Characteristics and Treatment Patterns of Patients with Advanced Soft Tissue Sarcoma in Korea

First-Line Anlotinib Treatment for Soft-Tissue Sarcoma in Chemotherapy-Ineligible Patients: An Open-Label, Single-Arm, Phase 2 Clinical Trial

PURPOSE

Standard treatment for patients with unresectable locally advanced or metastatic soft-tissue sarcoma (LA/M STS) is chemotherapy based on anthracyclines, but patient tolerance of chemotherapy is limited. The present trial (NCT03792542) investigated the use of anlotinib as first-line treatment for patients with advanced STS, in particular liposarcoma.

PATIENTS AND METHODS

Eligible patients were previously untreated, pathologically confirmed, unresectable LA/M STS cases. Anlotinib was given orally at a dose of 12 mg once daily from days 1 to 14 every 3 weeks until disease progression or intolerable adverse events (AE) occurred. The primary endpoint was progression-free survival (PFS), and the secondary endpoints were overall survival (OS), objective response rate, and disease control rate (DCR). The safety profile was also evaluated.

RESULTS

Forty patients were enrolled from April 2019 to June 2022 and are included in the intention-to-treat analysis. The median PFS was 6.83 months [95% confidence interval (CI), 4.17-8.71] and the median OS 27.40 months (95% CI, 16.43-not evaluable); 1 patient reached partial response and 26 attained stable disease, with a DCR of 67.5% (27/40). Median PFS and OS times for liposarcoma patients were 8.71 and 16.23 months, respectively. Ten (25.0%) patients had treatment-related AEs ≥ grade 3, with in particular a higher incidence of hypertension (15.0%) and proteinuria (7.5%).

CONCLUSIONS

The findings suggest a potential benefit in using front-line anlotinib to treat patients with STS, who are not eligible for cytotoxic chemotherapy. Of note, the clinical outcomes for the liposarcoma subgroup of patients were encouraging. See related commentary by Napolitano et al., p. 4257.

Secondary hematological malignancies in patients with sarcoma: A single‑center retrospective study

The present retrospective study investigated the clinical features and prognosis of secondary hematological malignancies (SHMs) in patients with sarcoma at Korea Cancer Center Hospital (Seoul, South Korea). Patients who had been diagnosed with SHMs after having received treatment for sarcoma between January 2000 and May 2023 were enrolled. Clinical data were collected from the patients' medical records. Clinical characteristics were analyzed, including SHM incidence, type and prognosis. Of 2,953 patients with sarcoma, 18 (0.6%) were diagnosed with SHMs. Their median age at the time of sarcoma diagnosis was 39.5 (range, 9-72) years, and 74% (n=14) of these patients were male. The histological features of sarcoma varied, with osteosarcoma diagnosed in nine patients (50%). All patients with sarcoma underwent surgical treatment, and 16 (88.8%) received chemotherapy. The most common type of SHMs was acute myeloid leukemia (n=6; 33.3%), followed by myelodysplastic syndrome (n=5; 27.7%). The median latency period between the sarcoma diagnosis and SHM identification was 30 (range, 11-121) months. A total of 13 (72.2%) patients received treatment for the SHM. The median overall survival after SHM diagnosis was 15.7 (range, 0.4-154.9) months. The incidence of SHMs in sarcoma in the present study was consistent with that reported previously. The presence of SHMs was associated with a poor patient prognosis, especially if treatment for SHMs was not administered.

Necroptosis-related lncRNA-based novel signature to predict the prognosis and immune landscape in soft tissue sarcomas

BACKGROUND

Necroptosis-related long noncoding RNAs (lncRNAs) play crucial roles in cancer initiation and progression. Nevertheless, the role and mechanism of necroptosis-related lncRNAs in soft tissue sarcomas (STS) is so far unknown and needs to be explored further.

METHODS

Clinical and genomic data were obtained from the UCSC Xena database. All STS patients' subclusters were performed by unsupervised consensus clustering method based on the prognosis-specific lncRNAs, and then assessed their survival advantage and immune infiltrates. In addition, we explored the pathways and biological processes in subclusters through gene set enrichment analysis. At last, we established the necroptosis-related lncRNA-based risk signature (NRLncSig) using the least absolute shrinkage and selection operator (LASSO) method, and explored the prediction performance and immune microenvironment of this signature in STS.

