Literature DB >> 31455347

Mutational concordance between primary and metastatic melanoma: a next-generation sequencing approach.

Antonella Manca1, Panagiotis Paliogiannis2, Maria Colombino1, Milena Casula1, Amelia Lissia2, Gerardo Botti3, Corrado Caracò3, Paolo A Ascierto3, Maria Cristina Sini1, Grazia Palomba1, Marina Pisano1, Valentina Doneddu2, Antonio Cossu2, Giuseppe Palmieri4.   

Abstract

BACKGROUND: Cutaneous malignant melanoma (CMM) is one of the most common skin cancers worldwide. Limited information is available in the current scientific literature on the concordance of genetic alterations between primary and metastatic CMM. In the present study, we performed next-generation sequencing (NGS) analysis of the main genes participating in melanoma pathogenesis and progression, among paired primary and metastatic lesions of CMM patients, with the aim to evaluate levels of discrepancies in mutational patterns.
METHODS: Paraffin-embedded tumor tissues of the paired lesions were retrieved from the archives of the institutions participating in the study. NGS was performed using a specific multiple-gene panel constructed by the Italian Melanoma Intergroup (IMI) to explore the mutational status of selected regions (343 amplicons; amplicon range: 125-175 bp; coverage 100%) within the main 25 genes involved in CMM pathogenesis; sequencing was performed with the Ion Torrent PGM System.
RESULTS: A discovery cohort encompassing 30 cases, and a validation cohort including eleven Sardinian patients with tissue availability from both the primary and metachronous metastatic lesions were identified; the global number of analyzed tissue specimens was 90. A total of 829 genetic non-synonymous variants were detected: 101 (12.2%) were pathogenic/likely pathogenic, 131 (15.8%) were benign/likely benign, and the remaining 597 (72%) were uncertain/unknown significance variants. Considering the global cohort, the consistency in pathogenic/pathogenic like mutations was 76%. Consistency for BRAF and NRAS mutations was 95.2% and 85.7% respectively, without statistically significant differences between the discovery and validation cohort.
CONCLUSIONS: Our study showed a high level of concordance in mutational patterns between primary and metastatic CMM, especially when pathogenic mutations in driver genes were considered.

Entities:  

Keywords:  BRAF; Cancer; Melanoma; Metastasis; Mutations; NRAS; Skin

Year:  2019        PMID: 31455347      PMCID: PMC6712827          DOI: 10.1186/s12967-019-2039-4

Source DB:  PubMed          Journal:  J Transl Med        ISSN: 1479-5876            Impact factor:   5.531


Background

Cutaneous malignant melanoma (CMM) is one of the most common skin cancers worldwide [1]. CMM incidence constantly increases in the last decades, and mortality rates rise, especially in white males [2]. CMM mortality is higher in advanced stage cases, not suitable for complete surgical removal, in which traditional chemotherapy is often characterized by poor oncological benefits [3]. Consistent improvements in survival in this subset of patients were obtained with the introduction of targeted and immunological therapies in recent years. Actually, targeted therapies are performed with the combination of BRAF inhibitors (dabrafenib, vemurafenib, encorafenib) and MEK inhibitors (cobimetinib, trametinib, binimetinib) in patients with CMM carrying a BRAF mutation (approximately, 50% of the cases), MEK inhibitors alone in BRAF wild-type cases with NRAS mutations, and KIT inhibitors (imatinib, nilotinib, etc.) in patients with KIT mutated lesions [4]. In other words, targeted therapies are based on the knowledge of specific genetic alterations occurring in the tumors to treat. Unfortunately, tumors are not static, but dynamic entities and their mutational landscape continuously changes during their progression from premalignant lesions to metastasis, and can also be influenced by the therapeutic interventions adopted. Several studies have been performed in the past to evaluate the concordance of BRAF and NRAS mutations between primary tumors and their metastases in order to better understand the pathophysiology of the metastatic process in CMM, and to respond on specific clinical issues regarding the quality of mutational analysis is tissue from metastases in comparison to that performed in the primary tumor [5]. Some of these studies showed a good concordance between primary tumors and lymph node or visceral metastases, but low rates when soft tissue metastatic samples were compared with the primary lesions [6-8]. Nevertheless, studies with consistently lower concordance rates, also between primary and lymph node or visceral metastases, have been published [9, 10]. Most of these reports regarding BRAF and NRAS used a single conventional method for identifying the mutations, and enrolled small cohorts, undermining the validity of conclusions, and making further investigations necessary. Additional studies employing conventional sequencing evaluated the concordance of the specific mutations on other genes participating in the oncogenic process of CMM, like CDKN2A, MITF, EGFR, CCND1, cMET, and cKIT and others, evidencing differences in genes selected during tumor progression (like CDKN2A, MITF, etc.) [11]. Globally, all the studies mentioned elucidated only a small frame of the global change of the mutational landscape of metastatic CMM, in comparison to the origin tumors. The advent of next-generation sequencing (NGS) technologies for genetic testing accelerated the efforts to identify the whole pattern of mutations involved in the CMM pathogenesis [12]. Recent whole exome (WES) or genome sequencing (WGS) studies provided precious details regarding genetic alterations in numerous genes included in a wide range of molecular pathways and networks in melanomagenesis and thus allowing the molecular sub-classification of the several types of melanoma [13-17]. Nevertheless, limited information is available on the concordance of the genetic alterations reported between primary and metastatic melanomas; such information is crucial for the comprehension of the single roles and the interplay between specific genetic events in the metastatic process, as well as for establishing the validity of testing in CMM metastatic tissue for all the mutations in genes used in clinical practice for current and future targeted therapies. In the present study, we performed NGS-based analysis of the main genes participating in melanoma pathogenesis and progression, included in a specific gene-panel designed by the Italian Melanoma Intergroup (IMI) on the basis of previous studies, in paired primary and metastatic lesions of patients with CMM, with the aim to evaluate potential discrepancies in mutational patterns. Although a more detailed picture of the pathogenic changes could be obtained with larger gene panels or, more extensively, WES/WGS screening approaches, the use of a panel containing a limited number of driver genes may be much easier to be introduced into the clinical practice.

