Next Article in Journal
Suppressors of Cytokine Signaling and Hepatocellular Carcinoma
Next Article in Special Issue
Telomere as a Therapeutic Target in Dedifferentiated Liposarcoma
Previous Article in Journal
Prognostic Value of Preclinical Markers after Radiotherapy of Metastatic Spinal Cord Compression—An Additional Analysis of Patients from Two Prospective Trials
Previous Article in Special Issue
Pediatric Sarcomas: The Next Generation of Molecular Studies
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The Molecular Biology of Soft Tissue Sarcomas: Current Knowledge and Future Perspectives

1
INSERM U830, Équipe Labellisée Ligue Nationale Contre le Cancer, Diversity and Plasticity of Childhood Tumors Lab, Institut Curie Research Center, PSL Research University, 75005 Paris, France
2
Department of Medical Oncology, Institut Curie Hospital, 75005 Paris, France
*
Author to whom correspondence should be addressed.
Submission received: 30 April 2022 / Revised: 15 May 2022 / Accepted: 21 May 2022 / Published: 22 May 2022

Abstract

:

Simple Summary

Over the past 20 years, significant advances in the field of genetics and molecular biology have led to the dismantlement of multiple subtypes of sarcomas. As a result, molecular approaches nowadays play a critical role in the diagnosis, prognostic classification, and therapeutic management of numerous mesenchymal tumor subtypes. This review of the current literature illustrates the main uses of molecular biology in the field of soft tissue sarcomas and the future challenges that remain to be addressed.

Abstract

Soft tissue sarcomas are malignant tumors of mesenchymal origin, encompassing a large spectrum of entities that were historically classified according to their histological characteristics. Over the last decades, molecular biology has allowed a better characterization of these tumors, leading to the incorporation of multiple molecular features in the latest classification of sarcomas as well as to molecularly-guided therapeutic strategies. This review discusses the main uses of molecular biology in current practice for the diagnosis and treatment of soft tissue sarcomas, in addition to perspectives for this rapidly evolving field of research.

1. Introduction

Soft tissue sarcomas comprise all malignant tumors that develop from soft tissues in the body and that are thought to derive from a mesenchymal origin. They are mostly rare tumors and characterized by a large clinical and biological heterogeneity, with more than 100 different subtypes in the latest WHO classification [1]. Their management is therefore complex and historically based on histological characteristics, but it has been transformed by the help of molecular biology for diagnosis and treatment [2]. Indeed, while sarcomas can be classified according to their microscopic appearance and probable mesenchymal cell-of-origin, it has become clear that many subtypes are characterized by specific genomic alterations that not only help to refine the diagnostic process but most importantly to understand their oncogenesis, which is paramount for prognosis and treatment. Accordingly, the latest WHO classification puts ever greater emphasis on molecular alterations in the definition of some subtypes of sarcomas [1]. In this review, we will discuss the current state-of-the-art for molecular diagnosis and treatment of soft tissue sarcomas, with a focus on well-established techniques but also on near future perspectives for this rapidly changing and promising field of molecular biology of sarcomas.

2. Molecular Biology for Sarcoma Diagnosis

Cancer diagnosis is classically based on pathology, with the consequence that cancers are usually classified according to their organ and/or supposed tissue of origin. However, cancer is primarily a genetic disease, and it has become clear that pathologically homogeneous cancers can harbor a large heterogeneity in their underlying genetic make-up. Since the genetic alterations leading to oncogenesis are determining for the behavior of the tumor, it has become increasingly essential to characterize them for better diagnosis, let alone prognosis, and potentially treatment guidance.
This is no exception for soft tissue sarcomas: the classification is historically based on histological characteristics, but molecular biology has allowed the refinement of the diagnostic nosology of this large and heterogenous group of tumors. For simplicity, sarcomas are classically divided into two groups based on genomic characteristics: (1) sarcomas with a single driver molecular alteration (or sarcomas with “simple genetics”) and (2) sarcomas with a complex genomic profile (sarcomas with “complex genetics”) [3]. The former group comprises sarcomas that are defined by specific driver molecular alterations, mainly oncogenic gene fusions, but also activating or inactivating mutations, or gene amplifications. Therefore, their overall genomic profile is usually “simple” with near-diploid karyotypes, meaning that there are few other genomic alterations other than the driver alteration. If the oncogenic properties of all the gene fusions found in rare sarcomas have not yet been assessed in relevant models, their similarities in terms of structure, the homogeneity of the gene expression profiles of tumors with a given fusion, as well as the scarcity of other genomic alterations found in their genomes, suggest that these molecular alterations are a very early driver event in the oncogenesis of these tumors. This contrasts with the second group of sarcomas which harbor highly rearranged genomic profiles, with large numbers of chromosomal and copy number alterations as well as point mutations including of tumor-suppressor genes, often reflecting genomic instability. This binary classification is probably oversimplifying, and it may be misleading, for instance dedifferentiated liposarcoma is characterized by a driver alteration (MDM2 amplification), but it also has a highly rearranged genomic profile [4].
For the group of sarcomas with a driver alteration, molecular biology is logically essential for their accurate diagnosis and characterization. For other sarcomas, it also has the potential to inform diagnosis, especially as a useful tool to distinguish them from morphologically similar benign tumors.

3. Sarcomas with “Simple Genetics”

Sarcomas with a simple genetic driver alteration represent 30% to 40% of soft tissue sarcomas. They are characterized by specific molecular alterations that are usually pathology-defining, therefore molecular biology is essential to make the diagnosis. Classically, these molecular alterations are divided into oncogenic gene fusions, activating and inactivating point mutations, and gene amplifications.

3.1. Gene Fusions

The most common driver alterations in sarcomas are gene fusions. A large number of sarcomas are translocation related, i.e., the result of a chromosomal translocation giving rise to a fusion gene encoding an oncogenic fusion protein, usually a chimeric transcription factor [5]. The paradigm of this model of oncogenesis is Ewing sarcoma [6]: this tumor which develops from bone but also soft tissues in young adults and adolescents is characterized by a translocation between chromosomes 11 and 22, giving rise to a fusion gene EWS-FLI1, leading to a chimeric transcription factor with oncogenic properties [7]. In recent years, dozens of other sarcoma-defining gene fusions have been described, thus extending the number of subtypes of oncogenic fusion-driven sarcomas and refining the classification of often similar-looking but biologically different tumors. Most gene fusions involve transcription factors, though some may lead to constitutive activation of a tyrosine kinase receptor or growth factor (Table 1).
In clinical practice, diagnosis of the oncogenic fusion is done using molecular techniques such as fluorescence in situ hybridization (FISH), reverse transcription–polymerase chain reaction (RT-PCR), or targeted RNA sequencing [8]. The former detects rearrangement of genes involved in the fusion, while RT-PCR and targeted RNA sequencing search for the resulting RNA transcript in tumor cells. While both methods are highly sensitive, specific, and accessible in most routine labs, they are targeted assays, and they require a good a priori knowledge of the differential diagnoses.
In contrast, a more recent technique based on next-generation sequencing and increasingly used for diagnosis of sarcomas is whole transcriptome profiling (RNA sequencing, RNA-seq). Using this unsupervised technique, a single assay can detect every possible gene fusion leading to a fusion transcript, including yet undescribed oncogenic fusion transcripts. In addition to its powerful fusion detection capacity, profiling the whole transcriptome enables refining, and it helps in classification using transcriptomic similarity to other sarcomas. In this way, novel entities with homogeneous transcriptomic profiles and specific gene fusions have been described. For instance, Watson et al. used RNA-seq to characterize a group of 180 sarcomas for which no diagnosis could be made using FISH or RT-PCR [9]. A gene fusion was detected in more than half of cases, including several previously uncharacterized fusion transcripts. Moreover, whole-transcriptome profiling allowed high-dimensional clustering of sarcomas, showing that most fusion genes are associated with a characteristic transcriptomic profile, and that some sarcomas with differing fusion transcripts can be grouped into transcriptomically homogeneous entities, such as CIC-fused sarcomas which comprise CIC-DUX4, CIC-FOX4, and CIC-NUTM1 sarcomas. Thus, transcriptomic profiling, and more generally molecular profiling, allows a grouping of sarcomas that may differ from simple pathological diagnosis or gene fusion detection: one can envision that techniques such as RNA-seq could lead to a novel classification of sarcomas complementary of the present pathologically oriented classification. Indeed, some centers such as the Institut Curie are using RNA-seq to help in the diagnosis of sarcomas, primarily for gene fusion detection but also for transcriptomic clustering. Of note, whereas initial use of RNA-seq was restricted to fresh frozen tissues, it has now evolved and can also be performed on paraffin-preserved tissues [10]. RNA-seq has since allowed the characterization of novel fusion genes such as CIC-NUTM1 [11], TFCP2-rearranged [12], EWSR1-SSX1 [13], as well as the identification of NTRK-rearranged sarcomas [14] or NRG1-fused sarcomas [15]. It has also led to the identification of different molecular subgroups of entities previously considered as pathologically homogeneous, for instance pediatric and spindle cell rhabdomyosarcomas [16,17]. These molecular alterations defining homogeneous groups of sarcomas have mostly been integrated in the current classification scheme as an essential complementary information to pathology [1].

3.2. Mutations

While gene fusions constitute the most frequent molecular alterations in sarcomas, some subtypes are characterized by mutations of specific genes, either oncogenesis “driver” genes (activating mutations), or tumor suppressor genes (inactivating mutations).

3.2.1. Activating Mutations

Though rare in the number of subtypes, some sarcomas present activating mutations in “driver” genes as their primary oncogenic mechanism. The paradigm of this are gastrointestinal stromal tumors (GISTs) that are characterized by gain-of-function mutations of the KIT gene (85%), and less often the PDGFRA gene (5%), which are both mutually exclusive and lead to constitutive activation of these transmembrane receptors and their downstream signaling pathways [18,19,20,21]. GISTs are the most common mesenchymal tumors of the gastrointestinal tract and molecular diagnosis has transformed their management. In clinical practice, these diagnosis-defining mutations are detected in tumor DNA by Sanger sequencing or gene panel targeted next-generation sequencing.

