Abstract

1. INTRODUCTION

Melanoma, a malignant tumor resulting from the transformation of melanocytes, has the highest mortality compared to other relatively common primary skin cancers, with 2.1 deaths per 100,000 Americans per year. Their pathogenesis, although multi‐faceted, is largely attributed to significant ultraviolet (UV) exposure for most primary cutaneous melanomas with the except of acral lentiginous melanoma (ALM); almost all melanomas are seemingly linked with an accumulation of mutated genetic drivers. ¹ Commonly mutated genes include BRAF, NRAS, NF1, CDKN2A, MUC16, and TTN. ^{2 , 3}

While some genes manifest mutations that are mutually exclusive, gene mutations in MUC16 and TTN may co‐occur in a substantial proportion of patients. ⁴ The clinical implications of these co‐occurrent mutations on patient prognosis are not well understood. Furthermore, gender and specific melanoma subtype may also impact prognosis. Stratification of gender and cancer subtype is critical to develop a better understanding of patient outcomes based on their genetic and demographic profiles. Therefore, we investigated the impact the two most commonly co‐occurrent genetic mutations, MUC16 and TTN, on patient prognosis and the impact of gender and melanoma subtype on patient mortality risk.

2. METHODS

We queried the cBioPortal database for melanoma studies, utilizing mutational and patient profile data from 16 studies. ^{5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20} The cBioPortal database is an open‐access resource that contains multiple cancer genomic data sets inputted from prior cancer studies. Patients were included if they had ALM, cutaneous melanoma (CM), or melanoma of an unknown primary origin (MUP). MUP is defined as having histologically confirmed melanoma metastasis without evidence of a melanoma of primary origin. We analyzed extrapolated data for mutation count, mutated gene, gender, melanoma subtype, survival status, and overall survival (in months). Patients were grouped into four gene groups: patients with neither MUC16 or TTN mutations, patients with MUC16 mutations but no TTN mutations, patients with TTN mutations but no MUC16 mutations, and patients with both MUC16 and TTN mutations.

Mutation frequency distribution analysis and co‐occurrence analysis were conducted to rank the most frequent mutations and the most prevalent co‐occurrent mutations. Univariate cox regression hazard ratio analysis was used to compare risk of mortality based on melanoma mutation type, gender, and melanoma type both within and across gene groups. Student's t‐tests were used to compare the mean number of mutations between genders based on mutation type. Analysis of variance tests were used to compare the number of mutations across melanoma types based on melanoma mutation type. An =0.05 was used for all analyses. Statistics were conducted in R (version 4.3, R Core Team 2023).

3. RESULTS

A total of 2447 melanoma patients and 2495 patient samples were included. Using mutation frequency distribution analysis, MUC16 (62.90%) and TTN (61.10%) mutations were the most frequent mutations in the cohort (Table S1). Using co‐occurrence analysis of the top 50 most frequently mutated genes, MUC16 and TTN were the most common co‐occurrent mutated genes occurring in 741 patient samples (OR >3; p<0.001) (Table S2). Overall, 126 patients had MUC16 mutations alone, 204 patients had TTN mutations alone, 765 patients had both MUC16 and TTN mutations, and 1352 patients had neither MUC16 nor TTN mutations.

4. DISCUSSION

TTN and MUC16 mutations were the most frequently mutated genes within this melanoma patient cohort and were the most common combination of concurrently mutated genes overall. These genes may be more prone to mutations because of their length. The TTN gene has one of the longest exon genomes (chromosome 2q31, 364 exons), and also has the greatest number of mutation sites. ²¹ The MUC16 gene has the second longest exon in the genome (chromosome 19p13, 84 exons), and is associated with increased tumor mutational burden. ²²