Materials and methods

Patients

Consecutive Italian patients with a histologically proven diagnosis of metastatic CMM from January 2009 to December 2017 were retrieved from the archives of the southern Italy anatomic pathology institutes participating in the study, and cases with tissue availability from both the primary and at least one metachronous lymph node or visceral metastatic lesion were identified. Metastatic melanomas were considered as metachronous when melanoma metastasis was diagnosed after at least 6 months from the diagnosis of the primary melanoma. Patients with soft tissue metastases were excluded because of the low concordance in mutational rates in comparison with the primary lesions described in older studies, as mentioned above [6-8]. Brain metastases samples were not available in any case. In addition, using the same criteria, a validation cohort of consecutive Sardinian patients with available paired primary and metastatic CMM samples was identified from the archives of the Anatomic Pathology Unit of the University of Sassari, within the same time frame. The demographic, clinical and pathological data of all patients were retrieved from clinical records and reports. All the patients gave their informed consent for the use of their clinical data for the purposes of the study. The study was performed in accordance with the principles of the declaration of Helsinki and was approved by the Committee for the Ethics of the Research and Bioethics of the National Research Council (CNR).

Molecular analysis

For mutation analysis, paraffin-embedded tumor tissues of the paired lesions were retrieved from the pathological archives of the institutions participating in the study. Using light microscopy, tissue sections were selected in order to obtain tumor samples with at least 80% neoplastic cells. Genomic DNA was isolated using the GeneRead DNA FFPE Kit (Qiagen, Hilden, Germany), following the manufacturer´s instructions. NGS was performed using a specific multiple-gene panel constructed by the IMI (IMI somatic DNA panel), arranged in three primer pools, and designed using the Ion AmpliSeq Designer to explore the mutational status of selected regions (343 amplicons; amplicon range: 125–175 bp; coverage 100%) within the 25 genes reported as the most frequently mutated in CMM specimens by The Cancer Genome Atlas (TGCA) and successive NGS-based studies [12, 13]. Figure 1 summarizes the characteristics of the IMI panel. Although this is the first time the IMI gene panel is used in a study, several genomic DNA samples from FFPE melanoma tissues were blindly analyzed in separate Italian laboratories using different NGS platforms in order to achieve full validation of the IMI panel for mutation pattern detection at somatic level (Ghiorzo and Palmieri, manuscript in preparation). Barcoded amplicon libraries were generated from 10 ng template DNA × primer pool and purified with AMPure beads (Beckman Coulter, Brea, CA, USA). Purified DNA was diluted at a final concentration of 50 pM, placed into the Ion Chef for emulsion PCR and Chip (316 v2BC) loading, and sequenced on the Ion Torrent PGM System (Life Technologies, Waltham, MA, USA). Sequencing data were processed with the Ion Torrent platform-specific pipeline software (Torrent Suite, V5.2.1; Life Technologies); the Ion Reporter and Integrative Genome Viewer were used for variant annotation and reads visualizations, respectively (http://www.broadinstitute.org/igv).
Fig. 1

The Italian Melanoma Intergroup (IMI Somatic DNA panel) used for genetic testing including 343 amplicons, size range 125–175 bp, coverage 100%, within the main 25 genes involved in the pathogenesis of melanoma

The Italian Melanoma Intergroup (IMI Somatic DNA panel) used for genetic testing including 343 amplicons, size range 125–175 bp, coverage 100%, within the main 25 genes involved in the pathogenesis of melanoma Coverage of > 300 reads and frequency of mutated alleles > 3% for gene amplicon, in order to get a total amount of at least 10 mutated alleles for each candidate amplicon, were adopted for mutation selection criteria at somatic level. In the discovery cohort, a total of 844,153 reads was achieved for selecting 750 nucleotide variants, with an average of 1125 reads per mutated gene amplicon (range, 302 to 2000). In the validation cohort, a total of 70,576 reads was achieved for selecting 79 nucleotide variants, with an average of 893 reads per mutated gene amplicon (range, 302 to 2000). Sequence variants were classified as pathogenic, likely pathogenic, uncertain significance, likely benign, or benign, according to their capability to either affect the function of the gene or be plausibly linked to the disease. In particular, pathogenicity was assessed through data comparisons using the following sequence databases: the ClinVar archive of reports of relationships among medically relevant variants and phenotypes (http://www.ncbi.nlm.nih.gov/clinvar/) and the Catalogue Of Somatic Mutations In Cancer (COSMIC v88; https://cancer.sanger.ac.uk/cosmic). All mutations in melanoma driver oncogenes (BRAF and NRAS) and a fraction of randomly-selected pathogenic variants with high rates of the mutated alleles in the remaining genes were confirmed by Sanger sequencing of gene-specific amplicons. Briefly, polymerase chain reaction (PCR) was performed on 20 ng of genomic DNA in a Veriti 96-Well Fast Thermal Cycler (Life Technologies-ThermoFisher Scientific); all PCR-amplified products were directly sequenced using an automated fluorescence-cycle sequencer (ABI3130, Life Technologies). Sequencing analysis was conducted in duplicate and in both directions (forward and reverse) for all evaluated samples.

