Activity of the Ubiquitin-activating Enzyme Inhibitor TAK-243 in Adrenocortical Carcinoma Cell Lines, Patient-derived Organoids, and Murine Xenografts.

Current treatment options for metastatic adrenocortical carcinoma (ACC) have limited efficacy, despite the common use of mitotane and cytotoxic agents. This study aimed to identify novel therapeutic options for ACC. An extensive drug screen was conducted to identify compounds with potential activity against ACC cell lines. We further investigated the mechanism of action of the identified compound, TAK-243, its synergistic effects with current ACC therapeutics, and its efficacy in ACC models including patient-derived organoids and mouse xenografts. TAK-243, a clinical ubiquitin-activating enzyme (UAE) inhibitor, showed potent activity in ACC cell lines. TAK-243 inhibited protein ubiquitination in ACC cells, leading to the accumulation of free ubiquitin, activation of the unfolded protein response, and induction of apoptosis. TAK-243 was found to be effluxed out of cells by MDR1, a drug efflux pump, and did not require Schlafen 11 (SLFN11) expression for its activity. Combination of TAK-243 with current ACC therapies (e.g., mitotane, etoposide, cisplatin) produced synergistic or additive effects. In addition, TAK-243 was highly synergistic with BCL2 inhibitors (Navitoclax and Venetoclax) in preclinical ACC models including patient-derived organoids. The tumor suppressive effects of TAK-243 and its synergistic effects with Venetoclax were further confirmed in a mouse xenograft model. These findings provide preclinical evidence to support the initiation of a clinical trial of TAK-243 in patients with advanced-stage ACC. TAK-243 is a promising potential treatment option for ACC, either as monotherapy or in combination with existing therapies or BCL2 inhibitors. SIGNIFICANCE: ACC is a rare endocrine cancer with poor prognosis and limited therapeutic options. We report that TAK-243 is active alone and in combination with currently used therapies and with BCL2 and mTOR inhibitors in ACC preclinical models. Our results suggest implementation of TAK-243 in clinical trials for patients with advanced and metastatic ACC.

NCI Cancer Research Data Commons: Cloud-Based Analytic Resources.

The NCI's Cloud Resources (CR) are the analytical components of the Cancer Research Data Commons (CRDC) ecosystem. This review describes how the three CRs (Broad Institute FireCloud, Institute for Systems Biology Cancer Gateway in the Cloud, and Seven Bridges Cancer Genomics Cloud) provide access and availability to large, cloud-hosted, multimodal cancer datasets, as well as offer tools and workspaces for performing data analysis where the data resides, without download or storage. In addition, users can upload their own data and tools into their workspaces, allowing researchers to create custom analysis workflows and integrate CRDC-hosted data with their own. See related articles by Brady et al., p. 1384, Wang et al., p. 1388, and Kim et al., p. 1404.

Unconstrained quantitative magnetization transfer imaging: disentangling T1 of the free and semi-solid spin pools.

Since the inception of magnetization transfer (MT) imaging, it has been widely assumed that Henkelman's two spin pools have similar longitudinal relaxation times, which motivated many researchers to constrain them to each other. However, several recent publications reported a T1s of the semi-solid spin pool that is much shorter than T1f of the free pool. While these studies tailored experiments for robust proofs-of-concept, we here aim to quantify the disentangled relaxation processes on a voxel-by-voxel basis in a clinical imaging setting, i.e., with an effective resolution of 1.24mm isotropic and full brain coverage in 12min. To this end, we optimized a hybrid-state pulse sequence for mapping the parameters of an unconstrained MT model. We scanned four people with relapsing-remitting multiple sclerosis (MS) and four healthy controls with this pulse sequence and estimated T1f≈1.84s and T1s≈0.34s in healthy white matter. Our results confirm the reports that T1s≪T1f and we argue that this finding identifies MT as an inherent driver of longitudinal relaxation in brain tissue. Moreover, we estimated a fractional size of the semi-solid spin pool of m0s≈0.212, which is larger than previously assumed. An analysis of T1f in normal-appearing white matter revealed statistically significant differences between individuals with MS and controls.

