Development and clinical application of an integrative genomic approach to personalized cancer therapy

Abstract

Background: 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.

Methods: 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.

Results: 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.

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

Keywords: Cancer; Clinical application; Genomics; Personalized medicine.

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)

Fig. 3

Multiple somatic alterations in components within the same pathways. a Multiple somatic alterations within the APC pathway observed in a colorectal cancer. A schematic of the signaling pathways converging on growth control of colorectal cancer patient P0027 is displayed where mutation and predicted loss of function of tumor suppressors is depicted in red. Several components excluding APC are mutated in the canonical WNT signaling pathway. b Identification of an oncogenic driver in a breast cancer. A schematic of the signaling pathways converging on growth control of breast cancer patient P0040 is displayed where mutation and predicted loss of function of tumor suppressors is depicted in red and activation of oncogenes is depicted in green. Amplification and overexpression of CCND1 is identified through the integrative approach utilized in this study. c An integrative approach identifies the PI3K pathway as potential drug target in a squamous cell carcinoma. A schematic of the signaling pathways converging on growth control of skin squamous cell carcinoma patient P0011 is displayed where mutation and predicted loss of function of tumor suppressors is depicted in red and activation of oncogenes is depicted in green. Multiple tumor suppressors in the PI3K-AKT pathway have mutations that predict loss of function (INPP5D and INPPL1). Additionally, PI3K is mutated, suggesting PI3K-AKT pathway as a possible drug target

Fig. 4

Actionability across multiple cancer types in this study. A summary of the distribution of recommendations across cancer types, where tier 1 and tier 2 drugs (see “Methods” for definitions) is displayed. "CRC" is colorectal cancer

Fig. 5

Presentation of a case study with a novel actionable mutation p.D587H (hg19 chr7:55233009G > C) in EGFR. a EGFR mutation frequencies in several cancer types were obtained from TCGA data (http://cancergenome.nih.gov) and plotted across the EGFR protein sequence. D587 (dashed red line) is located near a hotspot at G598 within domain IV. Kinase domain and domain II hotspots are also depicted. Domain structure is from Pfam [63]. b Structure of the extracellular region of EGFR depicting individual domains; I (yellow), II (orange), III (teal), and IV (silver). A view of the interaction between domains II and IV is illustrated (box). Side chain of D587 (black) and K609 (green) form an interaction (red dashed line). Hydrogen bonding (red dashed lines) between domain IV residues and domain II tyrosine residues (orange) stabilize the inactive conformation. Hotspot regions (green side chains) may be allowing for a conformation of the loop that permits interaction between D587 and K609. c HEK293 cells were transfected with EGFR, p.D587H, or p.L858R, and activity of EGFR was assayed by western blot using an anti-phosphotyrosine antibody to measure autophosphorylation