Citations

Abstract BRCA1 -deficient cancers experience persistent replication stress and structural genome instability yet retain the capacity for sustained proliferation, implying reliance on compensatory genome-maintenance mechanisms. Here, we establish BRCA1–FANCM synthetic lethality in human BRCA1 -deficient breast cancer and exploit temporally controlled FANCM depletion to capture genome evolution over successive cell divisions before declining cellular fitness becomes limiting. We show that FANCM restrains genome-wide structural variation in BRCA1 -deficient breast cancer cells under endogenous replication stress. FANCM loss amplifies the characteristic BRCA1 -associated short tandem duplication (TD) phenotype while permitting larger, including megabase-scale, TDs and diverse rearrangements to emerge. Newly emerged TDs preferentially associate with Pol II-occupied regions, and FANCM depletion increases proximity between the replication machinery and elongating RNAPII in BRCA1 -mutant breast cancer cells, linking FANCM-mediated genome protection to transcription–replication encounters. BRCA1 -altered human tumors with low FANCM expression recapitulate key features of this phenotype, while genome–transcriptome integration links newly emerged SVs to configuration-dependent local transcriptional changes. Together, these findings establish FANCM as a replication-stress safeguard coupling survival to restraint of structural genome evolution.

ABSTRACT Leptomeningeal disease (LMD) is a rapidly fatal complication of systemic cancer for which sensitive diagnostic tools and informative biomarkers remain limited. Here, we introduce CSF-Seq, a method for whole-transcriptome sequencing of cell-free RNA (cfRNA) from human cerebrospinal fluid (CSF), designed to enable molecular profiling of LMD and other central nervous system (CNS) conditions. Using a prospectively collected CSF biobank, we analyzed 125 samples spanning multiple pathologies, including breast and lung LMD, glioblastoma, traumatic brain injury, and non-cancer neurological controls. Through optimized RNA extraction, library preparation, and deep sequencing, CSF-Seq generated robust and reproducible transcriptome-wide profiles despite the low abundance and fragmentation of cfRNA in CSF. CSF transcriptomes exhibited disease-specific expression, separating LMD from non-cancer controls and from non-LMD cancers, independent of CSF collection modality. Tumor-associated epithelial transcripts, including CEACAM6 and MUC1, were consistently enriched in LMD samples, whereas immune and CNS-associated transcripts were broadly detected across disease states, consistent with contributions from both tumor and non-tumor sources. Cross-site processing of matched samples demonstrated high concordance, indicating preservation of sample-specific transcriptional signatures across independent workflows. Importantly, we identified a collection method– independent LMD gene expression signature that was significantly associated with overall survival, supporting its potential prognostic relevance. Together, these findings establish CSF-Seq as a technically robust and clinically informative platform for transcriptomic biomarker discovery in CNS metastatic disease, offering a minimally invasive approach for disease characterization, risk stratification, and longitudinal monitoring in patients with LMD.

<title>RESUMEN</title> <p>A pesar de que la Práctica Basada en la Evidencia (PBE) ha estandarizado los tratamientos psicológicos, la realidad clínica sigue enfrentándose a una barrera persistente: la dificultad de traducir los resultados de ensayos clínicos grupales a la singularidad de cada paciente en contextos reales. Como respuesta, la Salud Mental de Precisión (SMP) propone una evolución del modelo actual, integrando el cuidado basado en la medición y la toma de decisiones basada en datos para ajustar la intervención a las necesidades específicas de cada persona, gracias en gran medida a desarrollos tecnológicos recientes como la Inteligencia Artificial (IA). En este contexto, el presente artículo persigue dos objetivos fundamentales. En primer lugar, sintetiza los pilares operativos de la SMP, analizando cómo la medición rutinaria y las predicciones algorítmicas pueden potenciar el juicio clínico del profesional. En segundo lugar, se introduce el proyecto NOVA (Navigating Outcomes via Analytics), un proyecto traslacional diseñado para superar las barreras actitudinales, tecnológicas, estadísticas y contextuales de la implementación de herramientas de SMP en España. Se discute sobre los pasos necesarios para cerrar la brecha entre la innovación tecnológica y la práctica asistencial en psicología, acelerando la adopción sostenible de una psicología de precisión en el mundo real.</p>

Abstract Honoring a patient’s wishes for end-of-life care can be challenging if the patient loses decision-making capacity and the identified alternate decision-maker will not respect the patient’s wishes. This article discusses how to proceed ethically and legally when the alternate decision-maker and care team disagree about respecting a patient’s end-of-life preferences.

