Prognostic Value of Dynactin mRNA Expression in Cutaneous Melanoma.

BACKGROUND Dynactin (DCTN) is a multi-subunit protein encoded by DCTN genes for 6 subunits. In different diseases the DCTN genes may have different roles; therefore, we investigated the prognostic potential of DCTN mRNA expression in cutaneous melanoma (CM). MATERIAL AND METHODS Data for DCTN mRNA expression in CM patients were obtained from the OncoLnc database, which contains updated gene expression data for 459 CM patients based on the Cancer Genome Atlas. Kaplan-Meier analysis and a Cox regression model were used to determine overall survival (OS) with calculation of hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS The multivariate survival analysis showed that individually low expression of DCTN1, DCTN2, and DCTN5 and high expression of DCTN6 were associated with favorable OS (adjusted P=0.008, HR=0.676, 95% CI=0.506-0.903; adjusted P=0.004, HR=0.648, 95% CI=0.485-0.867; adjusted P=0.011, HR=0.686, 95% CI=0.514-0.916; and adjusted P=0.018, HR=0.706, 95% CI=0.530-0.942, respectively). In a joint-effects analysis, combinations of low expression of DCTN1, DCTN2, and DCTN5 and high expression of DCTN6 were found to be more highly correlated with favorable OS (all P<0.05). CONCLUSIONS Our findings suggest that downregulated DCTN1, DCTN2, and DCTN5 and upregulated DCTN6 mRNA expression in CM are associated with favorable prognosis and may represent potential prognostic biomarkers. Moreover, use of the 4 genes in combination can improve the sensitivity for predicting OS in CM patients.

Background

Cutaneous melanoma (CM) is one of the most aggressive tumors of the skin and mucosa [1], accounting for 6380 out of 9250 skin cancer-related deaths in the United States in 2017 [2]. With improved awareness and treatment options, the 5-year relative survival rate has reached 92% and the 10-year relative survival rate has reached 89% [3]. Still, early detection is important, as the prognosis is much better if the cancer is detected early. The primary treatment for CM is surgery, and adjuvant immunotherapy, immunotherapy, and targeted therapy drugs also are used to treat various stages of melanoma [3].

Dynactin (DCTN) is a multi-subunit protein that drives retrograde transport in cells [4-7]. The 6 subunits of DCTN are referred to as dynactin 1–6 (DCTN1–6). All subunits of DCTN are critical to the structure and function of DCTN [4,8-10]. DCTN1 was shown to act as a fusion partner in some but not all Spitz tumors [11] as well as in non-small cell lung cancer (NSCLC) [12]. DCTN1 and DCTN3 are upregulated in sporadic ALS [13]. DCTN2 is upregulated in the osteosarcoma SJSA-1 cell line, but a link between its altered expression and the prognosis of CM has not been reported [14]. Another study showed that the intronic regions of DCTN6 pre-mRNA interact with the SPRIGHTLY long non-coding (lnc)RNA of melanoma [15]. Based on this evidence for pathogenic roles of mutations in DCTN subunits, we questioned whether mutations in DCTN genes are associated with CM.

According to these previous studies, DCTN1 and DCTN2 are expressed in human epidermal melanocytes [16]. However, the relationships between DCTN family members and CM patients have not been investigated. Therefore, in the present study, we investigated the prognostic value of the mRNA expression levels of individual DCTN subunits and conducted a joint-effects analysis using data from 459 CM patients available in the OncoLnc database based on the Cancer Genome Atlas.

Material and Methods

Patient and disease characteristics

We used The Metabolic gEne Rapid Visualizer (MERAV: , accessed by November 5, 2017) to generate boxplots of the expression levels of DCTN subunits in normal tissue and primary CM tissue [17]. The Cancer Genome Atlas (, accessed by November 7, 2017) and OncoLnc (, accessed by November 8, 2017) [18] were searched to obtain the clinical information of 459 CM patients, including sex, age, body mass index (BMI), TNM stage, events, survival time, death status, and mRNA expression levels of DCTN1, DCTN2, DCTN3, DCTN4, DCTN5, and DCTN6 according to 50% cutoff values.

