Annotation and automated segmentation of single-molecule localisation microscopy data.

Single Molecule Localisation Microscopy (SMLM) is becoming a widely used technique in cell biology. After processing the images, the molecular localisations are typically stored in a table as xy (or xyz) coordinates, with additional information, such as number of photons, etc. This set of coordinates can be used to generate an image to visualise the molecular distribution, for example, a 2D or 3D histogram of localisations. Many different methods have been devised to analyse SMLM data, among which cluster analysis of the localisations is popular. However, it can be useful to first segment the data, to extract the localisations in a specific region of a cell or in individual cells, prior to downstream analysis. Here we describe a pipeline for annotating localisations in an SMLM dataset in which we compared membrane segmentation approaches, including Otsu thresholding and machine learning models, and subsequent cell segmentation. We used an SMLM dataset derived from dSTORM images of sectioned cell pellets, stained for the membrane proteins EGFR (epidermal growth factor receptor) and EREG (epiregulin) as a test dataset. We found that a Cellpose model retrained on our data performed the best in the membrane segmentation task, allowing us to perform downstream cluster analysis of membrane versus cell interior localisations. We anticipate this will be generally useful for SMLM analysis.

Increasing frequency of gene copy number aberrations is associated with immunosuppression and predicts poor prognosis in gastric adenocarcinoma.

BACKGROUND: Patients with Epstein-Barr virus-positive gastric cancers or those with microsatellite instability appear to have a favourable prognosis. However, the prognostic value of the chromosomal status (chromosome-stable (CS) versus chromosomal instable (CIN)) remains unclear in gastric cancer. METHODS: Gene copy number aberrations (CNAs) were determined in 16 CIN-associated genes in a retrospective study including test and validation cohorts of patients with gastric cancer. Patients were stratified into CS (no CNA), CINlow (1-2 CNAs) or CINhigh (3 or more CNAs). The relationship between chromosomal status, clinicopathological variables, and overall survival (OS) was analysed. The relationship between chromosomal status, p53 expression, and tumour infiltrating immune cells was also assessed and validated externally. RESULTS: The test and validation cohorts included 206 and 748 patients, respectively. CINlow and CINhigh were seen in 35.0 and 15.0 per cent of patients, respectively, in the test cohort, and 48.5 and 20.7 per cent in the validation cohort. Patients with CINhigh gastric cancer had the poorest OS in the test and validation cohorts. In multivariable analysis, CINlow, CINhigh and pTNM stage III-IV (P < 0.001) were independently associated with poor OS. CIN was associated with high p53 expression and low immune cell infiltration. CONCLUSION: CIN may be a potential new prognostic biomarker independent of pTNM stage in gastric cancer. Patients with gastric cancer demonstrating CIN appear to be immunosuppressed, which might represent one of the underlying mechanisms explaining the poor survival and may help guide future therapeutic decisions.

Spatial profiling of gastric cancer patient-matched primary and locoregional metastases reveals principles of tumour dissemination.

OBJECTIVE: Endoscopic mucosal biopsies of primary gastric cancers (GCs) are used to guide diagnosis, biomarker testing and treatment. Spatial intratumoural heterogeneity (ITH) may influence biopsy-derived information. We aimed to study ITH of primary GCs and matched lymph node metastasis (LNmet). DESIGN: GC resection samples were annotated to identify primary tumour superficial (PTsup), primary tumour deep (PTdeep) and LNmet subregions. For each subregion, we determined (1) transcriptomic profiles (NanoString 'PanCancer Progression Panel', 770 genes); (2) next-generation sequencing (NGS, 225 gastrointestinal cancer-related genes); (3) DNA copy number profiles by multiplex ligation-dependent probe amplification (MLPA, 16 genes); and (4) histomorphological phenotypes. RESULTS: NanoString profiling of 64 GCs revealed no differences between PTsup1 and PTsup2, while 43% of genes were differentially expressed between PTsup versus PTdeep and 38% in PTsup versus LNmet. Only 16% of genes were differently expressed between PTdeep and LNmet. Several genes with therapeutic potential (eg IGF1, PIK3CD and TGFB1) were overexpressed in LNmet and PTdeep compared with PTsup. NGS data revealed orthogonal support of NanoString results with 40% mutations present in PTdeep and/or LNmet, but not in PTsup. Conversely, only 6% of mutations were present in PTsup and were absent in PTdeep and LNmet. MLPA demonstrated significant ITH between subregions and progressive genomic changes from PTsup to PTdeep/LNmet. CONCLUSION: In GC, regional lymph node metastases are likely to originate from deeper subregions of the primary tumour. Future clinical trials of novel targeted therapies must consider assessment of deeper subregions of the primary tumour and/or metastases as several therapeutically relevant genes are only mutated, overexpressed or amplified in these regions.

Correction to: KRAS status is related to histological phenotype in gastric cancer: results from a large multicentre study.

In the original publication of this article, Fig. 2 was published incorrectly. The correct Fig. 2 is given in this correction.