RESULTS

A total of 911 normal soft tissue samples and 259 STS patients were included in current study. 39 prognosis-specific necroptosis-related lncRNAs were selected. Cluster 2 had a worse survival than the cluster 1 and characterized by different immune landscape in STS. A worse outcome in the high-risk group was observed by survival analysis and indicated an immunosuppressive microenvironment. The ROC curve analyses illustrated that the NRLncSig performing competitively in prediction of prognosis for STS patients. In addition, the nomogram presents excellent performance in predicting prognosis, which may be more beneficial towards STS patients' treatment.

CONCLUSIONS

Our result indicated that the NRLncSig could be a good independent predictor of prognosis, and significantly connected with immune microenvironment, thereby providing new insights into the roles of necroptosis-related lncRNAs in STS.

Factors predictive of second-line chemotherapy in soft tissue sarcoma: An analysis of the National Genomic Profiling Database

Of the drugs used in second-line chemotherapy for soft tissue sarcoma (STS), trabectedin is effective for liposarcoma and leiomyosarcoma (L-sarcoma), eribulin for liposarcoma, and pazopanib for non-liposarcoma. The indications for these drugs in STS other than L-sarcoma have not been established. Here we explored the prognosis, mutation profiles, and drug-response factors in STS using real-world big data. Clinicogenomic data on 1761 patients with sarcoma who underwent FoundationOne CDx were obtained from a national database in Japan. Patients with TP53 and KDM2D mutations had a significantly shorter survival period of 253 (95% CI, 99-404) and 330 (95% CI, 20-552) days, respectively, than those without mutations. Non-supervised clustering based on mutation profiles generated 13 tumor clusters. The response rate (RR) to trabectedin was highest in an MDM2-amplification cluster (odds ratio [OR]: 2.2; p = 0.2). The RR was lowest for eribulin in an MDM2-amplification cluster (OR: 0.4; p = 0.03) and highest in a TERT-mutation cluster (OR: 3.0; p = 0.03). The RR was highest for pazopanib in a PIK3CA/PTEN-wild type cluster (OR: 2.1; p = 0.03). In particular, patients harboring mutations in genes regulating the PI3K/Akt/mTOR pathway had a lower RR than patients without mutations (OR: 0.3; p = 0.04). In STS, mutation profiles were more useful in predicting the drug response than histology. The present study demonstrated the potential of tailored therapy guided by mutation profiles established by comprehensive genomic profiling testing in optimizing second-line chemotherapy for STS. The findings of this study will hopefully contribute some valuable insights into enhancing STS treatment strategies and outcomes.

Identification of m5C-related molecular subtypes and prediction models in the prognosis and tumor microenvironment infiltration of soft tissue sarcoma

Background

The epigenetic regulator in cancer progression and immune response has been demonstrated recently. However, the potential implications of 5-methylcytosine (m5C) in soft tissue sarcoma (STS) are unclear.

Methods

The RNA sequence profile of 911 normal and 259 primary STS tissues were obtained from GTEx and TCGA databases, respectively. We systematically analyzed the m5C modification patterns of STS samples based on 11 m5C regulators, and comprehensively correlated these modification patterns with clinical characteristics, prognosis, and tumor microenvironment (TME) cell-infiltrating. Furthermore, an m5C-related signature was generated using Cox proportional hazard model and validated by the GSE17118 cohort.

Results

Two distinct m5C modification patterns (cluster1/2) were discovered. The cluster1 had favorable overall survival, higher immune score, higher expression of most immune checkpoints, and active immune cell infiltration. The GSVA analysis of the P53 pathway, Wnt signaling pathway, G2M checkpoint, mTORC1 signaling, Wnt/β catenin signaling, and PI3K/AKT/mTOR signaling were significantly enriched in the cluster2. Moreover, 1220 genes were differentially expressed between two clusters, and a m5C prognostic signature was constructed with five m5C-related genes. The signature represented an independent prognostic factor and showed the favorable performance in the GSE17118 cohort. Patients in the low-risk group showed higher immunoscore and higher expression of most immune checkpoints. Further GSVA analysis indicated that the levels of P53 pathway, Wnt signaling pathway, and TGF-β signaling pathway were different between low- and high-risk groups. Moreover, a nomogram incorporating m5C signature and clinical variables was established and showed well performance.

Conclusion

This work showed that the m5C modification plays a significant role in the progression of STS and the formation of TME diversity. Evaluating the m5C modification pattern of tumor will enhance our cognition of TME infiltration characterization to guide more effective immunotherapy strategies.

