Search

Abstract Background Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes). Results Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%. Conclusion Long-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Abstract Oesophageal adenocarcinoma is a poor prognosis cancer and the molecular features underpinning response to treatment remain unclear. We investigate whole genome, transcriptomic and methylation data from 115 oesophageal adenocarcinoma patients mostly from the DOCTOR phase II clinical trial (Australian New Zealand Clinical Trials Registry-ACTRN12609000665235), with exploratory analysis pre-specified in the study protocol of the trial. We report genomic features associated with poorer overall survival, such as the APOBEC mutational and RS3-like rearrangement signatures. We also show that positron emission tomography non-responders have more sub-clonal genomic copy number alterations. Transcriptomic analysis categorises patients into four immune clusters correlated with survival. The immune suppressed cluster is associated with worse survival, enriched with myeloid-derived cells, and an epithelial-mesenchymal transition signature. The immune hot cluster is associated with better survival, enriched with lymphocytes, myeloid-derived cells, and an immune signature including CCL5, CD8A, and NKG7. The immune clusters highlight patients who may respond to immunotherapy and thus may guide future clinical trials.

IntroductionTumour Mutation Burden (TMB) is a potential biomarker for immune cancer therapies. Here we investigated parameters that might affect TMB using duplicate cytology smears obtained from endobronchial ultrasound transbronchial needle aspiration (EBUS TBNA)-sampled malignant lymph nodes.MethodsIndividual Diff-Quik cytology smears were prepared for each needle pass. DNA extracted from each smear underwent sequencing using large gene panel (TruSight Oncology 500 (TSO500 - Illumina)). TMB was estimated using the TSO500 Local App v. 2.0 (Illumina).ResultsTwenty patients had two or more Diff-Quik smears (total 45 smears) which passed sequencing quality control. Average smear TMB was 8.7 ± 5.0 mutations per megabase (Mb). Sixteen of the 20 patients had paired samples with minimal differences in TMB score (average difference 1.3 ± 0.85). Paired samples from 13 patients had concordant TMB (scores below or above a threshold of 10 mutations/Mb). Markedly discrepant TMB was observed in four cases, with an average difference of 11.3 ± 2.7 mutations/Mb. Factors affecting TMB calling included sample tumour content, the amount of DNA used in sequencing, and bone fide heterogeneity of node tumour between paired samples.ConclusionTMB assessment is feasible from EBUS-TBNA smears from a single needle pass. Repeated samples of a lymph node station have minimal variation in TMB in most cases. However, this novel data shows how tumour content and minor change in site of node sampling can impact TMB. Further study is needed on whether all node aspirates should be combined in 1 sample, or whether testing independent nodes using smears is needed.

Abstract Background Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. Methods We analysed somatic mutations from 229 MPM samples, including previously published data and 58 samples that had undergone WGS within this study. This was combined with RNA-seq analysis to characterize the tumour immune environment. Results The comprehensive genome analysis identified 12 driver genes, including new candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed SBS5/40 were dominant in 93% of samples, and defects in homologous recombination repair were infrequent in our cohort. The tumour immune environment contained high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immune suppressive environment. The expression of TGFB1 was associated with overall survival. A small subset of samples (less than 10%) had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a ‘hot’ immune environment independent of the somatic mutations. Conclusions We propose accounting for genomic and immune microenvironment status may influence therapeutic planning in the future.

Abstract Background Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprises four molecular subtypes with differing etiology, prognoses, and responses to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. As pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. Methods Here, we report whole exome or whole genome sequencing of 11 PDX models and their matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. Results PDX models were successfully generated from grade 2/3 tumors, including three uterine carcinosarcomas. The models showed similar histomorphology to the primary tumors and represented all four molecular subtypes of EC, including five mismatch-repair deficient models. The different PDX lineages showed a wide range of inter-tumor and intra-tumor heterogeneity. However, for most PDX models, one arm recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease; however, all lacked the HR deficiency genomic signature. Conclusions EC PDX models represent the four molecular subtypes of disease and can capture intra-tumor heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi; however, deeper and more durable responses will likely require combination of PARPi with other agents.