Statistical analysis

Results were expressed as percentages, mean (mean ± SD) or median values (median and IQR). Variables distribution was assessed by the Shapiro–Wilk test. Statistical differences were assessed using the unpaired Student’s t-test or Mann–Whitney rank sum test, the Chi-square test or Fisher’s exact test as appropriate. Correlations between clinical and genetic variables were assessed by Pearson’s or Spearman’s correlation, as appropriate. Statistical analyses were performed using MedCalc for Windows, version 15.4 64 bit (MedCalc Software, Ostend, Belgium).

Results

Thirty-five national cases with tissue availability from both the primary and at least one metachronous lymph node or visceral metastatic lesion were identified. Among them, five patients were excluded because of the low quality of the DNA extracted, and thus, the remaining 30 were enrolled in the study. Among the 15 Sardinian cases identified, eleven patients were enrolled and four were excluded because of sample DNA degradation. The global number of patients enrolled was 41, and the total of tissue samples retrieved 90 (Fig. 2); the primary CMMs were 41 and the metastatic lesions 49. Paired primary and lymph node metastasis specimens were available in 31 cases, while paired primary and visceral metastasis samples were obtained in 18 cases (nine liver, eight lung, and one small intestine metastasis).
Fig. 2

Description of the cohorts enrolled in the study

Description of the cohorts enrolled in the study The main demographic, clinical and pathological characteristics of the cohorts included in the study are summarized in Table 1; no statistically significant differences were found in such characteristics between the discovery and validations groups, with the exception of sex (all patients in the validation cohort were males) and the number of mitoses in the primary lesions which were significantly lower in the validation group.
Table 1

Demographic, clinical and pathological features of the patients included in the study

CharacteristicsGlobal cohort (41 cases)Discovery cohort (30 cases)Validation cohort (11 cases)p-value
Male sex, n (%)28 (68.3)15 (53.6)11 (100) 0.003
Age, (mean ± SD), years55 ± 12.753.9 ± 13.258 ± 11.10.324
IPMD, (mean ± SD), months24.3 ± 26.425.3 ± 29.221.1 ± 13.40.523
Melanoma type, n (%)
 NM12 (29.3)8 (26.7)4 (36.4)0.828
 SSM28 (68.3)21 (70)7 (63.6)0.993
 LMM1 (2.4)1 (3.3)0 (0)1.000
Melanoma site, n (%)
 A. Primitive
  Head2 (4.9)2 (6.7)0 (0)1.000
  Neck3 (7.3)2 (6.7)1 (9.1)1.000
  Trunk19 (46.3)13 (43.3)6 (54.5)0.776
  Upper limbs3 (7.3)2 (6.7)1 (9.1)1.000
  Lower limbs14 (34.1)11 (36.7)3 (27.3)1.000
 B. Metastasis49 (100)36 (73.5)13 (26.5)0.853
  Lymph nodes31 (64.6)23 (63.9)8 (66.7)
  Visceral18 (35.4)13 (36.1)5 (33.3)
Number of mitosis per smm (mean ± SD)3.4 ± 3.14.1 ± 3.01.6 ± 2.5 0.003
Breslow thickness, (mean ± SD)3.8 ± 2.44.0 ± 2.43.2 ± 1.40.566
Ulceration, n (%)18 (43.9)12 (40)6 (54.5)0.634
Initial T/N stage, n (%)
 A. T stage
  T12 (4.9)2 (6.7)01.000
  T27 (17.1)5 (16.7)2 (18.2)1.000
  T319 (46.3)13 (43.3)6 (54.5)0.776
  T413 (31.7)10 (33.3)3 (27.3)1.000
 B. N stage
  N08 (19.5)6 (20.0)2 (18.2)1.000
  N116 (39.0)11 (36.7)5 (45.4)0.723
  N213 (31.7)9 (30.0)4 (36.4)1.000
  N34 (9.8)4 (13.3)00.559

Significant p-values are indicated in italics

IPMD interval progression of metastatic disease, LMM lentigo maligna melanoma, NM nodular melanoma, SD standard deviation, SSM superficial spreading melanoma

