Abstract
Background/Aim: Myxofibrosarcomas (MFS) are highly infiltrative soft tissue sarcomas that most commonly occur in adults within the sixth to seventh decades. Diagnosis relies on histopathological analysis as no definitive molecular markers have been identified. This study seeks to describe the mutational landscape of MFS, characterize mutations unique to certain populations, and identify mutations that may be of particular utility in diagnosis and treatment.
Patients and Methods: Using the AACR Project GENIE database, we identified a cohort of 202 patients with MFS. Patients were stratified by sex, age, race, and ethnicity. Tumors were categorized as primary, metastatic, locally recurrent, or distant organ metastases. Somatic mutations and copy number alterations were identified. Data were analyzed using R and RStudio, with p<0.05 denoting statistical significance.
Results: We are the first to link the following mutations to MFS: NOTCH3, ALOX12B, SDHA, ETV6, NCOA2 and SOS2. The most common somatic mutations included TP53 (27.98%), ATRX (14.68%), NF1 (9.17%), and RB1 (7.80%). Homozygous deletions were most frequent in TP53 (28.7%), CDKN2A (20.5%), CDKN2B (19.48%), and RB1 (15.38%), while amplifications were most frequent in NCOR1 (6.29%) and FLCN (5.13%). Several mutations frequently co-occurred, while NF1 and RB1 demonstrated total mutual exclusivity. NCOA2 mutations were exclusive to White patients and NKX2-1 to non-White patients. Mutations in MAP2K4 and ALOX12B were unique to males, while SDHA mutations were unique to females.
Conclusion: As we enter the era of precision medicine, classifying cancers by molecular markers will become increasingly valuable. Our investigation enriches the literature by identifying novel mutations and mutations exclusive to certain demographic groups. These findings support a shift beyond histology toward molecularly informed diagnostics and pathway-directed therapeutic hypotheses for MFS. Next steps should validate candidate markers in independent cohorts and link genomic profiles to clinicopathologic features, disease course, and treatment response to improve clinical translation. These observations will help shape diagnostics and targeted therapies against MFS.
- Myxofibrosarcoma
- soft tissue sarcoma
- molecular markers
- somatic mutations
- copy number alterations
- AACR GENIE
- targeted therapy
Introduction
Myxofibrosarcomas (MFS) are an exceedingly rare and highly infiltrative type of soft tissue sarcoma (1). According to the 2020 World Health Organization Classification of Soft Tissue Tumors, MFS are categorized as malignant fibroblastic/myofibroblastic tumors (2). Histologically, all MFS tumors are defined by their characteristic abundant myxoid stroma (3). They may be classified as low-grade, intermediate-grade, or high-grade, depending on the degree of cellularity, nuclear pleomorphism, mitotic activity, and presence of tumor necrosis (3). MFS may be further stratified into the rare epithelioid variant, which carries a worse prognosis compared to non-epithelioid MFS and requires slightly different management (4).
MFS tumors have a propensity for the extremities but may grow in any anatomical location (1). Their onset is insidious, typically presenting as painless masses in adults between 60 and 80 years old, with one study citing a median age of 67 years old at diagnosis (1, 3, 5). Soft tissue sarcomas continue to increase in prevalence in the elderly population, yet elderly patients remain underrepresented in studies regarding the diagnosis and treatment of these cancers (6, 7). These tumors are somewhat more frequently encountered in males than females (3). The overall five-year survival rate is 60-70%, with this estimate varying based on poor prognostic factors including age older than 65 years old, male sex, tumor size greater than 5 cm, and the presence of distant metastases, among others (1, 8–10). The tumors are highly infiltrative into surrounding connective tissue, propelling local recurrence rates up to 39% (1). With the estimated incidence being less than 0.1 per 100,000 people per year, it is difficult to determine whether these tumors are more common in a specific geographic region or ethnicity (3). Likewise, it is difficult to determine risk factors specific to MFS. Most MFS tumors are idiopathic and are associated with increasing age, while a small subset have been correlated with prior ionizing radiation exposure (11).
