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Prospective Genomic Profiling Study in Sarcoma Patients

CC BY 4.0 · Indian J Med Paediatr Oncol 2025; 46(04): 377-383

DOI: DOI: 10.1055/s-0045-1805022

Author : Gwo Fuang Ho , E Von Cheong , Wei Ying Chye , Kein Seong Mun , Rozita Abdul Malik , Marniza Saad

Abstract

Introduction Sarcoma is a heterogenous group of malignancy with diverse pathology and clinical behavior. Survival rates differ among histological subtypes, but overall prognosis remains poor due to the scarcity of effective systemic therapies. An insight into the genomic characteristics of different sarcoma histological subtypes enhances our understanding of the disease and highlights potential targeted therapies.

Objective We aim to enhance our understanding on the genomic profile of sarcomas and identify actionable genetic variants with the associated targeted therapies.

Materials and Methods A prospective tumor genomic profiling study was conducted via next-generation sequencing, involving 30 patients with a diagnosis of soft tissue or bone sarcoma at the University of Malaya Medical Centre. We evaluated the frequency and types of genomic aberrations and identified genomic variants with a therapeutic target.

Results A total of 70 genetic mutations were identified. The most frequently involved genes were TP53 (30.0%), followed by RB1 (20.0%), PIK3CA (10.0%), KIT (10.0%), PDGFR-α (10.0%), CKS1B (10.0%), KDR (10.0%), and MCL1 (10.0%). Genomic alteration involving the ALK gene was the only actionable variant identified. The DCTN1–ALK fusion was found to be targetable using entrectinib.

Conclusion Although the number of actionable variants identified was limited, such data are crucial for the selection of patients into clinical trials on novel therapies in the future and for establishing prognostic biomarkers.

Keywords

sarcoma - genomics - mutation - entrectinib

Data Availability Statement

The data (i.e., FoundationOne Heme test results) used to support the findings of this study are available from the corresponding author upon request.

Authors' Contributions

G.F.H. designed, conducted, and supervised the study. E.V.C. conducted the literature search and drafted and edited the manuscript. W.Y.C. performed data collection and assisted the patients in the enrollment process. K.S.M. reviewed and prepared the patients' tumor samples to ensure quality control standards were met for genomic profiling. R.A.M. was involved in patient recruitment. M.S. was involved in patient recruitment.

All the authors reviewed and approved the final manuscript. Each named author has substantially contributed to conducting this study and the writing of this article. This manuscript has been reviewed and approved by all the coauthors.

Patient's Consent

Written, informed consent was taken from each participant after explanation of the aims, methods, and anticipated benefits of the study.

Publication History

Article published online:
03 March 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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    Abstract

    Introduction Sarcoma is a heterogenous group of malignancy with diverse pathology and clinical behavior. Survival rates differ among histological subtypes, but overall prognosis remains poor due to the scarcity of effective systemic therapies. An insight into the genomic characteristics of different sarcoma histological subtypes enhances our understanding of the disease and highlights potential targeted therapies.

    Objective We aim to enhance our understanding on the genomic profile of sarcomas and identify actionable genetic variants with the associated targeted therapies.

    Materials and Methods A prospective tumor genomic profiling study was conducted via next-generation sequencing, involving 30 patients with a diagnosis of soft tissue or bone sarcoma at the University of Malaya Medical Centre. We evaluated the frequency and types of genomic aberrations and identified genomic variants with a therapeutic target.

    Results A total of 70 genetic mutations were identified. The most frequently involved genes were TP53 (30.0%), followed by RB1 (20.0%), PIK3CA (10.0%), KIT (10.0%), PDGFR-α (10.0%), CKS1B (10.0%), KDR (10.0%), and MCL1 (10.0%). Genomic alteration involving the ALK gene was the only actionable variant identified. The DCTN1–ALK fusion was found to be targetable using entrectinib.

    Conclusion Although the number of actionable variants identified was limited, such data are crucial for the selection of patients into clinical trials on novel therapies in the future and for establishing prognostic biomarkers.

