Building a Robust Tumor Profiling Program: Synergy between Next-Generation Sequencing and Targeted Single-Gene Testing

Custom Pediatric Oncology Next-Generation Sequencing Panel Identifies Somatic Mosaicism in Archival Tissue and Enhances Targeted Clinical Care

BACKGROUND

Disorders in the PIK3CA-related overgrowth spectrum because of somatic mosaicism are associated with segmental overgrowth of the body in conjunction with vascular, skeletal, and brain malformations such as hemimegalencephaly. A pathogenic variant may only be detectable in affected tissue and not in peripheral blood or saliva samples; therefore archival tissue may be the only relevant available specimen for testing. Although this is a common approach for cancer testing, it is not typically used for constitutional genetic disorders.

METHODS

PIK3CA mosaicism was assessed with a custom pediatric oncology next-generation sequencing panel (OncoKids) designed to capture somatic mutations in pediatric malignancies. The panel covers a wide range of targets including PIK3CA and AKT1 hotspots. We used OncoKids on archival formalin-fixed, paraffin-embedded or frozen samples from seven patients with facial hemihypertrophy and lipomas, hemimegalencephaly, or hemihypertrophy with a lymphovascular malformation. The age of the archival tissue examined by next-generation sequencing ranged from two to 13 years (median 5 years). Every patient had clinical manifestations within the PIK3CA-related overgrowth spectrum and had a sample of an affected tissue available for testing from a prior surgical intervention.

RESULTS

PIK3CA mosaicism was detected in all seven patients and the mutant allele fraction was lower in the lymphovascular malformation tissues (8% to 11%) than in brain (20% to 32%) and lipomatous (16% to 23%) tissues.

CONCLUSIONS

Our study highlights the clinical utility of using a robust, oncology-focused next-generation sequencing assay to identify PIK3CA mosaicism in noncancer cases. It is feasible to use archival samples that are more than a decade old to obtain a molecular diagnosis, which can then be used to improve health care management.

Influence of TP53 Mutation on Survival in Patients With Advanced EGFR-Mutant Non-Small-Cell Lung Cancer

Purpose

TP53 mutation (MT) in epidermal growth factor receptor (EGFR) -MT non-small cell lung cancer (NSCLC) is associated with poor response to targeted therapy; however, its impact on survival is not clearly established.

Patients and Methods

We performed an analysis of patients with stage IV EGFR MT NSCLC with available gene sequencing data. Associations between baseline characteristics; molecular profile, including TP53 MT; and survival outcomes were assessed.

Results

We identified 131 consecutive patients with EGFR MT; 81 (62%) had a TP53 MT, and 55 (42%) had other coexisting oncogenic MTs. Emergent EGFR T790M MT was observed in 42 patients (32%). Overall survival (OS) was longer for younger patients (P = .003), never smokers (P = .002), those with Eastern Cooperative Oncology Group performance status 0 to 1 (P = .004), and emergent T790M MT (P = .018). TP53 MT (P = .021) and other coexisting oncogenic MTs (P = 0.011) were associated with inferior OS. In a multivariable regression analysis adjusted for age, smoking, Eastern Cooperative Oncology Group performance status, and the presence of TP53 MT (P = .063) and other coexisting MTs (P = .064) did not achieve statistical significance. Patients with EGFR T790M/TP53 double MT had worse OS compared with patients with T790M MT alone (46.4 months v 82.9 months). In our series, five patients transformed to small-cell lung cancer (5.6%). All had TP53 MT. In four patients, allelic fraction of TP53 MT increased at the time of transformation.

Conclusion

The presence of TP53 and other coexisting MTs in EGFR MT NSCLC were associated with inferior OS, including patients with emergent T790M MT. An increase in TP53 mutation allelic fraction may potentially be a useful clinical predictor of small-cell transformation.

In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature

Background

Epidermal growth factor receptor variant III (EGFRvIII) is a driver mutation and potential therapeutic target in glioblastoma. Non-invasive in vivo EGFRvIII determination, using clinically acquired multiparametric MRI sequences, could assist in assessing spatial heterogeneity related to EGFRvIII, currently not captured via single-specimen analyses. We hypothesize that integration of subtle, yet distinctive, quantitative imaging/radiomic patterns using machine learning may lead to non-invasively determining molecular characteristics, and particularly the EGFRvIII mutation.