3.2.2. Inactivating Mutations

Several sarcomas are associated to inactivating mutations of tumor suppressor genes. As in most cancers, genes such as TP53 and PTEN are frequently mutated during the course of oncogenesis [4,22,23], but some inactivating mutations constitute the primary molecular alteration. For instance, malignant peripheral nerve sheath tumors (MPNST) are characterized by mutations in the NF1 tumor suppressor gene (50%) [24]. Perivascular epithelioid cell tumors (PEComas) are associated with mutations in TSC1 and TSC2 with subsequent activation of the mTOR pathway [25,26]. Another group of sarcomas, BAF-deficient sarcomas, harbor mutations in genes of the BAF (also called SWI-SNF) complex: epithelioid sarcomas [27] and malignant rhabdoid tumors including atypical teratoid/rhabdoid tumors (ATRTs) of the central nervous system (SMARCB1 mutations) [28], small cell carcinomas of the ovary, hypercalcemic type (SCCOHT), and SMARCA4-deficient thoracic sarcomas (SMARCA4 mutations) [29,30]. It has been shown recently that a subgroup of ATRTs have mutations of SMARCA4, and they are distinct from classical SMARCB1-mutated ATRTs [31]. The BAF complex is involved in chromatin remodeling and highlights the essential role of epigenetics in the pathogenesis of sarcomas. In clinical practice, these mutations can be found in tumor DNA by Sanger sequencing or gene panel targeted next-generation sequencing. Moreover, loss of proteins of the BAF complex can be shown using immunohistochemistry.

3.3. Gene Amplifications

A significant proportion of sarcomas harbor gene amplifications, the most frequent of which is the 12q amplification characteristic of adipocytic tumors: atypical lipomatous tumors (ALT) and well-differentiated liposarcomas (WDLPS) and dedifferentiated liposarcomas (DDLPS) [32]. Less often, the same amplification can be found in other tumors such as intimal sarcomas [33]. The 12q amplicon can be different in length and composition from one tumor to another, but it invariably contains the MDM2 gene, which is an antagonist of TP53, and it promotes oncogenesis through suppression of the activity of the p53 protein [34], as well as through its direct binding to the chromatin to promote serine metabolism dependency [35]. DDLPS are tumors that contain two compartments: one is composed of adipocytic tumor cells and is similar to WDLPS, while the dedifferentiated compartment consists of undifferentiated high-grade tumor cells that may be confused with other high-grade non-lipogenic sarcomas such as undifferentiated pleomorphic sarcoma (UPS) or MPNST, or sometimes show heterologous differentiation with features of osteogenic or myogenic differentiation. Thus, MDM2 amplification is an essential diagnostic tool to diagnose liposarcomas and in practice it can be found with FISH [36]. Other techniques that can be used are comparative genomic hybridization (CGH) and whole exome sequencing. When using these techniques, it is common to find a large number of genomic rearrangements in DDLPS [37], highlighting the limits of classifying sarcomas into sarcomas with simple or complex genetics.

4. Sarcomas with “Complex Genetics”

Genomically complex sarcomas represent more than 50% of soft tissue sarcomas in adults. In contrast to sarcomas with simple genetics, they do not harbor specific and characteristic molecular alterations. Indeed, they show large numbers of genomic rearrangements, copy number variations and point mutations, sometimes dubbed “genomic chaos”. While some recurrent mutations can be found in tumor suppressor genes such as TP53, RB1, and ATRX [4], molecular biology techniques are less essential for the diagnosis of these sarcomas, which are still predominantly defined by pathology associated to immunohistochemistry. However, it can still be of help in difficult situations, for instance in differentiating a benign from a similar-looking malignant tumor. One example is the distinction to be made between benign leiomyomas and malignant leiomyosarcomas in smooth muscle tumors of the uterus. Microscopic features such as mitoses and tumor necrosis are classically used to distinguish between benign and malignant tumors, but they may sometimes be difficult to assess, leading to the diagnosis of uterine smooth muscle tumors of unknown malignant potential (STUMPs). Genomic analysis with CGH array or whole exome sequencing can be used in these cases to detect malignant tumors that show a genomic index (score of genomic rearrangement) of more than ten [38].

5. Molecular Biology for Sarcoma Treatment

Molecular biology has allowed a refined classification of sarcomas with the definition of novel molecular entities and the identification of driver alterations in recent years. Independently of this diagnostic interest, the identification of characteristic molecular alterations in many sarcomas has allowed the improvement of clinical management, by a combination of better prognostication and therapeutic targeting based on knowledge of the underlying molecular changes in sarcomas (Table 2). This can also inform the design of clinical trials so that homogeneous groups of patients with similar prognoses and response to treatment are studied in trials, as opposed to a current pathological selection criteria that tends to group together different molecular entities, as well as the search for relevant biomarkers of response to treatment.

5.1. Gene Fusions

As detailed previously, Ewing sarcoma is a paradigmatic example of fusion-driven sarcoma with gene fusions between the FET and the ETS family genes [64]. Until recently, some sarcomas were classified as “Ewing-like” because of similar clinical and pathological characteristics, but presenting without FET–ETS fusion genes. RNA-seq has since allowed identification of several other fusion genes that have enabled the accurate classification of these Ewing-like tumors into several entities with similar characteristics in terms of prognosis, thus informing clinical management [65,66]. For instance, BCOR-rearranged sarcomas [67] are characterized by overall favorable prognosis, and they are treated with classical multimodal treatment [68], while CIC-rearranged sarcomas [69] have a much poorer prognosis, and they exhibit an intrinsic resistance to classical chemotherapy and radiotherapy regimes [70]. Independently of routine practice, this refinement of molecular classification has also allowed the homogenization of patients enrolled in clinical trials.
In children, one of the most frequent sarcoma subtypes is rhabdomyosarcoma, which was classically divided into alveolar and embryonal subtypes based on histopathological characteristics. With molecular biology, the former was found to be characterized by the presence of the oncogenic fusion PAX3/PAX7-FOXO1, which was a better indication than pathology for worse prognosis than sarcomas without the fusion [71]. With recent techniques of next-generation sequencing, rhabdomyosarcomas were further divided into sarcomas with VGLL2 fusions [72] or SRF fusions [16] and overall favorable prognosis, TFCP2 fusions and intermediary prognosis [12], and MYOD1 mutations and worse prognosis [73]. This is an example of the clinical interest of identifying distinct molecular subgroups of differing prognoses as this may lead to altered clinical management and distinct inclusion into clinical trials.
Another example where molecular division can lead to different clinical management of previously similarly classified sarcomas are in endometrial stromal sarcoma (ESS). It has been shown that low-grade ESS is more often associated to JAZF1 fusions [74], while high-grade ESS is characterized by fusions of genes from the 14-3-3 family such as YWHAE [75]. Recently, the use of RNA-seq showed that ESS could be divided into three groups based on fusion genes with different prognoses, once again showing the interest of using molecular biology for clinical management and design of clinical trials with homogeneous entities [76].
While gene fusions in sarcomas often involve transcription factors which are not easily druggable, some fusions involve tyrosine kinase receptors which are molecular drivers of oncogenesis that can be directly targeted for molecularly-driven therapy. The most striking example is the case of NTRK-fused sarcomas [14,77], for which treatment by NTRK inhibitors such as larotrectinib showed efficacy with a 79% overall response rate, median overall survival of more than 3 years in NTRK-fused tumors comprising about half of sarcomas (infantile fibrosarcoma, which is associated with NTRK fusions in over 90% of cases, but also osteosarcoma, chondrosarcoma, GIST), with a remarkably low toxicity [39,40]. For patients with sarcomas, the response rates were 74% and 94% for adult and pediatric patients, respectively, with progression-free and overall survival not reached at more than one year of follow-up. Larotrectinib has been approved in North America and Europe for NTRK-fused advanced and metastatic solid cancers, while a more recent NTRK inhibitor, entrectinib, has also been approved by the FDA [41].
Inflammatory myofibroblastic tumors (IMT) are mesenchymal tumors of intermediary malignant potential characterized by fusions involving the ALK gene in more than 50% of cases inducing the upregulation of this tyrosine kinase receptor. Other fusions involving the ROS1 gene have been described in cases without ALK fusion [78]. Crizotinib, an ALK and ROS1 inhibitor, has shown a high response rate of 86% with a median response duration of more than 2.5 years in 14 patients with IMT [42]. This was further confirmed in a phase II trial with IMT patients of more than 15 years old, regardless of the presence of an ALK fusion, which showed response rates of 50% and 14% in patients harboring an ALK fusion or not, respectively [43]. Newer-generation ALK and ROS1 inhibitors including ceritinib (NCT02465528) and repotrectinib (NCT04094610) are currently evaluated in this indication.
Dermatofibrosarcoma protuberans (DFSP) is a cutaneous tumor of mesenchymal origin, and its intermediate malignant potential is characterized by recurrent fusion involving the genes COL1A1 and PDGFB, leading to uncontrolled synthesis of a constitutively active form of the PDGFB growth factor. Imatinib, a tyrosine kinase inhibitor against BCR-ABL, KIT but also PDGF receptors, has shown response rates near 67% in several studies of DFSP patients with many complete responses [44,45]. Additionally, imatinib has been used as neoadjuvant therapy with a response rate between 40% and 60%, with a reduction in the tumor burden of approximately 20% [46,47].
Pigmented villonodular synovitis (PVNS), also known as diffuse-type tenosynovial giant cell tumor (TGCT), is a mesenchymal tumor affecting the joints and juxtaarticular soft tissues, characterized by infiltration by inflammatory cells; more than 50% of them are characterized by a gene fusion between COL6A3 and CSF1 [79], leading to overproduction of the CSF1 protein, which attract inflammatory cells expressing CSF1R [80]. Emactuzumab is a monoclonal antibody directed against CSF1R, and it was shown in a phase I study to have a response rate of 86% in 24 patients, with 2 complete responses [48]. Another antibody, cabiralizumab, also showed efficacy in a phase I/II study with some partial responses [81]. Pexidartinib is a tyrosine kinase inhibitor that targets CSF1R: in a phase III trial with 120 patients, the response rate was 39% versus 0% in the placebo group, with significant clinical benefit in patients [49]. Pexidartinib has thus been approved as a reference therapy for inoperable PVNS/TGCT.
While transcription factors are notoriously more difficult to target therapeutically, all oncogenic fusions in sarcomas are attractive targets for drug development, since they are the driver event of these diseases, and they have been successfully targeted as outlined above. More effective therapies targeting them are thus expected for the future [82,83].

