequencing databases. Interactive networks of ITGA3 expression in LUSC (A) and LUAD (B). The gene names and functions are summarized in Table 5. ITGA3, integrin α3; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma. commercially available anti-ITGA3 antibodies and selected ITGA3 IHC expression in our study as weak (1+), moderate the Abcam ab131055 antibody in this study. We found that (2+) and strong (3+), which were detected in 66 (41.0%), ITGA3 was expressed in the majority (66.5%) of NSCLC 33 (20.5%), and 8 (5.0%) cases, respectively (Figure 2). specimens by IHC (Figure 2). We further categorized the The frequencies and patterns of ITGA3 expression in our

Table 5 Summary of key genes interacted with ITGA3 in the TCGA transcriptome databases Gene ID Interactive networks Function LUSC LUAD

ACTB Actin beta Cell motility, structure and integrity Yes Yes

ACTBL2 Actin beta like 2 Cytoskeletal protein; cell motility, structure and integrity Yes

ACTG1 Actin gamma 1 Actin protein family; cytoskeleton Yes Yes

ACTN2 Actinin alpha 2 Cytoskeletal protein Yes

ACTN4 Actinin alpha 4 Cytoskeletal protein; cell motility, structure and integrity Yes Yes

ARF6 ADP ribosylation factor 6 Vesicular trafficking; activators of phospholipase D Yes Yes

CAV1 Caveolin-1 Integrin signaling Yes

COL10A1 Collagen, type 10, alpha 1 Collagens family; Strengthen and support tissues Yes

COL11A1 Collagen, type 11, alpha 1 Collagens family; Strengthen and support tissues Yes Yes

COL12A1 Collagen, type 12, alpha 1 Collagens family; Strengthen and support tissues Yes

COL13A1 Collagen, type 13, alpha 1 Collagens family; Strengthen and support tissues Yes

COL14A1 Collagen, type 14, alpha 1 Collagens family; Strengthen and support tissues Yes

COL15A1 Collagen, type 15, alpha 1 Collagens family; Strengthen and support tissues Yes Yes

COL1A1 Collagen, type 1, alpha 1 Collagens family; Strengthen and support tissues Yes

COL1A2 Collagen, type 1, alpha 2 Collagens family; Strengthen and support tissues Yes

COL3A1 Collagen, type 3, alpha 1 Collagens family; Strengthen and support tissues Yes

COL4A4 Collagen, type 4, alpha 4 Collagens family; Strengthen and support tissues Yes Yes

COL4A5 Collagen, type 4, alpha 5 Collagens family; Strengthen and support tissues Yes

COL4A6 Collagen, type 4, alpha 6 Collagens family; Strengthen and support tissues Yes

COL5A1 Collagen, type 5, alpha 1 Collagens family; Strengthen and support tissues Yes

COL5A2 Collagen, type 5, alpha 2 Collagens family; Strengthen and support tissues Yes Yes

COL5A3 Collagen, type 5, alpha 3 Collagens family; Strengthen and support tissues Yes

COL6A1 Collagen, type 6, alpha 1 Collagens family; Strengthen and support tissues Yes

COL6A2 Collagen, type 6, alpha 2 Collagens family; Strengthen and support tissues Yes

COL8A1 Collagen, type 8, alpha 1 Collagens family; Strengthen and support tissues Yes

COL8A2 Collagen, type 8, alpha 2 Collagens family; Strengthen and support tissues Yes

COL9A2 Collagen, type 9, alpha 2 Collagens family; Strengthen and support tissues Yes

DAB1 DAB adaptor protein 1 Regulator of reelin signaling; brain development Yes

EGFR Epidermal growth factor receptor Cell migration, adhesion and proliferation Yes Yes

FLNA Filamin A, alpha Cytoskeletal protein; cell motility, structure and integrity Yes Yes

FYN FYN proto-oncogene Integrins signaling pathway; activates Ras Yes

IGTAL Integrin, alpha L Integrin family; Mediate cell-matrix or cell-cell adhesion Yes

ILK Integrin-linked kinase Integrin-mediated signal transduction Yes Yes

ITGA2B Integrin alpha-Iib Integrin family; Mediate cell-matrix or cell-cell adhesion Yes

ITGAD Integrin, alpha D Integrin family; Mediate cell-matrix or cell-cell adhesion Yes

Table 5 (continued)

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1372 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

Table 5 (continued) Gene ID Interactive networks Function LUSC LUAD

ITGAE Integrin, alpha E Integrin family; Mediate cell-matrix or cell-cell adhesion Yes Yes