Abstract Background Circulating cell-free DNA (cfDNA) in the plasma of cancer patients contains cell-free tumour DNA (ctDNA) derived from tumour cells and it has been widely recognized as a non-invasive source of tumour DNA for diagnosis and prognosis of cancer. Molecular profiling of ctDNA is often performed using targeted sequencing or low-coverage whole genome sequencing (WGS) to identify tumour specific somatic mutations or somatic copy number aberrations (sCNAs). However, these approaches cannot efficiently detect all tumour-derived genomic changes in ctDNA. Methods We performed WGS analysis of cfDNA from 4 breast cancer patients and 2 patients with benign tumours. We sequenced matched germline DNA for all 6 patients and tumour samples from the breast cancer patients. All samples were sequenced on Illumina HiSeqXTen sequencing platform and achieved approximately 30x, 60x and 100x coverage on germline, tumour and plasma DNA samples, respectively. Results The mutational burden of the plasma samples (1.44 somatic mutations/Mb of genome) was higher than the matched tumour samples. However, 90% of high confidence somatic cfDNA variants were not detected in matched tumour samples and were found to comprise two background plasma mutational signatures. In contrast, cfDNA from the di-nucleosome fraction (300 bp–350 bp) had much higher proportion (30%) of variants shared with tumour. Despite high coverage sequencing we were unable to detect sCNAs in plasma samples. Conclusions Deep sequencing analysis of plasma samples revealed higher fraction of unique somatic mutations in plasma samples, which were not detected in matched tumour samples. Sequencing of di-nucleosome bound cfDNA fragments may increase recovery of tumour mutations from plasma.

Lipoblastoma-like tumour of the vulva (LLTV) is a rare soft tissue neoplasm with only nineteen reported cases to date. The clinical behaviour in all cases has been benign, with a small number of local recurrences and no incidences of metastasis described. We present an unusual case of LLTV that arose in a 16-year-old female who subsequently developed histologically identical lesions in the breast, chest wall and retroperitoneum, over the course of three and a half years. Our comprehensive histopathological analysis and molecular genetic studies supported the diagnosis of LLTV, with absence of DDIT3 rearrangement and absence of other specific diagnostic genetic events for any other soft tissue neoplasm. Whole exome sequencing was performed on the vulva, vulva recurrence, breast, and lung lesions and revealed a complex genome with striking similarity between the tumours. Multiple somatic mutations of interest were identified, including in MTOR and the TERT promoter, which enabled patient treatment with a specific inhibitor. To our knowledge, this is the first reported case of metastasising LLTV, and the first comprehensive genetic analysis of such a tumour.

Introduction: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS TBNA) is an important means of obtaining a tissue for advanced lung cancer. Optimizing the EBUS TBNA needling technique is important to maintain procedural simplicity and maximize sample quality for emerging molecular diagnostics. Methods: We prospectively explored three versus 10 agitations of the needle in sequential passes into the lymph node using separate needles. Resulting Diff-Quik cytology smears were quantitatively assessed using microscopic (tumor cell cellularity, abundance scores, erythrocyte contamination) and DNA yields. Microscopy was reported by two cytopathologists, and an inter-rater assessment was made by four additional cytopathologists. Results: In 86 patients confirmed as having malignant disease by EBUS TBNA (45 males, 41 females), a mean of 5.3 smears were made per patient with a total of 459 smears scored by pathologists and 168 paired smears extracted for DNA. There was no significant difference between three versus 10 agitations for smear cellularity (p = 0.44), DNA yield (p = 0.84), or DNA integrity (p = 0.20), but there was significantly less contamination by erythrocytes from three agitations (chi-square p = 0.008). There was significantly more DNA in the first pass into the node using three agitations than with other passes and with 10 agitations (pass × agitations interaction, p = 0.031). Reviewing pathologists correctly classified smears as more than or equal to 25% cellularity 86.3% of the time (κ = 0.63 [95% confidence interval: 0.55–0.71]). Conclusions: Three agitations are noninferior to 10 agitations for overall abundance of malignant cells and DNA content on smears. A smear with adequate DNA for panel sequencing could almost always be made with the first needle pass using three agitations.