KRAS status is related to histological phenotype in gastric cancer: results from a large multicentre study.

BACKGROUND: Gastric cancer (GC) is histologically a very heterogeneous disease, and the temporal development of different histological phenotypes remains unclear. Recent studies in lung and ovarian cancer suggest that KRAS activation (KRASact) can influence histological phenotype. KRASact likely results from KRAS mutation (KRASmut) or KRAS amplification (KRASamp). The aim of the study was to investigate whether KRASmut and/or KRASamp are related to the histological phenotype in GC. METHODS: Digitized haematoxylin/eosin-stained slides from 1282 GC resection specimens were classified according to Japanese Gastric Cancer Association (JGCA) and the Lauren classification by at least two observers. The relationship between KRAS status, predominant histological phenotype and clinicopathological variables was assessed. RESULTS: KRASmut and KRASamp were found in 68 (5%) and 47 (7%) GCs, respectively. Within the KRASmut and KRASamp cases, the most frequent GC histological phenotype was moderately differentiated tubular 2 (tub2) type (KRASmut: n = 27, 40%; KRASamp: n = 21, 46%) or intestinal type (KRASmut: n = 41, 61%; KRASamp: n = 23, 50%). Comparing individual histological subtypes, mucinous carcinoma displayed the highest frequency of KRASmut (JGCA: n = 6, 12%, p = 0.012; Lauren: n = 6, 12%, p = 0.013), and KRASamp was more frequently found in poorly differentiated solid type (n = 12, 10%, p = 0.267) or indeterminate type (n = 12, 10%, p = 0.480) GC. 724 GCs (57%) had intratumour morphological heterogeneity. CONCLUSIONS: This is the largest GC study investigating KRAS status and histological phenotype. We identified a relationship between KRASmut and mucinous phenotype. The high level of intratumour morphological heterogeneity could reflect KRASmut heterogeneity, which may explain the failure of anti-EGFR therapy in GC.

Frequent Coamplification of Receptor Tyrosine Kinase and Downstream Signaling Genes in Japanese Primary Gastric Cancer and Conversion in Matched Lymph Node Metastasis.

OBJECTIVE: To establish the gene copy number status of receptor tyrosine kinase (RTK) and downstream signaling (DSS) genes genes in primary gastric cancer (primGC) and matched lymph node metastases (LNmet). BACKGROUND: Evidence suggests that coamplification between RTKs and DSSs and conversion between primGC and LNmet are associated with resistance to targeted therapy. METHODS: DNA from 237 Japanese primGC and 103 matched LNmet was analyzed using a newly developed multiplex ligation-dependent probe amplification (MLPA) probemix to investigate RTK (EGFR, HER2, FGFR2, and MET) and DSS (PIK3CA, KRAS, MYC, and CCNE1) gene copy number status. Results were compared between primGC and LNmet and related to clinicopathological data including survival. RESULTS: A total of 150 (63%) primGC had either RTK or DSS amplification. DSS coamplification was more frequent than RTK coamplification in primGC and LNmets. Moreover, 70 (30%) GC showed a disconcordant RTK and/or DSS gene copy number status between primGC and LNmet, most common was negative conversion for DSS genes (n=40 GC). The presence of RTK amplification in primGC was related to poorer survival in univariate analysis (P=0.04). CONCLUSIONS: This is the first and most comprehensive study in gastric cancer investigating the concordance between gene copy number status of targetable RTKs and downstream signaling oncogenes in primGC and LNmets. Future studies need to establish whether the relative high frequency of RTK and DSS coamplification and/or the relative high rate of negative conversion in LNmet can potentially explain recent failures of RTK targeted therapy in gastric cancer patients.

Adaptor Template Oligo-Mediated Sequencing (ATOM-Seq) is a new ultra-sensitive UMI-based NGS library preparation technology for use with cfDNA and cfRNA.

Liquid biopsy testing utilising Next Generation Sequencing (NGS) is rapidly moving towards clinical adoption for personalised oncology. However, before NGS can fulfil its potential any novel testing approach must identify ways of reducing errors, allowing separation of true low-frequency mutations from procedural artefacts, and be designed to improve upon current technologies. Popular NGS technologies typically utilise two DNA capture approaches; PCR and ligation, which have known limitations and seem to have reached a development plateau with only small, stepwise improvements being made. To maximise the ultimate utility of liquid biopsy testing we have developed a highly versatile approach to NGS: Adaptor Template Oligo Mediated Sequencing (ATOM-Seq). ATOM-Seq's strengths and versatility avoid the major limitations of both PCR- and ligation-based approaches. This technology is ligation free, simple, efficient, flexible, and streamlined, and it offers novel advantages that make it perfectly suited for use on highly challenging clinical material. Using reference and clinical materials, we demonstrate detection of known SNVs down to allele frequencies of 0.1% using as little as 20-25 ng of cfDNA, as well as the ability to detect fusions from RNA. We illustrate ATOM-Seq's suitability for clinical testing by showing high concordance rates between paired cfDNA and FFPE clinical samples.