Prognostic Threshold for Circulating Tumor Cells in Patients With Pancreatic and Midgut Neuroendocrine Tumors

BACKGROUND: Circulating tumour cells (CTCs) are detectable in patients with NET and are accurate prognostic markers although the optimum threshold has not been defined. OBJECTIVE: To define optimal prognostic CTC threshold in pancreatic and midgut NET. PATIENTS AND METHODS: CellSearch was used to enumerate CTCs in 199 patients with metastatic pancreatic (PanNET) (90) or midgut NET (109). Patients were followed for progression free survival (PFS) and overall survival (OS) for a minimum of 3 years or until death. RESULTS: AUROC for progression at 12 months in PanNET and midgut NET identified the optimal CTC threshold as ≥1 and ≥2 respectively. In multivariate logistic regression analysis, these thresholds were predictive for 12 month progression with OR of 6.69 (p< 0.01) for PanNET and 5.88 (p<0.003) for midgut. The same thresholds were found to be optimal for predicting death at 36 months with an OR of 2.87 (p< 0.03) and 5.09 (p<0.005) for PanNET and midgut NET respectively. In multivariate Cox hazard regression analysis for PFS in PanNET, ≥ 1 CTC had HR 2.6 (p <0.01) whilst ≥ 2 CTCs had HR 2.25 (p < 0.01) in midgut NET. In multivariate analysis OS in PanNET, ≥ 1 CTC had HR 3.16 (p < 0.01) and in midgut NET, ≥ 2 CTCs had HR of 1.73 (p < 0.06). CONCLUSIONS: The optimal CTC threshold to predict PFS and OS in metastatic PanNET and midgut NET is 1 and 2, respectively. These thresholds can be used to stratify patients in clinical practice and clinical trials

Expression of somatostatin receptors 2 and 5 in circulating tumour cells from patients with neuroendocrine tumours.

BACKGROUND: Neuroendocrine tumours (NET) overexpress somatostatin receptors (SSTR) that can be targeted for therapy. Somatostatin receptor expression is routinely measured by molecular imaging but the resolution is insufficient to define heterogeneity. We hypothesised that SSTR expression could be measured on circulating tumour cells (CTCs) and used to investigate heterogeneity of expression and track changes during therapy. METHODS: MCF-7 cells were transfected with SSTR2 or 5 and spiked into donor blood for analysis by CellSearch. Optimum anti-SSTR antibody concentration and exposure time were determined, and flow cytometry was used to evaluate assay sensitivity. For clinical evaluation, blood was analysed by CellSearch, and SSTR2/5 immunohistochemistry was performed on matched tissue samples. RESULTS: Flow cytometry confirmed CellSearch was sensitive and that detection of SSTR was unaffected by the presence of somatostatin analogue up to a concentration of 100 ng ml(-l). Thirty-one NET patients were recruited: grade; G1 (29%), G2 (45%), G3 (13%), primary site; midgut (58%), pancreatic (39%). Overall, 87% had SSTR-positive tumours according to somatostatin receptor scintigraphy or 68-Ga-DOTATE PET/CT. Circulating tumour cells were detected in 21 out of 31 patients (68%), of which 33% had evidence of heterogeneous expression of either SSTR2 (n=5) or SSTR5 (n=2). CONCLUSIONS: Somatostatin receptors 2 and 5 are detectable on CTCs from NET patients and may be a useful biomarker for evaluating SSTR-targeted therapies and this is being prospectively evaluated in the Phase IV CALMNET trial (NCT02075606)

Whole genome sequencing of single circulating tumor cells from neuroendocrine neoplasms

Single-cell profiling of circulating tumor cells (CTCs) as part of a minimally invasive liquid biopsy presents an opportunity to characterize and monitor tumor heterogeneity and evolution in individual patients. In this study, we aimed to compare single-cell copy number variation (CNV) data with tissue, and define the degree of intra- and inter-patient genomic heterogeneity. We performed next generation sequencing (NGS) whole genome CNV analysis of 125 single CTCs derived from seven patients with neuroendocrine neoplasms (NEN) alongside matched white blood cells (WBC), formalin fixed paraffin embedded (FFPE) and fresh frozen (FF) samples. CTC CNV profiling demonstrated recurrent chromosomal alterations in previously reported NEN copy number hotspots, including the prognostically relevant loss of chromosome 18. Unsupervised hierarchical clustering revealed CTCs with distinct clonal lineages as well as significant intra- and inter-patient genomic heterogeneity, including subclonal alterations not detectable by bulk analysis and previously unreported in NEN. Notably, we also demonstrate the presence of genomically distinct CTCs according to the enrichment strategy utilized (EpCAM-dependent versus size-based). This work has significant implications for the identification of therapeutic targets, tracking of evolutionary change and the implementation of CTC-biomarkers in cancer

