Citations

ABSTRACT Understanding lung cancer evolution can identify tools for intercepting its growth. In a landscape analysis of 1024 lung adenocarcinomas (LUAD) with deep whole-genome sequencing integrated with multiomic data, we identified 542 LUAD that displayed diverse clonal architecture. In this group, we observed an interplay between mobile elements, endogenous and exogenous mutational processes, distinct driver genes, and epidemiological features. Our results revealed divergent evolutionary trajectories based on tobacco smoking exposure, ancestry, and sex. LUAD from smokers showed an abundance of tobacco-related C:G>A:T driver mutations in KRAS plus short subclonal diversification. LUAD in never smokers showed early occurrence of copy number alterations and EGFR mutations associated with SBS5 and SBS40a mutational signatures. Tumors harboring EGFR mutations exhibited long latency, particularly in females of European-ancestry (EU_N). In EU_N, EGFR mutations preceded the occurrence of other driver genes, including TP53 and RBM10. Tumors from Asian never smokers showed a short clonal evolution and presented with heterogeneous repetitive patterns for the inferred mutational order. Importantly, we found that the mutational signature ID2 is a marker of a previously unrecognized mechanism for LUAD evolution. Tumors with ID2 showed short latency and high L1 retrotransposon activity linked to L1 promoter demethylation. These tumors exhibited an aggressive phenotype, characterized by increased genomic instability, elevated hypoxia scores, low burden of neoantigens, propensity to develop metastasis, and poor overall survival. Re-activated L1 retrotransposition-induced mutagenesis can contribute to the origin of the mutational signature ID2, including through the regulation of the transcriptional factor ZNF695 , a member of the KZFP family. The complex nature of LUAD evolution creates both challenges and opportunities for screening and treatment plans.

Background Neuropsychiatric symptoms (NPS) are frequent in Alzheimer's disease (AD) dementia, but a higher NPS burden is found in dementia with Lewy bodies (DLB). Lewy body (LB) pathology frequently co-occurs with AD pathology and may not meet neuropathological criteria for DLB (ADLB). NPS trajectories over disease course in these subgroups is not well understood. Objective We investigated changes in NPS severity over time, at two time points, comparing clinicopathologically defined cohorts of AD (without LB), ADLB, DLB, and controls. Methods Cases with two available Neuropsychiatric Inventory-Questionnaire (NPIQ), at the time of enrollment and within 2.5 years of death, were selected from the Arizona Study of Aging and Neurodegenerative Disorders. Differences and rate of change in NPIQ scores were compared between AD (n = 75), ADLB (n = 48) DLB (n = 65), and controls (n = 32) with covariates for age, sex, and cognition. Results First NPIQ scores were highest in ADLB when compared to AD (p = 0.04) and controls (p = 0.01) but not different from DLB. A significant increase in NPS severity was observed in DLB and AD (p < 0.001) over a mean follow up time of 4.9 ± 3.0 years, and the rate of change was significantly greater in DLB when compared to other groups. Final NPIQ scores were highest in DLB when compared to AD (p = 0.03) but not ADLB, and in DLB, ADLB, and AD than controls ( all p < 0.001). Conclusions Early NPS burden as well as NPS severity progression rate, independently of cognitive status, might be useful clinical metrics and may help predict underlying pathological diagnoses.

Abstract The development of targeted therapy for patients with multiple myeloma (MM) is hampered by the low frequency of actionable genetic abnormalities. Gain or amplification of chromosome 1q (1q+) is the most frequent arm-level copy number gain in patients with MM and is associated with higher risk of progression and death despite recent therapeutic advances. Thus, developing targeted therapy for patients with MM with 1q+ stands to benefit a large portion of patients in need of more effective management. Here, we used large-scale dependency screens and drug screens to systematically characterize the therapeutic vulnerabilities of MM with 1q+ and displayed increased sensitivity to myeloid cell leukemia-1 (MCL1) and phosphatidyl inositol 3-kinase (PI3K) inhibitors. Using single-cell RNA sequencing, we compared subclones with and without 1q+ within the same patient tumors and demonstrated that 1q+ is associated with higher levels of MCL1 and the PI3K pathway. Furthermore, by isolating isogenic clones with different copy number profiles for part of the chromosome 1q arm, we observed increased sensitivity to MCL1 and PI3K inhibitors with arm-level gain. Lastly, we demonstrated synergy between MCL1 and PI3K inhibitors and dissected their mechanism of action in MM with 1q+, uncovering a cytostatic effect. In conclusion, this study highlights that MM with 1q+ may present enhanced sensitivity to MCL1 and PI3K inhibitors, enabling their use at lower doses without sacrificing efficacy, and may thus accelerate the development of targeted therapy for patients with MM and 1q+.

Abstract Solid tumors develop within a complex environment called the tumor microenvironment (TME), which is sculpted by the presence of other cells, such as cancer‐associated fibroblasts (CAFs) and immune cells like macrophages (Mφs). Despite the presence of immune cells, tumor cells orchestrate a tumor‐supportive environment through intricate interaction with the components of the TME. However, the specific mechanism by which this intercellular dialogue is regulated is not fully understood. To that end, the development of an organotypic 3D breast TME‐on‐a‐chip (TMEC) model, integrated with single‐cell RNA sequencing analysis, is reported to mechanistically evaluate the progression of triple‐negative breast cancer (TNBC) cells in the presence of patient‐derived CAFs and Mφs. Extensive functional assays, including invasion and morphometric characterization, reveal the synergistic influence of CAFs and Mφs on tumor cells. Furthermore, gene expression and pathway enrichment analyses identify the involvement of the KYNU gene, suggesting a potential immune evasion mechanism through the kynurenine pathway. Lastly, the pharmacological targeting of the identified pathway is investigated.

ABSTRACTIntroductionVon Willebrand factor (VWF) multimer analysis is essential for diagnosing and classifying von Willebrand disease (VWD) but requires expert interpretation and is subject to inter‐rater variability. We developed an automated image analysis pipeline using deep learning to improve the reproducibility and efficiency of VWF multimer pattern classification.MethodsWe trained a YOLOv8 deep learning model on 514 gel images (6168 labeled instances) to classify VWF multimer patterns into 12 classes. The model was validated on 192 images (2304 instances) and tested on an independent set of 94 images (1128 instances). Images underwent preprocessing, including histogram equalization, contrast enhancement, and gamma correction. Two expert raters provided ground truth classifications.ResultsThe model achieved 91% accuracy compared to Expert 1 (macro‐averaged precision = 0.851, recall = 0.757, F1‐score = 0.786) and 87% accuracy compared to Expert 2 (macro‐averaged precision = 0.653, recall = 0.653, F1‐score = 0.641). Inter‐rater agreement was very high between experts (κ = 0.883), with strong agreement between the model and Expert 1 (κ = 0.845) and good agreement with Expert 2 (κ = 0.773). The model performed exceptionally well on common patterns (F1 > 0.93) but showed lower performance on rare subtypes.ConclusionAutomated VWF multimer analysis using deep learning demonstrates high accuracy in pattern classification and could standardize the interpretation of VWF multimer patterns. While not replacing expert analysis, this approach could improve the efficiency of expert human review, potentially streamlining laboratory workflow and expanding access to VWF multimer testing.

When one initially targets the null effect and the point estimate falls close to the null, two challenges exist in rating certainty of evidence. First, when the point estimate is near the null and the data, therefore, suggests little or no effect, rating certainty in a benefit or harm is misleading. Second, since in general the narrower the confidence interval (CI) the more precise the estimate, if the CI is narrow, rating down for imprecision due simply to crossing the null is inappropriate. This paper addresses these issues and provides a solution: to revise the target of certainty rating from a non-zero effect to a little or no effect. This solution requires estimating a range in which the minimal important difference (MID) for benefit and an MID for harm might lie, and thus establishing a range that represents little or no effect. If GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) users are confident that the point estimate represents an effect less than the smallest plausible MID, they will revise their target and rate certainty to a little or no effect. If the entire CI falls within the range of little or no effect, they will not rate down for imprecision. Otherwise (if the CI includes an important effect), they will rate down. Using the solution provided in this paper GRADE users can make an optimal choice of the target of certainty rating.

Alcohol use disorder (AUD) is the most prevalent substance use disorder. Excessive alcohol consumption leads to a range of health issues. We set out to identify inflammatory markers linked to alcohol consumption, which might ultimately offer novel insight into genetic underpinnings and have implications for alcohol-associated disease. Alcohol consumption and blood-based multi-omics data were collected by The Mayo Clinic Center for Individualized Treatment of Alcohol Dependence study. Plasma samples from patients with AUD were used for proteomics analysis using the OLINK “Explore Inflammation” panel (n=410). Liver enzymes were also measured. A genome-wide association study (GWAS) was performed to explore the relationship between genetic variants and plasma TREM2 levels. Our findings show thatplasma triggering receptor expressed on myeloid cells 2 (TREM2), a key gene associated with neurodegenerative disease, was the most significant signal correlated with alcohol consumption, and has also been associated with liver enzyme levels in patients with AUD. We identified the rs7232 single nucleotide polymorphism (SNP) in MS4A6A as a key genetic variant associated with plasma TREM2 levels, with the minor allele (A) linked to higher TREM2 levels and increased alcohol consumption, particularly in men. Furthermore, MA4A6A is an ethanol-responsive gene in a SNP-dependent manner, and the variant genotype of the rs7232 SNP was associated with lower expression for MA4A6A due to proteasome-mediated protein degradation. In summary, this study provides insight into the relationship between plasma TREM2 levels, alcohol consumption, and liver function in AUD patients, shedding light on genetic factors underlying alcohol-related diseases.

Abstract Purpose: Germline alterations in homologous recombination repair (gHRR) genes affect the pathogenesis, treatment options, and survival of patients with cancer. However, distinct gHRR gene alterations may differentially affect treatment response and oncogenic signaling. In this study, we interrogated genomic and transcriptomic data and assessed clinical outcomes of patients with gHRR mutations across four BRCA-associated cancers (breast, ovarian, pancreatic, and prostate cancers) to identify therapeutic vulnerabilities. Experimental Design: We assessed 24,309 patients undergoing matched tumor/normal next-generation DNA and RNA sequencing. Annotated gHRR gene variants [germline BRCA1, germline BRCA2, germline PALB2, germline ATM (gATM), and germline CHEK2] were analyzed. HRs were used to assess survival outcomes comparing germline versus sporadic groups. Somatic alterations and their frequencies were compared across gHRR-altered groups. Differential gene expression and gene set enrichment analysis were used to compare transcriptomic profiles. Results: Somatic TP53 mutations were depleted in gATM carriers (P &lt; 0.05) across all four BRCA-associated cancers by up to 2.5-fold. Tumors with germline BRCA1/2 mutations were associated with improved survival in patients with ovarian cancer and had consistent enrichment of TP53 mutations in all four cancers. gATM mutations displayed elevated p53 transcriptional activity in all four cancers, with significance reached in breast and prostate cancers (P &lt; 0.01). In breast, ovarian, and prostate cancers, gATM tumors demonstrated significantly increased inflammatory pathways (P &lt; 0.001). Finally, using gene dependency data, we found that cell lines that were highly dependent on ATM were co-dependent on canonical p53 function. Conclusions: gATM-associated cancers seem to require intact p53 activity and this synthetic essentiality may be used to guide targeted therapies that perturb canonical TP53 function.

Abstract Background Despite advances in clinical microbiology, the diagnosis of invasive fungal infections remains challenging. Giant magnetoresistance (GMR) is a novel technology that enables the detection of trace amounts of cell-free DNA (cfDNA). We evaluated a high-multiplex molecular diagnostic assay coupled with GMR-enabled lab-on-a-chip technology that can detect 18 different fungal species. Methods Analytical performance was evaluated in spiked plasma samples. After amplification, cfDNA was digested. Residual single-stranded DNA was flowed over a GMR sensor that was surface-coated with probes specific to different fungal species. After hybridization, magnetic beads bound to the probe complexes produced a GMR signal that was detected by the sensors. Clinical performance was determined using residual serum samples collected before the initiation of antifungal treatment from 20 patients with infection. Results The limit of detection of the assay ranged from 5 to 50 copies per polymerase chain reaction (PCR) reaction. Nonspecific signals were not observed in the spiked samples. Fungal cfDNA was detected in 80% of patients with invasive candidiasis (3/4 with candidemia, 5/6 with invasive candidiasis without candidemia), all 3 cases of invasive pulmonary aspergillosis, and all 3 cases of disseminated histoplasmosis. cfDNA was not detected in 2 patients with cryptococcosis (both had negative blood cultures) and 2 patients with Pneumocystis pneumonia. Conclusions We developed a novel GMR-enabled multiplex PCR assay detecting fungal pathogens that have been prioritized for public health action. Clinical sensitivity was highest in cases of presumed angioinvasion and dissemination. This technology has the potential for use in the clinical microbiology laboratory setting.

BACKGROUND: Pharmacological treatments for fibrocalcific aortic valve stenosis (FCAVS) have been elusive for >50 years. Here, we tested the hypothesis that reactivation of oxidized sGC (soluble guanylate cyclase), the primary receptor for nitric oxide, with ataciguat is a safe and efficacious strategy to slow progression of FCAVS. METHODS: We used quantitative real-time reverse transcription polymerase chain reaction, Western blotting, and immunohistochemistry to characterize sGC signaling and the biological effects of ataciguat on signaling cascades related to nitric oxide, calcification, and fibrosis in excised human aortic valve tissue, aortic valve interstitial cells, and mouse aortic valves. We then conducted randomized, placebo-controlled phase I (14-day safety/tolerance) and phase II (6-month efficacy) trials in patients with moderate aortic valve stenosis. RESULTS: In excised human tissue, we found robust losses in sGC signaling despite upregulation of sGC subunits. In vitro, ataciguat increased sGC signaling and reduced BMP2 (bone morphogenetic protein 2) signaling in aortic valve interstitial cells. In mice with established FCAVS, treatment with ataciguat attenuated BMP signaling and slowed progression of valve calcification and dysfunction. In a phase I, randomized, placebo-controlled trial, treatment with ataciguat for 2 weeks was safe and well tolerated in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02049203). In a separate phase II, randomized, placebo-controlled trial, treatment with ataciguat for 6 months slowed the progression of aortic valve calcification and tended to slow the progression of valvular and ventricular dysfunction in patients with moderate FCAVS ( https://www.clinicaltrials.gov ; Unique identifier: NCT02481258). CONCLUSIONS: Collectively, this study highlights the therapeutic potential of the targeted restoration of the diseased/inactive form of sGC for treatment of FCAVS. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02049203. URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02481258.