Lakis et al. report novel findings related to the epigenetic landscape of pancreatic neuroendocrine cancer. This relatively large cohort provides functional insights into the epigenetic wiring of pancreatic neuroendocrine tumor sub-types with the potential ability to stratify tumours of different prognosis.

Abstract For complex machine learning (ML) algorithms to gain widespread acceptance in decision making, we must be able to identify the features driving the predictions. Explainability models allow transparency of ML algorithms, however their reliability within high-dimensional data is unclear. To test the reliability of the explainability model SHapley Additive exPlanations (SHAP), we developed a convolutional neural network to predict tissue classification from Genotype-Tissue Expression (GTEx) RNA-seq data representing 16,651 samples from 47 tissues. Our classifier achieved an average F1 score of 96.1% on held-out GTEx samples. Using SHAP values, we identified the 2423 most discriminatory genes, of which 98.6% were also identified by differential expression analysis across all tissues. The SHAP genes reflected expected biological processes involved in tissue differentiation and function. Moreover, SHAP genes clustered tissue types with superior performance when compared to all genes, genes detected by differential expression analysis, or random genes. We demonstrate the utility and reliability of SHAP to explain a deep learning model and highlight the strengths of applying ML to transcriptome data.

Acral melanoma occurs on the soles of the feet, palms of the hands and in nail beds. Here, the authors reports the genomic landscape of 87 acral melanomas and find that some tumors harbor a UV signature and that the tumors are diverse at the levels of mutational signatures, structural aberrations and copy number signatures.

Abstract Background Despite the rapid uptake of genomic technologies within cancer care, few studies provide detailed information on the costs of sequencing across different applications. The objective of the study was to examine and categorise the complete costs involved in genomic sequencing for a range of applications within cancer settings. Methods We performed a cost-analysis using gross and micro-costing approaches for genomic sequencing performed during 2017/2018 across different settings in Brisbane, Australia. Sequencing was undertaken for patients with lung, breast, oesophageal cancers, melanoma or mesothelioma. Aggregated resource data were captured for a total of 1433 patients and point estimates of per patient costs were generated. Deterministic sensitivity analyses addressed the uncertainty in the estimates. Estimated costs to the public health system for resources were categorised into seven distinct activities in the sequencing process: sampling, extraction, library preparation, sequencing, analysis, data storage and clinical reporting. Costs were also aggregated according to labour, consumables, testing, equipment and ‘other’ categories. Results The per person costs were AU$347–429 (2018 US$240–297) for targeted panels, AU$871–$2788 (2018 US$604–1932) for exome sequencing, and AU$2895–4830 (2018 US$2006-3347) for whole genome sequencing. Cost proportions were highest for library preparation/sequencing materials (average 76.8% of total costs), sample extraction (8.1%), data analysis (9.2%) and data storage (2.6%). Capital costs for the sequencers were an additional AU$34–197 (2018 US$24–67) per person. Conclusions Total costs were most sensitive to consumables and sequencing activities driven by commercial prices. Per person sequencing costs for cancer are high when tumour/blood pairs require testing. Using the natural steps involved in sequencing and categorising resources accordingly, future evaluations of costs or cost-effectiveness of clinical genomics across cancer projects could be more standardised and facilitate easier comparison of cost drivers.

Mucosal melanomas are challenging to treat partly because so little is known about the genetic drivers underpinning them. Here, the authors perform a genomic landscape analysis of samples collected from three continents, revealing a potential role for CDK4/6 or MEK inhibition in the treatment of the disease.