    Keywords

    sarcoma - genomics - mutation - entrectinib

    Introduction

    Sarcoma is a rare group of mesenchymal neoplasm, comprising approximately 1% of all adult malignancies.[1] It comprises more than 70 histological subtypes and is especially challenging to study and treat given its diverse pathologies and clinical trajectories.[2] Survival rates vary across histological subtypes, but overall, prognosis is poor due to the limited effective systemic therapies. Five-year survival rates for metastatic soft tissue and bone sarcoma range between 15 and 24%.[3] [4]

    An insight into the genomic profile of different sarcoma histological subtypes facilitates our understanding of the disease and the potential targeted therapies that may improve prognosis. A high unmet need exists to explore options beyond conventional chemotherapeutic approach in the treatment of inoperable or metastatic sarcoma across different histological subtypes.

    In this study, we sought to utilize next-generation sequencing to ascertain the types and prevalence of genetic mutations across various histological subtypes of sarcoma. Our primary goal was to present an in-depth evaluation of the genomic profiles found in sarcoma that could be used to identify therapeutically actionable mutations and their associated targeted therapies. Our hypothesis is that there is a small number of actionable mutations with approved targeted therapies.

    Materials and Methods

    Study Design

    This single-center prospective study was conducted from August 2020 to July 2021 at the University of Malaya Medical Centre, a tertiary referral hospital with oncology services in Malaysia. Data cutoff was on July 31, 2021. All participants provided written informed consent prior to any study procedures.

    Patients

    Patients with a diagnosis of sarcoma confirmed via histopathological examination and tumor material suitable for genomic assay were deemed eligible for this study. Written informed consent prior to participation was a requirement. For patients under the age of 18 years, a legally authorized representative was required to consent on the patient's behalf. Patients were excluded from the study if they were pregnant or unwilling to provide written informed consent.

    The study did not require the patient to attend additional visits to the clinic other than the routine visits planned by their treating doctors during the study inclusion period.

    Sampling Protocol

    Patient data including demographics and clinical information were extracted from electronic medical records. Formalin-fixed paraffin-embedded (FFPE) tissue was obtained from each patient. Tumor samples from these patients were either FFPE blocks or 10 to 15 unstained slides with one original hematoxylin and eosin slide. The submission criteria for the submitted tissue samples included at least 25 mm2 of surface area, and a thickness of 4 to 5 μm. To maintain sensitivity for the detection of genomic alteration, it was a requirement for viable tumor cells to comprise at least 20% of the specimen.

    Tumor samples were sent for comprehensive genomic profiling (FoundationOne Heme test) at a Clinical Laboratory Improvement Amendments (CLIA) certified laboratory (Foundation Medicine, Cambridge, Massachusetts, United States). The FoundationOne Heme test is designed to detect genomic changes across numerous cancer-related genes in sarcomas. DNA sequencing was utilized to interrogate 406 genes and introns of 31 genes, and RNA sequencing for additional 265 genes. Microsatellite stability was evaluated by analyzing insertion and deletion characteristics at 114 homopolymer repeat loci within or near the targeted gene regions. Tumor mutational burden was established by measuring the number of somatic mutations in the sequenced genes.

    The primary outcomes in this study are the prevalence and types of genomic alterations in sarcoma patients. The secondary outcomes are the demographics and the histologic subtypes of sarcoma in our study population.

    Statistical Analysis

    Statistical analyses included counts and percentages for categorical variables and the median, minimum, and maximum for continuous variables.

    Ethical Approval

    Study approval was granted by the Medical Research Ethics Committee at the University of Malaya Medical Centre on August 11, 2020 (ethics approval number: 2020723- 8909). This study was conducted in accordance with the ethical standards of the Declaration of Helsinki (1964) and the International Council on Harmonization guidelines for Good Clinical Practice.

    Results

    Patient Characteristics

    Thirty-five patients with histopathological confirmation of sarcoma diagnosis consented to be enrolled in the study. Five patients were excluded as their tumor samples did not meet the quality control standards of the laboratory or our histopathologist (2 insufficient tissue samples, 1 insufficient tissue cellularity, 1 extensive decalcification, and 1 with multiple DNA signatures). Thirty patients underwent tumor genomic profiling.

