Complexity INdex In SARComas Research Articles

CINSARC in high-risk soft tissue sarcoma patients treated with neoadjuvant chemotherapy: Results from the ISG-STS 1001 study.

The Complexity INdex in SARComas (CINSARC) is a transcriptional signature derived from the expression of 67 genes involved in mitosis control and chromosome integrity. This study aims to assess CINSARC value of in an independent series of high-risk patients with localized soft tissue sarcoma (STS) treated with preoperative chemotherapy within a prospective, randomized, phase III study (ISG-STS 1001). Patients with available pre-treatment samples, treated with 3 cycles of either standard (ST) preoperative or histotype-tailored (HT) chemotherapy, were scored according to CINSARC (low-risk, C1; high-risk, C2). The 10-year overall survival probability (pr-OS) according to SARCULATOR was calculated, and patients were classified accordingly (low-risk, Sarc-LR, 10-year pr-OS>60%; high-risk, Sarc-HR, 10-year pr-OS<60%). Survival functions were estimated using the Kaplan-Meier method and compared using log-rank test. Eighty-six patients were included, 30 C1 and 56 C2, 49 Sarc-LR and 37 Sarc-HR. A low level of agreement between CINSARC and SARCULATOR was observed (Cohen's Kappa=0.174). The 5-year relapse-free survival in C1 and C2 were 0.57 and 0.55 (p= 0.481); 5-year metastases-free survival 0.63 and 0.64 (p= 0.740); 5-year OS 0.80 and 0.72 (p= 0.460). The 5-year OS in C1 treated with ST and HT chemotherapy was 0.84 and 0.76 (p= 0.251) respectively; in C2 treated it was 0.72 and 0.70 (p= 0.349). The 5-year OS in Sarc-LR treated with S and HT chemotherapy was 0.80 and 0.82 (p= 0.502) respectively; in Sarc-HR it was 0.70 and 0.61 (p= 0.233). Our results, although constrained by the small size of the series, suggest that CINSARC has weak prognostic power in high-risk, localized STS treated with neoadjuvant chemotherapy.

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

BackgroundSoft-tissue sarcomas (STSs) are heterogeneous and aggressive tumors, with high metastatic risk. The immunologic constant of rejection (ICR) 20-gene signature is a signature of cytotoxic immune response. We hypothesized that...

A Global and Integrated Analysis of CINSARC-Associated Genetic Defects.

The Complexity Index in Sarcomas (CINSARC) signature is a transcriptomic marker that identifies high-risk soft-tissue sarcomas and is associated with high metastatic potential. During the last decade, CINSARC has been successfully developed and validated and is currently being assessed in two prospective phase III clinical trials for stratification of therapy. Although the link between CINSARC expression and tumor aggressiveness is well established, questions remain about how CINSARC genes are regulated. In this study, we leveraged a The Cancer Genome Atlas multiomics study on sarcomas with complex genetics to appraise the association between CINSARC profile, genomic features, and two potential regulation mechanisms, DNA methylation and miRNA expression. CINSARC expression was associated with an increase of ploidy, intratumor heterogeneity, copy-number alteration, altered expression of 37 miRNAs, and a decrease of DNA methylation. These genetic changes are not independent, but rather act together to promote or repress CINSARC expression. These findings depict new insights into CINSARC regulation. SIGNIFICANCE: These findings demonstrate that CINSARC is associated with a variety of genomic aberrations that contribute to higher risk for metastasis and may serve as a prognostic factor in sarcomas and beyond.

The prognostic value of CINSARC in a randomised trial comparing histotype-tailored neoadjuvant chemotherapy versus standard chemotherapy in patients with high-risk soft-tissue sarcomas (ISG-STS 1001).

