Francesco Marass

Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA

Cancers acquire resistance to systemic treatment as a result of clonal evolution and selection. Repeat biopsies to study genomic evolution as a result of therapy are difficult, invasive and may be confounded by intra-tumour heterogeneity. Recent studies have shown that genomic alterations in solid cancers can be characterized by massively parallel sequencing of circulating cell-free tumour DNA released from cancer cells into plasma, representing a non-invasive liquid biopsy. Here we report sequencing of cancer exomes in serial plasma samples to track genomic evolution of metastatic cancers in response to therapy. Six patients with advanced breast, ovarian and lung cancers were followed over 1–2 years. For each case, exome sequencing was performed on 2–5 plasma samples (19 in total) spanning multiple courses of treatment, at selected time points when the allele fraction of tumour mutations in plasma was high, allowing improved sensitivity. For two cases, synchronous biopsies were also analysed, confirming genome-wide representation of the tumour genome in plasma. Quantification of allele fractions in plasma identified increased representation of mutant alleles in association with emergence of therapy resistance. These included an activating mutation in PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) following treatment with paclitaxel; a truncating mutation in RB1 (retinoblastoma 1) following treatment with cisplatin; a truncating mutation in MED1 (mediator complex subunit 1) following treatment with tamoxifen and trastuzumab, and following subsequent treatment with lapatinib, a splicing mutation in GAS6 (growth arrest-specific 6) in the same patient; and a resistance-conferring mutation in EGFR (epidermal growth factor receptor; T790M) following treatment with gefitinib. These results establish proof of principle that exome-wide analysis of circulating tumour DNA could complement current invasive biopsy approaches to identify mutations associated with acquired drug resistance in advanced cancers. Serial analysis of cancer genomes in plasma constitutes a new paradigm for the study of clonal evolution in human cancers.

Somatic mutations in ATP1A1 and CACNA1D underlie a common subtype of adrenal hypertension.

At least 5% of individuals with hypertension have adrenal aldosterone-producing adenomas (APAs). Gain-of-function mutations in KCNJ5 and apparent loss-of-function mutations in ATP1A1 and ATP2A3 were reported to occur in APAs. We find that KCNJ5 mutations are common in APAs resembling cortisol-secreting cells of the adrenal zona fasciculata but are absent in a subset of APAs resembling the aldosterone-secreting cells of the adrenal zona glomerulosa. We performed exome sequencing of ten zona glomerulosa–like APAs and identified nine with somatic mutations in either ATP1A1, encoding the Na+/K+ ATPase α1 subunit, or CACNA1D, encoding Cav1.3. The ATP1A1 mutations all caused inward leak currents under physiological conditions, and the CACNA1D mutations induced a shift of voltage-dependent gating to more negative voltages, suppressed inactivation or increased currents. Many APAs with these mutations were <1 cm in diameter and had been overlooked on conventional adrenal imaging. Recognition of the distinct genotype and phenotype for this subset of APAs could facilitate diagnosis.

Multifocal clonal evolution characterized using circulating tumour DNA in a case of metastatic breast cancer

Circulating tumour DNA analysis can be used to track tumour burden and analyse cancer genomes non-invasively but the extent to which it represents metastatic heterogeneity is unknown. Here we follow a patient with metastatic ER-positive and HER2-positive breast cancer receiving two lines of targeted therapy over 3 years. We characterize genomic architecture and infer clonal evolution in eight tumour biopsies and nine plasma samples collected over 1,193 days of clinical follow-up using exome and targeted amplicon sequencing. Mutation levels in the plasma samples reflect the clonal hierarchy inferred from sequencing of tumour biopsies. Serial changes in circulating levels of sub-clonal private mutations correlate with different treatment responses between metastatic sites. This comparison of biopsy and plasma samples in a single patient with metastatic breast cancer shows that circulating tumour DNA can allow real-time sampling of multifocal clonal evolution.

Tracking the origins and drivers of subclonal metastatic expansion in prostate cancer

Tumour heterogeneity in primary prostate cancer is a well-established phenomenon. However, how the subclonal diversity of tumours changes during metastasis and progression to lethality is poorly understood. Here we reveal the precise direction of metastatic spread across four lethal prostate cancer patients using whole-genome and ultra-deep targeted sequencing of longitudinally collected primary and metastatic tumours. We find one case of metastatic spread to the surgical bed causing local recurrence, and another case of cross-metastatic site seeding combining with dynamic remoulding of subclonal mixtures in response to therapy. By ultra-deep sequencing end-stage blood, we detect both metastatic and primary tumour clones, even years after removal of the prostate. Analysis of mutations associated with metastasis reveals an enrichment of TP53 mutations, and additional sequencing of metastases from 19 patients demonstrates that acquisition of TP53 mutations is linked with the expansion of subclones with metastatic potential which we can detect in the blood.