5.2. Mutations

While sarcomas with mutations are less frequent than fusion-driven sarcomas, they are natural candidates for classical targeted precision medicine, with the paradigmatic successful example being GISTs. As outlined above, these tumors are characterized by mutations in the genes KIT (85%) and PDGFRA (15%). As early as 2002, imatinib showed efficacy in locally advanced and metastatic GISTs [52]. Since then, continued improvements have been made in the development of new inhibitors and understanding of drug resistance in GISTs. In approximately twenty years, overall survival in this disease has been transformed from approximately 8 months to more than 10 years for a large proportion of patients. The latest generation of drugs include avapritinib, which specifically targets mutations of resistance to imatinib, such as D842V [84]. In these imatinib-resistant patients, a response rate of 88% has been shown [85], leading to its accelerated FDA approval in this indication [86]. Avapritinib has shown higher response rates than regorafenib (17.1% vs. 7.2%) in a recent phase III trial including KIT-mutated patients after third-line treatment, however, this trial failed to reach its primary endpoint as the median progression-free survival was not significantly changed between both arms [50]. Ripretinib is another inhibitor of KIT and PDGFRA that showed in a randomized phase III trial a response rate of 9.4% and progression-free survival of 6.3 months, versus 1 month in placebo, after treatment by imatinib, sunitinib, and regorafenib [51]. It has thus become the standard fourth-line therapy for GISTs. Though it failed to show superiority over sunitinib in second-line after treatment by imatinib in a recent phase III trial yet to be presented, it was associated with less adverse events than sunitinib [55].
PEComas are characterized by TSC1 and/or TSC2 loss-of-function mutations leading to uncontrolled activation of the mTOR pathway [87]. Sirolimus, an mTOR inhibitor, induced partial responses in some patients with PEComa [88,89], achieving a response rate of 73% with 5-year overall survival of 65% in a series of 15 patients [58]. A multicenter trial with 31 patients treated by nab-sirolimus showed a response rate of 39% including 2 complete responses and 67% of responses lasting more than 12 months with a median overall survival of 40.8 months [56], leading to the approval of nab-sirolimus by the FDA for unresectable or metastatic PEComas.
SMARCB1-deficient sarcomas are mainly malignant rhabdoid tumors, epithelioid sarcomas but also some rare tumors such as chordomas. Inactivating mutations in SMARCB1 lead to unregulated activity of the PRC2 histone methyltransferase complex and its EZH2 subunit. Tazemetostat is an oral selective EZH2 inhibitor that has been evaluated in pediatric SMARCB1-deficient sarcomas and adult epithelioid sarcomas. In the pediatric phase I trial, tazemetostat showed a response rate of 17% and median durations of response of more than 6 months in various histologies [59]. In a phase II trial of 62 adult patients with advanced epithelioid sarcoma, the response rate was 15% with median duration of response not reached after more than 1 year of follow-up; progression-free survival and overall survival were 5.5 and 19 months, respectively [60]. Based on these results, the FDA granted accelerated approval to tazemetostat for the treatment of advanced epithelioid sarcomas.
Some sarcomas harbor mutations in IDH1 or IDH2, rendering them sensitive to PARP inhibition due to defective homologous recombination repair. In a recent study of IDH1/2-mutant tumors, three out of five chondrosarcomas and one epithelioid hemangioendothelioma derived clinical benefit from olaparib monotherapy [63].

5.3. Gene Amplifications

The most frequent sarcoma with gene amplification is liposarcoma which harbors MDM2 amplification on the 12q amplicon. Numerous MDM2 inhibitors have been developed, and they have shown good activity in vitro and in xenografts [90,91]. However, phase I trials in humans showed response rates under 10% [61,62]. As the 12q amplicon also contains the CDK4 gene, inhibitors such as palbociclib and ribociclib were tested but without significant evidence of activity [92,93]. A potential practice-changing phase III trial (NCT05218499) has just begun with BI-907828, an MDM2 inhibitor, against doxorubicin in first-line treatment [94]. Combinations of MDM2 and CDK4 inhibitors showed preclinical activity in liposarcomas [95], and they are also being tested in patients, though one recent study showed only three partial responses in 74 patients [96].

6. Perspectives

Sarcoma is a rapidly changing field for molecular biology, with novel techniques constantly discovering molecular underpinnings that may be targetable. While refined diagnosis is key, prognosis can also benefit from molecular biology. An example is the CINSARC signature which is a transcriptomic signature of 67 genes that reflects genomic complexity of tumors [97]. For operated sarcomas with complex genomics, it does better at predicting relapse than histological grade. It was also shown to be useful in other cancers such as GISTs, but also lymphomas and some carcinomas [98]. Neoadjuvant chemotherapy given based on the CINSARC signature is currently being evaluated in two clinical trials for resectable soft tissue sarcomas (NCT03805022, NCT0430727).
Though immunotherapy is still to make real progress in sarcomas [99], the importance of the immune microenvironment and its characterization by molecular techniques has been shown in a recent study using transcriptomic data: using a bioinformatics tool called MCP-counter [100] to estimate the abundance of several microenvironment cell populations in a cohort of more than 600 sarcomas including leiomyosarcomas, liposarcomas and undifferentiated pleomorphic sarcomas, the authors showed that sarcomas could be classified in five subgroups according to immune microenvironment, one of them showing enhanced immune infiltration by T and B lymphocytes as well as NK cells, and the presence of tertiary lymphoid structures (TLS) had better survival [101]. This has led for instance to the design of a phase II trial evaluating immune checkpoint combined inhibition for tumors with TLS (NCT04095208). As more studies are done to evaluate immunotherapy in sarcomas, it is expected that molecular determinants of response and biomarkers will be of paramount importance to predict response to immunotherapy, including single-cell techniques that can guide precision immunotherapy.
As for molecularly targeted therapy, trials such as the MULTISARC randomized multicenter study (NCT03784014) are evaluating the value in advanced soft tissue sarcomas of using next-generation sequencing (whole exome sequencing and RNA sequencing) to propose molecularly guided therapy based on targetable genomic alterations after first-line treatment [102].
As for diagnosis, it has been shown above that RNA sequencing is an interesting technique especially for fusion-driven sarcomas, and it is being increasingly used for diagnostic purposes. Another molecular technique is the use of DNA methylation arrays for the profiling of genome-wide DNA methylation changes. Combined with machine learning algorithms, this technique originally showed its value in refining classification and helping the diagnosis of central nervous system tumors [103]. More recently, the same team showed that this tool could also accurately classify tumors into 62 methylation classes of a broad range of adult and pediatric sarcomas [104]. The end-product of DNA and RNA is protein, and proteomics is also one technique that has promising potential for characterizing sarcomas [105].
While these state-of-the-art molecular assays do enable refined diagnosis and improved scientific knowledge, they do not necessarily lead to treatment recommendations, they are costly, and they are not necessarily available in all centers. It is likely that these techniques will continue to be used only in dedicated reference centers, until diminishing costs, improved techniques, or stronger clinical impact can be achieved. For instance, RNA-seq is for now restricted to specialized centers, but it can be expected that as sequencing costs decrease and more centers have the means to perform RNA-seq, including on formalin-fixed, paraffin-embedded samples, this technique can be widely adopted and provide more data to demonstrate clinical practice-changing potential.
Finally, very recent technological breakthroughs have seen the advent of single-cell technologies, allowing the characterization of molecular features at the single-cell level and thus vastly increasing the capability to understand pathogenesis, tumor heterogeneity, interactions with the microenvironment, and resistance to treatment. Though the use of these costly single-cell technologies is still in its infancy for rare tumors such as sarcoma, they has been used to better characterize some tumors such as synovial sarcoma, Ewing sarcoma, and osteosarcoma [106,107,108]. It could be possible one day to use single-cell RNA-seq in routine to characterize tumor heterogeneity as prognostic or predictive biomarkers, as well as resistance mechanisms to therapy, especially immunotherapy [109,110].

7. Conclusions

Molecular biology has a prominent role in the diagnostic and therapeutic management of numerous soft tissue sarcoma subtypes. New techniques and future research hold great promise to tackle tumor heterogeneity and treatment resistance through individualized precision medicine strategies.