Enumeration and Molecular Characterisation of Circulating Tumour Cells in Endometrial Cancer

BACKGROUND: This is a feasibility study to determine whether circulating tumour cells (CTCs) are detectable and suitable for molecular profiling in advanced endometrial cancer (aEC). METHOD: Between October 2012 and February 2014, 30 patients with aEC had baseline and up to 3 follow-up samples. CTCs and stathmin expression were evaluated using the CellSearch platform. Epithelial cell adhesion molecule (EpCAM) and stathmin immunohistochemistry were performed on FFPE tumour tissue. RESULTS: Eighteen from 30 (60%) patients had detectable CTCs during study [1 CTC (n = 7), 2 (n = 4), 3 (n = 1), 4 (n = 2), 7 (n = 1), 8 (n = 1), 22 (n = 1), 172 (n = 1) in 7.5 ml blood]. Ten from 18 patients had between 50 and 100% of detectable CTCs that were stathmin positive. More CTC-positive than CTC-negative patients had non-endometrioid versus endometrioid histology, tumour size ≥5 versus 0.05, 95% confidence interval 0.7-16.2]. Twenty-one tumour blocks were tested for EpCAM and stathmin immunohistochemistry (IHC). Stathmin tumour immunostaining scores (TIS) on IHC were higher in CTC-positive patients. CONCLUSION: CTC enumeration and molecular profiling with stathmin on the CellSearch platform is feasible in aEC. Stathmin TIS on IHC, a known prognostic marker in EC, was associated with CTC positivity

Circulating tumour cells and their association with bone metastases in patients with neuroendocrine tumours

BACKGROUND: Bone metastases are associated with a worse outcome in patients with neuroendocrine tumours (NETs). Tumour overexpression of C-X-C chemokine receptor 4 (CXCR4) appears predictive of skeletal involvement. We investigated the role of circulating tumour cells (CTCs) and CXCR4 expression on CTCs as potential predictors of skeleton invasion. METHODS: Blood from patients with metastatic bronchial, midgut or pancreatic NET (pNET) was analysed by CellSearch. CXCR4 immunohistochemistry was performed on matched formalin-fixed paraffin-embedded (FFPE) samples. RESULTS: Two hundred and fifty-four patients were recruited with 121 midgut and 119 pNETs, of which 51 and 36% had detectable CTCs, respectively. Bone metastases were reported in 30% of midgut and 23% of pNET patients and were significantly associated with CTC presence (p = 0.003 and p < 0.0001). In a subgroup of 40 patients, 85% patients with CTCs had CTCs positive for CXCR4 expression. The proportion of CXCR4-positive CTCs in patients with bone metastases was 56% compared to 35% in those without (p = 0.18) it. Staining for CXCR4 on matched FFPE tissue showed a trend towards a correlation with CXCR4 expression on CTCs (p = 0.08). CONCLUSIONS: CTC presence is associated with bone metastases in NETs. CXCR4 may be involved in CTC osteotropism and present a therapeutic target to reduce skeletal morbidity

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Recurrent SARS-CoV-2 mutations in immunodeficient patients

Long-term severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in immunodeficient patients are an important source of variation for the virus but are understudied. Many case studies have been published which describe one or a small number of long-term infected individuals but no study has combined these sequences into a cohesive dataset. This work aims to rectify this and study the genomics of this patient group through a combination of literature searches as well as identifying new case series directly from the COVID-19 Genomics UK (COG-UK) dataset. The spike gene receptor-binding domain and N-terminal domain (NTD) were identified as mutation hotspots. Numerous mutations associated with variants of concern were observed to emerge recurrently. Additionally a mutation in the envelope gene, T30I was determined to be the second most frequent recurrently occurring mutation arising in persistent infections. A high proportion of recurrent mutations in immunodeficient individuals are associated with ACE2 affinity, immune escape, or viral packaging optimisation.There is an apparent selective pressure for mutations that aid cell–cell transmission within the host or persistence which are often different from mutations that aid inter-host transmission, although the fact that multiple recurrent de novo mutations are considered defining for variants of concern strongly indicates that this potential source of novel variants should not be discounted. © The Author(s) 2022. Published by Oxford University Press

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population