The diagnosis of MFS is primarily established through histopathological evaluation (3). Magnetic resonance imaging (MRI) is the imaging modality of choice for assessing these lesions, typically revealing nodular or lobulated masses that appear as low-to-intermediate signal intensity on T1-weighted images and high signal intensity on T2-weighted images (3). A characteristic feature, known as the “tail sign,” reflects the tumor’s infiltrative growth pattern, which can complicate accurate assessment of tumor extent (3). Consequently, local surgical excision necessitates wide margins to optimize the likelihood of complete tumor removal, which importantly has been found to improve prognosis in both the younger and elderly patient populations over the age of 85 (3, 7). Although surgical resection remains the primary treatment approach, more advanced cases — as well as those involving the epithelioid subtype — frequently require adjuvant radiotherapy and/or chemotherapy (3). Radiation therapy has not been shown to improve overall survival but may reduce local recurrence of high-grade MFS or in cases where wide surgical margins cannot be obtained (12). Doxorubicin-based chemotherapy regimens may also be helpful in advanced or unresectable MFS tumors, particularly those greater than 10 cm in size (12, 13). The role of immunotherapy is still being uncovered as advances continue to be made regarding the discovery of targetable genomic mutations and copy number alterations (12).
As previously mentioned, the diagnosis of MFS is currently based on histology as no characteristic mutational burden or definitive molecular markers have been identified (3,14). However, several mutations have been implicated, with TP53 (46%), RB1 (18%), CDKN2A (16%), CDKN2B (16%), NF1 (11%), GNAS (9%), and ATRX (9%) being some of the most commonly cited abnormalities (14-16). Nevertheless, the question remains whether additional gene mutations exist that are not yet well-characterized or linked to MFS. With continued advancements in precision medicine, a more comprehensive molecular profile of MFS is imperative for both efficient diagnosis and targeted treatment, particularly for advanced cases. Thus, in this study, we aim to describe the mutational landscape of MFS and uncover potentially novel and targetable mutations.
Patients and Methods
Data source and genomic sequencing. This study was exempt from institutional review board (IRB) approval by Creighton University (Omaha, NE, USA), as the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE®) database utilizes de-identified, publicly available data. The cBioPortal platform (version 17.0-public) was used to access data on June 9, 2025. The retrieved data included clinical and genomic information dating back to 2017.
AACR Project GENIE® is a multi-institutional, collaborative genomic database comprising contributions from 19 cancer centers. It integrates sequencing data from various platforms, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and targeted gene panels ranging from 50 to 555 genes. Most sequencing data were derived from targeted gene panels (80%), followed by WES (15%) and WGS (5%). Average sequencing depths were approximately 30× for WGS, 150× for WES, and over 500× for targeted panels.
Tumor samples in GENIE include both tumor-only specimens (65%) and matched tumor-normal pairs (35%). Germline variant filtering is possible due to the matched pairs. Genomic data across institutions is collected through standardized protocols established by the Genome NEXUS initiative. While individual centers follow their own bioinformatic protocols for variant calling and annotation, commonly utilizing tools such as the Genome Analysis Toolkit (GATK) and ANNOVAR, they adhere to GENIE’s harmonization framework to ensure cross-institutional data compatibility. Nonetheless, some variability in sequencing and analysis methods may persist, and consequently, not all genes were profiled in every tumor sample. For all mutational frequency calculations, percentages were computed only among samples in which the gene was actually sequenced. This heterogeneity in gene coverage may contribute to apparent subgroup exclusivity for certain mutations. Samples in which a gene was not assayed appear as “Not profiled” in Figure 1.
OncoPrint of the most frequent genetic mutations in the patient cohort. An OncoPrint is a compact genomic visualization that displays multiple alteration types across many samples, enabling rapid identification of common, co-occurring, and mutually exclusive events. Each column represents a tumor sample, and each row represents a gene. Colored tiles indicate detected somatic mutations or copy number alterations, while gray tiles labeled “Not profiled” denote samples in which that gene was not sequenced. Asterisks (*) next to gene names indicate genes for which not all samples were profiled, and mutation frequencies for these genes were calculated only among profiled samples. Importantly, the percentages presented within this table include all mutation types for a given gene, including small variant mutations, copy number alterations, and structural variants.
The GENIE database provides somatic mutation profiles and basic clinical demographics, including patient age, sex, race, and ethnicity. Between-race mutational analyses included a “non-White” group, which included Asian and Black patients. Clinical outcome data are available for select cancer types; however, treatment information was not available for the MFS cohort analyzed in this study.