Demographic, clinical and pathological features of the patients included in the study Significant p-values are indicated in italics IPMD interval progression of metastatic disease, LMM lentigo maligna melanoma, NM nodular melanoma, SD standard deviation, SSM superficial spreading melanoma A total of 829 genetic variants were detected in all the 90 lesions examined; the incidence of the variants was significantly higher in the discovery cohort (750 variants) in comparison to the validation cohort (79 variants, p = 0.001). All the genetic variants detected are included in Additional file 1: Table S1. The variants were classified as pathogenic/likely pathogenic, benign/likely benign, and uncertain/unknown significance variants in accordance with the COSMIC and ClinVar databases as mentioned above (Additional file 2: Table S2); globally, 101 (12.2%) variants were pathogenic/likely pathogenic, 131 (15.8%) were benign/likely benign, and the remaining 597 (72%) were uncertain/unknown significance variants. The pathogenic/likely pathogenic variants affected with higher frequency the discovery than the validation cohort (87 vs. 14), but the difference was not statistically significant (p = 0.117). Furthermore, these variants were equally distributed between primary and metastatic tumors (49 vs. 52). Half of the pathogenic/likely pathogenic variants involved the BRAF gene (50 variants, 49.5%); other genes harboring such variants were NRAS (14 variants, 13.9%), TP53 (14 variants, 13.9%), CDKN2A (4 variants, 4%), and others (Additional file 2: Table S2). Conversely, benign/likely benign variants were most often harbored in the TP53 (45 variants, 34.3%), KDR (24 variants, 18.3%), PIK3CA (21 variants, 16%), and KIT (20 variants, 15.3%) genes. Considering the global cohort, the consistency in pathogenic/pathogenic like mutational patterns between primary and metastatic melanomas was 76% (Table 2). Consistency was higher between primary lesions and lymph node metastasis than between primary tumors and visceral metastasis, with the difference being statistically significant (p = 0.019, Table 2). Furthermore, global primary tumor-metastasis consistency was slightly higher in the validation cohort, than in the discovery cohort, but the difference was not statistically significant (p = 0.708). Concordance was slightly reduced (63%) when the functionally known variants (pathogenic/likely pathogenic + benign/likely benign) were considered together in the whole cohort, and was significantly lower when all the variants were pooled together (24%, p = 0.001) (Table 3). We also searched for statistically significant differences in pathogenic/likely pathogenic mutations concordance by sex, age, and time to metastasis. No sex predilection was found comparing discordant with concordant cases (p = 0.722), as well as no statistical differences in age [52.5 (IQR 50–67.5) vs. 53 (IQR 46.2–61.5) years, p = 0.504] and the time to metastasis [13.5 (IQR 11–40) vs. 18 (0–25.7) months, p = 0.297]. Similar results were obtained dividing the patients in age groups (less than 50 years vs. 50 years or more, p = 0.466), and in groups by the time to metastasis (shorter vs. longer than 24 months, which was the mean time to metastasis observed, p = 0.726).
Table 2

Consistency between pathogenic/likely pathogenic mutation patterns in paired primary and metastatic lesions: A—all cases, B—discovery cohort, C—validation cohort

Paired tissue typesNo. of samplesCases with consistent mutation pattern (%)Cases with discrepant mutation pattern (%)
A. All cases
 Primary vs. lymph node metastasis3127 (87)4 (13)
 Primary vs. visceral metastasis1810 (56)8 (44)
 Primary vs. metastasis4937 (76)12 (24)
B. Discovery cohort
 Primary vs. lymph node metastasis2320 (87)3 (13)
 Primary vs. visceral metastasis158 (53)7 (47)
 Primary vs. metastasis3828 (74)10 (26)
C. Validation cohort
 Primary vs. lymph node metastasis87 (87.5)1 (12.5)
 Primary vs. visceral metastasis32 (67)1 (33)
 Primary vs. metastasis119 (82)2 (18)
Table 3

Consistency between variant patterns in paired primary and metastatic lesions: A—classified (pathogenic/likely pathogenic and benign/likely benign) variants, B—all variants

Paired tissue typesNo. of samplesCases with consistent mutation pattern (%)Cases with discrepant mutation pattern (%)
A. Pathogenic/likely pathogenic + benign/likely benign variants
 Primary vs. lymph node metastasis3123 (74)8 (26)
 Primary vs. visceral metastasis188 (44)10 (56)
 Primary vs. metastasis4931 (63)18 (37)
B. All variants
 Primary vs. lymph node metastasis319 (29)22 (71)
 Primary vs. visceral metastasis183 (17)15 (83)
 Primary vs. metastasis4912 (24)37 (76)
Consistency between pathogenic/likely pathogenic mutation patterns in paired primary and metastatic lesions: A—all cases, B—discovery cohort, C—validation cohort Consistency between variant patterns in paired primary and metastatic lesions: A—classified (pathogenic/likely pathogenic and benign/likely benign) variants, B—all variants We also evaluated the concordance of pathogenic/likely pathogenic mutations in the main single genes involved in clinical practice for the prescription of targeted therapies (Table 4). Consistency for BRAF mutations was 95.2% (V600E, V600K, and G469S variants) present in both the primary and metastatic tumors. Similarly, consistency for NRAS mutations was 85.7%; one patient had an NRAS mutation in the primary tumor and no mutation in the corresponding visceral metastasis examined. No significant differences were observed between the discovery and the validation cohort.
Table 4

Consistency in BRAF and NRAS pathogenic/likely pathogenic variants in our cohort

Cases with a mutation in the primary tumorConsistent mutation pattern with metastasis (%)
BRAF mutations
 Primary vs. lymph node metastasis1817 (94.4)
 Primary vs. visceral metastasis33 (100)
 Primary vs. metastasis2120 (95.2)
 Discovery cohort1717 (100)
 Validation cohort43 (75)
NRAS mutations
 Primary vs. lymph node metastasis33 (100)
 Primary vs. visceral metastasis43 (75)
 Primary vs. metastasis76 (85.7)
 Discovery cohort54 (80)
 Validation cohort22 (100)
Consistency in BRAF and NRAS pathogenic/likely pathogenic variants in our cohort