    The baseline characteristics of the 30 sarcoma patients who underwent tumor genetic profiling are summarized in [Table 1]. The median age of the patients was 42.5 years, ranging from 21 to 77 years. The majority of the patients were females (66.7%) and Chinese (83.3%). Soft tissue sarcoma was the most common type of sarcoma observed in patients enrolled in this study (n = 26; 86.7%). Seventeen sarcoma subtypes were identified in total. The most common sarcoma subtype was leiomyosarcoma (n = 5; 16.7%; [Fig. 1]), followed by sarcoma, not otherwise specified (n = 4; 13.3%). Over 60% of patients had metastatic disease upon participation (n = 19). Twenty-five patients (83.3%) underwent tumor genomic interrogation via both DNA and RNA sequencing, while five patients (16.7%) had DNA sequencing done only as RNA sequencing failed due to the sample quality.

    Table 1

    Baseline characteristics of sarcoma patients (n = 30)

    Characteristics

    Estimates[a]

    Age (y)

    42.5 (21–77)

    Sex

     Male

    10 (33.3)

     Female

    20 (66.7)

    Ethnicity

     Malay

    3 (10.0)

     Chinese

    25 (83.3)

     Indian

    2 (6.7)

    Sarcoma types

     Soft tissue

    26 (86.7)

     Bone

    4 (13.3)

    Histologic subtypes

     Leiomyosarcoma

    5 (16.7)

     Sarcoma (NOS)

    4 (13.3)

     Epithelioid sarcoma

    3 (10.0)

     Angiosarcoma

    2 (6.7)

     Liposarcoma

    2 (6.7)

     Fibrosarcoma

    2 (6.7)

     Osteosarcoma

    2 (6.7)

     Rhabdomyosarcoma

    1 (3.3)

     Ewing's Sarcoma

    1 (3.3)

     Synovial sarcoma

    1 (3.3)

     Carcinosarcoma

    1 (3.3)

     Chondrosarcoma

    1 (3.3)

     Clear cell sarcoma

    1 (3.3)

     Myxofibrosarcoma

    1 (3.3)

     Chordoma

    1 (3.3)

     Malignant peripheral nerve sheath tumor

    1 (3.3)

     Solitary fibrous tumor

    1 (3.3)

    Metastatic disease

     Yes

    19 (63.3)

     No

    11 (36.7)

    Genome sequencing

     DNA and RNA analyses

    25 (83.3%)

     DNA only analysis

    5 (16.7%)

    Abbreviation: NOS, not otherwise specified.

    a Estimates are reported as median (range) for age and N (%) for categorical variables.

      Fig 1: Leiomyosarcoma showing cellular tumor composed of spindle cells that are haphazardly arranged. The nuclei show varying degrees of pleomorphism, and numerous mitotic figures (red arrows) are present (hematoxylin and eosin stain; original magnification ×20 objective).

    Genomic Profile

    All patients in this study harbored at least one genetic mutation. The number of genetic mutations found in each patient ranged from 1 to 12, with an average of 3.5. The majority of patients had three or more coexisting genetic mutations (n = 16; 53.3%). The frequency, distribution and type of genomic aberrations are illustrated in [Fig. 2] and [Table 2]. A total of 70 genes were found to harbor mutations. The most frequently involved gene was TP53 (30.0%), followed by RB1 (20.0%), PIK3CA (10.0%), KIT (10.0%), PDGFRA (10.0%), CKS1B (10.0%), KDR (10.0%), and MCL1 (10.0%). Genomic alteration involving the ALK gene was the only targetable mutation identified. The DCTN1–ALK fusion was found to be targetable using entrectinib in this study.

      Fig 2 : Frequency and distribution of genomic alterations in sarcoma patients.