Highly Sensitive 3-Tesla Real Inversion Recovery MRI Detects Leptomeningeal Contrast Enhancement in Chronic Active Multiple Sclerosis.

BACKGROUND: Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive. PURPOSE: To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME. MATERIALS AND METHODS: We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data. RESULTS: We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume. CONCLUSIONS: Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation.

Pseudo-Label Assisted nnU-Net enables automatic segmentation of 7T MRI from a single acquisition.

Introduction: Automatic whole brain and lesion segmentation at 7T presents challenges, primarily from bias fields, susceptibility artifacts including distortions, and registration errors. Here, we sought to use deep learning algorithms (D/L) to do both skull stripping and whole brain segmentation on multiple imaging contrasts generated in a single Magnetization Prepared 2 Rapid Acquisition Gradient Echoes (MP2RAGE) acquisition on participants clinically diagnosed with multiple sclerosis (MS), bypassing registration errors. Methods: Brain scans Segmentation from 3T and 7T scanners were analyzed with software packages such as FreeSurfer, Classification using Derivative-based Features (C-DEF), nnU-net, and a novel 3T-to-7T transfer learning method, Pseudo-Label Assisted nnU-Net (PLAn). 3T and 7T MRIs acquired within 9 months from 25 study participants with MS (Cohort 1) were used for training and optimizing. Eight MS patients (Cohort 2) scanned only at 7T, but with expert annotated lesion segmentation, was used to further validate the algorithm on a completely unseen dataset. Segmentation results were rated visually by experts in a blinded fashion and quantitatively using Dice Similarity Coefficient (DSC). Results: Of the methods explored here, nnU-Net and PLAn produced the best tissue segmentation at 7T for all tissue classes. In both quantitative and qualitative analysis, PLAn significantly outperformed nnU-Net (and other methods) in lesion detection in both cohorts. PLAn's lesion DSC improved by 16% compared to nnU-Net. Discussion: Limited availability of labeled data makes transfer learning an attractive option, and pre-training a nnUNet model using readily obtained 3T pseudo-labels was shown to boost lesion detection capabilities at 7T.

Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis.

Background and objectives: Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL. Methods: A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2. Results: 59 adults with MS had ≥1 7T follow-up visit (mean follow-up time 2±0.5 years). 9 had "active" relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had "stable" RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010µl, range 13-9888 vs median 267µl, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183µl, range 270-9888 vs median 321µl, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS. Discussion: CL formation is rare in people with stable WML, even in those with worsening disability. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.

Preclinical Evaluation of the FGFR-Family Inhibitor Futibatinib for Pediatric Rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma. Despite decades of clinical trials, the overall survival rate for patients with relapsed and metastatic disease remains below 30%, underscoring the need for novel treatments. FGFR4, a receptor tyrosine kinase that is overexpressed in RMS and mutationally activated in 10% of cases, is a promising target for treatment. Here, we show that futibatinib, an irreversible pan-FGFR inhibitor, inhibits the growth of RMS cell lines in vitro by inhibiting phosphorylation of FGFR4 and its downstream targets. Moreover, we provide evidence that the combination of futibatinib with currently used chemotherapies such as irinotecan and vincristine has a synergistic effect against RMS in vitro. However, in RMS xenograft models, futibatinib monotherapy and combination treatment have limited efficacy in delaying tumor growth and prolonging survival. Moreover, limited efficacy is only observed in a PAX3-FOXO1 fusion-negative (FN) RMS cell line with mutationally activated FGFR4, whereas little or no efficacy is observed in PAX3-FOXO1 fusion-positive (FP) RMS cell lines with FGFR4 overexpression. Alternative treatment modalities such as combining futibatinib with other kinase inhibitors or targeting FGFR4 with CAR T cells or antibody-drug conjugate may be more effective than the approaches tested in this study.

A landscape of response to drug combinations in non-small cell lung cancer.

