Citations

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Lung Cancer Screening provide criteria for selecting individuals for screening and offer recommendations for evaluating and managing lung nodules detected during initial and subsequent annual screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.

ABSTRACT In our efforts to enhance sensitivity to PARP inhibitors, we identified clofarabine (CLF) as a potential therapy for drug-resistant ovarian cancer and nuclear trafficking of Cathepsin L (CTSL) as a treatment- responsive biomarker. Using PARP inhibitor-sensitive and -resistant OC cell lines, ex vivo cultures of patient-derived ovarian ascites (OVA), primary ovarian tumors, and xenografts (PDX), we found that CLF monotherapy induces nuclear CTSL (nCTSL) in CLF-responsive cells (CLF-r) and sensitizes them to PARP inhibitors olaparib and rucaparib. In CLF non-responsive cells (CLF-nr), a combination of CLF with olaparib is necessary for nCTSL trafficking and synergy. CLF+olaparib synergy was observed in 47% of CLF-r and 24% of CLF-nr OVA samples. Drug-induced nCTSL is crucial for DNA damage response, including cell cycle arrest and apoptosis. Knockdown of CTSL in both CLF-r and CLF-nr cells conferred resistance to the CLF+olaparib combination, emphasizing nCTSL’s role in the DNA damage response pathway (DDR). Mechanistically, CLF facilitates CTSL nuclear import via KPNB1 in CLF-r cells. In CLF-nr cells, both olaparib and CLF are needed to facilitate CTSL nuclear import. Additionally, CLF downregulates the nuclear export protein CRM1 (XPO1) in both cohorts. Interestingly, CLF does not downregulate CRM1 in a subset of OVAs (29%), and they were classified as CLF-resistant (CLF- Res). In these samples, inhibiting CRM1 with KPT8602 restored synergy between CLF and PARP inhibitors. In vivo, CLF-r and CLF-nr PDX models exhibited enhanced DDR, reduced tumor burden, and prolonged survival with the CLF+olaparib combination. These findings suggest the CLF+olaparib combination is a promising therapeutic strategy for drug-resistant OC by inducing DDR through CTSL nuclear localization.

Background: Cerebral venous sinus thrombosis (CVT) is a rare cause of stroke, constituting 0.5–3% of all strokes with an extremely varied spectrum of presentation, predisposing factors, neuroimaging findings, and eventual outcomes. A high index of suspicion is needed because timely diagnosis can significantly alter the natural course of the disease, reduce acute complications, and improve long-term outcomes. Due to its myriad causative factors, protean presentation, and association with several systemic diseases, CVT is encountered not only by neurologists but also by emergency care practitioners, internists, hematologists, obstetricians, and pediatricians. Discussion: Anticoagulation remains the mainstay of treatment for CVT. Heparin and warfarin previously had been the anticoagulation of choice. Recently there has been an increased interest in utilizing direct-acting oral anticoagulants in the treatment of CVT given comparable safety and efficacy with ease of utilization. However recent clinical guidelines given by multiple societies including the American Stroke guidelines and European guidelines do not include these agents so far in their treatment recommendations. Ongoing multicentric clinical trials are currently reviewing the role of these agents in both short-term as well as long-term. Our review of the literature supports the safety and reinforces the efficacy of DOAC in the treatment of CVT. Additionally, patient satisfaction has been shown to be better with the use of DOAC. In conclusion, DOAC continues to have a valid role in the management of CVT.

