Although solitary fibrous tumors (SFTs) have an unpredictable evolution, some specific clinicopathologic factors have been associated with the final outcome. We retrieved clinical, pathological and molecular data of 97 patients with a histological diagnosis of SFT and Signal transducer and activator of transcription 6 (STAT6) positivity. We retrospectively studied the pathological factors predictive of recurrence/metastasis and compared them with the clinical outcome. A wide immunohistochemical study and molecular analysis to detect NAB2/STAT6 gene fusion, tumor protein-53 (TP53) and/or (telomerase reverse transcriptase) TERT promotor mutation were performed. The risk of metastasis was calculated using the Demicco risk stratification system (RSS). The results were combined and examined to assess the accuracy of risk stratification and classification. The most common location was in non-extremities; 66% were located in soft tissue or subcutaneous areas and 92.8% in deep locations. On microscopic analysis, 38.1% of tumors revealed hypercellularity with a predominant patternless and/or hemangiopericytic growth pattern; 13.4% had ≥4 mitoses/10HPF; 16.5% showed necrosis, and almost half the tumors showed at least focal myxoid areas. Dedifferentiation was observed in three tumors. Immunomarker expression in SFTs was as follows: CD34 92.9%, CD99 57.1%, Bcl2 67.9%, neuroendocrine markers (at least 1) 25.7%, Desmin 14.3%, CK(AE1/AE3) 3%, Apoptotic Protease Activating Factor (APAF-1) 87% and finally Ki-67 ≥ 10% in 14.4%. The NAB2/STAT6 gene fusion was detected in 50 tumors. After a median follow-up of 90 months, 9.3% recurred, 11.3% metastasized, 10.3% died of disease and 76.2% were free of disease. TERT mutations were detected in 40.6% of the SFTs; the TP53 mutation was detected in 17%, and only 9.3% showed both mutations. According to the Demicco RSS, 6.1%, 11.3% and 82.4% of the tumors were classified as high, intermediate or low-risk of metastasis, respectively. All high-risk tumors had ≥4 mitoses/10HPF, necrosis, Ki-67 ≥ 10, HTER and/or TP53 mutation and poor evolution. The intermediate risk SFTs with worse evolution displayed the HTER mutation. Almost all low-risk tumors had a favorable evolution, although four showed at least one adverse factor (Ki-67 ≥ 10, ≥4 mitoses/10HPF or high tumor size) and had a worse evolution. An integration of clinical, morphologic, immunohistochemical and molecular findings may improve risk stratification and classification and better predict patient outcome. The unfavorable course seems to be more frequent in high-risk SFTs, although it is not exceptional in low-risk SFTs either; hence, a long-term follow-up is required independently of the assigned risk stratification score. The inclusion of molecular findings in risk stratification systems could improve the precision in the classification of SFTs, especially those of intermediate risk. Future studies will be required to determine the most effective way to incorporate molecular analyses into RSS on SFTs. The coexistence of several adverse factors such as ≥4 mitoses/10HPF, necrosis, Ki-67 ≥ 10%, mutations in HTER and/or p53 may suggest a closer clinical follow-up regardless of the histological appearance of the tumor.

