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Aggregate population genomics data from large cohorts are vital for assessing germline variant pathogenicity. However, there are no specifications on how sequencing quality metrics should be considered, and whether exome-derived and genome-derived allele frequencies should be considered in isolation. Germline genome sequence data were simulated for nine read-depths to identify a minimum acceptable read-depth for detecting variants. gnomAD exome-derived and genome-derived datasets were assessed for read-depth, for six key cancer genes selected for variant curation by ClinGen expert panels. Non-Finnish European allele frequency (AF) or filter AF of coding variants in these genes, assigned into frequency bins using modified ACMG-AMP criteria, was compared between exome-derived and genome-derived datasets. A 30X read-depth achieved acceptable precision and recall for detection of substitutions, but poor recall for small insertions/deletions. Exome-derived and genome-derived datasets exhibited low read-depth for different gene exons. Individual variants were mostly assigned to non-divergent AF bins (>95%) or filter AF bins (>97%). Two major bin divergences were resolved by applying the minimal acceptable read-depth threshold. These findings show the importance of assessing read-depth separately for population datasets sourced from different short-read sequencing technologies before assigning a frequency-based ACMG-AMP classification code for variant interpretation.

Uveal melanoma (UM) is the most common intraocular tumour in adults and despite surgical or radiation treatment of primary tumours, ~50% of patients progress to metastatic disease. Therapeutic options for metastatic UM are limited, with clinical trials having little impact. Here we perform whole-genome sequencing (WGS) of 103 UM from all sites of the uveal tract (choroid, ciliary body, iris). While most UM have low tumour mutation burden (TMB), two subsets with high TMB are seen; one driven by germline MBD4 mutation, and another by ultraviolet radiation (UVR) exposure, which is restricted to iris UM. All but one tumour have a known UM driver gene mutation (GNAQ, GNA11, BAP1, PLCB4, CYSLTR2, SF3B1, EIF1AX). We identify three other significantly mutated genes (TP53, RPL5 and CENPE)., Uveal melanoma has a propensity to metastasise. Here, the authors report the whole genome sequence of 103 uveal melanomas and find that the tumour mutational burden is variable and that two subsets of tumours are characterised by MBD4 mutations and a UV exposure signature.

The serrated neoplasia pathway gives rise to a distinct subgroup of colorectal cancers distinguished by the presence of mutant BRAFV600E and the CpG Island Methylator Phenotype (CIMP). BRAF mutant CRC are commonly associated with microsatellite instability, which have an excellent clinical outcome. However, a proportion of BRAF mutant CRC retain microsatellite stability and have a dismal prognosis. The molecular drivers responsible for the development of this cancer subgroup are unknown. To address this, we established a murine model of BRAFV600E mutant microsatellite stable CRC and comprehensively investigated the exome and transcriptome to identify molecular alterations in signaling pathways that drive malignancy. Exome sequencing of murine serrated lesions (mSL) and carcinomas identified frequent hot spot mutations within the gene encoding β-catenin (Ctnnb1). Immunohistochemical staining of β-catenin indicated that these mutations led to an increase in the presence of aberrant nuclear β-catenin that resulted in gene expression changes in targets of β-catenin transcription. Gene expression profiling identified a significant enrichment for transforming growth factor-β (TGF-β) signaling that was present in mSL and carcinomas. Early activation of TGF-β suggests that this pathway may be an early cue directing mSL to microsatellite stable carcinoma. These findings in the mouse model support the importance of alterations in WNT and TGF-β signaling during the transition of human sessile serrated lesions to malignancy. Keywords: BRAF, Colorectal cancer, WNT, TGF-β, Microsatellite

BackgroundEndometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprised of four molecular subtypes with differing etiology, prognoses, and response 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. 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.MethodsHere, we report whole exome or whole genome sequencing of 11 PDX models and the 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 different molecular subtypes of EC.ResultsPDX models were successfully generated from all four molecular subtypes of EC and uterine carcinosarcomas, and they recapitulated morphology and the molecular landscape of primary tumors without major genomic drift. We also observed a wide range of inter-tumor and intra-tumor heterogeneity, well captured by different PDX lineages, which could lead to different treatment responses. An in vivo response to talazoparib was detected in two p53mut models consistent with stable disease, however both lacked the HR deficiency genomic signature.ConclusionsEC PDX models represent the four molecular subtypes of disease and can capture intra-tumoral heterogeneity of the original primary tumor. PDXs of the p53mut molecular subtype showed sensitivity to PARPi, however, deeper and more durable responses will likely require combination of PARPi with other agents.

Here we report the DNA methylation profile of 84 sporadic pancreatic neuroendocrine tumors (PanNETs) with associated clinical and genomic information. We identified three subgroups of PanNETs, termed T1, T2 and T3, with distinct patterns of methylation. The T1 subgroup was enriched for functional tumors and ATRX, DAXX and MEN1 wild-type genotypes. The T2 subgroup contained tumors with mutations in ATRX, DAXX and MEN1 and recurrent patterns of chromosomal losses in half of the genome with no association between regions with recurrent loss and methylation levels. T2 tumors were larger and had lower methylation in the MGMT gene body, which showed positive correlation with gene expression. The T3 subgroup harboured mutations in MEN1 with recurrent loss of chromosome 11, was enriched for grade G1 tumors and showed histological parameters associated with better prognosis. Our results suggest a role for methylation in both driving tumorigenesis and potentially stratifying prognosis in PanNETs., 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.