Abstract Background Oesophageal adenocarcinoma (EAC) incidence is increasing and has a poor survival rate. Barrett’s oesophagus (BE) is a precursor condition that is associated with EAC and often occurs in conjunction with chronic gastro-oesophageal reflux, however many individuals diagnosed with BE never progress to cancer. An understanding of the genomic features of BE and EAC may help with the early identification of at-risk individuals. Methods In this study, we assessed the genomic features of 16 BE samples using whole-genome sequencing. These included non-dysplastic samples collected at two time-points from two BE patients who had not progressed to EAC over several years. Seven other non-dysplastic samples and five dysplastic BE samples with high-grade dysplasia were also examined. We compared the genome profiles of these 16 BE samples with 22 EAC samples. Results We observed that samples from the two non-progressor individuals had low numbers of somatic single nucleotide variants, indels and structural variation events compared to dysplastic and the remaining non-dysplastic BE. EAC had the highest level of somatic genomic variations. Mutational signature 17, which is common in EAC, was also present in non-dysplastic and dysplastic BE, but was not present in the non-progressors. Many dysplastic samples had mutations in genes previously reported in EAC, whereas only mutations in CDKN2A or in the fragile site genes appeared common in non-dysplastic samples. Rearrangement signatures were used to identify a signature associated with localised complex events such as chromothripsis and breakage fusion-bridge that are characteristic of EACs. Two dysplastic BE samples had a high contribution of this signature and contained evidence of localised rearrangements. Two other dysplastic samples also had regions of localised structural rearrangements. There was no evidence for complex events in non-dysplastic samples. Conclusions The presence of complex localised rearrangements in dysplastic samples indicates a need for further investigations into the role such events play in the progression from BE to EAC.

Background & Aims: Colorectal cancer is an epigenetically heterogeneous disease, however, the extent and spectrum of the CpG island methylator phenotype (CIMP) is not clear. Methods: Genome-scale methylation and transcript expression were measured by DNA Methylation and RNA expression microarray in 216 unselected colorectal cancers, and findings were validated using The Cancer Genome Atlas 450K and RNA sequencing data. Mutations in epigenetic regulators were assessed using CIMP-subtyped Cancer Genome Atlas exomes. Results: CIMP-high cancers dichotomized into CIMP-H1 and CIMP-H2 based on methylation profile. KRAS mutation was associated significantly with CIMP-H2 cancers, but not CIMP-H1 cancers. Congruent with increasing methylation, there was a stepwise increase in patient age from 62 years in the CIMP-negative subgroup to 75 years in the CIMP-H1 subgroup (P < .0001). CIMP-H1 predominantly comprised consensus molecular subtype 1 cancers (70%) whereas consensus molecular subtype 3 was over-represented in the CIMP-H2 subgroup (55%). Polycomb Repressive Complex-2 (PRC2)-marked loci were subjected to significant gene body methylation in CIMP cancers (P < 1.6 × 10-78). We identified oncogenes susceptible to gene body methylation and Wnt pathway antagonists resistant to gene body methylation. CIMP cluster–specific mutations were observed in chromatin remodeling genes, such as in the SWItch/Sucrose Non-Fermentable and Chromodomain Helicase DNA-Binding gene families. Conclusions: There are 5 clinically and molecularly distinct subgroups of colorectal cancer. We show a striking association between CIMP and age, sex, and tumor location, and identify a role for gene body methylation in the progression of serrated neoplasia. These data support our recent findings that CIMP is uncommon in young patients and that BRAF mutant polyps in young patients may have limited potential for malignant progression. Keywords: DNA Methylation, CIMP, Colorectal Cancer, Epigenetics, BRAF, KRAS

Abstract The centrosomal protein, CEP55, is a key regulator of cytokinesis, and its overexpression is linked to genomic instability, a hallmark of cancer. However, the mechanism by which it mediates genomic instability remains elusive. Here, we showed that CEP55 overexpression/knockdown impacts survival of aneuploid cells. Loss of CEP55 sensitizes breast cancer cells to anti‐mitotic agents through premature CDK1/cyclin B activation and CDK1 caspase‐dependent mitotic cell death. Further, we showed that CEP55 is a downstream effector of the MEK1/2‐MYC axis. Blocking MEK1/2‐PLK1 signaling therefore reduced outgrowth of basal‐like syngeneic and human breast tumors in in vivo models. In conclusion, high CEP55 levels dictate cell fate during perturbed mitosis. Forced mitotic cell death by blocking MEK1/2‐PLK1 represents a potential therapeutic strategy for MYC‐CEP55‐dependent basal‐like, triple‐negative breast cancers.

