In addition to the shared weights of the synaptic connections, we proposed a new neural network that includes the synaptic effective range weights for both the forward and back propagation. And lots of simulations were used which RNN cannot be achieved. The simulations of PNN fit very well in experiments and hypotheses of 6 papers CNS Journals, 6 papers of CNS family Journals and 1 paper top Physics Journal [14-26]. The brain plasticity in positive or negative memory may be quantum and produce short-term memory, and exhibits an exponential decay in the wave function over a period of time, produced in the hippocampus. And exponential decay occurs due to barriers, and barriers can refer to astrocytes. Brain plasticity in working memory flows through the brain, from the hippocampus to the cortex, through directional derivatives. The strong working memory brain plasticity turns to long-term memory means maximum of directional derivatives, and maximum of directional derivatives is gradient. Thus, long-term memory signifies the gradient of brain plasticity in working memory. The process of short-term memory turns to long-term memory is the process of non-classically turns to classically. Astrocytic cortex memory persistence factor also inhibits local synaptic accumulation, and the model inspires experiments. This could be the process of astrocytes phagocytose synapses is driven by both positive and negative memories of plasticity in the brain. In simulation, it is possible that thicker cortices and more diverse individuals within the brain could have high IQ, but thickest cortices and most diverse individuals may have low IQ in simulation. PSO considers global solution or best previous solution, but also considers relatively good and relatively inferior solution. And PNN modified ResNet to consider memory gradient. The simple PNN only considers astrocytes phagocytosed synapses. <<<

Despite the success of Transformer models in vision and language tasks, they often learn knowledge from enormous data implicitly and cannot utilize structured input data directly. On the other hand, structured learning approaches such as graph neural networks (GNNs) that integrate prior information can barely compete with Transformer models. In this work, we aim to benefit from both worlds and propose a novel Multimodal Graph Transformer for question answering tasks that requires performing reasoning across multiple modalities. We introduce a graph-involved plug-and-play quasi-attention mechanism to incorporate multimodal graph information, acquired from text and visual data, to the vanilla self-attention as effective prior. In particular, we construct the text graph, dense region graph, and semantic graph to generate adjacency matrices, and then compose them with input vision and language features to perform downstream reasoning. Such a way of regularizing self-attention with graph information significantly improves the inferring ability and helps align features from different modalities. We validate the effectiveness of Multimodal Graph Transformer over its Transformer baselines on GQA, VQAv2, and MultiModalQA datasets. <<<

Background: Qihuang needle therapy is a newly developed acupuncture therapy to treat tic disorders in clinical practice. However, the mechanism to reduce tic severity remains unknown. Changes in intestinal flora and circulation metabolites are perhaps the potential pathogenesis of tic disorders. As a result, we present a protocol for a controlled clinical trial using multi-omics analysis to probe the mechanism of the Qihuang needle in managing tic disorders.Methods: This is a matched-pairs design, controlled, clinical trial for patients with tic disorders. Participants will be allocated to either an experimental group or a healthy control group. The main acupoints are Baihui (GV20), Yintang (EX-HN3), and Jueyinshu (BL14). The experimental group will receive Qihuang needle therapy for a month, while the control group will receive no interventions.Expected outcomes: The change in the severity of the tic disorder is set as the main outcome. Secondary outcomes include gastrointestinal severity index and recurrence rate, which will be calculated after a 12-week follow-up. Gut microbiota, measured by 16S rRNA gene sequencing; serum metabolomics, assessed via LC/MS; and serum zonulin, assessed by enzyme-linked immunosorbent assay (ELISA), will be used as biological specimen analysis outcomes. The present study will investigate the possible interactions between intestinal flora and serum metabolites and the improvement of clinical profiles, which may elucidate the mechanism of Qihuang needle therapy for tic disorders.Trial registration: This trial is registered at the Chinese Clinical Trial Registry (http://www.chictr.org.cn/). Registration number: ChiCTR2200057723, Date: 2022-04-14. <<<

