Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

pyAmpli : an amplicon-based variant filter pipeline for targeted resequencing data

Abstract Background Haloplex targeted resequencing is a popular method to analyze both germline and somatic variants in gene panels. However, involved wet-lab procedures may introduce false positives that need to be considered in subsequent data-analysis. No variant filtering rationale addressing amplicon enrichment related systematic errors, in the form of an all-in-one package, exists to our knowledge. Results We present pyAmpli, a platform independent parallelized Python package that implements an amplicon-based germline and somatic variant filtering strategy for Haloplex data. pyAmpli can filter variants for systematic errors by user pre-defined criteria. We show that pyAmpli significantly increases specificity, without reducing sensitivity, essential for reporting true positive clinical relevant mutations in gene panel data. Conclusions pyAmpli is an easy-to-use software tool which increases the true positive variant call rate in targeted resequencing data. It specifically reduces errors related to PCR-based enrichment of targeted regions

RUNX2-related metaphyseal dysplasia with maxillary hypoplasia : a rare skeletal disorder resembling SFRP4-related Pyle disease

Abstract: Metaphyseal dysplasia with maxillary hypoplasia with or without brachydactyly (MDMHB) is an ultra-rare skeletal dysplasia caused by heterozygous intragenic RUNX2 duplications, comprising either exons 3 to 5 or exons 3 to 6 of RUNX2. In this study, we describe a 14-year-old Belgian boy with metaphyseal dysplasia with maxillary hypoplasia but without brachydactyly. Clinical and radiographic examination revealed mild facial dysmorphism, dental anomalies, enlarged clavicles, genua valga and metaphyseal flaring and thin cortices with an osteoporotic skeletal appearance. Exome sequencing led to the identification of a de novo heterozygous tandem duplication within RUNX2, encompassing exons 3 to 7. This duplication is larger than the ones previously reported in MDMHB cases since it extends into the C-terminal activation domain of RUNX2. We review previously reported cases with MDMHB and highlight the resemblance of this disorder with Pyle disease, which may be explained by intersecting molecular pathways between RUNX2 and sFRP4. This study expands our knowledge on the genotypic and phenotypic characteristics of MDMHB and the role of RUNX2 in rare bone disorders

Use of compound-specific nitrogen (d15N), oxygen (d18O), and bulk boron (d11B) isotope ratios to identify sources of nitrate-contaminated waters: a guideline to identify polluters

The use of various isotopes (d(15)N, d(18)O & d(11)B) to identify the sources of nitrate (NO3-) present in natural waters is described. Then a new guideline of how to apply the multi-isotope approach is presented. This guideline is written for policy makers and scientists who are involved in the different steps and processes related to nitrate contaminated waters including monitoring and data interpretation. NO3- is a common pollutant in water (both surface and groundwater). In several water bodies over Europe, point measurements identify that the level of this pollutant is higher than the reference value of 50 mgL(-1), defined by the European Union (EU) Water Framework Directive 2000/60/EC (European Parliament, 2000). This directive also states that all waters have to reach a "good status" (i.e., good quality) by 2015. This statement implies that EU member states have to take actions to achieve this goal. One of the major obstacles with NO3- contamination in water is the identification of the corresponding source(s) of pollution, a prerequisite for properly designing appropriate actions and remediation. Recent studies have proven the added value of analyzing compound specific isotopic signature (CSIA) of nitrate (both nitrogen (d(15)N), oxygen (d(18)O) and bulk boron (d(11)B) isotopic composition) to define the origin/source of NO3- in waters. This definition is possible because different sources of nitrate have distinct isotopic signatures. The recent EU-LIFE ISONITRATE project demonstrated the benefit of the multi-isotope approach, while the presented guideline to implement this method is one of the outcomes of this project. More details on the scientific results of ISONITRATE are available at http://isonitrate.brgm.fr/