Chemotherapeutic drugs for soft tissue sarcomas: a review

Despite the low incidence of soft tissue sarcomas (STSs), hundreds of thousands of new STS cases are diagnosed annually worldwide, and approximately half of them eventually progress to advanced stages. Currently, chemotherapy is the first-line treatment for advanced STSs. There are difficulties in selecting appropriate drugs for multiline chemotherapy, or for combination treatment of different STS histological subtypes. In this study, we first comprehensively reviewed the efficacy of various chemotherapeutic drugs in the treatment of STSs, and then described the current status of sensitive drugs for different STS subtypes. anthracyclines are the most important systemic treatment for advanced STSs. Ifosfamide, trabectedin, gemcitabine, taxanes, dacarbazine, and eribulin exhibit certain activities in STSs. Vinca alkaloid agents (vindesine, vinblastine, vinorelbine, vincristine) have important therapeutic effects in specific STS subtypes, such as rhabdomyosarcoma and Ewing sarcoma family tumors, whereas their activity in other subtypes is weak. Other chemotherapeutic drugs (methotrexate, cisplatin, etoposide, pemetrexed) have weak efficacy in STSs and are rarely used. It is necessary to select specific second- or above-line chemotherapeutic drugs depending on the histological subtype. This review aims to provide a reference for the selection of chemotherapeutic drugs for multi-line therapy for patients with advanced STSs who have an increasingly long survival.

Incidence and Temporal Variations of Bone and Soft Tissue Cancers in the Golestan Province, Northern Iran, 2004-2016

BACKGROUND

This study was conducted to evaluate the epidemiological features of bone and soft cancers in the Golestan province, Northern Iran from 2004 to 2016.

METHODS

This is a descriptive cross-sectional study. All patients with primary bone and soft tissue cancers between 2004 and 2016 were included. Data were obtained from Golestan population-based cancer registry (GPCR). We calculated age-standardized incidence rates (ASRs) and reported the rates per 100000 person-year. Estimated annual percent change (EAPC) was also calculated to assess temporal trends in incidence rates of these cancers.

RESULTS

The ASRs of bone cancers and soft tissue cancers were 1.33 and 1.43 per 100000 person-year, respectively. This study also showed that the ASR of bone cancer was higher in men (1.51) than women (1.15). The ASR of soft tissue cancers in the urban population (1.58) was higher than rural (1.27), and was lower in women (1.37) than men (1.49). Two peaks were seen in the incidence of bone cancer. The first peak was in the age group of 10 to 20 years and the second was in patients over 60. We did not find significant temporal trends in the incidence of bone (EAPC=-1.14; P>0.05) and soft tissue cancers (EAPC=-2.73; P>0.05) during the study period.

CONCLUSION

Epidemiological features of bone and soft tissue cancers including gender, age and place of residence should be considered by health policy makers in designing cancer control programs.

Mortality patterns of soft-tissue sarcomas worldwide up to 2018, with predictions for 2025

OBJECTIVE

The epidemiological evidence on soft-tissue sarcoma (STS) mortality is inconsistent in geographic and time coverage. This study provides mortality trends for STSs in selected countries worldwide over the last 2 decades, together with predicted figures for 2025.

METHODS

We extracted official numbers of certified deaths coded as C47 (i.e. malignant neoplasm of peripheral nerves and autonomic nervous system) and C49 (i.e. malignant neoplasm of other connective and soft tissue) according to the 10th Revision of the International Classification of Disease and population estimates from the WHO and the Pan American Health Organization databases. We computed age-standardized (world standard population) mortality rates (ASMRs). We used joinpoint regression analysis to identify significant changes in trends and to predict death numbers and rates for 2025.

RESULTS

The pattern emerging from the number of deaths and ASMRs up to 2018 shows an increase in most countries in both sexes. Around 2015 to 2018, ASMRs differed by 2.5-fold in both sexes with the highest rates being registered in Central-Eastern Europe, North America and Australia, while the lowest ones in Latin America, Japan, and Korea. In 2025, the number of STS deaths is predicted to increase in most countries and both sexes, and unfavourable rates are predicted in Central Europe in both sexes.

CONCLUSION

In addition to improvements in STSs registration, unfavourable mortality rates reported in this study reflect inadequate referral of patients with STSs to high-volume multidisciplinary centres, as well as insufficient advancements in STS prevention, diagnosis, and treatments.