    Table 2

    Types of mutations found for each gene

    Genes

    Types of mutation

    TP53

    C229fs*10, L194R, E346fs*24, loss, splice site 994–1G > A, R273C, P152L, H193P

    RB1

    Loss, R320, L477fs*18, loss exons 1–17, deletion exons 4–17, loss exons 3–27

    PIK3CA

    V344G, G118D, C378Y

    KIT

    Amplification

    PDGFRA

    Amplification

    CKS1B

    Amplification

    KDR

    Amplification

    MCL1

    Amplification

    EWSR1

    EWSR1-FLI1 fusion, EWSR1-CREB3L1 fusion

    SMARCB1

    E280, loss

    ATRX

    Q883fs*13, T1239fs*9

    CD36

    T111fs*22, Q74

    PTEN

    Loss exons 1–2, C136R

    CDKN2A/B

    Loss

    FGFR1

    N546K, amplification

    NFKBIA

    R17fs*69, amplification

    AURKB

    Amplification

    PIK3R1

    G376R

    GNAQ

    R183Q

    C17orf39

    Amplification

    LRP1B

    R902S

    EGFR

    P753S

    PASK

    R1267

    ARID2

    Rearrangement exon 21

    FGF14

    Amplification

    IRS2

    Amplification

    SOEN

    Rearrangement exon 11

    MDM4

    Amplification

    ARID1A

    Q510

    MET

    Amplification

    CDK6

    Amplification

    CHEK2

    Q487

    HGF

    Amplification

    MAP3K4

    Rearrangement exon 21

    PIIK3CG

    Amplification

    CUX1

    Splice site 1516–1G > A

    DAXX

    Rearrangement exon 2

    BRIP1

    Rearrangement intron 4

    CCNE1

    Amplification

    TRAF2

    Rearrangement exon 2

    ZNF703

    Amplification

    KDM6A

    S700fs*29

    MED12

    G44C

    FBXW7

    R505C

    ARAF

    R188H

    RET

    R813W

    DNM2

    Deletion exons 2–11

    WHSC1 (MMSET)

    E1099K

    RAD50

    E723fs*5

    NF1

    S1100

    ALK

    DCTN1-ALK fusion

    PTPN6

    R554C

    MEN1

    R521fs*15

    MYC

    Amplification

    BRD4

    Amplification

    CTCF

    Rearrangement exon 11

    CBL

    Y371N

    SUZ12

    Rearrangement intron 4

    BIRC3

    Loss

    MALT1

    Amplification

    MAP2K2 (MEK2)

    Amplification

    STAT6

    NAB2–STAT6 fusion

    APC

    C2042fs*2

    CCT6B

    I4V

    PIK3R2

    D163fs*24

    HNF1A

    R131W

    MUTYH

    Splice site 892–2A > G

    CDK4

    Amplification

    MDM2

    Amplification

    FRS2

    Amplification
    As illustrated in [Fig. 3], various types of genomic aberrations were identified in this study. Single nucleotide variants constituted the majority of the variation found (43.1%), followed by amplification (19.6%).


      Fig 3 : Types of genomic aberrations in sarcoma patients.

    Microsatellite status could not be determined in 2 patients, while the other 28 patients had microsatellite-stable tumors. Tumor mutational burden ranged from 0 to 7 mutations per megabase with an average of 3.0.

    Discussion

    In our single-institution cohort, only one actionable mutation was found. It was an ALK fusion in a patient with metastatic leiomyosarcoma, which is targetable with entrectinib. Our findings echo that of other large-scale studies that have demonstrated a small number of actionable variants with an approved clinical therapy.[5] [6] Of note, we found that patients with fusion-driven sarcomas had no co-occurring mutations, which correlates with findings from the Stanford Cancer Institute cohort.[6]

    ALK fusions have been identified in soft tissue inflammatory myofibroblast tumors and leiomyosarcoma cases.[7] [8] ALK fusions that alter the expression of the ALK kinase domain have been characterized as oncogenic.[9] In a murine model of leiomyosarcoma with a KANK2–ALK fusion, monotherapy with lorlatinib, an ALK kinase inhibitor, was found to hinder tumor growth and significantly prolong overall survival (p < 0.001), providing the first functional validation of an actionable oncogenic kinase fusion in leiomyosarcoma.[8] In our study, entrectinib was found to be a suitable target for our patient who harbored ALK alteration in the form of a DCTN1–ALK fusion. This suggests that distinct ALK fusions are targetable by specific ALK kinase inhibitors, hence the need for meticulous evaluation of genomic alterations.

