Very few people live to eighty-five years and older (the 'oldest old'), and even fewer live to this age without developing chronic diseases. It is important to understand the relationship, if any, of modifiable factors such as diet on healthy aging. However, there are few studies of diet among healthy oldest old, especially in North American populations. We aimed to characterize dietary patterns among 'super-seniors' (SS) within the Canadian Healthy Aging Study.
Introduction Given the high level of uncertainty surrounding the outcomes of early phase clinical trials, whole genome and transcriptome analysis (WGTA) can be used to optimize patient selection and study assignment. In this retrospective analysis, we reviewed the impact of this approach on one such program. Methods Patients with advanced malignancies underwent fresh tumor biopsies as part of our personalized medicine program (NCT02155621). Tumour molecular data were reviewed for potentially clinically actionable findings and patients were referred to the developmental therapeutics program. Outcomes were reviewed in all patients, including those where trial selection was driven by molecular data (matched) and those where there was no clear molecular rationale (unmatched). Results From January 2014 to January 2018, 28 patients underwent WGTA and enrolled in clinical trials, including 2 patients enrolled in two trials. Fifteen patients were matched to a treatment based on a molecular target. Five patients were matched to a trial based upon single-gene DNA changes, all supported by RNA data. Ten cases were matched on the basis of genome-wide data (n = 4) or RNA gene expression only (n = 6). With a median follow-up of 6.7 months, the median time on treatment was 8.2 weeks. Discussion When compared to single-gene DNA-based data alone, WGTA led to a 3-fold increase in treatment matching. In a setting where there is a high level of uncertainty around both the investigational agents and the biomarkers, more data are needed to fully evaluate the impact of routine use of WGTA.
Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
Pancreatic adenocarcinoma presents as a spectrum of a highly aggressive disease in patients. The basis of this disease heterogeneity has proved difficult to resolve due to poor tumor cellularity and extensive genomic instability. To address this, a dataset of whole genomes and transcriptomes was generated from purified epithelium of primary and metastatic tumors. Transcriptome analysis demonstrated that molecular subtypes are a product of a gene expression continuum driven by a mixture of intratumoral subpopulations, which was confirmed by single-cell analysis. Integrated whole-genome analysis uncovered that molecular subtypes are linked to specific copy number aberrations in genes such as mutant KRAS and GATA6. By mapping tumor genetic histories, tetraploidization emerged as a key mutational process behind these events. Taken together, these data support the premise that the constellation of genomic aberrations in the tumor gives rise to the molecular subtype, and that disease heterogeneity is due to ongoing genomic instability during progression.
Hairy cell leukemia (HCL) is a rare chronic B-cell lymphoproliferative disorder named for its characteristic hair-like cytoplasmic projections from the malignant cells. HCL is classified as an indolent lymphoproliferative neoplasm, representing ~2% of all leukemias with ~1240 new cases diagnosed annually in the US; median age-at-onset is 55 years . It affects males more than females (4:1), and whites more than African-Americans . Although familial and sporadic HCL exhibit similar clinical features, no characteristic germline genetic variation has been found. Familial HCL is rare with fewer than 20 families reported in the literature. Thirteen of the 15 reported pedigrees had two affected individuals; the remaining two pedigrees harbored three, including the family reported here [2,3,4,5]. Investigators have speculated that HCL may be an HLA-linked disorder but, in aggregate, the data are inconclusive [3,4,5]. The discovery that a somatic BRAF mutation (V600E) was nearly universal in HCL (but absent in other B-cell neoplasms) provided major insight into disease biology, identifying a critical therapeutic target , but no germline genetic susceptibility variants have been identified. In this study we applied high-throughput sequencing technology to four multiplex HCL pedigrees, seeking to identify shared germline variants conferring HCL susceptibility. In addition, we used CRISPR/Cas9-based genome editing to introduce CASP9 p.H237P, one of the variants shared by all four affected members of the largest pedigree, into a model cell line, followed by measurements of cellular caspase-9 activity and apoptotic response.
Although the evidence is not consistent, epidemiologic studies have suggested that taller adult height may be associated with an increased risk of some non-Hodgkin lymphoma (NHL) subtypes. Height is largely determined by genetic factors, but how these genetic factors may contribute to NHL risk is unknown. We investigated the relationship between genetic determinants of height and NHL risk using data from eight genome-wide association studies (GWAS) comprising 10,629 NHL cases, including 3,857 diffuse large B-cell lymphoma (DLBCL), 2,847 follicular lymphoma (FL), 3,100 chronic lymphocytic leukemia (CLL), and 825 marginal zone lymphoma (MZL) cases, and 9,505 controls of European ancestry. We evaluated genetically predicted height by constructing polygenic risk scores using 833 height-associated SNPs. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for association between genetically determined height and the risk of four NHL subtypes in each GWAS and then used fixed-effect meta-analysis to combine subtype results across studies. We found suggestive evidence between taller genetically determined height and increased CLL risk (OR = 1.08, 95% CI = 1.00–1.17, p = 0.049), which was slightly stronger among women (OR = 1.15, 95% CI: 1.01–1.31, p = 0.036). No significant associations were observed with DLBCL, FL, or MZL. Our findings suggest that there may be some shared genetic factors between CLL and height, but other endogenous or environmental factors may underlie reported epidemiologic height associations with other subtypes.
