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Trunk alterations arise at early stages of cancer and are shared among all malignant cells of the tumor. In order to identify trunk alterations in HCC, we characterized early stages of hepatocarcinogenesis represented by dysplastic nodules and small lesions. Mutations in TERT, TP53 and CTNNB1 genes were the most frequent. Analyses in more advanced lesions showed that mutations in these same genes were shared between different regions of the same tumor and between primary and metastatic tumors, suggesting their trunk role in this disease.

Intratumor heterogeneity (ITH) contributes to cancer progression and chemoresistance. We sought to comprehensively describe ITH of somatic mutations, copy number, and transcriptomic alterations involving clinically and biologically relevant gene pathways in colorectal cancer (CRC). We performed multiregion, high‐depth (384× on average) sequencing of 799 cancer‐associated genes in 24 spatially separated primary tumor and nonmalignant tissues from four treatment‐naïve CRC patients. We then used ultra‐deep sequencing (17 075× on average) to accurately verify the presence or absence of identified somatic mutations in each sector. We also digitally measured gene expression and copy number alterations using NanoString assays. We identified the subclonal point mutations and determined the mutational timing and phylogenetic relationships among spatially separated sectors of each tumor. Truncal mutations, those shared by all sectors in the tumor, affected the well‐described driver genes such as APC, TP53, and KRAS. With sequencing at 17 075×, we found that mutations first detected at a sequencing depth of 384× were in fact more widely shared among sectors than originally assessed. Interestingly, ultra‐deep sequencing also revealed some mutations that were present in all spatially dispersed sectors, but at subclonal levels. Ultra‐high‐depth validation sequencing, copy number analysis, and gene expression profiling provided a comprehensive and accurate genomic landscape of spatial heterogeneity in CRC. Ultra‐deep sequencing allowed more sensitive detection of somatic mutations and a more accurate assessment of ITH. By detecting the subclonal mutations with ultra‐deep sequencing, we traced the genomic histories of each tumor and the relative timing of mutational events. We found evidence of early mixing, in which the subclonal ancestral mutations intermixed across the sectors before the acquisition of subsequent nontruncal mutations. Our findings also indicate that different CRC patients display markedly variable ITH, suggesting that each patient's tumor possesses a unique genomic history and spatial organization.

Circulating tumour DNA (ctDNA) has the potential to be a specific biomarker for the monitoring of tumours in patients with colorectal cancer (CRC). Here, our aim was to develop a personalised surveillance strategy to monitor the clinical course of CRC after surgery. We developed patient-specific ctDNA assays based on multiplexed detection of somatic mutations identified from patient primary tumours, and applied them to detect ctDNA in 44 CRC patients, analysing a total of 260 plasma samples. We found that ctDNA detection correlated with clinical events – it is detectable in pre-operative but not post-operative plasma, and also in patients with recurrent CRC. We also detected ctDNA in 11 out of 15 cases at or before clinical or radiological recurrence of CRC, indicating the potential of our assay for early detection of metastasis. We further present data from a patient with multiple primary cancers to demonstrate the specificity of our assays to distinguish between CRC recurrence and a second primary cancer. Our approach can complement current methods for surveillance of CRC by adding an individualised biological component, allowing us not only to point to the presence of residual or recurrent disease, but also attribute it to the original cancer.

BackgroundAssessment of severity of liver fibrosis is essential in the management of non-alcoholic fatty liver disease (NAFLD). Second Harmonic Generation (SHG) microscopy is a novel optical tissue imaging system that provides automated quantification of fibrosis based on unique architectural features of collagen. This study aims to develop and validate a SHG-based index for automated staging of liver fibrosis in patients with NAFLD.MethodsSHG microscopy was performed on archived liver biopsy specimens from 83 patients with NAFLD. A unique algorithm was developed to identify specific SHG parameters that correlated with fibrosis stage. The accuracy of the algorithm was compared against clinical assessment by experienced liver histopathologists using the Brunt fibrosis staging and further validated using the leave-one-out cross-validation method.ResultsMean age of the study cohort was 51.8 ± 11.7 years, with 41% males. A fibrosis index (SHG B-index) was developed comprising 14 unique SHG-based collagen parameters that correlated with severity of NAFLD fibrosis in a continuous fashion. The SHG B-index had excellent correlation with Brunt fibrosis stage (Spearman’s correlation 0.820, p<0.001). AUROCs for prediction of Brunt fibrosis stages 1, 2, 3 and 4 were 0.853, 0.967, 0.985 and 0.941 respectively. In the cross-validation analysis, the SHG B-index demonstrated high specificity for diagnosis of all grades of fibrosis. A SHG B-index score of >1.76 had an overall diagnostic accuracy of 98.5% for prediction of presence of bridging fibrosis (Brunt stage ≥3) with sensitivity of 87.5%, specificity 98.0%, positive predictive value 96.6% and negative predictive value 92.6%.ConclusionThe SHG B-index is a unique SHG-based index that provides accurate automated assessment of fibrosis stage in NAFLD patients.

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This work established proof-of-principle for GC/TOFMS-based global metabotyping of PDAC and laid the foundation for future discovery of metabolic biomarkers predictive of gemcitabine resistance in PDAC chemotherapy.