    Entrectinib is an inhibitor of the tyrosine kinases TRKA/B/C, ROS1, and ALK. Two phase 1 trials (ALKA-372–001 and STARTRK-1) demonstrated that entrectinib was well tolerated with antitumor activity in NTRK, ROS1, or ALK fusion-positive solid tumors.[10] [11] [12] STARTRK-2 trial is a phase 2 basket study of entrectinib in solid tumors. While we await the results of the STARTRK-2 trial to be released, preliminary findings of the trial presented at the 2017 Connective Tissue Oncology Society Annual Meeting have been promising. Three sarcoma patients, two with ALK gene fusions and one with NTRK gene fusion, have had measurable clinical response to entrectinib.[13] Decrease in tumor size ranged from 30 to 68%. by RECIST criteria version 1.1.[13] [14]

    In our study, TP53 and RB1 were among the most frequently mutated genes, at the rates of 30 and 20%., respectively. This corresponds to findings from other large-scale genomic studies on sarcoma patients.[5] [6] Functional loss of the tumor suppressor p53 protein, encoded by the TP53 gene, plays a critical role in tumorigenesis. TP53 gene mutations have been reported in chondrosarcomas, leiomyosarcomas, and undifferentiated pleomorphic sarcoma.[15] [16] Although there are no approved therapies thus far to treat sarcomas with TP53 alterations, it is worth noting that a small, retrospective study reported improved survival in advanced soft tissue sarcoma patients with TP53 mutations who were treated with vascular endothelial growth factor (VEGF) inhibitors (18 patients on pazopanib, 1 patient on sunitinib).[17] The authors reported that the progression-free survival (PFS) of patients with TP53 mutations was significantly greater than TP53 wild-type tumors (208 vs. 136 days; p = 0.036; hazard ratio [HR]: 0.38; 95%. confidence interval: 0.09–0.83), when treated with VEGF inhibitors.[17] Larger prospective studies are needed to confirm if TP53 mutation may serve as a biomarker that predicts response to VEGF inhibitors.

    RB1 encodes the retinoblastoma protein (Rb), a tumor suppressor and cell cycle regulator.[18] Germline mutations in RB1 account for 40%. of retinoblastoma cases and are associated with soft tissue and bone sarcoma, malignant melanoma, and brain tumors.[19] [20] There are no approved targeted therapies thus far for RB1-mutated sarcomas, and data on its prognostic implications are scarce. Given that RB1 mutation is highly prevalent in sarcoma and is associated with other types of malignancies, this should prompt the clinician to perform RB1 germline testing in the appropriate clinical context.

    The frequency of PDGFR-α and KIT mutations in this study was 10%.. PDGFR-α encodes platelet-derived growth factor receptor α, a tyrosine kinase receptor that, upon binding of PDGF-α or PDGF-β ligands, activates several signaling pathways, including PI3K and MAPK.[21] PDGFR-α-mutated gastrointestinal stromal tumors (GISTs) generally have an indolent disease trajectory and are associated with localized disease and a low risk of recurrence.[22] Of note, imatinib has been reported to have limited efficacy specifically in PDGFR-α D842V mutated GIST, while other types of PDGFR-α mutations appear to be sensitive to imatinib.[22] To date, avapritinib, a selective, potent inhibitor of KIT- and PDGFR-α mutant kinases, is approved in the United States and the European Union for the treatment of PDGFR-α D842V mutated GISTs.[23] [24] These approvals were based on findings of the NAVIGATOR trial demonstrating the manageable safety profile and antitumor activity of avapritinib (88%. of 56 patients had an overall response, with 5 [9%.] complete responses and 44 [79%.] partial responses).[25]