A high organic content CE‐MS/MS (HOCE‐MS/MS) method was developed for the proteomic analysis of envelope proteins extracted from spinach leaves. Separation was performed in a 1‐m long hydroxypropyl cellulose coated capillary, using 8% (v/v) formic acid in 70% (v/v) methanol and 22% water as the BGE. A flow‐through microvial interface was used to couple the CE system with an Orbitrap Fusion Lumos mass spectrometer, and field‐amplified sample stacking was used to improve the concentration sensitivity. Using this optimized method, 3579 peptides and 1141 proteins were identified using the Proteome Discoverer software with a 1% false discovery rate at the protein level. Relative to conventional aqueous CE, HOCE‐MS did a better job of discovering hydrophobic peptides and provided more peptide and protein identifications. Relative to nano‐LC‐MS, it achieved comparable peptide and protein identification performance and detected peptides not identified by LC‐MS: of the full set of peptides identified using the two techniques, 19% were identified only using HOCE‐MS. It also outperformed nano‐LC‐MS with respect to the detection of low molecular weight peptides.
New streamlined models for genetic counseling and genetic testing have recently been developed in response to increasing demand for cancer genetic services. To improve access and decrease wait times, we implemented an oncology clinic-based genetic testing model for breast and ovarian cancer patients in a publicly funded population-based health care setting in British Columbia, Canada. This observational study evaluated the oncology clinic-based model as compared to a traditional one-on-one approach with a genetic counsellor using a multi-gene panel testing approach. The primary objectives were to evaluate wait times and patient reported outcome measures between the oncology clinic-based and traditional genetic counselling models. Secondary objectives were to describe oncologist and genetic counsellor acceptability and experience. Wait times from referral to return of genetic testing results were assessed for 400 patients with breast and/or ovarian cancer undergoing genetic testing for hereditary breast and ovarian cancer from June 2015 to August 2017. Patient wait times from referral to return of results were significantly shorter with the oncology clinic-based model as compared to the traditional model (403 vs. 191 days; p < 0.001). A subset of 148 patients (traditional n = 99; oncology clinic-based n = 49) completed study surveys to assess uncertainty, distress, and patient experience. Responses were similar between both models. Healthcare providers survey responses indicated they believed the oncology clinic-based model was acceptable and a positive experience. Oncology clinic-based genetic testing using a multi-gene panel approach and post-test counselling with a genetic counsellor significantly reduced wait times and is acceptable for patients and health care providers.
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1,2,3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10,11,12,13,14,15,16,17,18.
Clinical Practice Points
Non-V600 B-Raf Proto-Oncogene, Serine/Threonine Kinase (BRAF) mutated metastatic colorectal cancer (mCRC) has a better prognosis than V600 BRAF mCRC Non-V600 mutations can be further subdivided into class II or III variants; class III variants might respond to anti-epidermal growth factor receptor (EGFR) therapy.
We describe an mCRC patient with a G466V (class III) BRAF variant found in the primary tumor before anti-EGFR therapy, but not in a liver metastasis after anti-EGFR exposure. A reduction in the BRAF variant between pre- and post-treatment plasma samples was discordant with a concomitant increase in circulating tumor DNA (ctDNA) levels of comutations and radiologic progression in metastatic lesions.
There was copy number neutral loss of heterozygosity (CN-LOH) at the BRAF coding region in the liver biopsy. The CN-LOH might have resulted in loss of the class III BRAF variant that chronologically corresponded with a decrease of this variant in ctDNA.
In a retrospective cohort from 2 institutions, we show that the relative variant allele frequency (rVAF) of non-V600 BRAF mutations (0.74) is lower than for rVAF of V600 (class I) BRAF mutations (1.00; P < .0001). Among non-V600 mutations, class III (P < .0001) but not class II mutations (P = .10) had statistically lower allele frequencies than V600 mutations.
Discordant responses between ctDNA levels of comutations can occur because of tumor heterogeneity and evolutionary pressures.
The CN-LOH described might be a novel mechanism of resistance to anti-EGFR therapy because wild type BRAF is less RAS signaling-dependent than class III variants. Non-V600 BRAF occurs at a lower rVAF than V600 BRAF mutations and may undergo clonal selection.