Immune checkpoint inhibitor induced thyroid dysfunction is a frequent event post-treatment in NSCLC.

INTRODUCTION: Thyroid dysfunction is the most frequent endocrine immune related adverse event (irAE) in non-small cell lung cancer (NSCLC), typically arising 3-6 months into immune checkpoint inhibitor (ICI) therapy, but arising after ICI cessation, in some cases. Due to limited post-treatment adverse event reporting requirements on ICI trials, the incidence of ICI-induced thyroid dysfunction arising after therapy is unclear. We investigated ICI-induced thyroid dysfunction in a cohort of 294 NSCLC patients, with a specific focus on the post-treatment setting. METHODS: Retrospective analysis of ICI-induced thyroid dysfunction (clinically acted upon or laboratory only) was performed in 294 UCLA NSCLC patients treated 2012-2018. Clinically acted upon thyroid dysfunction was defined as thyroid diagnosis documentation and/or thyroid medication administration. Laboratory only dysfunction was defined as abnormal thyroid labs in the absence of clinical action. Timing of thyroid dysfunction relative to ICI treatment and thyroid monitoring patterns were also assessed. RESULTS: 82% (241/294) of ICI treated NSCLC patients had thyroid labs during treatment. Of these 241 patients, 13% (31/241) had clinically acted upon thyroid dysfunction prior to, 8% (18/241) during, and 4% (9/241) after ICI. Most patients, 66% (159/241), did not have thyroid labs after ICI, but in the 53 patients with labs and no prior clinical dysfunction, 17% (9/53) developed clinical dysfunction after ICI. In these 9 patients, median time from ICI initiation to dysfunction was 253 days. Two patients with post-treatment laboratory only dysfunction were observed. CONCLUSIONS: ICI-induced thyroid dysfunction arising post-treatment appears more common than previously appreciated, warranting additional evaluation.

Mutational landscape influences immunotherapy outcomes among patients with non-small-cell lung cancer with human leukocyte antigen supertype B44.

Human leukocyte antigen (HLA)-B has been recognized as a major determinant of discrepancies in disease outcomes, and recent evidence indicates a role in immune checkpoint blockade (ICB) efficacy. The B44 supertype, which features an electropositive binding pocket that preferentially displays peptides with negatively charged amino acid anchors, is associated with improved survival in ICB-treated melanoma. Yet this effect was not seen in ICB-treated non-small-cell lung cancer (NSCLC). Here we show that mutations leading to glutamic acid substitutions occur more often in melanoma than NSCLC based on mutational landscape. We additionally show stratifying B44 based on the presence of somatic mutations that lead to negatively charged glutamic acid anchors identifies patients with NSCLC with an ICB benefit similar to that seen in melanoma. We anticipate these findings could improve assessment of HLA-related outcomes and prediction of ICB benefit in those with B44, representing approximately half of the world's population.

A statistical validation of the individuality and repeatability of striated tool marks: screwdrivers and tongue and groove pliers.

Tool mark identification relies on the premise that microscopic imperfections on a tool's working surface are sufficiently unique and faithfully transferred to enable a one-to-one association between a tool and the tool marks it creates. This paper presents a study undertaken to assess the validity of this premise. As part of this study sets of striated tool marks were created under different conditions and on different media. The topography of these tool marks was acquired and the degree of similarity between them was quantified using well-defined metrics. An analysis of the resulting matching and nonmatching similarity distributions shows nearly error-free identification under most conditions. These results provide substantial support for the validity of the premise of tool mark identification. Because the approach taken in this study relies on a quantifiable similarity metric, the results have greater repeatability and objectivity than those obtained using less precise measures of similarity.

Pilot study of automated bullet signature identification based on topography measurements and correlations.

A procedure for automated bullet signature identification is described based on topography measurements using confocal microscopy and correlation calculation. Automated search and retrieval systems are widely used for comparison of firearms evidence. In this study, 48 bullets fired from six different barrel manufacturers are classified into different groups based on the width class characteristic for each land engraved area of the bullets. Then the cross-correlation function is applied both for automatic selection of the effective correlation area, and for the extraction of a 2D bullet profile signature. Based on the cross-correlation maximum values, a list of top ranking candidates against a ballistics signature database of bullets fired from the same model firearm is developed. The correlation results show a 9.3% higher accuracy rate compared with a currently used commercial system based on optical reflection. This suggests that correlation results can be improved using the sequence of methods described here.

Development of a 3D-based automated firearms evidence comparison system.

Since the early 1990's, the idea of automated systems for the comparison of microscopic firearms evidence has received considerable attention. The main objective of such systems is to enable the analysis of large amounts of evidence, therefore, transforming the comparison of firearms evidence from an evidence verification tool into a crime-fighting tool. Two such systems have been widely used in United States forensic laboratories: namely, the Integrated Ballistics Identification System (IBIS) (1) and DRUGFIRE (2). Both IBIS and DRUGFIRE have in common the fact that their characterization of a specimen is based on a two-dimensional (2D) representation of the specimen's surface. Although these systems have provided satisfactory results in the identification of cartridge cases, their performance in the identification of bullets has not yet met firearms examiner's expectations. This project was motivated by the premise that a better characterizations of the bullet's surface should translate into better performance of automated identification systems. A three-dimensional (3D) characterization of the bullet's surface is proposed as an alternative to a 2D characterization. This paper discusses the development and preliminary results obtained with SciClops, an automated microscopic comparison system based on the use of a 3D characterization of a bullet's surface.