We found that melanoma patients with TTN mutations alone and melanoma patients with both MUC16 and TTN mutations had worse prognosis than patients with neither MUC16 or TTN mutations. However, patients with MUC16 mutations alone had a similar prognosis to those with neither MUC16 or TTN mutations. Therefore, our findings suggest that, although MUC16 and TTN mutations often occur concurrently, TTN mutations may be the primary driver of poor prognosis in melanoma patients. We found that TTN mutations conferred a poorer prognosis amongst both males and females and in CM patients than patients with neither MUC16 or TTN mutations. Notably, TTN encodes the protein titin, which interacts with 170 different protein ligands, including telethonin, actinin, sAnk1, filamin C, nebulin, tropomyosin, B‐crystallin, FHL1, FHL2, calpains 1 and 3, and muscle ankyrin repeat proteins (MARPs), ²³ influencing key cellular processes, including phosphorylation, calcium binding, and myosin binding, and potentially contributing to tumorigenesis. Titin also plays a crucial role in myofibrillar signal transduction pathways ²⁴ by coordinating and integrating gene activation, protein folding, quality control, and degradation, ²³ which might foster tumor growth through uncontrolled cell proliferation and reduced apoptosis.

We found that patients with both MUC16 and TTN mutations had higher mortality risk than patients with neither mutation, and that patients with TTN mutations alone had an even higher mortality risk than patients with neither mutation, which differs from previous cancer literature. In a retrospective study analyzing somatic mutations in 480 patients with lung squamous cell carcinomas, patients with TTN mutations had a better prognosis than patients without TTN mutations. ²¹ In a separate retrospective study analyzing the same 480 patient cohort, patients with TTN mutations had better response to immune checkpoint blockade immunotherapy than patients without TTN mutations. ²⁵ These disparities in the prognostic impact of TTN could be attributed to different tumorigenic pathways being active in different tumor types.

Our findings indicate a complex interplay between MUC16 and TTN mutations and their impact on prognosis in ALM and CM patients. We found that ALM patients without MUC16 and TTN mutations had worse prognosis compared to CM patients without these mutations. However, when both mutations were present, ALM patients had a more favorable prognosis than either CM patients with both mutations or ALM patients with neither mutation. Taken together, since presence of both MUC16 and TTN mutations, particularly in ALM patients, is associated with improved overall survival, these two mutations could have an additive protective effect in ALM patients. Our findings align with a retrospective prognostic analysis of 437 samples from patients with gastric cancer, showing that presence of MUC16 mutations were associated with better prognosis when compared to patients without MUC16 mutations. ²² Similarly, in another retrospective genomic analysis of 37 different solid tumors from 7 public clinical cohorts, the presence of TTN mutations were associated with better response to immune checkpoint blockade therapies compared to patients without TTN mutations. ²⁵

The observed improved survival of ALM patients with concurrent MUC16 and TTN mutations might be attributed to the trend towards lower total mutation count in ALM patients with both mutations (in comparison to CM and MUP patients with both mutations), and the significantly higher total mutation count in ALM patients with neither mutations (in comparison to CM and MUP patients with neither mutations). Similarly, in a retrospective analysis of 262 gastric cancer patients, higher total mutation count (tumor mutational burden [TMB]≥8) was associated with poorer prognosis. ²⁶ In addition, in a retrospective database analysis of hepatocellular carcinoma patients, increased tumor mutational burden (top 20% TMB in patient cohort) was associated with worse survival rates. ²⁷

In TTN‐mutated patients, MUC16‐mutated patients, and patients with neither MUC16 nor TTN mutations, MUP patients consistently had worse prognosis than CM patients. Similarly, in a prospective institutional study of 2930 melanoma patients, MUP patients treated with systemic therapies had poorer outcomes than patients with melanomas of known primaries (including CM or ALM) treated with systemic therapies. ²⁸ For MUP patients in our study, only MUC16 mutations correlated with overall lower survival compared to MUP patients with neither mutation. Therefore, theoretically, genetic or immunologic targeting therapy towards MUC16 genes or MUC16‐associated proteins might improve overall patient outcomes for MUP patients.

