Prognostic and Clinicopathological Significance of CCND1/Cyclin D1 Upregulation in Melanomas: A Systematic Review and Comprehensive Meta-Analysis

cancers Systematic Review Prognostic and Clinicopathological Significance of CCND1/Cyclin D1 Upregulation in Melanomas: A Systematic Review and Comprehensive Meta-Analysis Lucía González-Ruiz 1, Miguel Ángel González-Moles 2,3,4,* , Isabel González-Ruiz 2,3, Isabel Ruiz-Ávila 3,5 and Pablo Ramos-García2,3   Citation: González-Ruiz, L.; González-Moles, M.Á.; González-Ruiz, I.; Ruiz-Ávila, I.; Ramos-García, P. Prognostic and Clinicopathological Significance of CCND1/Cyclin D1 Upregulation in Melanomas: A Systematic Review and Comprehensive Meta-Analysis. Cancers 2021,13, 1314. https:// doi.org/10.3390/cancers13061314 Academic Editor: Eduardo Nagore Received: 20 January 2021 Accepted: 9 March 2021 Published: 15 March 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Dermatology Service, Ciudad Real General University Hospital, 13005 Ciudad Real, Spain; [email protected] 2School of Dentistry, University of Granada, 18010 Granada, Spain; [email protected] (I.G.-R.); [email protected].es (P.R.-G.) 3Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain; [email protected] 4WHO Collaborating Group for Oral Cancer, 1211 Geneva, Switzerland 5Pathology Service, San Cecilio Hospital Complex, 18016 Granada, Spain *Correspondence: [email protected] Simple Summary: The incidence of cutaneous melanoma is increasing worldwide, currently responsible for 287,723 new cases and 60,712 deaths per year (GLOBOCAN, IARC, WHO). It should be also highlighted that some less frequent subtypes of melanomas—i.e., acral, uveal, and mucous melanoma—are responsible for significant morbidity associated with metastasis, responding typically worse to newer therapies. Therefore, new biomarkers are needed to improve the prognosis in individual patients. In this sense, the present study showed that CCND1/cyclin D1 upregulation is a common molecular oncogenic alteration in melanomas that probably favors the growth and expansion on cutaneous primary melanomas. Furthermore, immunohistochemical cyclin D1 overexpression strongly predicted a higher Breslow thickness, currently considered the most relevant prognostic factor in individual patients with melanomas. Finally, special attention should be paid to the CCND1/cyclin D1 complex in mucosal melanomas, whose upregulation was strikingly altered. Abstract: Our objective was to evaluate the prognostic and clinicopathological significance of cyclin D1 (CD1) overexpression/CCND1 amplification in melanomas. We searched studies published before September 2019 (PubMed, Embase, Web of Science, Scopus). We evaluated the quality of the studies included (QUIPS tool). The impact of CD1 overexpression/CCND1 amplification on overall survival and relevant clinicopathological characteristic were meta-analyzed. We performed heterogeneity, sensitivity, small-study effects, and subgroup analyses. Forty-one studies and 3451 patients met inclusion criteria. Qualitative evaluation demonstrated that not all studies were performed with the same rigor, finding the greatest risk of bias in the study confounding domain. Quantitative evaluation showed that immunohistochemical CD1 overexpression had a statistical association with Breslow thickness (p= 0.007; OR = 2.09,95% CI = 1.23–3.57), significantly higher frequency of CCND1/cyclin D1 abnormalities has been observed in the primary tumor compared to distant metastases (p= 0.004), revealed also by immunohistochemical overexpression of the protein (p< 0.001; OR = 0.53, 95% CI = 0.40–0.71), while the CCND1 gene amplification does not show association (p= 0.43); while gene amplification, on the contrary, appeared more frequently in distant metastases (p= 0.04; OR = 1.70, 95% CI = 1.01–2.85) and not in the primary tumor. In conclusion, CCND1/cyclin D1 upregulation is a common molecular oncogenic alteration in melanomas that probably favors the growth and expansion of the primary tumor. This upregulation is mainly consequence to the overexpression of the cyclin D1 protein, and not to gene amplification. Keywords: melanoma; cyclin D1; CCND1; systematic review; meta-analysis Cancers 2021,13, 1314. https://doi.org/10.3390/cancers13061314 https://www.mdpi.com/journal/cancers Cancers 2021,13, 1314 2 of 21 1. Introduction The incidence of cutaneous melanoma is currently 287,723 new cases, this tumor being responsible for 60,712 deaths per year (GLOBOCAN, IARC, WHO) [ 1 ]. These figures are increasing and is expected to continue growing worldwide [ 2 ] as a consequence essentially of excessive exposure to sunlight related to leisure, which undoubtedly will increase the health investment dedicated to the diagnosis and treatment of this tumor [ 3 ]. It should be also highlighted that some less frequent subtypes of melanomas—i.e., acral, uveal, and mucous melanomas—are responsible for significant morbidity associated with metastasis, responding typically worse to newer therapies [ 4 ]. Although the use of advanced therapies based on new drugs approved by the FDA have been applied to treatment since 2011 [ 5 ], all of the aforementioned advises the development of extensive research, which provides enough scientific evidence especially on new therapeutic targets, with the aim of developing new drugs specifically aimed toward these new targets that can improve patient