Correlation analysis and functional enrichment analysis

Pearson correlation coefficient analysis was used to identify correlations among DCTN family genes. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) v.6.8 (, accessed November 10, 2017) [19,20] was used for analyses of functional enrichment, including gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. GO functional analysis included molecular function (MF), cellular component (CC), and biological process (BP). A gene function prediction website (GeneMANIA: , accessed November 15, 2017) [21] was used to analyze interactions among DCTN family members.

Survival analysis

For each DCTN mRNA, patients were divided into high- and low-expression groups according to a 50th percentile cutoff. The prognosis of CM was evaluated based on overall survival (OS). The Kaplan-Meier estimator with a log-rank test was used to identify correlations between the 6 DCTN mRNAs and patient survival. Adjustment was made for race, age, sex, and TNM stage in the Cox proportional hazards regression model.

Joint-effects analysis

A joint-effects analysis was performed for the combination of genes identified as significant by the survival analysis. Groups were formulated by summarizing the selected expression of genes associated with better OS in one group, worse OS in another group, and others in the last group, as outlined in Tables 1–3.

Table 1

Grouping according to 2 selected genes.

Group	Composition	Group	Composition
I	Low DCTN1 + low DCTN2	X	Low DCTN2 + low DCTN5
II	Low DCTN1 + high DCTN2	XI	Low DCTN2 + high DCTN5
	High DCTN1 + low DCTN2		High DCTN2 + low DCTN5
III	High DCTN1 + high DCTN2	XII	High DCTN2 + high DCTN5
IV	Low DCTN1 + low DCTN5	XIII	Low DCTN2 + high DCTN6
V	Low DCTN1 + high DCTN5	XIV	Low DCTN2 + low DCTN2
	High DCTN1 + low DCTN5		High DCTN2 + high DCTN6
VI	High DCTN1 + high DCTN5	XV	High DCTN2 + low DCTN6
VII	Low DCTN1 + high DCTN6	XVI	Low DCTN5 + high DCTN6
VIII	Low DCTN1 + low DCTN6	XVII	Low DCTN5 + low DCTN6
	High DCTN1 + high DCTN6		High DCTN5 + high DCTN6
IX	High DCTN1 + low DCTN6	XVIII	High DCTN5 + low DCTN6

DCTN – dynactin.

Table 2

Grouping according to 3 selected genes.

Group	Composition	Group	Composition	Group	Composition
i	Low DCTN1 + low DCTN2 + low DCTN5	iv	Low DCTN1 + low DCTN2 + high DCTN6	vii	Low DCTN2 + low DCTN5 + high DCTN6
ii	High DCTN1 + low DCTN2 + low DCTN5	v	High DCTN1 + low DCTN2 + high DCTN6	viii	High DCTN2 + low DCTN5 + high DCTN6
	Low DCTN1 + high DCTN2 + low DCTN5		Low DCTN1 + high DCTN2 + high DCTN6		Low DCTN2 + high DCTN5 + high DCTN6
	Low DCTN1 + low DCTN2 + high DCTN5		Low DCTN1 + low DCTN2 + low DCTN6		Low DCTN2 + low DCTN5 + low DCTN6
	High DCTN1 + high DCTN2 + low DCTN5		High DCTN1 + high DCTN2 + high DCTN6		High DCTN2 + high DCTN5 + high DCTN6
	High DCTN1 + low DCTN2 + high DCTN5		High DCTN1 + low DCTN2 + low DCTN6		High DCTN2 + low DCTN5 + low DCTN6
	Low DCTN1 + high DCTN2 + high DCTN5		Low DCTN1 + high DCTN2 + low DCTN6		Low DCTN2 + high DCTN5 + low DCTN6
iii	High DCTN1 + high DCTN2 + high DCTN5	vi	High DCTN1 + high DCTN2 + low DCTN6	ix	High DCTN2 + high DCTN5 + low DCTN6

DCTN – dynactin.