The clinical evolution of solitary fibrous tumors (SFTs) is often uncertain and several risk stratification systems (RSS) have been proposed. The Demicco et al. RSS is the most frequently implemented. In this study we aim to validate two alternative RSS (Sugita et al. and G-Score) using results for the Demicco RSS from a previous study of 97 SFTs. In addition, we aim to determine whether reclassified cases had any distinctive molecular features. As the Sugita et al. system substitutes mitotic count with Ki-67 index we also investigated whether Ki-67 results for tissue microarrays are comparable to those obtained using whole tissue sections. In the present study we detected that many cases classified by Demicco RSS as low-risk were reclassified as intermediate risk using the new system (G-score RSS). Kaplan-Meier survival plots for G-Score RSS showed that the low-risk and intermediate-risk SFTs had a similar evolution that contrasted with the more aggressive high-risk group. Moreover, the similar evolution in both low and intermediate-risk groups occurred despite the G-score system being stricter in classifying low-risk tumors. We observed that Sugita RSS does not provide any better risk stratification in comparison with the Demicco RSS, and testing both RSS in our series produced similar Kaplan-Meier survival data. We found some discordant results when comparing whole sections and the corresponding tissue microarrays samples, finding the hotspot areas easier to locate in whole sections. Forty-one SFTs with initial low-risk assigned by the Demicco RSS were reclassified as intermediate-risk by G-score finding both TP53 and HTER mutations in four cases, only HTER mutation in 11 cases, and only TP53 mutation in 2 cases. All six cases of SFT classified as high-risk by both the Demicco and G-score RSS suffered recurrence/metastasis, and half showed both TP53 and HTER mutations. Five SFTs were categorized as low-risk by both Demicco and G-score, of which 4 cases revealed HTER mutation. Regarding the outcome of these 5 patients, two were lost to follow-up, and one of the remaining three patients suffered recurrence. We believe that although the presence of both TP53 and HTER mutations may confer or be related to poor evolution, the isolated presence of HTER mutation alone would not necessarily be related to poor outcome. The G-score RSS more accurately identified low-risk patients than the other two risk models evaluated in the present series. Late recurrence/metastasis may occasionally be observed even in low-risk SFTs categorized by stricter classification systems such as the G-score RSS. These findings support the possibility that additional, as yet unknown factors may influence the clinical evolution of SFTs. In conclusion, given the possibility of late recurrence, long-term follow-up is recommended for all SFT patients, even in cases classified as low risk by the stricter G-score system. An integration of clinical, radiological, pathological, and molecular findings may improve SFT risk stratification and better predict patient outcome.

Background: Angiosarcomas (ASs) represent a heterogeneous and highly aggressive subset of tumors that respond poorly to systemic treatments and are associated with short progression-free survival (PFS) and overall survival (OS). The aim of this study was to develop and validate an immune-related prognostic model—termed the AS score—using data from two independent sarcoma cohorts. Methods: A prognostic model was developed using a previously characterized cohort of 25 angiosarcoma samples. Candidate genes were identified via the Maxstat algorithm (Maxstat v0.7-25 for R), combined with log-rank testing. The AS score was then computed by weighing normalized gene expression levels according to Cox regression coefficients. For external validation, transcriptomic data from TCGA Sarcoma cohort (n = 253) were analyzed. The Immunoscore—which reflects the tumor immune microenvironment—was inferred using the ESTIMATE package (v1.0.13) in R. All statistical analyses were performed in RStudio (v 4.0.3). Results: Four genes—IGF1R, MAP2K1, SERPINE1, and TCF12—were ultimately selected to construct the prognostic model. The resulting AS score enabled the classification of angiosarcoma cases into two prognostically distinct groups (p = 0.00012). Cases with high AS score values, which included both cutaneous and non-cutaneous forms, exhibited significantly poorer outcomes, whereas cases with low AS scores were predominantly cutaneous. A significant association was observed between the AS score and the Immunoscore (p = 0.025), with higher Immunoscore values found in high-AS score tumors. Validation using TCGA sarcoma cohort confirmed the prognostic value of both the AS score (p = 0.0066) and the Immunoscore (p = 0.0029), with a strong correlation between their continuous values (p = 2.9 × 10⁻⁸). Further survival analysis, integrating categorized scores into four groups, demonstrated robust prognostic significance (p = 0.00021). Notably, in tumors with a low Immunoscore, AS score stratification was not prognostic. In contrast, among cases with a high Immunoscore, the AS score effectively distinguished outcomes (p < 0.0001), identifying a subgroup with poor prognosis but potential sensitivity to immunotherapy. Conclusions: This combined classification using the AS score and Immunoscore has prognostic relevance in sarcoma, suggesting that angiosarcomas with an immunologically active microenvironment (high Immunoscore) and poor prognosis (high AS score) may be prime candidates for immunotherapy and this approach warrants prospective validation.