Issues of diagnostic search of soft tissue sarcoma

Relevance. Soft tissue sarcoma is a heterogeneous group of relatively rare types of tumors, which demonstrates a huge variety of anatomical localization and histopathological characteristics. The rarity of soft tissue sarcomas combined with a variety of subtypes, forms of growth, progression and frequency of relapses makes it difficult to study them, make a correct diagnosis and early referral of patients for specialized care.

The purpose of study. To analyze the problem of differential diagnosis of malignant and benign soft tissue neoplasms.

Materials and methods. In the course of the work, current literary sources of domestic and foreign authors on a given topic were analyzed.

Results. Since it is absolutely impossible to determine the clinical features of the presented sarcoma, soft tissue tumors showing any of the following signs are considered malignant until the opposite is proven: increasing in size, >5 cm, deeply located and/or painful. The greater the number of these clinical signs present, the higher the risk that the soft tissue tumor will turn out to be malignant; at the same time, an increase in size is the best individual indicator. It is worth noting that the absence of concomitant constitutional symptoms, such as fever, chills, night sweats or unintentional weight loss, should not reduce the doctor's suspicion of malignancy.

Conclusion. In order to avoid erroneous diagnoses, a standardized diagnostic approach should be followed, starting from the moment of collecting the patient's medical history, clinical examination and ending with the use of appropriate imaging methods and biopsy.

Issues of diagnostic search of soft tissue sarcoma

Relevance. Soft tissue sarcoma is a heterogeneous group of relatively rare types of tumors, which demonstrates a huge variety of anatomical localization and histopathological characteristics. The rarity of soft tissue sarcomas combined with a variety of subtypes, forms of growth, progression and frequency of relapses makes it difficult to study them, make a correct diagnosis and early referral of patients for specialized care.

The purpose of study. To analyze the problem of differential diagnosis of malignant and benign soft tissue neoplasms.

Materials and methods. In the course of the work, current literary sources of domestic and foreign authors on a given topic were analyzed.

Results. Since it is absolutely impossible to determine the clinical features of the presented sarcoma, soft tissue tumors showing any of the following signs are considered malignant until the opposite is proven: increasing in size, >5 cm, deeply located and/or painful. The greater the number of these clinical signs present, the higher the risk that the soft tissue tumor will turn out to be malignant; at the same time, an increase in size is the best individual indicator. It is worth noting that the absence of concomitant constitutional symptoms, such as fever, chills, night sweats or unintentional weight loss, should not reduce the doctor's suspicion of malignancy.

Conclusion. In order to avoid erroneous diagnoses, a standardized diagnostic approach should be followed, starting from the moment of collecting the patient's medical history, clinical examination and ending with the use of appropriate imaging methods and biopsy.

A novel inflammatory signature for evaluating immune microenvironment status in soft tissue sarcoma

Background

Tumorigenesis and progression are intimately associated with inflammation. However, the inflammatory landscape in soft tissue sarcoma (STS) and its clinical consequences are yet unknown, and more investigation is needed.

Methods

RNA-seq expression data for STS and corresponding normal tissues were downloaded from The Cancer Genome Atlas database and the Genotype-Tissue Expression Portal. Differential and prognostic analyses were performed based on known inflammatory response genes from Gene Set Enrichment Analysis (GSEA). We utilized LASSO-Cox analysis to determine hub genes and built an inflammatory score (INFscore) and risk stratification model. Furthermore, a nomogram, including the risk stratification model, was established to predict the prognosis. We further elucidated the characteristics among different risk STS patients by GSEA, gene set variation analysis, and detailed immune infiltration analysis. Finally, the INFscore and risk stratification model in predicting prognosis and depicting immune microenvironment status were verified by pan-cancer analysis.

Results

Five hub genes (HAS2, IL1R1, NMI, SERPINE1, and TACR1) were identified and were used to develop the INFscore. The risk stratification model distinguished the immune microenvironment status and evaluated the efficacy of immunotherapy and chemotherapy in STS. The novel nomogram had good efficacy in predicting the prognosis of STS patients. Finally, a pan-cancer investigation verified the association of INFscore with prognosis and immunity.