Cohort selection and study design. The study cohort was derived from a larger set of MFS cases within the GENIE database, and patients with a confirmed diagnosis of MFS were identified and included in the analysis. Tumors were categorized as primary, metastatic, locally recurrent, or distant metastases, and comparisons between these groups were conducted to identify gene-specific differences in mutation frequencies using chi-squared tests. Histological subtype and grade were not available for the MFS cohort.
Somatic mutation filtering. To ensure analytic rigor and clinical relevance, somatic mutations were filtered to include only non-synonymous variants: missense, non-sense, frameshift, and splice-site mutations. Inclusion criteria required a minimum variant allele frequency (VAF) of 5% and a sequencing depth of at least 100×. Synonymous mutations and variants of unknown significance were excluded. Mutation data were obtained from GENIE’s harmonized mutation annotation format (MAF) files, which standardize gene names, protein-level changes, and variant classification across all participating centers.
Copy number alteration and tumor mutational burden analyses. Copy number alteration (CNA) analysis focused on identifying recurrent homozygous deletions and gene amplifications, with event frequencies calculated across the cohort. Mutation frequencies were calculated using the total number of tumor samples rather than the number of patients with each mutation.
Statistical analysis. All statistical analyses were performed using R and RStudio (R Foundation for Statistical Computing, Boston, MA, USA). Samples with incomplete or missing data were excluded. Categorical variables were reported as frequencies and percentages, with group comparisons conducted using chi-squared tests. Continuous variables were expressed as means with standard deviations. Prior to hypothesis testing, data distributions were assessed for normality. Normally distributed variables were compared using two-sided Student’s t-tests, while non-normally distributed data were analyzed using the Mann-Whitney U test. To adjust for multiple comparisons, p-values were corrected using the Benjamini-Hochberg false discovery rate (FDR) method, with significance set at p<0.05.
Results
Patient cohort demographics. The study cohort was composed of 218 total samples collected from 202 patients with MFS. Ninety-nine (49%) of the patients were male, 98 (48.5%) were female, and 5 (2.5%) were of unknown sex. The vast majority of the sample included adults over the age of 18 years old; 217 (99.5%) of the samples were obtained from adults while only 1 (0.5%) sample was obtained from a pediatric patient. One hundred sixty patients (79.2%) identified as non-Hispanic and 16 (7.9%) as Hispanic. Ethnicity was unknown in 17 (8.4%) patients and was not collected in nine (4.5%) patients. One hundred fifty-five (76.7%) patients identified as White, 13 (6.4%) as Asian, seven (3.5%) as Black, and nine (4.5%) as another race not listed; 11 (5.4%) patients did not have a race listed. MFS was the primary tumor in 151 (69.3%) of the total samples and was a metastatic tumor in 36 (16.5%) of samples. Twenty-one (9.6%) samples represented local recurrences (Table I).
Demographics of the patient cohort.
Common somatic mutations and copy number alterations. The three most prevalent somatic mutations identified from this sample included TP53 (n=61; 27.98%), ATRX (n=32; 14.68%), and NF1 (n=20; 9.17%) (Figure 1). Other significant mutations included RB1 (n=17; 7.80%), NOTCH1 (n=10; 4.59%), KMT2D (n=10; 4.59%), ARID1B (n=10; 4.59%), TRAF7 (n=9; 4.13%), TERT (n=9; 4.13%), FLT3 (n=9; 4.13%), NOTCH3 (n=8, 3.67%), CREBBP (n=7; 3.21%), FAT1 (n=7; 3.21%), EP300 (n=7; 3.21%), PTEN (n=7; 3.21%), ARID1A (n=7; 3.21%), and ERBB3 (n=7; 3.21%).
Recurrent copy number alterations were common. Of these, homozygous deletions were most prevalent, observed in TP53 (n=56; 28.7%), CDKN2A (n=40; 20.5%), CDKN2B (n=38; 19.48%), RB1 (n=30; 15.38%), and MTAP (n=14; 12.28%). There were also marked amplifications in NCOR1 (n=10; 6.29%), FLCN (n=10; 5.13%), YAP1 (n=9; 5.06%), BIRC3 (n=8; 5.26%), and MAP2K4 (n=7; 3.59%).