Methods

We integrated diverse imaging features, including the tumor's spatial distribution pattern, via support vector machines, to construct an imaging signature of EGFRvIII. This signature was evaluated in independent discovery (n = 75) and replication (n = 54) cohorts of de novo glioblastoma, and compared with the EGFRvIII status obtained through an assay based on next-generation sequencing.

Results

The cross-validated accuracy of the EGFRvIII signature in classifying the mutation status in individual patients of the independent discovery and replication cohorts was 85.3% (specificity = 86.3%, sensitivity = 83.3%, area under the curve [AUC] = 0.85) and 87% (specificity = 90%, sensitivity = 78.6%, AUC = 0.86), respectively. The signature was consistent with EGFRvIII+ tumors having increased neovascularization and cell density, as well as a distinctive spatial pattern involving relatively more frontal and parietal regions compared with EGFRvIII- tumors.

Conclusions

An imaging signature of EGFRvIII was found, revealing a complex, yet distinct macroscopic glioblastoma phenotype. By non-invasively capturing the tumor in its entirety, the proposed methodology can assist in evaluating the tumor's spatial heterogeneity, hence overcoming common spatial sampling limitations of tissue-based analyses. This signature can preoperatively stratify patients for EGFRvIII-targeted therapies, and potentially monitor dynamic mutational changes during treatment.

Feasibility of monitoring advanced melanoma patients using cell-free DNA from plasma

To determine the feasibility of liquid biopsy for monitoring of patients with advanced melanoma, cell-free DNA was extracted from plasma for 25 Stage III/IV patients, most (84.0%) having received previous therapy. DNA concentrations ranged from 0.6 to 390.0 ng/ml (median = 7.8 ng/ml) and were positively correlated with tumor burden as measured by imaging (Spearman rho = 0.5435, p = .0363). Using ultra-deep sequencing for a 61-gene panel, one or more mutations were detected in 12 of 25 samples (48.0%), and this proportion did not vary significantly for patients on or off therapy at the time of blood draw (52.9% and 37.5% respectively; p = .673). Sixteen mutations were detected in eight different genes, with the most frequent mutations detected in BRAF, NRAS, and KIT. Allele fractions ranged from 1.1% to 63.2% (median = 29.1%). Among patients with tissue next-generation sequencing, nine of 11 plasma mutations were also detected in matched tissue, for a concordance of 81.8%.

Genetic and Genomic Characterization of 462 Melanoma Patient-Derived Xenografts, Tumor Biopsies, and Cell Lines

Tumor-sequencing studies have revealed the widespread genetic diversity of melanoma. Sequencing of 108 genes previously implicated in melanomagenesis was performed on 462 patient-derived xenografts (PDXs), cell lines, and tumors to identify mutational and copy number aberrations. Samples came from 371 unique individuals: 263 were naive to treatment, and 108 were previously treated with targeted therapy (34), immunotherapy (54), or both (20). Models of all previously reported major melanoma subtypes (BRAF, NRAS, NF1, KIT, and WT/WT/WT) were identified. Multiple minor melanoma subtypes were also recapitulated, including melanomas with multiple activating mutations in the MAPK-signaling pathway and chromatin-remodeling gene mutations. These well-characterized melanoma PDXs and cell lines can be used not only as reagents for a large array of biological studies but also as pre-clinical models to facilitate drug development.

Low tumour cell content in a lung tumour bank: implications for molecular characterisation

Lung cancer encompasses multiple malignant epithelial tumour types, each with specific targetable, potentially actionable mutations, such that precision management mandates accurate tumour typing. Molecular characterisation studies require high tumour cell content and low necrosis content, yet lung cancers are frequently a heterogeneous mixture of tumour and stromal cells. We hypothesised that there may be systematic differences in tumour cell content according to histological subtype, and that this may have implications for tumour banks as a resource for comprehensive molecular characterisation studies in lung cancer. To investigate this, we estimated tumour cell and necrosis content of 4267 samples resected from 752 primary lung tumour specimens contributed to a lung tissue bank. We found that banked lung cancer samples had low tumour cell content (33%) generally, although it was higher in carcinoids (77.5%) than other lung cancer subtypes. Tumour cells comprise a variable and often small component of banked resected tumour samples, and are accompanied by stromal reaction, inflammation, fibrosis, and normal structures. This has implications for the adequacy of unselected tumour bank samples for diagnostic and molecular investigations, and further research is needed to determine whether tumour cell content has a significant impact on analytical results in studies using tissue from tumour bank resources.

