The number of druggable tumor-specific molecular aberrations has grown substantially in the past decade, with a significant survival benefit obtained from biomarker matching therapies in several cancer types. Molecular pathology has therefore become fundamental not only to inform on tumor diagnosis and prognosis but also to drive therapeutic decisions in daily practice. The introduction of next-generation sequencing technologies and the rising number of large-scale tumor molecular profiling programs across institutions worldwide have revolutionized the field of precision oncology. As comprehensive genomic analyses become increasingly available in both clinical and research settings, healthcare professionals are faced with the complex tasks of result interpretation and translation. This review summarizes the current and upcoming approaches to implement precision cancer medicine, highlighting the challenges and potential solutions to facilitate the interpretation and to maximize the clinical utility of molecular profiling results. We describe novel molecular characterization strategies beyond tumor DNA sequencing, such as transcriptomics, immunophenotyping, epigenetic profiling, and single-cell analyses. We also review current and potential applications of liquid biopsies to evaluate blood-based biomarkers, such as circulating tumor cells and circulating nucleic acids. Last, lessons learned from the existing limitations of genotype-derived therapies provide insights into ways to expand precision medicine beyond genomics.

Standard treatment in head and neck squamous cell carcinoma (HNSCC) is limited currently with decisions being made primarily based on tumor location, histology, and stage. The role of the human papillomavirus in risk stratification is actively under clinical trial evaluations. The molecular complexity and intratumoral heterogeneity of the disease are not actively integrated into management decisions of HNSCC, despite a growing body of knowledge in these areas. The advent of the genomic era has delivered vast amounts of information regarding different cancer subtypes and is providing new therapeutic targets, which can potentially be elucidated using next-generation sequencing and other modern technologies. The task ahead is to expand beyond the existent armamentarium by exploiting beyond the genome and perform integrative analysis using innovative systems biology methods, with the goal to deliver effective precision medicine-based theragnostic options in HNSCC.

Cancer is a genetic disease resulting from germline or somatic genetic aberrations. Rapid progress in the field of genomics in recent years is allowing for increased characterization and understanding of the various forms of the disease. The Ontario-wide Cancer Targeted Nucleic Acid Evaluation (octane) clinical trial, open at cancer centres across Ontario, aims to increase access to genomic sequencing of tumours and to facilitate the collection of clinical data related to enrolled patients and their clinical outcomes. The study is designed to assess the clinical utility of next-generation sequencing (ngs) in cancer patient care, including enhancement of treatment options available to patients. A core aim of the study is to encourage collaboration between cancer hospitals within Ontario while also increasing international collaboration in terms of sharing the newly generated data. The single-payer provincial health care system in Ontario provides a unique opportunity to develop a province-wide registry of ngs testing and a repository of genomically characterized, clinically annotated samples. It also provides an important opportunity to use province-wide real-world data to evaluate outcomes and the cost of ngs for patients with advanced cancer.    The octane study is attempting to translate knowledge to help deliver precision oncology in a Canadian environment. In this article, we discuss the background to the study and its implementation, current status, and future directions.

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6081 Background: Treatment selection based on actionable alterations (AAs) is an appealing strategy for pts with R/M SGT. The GEMS-001 study (NCT02069730) at Princess Margaret Cancer Centre (PM) and the Vall D´Hebron Institute of Oncology (VHIO) pre-screening program facilitate the identification of AAs for R/M SGT pts and treatment selection. Methods: We analyzed R/M SGT treated at PM and VHIO from 2015 to 2020. Clinicopathological features, molecular alterations and treatment modalities were correlated with outcomes. The primary endpoint was overall response rate (ORR) by RECIST 1.1. Clinical benefit rate (CBR) was defined by pts with partial response or stable disease ≥4 months. Clinical actionability of multigene panel testing (NGS) and immunohistochemistry (IHC) were assessed as per institutional molecular tumor boards or investigators. Pts were opportunistically matched to available therapies from each center. Results: In total 206 pts were enrolled. On IHC, HER2 overexpression was present in 9%, Androgen Receptor (AR) 33%, Estrogen/Progesterone Receptor (ER/PR) 11% and ALK overexpression 0%. On NGS, PIK3CA mutation (mut) was in 9%, NTRK fusion 6%, NOTCH1-3 mut 5%, HRAS mut 6%, ERBB2/3 alterations (alt) 4% and FGFR1-4 alt 3%. Up to 92 pts (45%) displayed at least 1 AA and 36 pts (18%) had ≥2 AAs. A total of 60 pts (29%) were matched to AAs. Of those matched, median age was 60 years (range 33-84), M:F 21:39, 95% ECOG≤1 with a median number of prior treatment lines 0 (range 0-3), and their AAs included 26 AR, 9 HER2 or ERBB2 overexpression, 9 PIK3CA mut, 3 NTRK fusion, 3 FGFR1-3 alt and 10 other AAs (2 ER/PR overexpression, 2 EGFR mut, 1 c-kit mut, 1 BAP1 mut, 1 Non-V600 BRAF mut, 1 CDKN2A mut, 1 CHEK2 mut and 1 PTCH1 mut). Overall, ORR was 27% for the matched population. See table for outcomes. Conclusions: In our cohort, almost one third of the population received therapies matched to AAs. Our results suggest that targeted therapies have promising activity in pts with R/M SGT supporting comprehensive molecular and IHC profiling in treatment determination.[Table: see text]