Conclusions

According to the present study, the risk stratification model can be used to evaluate STS prognosis, tumor microenvironment status, immunotherapy, and chemotherapy efficacy. The novel nomogram has an excellent predictive value. Thus, the INFscore and risk stratification model has potential value in assessing the prognosis and immune status of multiple malignancies.

A Necroptosis-Related lncRNA Signature Predicts Prognosis and Indicates the Immune Microenvironment in Soft Tissue Sarcomas

Background: The necroptosis and long noncoding RNA (lncRNA) are critical in the occurrence and development of malignancy, while the association between the necroptosis-related lncRNAs (NRlncRNAs) and soft tissue sarcoma (STS) remains controversial. Therefore, the present study aims to construct a novel signature based on NRlncRNAs to predict the prognosis of STS patients and investigate its possible role.

Methods: The transcriptome data and clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression database (GTEx). A novel NRlncRNA signature was established and verified by the COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the K-M survival analysis, ROC, univariate, multivariate Cox regression analysis, and nomogram were used to evaluate the predictive value of the signature. Also, a variety of bioinformatic analysis algorithms explored the differences between the potential mechanism, tumor immune status, and drug sensitivity in the two-risk group. Finally, the RT-qPCR was performed to evaluate the expression of signature NRlncRNAs.

Results: A novel signature consisting of seven NRlncRNAs was successfully established and verified with stable prediction performance and general applicability for STS. Next, the GSEA showed that the patients in the high-risk group were mainly enriched with tumor-related pathways, while the low-risk patients were significantly involved in immune-related pathways. In parallel, we found that the STS patients in the low-risk group had a better immune status than that in the high-risk group. Additionally, there were significant differences in the sensitivity to anti-tumor agents between the two groups. Finally, the RT-qPCR results indicated that these signature NRlncRNAs were abnormally expressed in STS.

Conclusion: To the best of our knowledge, it is the first study to construct an NRlncRNA signature for STS. More importantly, the novel signature displays stable value and translational potential for predicting prognosis, tumor immunogenicity, and therapeutic response in STS.

Incidence, Treatment and Outcome of Patients with Retroperitoneal Soft-Tissue Sarcoma in Switzerland 2005-2015: A Population-Based Analysis

BACKGROUND

Reports on the epidemiology and mortality of retroperitoneal soft tissue sarcoma (RSTS) in Switzerland are scarce. This study investigates the incidence and outcomes of surgically treated RSTS inpatients in Switzerland depending on the hospital type and size.

METHODS

Data from the Swiss Federal Statistical Office were used to conduct a retrospective analysis of all RSTS inpatients and hospitalizations in Switzerland between 2005 and 2015. RSTS was identified by the code C48.x of the International Classification of Diseases (ICD-10). Sarcoma centers were identified by the annual total number of sarcoma patients (> 50 patients/year). The analysis of yearly incidence, age distribution as well as in-hospital complication and mortality was performed for non- and surgical-treated patients. A centralization of treating sarcoma patients was analyzed by the trend of hospitalizations in sarcoma centers and high-volume hospitals.

RESULTS

During 2005-2015, 2.801 hospitalizations (1651 patients) were admitted to Swiss hospitals with the primary diagnosis of a RSTS. The yearly number of RSTS patients and the incidence (1.91/100.000) stayed constant within these 11 years. There were five sarcoma centers. We saw a clear trend of RSTS patients being treated (especially surgically) in centers over the 11 years. The complication rate of surgical-treated patients was higher in sarcoma centers (55% vs. 40%), though the overall mortality rate was lower (3.2% vs. 9.1%).

CONCLUSION

Centralization of RSTS treatment to certified sarcoma centers leads to a lower overall mortality rate and thus is highly recommended.

Demographics, Changes in Treatment Patterns, and Outcomes of Bone and Soft Tissue Sarcomas in Korea-A Sarcoma-Specific, Institutional Registry-Based Analysis

Purpose

Because of the heterogeneity of sarcomas, establishing a well-collected, sarcoma-specific database is important for sarcoma research. We analyzed the first histology-based, sarcoma-specific institutional registry in Korea, which collected 28 years of patient data according to a predefined data format.

Patients and Methods

Adult bone and soft tissue sarcoma patients who were treated from June 1989 to January 2017 were identified and analyzed, based on the ICD-O-3 codes.

