AKIP1 expression in tumor tissue as a new biomarker for disease monitoring and prognosis in non-small cell lung cancer: Results of a retrospective study.

BACKGROUND: A-kinase-interacting protein 1 (AKIP1) has been reported as an oncogenetic factor in multiple cancers; however, no study has reported its role in non-small cell lung cancer (NSCLC) yet. This study aimed to evaluate the expression of AKIP1, and its correlation with tumor characteristics as well as prognosis in patients with NSCLC.
METHODS: Four hundred and ninety patients with NSCLC who underwent resection were reviewed, and baseline clinical data were collected. AKIP1 expression in tumor tissue/paired adjacent tissue was detected by immunohistochemistry. Disease-free survival (DFS) and overall survival (OS) were calculated.
RESULTS: A-kinase-interacting protein 1 expression was elevated in tumor tissue compared with paired adjacent tissue (P < .001), and high AKIP1 tumor tissue expression was correlated with poor pathological differentiation (P < .001), tumor size >5 cm (P = .001), lymph node metastasis (P = .016), higher TNM stages (P < .001), and abnormal CEA level (>5 ng/mL) (P = .035). DFS was worse in patients with tumor tissue AKIP1 high expression compared with patients who had AKIP1 low expression in total patients (P < .001), TNM stage I (P < .001) and TNM stage III (P < .001) patients. And the OS was also decreased in patients with AKIP1 high expression in total patients (P < .001), TNM stage I patients (P = .001) and TNM stage III patients (P = .004). Moreover, multivariate Cox's proportional hazards regression model analysis revealed that AKIP1 high expression was an independent predictive factor for worse DFS (P < .001) and OS (P < .001).
CONCLUSION: Tumor tissue AKIP1 expression may have the potential to be a biomarker assisting in disease monitoring and prognosis in NSCLC.

INTRODUCTION

Lung cancer is the most frequent cancer and the leading cause of cancer‐related deaths worldwide according to the latest cancer epidemiology report in 2018, and China is one of the countries with highest lung cancer incidence of 40/100, 000 per year.1 Non‐small cell lung cancer (NSCLC), the most common pathological type of lung cancer, presents with poor prognosis despite the expeditious development of target therapy, which is largely due to that most patients were diagnosed at an advanced stage.2, 3, 4, 5 With respect to the treatment of NSCLC, thanks to the discovery of several genetic variations in patients with NSCLC, clinical outcomes of patients have been largely improved due to the existence of target therapies.6 However, targeted therapies are unable to benefit the whole NSCLC patients; therefore, result in heterogenous treatment responses and rather frequent drug resistance, which indicates a predominant challenge for developing a more precise personalized management of NSCLC. While the research of novel targeted drugs demands huge amount effort and financial support, therefore exploring potential biomarkers that could benefit the detection rate and boosting treatment efficacy is necessary.

A‐kinase–interacting protein 1 (AKIP1), a mediator of PKAc by interacting with the N‐terminal and advancing the nuclear translocation, is firstly found to be aberrantly expressed in breast cancer cell and prostate cancer.7, 8 Then through years of investigation, AKIP1 is reported as an oncogenetic factor in several cancers, including esophageal squamous cell carcinoma and hepatocellular carcinoma (HCC) etc, through regulating various oncogenetic signaling pathways.9, 10 Although specific biological and molecular functions of AKIP1 in oncology are still vague, based on the previous findings of its role in cancers, we deduced that AKIP1 might also plays a role in NSCLC and have the potentiality to serve as a biomarker for diagnosis or prognosis in patients with NSCLC; however, studies aiming at investigating this are very limited.

Thus, this study aimed to evaluate the expression of AKIP1 in tumor tissue, and its correlation with tumor characteristics and prognosis in patients with NSCLC.

METHODS

Patients

Four hundred and ninety patients with NSCLC who underwent resection in The Second People's Hospital of Liaocheng between January 2012 and December 2014 were screened and reviewed in this retrospective study. Patients were eligible for inclusion in the study if they met the following criteria: (a) histologically or cytologically confirmed diagnosis of primary NSCLC; (b) received resection; (c) tumor tissues and paired adjacent tissues were well reserved; and (d) medical records and follow‐up records were complete and available. The exclusion criteria were as follows: (a) tumor tissues and adjacent tissues were unavailable for immunohistochemistry (IHC) assay; (b) received neoadjuvant therapy; and (c) complicated with other malignancies or had a distant metastasis. In addition, tumor size and lymph node metastases of each patient were assessed by oncology experts. The protocol of this study was approved by the Institutional Review Board of The Second People's Hospital of Liaocheng, and the written informed consents or verbal agreements (with tape recording) were provided by patients or their guardians.