11040 Background: RIS is a rare subset of soft tissue sarcoma (STS) with poor prognosis and limited treatment options. We hypothesize that subsets of STS that carry genomic complexity, such as RIS, will have a neoepitope and immune signature that predicts response to immunotherapy as these mutations act as strong antigenic targets for eliciting immune response. Methods: Cases of RIS were identified from an institutional database. Formalin fixed paraffin embedded (FFPE) samples were stained for PD-1, PD-L1, CD3, CD4, CD8. Immune scoring was performed. Tumor-infiltrating lymphocytes (TILs) were assessed using a 4-tiered scale: 0 (no lymphocytes); 1 (1-10/HPF); 2 (11-50/HPF), 3 (51-100/HPF); 4 ( > 100/HPF). TIL staining with PD-1 and PD-L1 was also scored whereby the overall percentage of positive cells on the entire slide was quantified. Tumor DNA was extracted from FFPE samples and underwent whole exome sequencing (WES). Results: FFPE samples from 20 cases of RIS were selected for analysis. PD-1 and PD-L1 expression (threshold set at ≥ 1% positive cells) was seen in 35% and 45% of the cases respectively. CD3+, CD4+, CD8+ T cell infiltration (threshold set ≥ 11 cells /HPF) was seen in 45%, 15% and 20% of cases respectively. 12 exomes of unpaired RIS samples were successfully sequenced. The most common histologies were angiosarcoma (n = 3), undifferentiated spindle cell sarcoma (n = 3), de-differentiated liposarcoma (n = 2) and radiation induced spindle cell sarcoma (n = 2). Provisional analysis did not reveal any pattern to the relative mutational burden between the RIS’s. There does however seem to be relatively higher rate of mutation than that seen in other cancer subtypes. Half the samples had at least one pathogenic or likely pathogenic variant. Different HRAS mutations were seen in two samples (sarcoma NOS and angiosarcoma) and FGFR4 mutation was present in two samples, both spindle cell sarcomas. Conclusions: To our knowledge this is the first study to investigate the immune profile in RIS. Up to 45% of these tumors were positive for PD1/PDL1 expression, as well as presence of tumour infiltrating lymphocytes. Results from WES demonstrate that RIS may benefit from immunotherapy due to a relatively higher mutational burden.

Introduction: The anti-PD-1 immune checkpoint inhibitor nivolumab is currently approved for the treatment of patients with metastatic renal cell carcinoma (mRCC); approximately 25% of patients respond. We hypothesized that we could identify a biomarker of response using radiomics to train a machine learning classifier to predict nivolumab response outcomes. Methods: Patients with mRCC of different histologies treated with nivolumab in a single institution between 2013 and 2017 were retrospectively identified. Patients were labelled as responders (complete response [CR]/particle response [PR]/durable stable disease [SD]) or non-responders based on investigator tumor assessment using RECIST 1.1 criteria. For each patient, lesions were contoured from pre-treatment and first post-treatment computed tomography (CT) scans. This information was used to train a radial basis function support vector machine classifier to learn a prediction rule to distinguish responders from non-responders. The classifier was internally validated by a 10-fold nested cross-validation. Results: Thirty-seven patients were identified; 27 (73%) met the inclusion criteria. One hundred and four lesions were contoured from these 27 patients. The median patient age was 56 years, 78% were male, 89% had clear-cell histology, 89% had prior nephrectomy, and 89% had prior systemic therapy. There were 19 responders vs. eight non-responders. The lesions selected were lymph nodes (60%), lung metastases (23%), and renal/adrenal metastases (17%). For the classifier trained on the baseline CT scans, 69% accuracy was achieved. For the classifier trained on the first post-treatment CT scans, 66% accuracy was achieved. Conclusions: The set of radiomic signatures was found to have limited ability to discriminate nivolumab responders from non-responders. The use of novel texture features (two-point correlation measure, two-point cluster measure, and minimum spanning tree measure) did not improve performance.