Impact of SARS-CoV-2 Pandemic on Vascular Liver Diseases.

BACKGROUND & AIMS: Vascular liver diseases (VLDs) are represented mainly by portosinusoidal vascular disease (PSVD), noncirrhotic splanchnic vein thrombosis (SVT), and Budd Chiari syndrome (BCS). It is unknown whether patients with VLDs constitute a high-risk population for complications and greater coronavirus disease 2019 (COVID-19)-related mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our objective was to assess the prevalence and severity of SARS-CoV-2 infection among patients with VLDs, as well as to assess its impact on hepatic decompensation and survival. METHODS: This is an observational international study analyzing the prevalence and severity of SARS-CoV-2 infection in VLDs between March 2020 and March 2021, compared with the general population (GP). Patients from Spain (5 centers; n = 493) and France (1 center; n = 475) were included. RESULTS: Nine hundred sixty-eight patients were included: 274 with PSVD, 539 with SVT, and 155 with BCS. Among them, 138 (14%) were infected with SARS-CoV-2: 53 with PSVD, 77 with SVT, and 8 with BCS. The prevalence of SARS-CoV-2 infection in patients with PSVD (19%) and SVT (14%) was significantly higher than in the GP (6.5%; P < .05), whereas it was very similar in patients with BCS (5%). In terms of infection severity, patients with VLDs also presented a higher need of hospital admission (14% vs 7.3%; P < .01), intensive care unit admission (2% vs 0.7%; P < .01), and mortality (4% vs 1.5%; P < .05) than the GP. Previous history of ascites (50% vs 8%; P < .05) and post-COVID-19 hepatic decompensation (50% vs 4%; P < .05) were associated with COVID-19 mortality. CONCLUSIONS: Patients with PSVD and SVT could be at higher risk of infection by SARS-CoV-2 and at higher risk of severe COVID-19 disease.

Pixelwise H-score: A novel digital image analysis-based metric to quantify membrane biomarker expression from immunohistochemistry images.

Immunohistochemistry (IHC) assays play a central role in evaluating biomarker expression in tissue sections for diagnostic and research applications. Manual scoring of IHC images, which is the current standard of practice, is known to have several shortcomings in terms of reproducibility and scalability to large scale studies. Here, by using a digital image analysis-based approach, we introduce a new metric called the pixelwise H-score (pix H-score) that quantifies biomarker expression from whole-slide scanned IHC images. The pix H-score is an unsupervised algorithm that only requires the specification of intensity thresholds for the biomarker and the nuclear-counterstain channels. We present the detailed implementation of the pix H-score in two different whole-slide image analysis software packages Visiopharm and HALO. We consider three biomarkers P-cadherin, PD-L1, and 5T4, and show how the pix H-score exhibits tight concordance to multiple orthogonal measurements of biomarker abundance such as the biomarker mRNA transcript and the pathologist H-score. We also compare the pix H-score to existing automated image analysis algorithms and demonstrate that the pix H-score provides either comparable or significantly better performance over these methodologies. We also present results of an empirical resampling approach to assess the performance of the pix H-score in estimating biomarker abundance from select regions within the tumor tissue relative to the whole tumor resection. We anticipate that the new metric will be broadly applicable to quantify biomarker expression from a wide variety of IHC images. Moreover, these results underscore the benefit of digital image analysis-based approaches which offer an objective, reproducible, and highly scalable strategy to quantitatively analyze IHC images.

Detecting expression of 5T4 in CTCs and tumor samples from NSCLC patients.

The fetal oncogene 5T4 is a cell surface protein, with overexpression observed in a variety of cancers as compared to normal adult tissue. The ability to select patients with tumors that express high levels of 5T4 may enrich a clinical trial cohort with patients most likely to respond to 5T4 targeted therapy. To that end, we developed assays to measure 5T4 in both tumors and in circulating tumor cells (CTCs). We identified the presence of 5T4 in both adenocarcinoma and squamous cell carcinoma of lung, in all clinical stages and grades of disease. CTCs were identified in peripheral blood from the majority of patients with NSCLC, and 5T4 was detectable in most samples. Although 5T4 was present in both CTCs and tumors in most patients, there was no concordance between relative amount in either sample type. Clinical response rates of patients treated with the therapies directed against 5T4 in early stage clinical trials, as determined by these assays, may provide important insights into the biology of 5T4 in tumors and the mechanisms of action of 5T4-targeting therapy.

Multiplexed deep sequencing analysis of ALK kinase domain identifies resistance mutations in relapsed patients following crizotinib treatment.

The recently approved ALK kinase inhibitor crizotinib has demonstrated successful treatment of metastatic and late stage ALK fusion positive non-small cell lung cancer (NSCLC). However, the median duration of clinical benefit is ~10-11months due to the emergence of multiple and simultaneous resistance mechanisms in these tumors. Mutations in the ALK kinase domain confer resistance to crizotinib in about one-third of these patients. We developed a multiplex deep sequencing method using semiconductor sequencing technology to quickly detect resistance mutations within the ALK kinase domain from tumor biopsies. By applying a base-pair specific error-weighted mutation calling algorithm (BASCA) that we developed for this assay, genomic DNA analysis from thirteen relapsed patients revealed three known crizotinib resistance mutations, C1156Y, L1196M and G1269A. Our assay demonstrates robust and sensitive detection of ALK kinase mutations in NSCLC tumor samples and aids in the elucidation of resistance mechanisms pertinent to the clinical setting.