ITGB4 Integrin subunit beta 4 Integrin family; Mediate cell-matrix or cell-cell adhesion Yes Yes

ITGB5 Integrin subunit beta 5 Integrin family; Mediate cell-matrix or cell-cell adhesion Yes

ITGB6 Integrin subunit beta 6 Integrin family; Mediate cell-matrix or cell-cell adhesion Yes Yes

ITGB7 Integrin subunit beta 7 Integrin family; Mediate cell-matrix or cell-cell adhesion Yes Yes

ITGB8 Integrin subunit beta 8 Integrin family; Mediate cell-matrix or cell-cell adhesion Yes Yes

ITGBL1 Integrin subunit beta like 1 Integrin family; Mediate cell-matrix or cell-cell adhesion Yes

JAK2 Janus kinase 2 Cell growth and division; hematopoietic cells development Yes

LAMB4 Laminin subunit beta 4 mediate cell attachment and migration Yes

LIMS1 LIM zinc finger domain containing 1 Integrin signaling Yes

LRP8 Low-density lipoprotein receptor-related Low-density lipoprotein receptor family Yes Yes protein 8

NID1 Nidogen-1 Basement membrane glycoprotein Yes

PARVA Alpha-parvin Actin-binding proteins Yes

PLAU Plasminogen activator Converts plasminogen to plasmin Yes

PLAU Plasminogen activator, urokinase Converts plasminogen to plasmin Yes

PLAUR Plasminogen activator, urokinase Receptor for urokinase plasminogen activator Yes receptor

PTK2 Protein tyrosine kinase 2 Cellular adhesion and cell growth Yes Yes

PTPN2 Protein tyrosine phosphatase non- Cell growth, differentiation; catalytic activity Yes Yes receptor type 2

PXN Paxillin Adhere cells to the extracellular matrix Yes

TLN1 Talin-1 Cytoskeletal protein Yes Yes

TP63 Tumor protein P63 Transcription factor; cell growth and early development Yes

TYK2 Tyrosine kinase 2 Non-receptor tyrosine kinase; cytokine signaling Yes Yes

VCL Vinculin Cytoskeletal protein; adhesion formation and maturation Yes Yes

VEGFA Vascular endothelial growth factor A Proliferation and migration of vascular endothelial cells; Yes angiogenesis

VLDLR Very low-density lipoprotein (VLDL) Lipoprotein receptor Yes Yes receptor ITGA3, integrin α3; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

study are within the range of two different antibodies in expression (1+ to 3+) and prognosis is near the edge (HR the Human Protein Atlas (https://www.proteinatlas.org) =1.30, 95% CI: 0.99–1.71, P=0.056) after adjusting for (Table 6). These data further support our effort in targeting confounders. However, propensity-score-weighted survival ITGA3 using LXY30 in patients with live NSCLC. analysis demonstrated that the association of ITGA3 Propensity-score-weighted survival analysis demonstrated IHC expression and poor prognosis was not statistically that the significance of association between ITGA3 IHC significant in either LUSC patients (P=0.11) or LUAD

ITGA3 vs. EGFR

A B 90k 25k LUAD (N=566) LUSC (N=466) Spearman: 0.31 (p=1.54e-12) 80k Spearman: 0.26 (p=1.42e-8) Pearson: 0.22 (p=4.63e-7) Pearson: 0.16 (p=3.87e-4) 20k 70k 60k 15k ITGA3 mutated 50k ITGA3 mutated

EGFR mutated 40k EGFR mutated 10k Neither mutated 30k Neither mutated

20k 5k 10k mRNA Expression of EGFR (RSEM) mRNA Expression of EGFR (RSEM) mRNA Expression

0 0

−10000 −10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM) C ITGA3 vs. VEGFA D 30k LUAD (N=566) 35k LUSC (N=466) Spearman: 0.24 (p=4.77e-8) Spearman: 0.17 (p=2.51e-4) 25k Pearson: 0.31 (p=9.69e-13) Pearson: 0.18 (p=1.23e-4) 30k ITGA3 mutated ITGA3 mutated 20k VEGFA mutated 25k VEGFA mutated

Neither mutated 20k Neither mutated 15k

15k 10k 10k

5k 5k mRNA Expression of VEGFA (RSEM) of VEGFA mRNA Expression (RSEM) of VEGFA mRNA Expression

0 0

−10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM) E ITGA3 vs. MET F 70k LUSC (N=466) LUAD (N=566) Spearman: 0.35 (p=3.15e-15) 100k Spearman: 0.47 (p=4.19e-29) 60k Pearson: 0.31 (p=1.15e-11) Pearson: 0.32 (p=2.59e-13)

