Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA

Background: Early cancer detection could identify tumors at a time when outcomes are superior and treatment is less morbid. This prospective case-control sub-study (from NCT02889978 and NCT03085888) assessed the performance of targeted methylation analysis of circulating cell-free DNA (cfDNA) to detect and localize multiple cancer types across all stages at high specificity. / Participants and methods: The 6689 participants [2482 cancer (>50 cancer types), 4207 non-cancer] were divided into training and validation sets. Plasma cfDNA underwent bisulfite sequencing targeting a panel of >100 000 informative methylation regions. A classifier was developed and validated for cancer detection and tissue of origin (TOO) localization. / Results: Performance was consistent in training and validation sets. In validation, specificity was 99.3% [95% confidence interval (CI): 98.3% to 99.8%; 0.7% false-positive rate (FPR)]. Stage I–III sensitivity was 67.3% (CI: 60.7% to 73.3%) in a pre-specified set of 12 cancer types (anus, bladder, colon/rectum, esophagus, head and neck, liver/bile-duct, lung, lymphoma, ovary, pancreas, plasma cell neoplasm, stomach), which account for ∼63% of US cancer deaths annually, and was 43.9% (CI: 39.4% to 48.5%) in all cancer types. Detection increased with increasing stage: in the pre-specified cancer types sensitivity was 39% (CI: 27% to 52%) in stage I, 69% (CI: 56% to 80%) in stage II, 83% (CI: 75% to 90%) in stage III, and 92% (CI: 86% to 96%) in stage IV. In all cancer types sensitivity was 18% (CI: 13% to 25%) in stage I, 43% (CI: 35% to 51%) in stage II, 81% (CI: 73% to 87%) in stage III, and 93% (CI: 87% to 96%) in stage IV. TOO was predicted in 96% of samples with cancer-like signal; of those, the TOO localization was accurate in 93%. / Conclusions: cfDNA sequencing leveraging informative methylation patterns detected more than 50 cancer types across stages. Considering the potential value of early detection in deadly malignancies, further evaluation of this test is justified in prospective population-level studies

Multi-cancer early detection test sensitivity for cancers with and without current population-level screening options

There are four solid tumors with common screening options in the average-risk population aged 21 to 75 years (breast, cervical, colorectal, and, based on personalized risk assessment, prostate), but many cancers lack recommended population screening and are often detected at advanced stages when mortality is high. Blood-based multi-cancer early detection tests have the potential to improve cancer mortality through additional population screening. Reported here is a post-hoc analysis from the third Circulating Cell-free Genome Atlas substudy to examine multi-cancer early detection test performance in solid tumors with and without population screening recommendations and in hematologic malignancies. Participants with cancer in the third Circulating Cell-free Genome Atlas substudy analysis were split into three subgroups: solid screened tumors (breast, cervical, colorectal, prostate), solid unscreened tumors, and hematologic malignancies. In this post hoc analysis, sensitivity is reported for each subgroup across all ages and those aged ⩾50 years overall, by cancer, and by clinical cancer stage. Aggregate sensitivity in the solid screened, solid unscreened, and hematologic malignancy subgroups was 34%, 66%, and 55% across all cancer stages, respectively; restricting to participants aged ⩾50 years showed similar aggregate sensitivity. Aggregate sensitivity was 27%, 53%, and 60% across stages I to III, respectively. Within the solid unscreened subgroup, aggregate sensitivity was >75% in 8/18 cancers (44%) and >50% in 13/18 (72%). This multi-cancer early detection test detected cancer signals at high (>75%) sensitivity for multiple cancers without existing population screening recommendations, suggesting its potential to complement recommended screening programs. Clinical trial identifier: NCT02889978

Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set

BACKGROUND: A multi-cancer early detection (MCED) test used to complement existing screening could increase the number of cancers detected through population screening, potentially improving clinical outcomes. The Circulating Cell-free Genome Atlas study (CCGA; NCT02889978) was a prospective, case-controlled, observational study and demonstrated that a blood-based MCED test utilizing cell-free DNA (cfDNA) sequencing in combination with machine learning could detect cancer signals across multiple cancer types and predict cancer signal origin (CSO) with high accuracy. The objective of this third and final CCGA substudy was to validate an MCED test version further refined for use as a screening tool. PATIENTS AND METHODS: This pre-specified substudy included 4077 participants in an independent validation set (cancer: n = 2823; non-cancer: n = 1254, non-cancer status confirmed at year-one follow-up). Specificity, sensitivity, and CSO prediction accuracy were measured. RESULTS: Specificity for cancer signal detection was 99.5% [95% confidence interval (CI): 99.0% to 99.8%]. Overall sensitivity for cancer signal detection was 51.5% (49.6% to 53.3%); sensitivity increased with stage [stage I: 16.8% (14.5% to 19.5%), stage II: 40.4% (36.8% to 44.1%), stage III: 77.0% (73.4% to 80.3%), stage IV: 90.1% (87.5% to 92.2%)]. Stage I-III sensitivity was 67.6% (64.4% to 70.6%) in 12 pre-specified cancers that account for approximately two-thirds of annual USA cancer deaths and was 40.7% (38.7% to 42.9%) in all cancers. Cancer signals were detected across >50 cancer types. Overall accuracy of CSO prediction in true positives was 88.7% (87.0% to 90.2%). CONCLUSION: In this pre-specified, large-scale, clinical validation substudy, the MCED test demonstrated high specificity and accuracy of CSO prediction and detected cancer signals across a wide diversity of cancers. These results support the feasibility of this blood-based MCED test as a complement to existing single-cancer screening tests. CLINICAL TRIAL NUMBER: NCT02889978

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Evaluation of cell-free DNA approaches for multi-cancer early detection

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test

Evaluation of bioactive sphingolipids in 4-HPR-resistant leukemia cells

<p>Abstract</p> <p>Background</p> <p><it>N</it>-(4-hydroxyphenyl)retinamide (4-HPR, fenretinide) is a synthetic retinoid with potent pro-apoptotic activity against several types of cancer, but little is known regarding mechanisms leading to chemoresistance. Ceramide and, more recently, other sphingolipid species (e.g., dihydroceramide and dihydrosphingosine) have been implicated in 4-HPR-mediated tumor cell death. Because sphingolipid metabolism has been reported to be altered in drug-resistant tumor cells, we studied the implication of sphingolipids in acquired resistance to 4-HPR based on an acute lymphoblastic leukemia model.</p> <p>Methods</p> <p>CCRF-CEM cell lines resistant to 4-HPR were obtained by gradual selection. Endogenous sphingolipid profiles and in situ enzymatic activities were determined by LC/MS, and resistance to 4-HPR or to alternative treatments was measured using the XTT viability assay and annexin V-FITC/propidium iodide labeling.</p> <p>Results</p> <p>No major crossresistance was observed against other antitumoral compounds (i.e. paclitaxel, cisplatin, doxorubicin hydrochloride) or agents (i.e. ultra violet C, hydrogen peroxide) also described as sphingolipid modulators. CCRF-CEM cell lines resistant to 4-HPR exhibited a distinctive endogenous sphingolipid profile that correlated with inhibition of dihydroceramide desaturase. Cells maintained acquired resistance to 4-HPR after the removal of 4-HPR though the sphingolipid profile returned to control levels. On the other hand, combined treatment with sphingosine kinase inhibitors (unnatural (dihydro)sphingosines ((dh)Sph)) and glucosylceramide synthase inhibitor (PPMP) in the presence or absence of 4-HPR increased cellular (dh)Sph (but not ceramide) levels and were highly toxic for both parental and resistant cells.</p> <p>Conclusions</p> <p>In the leukemia model, acquired resistance to 4-HPR is selective and persists in the absence of sphingolipid profile alteration. Therapeutically, the data demonstrate that alternative sphingolipid-modulating antitumoral strategies are suitable for both 4-HPR-resistant and sensitive leukemia cells. Thus, whereas sphingolipids may not be critical for maintaining resistance to 4-HPR, manipulation of cytotoxic sphingolipids should be considered a viable approach for overcoming resistance.</p

A Rescorla-Wagner Drift-Diffusion Model of Conditioning and Timing

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used

Pediatric multiple sclerosis: update on diagnostic criteria, imaging, histopathology and treatment choices

Pediatric multiple sclerosis (MS) represents less than 5% of the MS population, but patients with pediatric-onset disease reach permanent disability at a younger age than adult onset patients. Accurate diagnosis at presentation and optimal long-term treatment is vital to mitigate ongoing neuroinflammation and irreversible neurodegeneration. However, it may be difficult to early differentiate pediatric MS from acute disseminated encephalomyelitis (ADEM) and neuromyelitis optica spectrum disorders (NMOSD) as they often have atypical presentation that differs from that of adult-onset MS. The purpose of this review is to summarize the updated views on diagnostic criteria, imaging, histopathology and treatment choices

An ecological future for weed science to sustain crop production and the environment. A review

Sustainable strategies for managing weeds are critical to meeting agriculture's potential to feed the world's population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weedsat the agroecosystem levelthat, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management