Table 3

Grouping according to 4 selected genes.

Group	Composition
1	High DCTN1 + high DCTN2 + high DCTN5 + low DCTN6
2	High DCTN1 + high DCTN2 + high DCTN5 + high DCTN6
	High DCTN1 + low DCTN2 + high DCTN5 + high DCTN6
	High DCTN1 + high DCTN2 + low DCTN5 + high DCTN6
	Low DCTN1 + high DCTN2 + high DCTN5 + high DCTN6
	Low DCTN1 + low DCTN2 + high DCTN5 + high DCTN6
	Low DCTN1 + high DCTN2 + low DCTN5 + high DCTN6
	Low DCTN1 + high DCTN2 + high DCTN5 + low DCTN6
	High DCTN1 + low DCTN2 + low DCTN5 + high DCTN6
	High DCTN1 + low DCTN2 + high DCTN5 + low DCTN6
	High DCTN1 + high DCTN2 + low DCTN5 + low DCTN6
	Low DCTN1 + low DCTN2 + high DCTN5 + low DCTN6
	Low DCTN1 + high DCTN2 + low DCTN5 + low DCTN6
	High DCTN1 + low DCTN2 + low DCTN5 + low DCTN6
	Low DCTN1 + low DCTN2 + low DCTN5 + low DCTN6
3	Low DCTN1 + low DCTN2 + low DCTN5 + high DCTN6

DCTN – dynactin.

Statistical analyses

Kaplan-Meier survival analysis and the log-rank test were used to calculate OS and P values for all associations. The Cox proportional hazards regression model was used for uni- and multivariate survival analyses. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated with the Cox proportional hazards regression model with adjustment for influential clinical characteristics such as race, sex, age, TNM stage, and BMI. P<0.05 was considered statistically significant. Statistical analyses were carried out using SPSS v.22.0 software (IBM, Chicago, IL, USA). Vertical scatter plots and survival curves were generated in GraphPad Prism v.7.0 (La Jolla, CA, USA).

Ethics statement

All data used in this study were obtained from a public database; therefore, approval of the study by an ethics committee was not required.

Results

Patient characteristics influencing survival and differential DCTN expression in CM

The detailed demographic and clinical data for the 459 included patients are provided in Table 4. Race, age, and TNM stage were significantly associated with median survival time (MST; P=0.004, P=0.001, and P<0.001, respectively; Table 4). Boxplots illustrating differences in the expression of the 6 DCTN genes in normal skin tissue versus primary CM tissue were generated using MERAV (Figure 1). The median expression levels of DCTN2 and DCTN3 were higher in normal skin tissue than in primary CM tissue, whereas the median expression levels of DCTN5 and DCTN6 were higher in primary CM tissue than in normal skin tissue. The median expression levels of DCTN1 and DCTN4 did not differ significantly between normal skin tissue and primary tumor.

Table 4

Demographic and clinical data for 459 CM patients.

Variables	Patients (n=459)	No. of events (%)	MST (days)	HR (95% CI)	Log-rank P
Race					0.004
White	436	208 (47.7%)	2470	Ref.
Others	13	8 (61.5%)	636	0.347 (0.170–0.707)
Missing	10
Sex					0.259
Male	284	146 (51.4%)	2454	Ref.
Female	175	72 (41.1%)	2030	0849 (0.638–1.128)
Age (years)					0.001
≥60	240	116 (48.3%)	3564	Ref.
<60	219	102 (46.6%)	1860	1.619 (1.227–2.136)
TNM stage					<0.001
0+I+II+I/II nos	232	108 (46.6%)	3259	Ref.
III+IV	191	91 (47.6%)	1960	1.673 (1.253–2.235)
Missing	36
BMI (kg/m2)					0.437
>25	80	25 (31.3%)	2101	Ref.
≤25	160	61 (38.1%)	3136	0.830 (0.519–1.327)
Missing	219

MST – median survival time; HR – hazard ratio; CI – confidence interval.