80k 50k ITGA3 mutated ITGA3 mutated

MET mutated 40k MET mutated 60k Neither mutated 30k Neither mutated 40k 20k

20k 10k mRNA Expression of MET (RSEM) mRNA Expression mRNA Expression of MET (RSEM) mRNA Expression 0 0

−10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM)

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1374 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

ITGA3 vs. VIM

G H 90k LUAD (N=566) LUSC (N=466) 140k Spearman: 0.26 (p=1.89e-9) 80k Spearman: 0.28 (p=7.76e-10) Pearson: 0.17 (p=8.96e-5) Pearson: 0.15 (p=1.22e-3) 120k 70k ITGA3 mutated ITGA3 mutated

100k 60k VIM mutated VIM mutated 50k Neither mutated 80k Both mutated Neither mutated 40k 60k 30k 40k 20k

20k 10k mRNA Expression of VIM (RSEM) mRNA Expression mRNA Expression of VIM (RSEM) mRNA Expression 0 0

−10000 −10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM)

I ITGA3 vs. FGF1 J 1.2k LUAD (N=566) 1k Spearman: 0.11 (p=0.0175) LUSC (N=466) Pearson: 0.01 (p=0.854) Spearman: 0.22 (p=9.57e-7) 1k Pearson: −0.01 (p=0.780) 800

800 ITGA3 mutated ITGA3 mutated 600 FGF1 mutated FGF1 mutated 600 Neither mutated Neither mutated 400 400

200 200 mRNA Expression of FGF1 (RSEM) mRNA Expression mRNA Expression of FGF1 (RSEM) mRNA Expression 0 0

−10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM) K ITGA3 vs. SNAI2 L 8k LUSC (N=466) LUAD (N=566) 5k Spearman: 0.22 (p=1.20e-6) Spearman: 0.16 (p=3.42e-4) Pearson: 0.17 (p=1.77e-4) 7k Pearson: 0.15 (p=7.43e-4)

4k ITGA3 6k ITGA3 mutated mutated SNAI2 5k SNAI2 mutated mutated 3k Neither Both mutated 4k mutated Neither mutated 2k 3k

2k 1k mRNA Expression of SNAI2 (RSEM) mRNA Expression 1k of SNAI2 (RSEM) mRNA Expression 0

−1000 −10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM)

M ITGA3 vs. MMP1 N 160k LUSC (N=466) LUAD (N=566) Spearman: 0.39 (p=1.54e-18) Spearman: 0.15 (p=1.03e-3) 140k Pearson: 0.22 (p=9.61e-7) Pearson: 0.05 (p=0.307) 120k

120k 100k 100k ITGA3 mutated ITGA3 mutated 80k MMP1 mutated MMP1 mutated 80k Neither mutated Neither mutated 60k 60k 40k 40k

20k 20k mRNA Expression of MMP1 (RSEM) mRNA Expression mRNA Expression ofMMP1 (RSEM) mRNA Expression 0 0

−10000 −10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM)

O ITGA3 vs. TGFB1 P

LUAD (N=566) 9k LUSC (N=466) Spearman: 0.35 (p=9.07e-16) Spearman: 0.52 (p=2.40e-34) 7k Pearson: 0.25 (p=8.82e-9) 8k Pearson: 0.49 (p=5.25e-30) 6k ITGA3 mutated 7k ITGA3 mutated

5k TGFB1 mutated 6k TGFB1 mutated

Neither mutated Neither mutated 4k 5k 4k 3k 3k 2k 2k 1k 1k mRNA Expression of TGFB1 (RSEM) mRNA Expression

mRNA Expression of TGFB1 (RSEM) mRNA Expression 0 0

−1000 −10000 0 10k 20k 30k 40k 50k 60k 70k 80k 0 10k 20k 30k 40k 50k 60k 70k mRNA Expression of ITGA3 (RSEM) mRNA Expression of ITGA3 (RSEM)

Figure 7 ITGA3 regulates malignant behaviors in LUSC and LUAD. Summary of selected key genes mediating EMT, angiogenesis, invasion and metastasis that had significant interaction with ITGA3 in TCGA RNA sequencing database. https://www.cbioportal.org/; last data access on 5/7/2020. ITGA3, integrin α3; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma.