Discussion

Cutaneous malignant melanoma, like most human cancers, is a disease resulting from a dynamic pathogenic process characterized by the accumulation of genetic alterations in the neoplastic cells, under the pressure of several oncogenic stimuli. The main genetic alterations necessary for melanomagenesis and early progression, have been widely elucidated [18]; less is known about the genetic mutational patterns determining and characterizing regional and distant melanoma metastasis. The latter issue is particularly interesting, also for practical reasons, in order to determine the clinical validity of mutational testing performed in metastatic biopsy specimens. What can undermine the validity of these tests is the occurrence of intratumoral and intertumoral heterogeneity. A high number of clones harboring various mutations contribute to a great level of intratumor heterogeneity of CMM and generate metastases which may originate from different subclones. Multiple molecular events on a genomic (point mutations, deletions, aberrations, etc.), transcriptomic/proteomic (over-, under-expression of genes, etc.), and epigenetic (methylation, micro-RNA and long non-coding RNA regulation, etc.) level can additionally contribute in further increase such heterogeneity [19]. Indeed, all these levels contributed to the molecular heterogeneity evidenced in The Cancer Genome Atlas (TCGA) study, in which across the eleven different cancer types included, there were 4473 primary tumor samples (104 from melanoma) and 395 tumor metastasis samples (including 369 from melanoma), but only 29 paired cases from the same patient, and external to the TCGA datasets were analyzed [20]. Moreover, the introduction of newly conceived targeted therapies has been demonstrated able to impact the mutational landscape of melanomas, creating further pressure on clonality, and molecular alterations at all the levels mentioned [21]. This influences, not only the validity of the diagnostic tests but also the effectiveness of the therapeutic strategies adopted and therefore dictates a better knowledge of the variations occurring during the course of the disease. The incidence of the main pathogenic mutations displaying critical roles in melanomagenesis (BRAF: 49.5%, NRAS: 13.9%, TP53: 13.9%) in our study was similar to that published in previous studies performed with NGS techniques, with the exception of KIT mutations. De Unamuno Bustos et al., Reiman et al., and Siroy et al. sequenced samples from 100, 151 and 699 CMM cases, with custom Ampliseq panels or pan-cancer hot spot NGS panels [22-24]. In these studies, the frequency of BRAF, NRAS, and KIT mutations was respectively 36–50%, 15–27%, 4–5%; in our study no pathogenic KIT variants were detected, while several unknown/uncertain and benign/likely benign were encountered. Similarly, in a previous study performed by the IMI using the AmpliSeq Cancer Panel HotSpot V2/CHPv2 on the Ion Torrent platform which investigates approximately 2800 mutations in 50 most common oncogenes and tumor suppressor genes, only KIT polymorphisms, but no mutations, were detected [25]. In a further study performed with conventional methods in the Italian population, including Sardinian patients, KIT amplifications were detected in 3.3% of the primary and 5.4% of the metastases examined [11]. Previous studies reported that the number of mutations in genes involved in the MAPK pathway, including BRAF and NRAS, was increased from premalignant lesions to melanoma; it was therefore stated that MAPK becomes activated at the earliest stage of neoplasia and progressively ramps up as malignant transformation proceeds [13, 26]. Nevertheless, this process seems to be completed in the early phases of melanomagenesis, because MAPK pathway mutations are constantly present in metastatic tissues with similar percentages as in primary lesions, with BRAF and NRAS mutations as almost mutually exclusive genetic events [27]. Shein et al. examined 12 pairs of primary CMM and the corresponding regional metastases and found most of the pathogenic mutations were shared between primary and metastatic lesions; other additional private mutations were detected, as occurred in our cohorts, but there is no evidence that their selection was associated with the metastatic spread [26]. In the study of Miraflor et al. performed with an NGS panel consisting of 207 amplicons covering over 20,000 bases across 50 genes with known cancer associations, a total of 8 patients with paired specimens were screened for somatic mutations [28]. Among them, four cases showed the same mutations in their metastatic lesions from different sites (ATM, NRAS, TP53, BRAF and JAK3 mutations), while the remaining four patients harbored different gene mutations at metastatic sites compared to their primary lesions or metastasis from different sites (BRAF, CDKN2A, PIK3CA, and ATM mutations). In our previous study, performed with the AmpliSeq HotSpot cancer panel, asynchronous (9 cases) and synchronous (16 cases) metastatic lymph nodes and the corresponding primary melanoma tissues were sequenced and no significant differences in BRAF/NRAS mutation rates between primary (19 of 25; 76%) and metastatic (39 of 50; 78%) lesions were observed, indicating that BRAF/NRAS mutations may occur early in melanoma development, and their incidence may remain quite unvaried during melanoma progression [25]. Our current results confirmed the high consistency level of pathogenic/likely pathogenic mutations between the primary tumors and the lymph node metastasis (87%). Concordance rates, were significantly lower when the visceral lesions were tested in comparison to lymph node metastases. This could raise some concerns, as current clinical guidelines recommend to perform mutational analysis on metastatic tissue in patients with advanced stage CMM, and if unavailable, to test the primary lesions [29, 30]. Nevertheless, when the pathogenic mutations to compare were restricted to the BRAF and NRAS activating variants, the concordance was higher irrespective of the metastatic site, confirming that genetic analysis can be performed in both types of lesions. The decreasing trend of consistency in pathogenic variants from primary to regional and then to distant metastasis supports the theory of the accumulation of genetic alterations during the linear progression of CMM, on which is based the surgical removal of lymph nodes with curative intent. Concordance rates do not seem to be influenced by sex, age or time to metastasis. The higher mutational discrepancies were observed in previous studies in soft tissue and brain metastases [6, 31], and for this reason, we decided to exclude these subsets of patients, which need specific studies and alternative guideline recommendations. In our study, and in most of the previous studies mentioned, high rates of concurrent BRAF (55%) and NRAS (20%) mutations were detected [26]. Furthermore, a great number of uncertain/unknown genetic variants was found. It is hard to predict the pathophysiological and clinical impact of these variants, and if they are or not passenger alterations which sporadically influence specific phases of the metastatic process. The validation cohort in our study was from Sardinia and had globally a lower incidence of these variants; this may be dependent on the genetic peculiarity of island populations. In Sardinia, whose population shows a high level of genetic homogeneity due to geographical isolation and strong genetic drift, different mutation rates in several driver oncogenes were already demonstrated for various types of cancer by our group [32, 33], strongly suggesting that different “genetic background” may also induce discrepant penetrance and distribution of somatic mutations in candidate cancer genes. Overall, most of these genetic variants do not display relevant roles in the metastatic process, as their absence does not prevent or attenuate it. Our study has some limitations, mainly the low number of cases, the retrospective approach used in selecting them, and the lack of data regarding the therapies employed for the clinical management of the patients during the evolution of the disease. We are aware that a larger collection of CMM patients with highly detailed clinical information could permit to also make comparisons between the concordant or discrepant alterations in driver genes and additional factors involved into the disease behavior (i.e. responsiveness or resistance to therapies, immune status, etc.). On the other hand, this is the first specifically designed study to investigate a tailored CMM panel of genetic alterations in primary and lymph node and visceral metastatic lesions, with an NGS approach, and in any case, includes the higher number of paired primary—metastatic tissues evaluated this way.

Conclusions

Our research showed a high level of concordance in mutational patterns between primary and metastatic CMM. Consistency was higher for pathogenic/likely pathogenic variants, which involved mainly the BRAF, NRAS and TP53 genes. Furthermore, consistency was higher between primary tumors and the corresponding lymph node metastasis, rather than visceral metastasis. Nevertheless, consistency for the main genes implicated in clinical practice (BRAF and NRAS) was extremely high, confirming previous evidence suggesting that metastatic or primary tissue can both be effectively used for mutational analysis. A high number of unknown/uncertain variants were detected in both primary and metastatic lesions, and their role remains to be elucidated in future studies (Additional file 3: Table S3). Additional file 1: Table S1. (A) The 750 somatic non-synonymous variants found in discovery cohort, in detail. In bold, variants classified as pathogenic/likely pathogenic mutations. (B) The 79 somatic non-synonymous variants found in validation cohort, in detail. In bold, variants classified as pathogenic/likely pathogenic mutations. Additional file 2: Table S2. Gene variants in paired melanoma samples. Asterisks indicate different variant types within the same patient. Additional file 3: Table S3. Gene variant patterns in paired melanoma samples. In gray, cases withconcordant patterns for pathogenic/likely pathogenic variants.
  29 in total

1.  A landscape of driver mutations in melanoma.

Authors:  Eran Hodis; Ian R Watson; Gregory V Kryukov; Stefan T Arold; Marcin Imielinski; Jean-Philippe Theurillat; Elizabeth Nickerson; Daniel Auclair; Liren Li; Chelsea Place; Daniel Dicara; Alex H Ramos; Michael S Lawrence; Kristian Cibulskis; Andrey Sivachenko; Douglas Voet; Gordon Saksena; Nicolas Stransky; Robert C Onofrio; Wendy Winckler; Kristin Ardlie; Nikhil Wagle; Jennifer Wargo; Kelly Chong; Donald L Morton; Katherine Stemke-Hale; Guo Chen; Michael Noble; Matthew Meyerson; John E Ladbury; Michael A Davies; Jeffrey E Gershenwald; Stephan N Wagner; Dave S B Hoon; Dirk Schadendorf; Eric S Lander; Stacey B Gabriel; Gad Getz; Levi A Garraway; Lynda Chin
Journal:  Cell       Date:  2012-07-20       Impact factor: 41.582

2.  BRAF/NRAS mutation frequencies among primary tumors and metastases in patients with melanoma.

Authors:  Maria Colombino; Mariaelena Capone; Amelia Lissia; Antonio Cossu; Corrado Rubino; Vincenzo De Giorgi; Daniela Massi; Ester Fonsatti; Stefania Staibano; Oscar Nappi; Elena Pagani; Milena Casula; Antonella Manca; Mariacristina Sini; Renato Franco; Gerardo Botti; Corrado Caracò; Nicola Mozzillo; Paolo A Ascierto; Giuseppe Palmieri
Journal:  J Clin Oncol       Date:  2012-05-21       Impact factor: 44.544

3.  Polyclonality of BRAF mutations in primary melanoma and the selection of mutant alleles during progression.

Authors:  J Lin; Y Goto; H Murata; K Sakaizawa; A Uchiyama; T Saida; M Takata
Journal:  Br J Cancer       Date:  2011-01-11       Impact factor: 7.640

4.  NRAS and BRAF mutations arise early during melanoma pathogenesis and are preserved throughout tumor progression.

Authors:  Katarina Omholt; Anton Platz; Lena Kanter; Ulrik Ringborg; Johan Hansson
Journal:  Clin Cancer Res       Date:  2003-12-15       Impact factor: 12.531

5.  Prevalence of KRAS, BRAF, and PIK3CA somatic mutations in patients with colorectal carcinoma may vary in the same population: clues from Sardinia.