e23531 Background: The Complexity INdex in SARComas (CINSARC) is a gene expression signature related to mitosis and chromosome integrity that stratifies risk for recurrence of soft tissue sarcoma (STS) patients. The aim of this study was to validate the prognostic value of CINSARC in patients enrolled in a randomised trial that compared histotype-tailored neoadjuvant chemotherapy with standard chemotherapy in patients with high-risk STS (ISG-STS 1001). Methods: CINSARC is 67-gene-expression-based signature that has been previously tested in retrospective series. The ISG-STS 1001 was a phase 3 RCT comparing histotype-tailored and anthracycline-based chemotherapy in localised, high-risk STS of the extremities or trunk wall, with one of five histological STS subtypes: high-grade myxoid liposarcoma, leiomyosarcoma, synovial sarcoma, malignant peripheral nerve sheath tumour, and undifferentiated pleomorphic sarcoma. Outcome variables were disease-free survival (DFS), overall survival (OS) and tumour response according to RECIST v1.1. Results: CINSARC was assessed in pre-treatment biopsies of 87 in 435 patients participating in the study. Thirty and 57 patients segregated in the lower (C1) and higher (C2) CINSARC risk group, respectively. Incidence of local recurrences (LR) and distant metastasis (DM) did not differ between C1 and C2 CINSARC groups [2 (6.6%) and 11 (19.3%) patients had a LR, respectively, and 10 (33.3%) and 14 (24.5%) patients had DM, respectively, P = 0.800]. Consistently, we did not observe statistically significant differences for DFS and OS between patients in the CINSARC C1 and C2 groups (log-rank test, P = 0.522 and P = 0.480, respectively). RECIST tumour response was analysed in a subset of patients (N = 39), showing that a RECIST SD was more likely in C1 (N = 12/14, 85.6%) compared to C2 (N = 18/25, 72%) group, while both RECIST PD and PR were more commonly detected in C2 [3/25 (12%) and 4/25 (16%), respectively] compared to C1 [0/14 (0%) and 1/14 (7.1%), respectively] group. Conclusions: In high-risk STS patients treated with preoperative chemotherapy within a RCT, CINSARC did not correlate with different DFS and OS. While this may well be due to a failure of this gene signature in this patient population, an alternative hypothesis is that preoperative chemotherapy may improve the prognosis of higher-risk patients. Clinical trial information: NCT01710176 .

Validation of the Complexity INdex in SARComas prognostic signature on formalin-fixed, paraffin-embedded, soft-tissue sarcomas

BackgroundPrediction of metastatic outcome in sarcomas is challenging for clinical management since they are aggressive and carry a high metastatic risk. A 67-gene expression signature, the Complexity INdex in SARComas (CINSARC), has been identified as a better prognostic factor than the reference pathological grade. Since it cannot be applied easily in standard laboratory practice, we assessed its prognostic value using nanoString on formalin-fixed, paraffin-embedded (FFPE) blocks to evaluate its potential in clinical routine practice and guided therapeutic management. MethodsA code set consisting of 67 probes derived from the 67 genes of the CINSARC signature was built and named NanoCind®. To compare the performance of RNA-seq and nanoString (NanoCind®), we used expressions of various sarcomas (n=124, frozen samples) using both techniques and compared predictive values based on CINSARC risk groups and clinical annotations. We also used nanoString on FFPE blocks (n=67) and matching frozen and FFPE samples (n=45) to compare their level of agreement. Metastasis-free survival and agreement values in classification groups were evaluated. ResultsCINSARC strongly predicted metastatic outcome using nanoString on frozen samples (HR=2.9, 95% CI: 1.23–6.82) with similar risk-group classifications (86%). While more than 50% of FFPE blocks were not analyzable by RNA-seq owing to poor RNA quality, all samples were analyzable with nanoString. When similar (risk-group) classifications were measured with frozen tumors (RNA-seq) compared with FFPE blocks (84% agreement), the CINSARC signature was still a predictive factor of metastatic outcome with nanoString on FFPE samples (HR=4.43, 95% CI: 1.25–15.72). ConclusionCINSARC is a material-independent prognostic signature for metastatic outcome in sarcomas and outperforms histological grade. Unlike RNA-seq, nanoString is not influenced by the poor quality of RNA extracted from FFPE blocks. The CINSARC signature can potentially be used in combination with nanoString (NanoCind®) in routine clinical practice on FFPE blocks to predict metastatic outcome.

RNA sequencing validation of the Complexity INdex in SARComas prognostic signature

BackgroundPrognosis of metastatic outcome in soft tissue sarcomas is an important clinical challenge since these tumours can be very aggressive (up to 50% of recurring events). A gene expression signature, Complexity INdex in SARComas (CINSARC), has been identified as a better prognostic factor compared to the current international grading system defined by the Fédération Nationale des Centres de Lutte Contre le Cancer. Since CINSARC has been established on frozen tumours analysed by microarrays, we were interested in evaluating its prognostic capacity using next generation sequencing (NGS) on formalin-fixed, paraffin-embedded (FFPE) blocks to better fit laboratory practices. MethodsMetastatic-free survivals (training/validation approach with independent datasets) and agreement values in classification groups were evaluated. Also, RNA degradation threshold has been established for FFPE blocks and differences in gene expression due to RNA degradation were measured. ResultsCINSARC remains a strong prognostic factor for metastatic outcome in both microarray and RNA-seq technologies (P < 0.05), with similar risk-group classifications (77%). We defined quality threshold to process degraded RNA extracted from FFPE blocks and measured similar classifications with frozen tumours (88%). ConclusionThese results demonstrate that CINSARC is a platform and material independent prognostic signature for metastatic outcome in various sarcomas. This result opens access to metastatic prognostication in sarcomas through NGS analysis on both frozen and FFPE tumours via the CINSARC signature.

