Abstract 1628: The molecular landscape of sarcoma can inform selection of personalized chemotherapy
Authors: Thyparambil Sheeno P. , Sellappan Shankar , Yan Dongyao , Cecchi Fabiola , Italiano Antoine , Hembrough Todd A. 
Published: August 2018

Background: Chemotherapy represents the cornerstone of treatment for patients with advanced sarcomas. Anthracyclines are the first line of treatment; however, other agents such as gemcitabine, topotecan, taxanes and temozolomide have shown clinical activity in sarcoma patients. While no biomarker for chemotherapy has been approved for clinical use, a growing body of literature has identified tumor molecular characteristics predictive of response or resistance to chemotherapy. These include expression of the proteins ERCC1 (platinum), TUBB3 (taxane), TOP2A (anthracyclines), TOP1 (irinotecan, topotecan), hENT1/RRM1 (gemcitabine) and MGMT (temozolomide). Our goal was to assess the landscape of chemotherapy biomarkers in several sarcoma subtypes to identify potentially beneficial treatment regimens.

Methods: Formalin-fixed, paraffin-embedded tumor tissues from clinical samples of sarcoma representing 5 subtypes were microdissected and assayed with the GPS Cancer molecular test. The test combines whole-genome sequencing, RNA-seq, and proteomic expression analysis of 30 biomarker proteins using mass spectrometry.

Results: Seventy-five sarcoma samples were characterized (Table 1). Expression of protein biomarkers varied by sarcoma subtype. Of interest, approximately two-thirds of leiomyosarcomas lacked resistance markers for platinum (ERCC1) and taxanes (TUBB3). Of osteosarcomas, 93% expressed the response marker for gemcitabine (hENT1), while only 14% expressed the protein marker of gemcitabine resistance (RRM1). The vast majority of Ewing's sarcomas expressed MGMT, a marker of temozolomide resistance.

Conclusions: In clinical sarcoma samples, proteomic analysis can identify distinct patterns of expression that are predictive of response or resistance to chemotherapies. Additional analysis is in progress; correlation between expression of chemotherapeutic biomarkers and clinical outcomes in a subset of sarcoma patients will be presented.

Table 1. Proportions of sarcoma patients (N=75) with tumor expression of chemotherapeutic biomarker proteinsMarkers of response (agent)Markers of resistance (agent)Sarcoma subtypeTOP1(topotecan, irinotecan)TOP2A(doxorubicin)hENT1(gemcitabine)ERCC1(platinum)TUBB3(taxane)RRM1(gemcitabine)MGMT(temozolomide)Leiomyosarcoma (n=25)4133228321658Liposarcoma (n=13)1504654621667Ewing's sarcoma (n=12)3383383504288Osteosarcoma (n=14)779346571467Rhabdomyosarcoma (n=11)36278264456488Tumor expression is defined as quantitated protein above the threshold determined to be indicative of clinical response/resistance. The thresholds (in attomoles per microgram of total tumor protein) are as follows: TOP1: 1340, TOP2A: 1570, hENT1: 100, ERCC1: 75, TUBB3: 850, RRM1: 700, MGMT: 200.

Citation Format: Sheeno P. Thyparambil, Shankar Sellappan, Dongyao Yan, Fabiola Cecchi, Antoine Italiano, Todd A. Hembrough. The molecular landscape of sarcoma can inform selection of personalized chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1628.