patients (P=0.07). Thus, histology alone should not be used associated with non-smoking history in both univariate and to select NSCLC for ITGA3 expression. multivariate analyses. The expression of specific integrin subtypes has been The TCGA datasets are publicly accessible resources linked to organotropic metastasis of circulating tumor cells containing sequencing data of human tumors and normal and exosomes in epithelial tumors (11,12,17). ITGA3 and tissues using NGS and other clinically relevant modern β1 subunits were detected in 13 (54%) and 24 (100%) of genomic technologies. Since its conception, TCGA datasets exosomes isolated from 24 human metastatic cell lines, have been proven invaluable tools to cancer research while the normal tissues or PBMCs did not express any community to study the role of specific genes and genomic integrin (4). Although there are a significant number of changes in the biology and prognosis of specific cancer patients with an unknown metastasis status, we found types (https://cancergenome.nih.gov). Using the TCGA that ITGA3 IHC expression was only significantly RNASeq dataset, we found a similar pattern of high ITGA3

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 1376 Li et al. High ITGA3 expression predicts poor prognosis in NSCLC

Table 6 Comparison of integrin α3 IHC expression in NSCLC with published datasets Antibody name Marker Host species Positive stain rate Intensity No. cases Percentage

HPA008572 (the human protein atlas) Sigma Aldrich Rabbit 92% Strong 4 33%

Moderate 6 50%

Weak 1 8%

Negative 1 8%

CAB018594 (the human protein atlas) Santa Cruz Mouse 41% Strong 1 8% biotech Moderate 3 25%

Weak 1 8%

Negative 5 42%

AB131055 (current study) abCAM Rabbit 67% Strong 8 5%

Moderate 32 20%

Weak 66 41%

Negative 54 34% ITGA3, integrin α3; IHC, immunohistochemistry; NSCLC, non-small cell lung cancer. expression in LUAD compared to LUSC. The interactive Our study has several limitations. First, we could not networking analysis showed that LUAD and LUSC shared explain the impact of sex, histology and smoking status many cell adhesion and motility genes while distinct on ITGA3 expression. Second, there were no molecular genes interaction was also noted for LUAD and LUSC, and immune biomarker data (such as PD-L1 IHC, tumor respectively (Figure 6). Similar to our recent report, ITGA3 mutation burden) of tumors available for this dataset, interacts with EGFR in LUAD (4). Furthermore, TP63 and which included NSCLC specimens from before the era PTK2 (FAK) modulates the ITGA3 expression in LUSC, of precision oncology. We plan to study the association of which warrant further validation. ITGA3 expression with molecular and immune biomarkers Our study has several translational potentials. First, we in future studies. have recently shown that a novel, potent peptide LXY30 In conclusion, we have shown that the expression of has high affinity for binding to α3β1 integrin, which can ITGA3 subunit in patients with NSCLC is associated with increase the sensitivity of cancer detection, molecular poor prognosis and tumor metastasis. Further research is diagnosis and in vivo targeted delivery of imaging dye and warranted for targeting α3β1 integrin in NSCLC. cancer drugs in α3β1 integrin-expression NSCLC (4). The ITGA3 IHC can be used to identify candidate NSCLC Acknowledgments patients using archived FFPE tissue specimens for targeted therapy although the caution should be excised to select the The authors would like to thank Dr. Regina Gandour primary antibody for ITGA3. Second, we have confirmed Edwards and Irmgard Feldman at the UC Davis Cancer that ITGA3 expression is associated with metastasis of Center Biorepository for the acquisition of the lung cancer NSCLC tumors. Analysis of TCGA databases showing tissue microarray. that ITGA3 significantly interacted with many key genes Funding: This research was supported by the University of regulating cell adhesion, motility, epithelial to mesenchymal California Cancer Research Coordinating Committee grant transition, angiogenesis, invasion and metastasis in both (3-444964-34912) and Personalized Cancer Therapy Gift LUAD and LUSC (Table 5 and Figure 7). Further study is Fund (TL), the Biostatistics Shared Resource funded by the warranted to delineate the mechanism by which ITGA3 UC Davis Comprehensive Cancer Center Support Grant may mediate these malignant processes, and to develop (CCSG) awarded by the National Cancer Institute (NCI therapeutic strategies for NSCLC patients. P30CA093373) (SC). QL was also supported by a research