Figure 1

MERAV boxplots for DCTN gene expression in normal skin tissue and primary CM tissue: (A) DCTN1 expression; (B) DCTN2 expression; (C) DCTN3 expression; (D) DCTN4 expression; (E) DCTN5 expression; and (F) DCTN6 expression.

Correlations among expression levels of DCTN genes and functions of DCTN genes

Correlations among the expression levels of individual DCTN genes were identified by Pearson correlation coefficient analysis. For DCTN1, DCTN2, DCTN3, and DCTN4, the expression level of each gene was correlated with that of each of the other genes (all P<0.05), but not with the expression levels of DCTN5 and DCTN6. DCTN5 expression was only correlated with DCTN1 expression (P<0.05). DCTN6 expression was correlated with DCTN1, DCTN3, and DCTN4 expression (all P<0.001; Figure 2A). Interactions among the expression levels of DCTN1, DCTN2, DCTN3, DCTN4, DCTN5, and DCTN6 are shown in Figure 2B. Scatter plots for the expression of the 6 genes according to the 50th percentile cutoff are shown in Figure 2C.

Figure 2

(A) Pearson’s correlation coefficients for DCTN1, DCTN2, DCTN3, DCTN4, DCTN5, and DCTN6 gene expression levels; (B) gene interaction networks among selected genes generated by GeneMANIA; (C) scatter plots for DCTN1, DCTN2, DCTN3, DCTN4, DCTN5, and DCTN6 gene expression levels in The Cancer Genome Atlas; and (D) analysis of enriched GO terms and KEGG pathways for DCTN genes obtained using DAVID. ** P<0.05, *** P<0.001.

The biological functions of the DCTN genes were evaluated according to the BP, MF, and CC categories for GO functional analysis (Figure 2D), and the results of KEGG pathway analysis are shown in Figure 2D.

Survival influence of differential DCTN gene expression

The results of univariate survival analysis were showed as Figure 3A–3F. The results showed that low expression levels of DCTN2 and DCTN5 separately were significantly associated with favorable OS in CM patients (P<0.01 and P=0.004, respectively; Figure 3B, 3E). High expression of DCTN6 also was significantly associated with favorable OS (P=0.002; Figure 3F). The multivariate Cox proportional hazards regression analysis identified associations of sex, race, age, and TNM stage with the prognosis of CM patients. The multivariate survival analysis showed that, individually, low expression levels of DCTN1, DCTN2, and DCTN5 and high expression level of DCTN6 were associated with favorable OS (adjusted P=0.008 HR=0.676 95% CI=0.506–0.903; adjusted P=0.004, HR=0.648, 95% CI=0.485–0.867; adjusted P=0.011, HR=0.686, 95% CI=0.514–0.916; and adjusted P=0.018, HR=0.706, 95% CI=0.530–0.942, respectively; Table 5).

Figure 3

Prognostic value of DCTN expression for OS. (A–F) Kaplan-Meier survival curves for all CM patients according to DCTN1 (A), DCTN2 (B), DCTN3 (C), DCTN4 (D), DCTN5 (E), and DCTN6 (F) expression (n=459).

Table 5

Prognostic survival analysis according to high or low expression of DCTN family genes.

Gene	Patients (n=459)	No. of events (%)	MST (days)	Crude HR (95% CI)	Crude P	Adjusted HR* (95% CI)	Adjusted P*
DCTN1					0.106		0.008
High	229	112 (48.9%)	1910	Ref.		Ref.
Low	229	105 (45.9%)	3259	0.803 (0.614–1.048)		0.676 (0.506–0.903)
Missing	1
DCTN2					<0.001		0.004
High	229	111 (48.5%)	1860	Ref.		Ref.
Low	229	107 (46.7%)	3379	0.590 (0.449–0.774)		0.648 (0.485–0.867)
Missing	1
DCTN3					0.846		0.437
High	229	94 (41.0%)	2273	Ref.		Ref.
Low	229	124 (54.1%)	2454	0.974 (0.744–1.275)		0.893 (0.671–1.188)
Missing	1
DCTN4					0.900		0.140
High	229	114 (49.8%)	2470	Ref.		Ref.
Low	229	104 (45.4%)	2071	1.017 (0.779–1.329)		0.806 (0.606–1.073)
missing	1
DCTN5					0.004		0.011
High	229	123 (53.7%)	1910	Ref.		Ref.
Low	229	94 (41%)	3195	0.673 (0.514–0.882)		0.686 (0.514–0.916)
Missing	1
DCTN6					0.002		0.018
Low	229	125 (54.6%)	2071	Ref.		Ref.
High	229	92 (40.2%)	3195	0.659 (0.503–0.864)		0.706 (0.530–0.942)
Missing	1