Results

Among the 3420 patients included, soft tissue and bone sarcomas comprised 77.8% (n = 2661) and 22.2% (n = 759), respectively. Median age at diagnosis was 50 (range, 16-98) in soft tissue sarcomas and 37 (range, 16-85) in bone sarcomas. Males and females comprised 45.5% and 54.5% of soft tissue sarcomas and 52.7% and 47.3% of bone sarcomas, respectively. Among the 3407 patients with treatment data available, 90.5% of the patients with soft tissue sarcomas and 80.8% of the patients with bone sarcomas received surgery first, of which 57.8% and 71.7% did not receive any subsequent treatment, respectively. Overall, the proportion of patients who received surgery alone decreased from 85.7% to 60.5% from the pre-2000 period to the 2010-2017 period. However, the use of adjuvant chemotherapy increased in patients with soft tissue sarcomas (from 8.0% to 17.2% in the same period), and the use of perioperative radiotherapy also increased in both groups (from 1.4% to 22.7% in soft tissue sarcomas, and 0% to 14.5% in bone sarcomas in the same period). In both soft tissue and bone sarcomas, old age (≥65 years) and diagnosis in the early study period were associated with poorer survival.

Conclusion

We presented a comprehensive summary of our sarcoma registry, including the demographics, changes in treatment patterns, and survival outcomes. This study will provide a framework for future studies.

Identification and Validation of Pyroptosis-Related lncRNA Signature and Its Correlation with Immune Landscape in Soft Tissue Sarcomas

Background

Pyroptosis is critically associated with cancer initiation and progression, which can be modulated by diverse long noncoding RNAs (lncRNAs). However, the roles of pyroptosis-related lncRNAs in soft tissue sarcomas (STS) are still largely unknown.

Methods

Our study included a total of 259 STS patients extracted from The Cancer Genome Atlas Sarcoma (TCGA-SARC) dataset. Gene expression data fragments per kilobase of transcript per million mapped reads (FPKM) values were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) for the investigation of the expression pattern of pyroptosis-related lncRNAs. Unsupervised clustering based on pyroptosis-related lncRNAs was performed, and the associations of pyroptosis-related lncRNAs with clinical outcomes and immune microenvironment were investigated. Two risk signatures for overall survival (OS) and disease-free survival (DFS) were constructed and validated in independent cohorts.

Results

A total of 166 pyroptosis-related lncRNAs were identified in STS. Patients were clustered into two subgroups by unsupervised clustering, and cluster 2 had better prognoses, higher immune scores, higher abundance of immune cells, and higher expression of some immune checkpoints. OS- and DFS-risk signatures based on 10 and 13 pyroptosis-related lncRNAs, respectively, with favorable discrimination were constructed and validated. High-risk patients had favorable prognoses, and receiver operating characteristic (ROC) curves showed that both risk signatures could function as excellent predictors for prognoses of STS patients. Besides, the OS-risk signature could also excellently predict the immune landscape of STS.

Conclusion

In conclusion, our study revealed the clinical significance and critical roles of pyroptosis-related lncRNAs in STS, and constructed novel risk signatures based on pyroptosis-related lncRNAs that could effectively predict clinical outcomes and immune microenvironment in STS.

Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations.

Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan–Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature.

Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS.

Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

Characterization of Immune-Related Long Non-coding RNAs to Construct a Novel Signature and Predict the Prognosis and Immune Landscape of Soft Tissue Sarcoma

Background: Increasing evidence has demonstrated that immune-related long non-coding RNAs (irlncRNAs) are critically involved in tumor initiation and progression and associated with the prognosis of various cancers. However, their role in soft tissue sarcoma (STS) remains significantly uninvestigated.

Materials and Methods: Gene expression profiles were extracted from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) for the identification of irlncRNAs. Univariate analysis and modified least absolute shrinkage and selection operator (LASSO) penalized regression analysis were employed to determine differently expressed irlncRNA (DEirlncRNA) pairs of prognostic value, and subsequently, a risk signature based on DEirlncRNA pairs was established. Furthermore, Kaplan–Meier analysis and the area under the receiver operating characteristic curve (AUC) were used to assess survival differences and the predictive accuracy of the risk signature, respectively. Lastly, the correlation of irlncRNAs with immune characteristics and chemosensitivity in patients with STS were further investigated.