46 Background: Primary results from the randomized, multicenter, open-label, phase 3 TRITON3 (NCT02975934) study demonstrated that rucaparib significantly improved radiographic progression-free survival (rPFS) vs physician’s choice of DTX or an ARPI. ECOG PS is used as a predictor of prostate cancer survival. In this post hoc analysis, we report results from the BRCA1/2 subgroup of pts stratified by ECOG PS. Methods: Pts with disease progression after 1 prior second-generation ARPI in any setting were randomized 2:1 to rucaparib 600 mg BID or physician’s choice of DTX or ARPI (abiraterone acetate or enzalutamide). Primary endpoint was rPFS by independent radiology review (IRR). Objective response rate (ORR) for pts with measurable disease and overall survival (OS) were key secondary endpoints. Crossover from physician’s choice to rucaparib was allowed after radiographic progression was confirmed by IRR. Data cutoff was August 25, 2022. Results: Of 302 pts in the BRCA1/2 population, 147 had an ECOG status of 0 (97 rucaparib; 50 physician’s choice) and 155 had ECOG 1 (104 rucaparib; 51 physician’s choice). Baseline characteristics and demographics were generally similar between arms for pts in the ECOG 0 and ECOG 1 groups. Median rPFS favored rucaparib vs physician’s choice for pts with ECOG 0 (11.4 vs 8.2 months; HR, 0.48 [95% CI, 0.30-0.76]) and ECOG 1 (10.9 vs 6.1 months; HR, 0.48 [95% CI, 0.31-0.74]) (Table). Additionally, rPFS favored rucaparib for ECOG 0 and ECOG 1 including those whose prespecified physician’s choice was ARPI or docetaxel (Table). The confirmed ORR (95% CI) of rucaparib vs physician’s choice for ECOG 0 was 54% (37%–69%) vs 16% (3%–40%); the ORR for ECOG 1 was 37% (22%–53%) vs 18% (5%–40%), respectively. Median OS was similar between arms for rucaparib or physician’s choice; median OS was 23.7 vs 21.7 months (HR, 0.91 [95% CI, 0.61–1.37]) for ECOG 0 and 21.8 vs 20.4 months (HR, 0.85 [95% CI, 0.58–1.24]) for ECOG 1. Conclusions: Rucaparib improved rPFS and ORR in pts with BRCA-mutated prostate cancer with an ECOG PS of 0 or 1. OS was similar for these groups in both arms. These data support rucaparib as a treatment option for pts with BRCA-mutated mCRPC, whether ECOG 0 or 1. Clinical trial information: NCT02975934 . Median rPFS in patients in the ECOG 0 and ECOG 1 groups. Rucaparib, n Physician’s choice, n rPFS Rucaparib, median months rPFS Physician’s choice, median months HR (95% CI) rPFS, ECOG 0 97 50 11.4 8.2 0.48 (0.30–0.76) rPFS, ECOG 1 104 51 10.9 6.1 0.48 (0.31–0.74) rPFS, physician’s choice ARPI, ECOG 0 51 24 11.2 5.6 0.42 (0.22–0.78) rPFS, physician’s choice docetaxel, ECOG 0 46 26 11.5 8.8 0.49 (0.24–0.98) rPFS, physician’s choice ARPI, ECOG 1 52 17 11.2 4.5 0.33 (0.16–0.68) rPFS, physician’s choice docetaxel, ECOG 1 52 34 10.7 7.1 0.59 (0.34–1.01)

Evidence-Based Practice (EBP) has increased the availability of psychological treatments, yet many people do not benefit from therapy, some report deteriorations in symptoms, and dropout rates remain high. Precision Mental Health (PMH) is proposed as an extension of EBP by combining systematic measurement with predictive analytics to support the right intervention, at the right time, for the right person. Recent advances in Artificial Intelligence (AI) make PMH increasingly feasible in routine psychotherapy; however, the implementation of these approaches in routine care is still incipient. In this context, the present article has two main aims. First, we summarize key advances in PMH, particularly measurement-based care and data-informed decision making. Second, we introduce the NOVA project (Navigating Outcomes via Analytics), a multi-phase translational program designed to implement PMH in real-world psychological services. Guided by the Implementing Precision Methods framework, NOVA integrates (i) stakeholder-informed work on clinician acceptability and intention to use, (ii) pragmatic evaluation of decision support tools in routine care, (iii) development of robust and interpretable predictive models, and (iv) training and dissemination activities aligned with responsible innovation and professional competencies for AI-supported precision care. By detailing NOVA’s implementation pathway, we aim to provide a concrete roadmap for bridging AI innovation and psychological practice, accelerating the sustainable adoption of PMH in real-world settings.

