Prognostic gene expression signatures in sarcoma: finding clarity in complexity
Authors: G.W. Charville, A.J. Lazar
Journal: Annals of Oncology (2018)

Adult soft tissue sarcomas (STS) encompass a heterogeneous subset of more than 50 malignant neoplasms united by their mesenchymal differentiation. These tumors exhibit diversity not only in terms of their underlying molecular pathogenesis but also in terms of their clinical behavior, which ranges from locally aggressive proliferations, that are cured by local excision to recurrent, widely metastatic, and even fatal tumors. Because the clinical potential of sarcomas very often dictates their treatment, predicting likelihood of progression at the time of initial biopsy or resection is essential. Currently, prognostication in sarcoma is achieved by morphologic assessment of tumor grade using the Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) criteria. The FNCLCC system incorporates the trio of differentiation, mitotic index, and tumor necrosis to subdivide sarcomas into three tiers, each showing a distinct risk for metastatic disease and death. Histologic type, resection margin status, and staging factors such as size, site, and extent of spread also inform prognosis. Although it remains, more than two decades after its inception, the ‘gold standard’ of prognostication in adult STS, the FNCLCC system is not without limitations. Because the parameters are somewhat subjective, reproducibility is imperfect [1.Coindre J.M. Trojani M. Contesso G. et al.Reproducibility of a histopathologic grading system for adult soft tissue sarcoma.Cancer. 1986; 58: 306-309Crossref PubMed Scopus (382) Google Scholar]. Moreover, small biopsies may not adequately represent necrosis or increased proliferative activity critical to accurate grading. Finally, FNCLCC grade is of greater predictive value in some histologic subtypes than others [2.Coindre J-M. Grading of soft tissue sarcomas: review and update.Arch Pathol Lab Med. 2006; 130: 1448-1453Crossref PubMed Google Scholar]. Given these limitations, Chibon et al. [3.Chibon F. Lagarde P. Salas S. et al.Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.Nat Med. 2010; 16: 781-787Crossref PubMed Scopus (322) Google Scholar] previously established a prognostic gene expression signature for STS derived from microarray-based analyses of 183 tumors. This ‘complexity index in sarcomas’ (CINSARC) consists of 67 genes identified using a selection algorithm that focused on genetic loci exhibiting differential expression in sample comparisons related to: (i) frequency of chromosomal imbalances, (ii) FNCLCC grade, and (iii) expression of a separate chromosome instability signature [4.Carter S.L. Eklund A.C. Kohane I.S. et al.A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers.Nat Genet. 2006; 38: 1043-1048Crossref PubMed Scopus (815) Google Scholar]. In an initial validation cohort of 127 sarcomas, CINSARC outperformed the FNCLCC system in predicting eventual metastasis. Since its development, CINSARC has been shown to be broadly applicable [3.Chibon F. Lagarde P. Salas S. et al.Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.Nat Med. 2010; 16: 781-787Crossref PubMed Scopus (322) Google Scholar, 5.Lesluyes T. Delespaul L. Coindre J.-M. et al.The CINSARC signature as a prognostic marker for clinical outcome in multiple neoplasms.Sci Rep. 2017; 7: 5480Crossref PubMed Scopus (23) Google Scholar], even demonstrating utility in tumors characterized by relatively simple oncogenic driver events such as synovial sarcoma and gastrointestinal stromal tumor [6.Lagarde P. Przybyl J. Brulard C. et al.Chromosome instability accounts for reverse metastatic outcomes of pediatric and adult synovial sarcomas.J Clin Oncol. 2013; 31: 608-615Crossref PubMed Scopus (117) Google Scholar, 7.Lagarde P. Pérot G. Kauffmann A. et al.Mitotic checkpoints and chromosome instability are strong predictors of clinical outcome in gastrointestinal stromal tumors.Clin Cancer Res. 2012; 18: 826-838Crossref PubMed Scopus (98) Google Scholar]. However, the use of CINSARC in routine practice has been limited, at least in part, by the damaging effects of formalin-fixed paraffin-embedded (FFPE) tissue processing on target mRNA. Storage conditions, time to and of fixation, duration of the storage interval, and embedding conditions have each been shown to contribute to RNA degradation in FFPE samples [8.von Ahlfen S. Missel A. Bendrat K. et al.Determinants of RNA Quality from FFPE Samples.PLoS One. 2007; 2: e1261Crossref PubMed Scopus (277) Google Scholar]. To overcome these hurdles, Le Guellec et al. [9.Le Guellec S. Lesluyes T. Sarot E. et al.Validation of the Complexity INdex in SARComas prognostic signature on formalin-fixed, paraffin-embedded, soft-tissue sarcomas.Ann Oncol. 2018; 29: 1828-1835Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar] report in this issue of Annals of Oncology a methodologic development enabling application of CINSARC to FFPE tissues using nanoString nCounter technology. With nCounter, single-stranded synthetic DNA oligonucleotide probes, each bearing a unique fluorescent barcode, are designed to complement specific target mRNA transcripts [10.Geiss G.K. Bumgarner R.E. Birditt B. et al.Direct multiplexed measurement of gene expression with color-coded probe pairs.Nat Biotechnol. 2008; 26: 317-325Crossref PubMed Scopus (1551) Google Scholar]. After hybridization and immobilization of target-probe pairs, imaging allows direct and robust digital quantification of mRNA abundance, bypassing the need for cDNA synthesis and amplification required by the most common array- or sequencing-based methods for gene expression analysis. Le Guellec et al. validated the nCounter approach by correlating raw mRNA counts for 75 target genes (67 CINSARC genes and 8 housekeeping genes) between two independent hybridizations of the same fresh-frozen sample. These mRNA counts fit to a linear regression across a dynamic range of 100–1000 ng of input RNA. The authors then used nCounter to analyze expression of the 67 CINSARC genes in a cohort of 124 fresh-frozen sarcoma samples with available RNA-seq expression data. The nCounter approach similarly classified 107 of 124 sarcomas into prognostic groups with low versus high risk for metastatic disease. More remarkably, the hazard ratio for metastasis-free survival was significant between the two groups stratified by nCounter [hazard ratio (HR) = 2.9], but not by RNA-seq (HR = 1.69). How did the nCounter approach fare in tests of FFPE tissue? Using a cohort of 45 sarcomas with paired fresh-frozen and FFPE samples, the authors found that expression values of CINSARC genes derived by the nCounter method in fresh-frozen versus FFPE tissue correlated about as well as expression values from nCounter on FFPE tissue versus RNA-seq on fresh-frozen tissue. Importantly, the nCounter approach on FFPE yielded the same CINSARC prognostic classification as RNA-seq on fresh-frozen tissue in 38 of 45 cases. The HR for metastasis-free survival between high- and low-risk CINSARC groups classified by nCounter data (HR = 4.43) was again significant and seemed to appropriately predict risk even in a subset of 20 biopsy samples. As a further test of the nCounter-based classification, Le Guellec et al. analyzed nCounter data in parallel with RNA-seq data for a separate validation cohort of 141 cases, again with paired fresh-frozen and FFPE material. Although both nCounter- and RNA-seq-derived expression data enabled CINSARC classification into two groups with marked differences in their predilection for metastasis-free survival, the authors point out that the nCounter data may be ‘more discriminating’ insofar as the HR is greater than that obtained from RNA-seq data. Intriguingly, while CINSARC classification of nCounter-derived data separated sarcomas into prognostically distinct groups, the FNCLCC system did not effectively discriminate risk in a comparison of grade 3 versus grade 1/2 [11.Trojani M. Contesso G. Coindre J.M. et al.Soft-tissue sarcomas of adults; study of pathological prognostic variables and definition of a histopathological grading system.Int J Cancer. 1984; 33: 37e42Crossref Scopus (954) Google Scholar] subgroups from the 116 cases for which a histologic grade was available. In a separate feat, nCounter expression data split the confoundingly nebulous cohort of FNCLCC grade 2 tumors into two prognostic groups (basically high and low risk), suggesting that this approach may be of particular value in clinical decision-making, where assignment to intermediate-risk should be minimized. While the CINSARC signature as evaluated by nCounter has proven itself to be widely applicable, one wonders whether, as in the FNCLCC system, the predictive value is better for certain histologic subtypes than others. Focused analyses of gene expression in specific subtypes might reveal opportunities for refined signatures that are tailored to unique histologic diagnoses. Along the same lines, although CINSARC is clearly effective for prognostication, further investigation of the contribution of individual genes to the estimation of disease outcome may provide insight into the biology of STS, and even yield opportunities for consolidation or enhancement of the predictive power of the expression signature. Application of machine learning approaches would presumably allow for unbiased evolution of existing gene signatures. Integration of gene expression data with complementary genetic and epigenetic (i.e. DNA methylation and histone modification) profiles, which are increasingly obtainable from FFPE tissues, are likely to further inform both classification and risk assessment in sarcoma. The results of prospective studies alluded to by Le Guellec et al., aiming to incorporate the CINSARC signature in clinical decision-making for sarcoma treatment, will be particularly valuable in guiding the integration of these exciting findings into daily practice. None declared.