prognosis. Cyclin D1, encoded by the CCND1 gene located on chromosome band 11q13, promotes cell cycle progression during the G1-S phase [ 6 ]. Since some years, it has been known that CCND1 can act as a relevant oncogene in some types of tumors, having established in addition to its pro-proliferative activity several others emerging oncogenic functions including increase of cell migration capacity, inhibition of cell differentiation, inhibition of DNA repair, and involvement in mitochondrial metabolism [ 7 ]. The canonical CCND1/cyclin D1 general role—i.e., sustaining cell proliferation—has also been also shown in in vitro [ 8 – 10 ] and in vivo [ 11 – 13 ] recent studies in melanoma. Although no studies have been designed to provide direct evidence of the other emerging functions of cyclin D1 in melanoma, some studies have observed an increase in cell migration after the activation of upstream regulators of cyclin D1 in melanomas [ 14 , 15 ]. Finally, the pro-proliferative activity of cyclin D1 has also been shown in melanomas in population-based studies, verified through the evaluation of the ki-67 proliferative index [16–18]. Gene amplification is the main mechanism of CCND1/cyclin D1 upregulation in cancer [ 19 – 21 ], although in melanoma, other genetic alterations seem to be also involved in the dysregulation of the cyclin D1 function, including mutations, polymorphisms, chromosomal translocations, and the activation of several oncogenic pathways (MAPK, PI3K, Wnt, NFκβ ) [ 22 ]. CCND1/cyclin D1 upregulation has been reported to be associated with reduced survival and lack of response to antitumor treatment in melanoma [ 22 – 24 ]. CCND1/cyclin D1 have also been proposed as a candidate therapeutic target, because their transcription depends on several upstream pathways essential for tumor development. Cyclin D1 could be targeted in melanoma in several ways—extensively reviewed in Yadav et al. (2015) and González-Ruiz et al. (2020)—by inhibition of chromosome band 11q13 and/or CCND1; by direct inhibition of cyclin D1; by CDK inhibition, acting upstream in melanoma-related pathways involving cyclin D1; or combining agents that act against cyclin D1 with other antitumor drugs. This latter therapy has been proposed as the most promising option [ 22 ], particulary the combination of BRaf inhibitory drugs with cyclin D1-CDK4/6 inhibitory agents (i.e., abemaciclib [LY2835219], palbociclib [PD0332991], or ribociclib [LEE011]), with some ongoing or completed phase II trials and clinical trials (NCT02202200, NCT02159066, NCT01820364) [13,25,26]. CCND1/cyclin D1 upregulation could also have specific importance in melanoma context as in the prediction of clinicopathological (e.g., higher Breslow thickness [ 27 ] or clinical stage [ 28 ]) and/or prognostic (e.g., poor survival [ 29 ]) outcomes. Although published data support an empirical assumption about the direction of the effect, and our hypothesis is that CCND1/cyclin D1 could behave as an useful biomarker, some primary-level studies have reported disparities or a lack of statistical significance [30,31]. With this background, the present paper aims to qualitatively and quantitatively evaluate for first time, through a systematic review and comprehensive meta-analysis, the available scientific evidence on the clinicopathological and prognostic implications of CCND1 gene amplification and cyclin D1 immunohistochemical protein overexpression in melanomas. Cancers 2021,13, 1314 3 of 21 2. Materials and Methods The present systematic review and meta-analysis complied with PRISMA guidelines [ 32 ] and closely followed the criteria of Cochrane Prognosis Methods Group [ 33 ], Cochrane Handbook for Systematic Reviews of Interventions [ 34 ], and Centre for Reviews and Dissemination (CRD)’s guidance for undertaking reviews in healthcare [35]. 2.1. Protocol In order to minimize the risk of bias and improve the transparency, precision, and integrity of our systematic review and meta-analysis, a protocol on its methodology was registered a protocol in PROSPERO international prospective register of systematic reviews (www.crd.york.ac.uk/PROSPERO (accessed on 15 March 2021), registration number CRD42020153664; a copy of the protocol was included in the Supplementary Materials, pp. 60–64) [ 36 ]. The protocol adhered to PRISMA-P guidelines in order to ensure a rigorous approach [37]. 2.2. Search Strategy We searched PubMed, Embase, Web of Science, and Scopus databases for studies published before the search date (upper limit = September 2019), with no lower date limit. Searches were conducted by combining thesaurus terms used by the databases (e.g., MeSH and EMTREE) with free terms (the syntax adapted to each database can be found in the Supplementary Materials, Table S1, p. 5), and constructed to maximize sensitivity. We also manually screened the reference lists of retrieved studies for additional relevant studies. All references were managed using Mendeley v.1.19.3 (Elsevier. Amsterdam, The Netherlands); duplicate references were eliminated using this software. 