Baseline data and tissue samples collection

The baseline clinical data were collected from medical records, which included (a) demographic features: age, gender, smoke, and drink; (b) tumor characteristics: tumor size, lymph node metastasis, TNM stage, and pathological differentiation (the differentiation degree of tumor tissues, which was defined as the similarities to the normal tissue regarding morphology and function of tumor tissues); and (c) tumor marker: carcinoembryonic antigen (CEA), and abnormal CEA was defined as the CEA level >5 ng/mL. The tumor tissues and paired adjacent tissues were obtained from pathology department and used for detecting the expression of AKIP1. All the tissues were isolated from surgery, fixed in 10% neutral buffered formalin and embedded in paraffin wax.

Adjuvant treatment after resection

After resection, patients received appropriate adjuvant treatments based on the TNM stage, surgical margin status, and other clinical conditions according to National Comprehensive Cancer Network (NCCN) clinical practice guidelines in Oncology: Non‐Small Cell Lung Cancer (Version 2.2013).11 Among patients with TNM stage I, observation or chemotherapy (for high‐risk patients) was performed for patients with negative margins, and the reresection ± chemotherapy or radiation therapy (RT) ± chemotherapy was performed for the patients with positive margins; among patients with TNM stage II, chemotherapy was performed for patients with negative margins, and the reresection + chemotherapy or chemoradiotherapy + chemotherapy was performed for the patients with positive margins; among patients with TNM stage III, chemotherapy + RT was performed for patients with negative margins, and the chemoradiotherapy + chemotherapy was performed for the patients with positive margins. Commonly used chemotherapy regimen included cisplatin + vinorelbine, cisplatin + etoposide, cisplatin + gemcitabine, and cisplatin + docetaxel.

Follow‐up data collection

Patients were followed up to December 31, 2018, with a median follow‐up duration of 45.5 months (range: 2.0‐81.0 months). The survival data were collected from follow‐up records, and the disease‐free survival (DFS) and overall survival (OS) were calculated. The DFS was defined as the duration from resection to disease recurrence, disease progression or death. The OS was defined as the time interval from resection to death.

IHC and assessment of AKIP1 expression

The expression of AKIP1 in tumor tissues and paired adjacent tissues were assessed by IHC. The paraffin‐embedded and 10% formalin (Sigma‐Aldrich, Burlington)‐fixed tissues were cut into 4 µm sections and then were deparaffinized using xylene (Sigma‐Aldrich, Burlington) followed by rehydration in graded ethanol. Antigen retrieval was performed by microwave heating, and the endogenous peroxidase activity was blocked by incubating with H2O2 (Sigma‐Aldrich, Burlington), and then, the tissue sections were incubated with 0.025% Triton X‐100 (Sigma‐Aldrich, Burlington) for 5 minutes. To prevent nonspecific binding, the tissue sections were incubated with 10% normal goat serum (Sigma‐Aldrich, Burlington) for 15 minutes at 37°C and then were incubated overnight at 4°C with anti‐C11orf17/AKIP1 antibody (1:100; Abcam). Next day, the tissue sections were incubated with horseradish peroxidase‐conjugated goat anti‐rabbit immunoglobulin G antibody (1:1000; Abcam) for 60 minutes at 37°C. Finally, the tissue sections were stained with diaminobenzidine (DAB) (Dako) and counterstained with hematoxylin (Sigma‐Aldrich, Burlington) and then were sealed with neutral resin (Sango Biotech). According to IHC staining, the expression of AKIP1 in the tumor and paired adjacent tissues was assessed by a semi‐quantitative scoring method based on the average intensity and percentage of positively stained tumor cells.12 The score of intensity was assessed as follows: 0 (no staining), 1 (weak staining), 2 (moderate staining), and 3 (strong staining). The percentage of positively stained tumor cells was scored according to the following standard: 0, 0%; 1, <25%; 2, 26 ~ 50%; 3, 51 ~ 75%; and 4, >75%. The final score was calculated by multiplying of staining intensity score and the proportion score. High expression of AKIP1 was defined as the total score >3, and the low expression of AKIP1 was defined as the total score ≤3.