Authors:  Grazia Palomba; Maria Colombino; Antonio Contu; Bruno Massidda; Giovanni Baldino; Antonio Pazzola; MariaTeresa Ionta; Francesca Capelli; Vittorio Trova; Tito Sedda; Giovanni Sanna; Francesco Tanda; Mario Budroni; Giuseppe Palmieri; Antonio Cossu; Marta Contu; Angelo Cuccu; Antonio Farris; Antonio Macciò; Giuseppe Mameli; Nina Olmeo; Salvatore Ortu; Elisabetta Petretto; Valeria Pusceddu; Luciano Virdis
Journal:  J Transl Med       Date:  2012-08-29       Impact factor: 5.531

6.  Melanoma genome sequencing reveals frequent PREX2 mutations.

Authors:  Michael F Berger; Eran Hodis; Timothy P Heffernan; Yonathan Lissanu Deribe; Michael S Lawrence; Alexei Protopopov; Elena Ivanova; Ian R Watson; Elizabeth Nickerson; Papia Ghosh; Hailei Zhang; Rhamy Zeid; Xiaojia Ren; Kristian Cibulskis; Andrey Y Sivachenko; Nikhil Wagle; Antje Sucker; Carrie Sougnez; Robert Onofrio; Lauren Ambrogio; Daniel Auclair; Timothy Fennell; Scott L Carter; Yotam Drier; Petar Stojanov; Meredith A Singer; Douglas Voet; Rui Jing; Gordon Saksena; Jordi Barretina; Alex H Ramos; Trevor J Pugh; Nicolas Stransky; Melissa Parkin; Wendy Winckler; Scott Mahan; Kristin Ardlie; Jennifer Baldwin; Jennifer Wargo; Dirk Schadendorf; Matthew Meyerson; Stacey B Gabriel; Todd R Golub; Stephan N Wagner; Eric S Lander; Gad Getz; Lynda Chin; Levi A Garraway
Journal:  Nature       Date:  2012-05-09       Impact factor: 49.962

7.  Molecular characterization and patient outcome of melanoma nodal metastases and an unknown primary site.

Authors:  Aleksandra Gos; Monika Jurkowska; Alexander van Akkooi; Caroline Robert; Hanna Kosela-Paterczyk; Senada Koljenović; Nyam Kamsukom; Wanda Michej; Arkadiusz Jeziorski; Piotr Pluta; Cornelis Verhoef; Janusz A Siedlecki; Alexander M M Eggermont; Piotr Rutkowski
Journal:  Ann Surg Oncol       Date:  2014-05-28       Impact factor: 5.344

8.  Beyond BRAF(V600): clinical mutation panel testing by next-generation sequencing in advanced melanoma.

Authors:  Alan E Siroy; Genevieve M Boland; Denái R Milton; Jason Roszik; Silva Frankian; Jared Malke; Lauren Haydu; Victor G Prieto; Michael Tetzlaff; Doina Ivan; Wei-Lien Wang; Carlos Torres-Cabala; Jonathan Curry; Sinchita Roy-Chowdhuri; Russell Broaddus; Asif Rashid; John Stewart; Jeffrey E Gershenwald; Rodabe N Amaria; Sapna P Patel; Nicholas E Papadopoulos; Agop Bedikian; Wen-Jen Hwu; Patrick Hwu; Adi Diab; Scott E Woodman; Kenneth D Aldape; Rajyalakshmi Luthra; Keyur P Patel; Kenna R Shaw; Gordon B Mills; John Mendelsohn; Funda Meric-Bernstam; Kevin B Kim; Mark J Routbort; Alexander J Lazar; Michael A Davies
Journal:  J Invest Dermatol       Date:  2014-08-22       Impact factor: 8.551

9.  Role of key-regulator genes in melanoma susceptibility and pathogenesis among patients from South Italy.

Authors:  Milena Casula; Antonio Muggiano; Antonio Cossu; Mario Budroni; Corrado Caracò; Paolo A Ascierto; Elena Pagani; Ignazio Stanganelli; Sergio Canzanella; Mariacristina Sini; Grazia Palomba; Giuseppe Palmieri
Journal:  BMC Cancer       Date:  2009-10-03       Impact factor: 4.430

10.  Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma.

Authors:  Michael Krauthammer; Yong Kong; Byung Hak Ha; Perry Evans; Antonella Bacchiocchi; James P McCusker; Elaine Cheng; Matthew J Davis; Gerald Goh; Murim Choi; Stephan Ariyan; Deepak Narayan; Ken Dutton-Regester; Ana Capatana; Edna C Holman; Marcus Bosenberg; Mario Sznol; Harriet M Kluger; Douglas E Brash; David F Stern; Miguel A Materin; Roger S Lo; Shrikant Mane; Shuangge Ma; Kenneth K Kidd; Nicholas K Hayward; Richard P Lifton; Joseph Schlessinger; Titus J Boggon; Ruth Halaban
Journal:  Nat Genet       Date:  2012-07-29       Impact factor: 38.330

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  9 in total

1.  Primary tumor characteristics and next-generation sequencing mutations as biomarkers for melanoma immunotherapy response.