2.3. Selection Criteria Study eligibility criteria were applied independently by two authors (LGR and PRG). Any discrepancies were resolved by consensus with the senior author (MAGM). Inclusion criteria: (1) Original research studies published in English. (2) Evaluation of CCND1 amplification or cyclin D1 overexpression in human cutaneous, uveal or mucosal melanomas. (3) Analysis of the association of CCND1 and/or cyclin D1 upregulation with clinicopathological and/or prognostic variables. Given the lack of international consensus standards to define survival endpoints, we included studies that used the direct designation of the terms overall survival (OS) or disease-free survival (DFS). OS was defined as the time elapsed from date of diagnosis/surgery to date of death by any cause. DFS was defined as the time elapsed from surgery to the detection of locoregional or distant recurrence or to death without recurrence. Other terms defined in the original studies as in the present article or compatible with our definitions (e.g., relapse-free survival) were also accepted. (4) The author names, affiliations, recruitment periods, and setting were examined to determine whether studies were conducted in the same study population. In such cases, we included the most recent study or that which published more complete data. Exclusion criteria: (1) Retractions, reviews, meta-analyses, case reports, editorials, letters, abstracts of scientific meetings, personal opinions or comments, book chapters, and any study in a language other than English; (2) Studies with no melanoma cases; (3) Reports of in vitro or animal experiments; (4) Evaluations of CCND1 gene alterations other than gene amplification (e.g., polymorphisms) and studies of chromosome band 11q13 that do not specifically discriminate the CCND1 gene; (5) No analysis of the relationship of upregulation with clinicopathological or prognostic variables; (6) Insufficient data for the estimation of odds ratios (ORs) for clinicopathological variables and, in studies only reporting time-to-event variables (OS/DFS), the absence of hazards ratios (HRs) with 95% confidence intervals (CIs) or the lack of adequate data for their calculation by survival analysis. Cancers 2021,13, 1314 4 of 21 We first screened the titles and abstracts of retrieved articles to select those that appeared to meet the review eligibility criteria. In a second phase, we examined the full texts of the selected articles and removed any that did not fulfill these criteria. 2.4. Data Extraction Two authors (LGR and PRG) independently extracted data from the articles selected for full text study in a standardized fashion using an Excel data collection template (Excel v.2015, Microsoft. Redmond, WA, USA). The extracted data were then reviewed by the senior author (MAGM). Discrepancies were solved by consensus. Data were gathered on: first author, year of publication, country and continent, sample size, alteration under study (CCND1 amplification and/or cyclin D1 overexpression), type of melanomas, location, recruitment and follow-up periods, methodology, and the upregulation frequency. Furthermore, in immunohistochemical studies, information was also recorded on the cutoff point, anti-cyclin D1 antibody, and intracellular immunopositivity pattern (nuclear/cytoplasmic). 2.5. Evaluation of Quality and Risk of Bias Two authors (LGR and PRG) evaluated the quality of studies and the risk of bias using the Quality in Prognosis Studies (QUIPS) tool of the Cochrane Prognosis Methods Group [ 38 ], which explores six main potential bias domains: (1) Study participation, (2) Study attrition, (3) Prognostic factor measurement, (4) Outcome measurement, (5) Study confounding, and (6) Statistical analysis and reporting [39]. The potential risk of bias was evaluated as low, moderate, or high for each domain. Discrepancies were resolved with a senior author (MAGM). 2.6. Statistical Analysis CCND1 amplification was considered “positive” or “negative” according to the methodology adopted in each study. Cyclin D1 expression was considered “high” or “low” according to the cutoff values applied in each study. We used hazards ratio (HR) with 95% confidence intervals (CIs) to estimate the impact of CCND1/cyclin D1 upregulation on time-to-event variables (OS and DFS). When reported, HRs and 95% CIs were directly extracted from the original articles. If HRs were not explicitly provided by the authors, they were calculated using the methods described in Parmar et al. [ 40 ] and Tierney et al. [ 41 ]. When HRs were evaluated in both univariable and multivariable models, we used the data from the multivariable model, which reflect a greater adjustment for potentially confounding variables [ 42 ]. When data were only depicted in Kaplan–Meier curves or HRs and 95% CIs were only expressed graphically, data were measured and extracted using Engauge Digitizer 4.1 (open-source digitizing software developed by M. Mitchell). In meta-analyses, HRs and 95% CIs were pooled using a random-effect model (REM, Der Simonian and Laird (D-L) method), because logic dictates the presence of a considerable degree of between-study heterogeneity. Clinicopathological parameters were meta-analyzed using odds ratios (OR) with 95% CIs. As the authors only reported raw data, this information was collected and re-expressed as ORs, which were pooled by Mantel–Haenszel’s method, using a fixed-effect model. A random-effects model using the inverse variance method was not considered a priori, because when data are sparse, heterogeneity is uncommon and the Mantel–Haenszel weighting method has been shown to have better statistical properties [ 43 ]. Peto’s method was not considered because many studies presented unbalanced arms. Finally, meta-analyses