Author Contributions

J.V. and S.W. wrote the full manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by GEFLUC Les Entreprises Contre le Cancer.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kallen, M.E.; Hornick, J.L. The 2020 WHO Classification: What’s New in Soft Tissue Tumor Pathology? Am. J. Surg. Pathol. 2021, 45, e1–e23. [Google Scholar] [CrossRef] [PubMed]
  2. Dufresne, A.; Brahmi, M.; Karanian, M.; Blay, J.-Y. Using Biology to Guide the Treatment of Sarcomas and Aggressive Connective-Tissue Tumours. Nat. Rev. Clin. Oncol. 2018, 15, 443–458. [Google Scholar] [CrossRef] [PubMed]
  3. Taylor, B.S.; Barretina, J.; Maki, R.G.; Antonescu, C.R.; Singer, S.; Ladanyi, M. Advances in Sarcoma Genomics and New Therapeutic Targets. Nat. Rev. Cancer 2011, 11, 541–557. [Google Scholar] [CrossRef] [Green Version]
  4. Abeshouse, A.; Adebamowo, C.; Adebamowo, S.N.; Akbani, R.; Akeredolu, T.; Ally, A.; Anderson, M.L.; Anur, P.; Appelbaum, E.L.; Armenia, J.; et al. Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas. Cell 2017, 171, 950–965.e28. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Mertens, F.; Antonescu, C.R.; Hohenberger, P.; Ladanyi, M.; Modena, P.; D’Incalci, M.; Casali, P.G.; Aglietta, M.; Alvegård, T. Translocation-Related Sarcomas. Semin. Oncol. 2009, 36, 312–323. [Google Scholar] [CrossRef] [PubMed]
  6. Riggi, N.; Suvà, M.L.; Stamenkovic, I. Ewing’s Sarcoma. N. Engl. J. Med. 2021, 384, 154–164. [Google Scholar] [CrossRef]
  7. Delattre, O.; Zucman, J.; Plougastel, B.; Desmaze, C.; Melot, T.; Peter, M.; Kovar, H.; Joubert, I.; de Jong, P.; Rouleau, G.; et al. Gene Fusion with an ETS DNA-Binding Domain Caused by Chromosome Translocation in Human Tumours. Nature 1992, 359, 162–165. [Google Scholar] [CrossRef]
  8. Schaefer, I.-M.; Cote, G.M.; Hornick, J.L. Contemporary Sarcoma Diagnosis, Genetics, and Genomics. J. Clin. Oncol. 2018, 36, 101–110. [Google Scholar] [CrossRef]
  9. Watson, S.; Perrin, V.; Guillemot, D.; Reynaud, S.; Coindre, J.-M.; Karanian, M.; Guinebretière, J.-M.; Freneaux, P.; Loarer, F.L.; Bouvet, M.; et al. Transcriptomic Definition of Molecular Subgroups of Small Round Cell Sarcomas. J. Pathol. 2018, 245, 29–40. [Google Scholar] [CrossRef] [Green Version]
  10. Macagno, N.; Pissaloux, D.; de la Fouchardière, A.; Karanian, M.; Lantuejoul, S.; Galateau Salle, F.; Meurgey, A.; Chassagne-Clement, C.; Treilleux, I.; Renard, C.; et al. Wholistic Approach: Transcriptomic Analysis and beyond Using Archival Material for Molecular Diagnosis. Genes Chromosomes Cancer 2022, 61, 382–393. [Google Scholar] [CrossRef]
  11. Le Loarer, F.; Pissaloux, D.; Watson, S.; Godfraind, C.; Galmiche-Rolland, L.; Silva, K.; Mayeur, L.; Italiano, A.; Michot, A.; Pierron, G.; et al. Clinicopathologic Features of CIC-NUTM1 Sarcomas, a New Molecular Variant of the Family of CIC-Fused Sarcomas. Am. J. Surg. Pathol. 2019, 43, 268–276. [Google Scholar] [CrossRef] [PubMed]
  12. Le Loarer, F.; Cleven, A.H.G.; Bouvier, C.; Castex, M.-P.; Romagosa, C.; Moreau, A.; Salas, S.; Bonhomme, B.; Gomez-Brouchet, A.; Laurent, C.; et al. A Subset of Epithelioid and Spindle Cell Rhabdomyosarcomas Is Associated with TFCP2 Fusions and Common ALK Upregulation. Mod. Pathol. 2020, 33, 404–419. [Google Scholar] [CrossRef] [PubMed]
  13. Antonescu, C.R.; Rosenberg, A.E.; Xie, Z.; Zhang, L.; Perell, K.A.; Loya, A.C. Sarcomas with Sclerotic Epithelioid Phenotype Harboring Novel EWSR1-SSX1 Fusions. Genes Chromosomes Cancer 2021, 60, 616–622. [Google Scholar] [CrossRef] [PubMed]
  14. Demetri, G.D.; Antonescu, C.R.; Bjerkehagen, B.; Bovée, J.V.M.G.; Boye, K.; Chacón, M.; Dei Tos, A.P.; Desai, J.; Fletcher, J.A.; Gelderblom, H.; et al. Diagnosis and Management of Tropomyosin Receptor Kinase (TRK) Fusion Sarcomas: Expert Recommendations from the World Sarcoma Network. Ann. Oncol. 2020, 31, 1506–1517. [Google Scholar] [CrossRef]
  15. Dermawan, J.K.; Zou, Y.; Antonescu, C.R. Neuregulin 1 (NRG1) Fusion-Positive High-Grade Spindle Cell Sarcoma: A Distinct Group of Soft Tissue Tumors with Metastatic Potential. Genes Chromosomes Cancer 2022, 61, 123–130. [Google Scholar] [CrossRef]
  16. Karanian, M.; Pissaloux, D.; Gomez-Brouchet, A.; Chevenet, C.; Le Loarer, F.; Fernandez, C.; Minard, V.; Corradini, N.; Castex, M.-P.; Duc-Gallet, A.; et al. SRF-FOXO1 and SRF-NCOA1 Fusion Genes Delineate a Distinctive Subset of Well-Differentiated Rhabdomyosarcoma. Am. J. Surg. Pathol. 2020, 44, 607–616. [Google Scholar] [CrossRef]
  17. El Zein, S.; Djeroudi, L.; Reynaud, S.; Guillemot, D.; Masliah-Planchon, J.; Frouin, E.; Nicolas, N.; Le Loarer, F.; Daniel, C.; Delattre, O.; et al. Novel EWSR1::UBP1 Fusion Expands the Spectrum of Spindle Cell Rhabdomyosarcomas. Genes Chromosomes Cancer 2022, 61, 200–205. [Google Scholar] [CrossRef]
  18. Hirota, S.; Isozaki, K.; Moriyama, Y.; Hashimoto, K.; Nishida, T.; Ishiguro, S.; Kawano, K.; Hanada, M.; Kurata, A.; Takeda, M.; et al. Gain-of-Function Mutations of c-Kit in Human Gastrointestinal Stromal Tumors. Science 1998, 279, 577–580. [Google Scholar] [CrossRef]
  19. Joensuu, H.; Hohenberger, P.; Corless, C.L. Gastrointestinal Stromal Tumour. Lancet 2013, 382, 973–983. [Google Scholar] [CrossRef]
  20. von Mehren, M.; Joensuu, H. Gastrointestinal Stromal Tumors. J. Clin. Oncol. 2018, 36, 136–143. [Google Scholar] [CrossRef]
  21. Heinrich, M.C.; Corless, C.L.; Duensing, A.; McGreevey, L.; Chen, C.-J.; Joseph, N.; Singer, S.; Griffith, D.J.; Haley, A.; Town, A.; et al. PDGFRA Activating Mutations in Gastrointestinal Stromal Tumors. Science 2003, 299, 708–710. [Google Scholar] [CrossRef] [PubMed]
  22. Kawaguchi, K.; Oda, Y.; Saito, T.; Takahira, T.; Yamamoto, H.; Tamiya, S.; Iwamoto, Y.; Tsuneyoshi, M. Genetic and Epigenetic Alterations of the PTEN Gene in Soft Tissue Sarcomas. Hum. Pathol. 2005, 36, 357–363. [Google Scholar] [CrossRef] [PubMed]
  23. Movva, S.; Wen, W.; Chen, W.; Millis, S.Z.; Gatalica, Z.; Reddy, S.; von Mehren, M.; Van Tine, B.A. Multi-Platform Profiling of over 2000 Sarcomas: Identification of Biomarkers and Novel Therapeutic Targets. Oncotarget 2015, 6, 12234–12247. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Farid, M.; Demicco, E.G.; Garcia, R.; Ahn, L.; Merola, P.R.; Cioffi, A.; Maki, R.G. Malignant Peripheral Nerve Sheath Tumors. Oncologist 2014, 19, 193–201. [Google Scholar] [CrossRef] [Green Version]
  25. Pan, C.-C.; Chung, M.-Y.; Ng, K.-F.; Liu, C.-Y.; Wang, J.-S.; Chai, C.-Y.; Huang, S.-H.; Chen, P.C.-H.; Ho, D.M.T. Constant Allelic Alteration on Chromosome 16p (TSC2 Gene) in Perivascular Epithelioid Cell Tumour (PEComa): Genetic Evidence for the Relationship of PEComa with Angiomyolipoma. J. Pathol. 2008, 214, 387–393. [Google Scholar] [CrossRef]
  26. Giannikou, K.; Malinowska, I.A.; Pugh, T.J.; Yan, R.; Tseng, Y.-Y.; Oh, C.; Kim, J.; Tyburczy, M.E.; Chekaluk, Y.; Liu, Y.; et al. Whole Exome Sequencing Identifies TSC1/TSC2 Biallelic Loss as the Primary and Sufficient Driver Event for Renal Angiomyolipoma Development. PLoS Genet. 2016, 12, e1006242. [Google Scholar] [CrossRef] [Green Version]
  27. Hornick, J.L.; Dal Cin, P.; Fletcher, C.D.M. Loss of INI1 Expression Is Characteristic of Both Conventional and Proximal-Type Epithelioid Sarcoma. Am. J. Surg. Pathol. 2009, 33, 542–550. [Google Scholar] [CrossRef]
  28. Margol, A.S.; Judkins, A.R. Pathology and Diagnosis of SMARCB1-Deficient Tumors. Cancer Genet. 2014, 207, 358–364. [Google Scholar] [CrossRef]