Clinical and pathological impact of VHL, PBRM1, BAP1, SETD2, KDM6A, and JARID1c in clear cell renal cell carcinoma

VHL is mutated in the majority of patients with clear cell renal cell carcinoma (ccRCC), with conflicting clinical relevance. Recent studies have identified recurrent mutations in histone modifying and chromatin remodeling genes, including BAP1, PBRM1, SETD2, KDM6A, and JARID1c. Current evidence suggests that BAP1 mutations are associated with aggressive disease. The clinical significance of the remaining genes is unknown. In this study, targeted sequencing of VHL and JARID1c (entire genes) and coding regions of BAP1, PBRM1, SETD2, and KDM6A was performed on 132 ccRCCs and matched normal tissues. Associations between mutations and clinical and pathological outcomes were interrogated. Inactivation of VHL (coding mutation or promoter methylation) was seen in 75% of ccRCCs. Somatic noncoding VHL alterations were identified in 29% of ccRCCs and may be associated with improved overall survival. BAP1 (11%), PBRM1 (33%), SETD2 (16%), JARID1c (4%), and KDM6A (3%) mutations were identified. BAP1‐mutated tumors were associated with metastatic disease at presentation (P = 0.023), advanced clinical stage (P = 0.042) and a trend towards shorter recurrence free survival (P = 0.059) when compared with tumors exclusively mutated for PBRM1. Our results support those of recent publications pointing towards a role for BAP1 and PBRM1 mutations in risk stratifying ccRCCs. Further investigation of noncoding alterations in VHL is warranted.

Optimized p53 immunohistochemistry is an accurate predictor of TP53 mutation in ovarian carcinoma

TP53 mutations are ubiquitous in high‐grade serous ovarian carcinomas (HGSOC), and the presence of TP53 mutation discriminates between high and low‐grade serous carcinomas and is now an important biomarker for clinical trials targeting mutant p53. p53 immunohistochemistry (IHC) is widely used as a surrogate for TP53 mutation but its accuracy has not been established. The objective of this study was to test whether improved methods for p53 IHC could reliably predict TP53 mutations independently identified by next generation sequencing (NGS). Four clinical p53 IHC assays and tagged‐amplicon NGS for TP53 were performed on 171 HGSOC and 80 endometrioid carcinomas (EC). p53 expression was scored as overexpression (OE), complete absence (CA), cytoplasmic (CY) or wild type (WT). p53 IHC was evaluated as a binary classifier where any abnormal staining predicted deleterious TP53 mutation and as a ternary classifier where OE, CA or WT staining predicted gain‐of‐function (GOF or nonsynonymous), loss‐of‐function (LOF including stopgain, indel, splicing) or no detectable TP53 mutations (NDM), respectively. Deleterious TP53 mutations were detected in 169/171 (99%) HGSOC and 7/80 (8.8%) EC. The overall accuracy for the best performing IHC assay for binary and ternary prediction was 0.94 and 0.91 respectively, which improved to 0.97 (sensitivity 0.96, specificity 1.00) and 0.95 after secondary analysis of discordant cases. The sensitivity for predicting LOF mutations was lower at 0.76 because p53 IHC detected mutant p53 protein in 13 HGSOC with LOF mutations. CY staining associated with LOF was seen in 4 (2.3%) of HGSOC. Optimized p53 IHC can approach 100% specificity for the presence of TP53 mutation and its high negative predictive value is clinically useful as it can exclude the possibility of a low‐grade serous tumour. 4.1% of HGSOC cases have detectable WT staining while harboring a TP53 LOF mutation, which limits sensitivity for binary prediction of mutation to 96%.