Authors:  Kimberly Loo; Gabrielle Gauvin; Iman Soliman; Madelyn Renzetti; Mengying Deng; Eric Ross; Biao Luo; Hong Wu; Sanjay Reddy; Anthony J Olszanski; Jeffrey M Farma
Journal:  Pigment Cell Melanoma Res       Date:  2020-07-07       Impact factor: 4.693

Review 2.  Detection of Gene Mutations in Liquid Biopsy of Melanoma Patients: Overview and Future Perspectives.

Authors:  Nasr Alrabadi; Razan Haddad; Ahmed K Alomari
Journal:  Curr Treat Options Oncol       Date:  2020-02-11

3.  The Genetic Evolution of Treatment-Resistant Cutaneous, Acral, and Uveal Melanomas.

Authors:  Alvin P Makohon-Moore; Evan J Lipson; Jody E Hooper; Amanda Zucker; Jungeui Hong; Craig M Bielski; Akimasa Hayashi; Collin Tokheim; Priscilla Baez; Rajya Kappagantula; Zachary Kohutek; Vladimir Makarov; Nadeem Riaz; Michael A Postow; Paul B Chapman; Rachel Karchin; Nicholas D Socci; David B Solit; Timothy A Chan; Barry S Taylor; Suzanne L Topalian; Christine A Iacobuzio-Donahue
Journal:  Clin Cancer Res       Date:  2020-12-15       Impact factor: 13.801

Review 4.  Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices.

Authors:  Shruti Rao; Beth Pitel; Alex H Wagner; Simina M Boca; Matthew McCoy; Ian King; Samir Gupta; Ben Ho Park; Jeremy L Warner; James Chen; Peter K Rogan; Debyani Chakravarty; Malachi Griffith; Obi L Griffith; Subha Madhavan
Journal:  JCO Clin Cancer Inform       Date:  2020-07

5.  Quality assessment of a clinical next-generation sequencing melanoma panel within the Italian Melanoma Intergroup (IMI).

Authors:  Irene Vanni; Milena Casula; Lorenza Pastorino; Antonella Manca; Bruna Dalmasso; Virginia Andreotti; Marina Pisano; Maria Colombino; Ulrich Pfeffer; Enrica Teresa Tanda; Carla Rozzo; Panagiotis Paliogiannis; Antonio Cossu; Paola Ghiorzo; Giuseppe Palmieri
Journal:  Diagn Pathol       Date:  2020-12-14       Impact factor: 2.644

6.  Recommendations for the Use of Next-Generation Sequencing and the Molecular Tumor Board for Patients with Advanced Cancer: A Report from KSMO and KCSG Precision Medicine Networking Group.

Authors:  Shinkyo Yoon; Miso Kim; Yong Sang Hong; Han Sang Kim; Seung Tae Kim; Jihun Kim; Hongseok Yun; Changhoon Yoo; Hee Kyung Ahn; Hyo Song Kim; In Hee Lee; In-Ho Kim; Inkeun Park; Jae Ho Jeong; Jaekyung Cheon; Jin Won Kim; Jina Yun; Sun Min Lim; Yongjun Cha; Se Jin Jang; Dae Young Zang; Tae Won Kim; Jin Hyoung Kang; Jee Hyun Kim
Journal:  Cancer Res Treat       Date:  2021-12-13       Impact factor: 4.679

7.  BRAF, C-KIT, and NRAS mutations correlated with different clinicopathological features: an analysis of 691 melanoma patients from a single center.

Authors:  Min Ren; Jing Zhang; Yunyi Kong; Qianming Bai; Peng Qi; Ling Zhang; Qian Wang; Xiaoyan Zhou; Yong Chen; Xiaoli Zhu
Journal:  Ann Transl Med       Date:  2022-01

8.  Detection and Localization of Solid Tumors Utilizing the Cancer-Type-Specific Mutational Signatures.

Authors:  Ziyu Wang; Tingting Zhang; Wei Wu; Lingxiang Wu; Jie Li; Bin Huang; Yuan Liang; Yan Li; Pengping Li; Kening Li; Wei Wang; Renhua Guo; Qianghu Wang
Journal:  Front Bioeng Biotechnol       Date:  2022-04-25

9.  BRAF Mutations and Dysregulation of the MAP Kinase Pathway Associated to Sinonasal Mucosal Melanomas.

Authors:  Maria Colombino; Panagiotis Paliogiannis; Antonio Cossu; Valli De Re; Gianmaria Miolo; Gerardo Botti; Giosuè Scognamiglio; Paolo Antonio Ascierto; Davide Adriano Santeufemia; Filippo Fraggetta; Antonella Manca; Maria Cristina Sini; Milena Casula; Grazia Palomba; Marina Pisano; Valentina Doneddu; Amelia Lissia; Maria Antonietta Fedeli; Giuseppe Palmieri
Journal:  J Clin Med       Date:  2019-10-01       Impact factor: 4.241

  9 in total

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