  29. Le Loarer, F.; Watson, S.; Pierron, G.; de Montpreville, V.T.; Ballet, S.; Firmin, N.; Auguste, A.; Pissaloux, D.; Boyault, S.; Paindavoine, S.; et al. SMARCA4 Inactivation Defines a Group of Undifferentiated Thoracic Malignancies Transcriptionally Related to BAF-Deficient Sarcomas. Nat. Genet. 2015, 47, 1200–1205. [Google Scholar] [CrossRef]
  30. Jelinic, P.; Mueller, J.J.; Olvera, N.; Dao, F.; Scott, S.N.; Shah, R.; Gao, J.; Schultz, N.; Gonen, M.; Soslow, R.A.; et al. Recurrent SMARCA4 Mutations in Small Cell Carcinoma of the Ovary. Nat. Genet. 2014, 46, 424–426. [Google Scholar] [CrossRef]
  31. Holdhof, D.; Johann, P.D.; Spohn, M.; Bockmayr, M.; Safaei, S.; Joshi, P.; Masliah-Planchon, J.; Ho, B.; Andrianteranagna, M.; Bourdeaut, F.; et al. Atypical Teratoid/Rhabdoid Tumors (ATRTs) with SMARCA4 Mutation Are Molecularly Distinct from SMARCB1-Deficient Cases. Acta Neuropathol. 2021, 141, 291–301. [Google Scholar] [CrossRef] [PubMed]
  32. Coindre, J.-M.; Pédeutour, F.; Aurias, A. Well-Differentiated and Dedifferentiated Liposarcomas. Virchows Arch. 2010, 456, 167–179. [Google Scholar] [CrossRef] [PubMed]
  33. Neuville, A.; Collin, F.; Bruneval, P.; Parrens, M.; Thivolet, F.; Gomez-Brouchet, A.; Terrier, P.; de Montpreville, V.T.; Le Gall, F.; Hostein, I.; et al. Intimal Sarcoma Is the Most Frequent Primary Cardiac Sarcoma: Clinicopathologic and Molecular Retrospective Analysis of 100 Primary Cardiac Sarcomas. Am. J. Surg. Pathol. 2014, 38, 461–469. [Google Scholar] [CrossRef] [PubMed]
  34. Momand, J.; Zambetti, G.P.; Olson, D.C.; George, D.; Levine, A.J. The Mdm-2 Oncogene Product Forms a Complex with the P53 Protein and Inhibits P53-Mediated Transactivation. Cell 1992, 69, 1237–1245. [Google Scholar] [CrossRef]
  35. Cissé, M.Y.; Pyrdziak, S.; Firmin, N.; Gayte, L.; Heuillet, M.; Bellvert, F.; Fuentes, M.; Delpech, H.; Riscal, R.; Arena, G.; et al. Targeting MDM2-Dependent Serine Metabolism as a Therapeutic Strategy for Liposarcoma. Sci. Transl. Med. 2020, 12, eaay2163. [Google Scholar] [CrossRef]
  36. Weaver, J.; Downs-Kelly, E.; Goldblum, J.R.; Turner, S.; Kulkarni, S.; Tubbs, R.R.; Rubin, B.P.; Skacel, M. Fluorescence in Situ Hybridization for MDM2 Gene Amplification as a Diagnostic Tool in Lipomatous Neoplasms. Mod. Pathol. 2008, 21, 943–949. [Google Scholar] [CrossRef] [Green Version]
  37. Hirata, M.; Asano, N.; Katayama, K.; Yoshida, A.; Tsuda, Y.; Sekimizu, M.; Mitani, S.; Kobayashi, E.; Komiyama, M.; Fujimoto, H.; et al. Integrated Exome and RNA Sequencing of Dedifferentiated Liposarcoma. Nat. Commun. 2019, 10, 5683. [Google Scholar] [CrossRef] [Green Version]
  38. Croce, S.; Ribeiro, A.; Brulard, C.; Noel, J.-C.; Amant, F.; Stoeckle, E.; Devouassoux-Shisheborah, M.; Floquet, A.; Arnould, L.; Guyon, F.; et al. Uterine Smooth Muscle Tumor Analysis by Comparative Genomic Hybridization: A Useful Diagnostic Tool in Challenging Lesions. Mod. Pathol. 2015, 28, 1001–1010. [Google Scholar] [CrossRef] [Green Version]
  39. Drilon, A.; Laetsch, T.W.; Kummar, S.; DuBois, S.G.; Lassen, U.N.; Demetri, G.D.; Nathenson, M.; Doebele, R.C.; Farago, A.F.; Pappo, A.S.; et al. Efficacy of Larotrectinib in TRK Fusion-Positive Cancers in Adults and Children. N. Engl. J. Med. 2018, 378, 731–739. [Google Scholar] [CrossRef]
  40. Hong, D.S.; DuBois, S.G.; Kummar, S.; Farago, A.F.; Albert, C.M.; Rohrberg, K.S.; van Tilburg, C.M.; Nagasubramanian, R.; Berlin, J.D.; Federman, N.; et al. Larotrectinib in Patients with TRK Fusion-Positive Solid Tumours: A Pooled Analysis of Three Phase 1/2 Clinical Trials. Lancet Oncol. 2020, 21, 531–540. [Google Scholar] [CrossRef]
  41. Marcus, L.; Donoghue, M.; Aungst, S.; Myers, C.E.; Helms, W.S.; Shen, G.; Zhao, H.; Stephens, O.; Keegan, P.; Pazdur, R. FDA Approval Summary: Entrectinib for the Treatment of NTRK Gene Fusion Solid Tumors. Clin. Cancer Res. 2021, 27, 928–932. [Google Scholar] [CrossRef] [PubMed]
  42. Mossé, Y.P.; Voss, S.D.; Lim, M.S.; Rolland, D.; Minard, C.G.; Fox, E.; Adamson, P.; Wilner, K.; Blaney, S.M.; Weigel, B.J. Targeting ALK With Crizotinib in Pediatric Anaplastic Large Cell Lymphoma and Inflammatory Myofibroblastic Tumor: A Children’s Oncology Group Study. J. Clin. Oncol. 2017, 35, 3215–3221. [Google Scholar] [CrossRef] [PubMed]
  43. Schöffski, P.; Sufliarsky, J.; Gelderblom, H.; Blay, J.-Y.; Strauss, S.J.; Stacchiotti, S.; Rutkowski, P.; Lindner, L.H.; Leahy, M.G.; Italiano, A.; et al. Crizotinib in Patients with Advanced, Inoperable Inflammatory Myofibroblastic Tumours with and without Anaplastic Lymphoma Kinase Gene Alterations (European Organisation for Research and Treatment of Cancer 90101 CREATE): A Multicentre, Single-Drug, Prospective, Non-Randomised Phase 2 Trial. Lancet Respir. Med. 2018, 6, 431–441. [Google Scholar] [CrossRef] [PubMed]
  44. McArthur, G.A.; Demetri, G.D.; van Oosterom, A.; Heinrich, M.C.; Debiec-Rychter, M.; Corless, C.L.; Nikolova, Z.; Dimitrijevic, S.; Fletcher, J.A. Molecular and Clinical Analysis of Locally Advanced Dermatofibrosarcoma Protuberans Treated with Imatinib: Imatinib Target Exploration Consortium Study B2225. J. Clin. Oncol. 2005, 23, 866–873. [Google Scholar] [CrossRef]
  45. Navarrete-Dechent, C.; Mori, S.; Barker, C.A.; Dickson, M.A.; Nehal, K.S. Imatinib Treatment for Locally Advanced or Metastatic Dermatofibrosarcoma Protuberans: A Systematic Review. JAMA Derm. 2019, 155, 361–369. [Google Scholar] [CrossRef]
  46. Kérob, D.; Porcher, R.; Vérola, O.; Dalle, S.; Maubec, E.; Aubin, F.; D’Incan, M.; Bodokh, I.; Boulinguez, S.; Madelaine-Chambrin, I.; et al. Imatinib Mesylate as a Preoperative Therapy in Dermatofibrosarcoma: Results of a Multicenter Phase II Study on 25 Patients. Clin. Cancer Res. 2010, 16, 3288–3295. [Google Scholar] [CrossRef] [Green Version]
  47. Ugurel, S.; Mentzel, T.; Utikal, J.; Helmbold, P.; Mohr, P.; Pföhler, C.; Schiller, M.; Hauschild, A.; Hein, R.; Kämpgen, E.; et al. Neoadjuvant Imatinib in Advanced Primary or Locally Recurrent Dermatofibrosarcoma Protuberans: A Multicenter Phase II DeCOG Trial with Long-Term Follow-Up. Clin. Cancer Res. 2014, 20, 499–510. [Google Scholar] [CrossRef] [Green Version]
  48. Cassier, P.A.; Italiano, A.; Gomez-Roca, C.A.; Le Tourneau, C.; Toulmonde, M.; Cannarile, M.A.; Ries, C.; Brillouet, A.; Müller, C.; Jegg, A.-M.; et al. CSF1R Inhibition with Emactuzumab in Locally Advanced Diffuse-Type Tenosynovial Giant Cell Tumours of the Soft Tissue: A Dose-Escalation and Dose-Expansion Phase 1 Study. Lancet Oncol. 2015, 16, 949–956. [Google Scholar] [CrossRef]
  49. Tap, W.D.; Gelderblom, H.; Palmerini, E.; Desai, J.; Bauer, S.; Blay, J.-Y.; Alcindor, T.; Ganjoo, K.; Martín-Broto, J.; Ryan, C.W.; et al. Pexidartinib versus Placebo for Advanced Tenosynovial Giant Cell Tumour (ENLIVEN): A Randomised Phase 3 Trial. Lancet 2019, 394, 478–487. [Google Scholar] [CrossRef]
  50. Kang, Y.-K.; George, S.; Jones, R.L.; Rutkowski, P.; Shen, L.; Mir, O.; Patel, S.; Zhou, Y.; von Mehren, M.; Hohenberger, P.; et al. Avapritinib Versus Regorafenib in Locally Advanced Unresectable or Metastatic GI Stromal Tumor: A Randomized, Open-Label Phase III Study. J. Clin. Oncol. 2021, 39, 3128–3139. [Google Scholar] [CrossRef]
  51. Blay, J.-Y.; Serrano, C.; Heinrich, M.C.; Zalcberg, J.; Bauer, S.; Gelderblom, H.; Schöffski, P.; Jones, R.L.; Attia, S.; D’Amato, G.; et al. Ripretinib in Patients with Advanced Gastrointestinal Stromal Tumours (INVICTUS): A Double-Blind, Randomised, Placebo-Controlled, Phase 3 Trial. Lancet Oncol. 2020, 21, 923–934. [Google Scholar] [CrossRef]