Differences in genetics stratified by sex and race. After stratifying by sex, MAP2K4 (n=7; 6.74%; p=0.0141) and ALOX12B (n=5; 5.95%; p=0.0269) mutations were exclusively identified in samples from male patients, while SDHA (n=5; 5.10%; p=0.0275) was exclusively identified in samples from female patients. Eight (7.69%) ETV6 mutations occurred in samples from males while only 1 (1.00%) occurred in samples from females (p=0.0353). However, none of these sex-stratified mutations survived FDR correction (q=1.00 for all). There were no significant differences between males and females in the incidence of more common mutations, such as TP53, RB1, ATRX, and NF1 (Table II).
Comparison of genetic mutations between male and female patients.
When stratified by White versus non-White patients, NCOA2 (n=2; 40.00%; p=0.0308) and SOS2 (n=2; 40.00%; p=0.0308) were exclusively mutated in White patients, while NKX2-1 (n=2; 10.00%; p=0.0107) was exclusively mutated in non-White patients (Table III). Comparing Asian patients to Black patients, mutations in KMT2C were unique to Black patients (n=3; 50.00%; p=0.0245) (Table IV). Again, these race-stratified mutations did not survive FDR correction (q=1.00 for all).
Comparison of genetic mutations between White vs. non-White patients.
Comparison of genetic mutations between Asian and Black patients.
Co-occurring and mutually exclusive alterations. Several patterns of genetic mutations were identified that frequently occurred together. TP53 mutations co-occurred with RB1 mutations in 42/122 samples (p<0.001; q<0.001), while TP53 and ATRX mutations co-occurred in 33/127 samples (p=0.012; q=0.105). ATRX and RB1 mutations occurred together in 18/70 samples (p=0.002; q=0.030), whereas ATRX and NOTCH3 mutations co-occurred in 6/44 samples (p=0.009; q=0.100). NF1 and TERT mutations co-occurred in 4/31 samples (p=0.044; q=0.333). NF1 and RB1—two of the more prevalent genetic mutations—demonstrated total mutual exclusivity (p<0.001; q=0.018).
Primary vs. metastatic samples. As previously mentioned, 151 (69.3%) MFS samples represented primary tumors while 36 (16.5%) represented metastatic tumors. There were several genetic mutations that occurred in the metastatic tumors but not in the primary tumors, including HLA-DPA1, HLA-DRB1, KDM5D, and PALLD (n=1 for all; p=0.0131 for all), MLLT3 (n=1; p=0.0195), ERBB2 (n=2; p=0.0362), SOX2 (n=2; p=0.0400), SRSF2 (n=2; p=0.0409), and TBX3 (n=2; p=0.0485). In contrast, only one mutation was found to exclusively occur in the primary tumors, that being NCOA2 (n=2; p<0.001). That being said, while these findings met nominal significance (p<0.05), the FDR-adjusted values were consistently q=1.00. The more common genetic mutations associated with MFS, such as TP53, ATRX, NF1, and RB1, did not show any significant difference in prevalence in primary tumors versus metastatic tumors (Table V).
Distribution of genetic mutations found in primary tumors compared to metastasis sites.
Discussion
This investigation described the mutational landscape of MFS by aggregating data from the AACR Project GENIE repository. We identified novel and potentially targetable mutations to create a more robust molecular profile for MFS.
Novel mutations. We identified several novel mutations that have not been previously associated with MFS. These include NOTCH3, ALOX12B, SDHA, ETV6, NCOA2 and SOS2. NOTCH3 is implicated in many different cancers and may function either as an oncogene or tumor suppressor depending on the cancer type, stage, and grade (17). It has known associations with pediatric soft tissue sarcomas and osteosarcomas, but our study is the first to suggest its involvement in MFS (18). Interestingly, mutant NOTCH3 also underlies the pathology of CADASIL – a rare, inherited small vessel disease of the brain (19). Through disrupting the normally stable beta-sheet structure, mutant NOTCH3 undermines protein stability, inhibiting the survival and signaling of vascular cells (19). Similar effects may be seen with NOTCH3 disrupting the signaling of other healthy cells throughout the body, leading to tumorigenesis.