Abstract Background The return of research results (RoR) remains a complex and well-debated issue. Despite the debate, actual data related to the experience of giving individual results back, and the impact these results may have on clinical care and health outcomes, is sorely lacking. Through the work of the Australian Pancreatic Cancer Genome Initiative (APGI) we: (1) delineate the pathway back to the patient where actionable research data were identified; and (2) report the clinical utilisation of individual results returned. Using this experience, we discuss barriers and opportunities associated with a comprehensive process of RoR in large-scale genomic research that may be useful for others developing their own policies. Methods We performed whole-genome (n = 184) and exome (n = 208) sequencing of matched tumour-normal DNA pairs from 392 patients with sporadic pancreatic cancer (PC) as part of the APGI. We identified pathogenic germline mutations in candidate genes (n = 130) with established predisposition to PC or medium–high penetrance genes with well-defined cancer associated syndromes or phenotypes. Variants from candidate genes were annotated and classified according to international guidelines. Variants were considered actionable if clinical utility was established, with regard to prevention, diagnosis, prognostication and/or therapy. Results A total of 48,904 germline variants were identified, with 2356 unique variants undergoing annotation and in silico classification. Twenty cases were deemed actionable and were returned via previously described RoR framework, representing an actionable finding rate of 5.1%. Overall, 1.78% of our cohort experienced clinical benefit from RoR. Conclusion Returning research results within the context of large-scale genomics research is a labour-intensive, highly variable, complex operation. Results that warrant action are not infrequent, but the prevalence of those who experience a clinical difference as a result of returning individual results is currently low.

Epigenetics: A genome-wide picture in patient-derived cells Schizophrenia-associated differences in the DNA methylation status of patient-derived cells suggest it could affect early brain development. Mechanisms that control gene expression without altering the genetic code, such as DNA methylation, could explain how environmental risk factors contribute to schizophrenia in genetically susceptible individuals. Alan Mackay-Sim and colleagues from Griffith University, Australia, carried out genome-wide comparisons of DNA methylation in induced pluripotent stem (iPS) cells, olfactory neurosphere-derived cells and fibroblasts from patients and controls. Differences in the DNA methylation pattern between patient and control iPS cells, which could reflect what happens in the embryo, suggest a disease-associated effect very early on in development. Only five genes were differentially methylated in all three patient-derived cell types compared to controls. None of these genes has previously been associated with schizophrenia and may represent new targets for future research.

Technological innovation and increased affordability have contributed to the widespread adoption of genome sequencing technologies in biomedical research. In particular large cancer research consortia have embraced next generation sequencing, and have used the technology to define the somatic mutation landscape of multiple cancer types. These studies have primarily utilised the Illumina HiSeq platforms. In this study we performed whole genome sequencing of three malignant pleural mesothelioma and matched normal samples using a new platform, the BGISEQ-500, and compared the results obtained with Illumina HiSeq X Ten. Germline and somatic, single nucleotide variants and small insertions or deletions were independently identified from data aligned human genome reference. The BGISEQ-500 and HiSeq X Ten platforms showed high concordance for germline calls with genotypes from SNP arrays (>99%). The germline and somatic single nucleotide variants identified in both sequencing platforms were highly concordant (86% and 72% respectively). These results indicate the potential applicability of the BGISEQ-500 platform for the identification of somatic and germline single nucleotide variants by whole genome sequencing. The BGISEQ-500 datasets described here represent the first publicly-available cancer genome sequencing performed using this platform.

Somatic rearrangements, which are commonly found in human cancer genomes, contribute to the progression and maintenance of cancers. Conventionally, the verification of somatic rearrangements comprises many manual steps and Sanger sequencing. This is labor intensive when verifying a large number of rearrangements in a large cohort. To increase the verification throughput, we devised a high-throughput workflow that utilizes benchtop next-generation sequencing and in-house bioinformatics tools to link the laboratory processes. In the proposed workflow, primers are automatically designed. PCR and an optional gel electrophoresis step to confirm the somatic nature of the rearrangements are performed. PCR products of somatic events are pooled for Ion Torrent PGM and/or Illumina MiSeq sequencing, the resulting sequence reads are assembled into consensus contigs by a consensus assembler, and an automated BLAT is used to resolve the breakpoints to base level. We compared sequences and breakpoints of verified somatic rearrangements between the conventional and high-throughput workflow. The results showed that next-generation sequencing methods are comparable to conventional Sanger sequencing. The identified breakpoints obtained from next-generation sequencing methods were highly accurate and reproducible. Furthermore, the proposed workflow allows hundreds of events to be processed in a shorter time frame compared with the conventional workflow.