Grading of soft tissue sarcomas: from histological to molecular assessment

Several histological grading systems for soft tissue sarcomas have been described since the early 1980s. Their main objective is to select patients for adjuvant chemotherapy. Two histological grading systems are used in daily practice, the National Cancer Institute (NCI) and the French Federation of Cancer Centers Sarcoma Group (FNCLCC) systems. They have been devised by combining histological parameters: number of mitoses per high-power field, the presence of necrosis, cellular and nuclear morphology and the degree of cellularity for the NCI grading; and tumour differentiation, mitotic index and extent of necrosis for the French system. Histological grading is far more appropriate to assess the risk of metastasis. However, several limitations prevent its use: grade cannot be applied to all histological types, its reproducibility is not perfect, a three-grade system generates an intermediate grade with undetermined prognosis, and finally the core needle biopsy, now widely used for the diagnosis of soft tissue sarcoma, is not the best sample to assess the grade. The development of molecular grading in addition to histological grading probably represents the next step. Molecular signatures based on quantitative evaluation of chromosomal complexity such as CINSARC (complexity index in sarcomas) appear as a strong independent predictive factor for metastasis in several types of sarcoma, and even in several other types of cancer. When they can be instituted in daily practice on formalin fixed, paraffin embedded material, molecular signatures will not only provide information on risk of metastasis, but also better understanding of cancer development, response or resistance to evaluated drugs, and potential targets for future treatments.

Abstract 19: Metastatic potential is determined early in synovial sarcoma development and reflected by tumor molecular features.

Abstract Introduction. Synovial sarcoma (SynSa) is an aggressive type of tumor, comprising approximately 10% of soft tissue sarcomas. Over half of SynSa patients develop metastases or local recurrence, but the molecular mechanism of aggressive SynSa outcome remains poorly characterized. Methods.Sixty five frozen tumor specimens from 54 SynSa patients [34 males; median age 37 years (range 5-86 years)] were subjected to aCGH and gene expression profiling. Examined set of tumor specimens included 16 primary tumors from untreated patients who did not develop metastasis/local recurrence (“SynSa1 group;" median follow-up 76 months), 26 primary tumors from untreated patients who developed metastases or local recurrence during follow-up (“SynSa2 group;" median follow-up 29 months), and 23 metastatic/recurrent SynSa tumors (“SynSa3 group;" median follow-up 46 months). For 8 patients primary tumor specimen was paired with metastatic/recurrent tumor specimens. Median follow-up for all patients was 40 months (range 3-218 months). Results. AURKA and KIF18A, which play important roles in various mitotic events, were the two most up-regulated genes in SynSa2 and SynSa3 groups compared to the SynSa1 group (corr p = 4.48e-6 and corr p = 8.65e-6, respectively). Moreover, we identified 125 genes differentially expressed between SynSa1 and SynSa2 groups (t test unpaired, corr p value cut-off = 0.05, fold change ≥ 2), 38 of which were common with recently published CINSARC (Complexity Index in Sarcomas) prognostic signature (Ref. 1, 2). Comparison of expression profiles between SynSa2 and SynSa3 groups did not show any significant differences. Analysis of genomic index (GI) based on aCGH profiles demonstrated that the SynSa1 group consisted of tumors with significantly less complex genomes compared to SynSa2 and SynSa3 groups (p = 0.021 and p = 0.020, respectively). The median GI in SynSa1, SynSa2 and SynSa3 groups was 9 (range 0-49), 16 (range 0-123) and 28 (range 0-130), respectively. Of note, there was no statistically significant difference in genome complexity between SynSa2 and SynSa3 groups, which suggests that progressive disease is not associated with accumulation of secondary genomic rearrangements/copy number changes. Conclusions. Primary SynSa tumors from patients who develop metastases or local recurrence share common molecular features with metastatic/recurrent SynSa. Presented data confirm that aggressive SynSa behavior is determined early in SynSa development and may be related to impaired mitotic regulatory mechanism. Citation Format: Joanna Przybyl, Raf Sciot, Agnieszka Wozniak, Patrick Schöffski, Vanessa Vanspauwen, Ignace Samson, Janusz A. Siedlecki, Piotr Rutkowski, Maria Debiec-Rychter. Metastatic potential is determined early in synovial sarcoma development and reflected by tumor molecular features. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 19. doi:10.1158/1538-7445.AM2013-19

Integrating Bioinformatics and Clinicopathological Research of Gastrointestinal Stromal Tumors: Identification of Aurora Kinase A as a Poor Risk Marker