Results: A total of 1088 irlncRNAs were identified, and 311 irlncRNAs were distinguished as DEirlncRNAs. A total of 130 DEirlncRNA pairs were further identified as prognostic markers, and 14 pairs were selected for establishing a risk signature. The irlncRNA-based risk signature functioned as an independent prognostic marker for STS. Compared with the patients in the high-risk group, those in the low-risk group exhibited a better prognosis and were more sensitive to several chemotherapeutic agents. In addition, the irlncRNA-based risk signature was significantly associated with immune scores, infiltrating immune cells, and the expression of several immune checkpoints.

Conclusion: In conclusion, our data revealed that the irlncRNA-based risk signature resulted in reliable prognosis, effectively predicted the immune landscape of patients with STS and was significantly correlated with chemosensitivity, thus providing insights into the potential role of irlncRNAs as prognostic biomarkers and novel therapeutic targets for STS.

Pulmonary metastasectomy in bone and soft tissue sarcoma with metastasis to the lung

 

OBJECTIVES

This study investigated the outcomes of sarcoma patients with lung metastases who underwent pulmonary metastasectomy (PM), compared to patients who underwent medical management alone. The secondary objective was to compare survival after PM between variables of interest.

METHODS

This was a retrospective review of 565 sarcoma patients with confirmed, isolated pulmonary metastasis identified from the Surveillance, Epidemiology and End Results database between 2010 and 2015. 1:4 propensity score matching was used to select PM and non-PM groups. The multivariable Cox proportional hazards model was used to analyse prognostic factors of disease-free survival (DFS).

RESULTS

Of the eligible 565 patients, 59 PM patients were matched to 202 non-PM patients in a final ratio of 3.4. After propensity matching, there were no significant differences in baseline characteristics between PM and non-PM patients. The median DFS after PM was 32 months (interquartile range 18–59), compared to 20 months (interquartile range 7–40) in patients without PM (P = 0.032). Using a multivariable Cox proportional hazards model, metastasectomy (hazard ratio 0.536, 95% confidence interval 0.33–0.85; P = 0.008) was associated with improved DFS. In a subset analysis of patients who underwent PM only, the median DFS was longer in males compared to females (P = 0.021), as well as in bone sarcoma compared to soft tissue sarcoma (P = 0.014).

CONCLUSIONS

For sarcoma patients with metastatic lung disease, PM appears to improve the prognosis compared to medical management. Furthermore, there may be a survival association with gender and tumour origin in patients who underwent PM. These data may be used to inform the surgical indications and eligibility criteria for metastasectomy in this setting.

Identification of Novel Prognostic Risk Signatures of Soft Tissue Sarcoma Based on Ferroptosis-Related Genes

Background

The role of ferroptosis in tumorigenesis has been confirmed in previous studies. However, the comprehensive analysis of ferroptosis-related gene (FRG) to study the role of FRG in soft tissue sarcoma (STS) is lacking.

Methods

RNA sequencing profile of TCGA-SARC cohort and GTEx were used to select differentially expressed FRGs (DEFRGs). Univariate, LASSO, and multivariate Cox analyses were selected to determine overall survival (OS)- and disease-free survival (PFS)-related FRGs. Two prognostic signatures were established and validated in two independent sets from Gene Expression Omnibus (GEO). Finally, the expression of key FRGs were validated with RT-qPCR.

Results

In total, 198 FRGs (90.4%) were abnormally expressed in STS. Twelve DEFRGs were incorporated in the final signatures and showed favorable discrimination in both training and validation cohorts. Patients in the different risk groups not only showed different prognosis, but also showed different infiltration of immune cells. Two nomograms combining signature and clinical variables were established and the C-indexes were 0.852 and 0.752 for the OS and DFS nomograms, respectively. Finally, the expression of NOX5, HELLS, and RPL8 were validated with RT-qPCR.

Conclusion

This comprehensive analysis of the FRG landscape in STS revealed novel FRGs related to carcinogenesis and prognosis. These findings have implications for prognosis and therapeutic responses, which revealed potential prognostic biomarkers and promote precision medicine.

Development and validation of an immune gene-set based prognostic signature for soft tissue sarcoma

Background

Sarcomas is a group of heterogeneous malignant tumors originated from mesenchymal tissue and different types of sarcomas have disparate outcomes. The present study aims to identify the prognostic value of immune-related genes (IRGs) in sarcoma and establish a prognostic signature based on IRGs.