ALOX12B mutations, with established roles in cervical, breast, and lung cancer, had yet to be linked to any sarcoma cases until the present study (20). SDHA, while probably best known for its involvement in gastrointestinal stromal tumors, was recently linked to tumorigenesis of fibrosarcomas; our data further describes its involvement in MFS specifically (21). Both ETV6 and NCOA2 have been observed as fusion genes in certain sarcomas (22-25). The ETV6-NTRK3 fusion is a defining feature of infantile fibrosarcoma, while the VGLL2-NCOA2 fusion is observed in pediatric sarcomagenesis, and the MAZ-NCOA2 fusion was just recently described for the first time in a case of small round cell sarcoma of infancy (22-25). Our study could not determine whether the observed ETV6 and NCOA2 mutations were also present as fusion genes, but to our knowledge, this series is the first of its kind to characterize their involvement in MFS. Lastly, we present the first documented account of SOS2 in both MFS specifically and sarcomas more broadly. Collectively, we have documented several novel mutations that will shape the future of both detailed molecular profiling and targeted therapeutics for MFS.
Genetic alterations stratified by sex. Consistent with previous studies, our study cohort consisted of slightly more men than women with MFS (3). Predictably, many of the more common and well-known genetic mutations associated with MFS appeared in both men and women with no significant differences between these two groups, including TP53, RB1, ATRX, CDKN2A, CDKN2B, and NF1 (14-16). Notably, our data also revealed several mutations exclusive to either men or women within our limited sample size. Within our cohort, MAP2K4 and ALOX12B mutations were unique to men, whereas SDHA mutations were unique to women. ETV6 mutations were more frequently observed in men compared to women. MAP2K4 mutations have been previously shown to occur somewhat frequently in all soft tissue sarcomas, including MFS (26). However, as detailed above, we are the first to describe alterations in ALOX12B, SDHA, and ETV6 as being linked to MFS. While the novelty of these mutations certainly invites investigation into new diagnostic and therapeutic targets, taken together, these data further suggest the potential for new targets on the basis of patient sex. However, given the low event counts and failure to survive FDR-correction, these findings should ultimately be considered exploratory pending further validation with a larger cohort.
Genetic alterations stratified by race. While MFS tumors are not known to favor any particular race or ethnicity, our study cohort was predominantly composed of White patients (76.7%), followed by Asian patients (6.4%), Black patients (3.5%), and the remaining being another race or unknown race. Comparison of White patients against non-White patients revealed no significant differences in the incidence of more common MFS-associated mutations, such as TP53, RB1, ATRX, CDKN2A, CDKN2B, and NF1. However, two mutations – NCOA2 and SOS2 – were observed exclusively in White patients. As previously mentioned, this is the first study to associate NCOA2 and SOS2 mutations with MFS to date. Their exclusivity to White patients within our limited data set further adds to the robust molecular profile of MFS from a population-based standpoint, which may be of particular interest in targeting therapies to specific patient populations.
In contrast, NKX2-1 mutations were observed exclusively in non-White patients. Prior research has demonstrated that NKX2-1 alterations are unique to MFS compared to other soft tissue sarcomas, such as leiomyosarcoma, de-differentiated liposarcoma, and undifferentiated pleomorphic sarcoma (15). Our study’s finding that these mutations are uniquely seen in non-White patients may be of additional utility in the targeting of future therapies to certain population groups. Importantly, due to the limited number of samples analyzed in our study and their failure to survive FDR-correction, it is plausible that these race-specific findings are due to chance. Thus, these results require additional validation using different sample pools, such as other gene-sequencing panels or data from various medical centers.
Comparative analysis between Black and Asian patients revealed an incidence of KMT2C mutations in three samples from Black patients compared with zero samples from Asian patients. KMT2C has been previously linked to DNA transcription and repair and interestingly seems to encourage proliferation of certain cancers, such as squamous cell carcinoma of the lung, while protecting against development of others, such as renal clear cell carcinoma (27, 28). Although KMT2C alterations are a marker for certain sarcomas, including osteosarcoma, their incidence in MFS has not been consistently described (29). Its novel occurrence in Black patients from our study’s cohort suggests it may have a yet uncharacterized role in MFS development or progression.
Cell cycle and checkpoint pathway alterations. While the landscape of MFS mutations is heterogeneous, mutations to cell cycle and checkpoint pathway alterations have been previously implicated as a leading genetic anomaly (14-16). Both mutations and deletions of TP53 and RB1 promote tumorigenesis by allowing for unrestricted movement through the cell cycle (14). Our results give further credence to the association of TP53 and RB1 mutations with higher-grade cases of MFS as well as a more rapid recurrence post-treatment (30, 31). Similarly, deletions of CDKN2A and CDKN2B are common, having been identified in 20.5% and 19.48% of our cohort’s tumor samples, respectively. Previous research has found the incidence of CDKN2 mutations to be between 16%-30% (15, 16). Collectively, these findings are consistent with existing literature, confirming that alterations to cell cycle and checkpoint pathway alterations have a crucial function in the development of MFS. However, as these mutations are non-specific to MFS, they cannot reliably be used for definitive molecular diagnosis.