Yazan N Billeh, Binghuang Cai, Sergey L Gratiy, Kael Dai, Ramakrishnan Iyer, Nathan W Gouwens, Reza Abbasi-Asl, Xiaoxuan Jia, Joshua H Siegle, Shawn R Olsen, Christof Koch, Stefan Mihalas, Anton Arkhipov <<<

Structural rules underlying functional properties of cortical circuits are poorly understood. To explore these rules systematically, we integrated information from extensive literature curation and large-scale experimental surveys into a data-driven, biologically realistic simulation of the awake mouse primary visual cortex. The model was constructed at two levels of granularity, using either biophysically detailed or point neurons. Both variants have identical network connectivity and were compared to each other and to experimental recordings of visual-driven neural activity. While tuning these networks to recapitulate experimental data, we identified rules governing cell-class-specific connectivity and synaptic strengths. These structural constraints constitute hypotheses that can be tested experimentally. Despite their distinct single-cell abstraction, both spatially extended and point models perform similarly at the level of firing rate distributions for the questions we investigated. All data and models are freely available as a resource for the community. <<<

Ann H Partridge, Samuel M Niman, Monica Ruggeri, Fedro A Peccatori, Hatem A Azim, Marco Colleoni, Cristina Saura, Chikako Shimizu, Anna B Sætersdal, Judith R Kroep, Audrey Mailliez, Ellen Warner, Virginia F Borges, Frédéric Amant, Andrea Gombos, Akemi Kataoka, Christine Rousset-Jablonski, Simona Borstnar, Junko Takei, Jeong E Lee, Janice M Walshe, Manuel Ruíz-Borrego, Halle C F Moore, Christobel Saunders, Vesna Bjelic-Radisic, Snezana Susnjar, Fatima Cardoso, Karen L Smith, Teresa Ferreiro, Karin Ribi, Kathryn Ruddy, Roswitha Kammler, Sarra El-Abed, Giuseppe Viale, Martine Piccart, Larissa A Korde, Aron Goldhirsch, Richard D Gelber, Olivia Pagani, International Breast Cancer Study Group, POSITIVE Trial Collaborators <<<

BACKGROUND: Prospective data on the risk of recurrence among women with hormone receptor-positive early breast cancer who temporarily discontinue endocrine therapy to attempt pregnancy are lacking.METHODS: We conducted a single-group trial in which we evaluated the temporary interruption of adjuvant endocrine therapy to attempt pregnancy in young women with previous breast cancer. Eligible women were 42 years of age or younger; had had stage I, II, or III disease; had received adjuvant endocrine therapy for 18 to 30 months; and desired pregnancy. The primary end point was the number of breast cancer events (defined as local, regional, or distant recurrence of invasive breast cancer or new contralateral invasive breast cancer) during follow-up. The primary analysis was planned to be performed after 1600 patient-years of follow-up. The prespecified safety threshold was the occurrence of 46 breast cancer events during this period. Breast cancer outcomes in this treatment-interruption group were compared with those in an external control cohort consisting of women who would have met the entry criteria for the current trial.RESULTS: Among 516 women, the median age was 37 years, the median time from breast cancer diagnosis to enrollment was 29 months, and 93.4% had stage I or II disease. Among 497 women who were followed for pregnancy status, 368 (74.0%) had at least one pregnancy and 317 (63.8%) had at least one live birth. In total, 365 babies were born. At 1638 patient-years of follow-up (median follow-up, 41 months), 44 patients had a breast cancer event, a result that did not exceed the safety threshold. The 3-year incidence of breast cancer events was 8.9% (95% confidence interval [CI], 6.3 to 11.6) in the treatment-interruption group and 9.2% (95% CI, 7.6 to 10.8) in the control cohort.CONCLUSIONS: Among select women with previous hormone receptor-positive early breast cancer, temporary interruption of endocrine therapy to attempt pregnancy did not confer a greater short-term risk of breast cancer events, including distant recurrence, than that in the external control cohort. Further follow-up is critical to inform longer-term safety. (Funded by ETOP IBCSG Partners Foundation and others; POSITIVE ClinicalTrials.gov number, NCT02308085.). <<<

