Personalized therapy provides the best outcome of cancer care and its implementation in the clinic has been greatly facilitated by recent convergence of enormous progress in basic cancer research, rapid advancement of new tumor profiling technologies, and an expanding compendium of targeted cancer therapeutics.

We developed a personalized cancer therapy (PCT) program in a clinical setting, using an integrative genomics approach to fully characterize the complexity of each tumor. We carried out whole exome sequencing (WES) and single-nucleotide polymorphism (SNP) microarray genotyping on DNA from tumor and patient-matched normal specimens, as well as RNA sequencing (RNA-Seq) on available frozen specimens, to identify somatic (tumor-specific) mutations, copy number alterations (CNAs), gene expression changes, gene fusions, and also germline variants. To provide high sensitivity in known cancer mutation hotspots, Ion AmpliSeq Cancer Hotspot Panel v2 (CHPv2) was also employed. We integrated the resulting data with cancer knowledge bases and developed a specific workflow for each cancer type to improve interpretation of genomic data.

We returned genomics findings to 46 patients and their physicians describing somatic alterations and predicting drug response, toxicity, and prognosis. Mean 17.3 cancer-relevant somatic mutations per patient were identified, 13.3-fold, 6.9-fold, and 4.7-fold more than could have been detected using CHPv2, Oncomine Cancer Panel (OCP), and FoundationOne, respectively. Our approach delineated the underlying genetic drivers at the pathway level and provided meaningful predictions of therapeutic efficacy and toxicity. Actionable alterations were found in 91 % of patients (mean 4.9 per patient, including somatic mutations, copy number alterations, gene expression alterations, and germline variants), a 7.5-fold, 2.0-fold, and 1.9-fold increase over what could have been uncovered by CHPv2, OCP, and FoundationOne, respectively. The findings altered the course of treatment in four cases.

These results show that a comprehensive, integrative genomic approach as outlined above significantly enhanced genomics-based PCT strategies.

Cancer Genomics Personalized medicine Clinical application

Personalizing cancer therapy is a well-established concept, given that every patient harbors a unique constellation of variants that influence the risk, onset, and progression of their disease. For every specific type and stage of cancer, clinical manifestations differ between individuals, showing variations in tumor behavior and progression as well as variations in responses to a given treatment regimen, largely driven by the unique genomic (DNA, RNA, and epigenetic) makeup of the individual tumors. Developing a personalized therapy strategy to ensure an optimal outcome for individual cancer patients is possible given the dramatic progress in basic cancer research at the molecular and cellular levels, the rapid advancement of new technologies that enable fast and cost-effective comprehensive characterizations of tumors at the molecular level, and an expanding compendium of targeted cancer therapeutics.

Many FDA-approved targeted cancer drugs have pharmacogenomic labels that include biomarkers predictive of drug response, in addition to germline variants that are associated with drug metabolism or may impact treatment response [1]. In cases where a patient tests positive for a specific biomarker that indicates an FDA-approved therapy for the given tumor type, developing a personalized therapeutic strategy is straightforward. For example, crizotinib is indicated as a treatment for non-small cell lung cancer tumors harboring ALK gene translocations and vemurafenib is indicated as a treatment for metastatic melanoma tumors harboring the BRAF p.V600E mutation. However, for the vast majority of tumor types and available therapeutics, a biomarker-therapeutic link is not straightforward.