Combination of anti-cancer drugs is broadly seen as way to overcome the often-limited efficacy of single agents. The design and testing of combinations are however very challenging. Here we present a uniquely large dataset screening over 5000 targeted agent combinations across 81 non-small cell lung cancer cell lines. Our analysis reveals a profound heterogeneity of response across the tumor models. Notably, combinations very rarely result in a strong gain in efficacy over the range of response observable with single agents. Importantly, gain of activity over single agents is more often seen when co-targeting functionally proximal genes, offering a strategy for designing more efficient combinations. Because combinatorial effect is strongly context specific, tumor specificity should be achievable. The resource provided, together with an additional validation screen sheds light on major challenges and opportunities in building efficacious combinations against cancer and provides an opportunity for training computational models for synergy prediction.

Targeting neddylation sensitizes colorectal cancer to topoisomerase I inhibitors by inactivating the DCAF13-CRL4 ubiquitin ligase complex.

Colorectal cancers (CRCs) are prevalent worldwide, yet current treatments remain inadequate. Using chemical genetic screens, we identify that co-inhibition of topoisomerase I (TOP1) and NEDD8 is synergistically cytotoxic in human CRC cells. Combination of the TOP1 inhibitor irinotecan or its bioactive metabolite SN38 with the NEDD8-activating enzyme inhibitor pevonedistat exhibits synergy in CRC patient-derived organoids and xenografts. Mechanistically, we show that pevonedistat blocks the ubiquitin/proteasome-dependent repair of TOP1 DNA-protein crosslinks (TOP1-DPCs) induced by TOP1 inhibitors and that the CUL4-RBX1 complex (CRL4) is a prominent ubiquitin ligase acting on TOP1-DPCs for proteasomal degradation upon auto-NEDD8 modification during replication. We identify DCAF13, a DDB1 and Cullin Associated Factor, as the receptor of TOP1-DPCs for CRL4. Our study not only uncovers a replication-coupled ubiquitin-proteasome pathway for the repair of TOP1-DPCs but also provides molecular and translational rationale for combining TOP1 inhibitors and pevonedistat for CRC and other types of cancers.

The etiology and evolution of magnetic resonance imaging-visible perivascular spaces: Systematic review and meta-analysis.

Objectives: Perivascular spaces have been involved in neuroinflammatory and neurodegenerative diseases. Upon a certain size, these spaces can become visible on magnetic resonance imaging (MRI), referred to as enlarged perivascular spaces (EPVS) or MRI-visible perivascular spaces (MVPVS). However, the lack of systematic evidence on etiology and temporal dynamics of MVPVS hampers their diagnostic utility as MRI biomarker. Thus, the goal of this systematic review was to summarize potential etiologies and evolution of MVPVS. Methods: In a comprehensive literature search, out of 1,488 unique publications, 140 records assessing etiopathogenesis and dynamics of MVPVS were eligible for a qualitative summary. 6 records were included in a meta-analysis to assess the association between MVPVS and brain atrophy. Results: Four overarching and partly overlapping etiologies of MVPVS have been proposed: (1) Impairment of interstitial fluid circulation, (2) Spiral elongation of arteries, (3) Brain atrophy and/or perivascular myelin loss, and (4) Immune cell accumulation in the perivascular space. The meta-analysis in patients with neuroinflammatory diseases did not support an association between MVPVS and brain volume measures [R: -0.15 (95%-CI -0.40-0.11)]. Based on few and mostly small studies in tumefactive MVPVS and in vascular and neuroinflammatory diseases, temporal evolution of MVPVS is slow. Conclusion: Collectively, this study provides high-grade evidence for MVPVS etiopathogenesis and temporal dynamics. Although several potential etiologies for MVPVS emergence have been proposed, they are only partially supported by data. Advanced MRI methods should be employed to further dissect etiopathogenesis and evolution of MVPVS. This can benefit their implementation as an imaging biomarker. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564.

Preclinical validation of a novel therapeutic strategy for choroid plexus carcinoma.