  52. Demetri, G.D.; von Mehren, M.; Blanke, C.D.; Van den Abbeele, A.D.; Eisenberg, B.; Roberts, P.J.; Heinrich, M.C.; Tuveson, D.A.; Singer, S.; Janicek, M.; et al. Efficacy and Safety of Imatinib Mesylate in Advanced Gastrointestinal Stromal Tumors. N. Engl. J. Med. 2002, 347, 472–480. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Demetri, G.D.; van Oosterom, A.T.; Garrett, C.R.; Blackstein, M.E.; Shah, M.H.; Verweij, J.; McArthur, G.; Judson, I.R.; Heinrich, M.C.; Morgan, J.A.; et al. Efficacy and Safety of Sunitinib in Patients with Advanced Gastrointestinal Stromal Tumour after Failure of Imatinib: A Randomised Controlled Trial. Lancet 2006, 368, 1329–1338. [Google Scholar] [CrossRef]
  54. Demetri, G.D.; Reichardt, P.; Kang, Y.-K.; Blay, J.-Y.; Rutkowski, P.; Gelderblom, H.; Hohenberger, P.; Leahy, M.; von Mehren, M.; Joensuu, H.; et al. Efficacy and Safety of Regorafenib for Advanced Gastrointestinal Stromal Tumours after Failure of Imatinib and Sunitinib: An International, Multicentre, Prospective, Randomised, Placebo-Controlled Phase 3 Trial (GRID). Lancet 2013, 381, 295–302. [Google Scholar] [CrossRef] [Green Version]
  55. Heinrich, M.C.; Jones, R.L.; Gelderblom, H.; George, S.; Schöffski, P.; von Mehren, M.; Zalcberg, J.R.; Kang, Y.-K.; Abdul Razak, A.R.; Trent, J.C.; et al. INTRIGUE: A Phase III, Randomized, Open-Label Study to Evaluate the Efficacy and Safety of Ripretinib versus Sunitinib in Patients with Advanced Gastrointestinal Stromal Tumor Previously Treated with Imatinib. J. Clin. Oncol. 2022, 40, 359881. [Google Scholar] [CrossRef]
  56. Wagner, A.J.; Ravi, V.; Riedel, R.F.; Ganjoo, K.; Van Tine, B.A.; Chugh, R.; Cranmer, L.; Gordon, E.M.; Hornick, J.L.; Du, H.; et al. Nab-Sirolimus for Patients With Malignant Perivascular Epithelioid Cell Tumors. J. Clin. Oncol. 2021, 39, 3660–3670. [Google Scholar] [CrossRef]
  57. Sanfilippo, R.; Jones, R.L.; Blay, J.-Y.; Le Cesne, A.; Provenzano, S.; Antoniou, G.; Mir, O.; Fucà, G.; Fumagalli, E.; Bertulli, R.; et al. Role of Chemotherapy, VEGFR Inhibitors, and MTOR Inhibitors in Advanced Perivascular Epithelioid Cell Tumors (PEComas). Clin. Cancer Res. 2019, 25, 5295–5300. [Google Scholar] [CrossRef]
  58. Świtaj, T.; Sobiborowicz, A.; Teterycz, P.; Klimczak, A.; Makuła, D.; Wągrodzki, M.; Szumera-Ciećkiewicz, A.; Rutkowski, P.; Czarnecka, A.M. Efficacy of Sirolimus Treatment in PEComa-10 Years of Practice Perspective. J. Clin. Med. 2021, 10, 3705. [Google Scholar] [CrossRef]
  59. Chi, S.N.; Bourdeaut, F.; Laetsch, T.W.; Fouladi, M.; Macy, M.E.; Makin, G.W.; Shukla, N.N.; Wetmore, C.; Margol, A.S.; Casanova, M.; et al. Phase I Study of Tazemetostat, an Enhancer of Zeste Homolog-2 Inhibitor, in Pediatric Pts with Relapsed/Refractory Integrase Interactor 1-Negative Tumors. J. Clin. Oncol. 2020, 38, 10525. [Google Scholar] [CrossRef]
  60. Gounder, M.; Schöffski, P.; Jones, R.L.; Agulnik, M.; Cote, G.M.; Villalobos, V.M.; Attia, S.; Chugh, R.; Chen, T.W.-W.; Jahan, T.; et al. Tazemetostat in Advanced Epithelioid Sarcoma with Loss of INI1/SMARCB1: An International, Open-Label, Phase 2 Basket Study. Lancet Oncol. 2020, 21, 1423–1432. [Google Scholar] [CrossRef]
  61. de Jonge, M.; de Weger, V.A.; Dickson, M.A.; Langenberg, M.; Le Cesne, A.; Wagner, A.J.; Hsu, K.; Zheng, W.; Macé, S.; Tuffal, G.; et al. A Phase I Study of SAR405838, a Novel Human Double Minute 2 (HDM2) Antagonist, in Patients with Solid Tumours. Eur. J. Cancer 2017, 76, 144–151. [Google Scholar] [CrossRef] [PubMed]
  62. Wagner, A.J.; Banerji, U.; Mahipal, A.; Somaiah, N.; Hirsch, H.; Fancourt, C.; Johnson-Levonas, A.O.; Lam, R.; Meister, A.K.; Russo, G.; et al. Phase I Trial of the Human Double Minute 2 Inhibitor MK-8242 in Patients With Advanced Solid Tumors. J. Clin. Oncol. 2017, 35, 1304–1311. [Google Scholar] [CrossRef] [PubMed]
  63. Eder, J.P.; Doroshow, D.B.; Do, K.T.; Keedy, V.L.; Sklar, J.S.; Glazer, P.; Bindra, R.; Shapiro, G.I. Clinical Efficacy of Olaparib in IDH1/IDH2-Mutant Mesenchymal Sarcomas. JCO Precis. Oncol. 2021, 5, 466–472. [Google Scholar] [CrossRef] [PubMed]
  64. Grünewald, T.G.P.; Cidre-Aranaz, F.; Surdez, D.; Tomazou, E.M.; de Álava, E.; Kovar, H.; Sorensen, P.H.; Delattre, O.; Dirksen, U. Ewing Sarcoma. Nat. Rev. Dis. Primers 2018, 4, 5. [Google Scholar] [CrossRef] [PubMed]
  65. Renzi, S.; Anderson, N.D.; Light, N.; Gupta, A. Ewing-like Sarcoma: An Emerging Family of Round Cell Sarcomas. J. Cell. Physiol. 2019, 234, 7999–8007. [Google Scholar] [CrossRef] [PubMed]
  66. Sbaraglia, M.; Righi, A.; Gambarotti, M.; Dei Tos, A.P. Ewing Sarcoma and Ewing-like Tumors. Virchows Arch. 2020, 476, 109–119. [Google Scholar] [CrossRef] [PubMed]
  67. Pierron, G.; Tirode, F.; Lucchesi, C.; Reynaud, S.; Ballet, S.; Cohen-Gogo, S.; Perrin, V.; Coindre, J.-M.; Delattre, O. A New Subtype of Bone Sarcoma Defined by BCOR-CCNB3 Gene Fusion. Nat. Genet. 2012, 44, 461–466. [Google Scholar] [CrossRef] [Green Version]
  68. Kao, Y.-C.; Owosho, A.A.; Sung, Y.-S.; Zhang, L.; Fujisawa, Y.; Lee, J.-C.; Wexler, L.; Argani, P.; Swanson, D.; Dickson, B.C.; et al. BCOR-CCNB3 Fusion Positive Sarcomas: A Clinicopathologic and Molecular Analysis of 36 Cases With Comparison to Morphologic Spectrum and Clinical Behavior of Other Round Cell Sarcomas. Am. J. Surg. Pathol. 2018, 42, 604–615. [Google Scholar] [CrossRef]
  69. Yoshimoto, M.; Graham, C.; Chilton-MacNeill, S.; Lee, E.; Shago, M.; Squire, J.; Zielenska, M.; Somers, G.R. Detailed Cytogenetic and Array Analysis of Pediatric Primitive Sarcomas Reveals a Recurrent CIC-DUX4 Fusion Gene Event. Cancer Genet. Cytogenet. 2009, 195, 1–11. [Google Scholar] [CrossRef]
  70. Antonescu, C.R.; Owosho, A.A.; Zhang, L.; Chen, S.; Deniz, K.; Huryn, J.M.; Kao, Y.-C.; Huang, S.-C.; Singer, S.; Tap, W.; et al. Sarcomas with CIC-Rearrangements Are a Distinct Pathologic Entity with Aggressive Outcome: A Clinicopathologic and Molecular Study of 115 Cases. Am. J. Surg. Pathol. 2017, 41, 941–949. [Google Scholar] [CrossRef]
  71. Missiaglia, E.; Williamson, D.; Chisholm, J.; Wirapati, P.; Pierron, G.; Petel, F.; Concordet, J.-P.; Thway, K.; Oberlin, O.; Pritchard-Jones, K.; et al. PAX3/FOXO1 Fusion Gene Status Is the Key Prognostic Molecular Marker in Rhabdomyosarcoma and Significantly Improves Current Risk Stratification. J. Clin. Oncol. 2012, 30, 1670–1677. [Google Scholar] [CrossRef] [PubMed]
  72. Butel, T.; Karanian, M.; Pierron, G.; Orbach, D.; Ranchere, D.; Cozic, N.; Galmiche, L.; Coulomb, A.; Corradini, N.; Lacour, B.; et al. Integrative Clinical and Biopathology Analyses to Understand the Clinical Heterogeneity of Infantile Rhabdomyosarcoma: A Report from the French MMT Committee. Cancer Med. 2020, 9, 2698–2709. [Google Scholar] [CrossRef] [PubMed]
  73. Agaram, N.P.; LaQuaglia, M.P.; Alaggio, R.; Zhang, L.; Fujisawa, Y.; Ladanyi, M.; Wexler, L.H.; Antonescu, C.R. MYOD1-Mutant Spindle Cell and Sclerosing Rhabdomyosarcoma: An Aggressive Subtype Irrespective of Age. A Reappraisal for Molecular Classification and Risk Stratification. Mod. Pathol. 2019, 32, 27–36. [Google Scholar] [CrossRef] [PubMed]
  74. Koontz, J.I.; Soreng, A.L.; Nucci, M.; Kuo, F.C.; Pauwels, P.; van Den Berghe, H.; Dal Cin, P.; Fletcher, J.A.; Sklar, J. Frequent Fusion of the JAZF1 and JJAZ1 Genes in Endometrial Stromal Tumors. Proc. Natl. Acad. Sci. USA 2001, 98, 6348–6353. [Google Scholar] [CrossRef] [Green Version]