Importance Treatment for cognitive dysfunction due to postacute sequelae of long COVID (ie, symptoms of fatigue, malaise, weakness, confusion that persist beyond 12 weeks after an initial COVID infection) remains a significant unmet need. Objective To test evidence-based rehabilitation strategies for improving cognitive symptoms in persons with long COVID. Design, Setting, and Participants This was a 5-arm, multicenter, randomized clinical trial of 3 remotely delivered interventions conducted between August 17, 2023, and June 10, 2024. The study took place at 22 trial sites and included the screening of individuals with cognitive long COVID. Interventions Participants were randomized to 1 of 5 arms: adaptive computerized cognitive training (BrainHQ [Posit Science]), cognitive-behavioral rehabilitation involving both group and individual counseling sessions (PASC-Cognitive Recovery [PASC-CoRE]) paired with BrainHQ, and transcranial direct current stimulation (tDCS) paired with BrainHQ. Two comparator arms were included as follows: unstructured computer puzzles and games (active comparator) and sham tDCS paired with BrainHQ. The interventions occurred 5 times per week over 10 weeks. Main Outcomes and Measures Cognitive and behavioral in-person assessments were performed at baseline, midintervention, at the end of intervention, and 3 months after the end of the intervention. The primary outcome measure was the modified Everyday Cognition Scale 2 (ECog2) completed at the end of the intervention compared to the baseline visit based on participant self-report looking back over the prior 7 days. Results A total of 378 individuals were screened, from which there were 328 participants (median [IQR] age, 48.0 [37.0-58.0] years; 241 female [73.5%]; race: 15 Asian [4.6%], 47 Black [14.3%], and 235 White [71.6%]; ethnicity: 52 Hispanic [15.9%]). None of the 3 active interventions demonstrated benefits on the modified ECog2 in the intention-to-treat population by the end of the intervention period. The adjusted differences in mean change were 0.0 (95% CI, −0.2 to 0.2) for BrainHQ vs active comparator, 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs active comparator, 0.0 (95% CI, −0.2 to 0.2) for tDCS-active + BrainHQ vs tDCS-sham + BrainHQ, and 0.1 (95% CI, −0.1 to 0.3) for PASC-CoRE + BrainHQ vs BrainHQ alone. Secondary participant-reported outcomes and neuropsychological tests showed no differential benefits for any treatment arm. All 5 arms demonstrated some improvements over time on the modified ECog2 and on secondary outcomes. There were no serious adverse events attributable to the interventions. Conclusions and Relevance This phase 2 randomized clinical trial failed to demonstrate differential benefits for online cognitive training, a structured cognitive rehabilitation program, and tDCS for cognitive long COVID. Trial Registration ClinicalTrials.gov Identifier: NCT05965739 .

Abstract Objectives/Background This study was undertaken to review the published literature and provide a position statement from the American Headache Society regarding the safety, efficacy, and impact on access to care of telemedicine for the clinical management of patients with headache disorders. Access to specialized care in headache medicine is severely limited in the United States and worldwide. Telemedicine has been used as an approach to care delivery in headache medicine for more than a decade, with accelerated adoption during the COVID‐19 pandemic. There is now uncertainty regarding the extent to which telemedicine will be accepted by health systems and reimbursed by payers moving forward. The purpose of this position statement is to summarize evidence and clinical experience supporting the utility of telemedicine in headache medicine. Methods Evidence regarding the safety and efficacy of telemedicine, and patient and clinician satisfaction with the use of telemedicine for headache specialty care, was gathered from a variety of sources, including PubMed, Google Scholar, and ClinicalTrials.gov . The results and conclusions based upon these results were reviewed and discussed by the authors and the Board of Directors of the American Headache Society to confirm consistency with clinical experience and to achieve consensus. Results Several randomized clinical trials and observational studies have been performed to compare telemedicine with in‐person visits in the management of patients with headache disorders. These studies showed consistently that telemedicine is noninferior to in‐person care based upon multiple outcome measures, including disability measures, patient satisfaction, and clinician satisfaction. In addition, these studies found that telemedicine rarely leads to a missed diagnosis of secondary headache or mismanagement of primary headache. Telemedicine has substantial advantages for patients, including improved access to care and reduced costs associated with obtaining care. Studies evaluating health care utilization indicate no significant differences between patients evaluated and treated virtually versus in person. Obvious limitations of telemedicine include the inability to perform an in‐person physical exam or to perform injections. For a substantial number of patients, however, these limitations are outweighed by its advantages. The experience with telemedicine reported in the literature is consistent with the experience of the Board of Directors of the American Headache Society, who endorse its use for patients when feasible and appropriate. Conclusion Telemedicine has significantly advanced the care of patients with headache disorders. Its further development and deployment should be supported and reimbursed.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.