AbstractBackgroundThe residual approach has found wide application in researching cognitive resilience, a phenomenon conceptually understood as cognitive performance being better‐than‐typical for an individual, despite apparent AD pathology. The standard residual approach extracts information about an individual’s resilience from the residuals of a linear model predicting cognition. This approach is subject to several limiting assumptions. Here, we explore the implications of these assumptions and propose an alternative predictive modeling approach which circumvents them.MethodsOur alternative approach relies on training a machine learning model on a sample of participants who follow a “typical” clinical progression (Fig. 1A). Residuals are then extracted for a heterogeneous dataset that potentially includes resilient participants by comparing observed cognitive outcomes to those predicted by the “typical” model (Fig. 1B). Additionally, our estimate can be refined by effectively estimating and removing model error from the extracted residual by leveraging a second predictive model (Fig. 1C). Using simulated data, we explore the assumptions made by the standard approach and the consequences of their violation. We then contrast this against our approach.ResultsOur simulations demonstrated that the standard residual approach only extracted accurate resilience estimates if the predictors used in the model explained cognition sufficiently well, while being unrelated to resilience itself. That is, as the predictors explain more of the resilience, the residuals became increasingly determined by model error (Fig. 2). We found that residuals achieved with our approach are more precise and provide individualized estimates that are unaffected by the aforementioned trade‐off (Fig. 3).ConclusionsOur approach holds several advantages over the standard approach: The definition of resilience can be freely adjusted and enforced via different definitions of “typical”, it allows for incorporating complex, non‐linear models without removing relevant information from the residual, the error component of the residual can be estimated through cross‐validation, and all predictors that potentially explain cognition can be included into the model without losing resilience information from the residual. Our approach can be used to measure any phenomenon that can be operationalized as a deviation from a typical outcome and, thus, is also applicable for researching resistance to pathology.

Abstract High-dose methotrexate (MTX) results in high rates of acute kidney injury (AKI), neutropenia, and hepatotoxicity. Glucarpidase is a recombinant enzyme that cleaves MTX, but clinical data supporting its use are scarce. We examined the association between glucarpidase administration and outcomes in adults with MTX-AKI from 28 cancer centers across the United States using a sequential target trial emulation framework. The primary end point was kidney recovery at hospital discharge, defined as survival to discharge with serum creatinine <1.5-fold baseline and without dialysis dependence. Key secondary end points were time to kidney recovery, neutropenia, and transaminitis on day 7, and time to death. Using multivariable logistic and Cox regression models, we compared outcomes in patients who received glucarpidase within 4 days following MTX initiation with those in patients who did not. Among 708 patients with MTX-AKI, 209 (29.5%) received glucarpidase. Overall, 183 (25.8%) had a primary end point event. Glucarpidase receipt was associated with a 2.70-fold higher adjusted odds of kidney recovery (95% confidence interval [CI], 1.69–4.31) compared with no glucarpidase receipt. Patients treated with glucarpidase also had faster time to kidney recovery (adjusted hazard ratio [aHR], 1.88; 95% CI, 1.18–3.33) and lower risks of grade ≥2 neutropenia (adjusted odds ratio [aOR], 0.50; 95% CI, 0.28–0.91) and grade ≥2 transaminitis (aOR, 0.50; 95% CI, 0.28–0.91) on day 7. There was no difference in time to death (aHR, 0.76; 95% CI, 0.49–1.18). These data suggest glucarpidase may improve both renal and extrarenal outcomes in patients with MTX-AKI.

Abstract Pharmacogenomics (PGx) is focused on the relationship between an individual's genetic makeup and their response to medications, with the overarching aim of guiding prescribing decisions to improve drug efficacy and reduce adverse events. The PGx and genomic medicine communities have worked independently for over 2 decades, developing separate standards and terminology, making implementation of PGx across all areas of genomic medicine difficult. To address this issue, the Clinical Genome Resource (ClinGen) Pharmacogenomics Working Group (PGxWG) was established by the National Institutes of Health (NIH)-funded ClinGen to initially create frameworks for evaluating gene–drug response clinical validity and actionability aligned with the ClinGen frameworks for evaluating monogenic gene–disease relationships, and a framework for classifying germline PGx variants similar to the American College of Medical Genetics (ACMG) and Association of Molecular Pathology (AMP) system for interpretation of disease-causing variants. These frameworks will leverage decades of work from well-established PGx resources facilitating buy-in among PGx stakeholders. In this report, we describe the background and major activities of the ClinGen PGxWG, and how this initiative will facilitate the critical inclusion of PGx into the larger context of genomic medicine.