Methods

We collected the expression profile and clinical information of 255 soft tissue sarcoma samples from The Cancer Genome Atlas (TCGA) database and 2498 IRGs from the ImmPort database. The LASSO algorithm and Cox regression analysis were used to identify the best candidate genes and construct a signature. The prognostic ability of the signature was evaluated by ROC curves and Kaplan-Meier survival curves and validated in an independent cohort. Besides, a nomogram based on the IRGs and independent prognostic clinical variables was developed.

Results

A total of 19 IRGs were incorporated into the signature. In the training cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.938, 0.937 and 0.935, respectively. The Kaplan-Meier survival curve indicated that high-risk patients were significantly worse prognosis (P < 0.001). In the validation cohort, the AUC values of signature at 1-, 2-, and 3-years were 0.730, 0.717 and 0.647, respectively. The Kaplan-Meier survival curve also showed significant distinct survival outcome between two risk groups. Furthermore, a nomogram based on the signature and four prognostic variables showed great accuracy in whole sarcoma patients and subgroup analyses. More importantly, the results of the TF regulatory network and immune infiltration analysis revealed the potential molecular mechanism of IRGs.

Conclusions

In general, we identified and validated an IRG-based signature, which can be used as an independent prognostic signature in evaluating the prognosis of sarcoma patients and provide potential novel immunotherapy targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07852-2.

Comprehensive profiling of immune-related genes in soft tissue sarcoma patients

Background

Immune-related genes (IRGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of IRGs and their clinical significance in soft tissue sarcoma (STS) patients is lacking.

Methods

Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed immune-related genes (DEIRGs) were determined by matching the DEG and ImmPort gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEIRGs was conducted, and associations with prognosis, the tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for progression free survival (PFS), were established and validated in an independent set. Finally, two transcription factor (TF)-IRG regulatory networks were constructed, and a crucial regulatory axis was validated.

Results

In total, 364 DEIRGs and four clusters were identified. OS, TME scores, five immune checkpoints, and 12 types of immune cells were found to be significantly different among the four clusters. The two prognostic signatures incorporating 20 DEIRGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.879 (95%CI 0.832 ~ 0.926) and 0.825 (95%CI 0.776 ~ 0.874) for the OS and PFS signatures, respectively. Finally, TF-IRG regulatory networks were established, and the MYH11-ADM regulatory axis was verified in three independent datasets.

Conclusion

This comprehensive analysis of the IRG landscape in soft tissue sarcoma revealed novel IRGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

Real-World Outcomes of Pazopanib Treatment in Korean Patients with Advanced Soft Tissue Sarcoma: A Multicenter Retrospective Cohort Study

BACKGROUND

Pazopanib is the only tyrosine kinase inhibitor approved for the treatment of patients with advanced soft tissue sarcoma (STS) who have received prior chemotherapy, but there have been limited real-world data on pazopanib for the treatment of advanced STS.

OBJECTIVE

We aimed to evaluate clinical outcomes of pazopanib in patients with multiple histologic STS types in real-world settings.

PATIENTS AND METHODS

We retrospectively analyzed clinical data of Korean patients with advanced STS treated with pazopanib between 2008 and 2019. Outcomes of interest included treatment response, survival according to histologic subtypes, and adverse events.

RESULTS

The analysis included 347 STS patients. The disease control rate for all pazopanib-treated patients was 54.8% (95% confidence interval (CI) 49.5-60.0); 54 patients (15.6%) achieved a partial response and 136 (39.2%) had stable disease. Patients with alveolar soft-part sarcoma (ASPS; 90%), solitary fibrous tumor (SFT; 88.2%), synovial sarcoma (66.7%), leiomyosarcoma (61.1%), and undifferentiated pleomorphic sarcoma (59.6%) showed higher disease control rates than those with other STS subtypes. Overall, median progression-free survival (PFS) and overall survival (OS) were 5.3 months (95% CI 4.5-6.0) and 12 months (95% CI 10-14), respectively. Noticeable survival outcomes occurred in patients with ASPS and SFT, with a median PFS of 24.5 (95% CI 2.5-30.0) and 13.0 (95% CI 3.0-21.3) months, respectively. The median OS of patients with ASPS and SFT was 48 (95% CI 17-52) and 32 (95% CI 19-66) months, respectively. Adverse drug reactions occurred in 170 patients (49.0%) but were not life-threatening.

CONCLUSIONS

This real-world data analysis showed acceptable efficacy and tolerability of pazopanib in patients pretreated with cytotoxic chemotherapy for advanced STS, with favorable treatment outcomes for ASPS and SFT.