For completely resected primary gastrointestinal stromal tumors (GISTs), mitotic rate, tumor size, and tumor location are important risk factors for recurrence. However, molecular markers for recurrence are still lacking. We reanalyzed GIST gene expression profile GSE8167 available from the Gene Expression Omnibus (GEO) and confirmed the prognostic influence of one selected gene, aurora kinase A (AURKA), in another cohort of 142 patients using immunohistochemistry (IHC). Thirty-two cases in GSE8167 were classified into two risk groups with distinct recurrence-free survival (RFS) and expression profiles using modified criteria of Miettinen et al. from the Armed Forces Institute of Pathology (AFIP-Miettinen). AURKA was among the 19 genes common to the top 50 features of the high-risk phenotype and a 67-gene signature called the complexity index in sarcomas. AURKA was significantly overexpressed in the high-risk group, and patients with high AURKA expression had significantly worse RFS than those with low expression. In the IHC-validated cohort, AURKA expression was significantly higher in nongastric tumors than in gastric tumors and was significantly correlated with AFIP-Miettinen risk group. Univariate analysis showed that RFS was significantly influenced by tumor size, mitotic count, AFIP-Miettinen risk group classification, and AURKA expression. However, only tumor size (P = 0.017), mitotic count (P = 0.007), and AURKA expression (P = 0.039) were identified as independent unfavorable prognostic factors for RFS in multivariate analysis. By integrating bioinformatics and clinicopathological studies, AURKA was identified as a marker for high-risk GIST.

Mitotic Checkpoints and Chromosome Instability Are Strong Predictors of Clinical Outcome in Gastrointestinal Stromal Tumors

The importance of KIT and PDGFRA mutations in the oncogenesis of gastrointestinal stromal tumors (GIST) is well established, but the genetic basis of GIST metastasis is poorly understood. We recently published a 67 gene expression prognostic signature related to genome complexity (CINSARC for Complexity INdex in SARComas) and asked whether it could predict outcome in GISTs. We carried out genome and expression profiling on 67 primary untreated GISTs. We show and validate here that it can predict metastasis in a new data set of 67 primary untreated GISTs. The gene whose expression was most strongly associated with metastasis was AURKA, but the AURKA locus was not amplified. Instead, we identified deletion of the p16 (CDKN2A) and retinoblastoma (RB1) genes as likely causal events leading to increased AURKA and CINSARC gene expression, to chromosome rearrangement, and ultimately to metastasis. On the basis of these findings, we established a Genomic Index that integrates the number and type of DNA copy number alterations. This index is a strong prognostic factor in GISTs. We show that CINSARC class, AURKA expression, and Genomic Index all outperform the Armed Forces Institute of Pathology (AFIP) grading system in determining the prognosis of patients with GISTs. Interestingly, these signatures can identify poor prognosis patients in the group classified as intermediate-risk by the AFIP classification. We propose that a high Genomic Index determined by comparative genomic hybridization from formalin-fixed, paraffin-embedded samples could be used to identify AFIP intermediate-risk patients who would benefit from imatinib therapy.

Grading sarcomas: histologic and molecular approaches

Histological grading, that is, grading based only on histological parameters, evaluates the degree of malignancy and the probability of distant metastasis for cancer. Several grading systems have been reported for sarcomas but the two most widely-used systems are the National Cancer Institute and the French systems. Histological grade is recognized as the most important prognostic factor for soft tissue sarcomas. However, this approach presents several limitations such as moderate reproducibility, existence of an intermediate grade and the current nearly universal use of core needle biopsies. A molecular grading system which significantly outperforms histological grading has been recently described for sarcomas. It is based on the expression profile of 67 genes related to chromosome complexity and mitosis management (CINSARC for Complexity INdex in SARComas). In this article we discuss both approaches as well as the future of grading, regarding the respective values of histological and molecular grading systems, validation, extension, refinement and practical use of the molecular grading.

Complexity index in sarcomas (CINSARC) profile for predicting clinical outcome in cancer patients

Complexity index in sarcomas (CINSARC) profile for predicting clinical outcome in cancer patients

Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity

Sarcomas are heterogeneous and aggressive mesenchymal tumors. Histological grading has so far been the best predictor for metastasis-free survival, but it has several limitations, such as moderate reproducibility and poor prognostic value for some histological types. To improve patient grading, we performed genomic and expression profiling in a training set of 183 sarcomas and established a prognostic gene expression signature, complexity index in sarcomas (CINSARC), composed of 67 genes related to mitosis and chromosome management. In a multivariate analysis, CINSARC predicts metastasis outcome in the training set and in an independent 127 sarcomas validation set. It is superior to the Fédération Francaise des Centres de Lutte Contre le Cancer grading system in determining metastatic outcome for sarcoma patients. Furthermore, it also predicts outcome for gastrointestinal stromal tumors (GISTs), breast carcinomas and lymphomas. Application of the signature will permit more selective use of adjuvant therapies for people with sarcomas, leading to decreased iatrogenic morbidity and improved outcomes for such individuals.