were carried out trying to estimate the overall frequency of cyclin D1/CCND1 expression and amplification levels for the different types of melanoma under investigation (i.e., cutaneous [nodular, superficial spreading, lentigo malignant, and acral melanoma], uveal and mucosal). To achieve this, pooled proportions (PP) with their corresponding 95% CIs were estimated. Proportions in individual studies were calculated by extracting raw numerators (number of cases with cyclin D1 high expression or CCND1 positive amplification) and denominators (total number of melanoma cases). The 95% Cancers 2021,13, 1314 5 of 21 CIs were constructed based on the score-test statistic [ 44 ].The influence of studies with extremely small or high values (0 or 100, or close to 0 or 100) was minimized by using Freeman–Tukey double-arcsine transformation to stabilize the variance of proportions [ 45 ]. PP were estimated using a REM (D-L method). In all conducted meta-analyses, forest plots were constructed to graphically represent the overall effect and for its subsequent analysis (a p-value < 0.05 was considered statistically significant) [ 46 ]. Heterogeneity between studies was checked using the χ2 based Cochran’s Q test. Given the low statistical power of this test, p< 0.1 was considered significant. We also used Higgins I 2 statistic to quantify the percentage heterogeneity, considering values of 25, 50, and 75% to indicate low, moderate, and high heterogeneity, respectively [ 46 , 47 ]. Additionally, subgroup analyses—preplanned in our protocol—were performed (stratifying by CCND1/cyclin D1 upregulation, geographic area, cut-off value, and immunostaining pattern) to identify potential sources of heterogeneity and to explore the relationship between the meta-analyzed parameters in these subgroups. Sensitivity analyses were additionally carried out to test the reliability of combined results, evaluating the influence of each individual study on the final estimations for each meta-analysis performed [ 48 ]. For this, the “leave-one-out” method was used (i.e., the meta-analyses were repeated sequentially, omitting one study at a time). Funnel plots were constructed and the Egger regression test (p Egger < 0.1) was applied to evaluate small-study effects, such as publication bias [ 49 , 50 ]. Stata version 14.1 (Stata Corporation, College Station, TX, USA) was employed for all tests, using commands written by the user. 3. Results 3.1. Literature Search The flow diagram in Figure 1depicts search, study selection process, and the results obtained. A total of 3175 records published before September 2019 were retrieved from PubMed (n= 492), Embase (n= 1110), Web of Science (n= 728), and Scopus (n= 845). One additional record was also identified handsearching the references lists of the studies included. After duplicates removal, 1428 studies were considered potentially eligible. After the titles and abstracts screening, 109 records were selected for full-text evaluation, of which 68 did not meet all inclusion criteria, leaving a final sample of 41 studies (the references of the studies included in the systematic review and meta-analysis are listed in the Supplementary Materials, pp. 56–59). 3.2. Study Characteristics Table 1summarizes the main characteristics of the 41 studies analyzing the prognostic and clinicopathological implications of CCND1/cyclin D1 upregulation in 3451 melanomas. CyclinD1proteinoverexpressionwasassessedby21studiesin1473melanomas (range: 7–245); CCND1 gene amplification was also analyzed by 22 studies in 2096 melanomas (range: 6– 514). Two studies analyzed both CCND1/cyclin D1 alterations (118 melanomas) [ 24 , 51 ]. The studies were conducted in 6 continents (Europe, 17 studies/1727 melanomas; North America, 12 studies/498 melanomas; Asia, 5 studies/893 melanomas; South and Central America, 3 studies/110 melanomas; and two global multicentric studies, 60 melanomas) and 17 countries (Australia, 2 studies; Brazil, 1 study; China, 3 studies; France, 1 study; Germany, 4 studies; Greece, 1 study; Hungary, 2 studies; Italy, 3 studies; Japan, 2 studies; global multicentric, 2 studies (Australia-USA, and Germany-Japan-South Korea-USA); South and Central America multicentric, 2 studies (Bolivia-Brazil and Brazil-Guatemala-Mexico-Peru); Norway, 2 studies; Spain, 3 studies; Switzerland, 1 study; and USA, 12 studies). Table S2 (Supplementary Materials, pp. 6–12) exhibits in more detail the characteristics (type of melanoma, affected sites, and methods) gathered from each study. Cancers 2021,13, 1314 6 of 21 Cancers 2021, 13, x 6 of 23 Figure 1. Flow diagram of the identification and selection of relevant studies, analyzing the prognostic and clinicopathological significance of CCND1/cyclin D1 alterations in melanomas. 