Statistical analysis

Statistical analyses were performed using SPSS 24.0 software (IBM), and figures were plotted using GraphPad Prism 7.00 (GraphPad Software). Data were presented as mean ± standard deviation (SD), median (range), or count (percentage). The expression of AKIP1 in tumor tissue and paired adjacent tissue were compared by McNemar's test. Correlation analyses were determined by chi‐square test or Wilcoxon's rank‐sum test. The DFS and OS were illustrated by Kaplan‐Meier curve. The difference of DFS and OS between groups was determined using log‐rank test. The factors affecting DFS and OS were determined by univariate and multivariate Cox's proportional hazards regression model analyses. P value <.05 was considered as significant.

RESULTS

Study flow

At the beginning of this retrospective cohort study, 761 patients with NSCLC who underwent resection were screened and then 217 patients were excluded (including 93 patients with unavailable tumor tissues and adjacent tissues, 68 who received neoadjuvant therapy, 50 with incomplete medical records and follow‐up records, and 6 who were complicated with other malignancies) (Figure 1). Then, there left 544 patients who were eligible for our study; however, 54 patients were excluded subsequently due to not being able to be contacted to acquire informed consents (N = 43) and declining the use of their clinical data in this study (N = 11). So there remained 490 patients who were reviewed in our study (Figure 2).

Figure 1

Study flow

Figure 2

AKIP1 expression in tumor tissue and adjacent tissue. The AKIP1 expression in tumor tissue and adjacent tissue under microscope with different magnifications A, the percentage of NSCLC patients with AKIP1 high expression and AKIP1 low expression in tumor tissues and paired adjacent tissues B, Comparison between two groups was determined by McNemar's test. P value <.05 was considered as significant. NSCLC, non‐small cell lung cancer; and AKIP1, A‐kinase–interacting protein 1

Baseline characteristics

The mean age of 490 patients with NSCLC in our study was 61.7 ± 10.6 years, and the male and female numbers were 385 (78.6%) and 105 (21.4%), respectively (Table 1). In addition, the numbers of patients who had drink and patients with smoke history were, respectively, 267 (54.5%) and 195 (39.8%). And the numbers of patients with well, moderate, and poor pathological differentiation were 69 (14.0%), 307 (62.7%) and 114 (23.3%), respectively. The mean value of tumor size was 5.3 ± 2.1 cm, and 172 (35.1%) patients had lymph node metastasis. Hundred and fifty‐eight (32.2%) patients were in TNM stage I, 160 (32.7%) patients were in TNM stage II, and 172 patients (35.1%) were in TNM stage III. Besides, the median CEA level was 6.8 (0.3‐1941.8) ng/mL.

Table 1

Baseline characteristics of NSCLC patients

Characteristics	NSCLC patients (N = 490)
Age (years), mean ± SD	61.7 ± 10.6
Gender, No. (%)
Male	385 (78.6)
Female	105 (21.4)
Smoke, No. (%)	267 (54.5)
Drink, No. (%)	195 (39.8)
Pathological differentiation, No. (%)
Well	69 (14.0)
Moderate	307 (62.7)
Poor	114 (23.3)
Tumor size (cm), mean ± SD	5.3 ± 2.1
Lymph node metastasis, No. (%)	172 (35.1)
TNM stage, No. (%)
I	158 (32.2)
II	160 (32.7)
III	172 (35.1)
CEA (ng/mL), median (range)	6.8 (0.3‐1941.8)

Abbreviations: CEA, carcinoembryonic antigen; NSCLC, non‐small cell lung cancer; SD, standard deviation.

AKIP1 expression in tumor tissue and paired adjacent tissue

The AKIP1 expression in tumor tissue and paired adjacent tissue was detected by IHC (Figure 1A), which presented that the percentage of patients with AKIP1 high expression was elevated while proportion of patients with AKIP1 low expression was decreased in tumor tissues compared with those in paired adjacent tissues (P < .001) (Figure 1B).

Association of tumor tissue AKIP1 expression with tumor characteristics

Correlation of tumor tissue AKIP1 expression with tumor characteristics in patients with NSCLC were assessed, which showed that high AKIP1 expression in tumor tissue was correlated with poorer pathological differentiation (P < .001), tumor size >5 cm (P = .001), lymph node metastasis (P = .016), higher TNM stages (P < .001), and abnormal CEA level (P = .035) (Table 2).

Table 2

Correlation of AKIP1 expression with tumor characteristics

Items	AKIP1 expression		P value
	High	Low
Pathological differentiation, No. (%)
Well	25 (36.2)	44 (63.8)	<.001
Moderate	161 (52.4)	146 (47.6)
Poor	77 (67.5)	37 (32.5)
Tumor size, No. (%)
≤5 cm	133 (47.3)	148 (52.7)	.001
>5 cm	130 (62.2)	79 (37.8)
Lymph node metastasis, No. (%)
No	158 (49.7)	160 (50.3)	.016
Yes	105 (61.0)	67 (39.0)
TNM stage, No. (%)
I	66 (41.8)	92 (58.2)	<.001
II	89 (55.6)	71 (44.4)
III	108 (62.8)	64 (37.2)
CEAa, No. (%)
Normal	98 (48.0)	106 (52.0)	.035
Abnormal	165 (57.7)	121 (42.3)

Comparison was determined by chi‐square test or Wilcoxon's rank‐sum test. P value <.05 was considered significant.

Abbreviations: AKIP1, A‐kinase–interacting protein 1; CEA, carcinoembryonic antigen.

Abnormal: CEA >5 ng/mL and normal: CEA ≤5 ng/mL.

Association of tumor tissue AKIP1 expression with DFS and OS

In total NSCLC patients, the DFS was worse in patients who had AKIP1 high expression compared with patients who had AKIP1 low expression (P < .001) (Figure 3A). In patients with distinctive TNM stages, the DFS was shorter in patients with AKIP1 high expression compared with patients with AKIP1 low expression in both TNM stage I patients (P = .210) (Multivariate Cox's regression) and TNM stage III patients (P = .002) (Figure 3D). However, no difference of DFS was found between patients with AKIP1 high expression and patients with AKIP1 low expression in TNM stage II patients (P = .210) (Figure 3C). As for OS, in total patients, the OS of patients with AKIP1 high expression was less prolonged compared to patients with AKIP1 low expression (P < .001) (Figure 4A). And in TNM stage I patients (P = .001) (Figure 4B) as well as TNM stage III patients (P = .004) (Figure 4D), the OS was decreased in patients with AKIP1 high expression compared with patients with AKIP1 low expression. In addition, the OS of patients in TNM stage III showed no difference between patients with high AKIP1 expression and patients with low AKIP1 expression (P = .172) (Figure 4C).

Figure 3

Correlation of tumor tissue AKIP1 expression with DFS. The DFS in NSCLC patients with tumor tissue AKIP high expression and patients with AKIP1 low expression in total patients A, TNM stage I patients B, TNM stage II patients C, and TNM stage III patients D, DFS were illustrated by Kaplan‐Meier curve. The difference of DFS between groups was determined using log‐rank test. P value <.05 was considered as significant. AKIP1, A‐kinase–interacting protein 1; DFS, disease‐free survival; and NSCLC, non‐small cell lung cancer

Figure 4

Correlation of tumor tissue AKIP1 expression with OS. The OS in NSCLC patients with tumor tissue AKIP high expression and patients with AKIP1 low expression in total patients A, TNM stage I patients B, TNM stage II patients C, and TNM stage III patients D, OS were illustrated by Kaplan‐Meier curve. The difference of OS between groups was determined using log‐rank test. P value <.05 was considered as significant. AKIP1, A‐kinase–interacting protein 1; NSCLC, non‐small cell lung cancer; and OS, overall survival

Factors affecting DFS and OS

Univariate Cox's proportional hazards regression model analysis revealed that high AKIP1 expression in tumor tissue was correlated with worse DFS (P < .001) in patients with NSCLC, and age >60 years (P = .037), poor pathological differentiation (P = .001), tumor size >5 cm (P < .001), lymph node metastasis (P < .001), TNM stage III, (P < .001) and CEA abnormal (P = .037) were also correlated with shorter DFS (Table 3). Then, all the factors were included in the multivariate Cox's proportional hazards regression model analysis, which disclosed that high AKIP expression (P < .001) was an independent predictive factor for worse DFS, and lymph node metastasis (P < .001), poor pathological differentiation (P = .011), and abnormal CEA level (P = .028) were also independent predictive factors for declined DFS. With respect to OS, the univariate Cox's proportional hazards regression model displayed that high AKIP1 expression in tumor tissue (P < .001), poor pathological differentiation (P = .017), tumor size >5 cm (P < .001), lymph node metastasis (P < .001), TNM stage III (P < .001), and abnormal CEA level (P = .002) were predictive factors for deteriorative OS (Table 4). Then, the multivariate Cox's proportional hazards regression model analysis elucidated that high AKIP1 expression in tumor tissue (P < .001) could independently predict decreased OS. And other independent predictive factors for worse OS were lymph node metastasis (P < .001) and abnormal CEA level (P = .002).

Table 3

Analysis of factors affecting DFS by univariate and multivariate Cox's proportional hazards regression model

Items	Univariate Cox's regression				Multivariate Cox's regression
	P value	HR	95% CI		P value	HR	95% CI
			Lower	Higher			Lower	Higher
AKIP1 expression (high)	<.001	1.765	1.440	2.163	<.001	1.696	1.369	2.102
Age (>60 y)	.037	1.238	1.013	1.512	.231	1.137	0.922	1.402
Gender (male)	.702	1.049	0.820	1.343	.538	0.919	0.702	1.203
Smoke	.619	1.052	0.862	1.284	.604	1.057	0.857	1.305
Drink	.341	1.103	0.901	1.350	.120	1.177	0.958	1.447
Pathological differentiation (poor)	.001	1.466	1.169	1.840	.011	1.373	1.077	1.750
Tumor size (>5 cm)	<.001	1.533	1.255	1.872	.131	0.806	0.610	1.066
Lymph node metastasis	<.001	2.792	2.268	3.437	<.001	2.870	2.194	3.753
TNM stage (III)	<.001	1.853	1.512	2.270	.395	1.137	0.846	1.529
CEAa (abnormal)	.037	1.240	1.013	1.516	.028	1.260	1.026	1.548

Abbreviations: AKIP1, A‐kinase–interacting protein 1; CEA, carcinoembryonic antigen; CI, confidence interval; DFS, disease‐free survival; HR, hazard ratio.

Abnormal: CEA >5 ng/mL and normal: CEA ≤5 ng/mL.

Table 4

Analysis of factors affecting OS by univariate and multivariate Cox's proportional hazards regression model

Items	Univariate Cox's regression				Multivariate Cox's regression
	P value	HR	95% CI		P value	HR	95% CI
			Lower	Higher			Lower	Higher
AKIP1 expression (high)	<.001	1.797	1.438	2.245	<.001	1.795	1.422	2.267
Age (>60 y)	.425	1.092	0.880	1.357	.349	0.897	0.713	1.127
Gender (male)	.604	0.933	0.719	1.212	.266	0.850	0.639	1.131
Smoke	.843	0.978	0.789	1.214	.869	1.019	0.810	1.283
Drink	.542	1.071	0.860	1.334	.155	1.177	0.940	1.474
Pathological differentiation (poor)	.017	1.349	1.055	1.726	.096	1.253	0.961	1.633
Tumor size (>5 cm)	<.001	1.754	1.413	2.177	.812	1.035	0.779	1.375
Lymph node metastasis	<.001	3.516	2.815	4.392	<.001	3.924	2.950	5.220
TNM stage (III)	<.001	1.822	1.462	2.271	.203	0.817	0.599	1.115
CEAa (abnormal)	.002	1.421	1.138	1.774	.002	1.440	1.147	1.806

Abbreviations: AKIP1, A‐kinase–interacting protein 1; CEA, carcinoembryonic antigen; CI, confidence interval; HR, hazard ratio; OS, overall survival.

Abnormal: CEA >5 ng/mL and normal: CEA ≤5 ng/mL.

DISCUSSION

In this study, we detected the expression of AKIP1 in tumor tissue and adjacent tissue, and the correlation of tumor tissue AKIP1 expression with tumor characteristics and patients’ prognosis in NSCLC, and found that (a) AKIP1 expression was elevated in tumor tissue compared with paired adjacent tissue; (b) high tumor tissue AKIP1 expression correlated with more severe tumor characteristics; and (c) high AKIP1 expression in tumor tissue was an independent predictive factor for both worse DFS and OS.