  75. Lee, C.-H.; Ou, W.-B.; Mariño-Enriquez, A.; Zhu, M.; Mayeda, M.; Wang, Y.; Guo, X.; Brunner, A.L.; Amant, F.; French, C.A.; et al. 14-3-3 Fusion Oncogenes in High-Grade Endometrial Stromal Sarcoma. Proc. Natl. Acad. Sci. USA 2012, 109, 929–934. [Google Scholar] [CrossRef] [Green Version]
  76. Brahmi, M.; Franceschi, T.; Treilleux, I.; Pissaloux, D.; Ray-Coquard, I.; Dufresne, A.; Vanacker, H.; Carbonnaux, M.; Meeus, P.; Sunyach, M.-P.; et al. Molecular Classification of Endometrial Stromal Sarcomas Using RNA Sequencing Defines Nosological and Prognostic Subgroups with Different Natural History. Cancers 2020, 12, 2604. [Google Scholar] [CrossRef]
  77. Cocco, E.; Scaltriti, M.; Drilon, A. NTRK Fusion-Positive Cancers and TRK Inhibitor Therapy. Nat. Rev. Clin. Oncol. 2018, 15, 731–747. [Google Scholar] [CrossRef]
  78. Lovly, C.M.; Gupta, A.; Lipson, D.; Otto, G.; Brennan, T.; Chung, C.T.; Borinstein, S.C.; Ross, J.S.; Stephens, P.J.; Miller, V.A.; et al. Inflammatory Myofibroblastic Tumors Harbor Multiple Potentially Actionable Kinase Fusions. Cancer Discov. 2014, 4, 889–895. [Google Scholar] [CrossRef] [Green Version]
  79. Cupp, J.S.; Miller, M.A.; Montgomery, K.D.; Nielsen, T.O.; O’Connell, J.X.; Huntsman, D.; van de Rijn, M.; Gilks, C.B.; West, R.B. Translocation and Expression of CSF1 in Pigmented Villonodular Synovitis, Tenosynovial Giant Cell Tumor, Rheumatoid Arthritis and Other Reactive Synovitides. Am. J. Surg. Pathol. 2007, 31, 970–976. [Google Scholar] [CrossRef]
  80. West, R.B.; Rubin, B.P.; Miller, M.A.; Subramanian, S.; Kaygusuz, G.; Montgomery, K.; Zhu, S.; Marinelli, R.J.; De Luca, A.; Downs-Kelly, E.; et al. A Landscape Effect in Tenosynovial Giant-Cell Tumor from Activation of CSF1 Expression by a Translocation in a Minority of Tumor Cells. Proc. Natl. Acad. Sci. USA 2006, 103, 690–695. [Google Scholar] [CrossRef] [Green Version]
  81. Sankhala, K.K.; Blay, J.-Y.; Ganjoo, K.N.; Italiano, A.; Hassan, A.B.; Kim, T.M.; Ravi, V.; Cassier, P.A.; Rutkowski, P.; Sankar, N.; et al. A Phase I/II Dose Escalation and Expansion Study of Cabiralizumab (Cabira; FPA-008), an Anti-CSF1R Antibody, in Tenosynovial Giant Cell Tumor (TGCT, Diffuse Pigmented Villonodular Synovitis D-PVNS). J. Clin. Oncol. 2017, 35, 11078. [Google Scholar] [CrossRef]
  82. Perry, J.A.; Seong, B.K.A.; Stegmaier, K. Biology and Therapy of Dominant Fusion Oncoproteins Involving Transcription Factor and Chromatin Regulators in Sarcomas. Annu. Rev. Cancer Biol. 2019, 3, 299–321. [Google Scholar] [CrossRef]
  83. Knott, M.M.L.; Hölting, T.L.B.; Ohmura, S.; Kirchner, T.; Cidre-Aranaz, F.; Grünewald, T.G.P. Targeting the Undruggable: Exploiting Neomorphic Features of Fusion Oncoproteins in Childhood Sarcomas for Innovative Therapies. Cancer Metastasis Rev. 2019, 38, 625–642. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Farag, S.; Smith, M.J.; Fotiadis, N.; Constantinidou, A.; Jones, R.L. Revolutions in Treatment Options in Gastrointestinal Stromal Tumours (GISTs): The Latest Updates. Curr. Treat. Options Oncol. 2020, 21, 55. [Google Scholar] [CrossRef]
  85. Heinrich, M.C.; Jones, R.L.; von Mehren, M.; Schöffski, P.; Serrano, C.; Kang, Y.-K.; Cassier, P.A.; Mir, O.; Eskens, F.; Tap, W.D.; et al. Avapritinib in Advanced PDGFRA D842V-Mutant Gastrointestinal Stromal Tumour (NAVIGATOR): A Multicentre, Open-Label, Phase 1 Trial. Lancet Oncol. 2020, 21, 935–946. [Google Scholar] [CrossRef]
  86. Avapritinib Approved for GIST Subgroup. Cancer Discov. 2020, 10, 334. [CrossRef] [Green Version]
  87. Kenerson, H.; Folpe, A.L.; Takayama, T.K.; Yeung, R.S. Activation of the MTOR Pathway in Sporadic Angiomyolipomas and Other Perivascular Epithelioid Cell Neoplasms. Hum. Pathol. 2007, 38, 1361–1371. [Google Scholar] [CrossRef] [Green Version]
  88. Italiano, A.; Delcambre, C.; Hostein, I.; Cazeau, A.L.; Marty, M.; Avril, A.; Coindre, J.-M.; Bui, B. Treatment with the MTOR Inhibitor Temsirolimus in Patients with Malignant PEComa. Ann. Oncol. 2010, 21, 1135–1137. [Google Scholar] [CrossRef]
  89. Wagner, A.J.; Malinowska-Kolodziej, I.; Morgan, J.A.; Qin, W.; Fletcher, C.D.M.; Vena, N.; Ligon, A.H.; Antonescu, C.R.; Ramaiya, N.H.; Demetri, G.D.; et al. Clinical Activity of MTOR Inhibition with Sirolimus in Malignant Perivascular Epithelioid Cell Tumors: Targeting the Pathogenic Activation of MTORC1 in Tumors. J. Clin. Oncol. 2010, 28, 835–840. [Google Scholar] [CrossRef]
  90. Bill, K.L.J.; Garnett, J.; Meaux, I.; Ma, X.; Creighton, C.J.; Bolshakov, S.; Barriere, C.; Debussche, L.; Lazar, A.J.; Prudner, B.C.; et al. SAR405838: A Novel and Potent Inhibitor of the MDM2:P53 Axis for the Treatment of Dedifferentiated Liposarcoma. Clin. Cancer Res. 2016, 22, 1150–1160. [Google Scholar] [CrossRef] [Green Version]
  91. Laroche, A.; Chaire, V.; Algeo, M.-P.; Karanian, M.; Fourneaux, B.; Italiano, A. MDM2 Antagonists Synergize with PI3K/MTOR Inhibition in Well-Differentiated/Dedifferentiated Liposarcomas. Oncotarget 2017, 8, 53968–53977. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Dickson, M.A.; Schwartz, G.K.; Keohan, M.L.; D’Angelo, S.P.; Gounder, M.M.; Chi, P.; Antonescu, C.R.; Landa, J.; Qin, L.-X.; Crago, A.M.; et al. Phase 2 Trial of the CDK4 Inhibitor Palbociclib (PD0332991) at 125 Mg Dose in Well-Differentiated or Dedifferentiated Liposarcoma. JAMA Oncol. 2016, 2, 937–940. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Movva, S.; von Mehren, M.; Handorf, E.A.; Morgan, J.A.; Nathenson, M.; Thornton, K.A.; Tetzlaff, E.D.; Barker, E.; Thibodeau, L.; Harley, A.C.; et al. SAR-096: A Phase II Trial of Ribociclib in Combination with Everolimus in Advanced Dedifferentiated Liposarcoma (DDL), and Leiomyosarcoma (LMS). J. Clin. Oncol. 2020, 38, 11544. [Google Scholar] [CrossRef]
  94. Cornillie, J.; Wozniak, A.; Li, H.; Gebreyohannes, Y.K.; Wellens, J.; Hompes, D.; Debiec-Rychter, M.; Sciot, R.; Schöffski, P. Anti-Tumor Activity of the MDM2-TP53 Inhibitor BI-907828 in Dedifferentiated Liposarcoma Patient-Derived Xenograft Models Harboring MDM2 Amplification. Clin. Transl. Oncol. 2020, 22, 546–554. [Google Scholar] [CrossRef] [PubMed]
  95. Laroche-Clary, A.; Chaire, V.; Algeo, M.-P.; Derieppe, M.-A.; Loarer, F.L.; Italiano, A. Combined Targeting of MDM2 and CDK4 Is Synergistic in Dedifferentiated Liposarcomas. J. Hematol. Oncol. 2017, 10, 123. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Abdul Razak, A.R.; Bauer, S.; Suarez, C.; Lin, C.-C.; Quek, R.; Hütter-Krönke, M.L.; Cubedo, R.; Ferretti, S.; Guerreiro, N.; Jullion, A.; et al. Co-Targeting of MDM2 and CDK4/6 with Siremadlin and Ribociclib for the Treatment of Patients with Well-Differentiated or Dedifferentiated Liposarcoma: Results from a Proof-of-Concept, Phase Ib Study. Clin. Cancer Res. 2022, 28, 1087–1097. [Google Scholar] [CrossRef]
  97. Chibon, F.; Lagarde, P.; Salas, S.; Pérot, G.; Brouste, V.; Tirode, F.; Lucchesi, C.; de Reynies, A.; Kauffmann, A.; Bui, B.; et al. Validated Prediction of Clinical Outcome in Sarcomas and Multiple Types of Cancer on the Basis of a Gene Expression Signature Related to Genome Complexity. Nat. Med. 2010, 16, 781–787. [Google Scholar] [CrossRef]
  98. Lesluyes, T.; Delespaul, L.; Coindre, J.-M.; Chibon, F. The CINSARC Signature as a Prognostic Marker for Clinical Outcome in Multiple Neoplasms. Sci. Rep. 2017, 7, 5480. [Google Scholar] [CrossRef] [Green Version]