Choroid plexus carcinoma (CPC) is a rare infantile brain tumor with an aggressive clinical course that often leaves children with debilitating side effects due to aggressive and toxic chemotherapies. Development of novel therapeutical strategies for this disease have been extremely limited owing to the rarity of the disease and the paucity of biologically relevant substrates. We conducted the first high-throughput screen (HTS) on a human patient-derived CPC cell line (Children Cancer Hospital Egypt, CCHE-45) and identified 427 top hits highlighting key molecular targets in CPC. Furthermore, a combination screen with a wide variety of targets revealed multiple synergistic combinations that may pave the way for novel therapeutical strategies against CPC. Based on in vitro efficiency, central nervous system (CNS) penetrance ability and feasible translational potential, two combinations using a DNA alkylating or topoisomerase inhibitors in combination with an ataxia telangiectasia mutated and rad3 (ATR) inhibitor (topotecan/elimusertib and melphalan/elimusertib respectively) were validated in vitro and in vivo. Pharmacokinetic assays established increased brain penetrance with intra-arterial (IA) delivery over intra-venous (IV) delivery and demonstrated a higher CNS penetrance for the combination melphalan/elimusertib. The mechanisms of synergistic activity for melphalan/elimusertib were assessed through transcriptome analyses and showed dysregulation of key oncogenic pathways (e.g. MYC, mammalian target of rapamycin mTOR, p53) and activation of critical biological processes (e.g. DNA repair, apoptosis, hypoxia, interferon gamma). Importantly, IA administration of melphalan combined with elimusertib led to a significant increase in survival in a CPC genetic mouse model. In conclusion, this study is, to the best of our knowledge, the first that identifies multiple promising combinatorial therapeutics for CPC and emphasizes the potential of IA delivery for the treatment of CPC.

High-throughput approaches to uncover synergistic drug combinations in leukemia.

We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T.

MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.

Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection.

Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.

Evaluation of immunological responses to third COVID-19 vaccine among people treated with sphingosine receptor-1 modulators and anti-CD20 therapy.

BACKGROUND: People living with multiple sclerosis (MS) and other disorders treated with immunomodulatory therapies remain concerned about suboptimal responses to coronavirus disease 2019 (COVID-19) vaccines. Important questions persist regarding immunological response to third vaccines, particularly with respect to newer virus variants. The objective of this study is to evaluate humoral and cellular immune responses to a third COVID-19 vaccine dose in people on anti-CD20 therapy and sphingosine 1-phosphate receptor (S1PR) modulators, including Omicron-specific assays. METHODS: This is an observational study evaluating immunological responses to third COVID-19 vaccine dose in participants treated with anti-CD20 agents, S1PR modulators, and healthy controls. Neutralizing antibodies against USA-WA1/2020 (WA1) and B.1.1.529 (BA.1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were measured before and after third vaccine. Groups were compared by one-way ANOVA with Tukey multiple comparisons. Cellular responses to spike peptide pools generated from WA1 and BA.1 were evaluated. Pre-post comparisons were made by Wilcoxon paired t-tests, inter-cohort comparisons by Mann-Whitney t-test. RESULTS: This cohort includes 25 participants on anti-CD20 therapy, 12 on S1PR modulators, and 14 healthy controls. Among those on anti-CD20 therapy, neutralizing antibodies to WA1 were significantly reduced compared to healthy controls (ID50% GM post-vaccination of 8.1 ± 2.8 in anti-CD20 therapy group vs 452.6 ± 8.442 healthy controls, P < 0.0001) and neutralizing antibodies to BA.1 were below the threshold of detection nearly universally. However, cellular responses, including to Omicron-specific peptides, were not significantly different from controls. Among those on S1PR modulators, neutralizing antibodies to WA1 were detected in a minority, and only 3/12 had neutralizing antibodies just at the limit of detection to BA.1. Cellular responses to Spike antigen in those on S1PR modulators were reduced by a factor of 100 compared to controls (median 0.0008% vs. 0.08%, p < 0.001) and were not significantly "boosted" by a third injection. CONCLUSIONS: Participants on anti-CD20 and S1PR modulator therapies had impaired antibody neutralization capacity, particularly to BA.1, even after a third vaccine. T cell responses were not affected by anti-CD20 therapies, but were nearly abrogated by S1PR modulators. These results have clinical implications warranting further study.