Adjustment for race, sex, age, and TNM stage.

DCTN – dynactin; MST – median survival time; HR – hazard ratio; CI – confidence interval.

Survival influence of combinations of DCTN gene expression

Based on the DCTN genes identified as influential by the multivariate survival analysis, a joint-effects model was used to determine the combined effects of DCTN genes on the OS of CM patients. The different groups for this analysis were generated according to the expression of DCTN1, DCTN2, DCTN5, and DCTN6 (Tables 1–3). The Kaplan-Meier estimator with a log-rank test was used to evaluate the prognostic value of the gene expression combinations represented by each group (Figures 4, 5). In the analysis of low DCTN1, DCTN2, and DCTN5 expression with high DCTN6 expression, the combinations in groups I, IV, XII, X, XIII, XVI, i, iv, vii, and 1 were found to be more highly correlated with favorable OS (all P<0.05; Table 6). On the contrary, in the analysis of high expression of DCTN1, DCTN2, and DCTN5 and low DCTN6 expression, the combinations in groups III, VI, IX, XIII, XV, XVIII, iii, vi, ix, and 3 were found to be more highly correlated with poor OS (all P<0.05; Table 6).

Figure 4

Joint-effects analysis of the influence of combined DCTN gene expression on OS with stratification according to 2 selected DCTN genes among DCTN1, DCTN2, DCTN5, and DCTN6. (A) DCTN1 and DCTN2, (B) DCTN1 and DCTN5, (C) DCTN1 and DCTN6, (D) DCTN2 and DCTN5, (E) DCTN2 and DCTN6, and (F) DCTN5 and DCTN6. I, low DCTN1+low DCTN2; III, high DCTN1+high DCTN2; IV, low DCTN1+low DCTN5; VI, high DCTN1+high DCTN5; VII, low DCTN1+high DCTN6; IX, high DCTN1+low DCTN6; X, low DCTN2+low DCTN5; XII, high DCTN2+high DCTN5; XIII, low DCTN2+high DCTN6; XV, high DCTN2+low DCTN6; XVI, low DCTN5+high DCTN6; XVIII, high DCTN5+low DCTN6; II, V, VIII, XI, XIV, and XVII correspond to other combinations of genes as detailed in Table 1.

Figure 5

Joint-effects analysis of the influence of combined DCTN gene expression on OS with stratification according to 3 or 4 selected DCTN genes among DCTN1, DCTN2, DCTN5, and DCTN6. (A) DCTN1, DCTN2, and DCTN5; (B) DCTN1, DCTN2, and DCTN6 (C) DCTN2, DCTN5 and DCTN6, (D) DCTN1, DCTN2, DCTN5, and DCTN6. i, low DCTN1+low DCTN2+low DCTN5; iii, high DCTN1+high DCTN2+high DCTN5; iv, low DCTN1+low DCTN2+high DCTN6; vi, high DCTN1+high DCTN2+low DCTN6; vii, low DCTN2+low DCTN5+high DCTN6; ix, high DCTN2+high DCTN5+low DCTN6; 1, high DCTN1+high DCTN2+high DCTN5+low DCTN6; 3, low DCTN1+low DCTN2+low DCTN5+high DCTN6; ii, v, viii, and 2 correspond to other combinations of genes as detailed in Tables 2 and 3.

Table 6

Joint-effects analysis of the prognostic value of combinations of DCTN1, DCTN2, DCTN5, and DCTN6 expression in CM.

Group	Patients (n=459)	MST (days)	Crude P	Crude HR (95% CI)	Adjusted P*	Adjusted HR* (95% CI)
I	141	3424	0.001	Ref.	0.001	Ref.
II	176	2711	0.415	1.146 (0.826–1.589)	0.509	1.118 (0.803–1.558)
III	142	3733	<0.001	1.855 (1.323–2.601)	<0.001	1.859 (1.315–2.629)
IV	130	3587	0.007	Ref.	0.003	Ref.
V	199	2030	0.201	1.248 (0.888–1.754)	0.277	1.803 (1.255–2.590)
VI	130	1544	0.002	1.749 (1.220–2.509)	0.001	1.210 (0.858–1.705)
VII	124	3564	0.001	Ref.	<0.001	Ref.
VIII	210	2993	0.289	1.206 (0.853–1.704)	0.341	1.186 (0.835–1.686)
IX	125	1506	0.001	1.895 (1.304–2.752)	<0.001	2.012 (1.375–2.944)
X	114	4648	<0.001	Ref.	<0.001	Ref.
XI	231	2071	0.001	1.785 (1.256–2.536)	0.004	1.680 (1.180–2.391)
XII	114	1544	<0.001	2.567 (1.729–3.812)	<0.001	2.307 (1.542–3.452)
XIII	115	4222	<0.001	Ref.	<0.001	Ref.
XIV	228	2927	0.002	1.765 (1.238–2.516)	0.005	1.673 (1.170–2.392)
XV	116	1691	<0.001	2.643 (1.776–3.933)	<0.001	2.443 (1.628–3.665)
XVI	119	4000	<0.001	Ref.	0.001	Ref.
XVII	220	2711	0.016	1.559 (1.088–2.234)	0.018	1.546 (1.078–2.217)
XVIII	120	1766	<0.001	2.185 (1.495–3.193)	<0.001	2.089 (1.421–3.071)
i	78	4648	<0.001	Ref.	<0.001	Ref.
ii	302	2184	0.020	1.598 (1.076–2.374)	0.036	1.531 (1.028–2.281)
iii	79	1413	<0.001	2.999 (1.873–4.802)	<0.001	3.013 (1.870–4.857)
iv	68	4000	<0.001	Ref.	<0.001	Ref.
v	307	2927	0.056	1.503 (0.990–2.281)	0.104	1.422 (0.931–2.171)
vi	84	1486	<0.001	2.780 (1.659–4.422)	<0.001	2.679 (1.630–4.404)
vii	56	6598	<0.001	Ref.	<0.001	Ref.
viii	339	2421	<0.001	2.530 (1.513–4.231)	0.001	2.354 (1.403–3.949)
ix	64	1544	<0.001	4.088 (2.226–7.375)	<0.001	3.572 (1.955–6.524)
1	34	6598	<0.001	Ref.	<0.001	Ref.
2	373	2470	0.008	2.493 (1.275–4.875)	0.009	2.451 (1.248–4.816)
3	52	1429	<0.001	5.271 (2.500–11.113)	<0.001	5.216 (2.455–11.080)

Adjustment for race, sex, age, and TNM stage.

Bold type highlights statistically significant values (P≤0.05). DCTN – dynactin; MST – median survival time; HR – hazard ratio; CI – confidence interval.

Discussion

The 6 DCTN genes are known to encode the 6 subunits of DCTN, which are all essential for the DCTN activity of driving retrograde transport in cells [4-7]. Specific functions of individual DCTN subunits have also been reported. In human epidermal melanocytes, DCTN1 expression was detected in the dendrite tips, and DCTN2 expression was also localized in the perinuclear area and dendrite tips [16]. Notably, overexpression of DCTN3 is lethal to cells, and overexpression of DCTN2 leads to the disruption of the Golgi apparatus [6,22]. Mutations of DCTN1 have been identified in many serious motor neuron diseases, including ALS, ALS-frontotemporal dementia ALS/FTD, and PS [23-28], and a mutation in DCTN4 was linked to Pa airway infection, chronic Pa infection, and mucoid Pa in cystic fibrosis patients [29,30]. Finally, the interaction between DCTN4 and the P-type ATPase (ATP7B) is a key component of Wilson disease [31].

Most studies to date have investigated associations between DCTN genes and nervous system diseases, infection diseases, both through functional studies and mutational studies. Only a few reports have been published on connections between DCTN genes and cancer, although the DCTN family may play a crucial role in some cancers via their effect of the function and structure of DCTN. For example, it was reported that DCTN1 and DCTN2 could coprecipitate with human EB1, which may be correlated with human adenomatous polyposis coli in vivo [32]. Most relevant to our study, the intronic regions of DCTN6 pre-mRNA were shown to interact with the SPRIGHTLY lncRNA of melanoma [15]. Still, there were no reports about the connection between DCTN mRNA expression and the prognosis of CM. Here, we used data for DCTN mRNA expression and clinical information in CM patients from the OncoLnc database according to the Cancer Genome Atlas to investigate the correlation of DCTN family mRNA expression and prognosis in CM patients and assess whether expression of any DCTN genes, individually or in combination, could be used as biomarkers for predicting prognosis in CM.

In our study, we found high expression levels of DCTN2 and DCTN5 in normal tissue, while the Kaplan-Meier curves from univariate survival analysis showed that low expression of DCTN2 and DCTN5 in tumor tissue was correlated with favorable OS in all CM patients, suggesting that DCTN2 and DCTN5 act as oncogenes in CM. In contrast, DCTN6 was highly expressed in primary skin tumor tissue, and high expression of DCTN6 was found to be correlated with favorable OS. This may be because DCTN6 can act as a tumor suppressor. DCTN2 was downregulated in CM but upregulated in the SJSA-1 osteosarcoma cell line [14], indicating that DCTN2 may have different roles in different cancers.

Multivariate survival analysis confirmed the results of the univariate survival analysis, except for DCTN1. Multivariate survival analysis showed that a low expression of DCTN1 was correlated with favorable prognosis, whereas in univariate survival analysis, neither low nor high expression of DCTN1 was found to be correlated with OS. This may be due to adjustment in the Cox proportional hazards regression model, which indicated that DCTN1 expression affects CM prognosis. Expression of both DCTN1 and DCTN2 was previously found in human epidermal melanocytes [16], suggesting that the mutations of DCTN1 and DCTN2 are important components of CM, and downregulated expression of these 2 genes may predict a favorable prognosis in CM.

The joint-effects analysis showed that expression of DCTN1, DCTN2, and DCTN5 at low levels and DCTN6 at a high level were correlated with a favorable OS in CM patients. In contrast, high expression of DCTN1, DCTN2, and DCTN5 and low expression of DCTN6 were correlated with poor OS.

There were some limitations in our study. First, a larger sample size is required to increase the reliability of our results. Second, more clinical data are required from further studies, including smoke and alcohol history, main tumor size, tumor sites in areas exposed or not exposed to the sun, anti-therapy status, radical resection status, family history, and pathological diagnosis, as well as data for more races among Asian and African populations. Thirdly, the patient data in our study were exclusively from a single source; therefore, the results need to be validated in another group. Despite these limitations, our study is the first to report that downregulation of DCTN1, DCTN2, and DCTN5 and upregulation of DCTN6 in CM are associated with a favorable prognosis. These 4 genes may be used as a prognostic biomarker panel in CM patients.

Conclusions

Our study demonstrated that low mRNA expression of DCTN1, DCTN2, and DCTN5 and high mRNA expression of DCTN6 were individually and jointly correlated with favorable prognosis among CM patients. Those 4 genes may be used as potential prognostic biomarkers in CM patients. Due to the small sample size and limited clinical information available in this study, these results need to be confirmed in further studies.