  99. Tawbi, H.A.; Burgess, M.; Bolejack, V.; Tine, B.A.V.; Schuetze, S.M.; Hu, J.; D’Angelo, S.; Attia, S.; Riedel, R.F.; Priebat, D.A.; et al. Pembrolizumab in Advanced Soft-Tissue Sarcoma and Bone Sarcoma (SARC028): A Multicentre, Two-Cohort, Single-Arm, Open-Label, Phase 2 Trial. Lancet Oncol. 2017, 18, 1493–1501. [Google Scholar] [CrossRef]
  100. Becht, E.; Giraldo, N.A.; Lacroix, L.; Buttard, B.; Elarouci, N.; Petitprez, F.; Selves, J.; Laurent-Puig, P.; Sautès-Fridman, C.; Fridman, W.H.; et al. Estimating the Population Abundance of Tissue-Infiltrating Immune and Stromal Cell Populations Using Gene Expression. Genome Biol. 2016, 17, 218. [Google Scholar] [CrossRef]
  101. Petitprez, F.; de Reyniès, A.; Keung, E.Z.; Chen, T.W.-W.; Sun, C.-M.; Calderaro, J.; Jeng, Y.-M.; Hsiao, L.-P.; Lacroix, L.; Bougoüin, A.; et al. B Cells Are Associated with Survival and Immunotherapy Response in Sarcoma. Nature 2020, 577, 556–560. [Google Scholar] [CrossRef] [PubMed]
  102. Italiano, A.; Dinart, D.; Soubeyran, I.; Bellera, C.; Espérou, H.; Delmas, C.; Mercier, N.; Albert, S.; Poignie, L.; Boland, A.; et al. Molecular Profiling of Advanced Soft-Tissue Sarcomas: The MULTISARC Randomized Trial. BMC Cancer 2021, 21, 1180. [Google Scholar] [CrossRef] [PubMed]
  103. Capper, D.; Jones, D.T.W.; Sill, M.; Hovestadt, V.; Schrimpf, D.; Sturm, D.; Koelsche, C.; Sahm, F.; Chavez, L.; Reuss, D.E.; et al. DNA Methylation-Based Classification of Central Nervous System Tumours. Nature 2018, 555, 469–474. [Google Scholar] [CrossRef] [PubMed]
  104. Koelsche, C.; Schrimpf, D.; Stichel, D.; Sill, M.; Sahm, F.; Reuss, D.E.; Blattner, M.; Worst, B.; Heilig, C.E.; Beck, K.; et al. Sarcoma Classification by DNA Methylation Profiling. Nat. Commun. 2021, 12, 498. [Google Scholar] [CrossRef] [PubMed]
  105. Burns, J.; Wilding, C.P.; Jones, R.L.; Huang, P.H. Proteomic Research in Sarcomas-Current Status and Future Opportunities. Semin. Cancer Biol. 2020, 61, 56–70. [Google Scholar] [CrossRef]
  106. Jerby-Arnon, L.; Neftel, C.; Shore, M.E.; Weisman, H.R.; Mathewson, N.D.; McBride, M.J.; Haas, B.; Izar, B.; Volorio, A.; Boulay, G.; et al. Opposing Immune and Genetic Mechanisms Shape Oncogenic Programs in Synovial Sarcoma. Nat. Med. 2021, 27, 289–300. [Google Scholar] [CrossRef]
  107. Aynaud, M.-M.; Mirabeau, O.; Gruel, N.; Grossetête, S.; Boeva, V.; Durand, S.; Surdez, D.; Saulnier, O.; Zaïdi, S.; Gribkova, S.; et al. Transcriptional Programs Define Intratumoral Heterogeneity of Ewing Sarcoma at Single-Cell Resolution. Cell Rep. 2020, 30, 1767–1779.e6. [Google Scholar] [CrossRef] [Green Version]
  108. Zhou, Y.; Yang, D.; Yang, Q.; Lv, X.; Huang, W.; Zhou, Z.; Wang, Y.; Zhang, Z.; Yuan, T.; Ding, X.; et al. Single-Cell RNA Landscape of Intratumoral Heterogeneity and Immunosuppressive Microenvironment in Advanced Osteosarcoma. Nat. Commun. 2020, 11, 6322. [Google Scholar] [CrossRef]
  109. Yofe, I.; Dahan, R.; Amit, I. Single-Cell Genomic Approaches for Developing the next Generation of Immunotherapies. Nat. Med. 2020, 26, 171–177. [Google Scholar] [CrossRef]
  110. Davis-Marcisak, E.F.; Deshpande, A.; Stein-O’Brien, G.L.; Ho, W.J.; Laheru, D.; Jaffee, E.M.; Fertig, E.J.; Kagohara, L.T. From Bench to Bedside: Single-Cell Analysis for Cancer Immunotherapy. Cancer Cell 2021, 39, 1062–1080. [Google Scholar] [CrossRef]
Table 1. Examples of chromosomal translocations and associated gene fusions most frequently detected in soft tissue sarcomas and mesenchymal tumors.
Table 1. Examples of chromosomal translocations and associated gene fusions most frequently detected in soft tissue sarcomas and mesenchymal tumors.
Sarcoma SubtypeTranslocationGenesOncogenic Mechanism
Ewing sarcomat (11; 22) (q24; q12)EWSR1, FLI1Transcription factor
t (21; 22) (q22; q12)EWSR1, ERG
t (16; 21) (p11; q22)FUS, ERG
DSRCTt (11; 22) (p13; q12)EWSR1, WT1Transcription factor
Alveolar rhabdomyosarcomat (2;13) (q35; q14)PAX3, FOXO1Transcription factor
t (1; 13) (p36; q14)PAX7, FOXO1
Clear cell sarcomat (12; 22) (q13; q12)EWSR1, ATF1Transcription factor
Extraskeletal myxoid chondrosarcomat (9; 22)
(q22–31; q11–12)
EWSR1, NR4A3Transcription factor
Myxoid liposarcomat (12; 22) (q13; q12)EWSR1, CHOPTranscription factor
t (12; 16) (q13; p11)FUS, CHOP
Alveolar soft part sarcomat (X; 17) (p11.2; q25)ASPL, TFE3Transcription factor
PEComaXp11 rearrangement*, TFE3Transcription factor
Low grade fibromyxoid sarcomat (7; 16) (q33; p11)FUS, CREB3L2Transcription factor
Sclerosing epithelioid fibrosarcomat (11; 22) (p11; q12)EWSR1, CREB3L1Transcription factor
Low grade endometrial stromal tumort (7; 17) (p15; q21)JAZF1, JJAZ1Transcription factor
Synovial sarcomat (X; 18) (p11; q11)SYT, SSX1, SSX2, SSX4Chromatin remodeling
Congenital fibrosarcomat (12; 15) (p13; q25)ETV6, NTRK3Tyrosine Kinase
Inflammatory myofibroblastic tumort (2; 19) (p23; p13.1)TPM4, ALKTyrosine Kinase
t (1; 2) (q22–23; p23)TPM3, ALK
Dermatofibrosarcoma protuberanst (17; 22) (q22; q13)COL1A1, PDGFβGrowth Factor
PVNS/TGCTt (1; 2) (p13; q37)COL6A3, CSF1Growth Factor
Abbreviations: DSRCT: desmoplastic small round cell tumor, PVNS/TGCT: pigmented villonodular synovitis/tenosynovial giant cell tumor. * Multiple gene partners.
Table 2. Examples of molecularly targeted therapies in soft tissue sarcomas.
Table 2. Examples of molecularly targeted therapies in soft tissue sarcomas.
Sarcoma SubtypeMolecular TargetTargeted TherapyOverall Response RateClinical UseReferences
NTRK-fused sarcomaNTRK1/2/3 fusionsEntrectinib46%FDA-approved[39,40,41]
74% (adults)
Larotrectinib94% (children)FDA-approved
IMTALK/ROS fusionsCrizotinib50% (adults)Off-label use[42,43]
85% (children)
DFSPCOL1A1-PDGFB fusionImatinib67% (advanced phase)FDA-approved[44,45,46,47]
40–60% (neoadjuvant)
PVNS/TGCTCOL6A3-CSF1 fusionsEmactuzumab86%Not approved[48,49]
Pexidartinib39%FDA-approved
GISTKIT mutationsImatinib53.7%FDA-approved[50,51,52,53,54]
Sunitinib7%FDA-approved
Regorafenib4.5%FDA-approved
Ripretinib9.4% (4th line)FDA-approved
Avapritinib17.1% (>2nd line)Not approved
GISTPDGFRA D842V mutationAvapritinib88%FDA-approved[55]
PEComaTSC1/2 mutationEverolimus41%Off-label use[56,57,58]
Sirolimus73%Off-label use
Nab-sirolimus39%FDA-approved
Epithelioid sarcomaSMARCB1 mutationTazemetostat15% (adults)FDA-approved[59,60]
MRT/ATRT17% (children)
DDLPSMDM2 amplificationSAR405838<10%Not approved[61,62]
MK-8242
Mesenchymal sarcomasIDH1-2 mutationOlaparib17%Not approved[63]
Abbreviations: IMT: inflammatory myofibroblastic tumors; DFSP: dermatofibrosarcoma protuberans; PVNS/TGCT: pigmented villonodular synovitis/tenosynovial giant cell tumor; GIST: gastrointestinal stromal tumors, MRT: malignant rhabdoid tumors; ATRT: atypical teratoid rhabdoid tumors; DDLPS: dedifferentiated liposarcoma.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Vibert, J.; Watson, S. The Molecular Biology of Soft Tissue Sarcomas: Current Knowledge and Future Perspectives. Cancers 2022, 14, 2548. https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14102548

AMA Style

Vibert J, Watson S. The Molecular Biology of Soft Tissue Sarcomas: Current Knowledge and Future Perspectives. Cancers. 2022; 14(10):2548. https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14102548

Chicago/Turabian Style

Vibert, Julien, and Sarah Watson. 2022. "The Molecular Biology of Soft Tissue Sarcomas: Current Knowledge and Future Perspectives" Cancers 14, no. 10: 2548. https://0-doi-org.brum.beds.ac.uk/10.3390/cancers14102548

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop