Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas

Abstract: Soft tissue sarcomas (STSs) are a heterogeneous group of rare tumors. Although constituting only 1% of all human malignancies, STSs represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. Over 100 histologic subtypes have been characterized to date (occurring predominantly in the trunk, extremity, and retroperitoneum), and many more are being discovered due to molecular profiling. STS mortality remains high, despite adjuvant chemotherapy. New prognostic stratification markers are needed to help identify patients at risk of recurrence and possibly apply more intensive or novel treatments. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the most relevant cellular, molecular and metabolic biomarkers for STS, and highlight advances in STS-related biomarker research.

Abstract: Metabolic rewiring offers novel therapeutic opportunities in cancer. Until recently, there was scant information regarding soft tissue sarcomas, due to their heterogeneous tissue origin, histological definition and underlying genetic history. Novel large-scale genomic and metabolomics approaches are now helping stratify their physiopathology. In this review, we show how various genetic alterations skew activation pathways and orient metabolic rewiring in sarcomas. We provide an update on the contribution of newly described mechanisms of metabolic regulation. We underscore mechanisms that are relevant to sarcomagenesis or shared with other cancers. We then discuss how diverse metabolic landscapes condition the tumor microenvironment, anti-sarcoma immune responses and prognosis. Finally, we review current attempts to control sarcoma growth using metabolite-targeting drugs.

Abstract: Soft tissue sarcomas (STS), a group of rare malignant tumours with high tissue heterogeneity, still lack effective clinical stratification and prognostic models. Therefore, we conducted this study to establish a reliable prognostic gene signature. Using 189 STS patients' data from The Cancer Genome Atlas database, a four-gene signature including DHRS3, JRK, TARDBP and TTC3 was established. A risk score based on this gene signature was able to divide STS patients into a low-risk and a high-risk group. The latter had significantly worse overall survival (OS) and relapse free survival (RFS), and Cox regression analyses showed that the risk score is an independent prognostic factor. Nomograms containing the four-gene signature have also been established and have been verified through calibration curves. In addition, the predictive ability of this four-gene signature for STS metastasis free survival was verified in an independent cohort (309 STS patients from the Gene Expression Omnibus database). Finally, Gene Set Enrichment Analysis indicated that the four-gene signature may be related to some pathways associated with tumorigenesis, growth, and metastasis. In conclusion, our study establishes a novel four-gene signature and clinically feasible nomograms to predict the OS and RFS. This can help personalized treatment decisions, long-term patient management, and possible future development of targeted therapy.

Abstract: Background: Collagen type 1 alpha 1 chain (COL1A1) is an extracellular matrix protein comprising two alpha 1 chains and one alpha 2 chain. Our previous study identified that COL1A1 is the key gene during the development and progression of lung adenocarcinoma by multi-omics analysis. However, the clinical significance of COL1A1 expression in lung cancer samples remains largely unknown. Here, we aimed to evaluate the level of COL1A1 in lung cancer samples and correlate its level with the clinical outcome. Methods: COL1A1 gene expression in lung cancer samples was analyzed using the Oncomine database (www.oncomine.org). A total of 308 lung cancer samples (208 formalin-fixed paraffin-embedded tissues and 100 blood samples) were assessed for protein expression of COL1A1. Immunohistochemistry staining and enzyme-linked immunosorbent assay were used to detect COL1A1 expression in tissues and serum, respectively. Results: We identified an elevation of COL1A1 in mRNA level and gene amplification in lung cancer tissues compared with normal lung tissues. High COL1A1 expression was observed in lung cancer tissues and serum (P < 0.05), it was significantly correlated with the peripheral type tumor, the larger diameter of the tumor, the occurrence of lymph node metastases and distant metastases, a higher TNM stage, and smoking (P < 0.05). High COL1A1 expression was associated with poor progression-free survival (PFS) and chemoresistance in lung cancer patients (P < 0.05). Multivariable Cox-regression analysis showed that COL1A1 expression was an independent prognostic factor (P < 0.05). Furthermore, the area under the receiver operating characteristic (AUC) curve was 0.909 for the combined COL1A1 and carcinoembryonic antigen (CEA) measurement. Conclusion: Our findings revealed that COL1A1 could be used as a novel diagnostic, prognostic, and chemoresistance biomarker of human lung cancer, and these results provide a potential therapeutic strategy for lung cancer patients.

Abstract: Soft tissue sarcomas (STSs) are rare mesenchymal tumors. With more than 80 histological subtypes of STSs, data regarding novel biomarkers of strong prognostic and therapeutic value are very limited. To date, the most important prognostic factor is the tumor grade, and approximately 50% of patients that are diagnosed with high-grade STSs die of metastatic disease within five years. Systemic chemotherapy represents the mainstay of metastatic STSs treatment for decades but induces response in only 15–35% of the patients, irrespective of the histological subtype. In the era of immunotherapy, deciphering the immune cell signatures within the STSs tumors may discriminate immunotherapy responders from non-responders and different immunotherapeutic approaches could be combined based on the predominant cell subpopulations infiltrating the STS tumors. Furthermore, understanding the immune diversity of the STS tumor microenvironment (TME) in different histological subtypes may provide a rationale for stratifying patients according to the TME immune parameters. In this review, we introduce the most important immune cell types infiltrating the STSs tumors and discuss different immunotherapies, as well as promising clinical trials, that would target these immune cells to enhance the antitumor immune responses and improve the prognosis of metastatic STSs patients.

Abstract: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is de- scribed that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be inter- preted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly charac- terized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

Abstract: E. Senkus1, S. Kyriakides2, F. Penault-Llorca3,4, P. Poortmans5, A. Thompson6, S. Zackrisson7 & F. Cardoso8,9, on behalf of the ESMO Guidelines Working Group* Department of Oncology and Radiotherapy, Medical University of Gdansk, Gdansk, Poland; Europa Donna Cyprus, Nicosia, Cyprus; Department of Pathology, Centre Jean Perrin, Clermont-Ferrand; EA 4677 Universite d’Auvergne, Clermont-Ferrand, France; Institute Verbeeten, Tilburg, The Netherlands; Dundee Cancer Centre, University of Dundee, Dundee, UK; Diagnostic Radiology, Lund University, Malmo, Sweden; European School of Oncology, Milan, Italy; Breast Cancer Unit, Champalimaud Centre Center, Lisbon, Portugal

Abstract: Background: Histologic grade in breast cancer provides clinically important prognostic information. However, 30% – 60% of tumors are classifi ed as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profi les of breast cancers and whether such profi les could be used to improve histologic grading. Methods: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identifi ed differentially expressed genes in a training set of 64 estrogen receptor (ER) – positive tumor samples by comparing expression profi les between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to defi ne the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan – Meier analysis. All statistical tests were two-sided. Results: We identifi ed 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1 – 3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confi dence interval = 2.25 to 5.78; P <.001, log-rank test). Conclusions: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value. [J Natl Cancer Inst 2006;98:262 – 72]

Abstract: Experimental tumors contain a significant fraction of microregions that are chronically or transiently hypoxic. Experimental evidence showing that hypoxia (and subsequent reoxyenation) may have a profound impact on malignant progression and on responsiveness to therapy is growing. The clinical relevance of tumor oxygenation in human solid malignancies is under investigation. We have developed and validated a clinically applicable method for measurement of tumor oxygenation in locally advanced cancer of the uterine cervix using a computerized polarographic electrode system. Applying this procedure in patients with cervical cancers ≥3 cm in diameter, who gave informed consent, we have been studying the clinical relevance of tumor oxygenation prospectively since 1989. As of June 1995, 103 patients with advanced cancers of the uterine cervix [Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stages Ib, bulky ( n = 13), IIa and IIb ( n = 51), IIIa and IIIb ( n = 34), and IVa and IVb ( n = 5)] had entered the study. Fifty % of the patients had carcinomas with median pO 2 readings hypoxic tumors. Tumor oxygenation was found to be independent of various patient demographics and also of pretreatment tumor characteristics, such as clinical tumor stage and size, histological type, and differentiation. However, histopathological examination of the surgical specimens following radical tumor resection in 47 patients showed that low-pO 2 tumors exhibited larger tumor extensions and more frequent (occult) parametrial spread, as well as lymph-vascular space involvement, compared to well-oxygenated tumors of similar clinical stage and size. Forty-two patients completing primary radiation therapy and 47 patients who underwent radical surgery were analyzed for treatment outcome after a median observation period of 28 months (range, 3–76 months). Patients with hypoxic tumors had significantly worse disease-free and overall survival probabilities compared to patients with nonhypoxic tumors. Cox regession analysis identified tumor oxygenation and FIGO stage as the most important independent prognostic factors. The poorer outcome of the patients with hypoxic tumors was mainly due to locoregional failures with and without distant metastases, irrespective of whether surgery or radiation was applied as primary treatment. Tumor oxygenation as measured with a standardized polarographic method proved to be a powerful new pretherapeutic prognostic parameter providing important information on malignant progression in terms of extracervical tumor spread and radioresistance in advanced cervical cancers.

Abstract: This study was performed to explore the relationship between tumor oxygenation and treatment outcome in human soft tissue sarcoma. Twenty-two patients with nonmestastatic, high-grade, soft tissue sarcomas underwent preoperative irradiation and hyperthermia and pretreatment measurement of tumor oxygenation. The 18-month actuarial disease-free survival was 70% for patients with tumor median oxygen pressure (pO2) values of >10 mm Hg but only 35% for those with median pO2 values of <10 mm Hg (P=0.01). There were eight treatment failures; the first site of recurrence was lung in all patients. Median pO2 was 7.5 mm Hg for metastasizing tumors versus 20 mm Hg for nonmetastasizing tumors (P=0.03). Potential mechanisms and implications for clinical trial design are discussed.