3.2. Study Characteristics Table 1 summarizes the main characteristics of the 41 studies analyzing the prognostic and clinicopathological implications of CCND1/cyclin D1 upregulation in 3451 melanomas. Cyclin D1 protein overexpression was assessed by 21 studies in 1473 melanomas (range: 7–245); CCND1 gene amplification was also analyzed by 22 studies in 2096 melanomas (range: 6–514). Two studies analyzed both CCND1/cyclin D1 alterations (118 melanomas) [24,51]. The studies were conducted in 6 continents (Europe, 17 studies/1727 melanomas; North America, 12 studies/498 melanomas; Asia, 5 studies/893 melanomas; South and Central America, 3 studies/110 melanomas; and two global multicentric studies, 60 melanomas) and 17 countries (Australia, 2 studies; Brazil, 1 study; China, 3 studies; France, 1 study; Germany, 4 studies; Greece, 1 study; Hungary, 2 studies; Italy, 3 studies; Japan, 2 studies; global multicentric, 2 studies (Australia-USA, and Germany-Japan-South Korea-USA); South and Central America multicentric, 2 studies (Bolivia-Brazil and Brazil-Guatemala-Mexico-Peru); Norway, 2 studies; Spain, 3 studies; Switzerland, 1 study; and USA, 12 studies). Table S2 (supplementary materils, pp. 6–12) exhibits in more detail the characteristics (type of melanoma, affected sites, and methods) gathered from each study. Table 1. Summarizes the main characteristics of reviewed studies. Table S2 (in Supplementary Materials, pp. 6–12) exhibits in detail the characteristics (type of melanoma, affected sites, and Figure 1. Flow diagram of the identification and selection of relevant studies, analyzing the prognostic and clinicopathological significance of CCND1/cyclin D1 alterations in melanomas. Table 1. Summarizes the main characteristics of reviewed studies. Table S2 (in Supplementary Materials, pp. 6–12) exhibits in detail the characteristics (type of melanoma, affected sites, and methods) of each study. * —Two studies analyzed both CCND1/cyclin D1 alterations (118 melanomas). Total 41 Studies Year of publication 1999–2019 Number of melanomas analyzed Total 3451 Sample size, range 6–514 Cyclin D1 protein overexpression * Total 21 studies (1473 melanomas) Sample size, range 7–245 CCND1 gene amplification * Total 22 studies (2096 melanomas) Sample size, range 6–514 Geographical region Europe 17 studies (1727 melanomas) North America 12 studies (498 melanomas) Asia 5 studies (893 melanomas) South and Central America 3 studies (110 melanomas) Australia 2 studies (163 melanomas) Global multicentric 2 studies (60 melanomas) Total 6 continents, 17 countries Cancers 2021,13, 1314 7 of 21 3.3. Qualitative Evaluation Qualitative analysis was conducted using the QUIPS tool, which evaluates potential sources of bias in six domains (Figure 2). Figure 2. Evaluation of the risk of bias using the Quality in Prognosis Studies (QUIPS) tool (the references cited in this figure are listed in Supplementary Materials). Study participation. The studies had a high (53.66%), moderate (29.27%), or low (17.07%) risk of bias (Figure 2), related to the lack of reporting relevant data (type of melanomas, affected site, age, sex, recruitment period, and/or relevant parameters with prognostic implications, e.g., Breslow thickness). Study attrition. The studies evaluated had a high (4.88%), moderate (9.76%), or low (85.36%) risk of bias (Figure 2), mainly due to the lack of information on the follow-up period. The attempt to gather information on patients lost in the follow up period was not described by the studies. Prognostic factor measurement. The studies had a high (24.39%), moderate (9.76%), or low (65.85%) risk of bias (Figure 2). The biases encountered were due to insufficient information on the techniques used to measure the levels of amplification or overexpression (e.g., laboratory methods or scoring system) or questionable methodologies (e.g., use of inappropriate cutoff points). In immunohistochemical studies, insufficient information about anti-cyclin D1 antibodies, immunopositivity pattern (nuclear or cytoplasmic), or the failure to report images of the technique. Outcome measurement. The studies had a high (34.15%), moderate (12.19%), or low (53.66%) risk of bias (Figure 2), due to failure to define the survival outcomes evaluated (this is essential, due to the lack of international consensus on survival endpoints). Furthermore, the reporting of N and M status in combination, or an inadequate measurement of prognostic parameters (e.g., optimized cut-off points for clinicopathological variables to obtain significant p-values). Study confounding. The studies had a high (95.24%) or moderate (4.76%) risk of bias (Figure 2), due to the failure considering potential confounders. None of the studies defined a priori the confounding factors under evaluation or a posteriori discussed potentially candidate factors or the biological principles by which they might distort the impact of CCND1/cyclin D1 upregulation on study parameters. Cancers 2021,13, 1314 8 of 21 Statistical analysis and reporting. The studies had a high (65.86%), moderate (17.07%), or low (17.07%) risk of bias (Figure 2) due to selective outcome reporting, lack of essential information in survival analysis (i.e., Kaplan–Meier courves or hazard ratios with confidence intervals), suspected data errors, or an inappropriate statistical analysis. 4. Quantitative Evaluation (Meta-Analysis) 4.1. Association between CCND1/Cyclin D1 Upregulation and Cutaneous Melanoma 4.1.1. Upregulation Frequency Upregulation was a frequent phenomenon in acral melanomas (overexpression: PP = 62.07%, 95% CI = 31.17–89.27; amplification: PP = 25.06%, 95% CI = 15.80–35.44), and less frequent—although also present—in nodular (overexpression: PP = 13.69%, 95% CI = 2.33–29.67; amplification: PP = 22.66%, 95% CI = 3.65–48.29), superficial spreading (overexpression: PP = 36.72%, 95% CI = 17.57–57.90; amplification: PP = 15.79%, 95% CI = 3.44–32.85), and lentigo malignant melanomas (overexpression: PP = 52.24%, 95% CI = 33.36–70.82; amplification: PP = 16.16%, 95% CI = 2.53–35.62) (Table 2, Figures S1–S4, Supplementary Materials, pp. 13–16). Although considerable degrees of heterogeneity were reached for the alterations analyzed together, the subgroups were more homogeneous after applying the stratification by overexpression and amplification. 