Genetic variation modulates gene expression transcriptionally or post-transcriptionally, and can profoundly alter an individual's phenotype. Measuring allelic differential expression at heterozygous loci within an individual, a phenomenon called allele-specific expression (ASE), can assist in identifying such factors. Massively parallel DNA and RNA sequencing and advances in bioinformatic methodologies provide an outstanding opportunity to measure ASE genome-wide. In this study, matched DNA and RNA sequencing, genotyping arrays and computationally phased haplotypes were integrated to comprehensively and conservatively quantify ASE in a single human brain and liver tissue sample. We describe a methodological evaluation and assessment of common bioinformatic steps for ASE quantification, and recommend a robust approach to accurately measure SNP, gene and isoform ASE through the use of personalized haplotype genome alignment, strict alignment quality control and intragenic SNP aggregation. Our results indicate that accurate ASE quantification requires careful bioinformatic analyses and is adversely affected by sample specific alignment confounders and random sampling even at moderate sequence depths. We identified multiple known and several novel ASE genes in liver, including WDR72, DSP and UBD, as well as genes that contained ASE SNPs with imbalance direction discordant with haplotype phase, explainable by annotated transcript structure, suggesting isoform derived ASE. The methods evaluated in this study will be of use to researchers performing highly conservative quantification of ASE, and the genes and isoforms identified as ASE of interest to researchers studying those loci.

Somatic mutation calling from next-generation sequencing data remains a challenge due to the difficulties of distinguishing true somatic events from artifacts arising from PCR, sequencing errors or mis-mapping. Tumor cellularity or purity, sub-clonality and copy number changes also confound the identification of true somatic events against a background of germline variants. We have developed a heuristic strategy and software (http://www.qcmg.org/bioinformatics/qsnp/) for somatic mutation calling in samples with low tumor content and we show the superior sensitivity and precision of our approach using a previously sequenced cell line, a series of tumor/normal admixtures, and 3,253 putative somatic SNVs verified on an orthogonal platform.

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 ([Formula: see text]-value=0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 ([Formula: see text]-value [Formula: see text] 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 ([Formula: see text]-value=0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.

Two gene expression profiling studies designed to identify maternal influences on development of the neonate immune system and to address the population structure of the leukocyte transcriptome were carried out in Brisbane, Australia. In the first study, a comparison of 19 leukocyte samples obtained from mothers in the last three weeks of pregnancy with 37 umbilical cord blood samples documented differential expression of 7,382 probes at a false discovery rate of 1%, representing approximately half of the expressed transcriptome. An even larger component of the variation involving 8,432 probes, notably enriched for Vitamin E and methotrexate-responsive genes, distinguished two sets of individuals, with perfect transmission of the two profile types between each of 16 mother-child pairs in the study. A minor profile of variation was found to distinguish the gene expression profiles of obese mothers and children of gestational diabetic mothers from those of children born to obese mothers. The second study was of adult leukocyte profiles from a cross-section of Red Cross blood donors sampled throughout Brisbane. The first two axes in this study are related to the third and fourth axes of variation in the first study and also reflect variation in the abundance of CD4 and CD8 transcripts. One of the profiles associated with the third axis is largely excluded from samples from the central portion of the city. Despite enrichment of insulin signaling and aspects of central metabolism among the differentially expressed genes, there was little correlation between leukocyte expression profiles and body mass index overall. Our data is consistent with the notion that maternal health and cytokine milieu directly impact gene expression in fetal tissues, but that there is likely to be a complex interplay between cultural, genetic, and other environmental factors in the programming of gene expression in leukocytes of newborn children.