T1 /T2 ratio from 3T MRI improves multiple sclerosis cortical lesion contrast.

BACKGROUND AND PURPOSE: Cortical demyelinated lesions are prevalent in multiple sclerosis (MS), associated with disability, and have recently been incorporated into MS diagnostic criteria. Presently, advanced and ultrahigh-field MRIs-not routinely available in clinical practice-are the most sensitive methods for detection of cortical lesions. Approaches utilizing MRI sequences obtainable in routine clinical practice remain an unmet need. We plan to assess the sensitivity of the ratio of T1 -weighted and T2 -weighted (T1 /T2 ) signal intensity for focal cortical lesions in comparison to other high-field imaging methods. METHODS: 3-Tesla and 7-Tesla MRI collected from 10 adults with MS were included in the study. T1 /T2 images were calculated by dividing 3T T1 -weighted (T1 w) images by 3T T2 -weighted (T2 w) fluid-attenuated inversion recovery images for each participant. A total of 614 cortical lesions were identified using 7T T2 *w and T1 w images and corresponding voxels were assessed on registered 3T images. Signal intensities were compared across 3T imaging sequences, including T1 /T2 , T1 w, T2 w, and inversion recovery susceptibility-weighted imaging with enhanced T2 weighting (IR-SWIET) images. RESULTS: T1 /T2 images demonstrated a larger contrast between median lesional and nonlesional cortical signal intensity (median ratio = 1.29, range: 1.19-1.38) when compared to T1 w (1.01, 0.97-1.10, p < .002), T2 w (1.17, 1.07-1.26, p < .002), and IR-SWIET (1.21, 1.01-1.29, p < .03). CONCLUSION: T1 /T2 images are sensitive to cortical lesions. Approaches incorporating T1 /T2 could improve the accessibility of cortical lesion detection in research settings and clinical practice.

Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues.

The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.

Oncogenic RAS commandeers amino acid sensing machinery to aberrantly activate mTORC1 in multiple myeloma.

Oncogenic RAS mutations are common in multiple myeloma (MM), an incurable malignancy of plasma cells. However, the mechanisms of pathogenic RAS signaling in this disease remain enigmatic and difficult to inhibit therapeutically. We employ an unbiased proteogenomic approach to dissect RAS signaling in MM. We discover that mutant isoforms of RAS organize a signaling complex with the amino acid transporter, SLC3A2, and MTOR on endolysosomes, which directly activates mTORC1 by co-opting amino acid sensing pathways. MM tumors with high expression of mTORC1-dependent genes are more aggressive and enriched in RAS mutations, and we detect interactions between RAS and MTOR in MM patient tumors harboring mutant RAS isoforms. Inhibition of RAS-dependent mTORC1 activity synergizes with MEK and ERK inhibitors to quench pathogenic RAS signaling in MM cells. This study redefines the RAS pathway in MM and provides a mechanistic and rational basis to target this mode of RAS signaling.

From pathology to MRI and back: Clinically relevant biomarkers of multiple sclerosis lesions.

Focal lesions in both white and gray matter are characteristic of multiple sclerosis (MS). Histopathological studies have helped define the main underlying pathological processes involved in lesion formation and evolution, serving as a gold standard for many years. However, histopathology suffers from an intrinsic bias resulting from over-reliance on tissue samples from late stages of the disease or atypical cases and is inadequate for routine patient assessment. Pathological-radiological correlative studies have established advanced MRI's sensitivity to several relevant MS-pathological substrates and its practicality for assessing dynamic changes and following lesions over time. This review focuses on novel imaging techniques that serve as biomarkers of critical pathological substrates of MS lesions: the central vein, chronic inflammation, remyelination and repair, and cortical lesions. For each pathological process, we address the correlative value of MRI to MS pathology, its contribution in elucidating MS pathology in vivo, and the clinical utility of the imaging biomarker.