© Translational Lung Cancer Research. All rights reserved. Transl Lung Cancer Res 2020;9(4):1361-1378 | http://dx.doi.org/10.21037/tlcr-19-633 Translational Lung Cancer Research, Vol 9, No 4 August 2020 1377 and training scholarship from Shanghai Jiaotong University 4. Xiao W, Ma W, Wei S, et al. High-affinity peptide ligand Affiliated Sixth People’s Hospital. LXY30 for targeting alpha3beta1 integrin in non-small cell lung cancer. J Hematol Oncol 2019;12:56. 5. Millard M, Odde S, Neamati N. Integrin targeted Footnote therapeutics. Theranostics 2011;1:154-88. Data Sharing Statement: Available at http://dx.doi. 6. Desgrosellier JS, Cheresh DA. Integrins in cancer: org/10.21037/tlcr-19-633 biological implications and therapeutic opportunities. Nat Rev Cancer 2010;10:9-22. Peer Review File: Available at http://dx.doi.org/10.21037/ 7. Legate KR, Wickstrom SA, Fassler R. Genetic and cell tlcr-19-633 biological analysis of integrin outside-in signaling. Genes Dev 2009;23:397-418. Conflicts of Interest: All authors have completed the ICMJE 8. Morse EM, Brahme NN, Calderwood DA. Integrin uniform disclosure form (available at http://dx.doi. cytoplasmic tail interactions. Biochemistry 2014;53:810-20. org/10.21037/tlcr-19-633). The authors have no conflicts of 9. Bartolazzi A, Cerboni C, Flamini G, et al. Expression of interest to declare. alpha 3 beta 1 integrin receptor and its ligands in human lung tumors. Int J Cancer 1995;64:248-52. Ethical Statement: The authors are accountable for all 10. Guo L, Zhang F, Cai Y, et al. Expression profiling aspects of the work in ensuring that questions related of integrins in lung cancer cells. Pathol Res Pract to the accuracy or integrity of any part of the work are 2009;205:847-53. appropriately investigated and resolved. The study was 11. Hoshino A, Costa-Silva B, Shen TL, et al. Tumour approved by the institutional review board (IRB) at the exosome integrins determine organotropic metastasis. University of California, Davis (Protocol No. 226210) and Nature 2015;527:329-35. conducted in accordance with the Declaration of Helsinki (as 12. Yoshimasu T, Sakurai T, Oura S, et al. Increased expression revised in 2013). of integrin alpha3beta1 in highly brain metastatic subclone of a human non-small cell lung cancer cell line. Cancer Sci Open Access Statement: This is an Open Access article 2004;95:142-8. distributed in accordance with the Creative Commons 13. Shirakihara T, Kawasaki T, Fukagawa A, et al. Attribution-NonCommercial-NoDerivs 4.0 International Identification of integrin alpha3 as a molecular marker of License (CC BY-NC-ND 4.0), which permits the non- cells undergoing epithelial-mesenchymal transition and commercial replication and distribution of the article with of cancer cells with aggressive phenotypes. Cancer Sci the strict proviso that no changes or edits are made and the 2013;104:1189-97. original work is properly cited (including links to both the 14. Du Q, Wang W, Liu T, et al. High Expression of Integrin formal publication through the relevant DOI and the license). alpha3 Predicts Poor Prognosis and Promotes Tumor See: https://creativecommons.org/licenses/by-nc-nd/4.0/. Metastasis and Angiogenesis by Activating the c-Src/ Extracellular Signal-Regulated Protein Kinase/Focal Adhesion Kinase Signaling Pathway in Cervical Cancer. References Front Oncol 2020;10:36. 1. DeSantis CE, Miller KD, Goding Sauer A, et al. Cancer 15. Nakada M, Nambu E, Furuyama N, et al. Integrin alpha3 statistics for African Americans, 2019. CA Cancer J Clin is overexpressed in glioma stem-like cells and promotes 2019;69:211-33. invasion. Br J Cancer 2013;108:2516-24. 2. Li T, Kung HJ, Mack PC, et al. Genotyping and 16. Morini M, Mottolese M, Ferrari N, et al. The alpha 3 genomic profiling of non-small-cell lung cancer: beta 1 integrin is associated with mammary carcinoma cell implications for current and future therapies. J Clin metastasis, invasion, and gelatinase B (MMP-9) activity. Oncol 2013;31:1039-49. Int J Cancer 2000;87:336-42. 3. Postmus PE, Kerr KM, Oudkerk M, et al. Early and locally 17. Zhou B, Gibson-Corley KN, Herndon ME, et al. Integrin advanced non-small-cell lung cancer (NSCLC): ESMO alpha3beta1 can function to promote spontaneous Clinical Practice Guidelines for diagnosis, treatment and metastasis and lung colonization of invasive breast follow-up. Ann Oncol 2017;28:iv1-21. carcinoma. Mol Cancer Res 2014;12:143-54.

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Cite this article as: Li Q, Ma W, Chen S, Tian EC, Wei S, Fan RR, Wang T, Zhou C, Li T. High integrin α3 expression is associated with poor prognosis in patients with non-small cell lung cancer. Transl Lung Cancer Res 2020;9(4):1361-1378. doi: 10.21037/tlcr-19-633