    KIT encodes a cell surface tyrosine kinase receptor that activates the PI3K–AKT and RAS–MAPK signaling pathways upon ligand binding and dimerization. Up to 80%. of GISTs harbor KIT mutations, a targetable genomic alteration sensitive to imatinib.[26] KIT mutations have also been reported in osteosarcoma and are associated with disease recurrence and shorter survival time.[27] [28] Tyrosine kinase inhibitors such as sorafenib and sunitinib have been shown to have clinical benefit in patients with KIT-mutated tumors, albeit current evidence is limited to advanced melanoma cases.[29] [30]

    In this study, PIK3CA mutations were reported in 10%. of our patients. Although this genomic alteration is still of unknown clinical importance in the treatment of sarcoma, there are clinical data indicating response to therapies targeting PI3K (alpelisib) and AKT (capivasertib) in PIK3CA-mutated breast cancer.[31] [32] PIK3CA mutations in soft tissue sarcoma have been associated with shorter disease-specific survival.[33] Further studies are needed for characterizing the functional importance of PIK3CA mutations in sarcoma and therapies with clinical benefit.

    Many patients in our cohort had microsatellite-stable tumors and low tumor mutational burden (mean: 3.0 mutations per megabase). Generally, sarcomas harbor a low median tumor mutational burden of 2.5 mutations per megabase.[34] Reports on microsatellite instability (MSI) in sarcomas in the literature are conflicting and varied due to the diverse methodology for MSI assessment and small sample size in many studies.[35] [36] [37] Based on clinical evidence, microsatellite-stable tumors and low tumor mutational burden are associated with reduced sensitivity to immunotherapeutic agents.[38]

    Several limitations should be considered when evaluating the clinical significance of our findings. This study is based on a single institution's cohort with a limited sample size. A larger dataset would be beneficial in identifying more actionable variants with the corresponding targeted therapy. It should be noted that five of our patients underwent only DNA analysis instead of DNA and RNA sequencing due to sample quality. Hence, this may have reduced sensitivity for detection of copy number alterations. In addition, genomic alterations that take place throughout one's disease trajectory may not be captured by a single time point biopsy. The possibility of genomic heterogeneity between primary tumor and metastatic sites should be taken into consideration. Utilizing circulating tumor DNA from peripheral blood, which potentially captures DNA from multiple tumor sites, might offer a solution to this issue. This study should prompt future studies using circulating tumor DNA to identify actionable genomic alterations.

    Conclusion

    This study shows that sarcomas do carry genetic mutations, some of which are targetable. Although the number of actionable variants identified remains limited, such data will be crucial for the selection of patients into clinical trials on novel therapies in the future and for establishing prognostic biomarkers. An understanding of the type and prevalence of mutations in sarcoma patients may guide treatment decisions and facilitate prognostication.

    Conflict of Interest

    None declared.

    Acknowledgments

    The authors would like to thank their patients for consenting to participate in this study.

    Data Availability Statement

    The data (i.e., FoundationOne Heme test results) used to support the findings of this study are available from the corresponding author upon request.

    Authors' Contributions

    G.F.H. designed, conducted, and supervised the study. E.V.C. conducted the literature search and drafted and edited the manuscript. W.Y.C. performed data collection and assisted the patients in the enrollment process. K.S.M. reviewed and prepared the patients' tumor samples to ensure quality control standards were met for genomic profiling. R.A.M. was involved in patient recruitment. M.S. was involved in patient recruitment.

    All the authors reviewed and approved the final manuscript. Each named author has substantially contributed to conducting this study and the writing of this article. This manuscript has been reviewed and approved by all the coauthors.

    Patient's Consent

    Written, informed consent was taken from each participant after explanation of the aims, methods, and anticipated benefits of the study.