NF1 and RAS-MAPK pathway. Mutations to NF1 were also commonly observed in this study. NF1 encodes neurofibromin, which keeps RAS proteins in their inactive state (32). Therefore, loss of function of NF1 leads to constitutive activation of RAS, promoting unchecked cell signaling through the RAS-MAPK pathway (33). In 2013, a study performed by Dodd et al. found that MEK inhibitors showed promise in treating NF1-deleted sarcomas in mice (34). Selumetinib, a MEK inhibitor, was subsequently trialed in human patients and showed effectiveness in treating inoperable plexiform neurofibromas and low-grade gliomas, as well as in improving progression-free survival in leiomyosarcoma patients (35, 36). A clinical trial with another MEK inhibitor, Cobimetinib, is currently ongoing for its utility in locally advanced and/or metastatic soft tissue sarcomas (37). As we enter the era of precision medicine, MEK inhibition represents a possible new target for NF1-deleted tumors and should be further examined for MFS specifically. Previous studies, however, have shown that cancer cells may quickly develop resistance to these agents through subsequent loss of inhibitory genes such as CDKN2 which may limit the effectiveness of these agents in MFS, since MFS has been shown to frequently exhibit CDKN2 driver mutations (15, 16, 35).
ATRX and the alternative telomere lengthening (ALT) pathway. Mutations to ATRX were another leading alteration, present in 14.68% of the collected samples. ATRX encodes proteins crucial for chromatin remodeling and is therefore essential for maintaining the stability of DNA (15). ATRX further functions to suppress the ALT pathway, which may be hijacked by cancer cells (38). When mutated or deleted, ATRX can no longer suppress this pathway, allowing cells to proliferate uncontrollably (38). Prior research has revealed that ATRX deletions are frequently seen in solid tumors, particularly in soft tissue sarcomas like MFS (39).
The current treatment guidelines for localized MFS recommend surgical resection with adjunctive radiation therapy (3, 12, 40). Radiation therapy reduces local recurrence rates but has not been shown to improve overall survival (3, 12, 40). However, it is possible that the role of radiation is more far-reaching than what is currently being utilized in clinical practice. Interestingly, a study conducted by Floyd et al. adopted a mouse model of ATRX-deleted soft tissue sarcomas, finding that these tumors were more sensitive to radiation therapy compared to tumors without the ATRX deletion (39). Together, these findings suggest that ATRX-deleted MFS tumors may be more responsive to radiation than ATRX-positive tumors, possibly requiring a lower dose of radiation or fewer treatment sessions than previously thought compared to tumors not demonstrating this mutational burden. Radiation therapy may also act as an increasingly important arm of therapy in the treatment of metastatic MFS when the tumors harbor ATRX deletions.
TERT pathway. Telomerase reverse transcriptase (TERT) mutations were present in 4.13% samples. TERT, which encodes telomerase, is reactivated in a multitude of cancers and is another method by which cancer cells may attempt to preserve their immortality (41). Interestingly, these mutations are not seen as frequently in MFS as they are in other cancers. Previous studies have investigated the presence of TERT promoter mutations in a variety of soft tissue sarcomas, reporting they are most frequently associated with myxoid liposarcomas compared to other soft tissue sarcomas (42, 43). Rather than being TERT-driven, MFS tumors may alternatively rely more heavily on ATRX mutations and the subsequent activation of the alternative telomere lengthening pathway (38, 44). This information may be helpful in better understanding the pathogenesis of MFS and delineating the targeted therapies to which it will best respond.
Early-stage clinical trials of TERT or telomerase inhibitors have unfortunately failed to demonstrate clinical efficacy thus far in a variety of solid tumors, with research ongoing to better understand the lack of response (45). A recent study from February 2025 explored the ALT pathway, finding that ATRX-deleted tumors are successful in activating this pathway due to concurrent suppression of the cGAS-STING pathway, allowing the cells to evade immune detection (46). The authors therefore concluded that a potential avenue for future research may involve reactivating STING in ATRX-deleted tumors, therefore suppressing the means by which the cancer cells maintain telomere length (46). These findings may be foundational to future treatments that can target ATRX-deleted tumors and should therefore be more closely examined in the context of MFS.
Co-occurring mutations. Several co-occurring mutations were identified, including TP53 and RB1, TP53 and ATRX, ATRX and RB1, ATRX and NOTCH3, and NF1 and TERT. The frequent co-occurrence of TP53, RB1, and ATRX has been previously established by several studies as these are consistently among the most common mutations seen in MFS (15, 16). While TP53 and RB1 deletions work synergistically to promote rapid, unchecked movement through the cell cycle, ATRX deletions allow for cancer cells to escape senescence (30, 31, 38). The collective presence of these three mutations lays a foundation upon which cells may replicate indefinitely, driving aggressive tumor formation.
TP53 and RB1 mutations may co-occur in up to 60% of MFS tumors (47). Tumors with these co-existing mutations positively express Skp2, a cell cycle proto-oncogene (47). Cancers with concurrent loss of both TP53 and RB1 become heavily dependent on Skp2 for degradation of p21 and p27 in order to drive progression through the cell cycle (47). Pevonedistat is a neddylation-activating enzyme inhibitor that blocks Skp2, and it has been shown to decrease growth of both TP53/RB1-negative MFS and undifferentiated pleomorphic sarcoma (UPS) in patient-derived cell lines and mouse xenografts (47). A phase I clinical trial demonstrated general efficacy for Pevonedistat in several different cancers, but neither this medication nor other Skp2 inhibitors have been specifically trialed in human patients with MFS (48). Hu et al. published a 2024 study investigating novel Skp2 inhibitors, finding a specific compound which shows promising utility in designing future cancer therapies (49). As cancer treatment continues to become more individualized, it may be worthwhile to continue exploring this pathway as a potential treatment target for MFS.
The co-occurrence patterns of ATRX and NOTCH3 as well as NF1 and TERT in MFS are not well-characterized in the current literature. As previously discussed, TERT has not been frequently identified as a common mutation in MFS as the cancer seems to instead rely on ATRX deletions to achieve immortality (38, 42). Additionally, NOTCH3 has not been previously identified in other large-scale studies on the mutational landscape of MFS and therefore may be a novel mutation in our study as well (15, 16). As such, future research is warranted to better characterize the role of NOTCH3 and to understand the significance of its co-occurrence with ATRX. It is possible their co-existence is due to the general prevalence of ATRX, but additional studies are necessary to clarify the basis of their interaction.
Mutually exclusive alterations. Interestingly, total mutual exclusivity was demonstrated in two of the more prevalent genetic mutations, NF1 and RB1. The existing body of knowledge, while describing the high frequency of these mutations, does not specify whether these alterations co-exist within the same patient’s tumor or whether they are merely common to these tumors generally. To date, there are no studies detailing that these mutations have demonstrated total mutual exclusivity. While this observation seems contradictory to the current evidence, we hypothesize two potential explanations.
First, an early mutation in either NF1 or RB1 may make the other redundant. For example, loss of NF1 leads to constitutive activation of RAS. RAS, in turn, increases expression of cyclin D, which binds to CDK4/6 and phosphorylates RB1, thereby inactivating it (33, 50). Should the mutation in NF1 occur upstream of an RB1 mutation, an additional mutation in RB1 may not confer a selective advantage for the tumor. Conversely, an early loss of RB1 may make an upstream mutation in NF1 unnecessary as well, as the tumor already possesses the ability to bypass cell cycle checkpoints. The temporality of these mutations should be studied in subsequent research. Secondarily, it is possible that a mutation in either NF1 or RB1 is associated with a specific grade of MFS and is therefore exclusively seen in low- or high-grade tumors. Our present study did not distinguish which mutations were associated with which tumor grade, so it is entirely possible that one of these mutations may demonstrate preference for a certain tumor grade.
