The Association of Residential Altitude on the Molecular Profile and Survival of Melanoma: Results of an Interreg Study

Simple Summary Environmental factors such as UVR exposure and altitude of residence can contribute to the development of cutaneous melanoma. We hereby report that altitude of residence significantly associates with the molecular profiling of CM and melanoma specific survival. The fact that different miRNAs and transcriptomic profile vary with different geographical areas and residences altitude could support for possible regulatory mechanisms induced by environmental conditions, such as hypoxic environment and/or higher UVR exposure. Abstract Cutaneous melanoma (CM) incidence is rising worldwide and is the primary cause of death from skin disease in the Western world. Personal risk factors linked to environmental ultraviolet radiation (UVR) are well-known etiological factors contributing to its development. Nevertheless, UVR can contribute to the development of CM in different patterns and to varying degrees. The present study aimed at investigating whether altitude of residence can contribute to the development of specific types of CM and/or influence its progression. To this aim, 306 formalin-fixed and paraffin-embedded (FFPE) tissues from primary CM diagnosed in different geographical areas were submitted to B-RAF proto-oncogene serine/threonine kinase (BRAF) and N-RAS proto-oncogene GTPase (NRAS) mutational status detection and mRNA and miRNA profiling by qPCR. Genes were chosen for their functions in specific processes, such as immune response (CD2, PDL1, or CD274) and pigmentation (MITF, TYRP1, and TRPM1). Furthermore, four microRNAs, namely miR-150-5p, miR-155-5p, miR-204-5p, and miR-211-5p, were included in the profiling. Our results highlight differences in the gene expression profile of primary CM with respect to the geographical area and the altitude of residence. Melanoma-specific survival was influenced by the gene expression of mRNA and miRNAs and varied with the altitude of patients’ residence. In detail, TYRP1 and miR-204-5p were highly expressed in patients living at higher altitudes, unlike miR-150-5p, miR-155-5p, and miR-211-5p. Since miRNAs are highly regulated by reactive oxygen species, it is possible that different regulatory mechanisms characterize CMs at different altitudes due to the different environment and UVR intensity.


Molecular Subtypes
To define molecular subtypes, gene expression was dichotomized into high or low level depending if the expression level in term of fold change was higher or lower than its median value. Accordingly, each transcriptomic subtype was described as follows: "keratin" with high level of MITF, TYRP1, and low expression levels of miR-150-5p; "MITF-low" had low expression of MITF, TYRP1, and high expression of miR-204-5p; the "immune" subtype was characterized by high expression of CD2, PDL1 (CD274) and miR-150-5p.

mRNAs and microRNAs Real-Time PCR
The results of real-time PCR efficiencies for each primer set were reported in Table 3. Although efficiencies were less than 100%, the ∆∆ Ct method 23 was applied because all the regression lines were parallel and efficiencies values were comparable. As housekeeping, the geometric mean of at least two genes was employed. Based on their stability and their expression levels, the geometric mean of HPRT1 and PDGB was used to normalize CD2, CD274, HIF1A and TRPM1; while ACTB and GAPDH were used for TYRP1 and MITF normalization and the geometric mean of Let-7e-5p and miR-423-3p was used to normalize all the miRNAs. As calibrator was used a pool of cDNA made of 10 samples from the cohorts.

Molecular Subtypes
According to the transcriptomic classification as defined in the material and method section CM were grouped as follows: 52 CM resulted of "keratin" type, 37 "MITF-low", 58 "immune" and 117 as unclassified.
Among the tumor characteristics, the distribution of CM stages across molecular subtypes resulted significant different, namely the defined "immune" cluster was more represented in stage I and II, while the "keratin" group appeared more numerous in stage III (p = 0.009, Fig. 6a). Furthermore, in our dataset samples with negative lymph nodes belonged mostly to "immune" cluster, on contrary the "keratin" one fitted in positive lymph nodes samples (p = 0.0006; Supplementary Figure 6b). Figure S6. (a) Bar plots representing the percentage of CM cases per tumor stage divided by molecular subtype, unclassified CM were excluded from the analysis (p value refers to extended Wilcoxon ranksum test). The "immune" cluster was more represented in stage I and II, while the "keratin" one was more numerous in stage III (p = 0.009). (b) Bar plot representing the percentage of CM cases per lymph nodes positivity divided by molecular subtypes; unclassified CM were excluded from the analysis (p value refers to Chi-square test). Negative lymph nodes samples belong mostly to "immune" group, while the positive lymph nodes patients belong to "keratin" cluster (p = 0.0006). The Cox proportional hazard regression method was applied to analyze patients' demographics (age at diagnosis, gender, altitude of residence, geographical areas), pathological covariates (stage, ulceration, anatomical site), mutational status, gene and miRNA expression levels in the entire cohort of patients, to test the joint effects of the covariates on patients' overall survival. The same analysis excluding patients from Innsbruck and its land did not fit the proportional hazard assumption, therefore results were not reported.  Figure S8. Kaplan Meier survival curves for relapse free survival (RFS) for CD2 (p = 0.008). CD2 mRNA expression was dichotomized in low expression and high expression for the median value of each transcript (p values on the graph refers to the Log-rank test).

Analysis of HIF1A
The expression level of HIF1A was analyzed in the entire cohort of patients. Results are reported in the Table S5. The influence of HIF1A mRNA on patients' survival was investigated by dichotomizing HIF1A expression levels according to its median value. Over the entire cohort, HIF1A did not result to influence on melanoma specific survival (p = 0.4); overall survival (p = 0.06) and relapse free survival (0.1).
To explore on the regulatory effect of miR155-5p on HIF1A transcript a correlation analysis was carried out comparing ∆∆Ct ratio of miR155-5p with those of HIF1A in the entire cohort or samples as well as grouping them in the different altitude ranges. Results are listed in Table S6.