    References


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    28.  Entz-Werlé N, Marcellin L, Gaub M-P. et al. Prognostic significance of allelic imbalance at the c-kit gene locus and c-kit overexpression by immunohistochemistry in pediatric osteosarcomas. J Clin Oncol 2005; 23 (10) 2248-2255
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    30.  Minor DR, Kashani-Sabet M, Garrido M, O'Day SJ, Hamid O, Bastian BC. Sunitinib therapy for melanoma patients with KIT mutations. Clin Cancer Res 2012; 18 (05) 1457-1463
      Crossref PubMed Search in Google Scholar
    31.  André F, Ciruelos E, Rubovszky G. et al; SOLAR-1 Study Group. Alpelisib for PIK3CA-mutated, hormone receptor–positive advanced breast cancer. N Engl J Med 2019; 380 (20) 1929-1940
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    32.  Schmid P, Abraham J, Chan S. et al. Capivasertib plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer: the PAKT trial. J Clin Oncol 2020; 38 (05) 423-433
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    33.  Barretina J, Taylor BS, Banerji S. et al. Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy. Nat Genet 2010; 42 (08) 715-721
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    34.  Chalmers ZR, Connelly CF, Fabrizio D. et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 2017; 9 (01) 34
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    35.  Monument MJ, Lessnick SL, Schiffman JD, Randall RT. Microsatellite instability in sarcoma: fact or fiction?. ISRN Oncol 2012; 2012: 473146
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    36.  Lam SW, Kostine M, de Miranda NFCC. et al. Mismatch repair deficiency is rare in bone and soft tissue tumors. Histopathology 2021; 79 (04) 509-520
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    Publication History

    Article published online:
    03 March 2025

    © 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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        Fig 1: Leiomyosarcoma showing cellular tumor composed of spindle cells that are haphazardly arranged. The nuclei show varying degrees of pleomorphism, and numerous mitotic figures (red arrows) are present (hematoxylin and eosin stain; original magnification ×20 objective).


        Fig 2 : Frequency and distribution of genomic alterations in sarcoma patients.


        Fig 3 : Types of genomic aberrations in sarcoma patients.


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        Crossref PubMed Search in Google Scholar
      28.  Entz-Werlé N, Marcellin L, Gaub M-P. et al. Prognostic significance of allelic imbalance at the c-kit gene locus and c-kit overexpression by immunohistochemistry in pediatric osteosarcomas. J Clin Oncol 2005; 23 (10) 2248-2255
        Crossref PubMed Search in Google Scholar
      29.  Handolias D, Hamilton AL, Salemi R. et al. Clinical responses observed with imatinib or sorafenib in melanoma patients expressing mutations in KIT. Br J Cancer 2010; 102 (08) 1219-1223
        Crossref PubMed Search in Google Scholar
      30.  Minor DR, Kashani-Sabet M, Garrido M, O'Day SJ, Hamid O, Bastian BC. Sunitinib therapy for melanoma patients with KIT mutations. Clin Cancer Res 2012; 18 (05) 1457-1463
        Crossref PubMed Search in Google Scholar
      31.  André F, Ciruelos E, Rubovszky G. et al; SOLAR-1 Study Group. Alpelisib for PIK3CA-mutated, hormone receptor–positive advanced breast cancer. N Engl J Med 2019; 380 (20) 1929-1940
        Crossref PubMed Search in Google Scholar
      32.  Schmid P, Abraham J, Chan S. et al. Capivasertib plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer: the PAKT trial. J Clin Oncol 2020; 38 (05) 423-433
        Crossref PubMed Search in Google Scholar
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        Crossref PubMed Search in Google Scholar
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        Crossref PubMed Search in Google Scholar
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        PubMed Search in Google Scholar
      36.  Lam SW, Kostine M, de Miranda NFCC. et al. Mismatch repair deficiency is rare in bone and soft tissue tumors. Histopathology 2021; 79 (04) 509-520
        Crossref PubMed Search in Google Scholar
      37.  Fernandes I, Dias E Silva D, Segatelli V. et al. Microsatellite instability and clinical use in sarcomas: systematic review and illustrative case report. JCO Precis Oncol 2024; 8: e2400047
        Crossref PubMed Search in Google Scholar
      38.  Samstein RM, Lee CH, Shoushtari AN. et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet 2019; 51 (02) 202-206
        Crossref PubMed Search in Google Scholar

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