Our data shows that while, on average, male melanoma patients had greater numbers of total mutations than female melanoma patients across different gene groups, there were no prognostic differences based on gender. These findings are in contrast to prior studies. For example, in a genome‐wide review of gender based differences in cancer prognosis, including melanoma, as well as lung adenocarcinoma, melanoma, urothelial cell, papillary renal cell, and hepatocellular carcinoma, males compared to females had higher mutation burden, which conferred worse overall prognosis. ²⁹ In this same study, female melanoma patients with high mutation counts (greater than 130 mutations) still had greater overall survival compared to males with high or low mutation counts. ²⁹ While we did not find gender‐based differences in survival based on mutation count, there may be gender‐specific differences in other mutually‐exclusive genetic mutations (i.e., TP53), which were not measured in our study. For example, in a retrospective genomic analysis using The Cancer Genome Atlas Program database, male melanoma patients harbored more TP53 gene mutations than female melanoma patients (TP53 mutation frequency per 100,000 people for males vs. females: 4.7 vs. 2.2; p≈0), which was associated with poorer prognosis. ³⁰ In a prospective study of 3324 melanoma patients, male patients had higher prevalence of tumor ulceration (63.8% vs. 36.2%; p<0.0001) and metastasis to the axial skeleton (69.3% vs. 30.7%; p<0.0001) than female patients, both being independent predictors of poorer outcomes in these patients. ³¹

Limitations include retrospective design, lack of data pertaining to treatment history, lifestyle and environmental factors, Breslow depth, race, ethnicity, socio‐economic factors, family history, and epigenetic background. Not all gene mutations involved in melanoma development were included in the database. Furthermore, the database may have inherent patient selection biases due to the limited set of studies included, potentially limiting the generalizability of our findings. The representation of specific institutions or geographic regions could also affect the applicability of the results to a broader population. Additionally, there is a lack of literature on how different treatment modalities might influence patient outcomes specifically for those with MUC16 and TTN mutations, which we recommend as an important area for future research.

5. CONCLUSION

Our study showed that MUC16 and TTN were the most common co‐occurrent mutations in this cohort of melanoma patients. TTN mutations were a consistent marker of poor prognosis, either alone or combined with MUC16 mutations in the overall patient cohort, CM patients, and for both genders. For ALM patients, having both MUC16 and TTN mutations had a better prognosis, while having neither mutation conferred a worse prognosis. MUP patients consistently exhibited a worse prognosis than CM patients across MUC16‐mutated patients, TTN‐mutated patients, and patients with neither mutation. Only the presence of MUC16 mutations in MUP patients was associated with a worse outcome. There were no significant gender‐based differences in mortality risk across all gene combinations. Our study underscores the need for adequate genetic profiling in melanoma patients. Personalized therapeutic strategies might provide more effective treatment solutions, enhancing survival rates and improving overall melanoma patient care.

AUTHOR CONTRIBUTIONS

Nilesh Kodali: Conceptualization (lead); data curation (lead); formal analysis (equal); investigation (lead); methodology (lead); project administration (lead); resources (equal); software (equal); supervision (lead); validation (lead); visualization (lead); writing – original draft (lead); writing – review and editing (equal). Simona Alomary: Methodology (equal); resources (equal); validation (equal); visualization (equal); writing – original draft (equal); writing – review and editing (equal). Abhijit Bhattaru: Formal analysis (lead); methodology (lead); project administration (equal); validation (lead); visualization (lead); writing – review and editing (equal). Ahmed Eldaboush: Investigation (equal); validation (equal); writing – review and editing (equal). Robert A. Schwartz: Conceptualization (equal); investigation (equal); methodology (equal); project administration (equal); supervision (equal); validation (equal); visualization (equal); writing – review and editing (equal). Shari R. Lipner: Conceptualization (equal); investigation (equal); methodology (equal); project administration (equal); supervision (lead); validation (equal); visualization (equal); writing – review and editing (equal).

FUNDING INFORMATION

The authors report no funding sources relevant to this work.

CONFLICT OF INTEREST STATEMENT

Mr. Kodali, Ms. Alomary, and Mr. Bhattaru, Dr. Schwartz and Dr. Lipner have no conflicts of interest. Dr. Lipner has served as a consultant for Ortho‐Dermatologics, Lilly, Moberg Pharmaceuticals and BelleTorus Corporation.

Supporting information

ACKNOWLEDGEMENTS

Notes

Kodali N, Alomary S, Bhattaru A, Eldaboush A, Schwartz RA, Lipner SR. Gender and melanoma subtype‐based prognostic implications of MUC16 and TTN co‐occurrent mutations in melanoma: A retrospective multi‐study analysis. Cancer Med. 2024;13:e70199. 10.1002/cam4.70199 [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]

REFERENCES