Primary vs. metastatic samples. As previously discussed, the majority of the common genetic mutations associated with MFS did not significantly differ in prevalence between primary and metastatic tumors. The only mutation exclusive to primary tumors was NCOA2. The existing body of knowledge does not describe NCOA2 mutations as being associated with MFS cases, though these alterations are present in other sarcomas as fusion genes, demonstrated in alveolar/embryonal rhabdomyosarcoma, spindle cell rhabdomyosarcoma, mesenchymal chondrosarcoma, uterine sarcoma, and small round cell sarcoma of infancy (24, 51). It is unlikely that this mutation has a significant role in the development of MFS primary tumors or metastatic lesions, but recognizing its incidence will help further delineate the molecular profile of MFS. It is most plausible that this mutation is exclusively identified in primary tumors due to its overall rarity in MFS, further supported by the fact that the mutation was only present in two samples from the cohort.
Several other mutations were exclusive to metastatic tumors, including HLA-DPA1, HLA-DRB1, KDM5D, PALLD, MLLT3, ERBB2, SOX2, SRSF2, and TBX3. None of these mutations are known as key drivers of primary or metastatic lesions of MFS. Given the low overall incidence of these mutations, combined with their failure to survive FDR-correction, it is reasonable to suggest that they do not have a major influence on the metastatic spread or overall aggressiveness of the tumors. The current dominant catalysts of metastatic transformation include genetic mutations of TP53, RB1, CDKN2, NF1, ATRX, and other common driver mutations (15). Heitzer et al. found that metastatic MFS tumors actually tended to demonstrate a less complex karyotype than the primary tumors (14). The significance of these more infrequent genetic alterations should be further investigated; as we progress toward being able to define MFS by a distinct molecular profile, it is important to note even small aberrations as they may further characterize tumor behavior or incidence in certain populations.
Study limitations. We acknowledge the limitations in our study. First, the relatively small cohort size may reduce the statistical power of our findings, underscoring the need for larger future studies. The GENIE database may introduce confounding factors, such as the inclusion of multiple tumor samples from the same patient; however, prior studies suggest this risk is minimal. Additionally, the platform lacks data on miRNA, DNA methylation, and transcriptional changes, limiting our ability to link mutations with pathway-level effects, tumor behavior, and treatment response. It also does not provide information on the timing of mutations, making it difficult to distinguish early drivers from later, potentially metastatic mutations. The absence of histological subtype or tumor grade stratification further prevented subtype-specific analysis. Moreover, the lack of treatment data precluded assessment of mutation-specific outcomes or therapeutic responses. Finally, variability in sequencing methods across contributing institutions may introduce reporting bias. Despite these limitations, our study contributes to the growing molecular understanding of MFS by highlighting key and potentially novel driver mutations relevant to future research and clinical applications.
Conclusion
Diagnosis of MFS currently relies on histopathological analysis, but we are quickly approaching an era of medicine where we will instead be able to define MFS by its distinct molecular profile. Our investigation enriches the current literature by describing the relevance of common genetic mutations in the context of their respective pathways, such as TP53, RB1, CKDN2, NF1, ATRX, and TERT. We are the first to characterize the novel involvement of NOTCH3, ALOX12B, SDHA, ETV6, NCOA2 and SOS2 in MFS, as well as to identify the mutual exclusivity of NF1 and RB1 mutations in MFS. We also note alterations that are exclusive to certain demographic groups based on their sex or race. In continuing to define the mutational landscape of MFS, efforts should focus on understanding the clinical value of these novel mutations, especially those exclusive to certain patient populations. Notably, subsequent studies must also correlate our findings with tumor behavior, clinical course, and treatment response. As we enter the transformative age of precision medicine, this pursuit will enable the ability to better characterize, target, and predict the behavior of MFS.
Acknowledgements
Not applicable.
Footnotes
Authors’ Contributions
E.T. and B.H. conceived and designed the study. M.N. and B.R. curated and analyzed the data and drafted the original manuscript. M.N., B.R., and M.B. reviewed and edited the manuscript. E.T., A.T., and A.M. supervised the project while A.T. and A.M. acted as project administrators. All Authors have read and agreed to the published version of the manuscript.
Data Availability Statement
The datasets analyzed for this study can be found in the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE®) database: genie.cbioportal.org
Conflicts of Interest
The Authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Funding
Not applicable.
Artificial Intelligence (AI) Disclosure
No artificial intelligence (AI) tools, including large language models or machine learning software, were used in the preparation, analysis, or presentation of this manuscript.
- Received November 16, 2025.
- Revision received December 1, 2025.
- Accepted December 9, 2025.
- Copyright © 2026 The Author(s). Published by the International Institute of Anticancer Research.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.