4.1.2. Overall Survival (OS) A non-significant association was found for both cyclin D1 overexpression (HR = 1.00, 95% CI = 0.64–1.58, p= 0.99) and CCND1 amplification (HR = 1.32, 95% CI = 0.81–1.52, p= 0.11) (Table 2, Figure S5, Supplementary Materials, p. 17). There was no evidence of heterogeneity among studies (p het = 0.30, I 2 = 16.7%). In the stratified analyses by geographic area and immunohistochemical pattern, the results did not vary significantly among the subgroups under analysis (Table 2, Figures S6 and S7, Supplementary Materials, pp. 18, 19). Additional planned analyses (by anti-cyclin D1 antibody and cutoff point) were not possible for any parameter due to the heterogeneous and small amount of data reported by the studies. 4.1.3. Disease-Free Survival (DFS) CCND1/cyclin D1 upregulation was not significantly associated with poor DFS (HR = 1.45, 95% CI = 0.60–3.51, p= 0.41) (Table 2, Figure S8, Supplementary Materials, p. 20). As only 2 studies were included for this variable, subgroups analyses were not performed. 4.1.4. Breslow Thickness A significant large effect size (OR = 2.09, 95% CI = 1.23–3.57, p= 0.007) was found with cyclin D1 overexpression, while this association was not found for gene amplification (OR = 1.21, 95% CI = 0.75–1.95, p= 0.43) (Table 2, Figure 3). Heterogeneity across studies was not evident (p het = 0.52, I 2 = 0.0%). In the stratified analysis, the European (OR = 1.91, 95% CI = 1.15–3.19, p= 0.01) subgroup maintained the significant association (Table 2, Figure S9, Supplementary Materials, p. 21). Cancers 2021,13, 1314 9 of 21 Table 2. Cyclin D1/CCND1 upregulation in melanoma: frequency, clinicopathological, and prognostic significance. Meta-Analyses No. of Studies No. of Cases Wt Stat. Model Pooled Data Hetero Geneity Supplementary Materials a ES (95% CI) p-value phet I2(%) CUTANEOUS MELANOMA Frequency of cyclin D1/CCND1 upregulation Nodular melanoma b15 219 D-L REM PP = 19.19% (7.12–34.06) - <0.001 70.63 Figure S1, p. 13 Nodular melanoma by alteration cFigure S1, p. 13 Cyclin D1 overexpression 7 103 D-L REM PP = 13.69% (2.33–29.67) - 0.13 39.69 CCND1 amplification 8 116 D-L REM PP = 22.66% (3.65–48.29) - <0.001 80.92 Superficial spreading melanoma b15 553 D-L REM PP = 24.71% (13.29–37.84) - <0.001 86.26 Figure S2, p. 14 Superficial spreading melanoma by alteration cFigure S2, p. 14 Cyclin D1 overexpression 7 325 D-L REM PP = 36.72% (17.57–57.90) - <0.001 88.53 CCND1 amplification 8 228 D-L REM PP = 15.79% (3.44–32.85) - <0.001 83.30 Lentigo malignant melanoma b5 63 D-L REM PP = 34.73% (10.61–63.09) <0.001 76.77 Figure S3, p. 15 Lentigo malignant melanoma by alteration cFigure S3, p. 15 Cyclin D1 overexpression 2 29 D-L REM PP = 52.24% (33.36–70.82) - - - CCND1 amplification 3 34 D-L REM PP = 16.16% (2.53–35.62) - 0.27 23.42 Acral melanoma b7 98 D-L REM PP = 30.90% (18.27–44.86) - 0.15 36.98 Figure S4, p. 16 Acral melanoma by alteration cFigure S4, p. 16 Cyclin D1 overexpression 2 13 D-L REM PP = 62.07% (31.17–89.27) - - - CCND1 amplification 5 85 D-L REM PP = 25.06% (15.80–35.44) - 0.44 0.00 Survival parameters Overall survival d7 1022 D-L REM HR = 1.11 (0.81–1.52) 0.51 0.30 16.7 Figure S5, p. 17 Overall survival by alteration eFigure S5, p. 17 Cyclin D1 overexpression 5 399 D-L REM HR = 1.00 (0.64–1.58) 0.99 0.26 24.3 CCND1 amplification 2 623 D-L REM HR = 1.32 (0.81–1.52) 0.11 - - Overall survival by geographic area eFigure S6, p. 18 Asian 2 592 D-L REM HR = 1.30 (0.92–1.82) 0.13 - - Non-Asian 5 430 D-L REM HR = 1.03 (0.63–1.69) 0.90 0.23 28.3 Overall survival by IHQ pattern eFigure S7, p. 19 Nuclear 3 235 D-L REM HR = 0.77 (0.50–1.17) 0.22 0.58 0.0 Nuclear and cytoplasmic 1 78 - - - - - - Not available 1 86 - - - - - - Clinicopathological parameters Disease-free survival d2 70 D-L REM HR = 1.45 (0.60–3.51) 0.41 - - Figure S8, p. 20 Breslow thickness d16 760 M-H FEM OR = 1.54 (1.08–2.20) 0.02 0.52 0.0 Manuscript, Figure 3 Breslow thickness by alteration e Cyclin D1 overexpression 7 264 M-H FEM OR = 2.09 (1.23–3.57) 0.007 0.27 20.4 CCND1 amplification 9 496 M-H FEM OR = 1.21 (0.75–1.95) 0.43 0.87 0.0 Breslow thickness by geographic area eFigure S9, p. 21 Asia 2 120 M-H FEM OR = 1.31 (0.63–2.74) 0.47 - - Cancers 2021,13, 1314 16 of 21 important role in the development of the metastatic process, which could explain its lack of value as a predictor of survival in melanomas, since distant metastases are the main cause of death in this tumor. According to our qualitative evaluation, carried out using the Quality in Prognosis Studies (QUIPS) tool of the Cochrane Prognosis Methods Group [38], all studies were not conducted with the same rigor. The domain “study confounding” harbored the highest risk of potential bias, caused by the failure considering or measuring confounding factors. Future studies assessing the prognostic and clinicopathological significance of CCND1/cyclin D1 in melanomas should consider the potential biases reported in the present systematic review and meta-analysis, using the QUIPS tool to improve the validity of findings and facilitating comparisons. Some potential limitations of our meta-analysis