AbstractBackgroundLewy body dementia (LBD) is the second most prevalent dementia in the United States after Alzheimer’s disease (AD). Recent studies have implicated rare mutations in two lipid transport genes, ABCA1 and ATP8B4, in Alzheimer’s disease. Substantial co‐pathology and shared risk factors indicate an intersectional genetic architecture between LBD and AD; therefore, we investigated the association of rare mutations in ABCA1 and ATP8B4 with LBD. Additionally, we examined rare mutations in 25 genes involved in ABCA1‐related lipid‐specific pathway with risk of developing LBD.MethodWe annotated rare missense and loss‐of‐function (LOF) mutations in ABCA1 and ATP8B4 genes, using Ensembl Variant Effect Predictor, in previously published whole‐genome sequence data from 2,591 LBD cases and 4,027 healthy controls of European ancestry. To test the association with LBD risk, we applied the optimized sequence kernel association test (SKAT‐O), followed by single‐variant association test (Fisher’s exact test), and multiple testing (Bonferroni correction). Additionally, we evaluated rare coding variants of 25 genes in ABCA1‐related positive regulation of the cholesterol efflux pathway (GO: 0010875) by performing single‐gene burden and gene‐set burden analyses.ResultsWe found a significant enrichment of rare ABCA1 missense mutations in LBD (SKAT‐O p = 2.68E‐02). However, no significant associations were found between LBD and ABCA1 LOF, and ATP8B4 LOF or missense mutations. Interestingly, the single‐variant analysis identified two ABCA1 missense variants, c.5398A>C; p.N1800H (Fisher’s test: p‐value = 1.16E‐04) and c.3544G>A; p.A1182T (p‐value = 4.29E‐02), with the p.N1800H substitution surviving Bonferroni multiple testing. The p.N1800H variant is reported to be pathogenic, and it was observed in twelve LBD patients and one control, with an odds ratio of 18.48 (95%CI = 2.4‐142.8). This mutation is reported to be pathogenic, in our LBD cohort, six out of twelve ABCA1 p.N1800H carriers also carry the APOE ε4 risk allele. However, neither a single‐gene burden nor a gene‐set burden analysis in 25 genes in the positive regulation of the cholesterol efflux pathway revealed any significant associations with LBD.ConclusionOur findings reveal significant enrichment of ABCA1 missense mutations in LBD emphasizing the genomic complexity surrounding LBD and AD.

AbstractBackgroundAlthough the rate of Alzheimer’s disease (AD) in African‐ancestry (AA) Americans is higher than that of persons from European‐ancestry (EA) populations, AA participants have been underrepresented in AD neuropathological studies.MethodUtilizing the AD Research Centers (ADRC) infrastructure, we obtained AA donor pre‐frontal cortex (PFC) tissue from brain repositories of 12 ADRC and generated bulk RNA sequencing (RNA‐seq) data for 179 samples that met QC and inclusion criteria. Previously generated PFC RNAseq data were obtained for 28 additional AA donors from the Columbia University ADRC. Differential gene expression was evaluated among 125 donors with a neuropathological diagnosis of AD (NIA‐Reagan intermediate or high likelihood) and 82 neuropathologically confirmed controls using regression models including covariates for age at death, sex, cell‐type frequencies, and RNA integrity number (RIN) calculated with Limma. FDR‐corrected p‐values (padj) were calculated to control for the 33,611 genes examined.ResultA total of 482 genes surpassed the multiple‐testing threshold. The most significant, ADAMTS2 (p = 2.96 × 10‐8, padj = 0.001), showed increased expression in AD cases (see Table/Figure). We note that ADAMTS2 was differentially expressed in a prior EA study of neuropathologically confirmed AD cases and controls (Panitch et al. Molecular Psychiatry 2021). Additionally, a recent analysis of cognitive resilience in EA neuropathological AD cases identified a strong association with ADAMTS2 (See Li et al. AAIC2024 abstract). Of the differentially expressed genes observed in the Panitch et al. EA study, 385 (35%) were nominally significant,65 (5.8%) were corrected significant, and most (89%) of these genes had the same effect direction in the AA cohort. Some of the observed associations appear to be AA specific (e.g., EFR3B, IRS4, and CA12; see Table). Additionally, we found nominally significant (p<0.05) associations with expression of APOE (Log2 fold change [L2FC = ‐0.20, p = 0.012) and several other established AD genes including SORL1 (L2FC = ‐0.10, p = 0.014) and IGF1R(L2FC = 0.11, p = 0.0013).ConclusionThis largest‐ever (to our knowledge) gene expression study of AD in postmortem brain tissue from AA donors implicates many more genes as having a role in AD in this population than previously identified in genome‐wide association studies and provides insight into trans‐ancestry differences risk for AD.