A phylogenetic latent feature model for clonal deconvolution

Tumours develop in an evolutionary process, in which the accumulation of mutations produces subpopulations of cells with distinct mutational profiles, called clones. This process leads to the genetic heterogeneity widely observed in tumour sequencing data, but identifying the genotypes and frequencies of the different clones is still a major challenge. Here, we present Cloe, a phylogenetic latent feature model to deconvolute tumour sequencing data into a set of related genotypes. Our approach extends latent feature models by placing the features as nodes in a latent tree. The resulting model can capture both the acquisition and the loss of mutations, as well as episodes of convergent evolution. We establish the validity of Cloe on synthetic data and assess its performance on controlled biological data, comparing our reconstructions to those of several published state-of-the-art methods. We show that our method provides highly accurate reconstructions and identifies the number of clones, their genotypes and frequencies even at a modest sequencing depth. As a proof of concept we apply our model to clinical data from three cases with chronic lymphocytic leukaemia, and one case with acute myeloid leukaemia.

CVE: an R package for interactive variant prioritisation in precision oncology

BackgroundAn increasing number of precision oncology programmes are being launched world-wide. To support this development, we present the Cancer Variant Explorer (CVE), an R package with an interactive Shiny web browser interface.ResultsLeveraging Oncotator and the Drug Gene Interaction Database, CVE offers exploration of variants within single or multiple tumour exomes to identify drivers, resistance mechanisms and to assess druggability. We present example applications including the analysis of an individual patient and a cohort-wide study, and provide a first extension of CVE by adding a tumour-specific co-expression network.ConclusionsThe CVE package allows interactive variant prioritisation to expedite the analysis of cancer sequencing studies. Our framework also includes the prioritisation of druggable targets, allows exploratory analysis of tissue specific networks and is extendable for specific applications by virtue of its modular design. We encourage the use of CVE within translational research studies and molecular tumour boards. The CVE package is available via Bioconductor (http://bioconductor.org/packages/CVE/).

Dynamics of multiple resistance mechanisms in plasma DNA during EGFR-targeted therapies in non-small cell lung cancer.

Tumour heterogeneity leads to the development of multiple resistance mechanisms during targeted therapies. Identifying the dominant driver(s) is critical for treatment decision. We studied the relative dynamics of multiple oncogenic drivers in longitudinal plasma of 50 EGFR‐mutant non‐small‐cell lung cancer patients receiving gefitinib and hydroxychloroquine. We performed digital PCR and targeted sequencing on samples from all patients and shallow whole‐genome sequencing on samples from three patients who underwent histological transformation to small‐cell lung cancer. In 43 patients with known EGFR mutations from tumour, we identified them accurately in plasma of 41 patients (95%, 41/43). We also found additional mutations, including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%) and PTEN (4/50, 8%). Patients with both TP53 and EGFR mutations before treatment had worse overall survival than those with only EGFR. Patients who progressed without T790M had worse PFS during TKI continuation and developed alternative alterations, including small‐cell lung cancer‐associated copy number changes and TP53 mutations, that tracked subsequent treatment responses. Longitudinal plasma analysis can help identify dominant resistance mechanisms, including non‐druggable genetic information that may guide clinical management.

Effects of Collection and Processing Procedures on Plasma Circulating Cell-Free DNA from Cancer Patients

Circulating tumor DNA (ctDNA) offers new opportunities for noninvasive cancer management. Detecting ctDNA in plasma is challenging because it constitutes only a minor fraction of the total cell-free DNA (cfDNA). Pre-analytical factors affect cfDNA levels contributed from leukocyte lysis, hence the ability to detect low-frequency mutant alleles. This study investigates the effects of the delay in processing, storage temperatures, different blood collection tubes, centrifugation protocols, and sample shipment on cfDNA levels. Peripheral blood (n = 231) from cancer patients (n = 62) were collected into K3EDTA or Cell-free DNA BCT tubes and analyzed by digital PCR, targeted amplicon, or shallow whole-genome sequencing. To assess pre-analytic effects, plasma was processed under different conditions after 0, 6, 24, 48, 96 hours, and 1 week at room temperature or 4°C, or using different centrifugation protocols. Digital PCR showed that cfDNA levels increased gradually with time in K3EDTA tubes, but were stable in BCT tubes. K3EDTA samples stored at 4°C showed less variation than room temperature storage, but levels were elevated compared with BCT. A second centrifugation at 3000 × g gave similar cfDNA yields compared with higher-speed centrifugation. Next-generation sequencing showed negligible differences in background error or copy number changes between K3EDTA and BCT, or following shipment in BCT. This study provides insights into the effects of sample processing on ctDNA analysis.