The rapid development of next-generation sequencing (NGS) technologies as a high-throughput, low-cost way of generating whole genome (WGS) and whole exome (WES) sequence data has enabled a new paradigm in precision medicine for oncology. Large-scale NGS studies over the last several years have uncovered novel oncogenic drivers and started to depict genetic landscapes across a number of cancer types [2, 3, 4]. This research advanced the understanding of the underlying genetics of cancer and enabled acceleration of personalized cancer therapy (PCT) [5]. Retrospective analyses of archived tumor samples using targeted gene panels or WES have been reported [6, 7, 8, 9]. Actionable mutations were identified in 80–90 % of the tumor samples in these studies. A number of prospective studies have also demonstrated the clinical utility of NGS-based cancer genetic testing. One pilot study generated low-depth WGS, WES, and RNA sequencing (RNA-Seq) data on four patients with advanced cancers, and these genomic data for two patients were reviewed by a molecular tumor board to deliver clinical recommendations [10]. WES of formalin-fixed, paraffin-embedded (FFPE) tumor samples has been recently reported suggesting that comprehensive exome sequencing provides a complete spectrum of clinically relevant genetic alterations, as demonstrated in one case where previously undetected genetic alterations led to clinical trial enrollment and objective clinical response [11]. WES of tumor-normal pairs from a 97-patient cohort of metastatic and treatment-resistant cancers provided informative, actionable results in 91 (94 %) cases, and treatment was guided by WES results in five (5 %) of these cases [12]. A multi-institutional integrative WES and RNA-Seq of 150 metastatic, castration-resistant prostate cancer (mCRPC) has identified actionable molecular alterations in 90 % of cases with 8 % harboring germline findings [13]. Most recently, the Peds-MiOncoSeq consortium reported clinical WES and RNA-Seq of 91 pediatric refractory or relapsed cancer patient samples [14]. Actionable findings were obtained in 42 (46 %) cases, and resulted in individualized actions involving either a change of treatment or genetic counseling in 23 (25 %) cases.

Here we describe the development and clinical application of an integrative genomic approach to facilitate PCT. At the time of this writing, a total of 65 patients with malignancies were enrolled in our study. For these patients, we performed WES, targeted panel sequencing, and single-nucleotide polymorphism (SNP) microarray genotyping on tumor and patient-matched normal DNA samples, as well as RNA-Seq on tumor and adjacent normal tissue samples, when available. Genomic data analysis was integrated with cancer knowledge bases and a cancer-type-specific workflow was developed for data interpretation. Our results support the concept that WES provides a more complete spectrum of cancer genomic alterations in comparison to targeted cancer panels. WES of tumor-normal paired samples also allowed us to assess germline variants conferring increased cancer risk or having involvement in drug metabolism. Moreover, we show that RNA-Seq data provide additional clinically relevant information. As expected, the integrated genomic approach utilized in our study identified more cancer-relevant somatic mutations and more actionable alterations than several commercially available targeted cancer panels in use today. In comparison to previous prospective clinical sequencing studies using WES [11, 12], we applied comprehensive genomic profiling utilizing multiple platforms including WES, SNP microarrays, and RNA-Seq. Although both WES and RNA-Seq were used in the mCRPC study, it was not clear if written reports of genomic findings with therapeutic recommendations were returned to the patients and the physicians, and if the findings had impacted therapeutic decisions [13]. While the Peds-MiOncoSeq consortium published WES and RNA-Seq of 91 pediatric cancers and the clinical actions taken based on genomic findings [14], our report represents a large-scale prospective clinical study in adult solid-tumor cancer patients applying comprehensive genomic profiling to guide PCT and returning results to patients and physicians. In addition, this is also the first study in a prospective clinical setting where multiple platforms are utilized to identify somatic mutations (WES and targeted panel) and to detect copy number alterations (WES and SNP array) for cross-platform comparison and validation.

Fig. 1

Overview of workflow

Fig. 2

Somatic mutation frequencies in 40 patients having WES data, grouped by cancer type: breast, colorectal, medullary thyroid carcinoma (MTC), and other. Each dot represents a tumor-normal sample pair from a patient; patients with multiple tumors are shown as multiple points, one per tumor. The bottom panel shows the distribution of six possible base pair substitutions in each tumor (see “Methods” for mutation nomenclature), ordered to correspond with frequency data points. Only non-synonymous SNVs and SNVs altering the canonical splice sites are counted and only if this functional impact is in a canonical protein isoform of the gene. Frequencies were obtained by dividing these mutation counts by the genomic area in coding exons in WES-targeted regions. Patient P0003 was omitted because the purity of WES-sequenced tumor was <5 % based on the allelic fraction distribution of somatic mutations (Additional file 2: Supplementary Results)

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