Similar to many other carcinomas, NSCLC is united by having multiple genetic abnormalities, such as the epidermal growth factor receptor (EFGR) and c‐ros oncogene 1 (ROS1) mutations, and those genetic features also contribute to the improvement pf NSCLC management.13, 14, 15, 16 Besides these altered genes, a diverse class of protein biomarkers also exist in the development of individualized treatment of NSCLC, and there have been studies indicate that combining biomarkers may have more satisfactory effect in the diagnosis and prognosis in NSCLC patients compared with a single genetic or protein biomarker.17 Hence, researching for more biomarkers which could reinforce the detection rate and prognosis of patients with NSCLC is of urgent need. AKIP1 has shown promising values to be a biomarker in various cancers other than NSCLC as reported in the previous studies; however, its role of being a biomarker in patients with NSCLC has not been investigated.

A‐kinase–interacting protein 1, also called breast cancer associated protein 3 (BCA3), is firstly discovered in breast cancer and prostate cancer cells lines, consisting of three kinds of splice variants in human, AKIP1a, AKIP1b, and AKIP1c.8 In recent years, studies have revealed a role of AKIP1 in carcinogenesis in several cancers, and most of them indicate that AKIP1 engages in cancer development and progression. A recent in vivo and in vitro experiment shows that AKIP1 advocates early progression of HCC via stimulating the Wnt/β‐catenin signaling pathway.10 And another cell experiment elucidates that AKIP1 enhances cervical cancer angiogenesis and growth through increasing the NF‐κB‐dependent chemokines CXC chemokine ligand 1 (CXCL1), CXCL2, and CXCL8 levels.18 Also, in HCC, AKIP1 promotes the tumor growth, metastasis and angiogenesis in vivo and in vitro via activating AKT and translocating NF‐κB.19 More importantly, there is also a report illuminating that AKIP1 participates in etiology of NSCLC as well. An experiment demonstrates that AKIP1 enhances cell migration, invasion, and epithelial‐mesenchymal transition (EMT) by transactivating zinc finger E‐box‐binding homeobox 1.20 In addition, there are also studies assessing the prognostic value of AKIP1 in carcinomas. A previous study reports that high AKIP1 level in tumor tissue associates with larger tumor diameter, higher TNM stage, and lymph node metastasis, and is also correlated with shorter survival time in colorectal cancer.21 And in breast carcinoma, AKIP1 expression in tumor tissue is elevated than that in paired normal tissue, and is positively associated with tumor stage, tumor size, and lymph node metastasis.22 Nonetheless, the potential role of AKIP1 serving as biomarker in patients with NSCLC has not been investigated. In this study, the AKIP1 expression was elevated in tumor tissue compared with paired normal tissue, and an increased AKIP1 expression was correlated with worse tumor characteristics and survival profiles, which were partially in accordance with the previous findings observed in other cancers. As for possible explanations to the results in our study, it might be due to that AKIP1 could promote the development and aggravation of NSCLC through the following ways: (a) promoting the progressive tumor cell functions via multiple oncogenesis‐related signaling pathways, for instance, enhancing NSCLC cell migration and invasion via transactivating zinc finger E‐box‐binding homeobox 1; (b) promoting the malignant behaviors of tumor by mediating various factors, such as advocating the angiogenesis and tumor growth via mediating CXC chemokines and enhancing the EMT, which subsequently exacerbates the progression of NSCLC; and (c) in addition, it is also possible that AKIP1 promotes NSCLC progression through advancing inflammation, which has been revealed as a crucial process in oncogenesis, through mediating the NF‐κB signaling pathway.10, 18, 19, 20, 21, 22, 23, 24

Although our study was the first to evaluate the value of AKIP1 in disease monitoring and prognosis of NSCLC, there were still some limitations in our study, which included (a) our study was conducted in a single center, and patients were mainly from East China, which might cause selection bias; (b) patients in TNM stage IV were not included in our study, which indicated a relatively insufficient representativeness of our patient cohort; however, we excluded the patients in TNM stage IV to avoid the confounding effect caused by distant metastasis; (c) the molecular and biochemical mechanisms of AKIP1 in NSCLC pathogenesis were not evaluated in this study; and (d) chemotherapy or radiotherapy are critical factors affecting patients’ prognosis, and the correlation of AKIP1 with chemotherapy/radiotherapy was not evaluated in our study. However, most of our patients were non‐local patients, and it has been quite a long time since we enrolled our patients; thus, it was difficult to obtain a complete data regarding the records of chemotherapy or radiotherapy of all the patients. Therefore, prospective multicenter studies and molecular experiments should be performed in the future.

In conclusion, tumor tissue AKIP1 expression may have the potential to be a biomarker assisting in disease monitoring and prognosis in NSCLC.