In Vivo Detection of EGFRvIII in Glioblastoma via Perfusion Magnetic Resonance Imaging Signature Consistent with Deep Peritumoral Infiltration: The φ-Index

Purpose: The epidermal growth factor receptor variant III (EGFRvIII) mutation has been considered a driver mutation and therapeutic target in glioblastoma, the most common and aggressive brain cancer. Currently, detecting EGFRvIII requires postoperative tissue analyses, which are ex vivo and unable to capture the tumor's spatial heterogeneity. Considering the increasing evidence of in vivo imaging signatures capturing molecular characteristics of cancer, this study aims to detect EGFRvIII in primary glioblastoma noninvasively, using routine clinically acquired imaging.Experimental Design: We found peritumoral infiltration and vascularization patterns being related to EGFRvIII status. We therefore constructed a quantitative within-patient peritumoral heterogeneity index (PHI/φ-index), by contrasting perfusion patterns of immediate and distant peritumoral edema. Application of φ-index in preoperative perfusion scans of independent discovery (n = 64) and validation (n = 78) cohorts, revealed the generalizability of this EGFRvIII imaging signature.Results: Analysis in both cohorts demonstrated that the obtained signature is highly accurate (89.92%), specific (92.35%), and sensitive (83.77%), with significantly distinctive ability (P = 4.0033 × 10^-10, AUC = 0.8869). Findings indicated a highly infiltrative-migratory phenotype for EGFRvIII⁺ tumors, which displayed similar perfusion patterns throughout peritumoral edema. Contrarily, EGFRvIII^- tumors displayed perfusion dynamics consistent with peritumorally confined vascularization, suggesting potential benefit from extensive peritumoral resection/radiation.Conclusions: This EGFRvIII signature is potentially suitable for clinical translation, since obtained from analysis of clinically acquired images. Use of within-patient heterogeneity measures, rather than population-based associations, renders φ-index potentially resistant to inter-scanner variations. Overall, our findings enable noninvasive evaluation of EGFRvIII for patient selection for targeted therapy, stratification into clinical trials, personalized treatment planning, and potentially treatment-response evaluation. Clin Cancer Res; 23(16); 4724-34. ©2017 AACR.

Detection of Therapeutically Targetable Driver and Resistance Mutations in Lung Cancer Patients by Next-Generation Sequencing of Cell-Free Circulating Tumor DNA

PURPOSE

The expanding number of targeted therapeutics for non-small cell lung cancer (NSCLC) necessitates real-time tumor genotyping, yet tissue biopsies are difficult to perform serially and often yield inadequate DNA for next-generation sequencing (NGS). We evaluated the feasibility of using cell-free circulating tumor DNA (ctDNA) NGS as a complement or alternative to tissue NGS.

EXPERIMENTAL DESIGN

A total of 112 plasma samples obtained from a consecutive study of 102 prospectively enrolled patients with advanced NSCLC were subjected to ultra-deep sequencing of up to 70 genes and matched with tissue samples, when possible.

RESULTS

We detected 275 alterations in 45 genes, and at least one alteration in the ctDNA for 86 of 102 patients (84%), with EGFR variants being most common. ctDNA NGS detected 50 driver and 12 resistance mutations, and mutations in 22 additional genes for which experimental therapies, including clinical trials, are available. Although ctDNA NGS was completed for 102 consecutive patients, tissue sequencing was only successful for 50 patients (49%). Actionable EGFR mutations were detected in 24 tissue and 19 ctDNA samples, yielding concordance of 79%, with a shorter time interval between tissue and blood collection associated with increased concordance (P = 0.038). ctDNA sequencing identified eight patients harboring a resistance mutation who developed progressive disease while on targeted therapy, and for whom tissue sequencing was not possible.

CONCLUSIONS

Therapeutically targetable driver and resistance mutations can be detected by ctDNA NGS, even when tissue is unavailable, thus allowing more accurate diagnosis, improved patient management, and serial sampling to monitor disease progression and clonal evolution. Clin Cancer Res; 22(23); 5772-82. ©2016 AACR.