The path to a better biomarker: Application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice

Immune checkpoint inhibitor therapies targeting PD-1/PD-L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD-L1 expression on immune cells occupying 651% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab-paclitaxel. However, concerns regarding variability between immunohistochemical PD-L1 assay performance and inter-reader reproducibility have been raised. High tumor-infiltrating lymphocytes (TILs) have also been associated with response to PD-1/PD-L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin\u2013stained slides and have shown reliable inter-reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD-L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD-L1 and TIL analyses as a more comprehensive immuno-oncological biomarker for patient selection for PD-1/PD-L1 inhibition-based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk-management framework that may help mitigate the risks of suboptimal patient selection for immuno-therapeutic approaches in clinical trials and daily practice based on combined TILs/PD-L1 assessment in BC. \ua9 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd

Improved canine exome designs, featuring ncRNAs and increased coverage of protein coding genes OPEN

By limiting sequencing to those sequences transcribed as mRNA, whole exome sequencing is a costefficient technique often used in disease-association studies. We developed two target enrichment designs based on the recently released annotation of the canine genome: the exome-plus design and the exome-CDS design. The exome-plus design combines the exons of the CanFam 3.1 Ensembl annotation, more recently discovered protein-coding exons and a variety of non-coding RNA regions (microRNAs, long non-coding RNAs and antisense transcripts), leading to a total size of ≈152 Mb. The exome-CDS was designed as a subset of the exome-plus by omitting all 3' and 5' untranslated regions. This reduced the size of the exome-CDS to ≈71 Mb. To test the capturing performance, four exome-plus captures were sequenced on a NextSeq 500 with each capture containing four precapture pooled, barcoded samples. At an average sequencing depth of 68.3x, 80% of the regions and well over 90% of the targeted base pairs were completely covered at least 5 times with high reproducibility. Based on the performance of the exome-plus, we estimated the performance of the exome-CDS. Overall, these designs provide flexible solutions for a variety of research questions and are likely to be reliable tools in disease studies. In 2014, the first report detailing the design and performance of a whole exome sequencing (WES) enrichment assay for the dog was published by our group 1 . Aiming to selectively sequence all the regions that are transcribed to mRNA, WES is a reliable tool used to identify disease-causing or predisposing mutations at a fraction of the price of whole genome sequencing (WGS) studies. A limitation of WES is that it is based on our current knowledge of the annotation of the genome and that many disease causing mutations are likely to fall outside protein-coding regions. With new information becoming available, updates and extensions are required. Recently, an improved annotation for the dog genome has been published and new data on non-protein coding genes has been obtained 2 . Based on this data, two new target enrichment designs for dogs, called the exome-plus and the exome-CDS, were developed. The exome-plus offers the most comprehensive design. The exome-CDS is a subset of the exome-plus, focusing on the coding DNA sequences (CDS) by excluding the 3′ and 5′ untranslated regions (UTRs). Thes

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland

Classification of feline hypertrophic cardiomyopathy-associated gene variants according to the American College of Medical Genetics and Genomics guidelines

IntroductionThe correct labeling of a genetic variant as pathogenic is important as breeding decisions based on incorrect DNA tests can lead to the unwarranted exclusion of animals, potentially compromising the long-term health of a population. In human medicine, the American college of Medical Genetics (ACMG) guidelines provide a framework for variant classification. This study aims to apply these guidelines to six genetic variants associated with hypertrophic cardiomyopathy (HCM) in certain cat breeds and to propose a modified criterion for variant classification.MethodsGenetic samples were sourced from five cat breeds: Maine Coon, Sphynx, Ragdoll, Devon Rex, and British Short- and Longhair. Allele frequencies were determined, and in the subset with phenotypes available, odds ratios to determine the association with HCM were calculated. In silico evaluation followed with joint evidence and data from other publications assisting in the classification of each variant.ResultsTwo variants, MYBPC3:c.91G > C [A31P] and MYBPC3:c.2453C > T [R818W], were designated as pathogenic. One variant, MYH7:c.5647G > A [E1883K], was found likely pathogenic, while the remaining three were labeled as variants of unknown significance.DiscussionRoutine genetic testing is advised solely for the MYBPC3:c.91G > C [A31P] in the Maine Coon and MYBPC3:c.2453C > T [R818W] in the Ragdoll breed. The human ACMG guidelines serve as a suitable foundational tool to ascertain which variants to include; however, refining them for application in veterinary medicine might be beneficial

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)