Treatment for metastatic melanoma includes targeted and/or immunotherapy. Although many patients respond, only a subset has complete response. As late-stage patients often have multiple tumors in difficult access sites, non-invasive techniques are necessary for the development of predictive/prognostic biomarkers. PET/CT scans from 52 patients with stage III/IV melanoma were assessed and CT image parameters were evaluated as prognostic biomarkers. Analysis indicated patients with high standard deviation or high mean of positive pixels (MPP) had worse progression-free survival (P = 0.00047 and P = 0.0014, respectively) and worse overall survival (P = 0.0223 and P = 0.0465, respectively). Whole-exome sequencing showed high MPP was associated with BRAF mutation status (P = 0.0389). RNA-sequencing indicated patients with immune “cold” signatures had worse survival, which was associated with CT biomarker, MPP4 (P = 0.0284). Multiplex immunofluorescence confirmed a correlation between CD8 expression and image biomarkers (P = 0.0028). Implications: CT parameters have the potential to be cost-effective biomarkers of survival in melanoma, and reflect the tumor immune-microenvironment.

Patients with late stage resected cutaneous melanoma have poor overall survival (OS) and experience irreversible adverse events from systemic therapy. There is a clinical need to identify biomarkers to predict outcome. Performing germline/tumour whole-exome sequencing of 44 stage III/IV melanoma patients we identified pathogenic germline mutations in CDKN2A, CDK4, ATM, POLH, MRE11A, RECQL4 and XPC, affecting 7/44 patients. These mutations were associated with poor OS (p = 0.0082). We confirmed our findings in The Cancer Genome Atlas (TCGA) human skin cutaneous melanoma cohort where we identified pathogenic variants in 40/455 patients (p = 0.0203). Combining these cohorts (n = 499) further strengthened these findings showing germline carriers had worse OS (p = 0.0009). Additionally, we determined whether tumour mutation burden (TMB) or BRAF status were prognostic markers of survival. Low TMB rate (p = 0.0034) and BRAF p.V600 mutation (p = 0.0355) were associated with worse progression-free survival. Combining these biomarkers indicated that V600 mutant patients had significantly lower TMB (p = 0.0155). This was confirmed in the TCGA (n = 443, p = 0.0007). Integrative analysis showed germline mutation status conferred the highest risk (HR 5.2, 95% CI 1.72–15.7). Stage IV (HR 2.5, 0.74–8.6) and low TMB (HR 2.3, 0.57–9.4) were similar, whereas BRAF V600 status was the weakest prognostic biomarker (HR 1.5, 95% CI 0.44–5.2).

To increase understanding of the genomic landscape of acral melanoma, a rare form of melanoma occurring on palms, soles or nail beds, whole genome sequencing of 87 tumors with matching transcriptome sequencing for 63 tumors was performed. Here we report that mutational signature analysis reveals a subset of tumors, mostly subungual, with an ultraviolet radiation signature. Significantly mutated genes are BRAF, NRAS, NF1, NOTCH2, PTEN and TYRP1. Mutations and amplification of KIT are also common. Structural rearrangement and copy number signatures show that whole genome duplication, aneuploidy and complex rearrangements are common. Complex rearrangements occur recurrently and are associated with amplification of TERT, CDK4, MDM2, CCND1, PAK1 and GAB2, indicating potential therapeutic options., 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.

Background Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear. Results Using targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants. Conclusions We have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits.

Endometrial cancer is a major gynaecological cancer with a high incidence resulting in over 500 Australian women dying every year. Good pre-clinical models are urgently needed to study the biology of this disease, and to develop and test novel treatment strategies. Most current pre-clinical research is conducted in cell lines that often do not resemble the disease on the molecular level and do not recapitulate tumour heterogeneity, which results in untranslatable research findings. Patient-derived xenograft (PDX) models overcome the issues of representing tumour molecular landscape and heterogeneity, making them a translatable pre-clinical cancer model. Here, we generated and genomically characterised 11 PDX models by performing whole genome or whole exome sequencing of primary patient tumours and matched PDX samples. We performed a detailed genomic characterisation of these models to determine their suitability as pre-clinical models, study tumour heterogeneity and identify biomarkers of response and resistance. PDX models were successfully generated from all four molecular subtypes of EC and uterine carcinosarcomas, and they recapitulated morphology and the molecular landscape of primary tumors without major genomic drift. We also observed a wide range of inter-tumor and intra-tumor heterogeneity, well captured by different PDX lineages, which could lead to different treatment responses. An in vivo response to talazoparib was detected in two p53mut models consistent with stable disease, however both lacked the HR deficiency genomic signature. EC PDX models represent the four molecular subtypes of disease and can capture intra-tumoral heterogeneity of the original primary tumor. PDXs of the p53mut molecular subtype showed sensitivity to PARPi, however, deeper and more durable responses will likely require combination of PARPi with other agents. Citation Format: Olga Kondrashova, Vanessa F. Bonazzi, Deborah Smith, Katia Nones, Asmerom Sengal, Robert Ju, Leisl M. Packer, Lambros T Koufariotis, Stephen H. Kazakoff, Aimee L. Davidson, Priya Ramarao-Milne, Vanessa Lakis, Felicity Newell, Rebecca Rogers, Claire Davies, Naven Chetty, Lewis Perrin, John Pearson, Ann-Marie Patch, Andrea Garrett, Nicola Waddell, Pamela Pollock, James Nicklin. Genomic characterization of endometrial cancer patient-derived xenografts reveals intratumor heterogeneity [abstract]. In: Proceedings of the AACR Virtual Special Conference: Endometrial Cancer: New Biology Driving Research and Treatment; 2020 Nov 9-10. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(3_Suppl):Abstract nr PR007.