should be discussed. First, the restriction to studies published in English may imply a loss of information published in other languages, which would have been missed. Second, consistent heterogeneity was observed in some variables (mainly in meta-analyses of proportions). In order to overcome this limitation, a random-effect statistical model was applied in these meta-analyses. We also conducted several secondary stratified analyses, obtaining more homogeneous subgroups of studies. One potential source of methodological and statistical heterogeneity was the combination CCND1 amplification and cyclin D1 overexpression at protein level (assessed using immunohistochemistry), as observed after several stratifications. In general, the amplification-based meta-analyses seem less significant in many-analyses and the reason for this phenomenon could be due to various explanations among which are the following: CCND1 amplification was not evaluated homogeneously across the studies, so a heterogeneity extent could be due to the inherent differences of the wide range of experimental methods; Primary-level studies also presented differences in their statistical study designs, and some considered the number of copies as a continuous variable (i.e., means of copies with standard deviations), so when papers did not openly report individual patient data, those reporting continuous variables had to be excluded under the “lack of essential data” criterion, since in our meta-analysis, we estimated effect sizes for categorical variables (i.e., odds ratios, hazard ratios, and pooled proportions); Finally, the non-significant results in amplification-based meta-analyses could also be due to the low sample sizes of some included cohorts, with statistical analyses in underpowered conditions, yielding non-significant results mainly due to type II errors (i.e., false negative results), so, another important recommendation of the present work is the development of future better designed studies—preferably prospective cohorts—assessing CCND1 amplification on higher sample sizes. Another relevant recommendation, as previously commented, is the necessity of future integrative bioinformatics analyses in melanomas in order to comprehensively describe the somatic copy number alteration linked to 11q13/CCND1 from massive datasets (e.g., TCGA, ICGC projects, or from Gene Expression Omnibus (GEO). Specific bioinformatics study design could better respond to additional research questions that could not be addressed in this meta-analysis design (e.g., relationships between CCND1 amplification and CCND1 RNA expression). Third, some variables (e.g., mitotic rate or ulceration) were reported by a low number of studies and their meta-analyses were probably underpowered to detect significant differences. Future studies should further elucidate the potential influence of CCND1/cyclin D1 on these parameters. Finally, some studies reported a low amount of data (e.g., anti-cyclin D1 antibody or cutoff points), limiting additional analyses. The lack of essential information in the survival analysis (i.e., HR or 95% CI) was countered estimating HR from the data provided by these studies, following the methodology of Tierney et al. [ 41 ] and Parmar et al. [ 40 ]. Despite the above limitations, the results of our meta-analysis are robust, as demonstrated by sensitivity and small-study effects analyses, and as depicted in forest plots. Cancers 2021,13, 1314 17 of 21 6. Conclusions In conclusion, CCND1/cyclin D1 upregulation is a common molecular oncogenic alteration in melanomas that probably favors the growth and expansion of the primary tumor. This upregulation is mainly a consequence to the overexpression of the cyclin D1 protein, and not to gene amplification, which probably suggests the inclusion of the immunohistochemical expression of cyclin D1 in the global evaluation of melanomas, and opens the possibility of its use as a therapeutic target. Supplementary Materials: The following are available online at https://www.mdpi.com/2072-6 694/13/6/1314/s1, Table S1. Search strategy for each database, number of results, and execution date; Table S2. Characteristics of studies; Table S3. Sensitivity analysis of the studies pooled in the meta-analysis on the association between CCND1/cyclin D1 alterations and overall survival in cutaneous melanoma; Table S4. Sensitivity analysis of the studies pooled in the meta-analysis on the association between CCND1/cyclin D1 alterations and Breslow Thickness in cutaneous melanoma; Table S5. Sensitivity analysis of the studies pooled in the meta-analysis on the association between CCND1/cyclin D1 alterations and Ulceration in cutaneous melanoma; Table S6. Sensitivity analysis of the studies pooled in the meta-analysis on the association between CCND1/cyclin D1 alterations and Clark in cutaneous melanoma; Table S7. Sensitivity analysis of the studies pooled in the metaanalysis on the association between CCND1/cyclin D1 alterations and Type of cutaneous melanoma; Table S8. Sensitivity analysis of the studies pooled in the meta-analysis on the association between CCND1/cyclin D1 alterations and Distance metastasis vs primary in cutaneous melanoma; List of studies included in this systematic review and meta-analysis; and copy of protocol. Figure S1. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Nodular Melanomas; Figure S2. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Superficial Spreading Melanomas; Figure S3. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Lentigo Malignant Melanomas; Figure S4. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Acral Melanomas; Figure S5. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Overall Survival in Cutaneous Melanomas; Figure S6. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Overall Survival in Cutaneous Melanomas by geographic area; Figure S7. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Overall Survival in Cutaneous Melanomas by immunohistochemical pattern; Figure S8. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Disease-Free Survival in Cutaneous Melanomas; Figure S9. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Breslow Thickness in Cutaneous Melanomas by geographic area; Figure S10. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Breslow Thickness in Cutaneous Melanomas by immunohistochemical pattern; Figure S11. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Ulceration in Cutaneous Melanomas; Figure S12. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and N status in Cutaneous Melanomas; Figure S13. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and M status in Cutaneous Melanomas; Figure S14. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Clinical Stage in Cutaneous Melanomas; Figure S15. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Mitotic Rate in Cutaneous Melanomas; Figure S16. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Clark levels in Cutaneous Melanomas; Figure S17. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and types of melanoma (nodular vs. SSM/LMM/AM) in Cutaneous Melanomas; Figure S18. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and types of melanoma (nodular vs. SSM/LMM/AM) in Cutaneous Melanomas by geographic area; Figure S19. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and types of melanoma (nodular vs. SSM/LMM/AM) in Cutaneous Melanomas by immunohistochemical pattern; Figure S20. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and tisular expression (Lymph node metastasis vs. primary tissue) in Cutaneous Melanomas; Figure S21. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and tisular expression (distance metastasis vs. primary tissue) Cancers 2021,13, 1314 18 of 21 in Cutaneous Melanomas; Figure S22. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and tisular expression (distance metastasis vs. primary tissue) in Cutaneous Melanomas by geographic area; Figure S23. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and tisular expression (distance metastasis vs. primary tissue) in Cutaneous Melanomas by geographic area; Figure S24. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Uveal Melanomas; Figure S25. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Largest Basal Dimension in Uveal Melanomas; Figure S26. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and pathology (epithelioid vs. spindle/mixed cell shape) in Uveal Melanomas; Figure S27. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Mucosal Melanomas; Figure S28. Forest plot graphically representing the frequency of CCND1/cyclin D1 alterations in Mucosal Melanomas by anatomical site; Figure S29. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Recurrence in Mucosal Melanomas; Figure S30. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Thickness in Mucosal Melanomas; Figure S31. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and M status in Mucosal Melanomas; Figure S32. Forest plot graphically representing the association between CCND1/cyclin D1 alterations and Necrosis in Mucosal Melanomas; Figure S33. A funnel plot of estimated logHR against its standard error, graphically representing the analysis of small-study effects on Overall Survival in Cutaneous Melanomas; Figure S34. A funnel plot of estimated logOR against its standard error, graphically representing the analysis of small-study effects on Distance Metastasis vs. Primary tissue in Cutaneous Melanomas; Figure S35. A funnel plot of estimated logOR against its standard error, graphically representing the analysis of small-study effects on Type of Cutaneous Melanomas; Figure S36. A funnel plot of estimated logOR against its standard error, graphically representing the analysis of small-study effects on Ulceration in Cutaneous Melanomas; Figure S37. A funnel plot of estimated logOR against its standard error, graphically representing the analysis of small-study effects on Ulceration in Cutaneous Melanomas. Author Contributions: The author contributions according to CRediT taxonomy were: conceptualization (L.G.-R., M.Á.G.-M. and P.R.-G.), data curation (L.G.-R., M.Á.G.-M., I.G.-R., I.R.-Á. and P.R.-G.), formal analysis (L.G.-R., M.Á.G.-M. and P.R.-G.), investigation (L.G.-R., M.Á.G.-M., I.G.-R., I.R.-Á. and P.R.-G.), methodology (L.G.-R., M.Á.G.-M. and P.R.-G.), project administration (M.Á.G.-M.), resources (M.Á.G.-M.), visualization (L.G.-R., M.Á.G.-M. and P.R.-G.), validation (L.G.-R., M.Á.G.-M., I.G.-R., I.R.-Á. and P.R.-G.), writing-original draft (L.G.-R., M.Á.G.-M. and P.R.-G.), writing-review and editing (L.G.-R., M.Á.G.-M., I.G.-R., I.R.-Á. and P.R.-G.). All listed authors have made substantial contributions and have approved the submitted version. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. 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