Decision-making requires flexibility to rapidly switch one's actions in response to sensory stimuli depending on information stored in memory. We identified cortical areas and neural activity patterns underlying this flexibility during virtual navigation, where mice switched navigation toward or away from a visual cue depending on its match to a remembered cue. Optogenetics screening identified V1, posterior parietal cortex (PPC), and retrosplenial cortex (RSC) as necessary for accurate decisions. Calcium imaging revealed neurons that can mediate rapid navigation switches by encoding a mixture of a current and remembered visual cue. These mixed selectivity neurons emerged through task learning and predicted the mouse's choices by forming efficient population codes before correct, but not incorrect, choices. They were distributed across posterior cortex, even V1, and were densest in RSC and sparsest in PPC. We propose flexibility in navigation decisions arises from neurons that mix visual and memory information within a visual-parietal-retrosplenial network. <<<

Desheng Liang, David S Cram, Hu Tan, Siyuan Linpeng, Yingdi Liu, Huaiyu Sun, Yu Zhang, Feng Tian, Hongmin Zhu, Mengnan Xu, Hua Wang, Fuli Yu, Lingqian Wu <<<

PURPOSE: To assess the clinical performance of an expanded noninvasive prenatal screening (NIPS) test ("NIPS-Plus") for detection of both aneuploidy and genome-wide microdeletion/microduplication syndromes (MMS).METHODS: A total of 94,085 women with a singleton pregnancy were prospectively enrolled in the study. The cell-free plasma DNA was directly sequenced without intermediate amplification and fetal abnormalities identified using an improved copy-number variation (CNV) calling algorithm.RESULTS: A total of 1128 pregnancies (1.2%) were scored positive for clinically significant fetal chromosome abnormalities. This comprised 965 aneuploidies (1.026%) and 163 (0.174%) MMS. From follow-up tests, the positive predictive values (PPVs) for T21, T18, T13, rare trisomies, and sex chromosome aneuploidies were calculated as 95%, 82%, 46%, 29%, and 47%, respectively. For known MMS (n = 32), PPVs were 93% (DiGeorge), 68% (22q11.22 microduplication), 75% (Prader-Willi/Angleman), and 50% (Cri du Chat). For the remaining genome-wide MMS (n = 88), combined PPVs were 32% (CNVs ≥10 Mb) and 19% (CNVs <10 Mb).CONCLUSION: NIPS-Plus yielded high PPVs for common aneuploidies and DiGeorge syndrome, and moderate PPVs for other MMS. Our results present compelling evidence that NIPS-Plus can be used as a first-tier pregnancy screening method to improve detection rates of clinically significant fetal chromosome abnormalities. <<<

Background Approximately 40% of pancreatic tumors smaller than 2 cm are missed at abdominal CT. Purpose To develop and to validate a deep learning (DL)-based tool able to detect pancreatic cancer at CT. Materials and Methods Retrospectively collected contrast-enhanced CT studies in patients diagnosed with pancreatic cancer between January 2006 and July 2018 were compared with CT studies of individuals with a normal pancreas (control group) obtained between January 2004 and December 2019. An end-to-end tool comprising a segmentation convolutional neural network (CNN) and a classifier ensembling five CNNs was developed and validated in the internal test set and a nationwide real-world validation set. The sensitivities of the computer-aided detection (CAD) tool and radiologist interpretation were compared using the McNemar test. Results A total of 546 patients with pancreatic cancer (mean age, 65 years ± 12 [SD], 297 men) and 733 control subjects were randomly divided into training, validation, and test sets. In the internal test set, the DL tool achieved 89.9% (98 of 109; 95% CI: 82.7, 94.9) sensitivity and 95.9% (141 of 147; 95% CI: 91.3, 98.5) specificity (area under the receiver operating characteristic curve [AUC], 0.96; 95% CI: 0.94, 0.99), without a significant difference ( = .11) in sensitivity compared with the original radiologist report (96.1% [98 of 102]; 95% CI: 90.3, 98.9). In a test set of 1473 real-world CT studies (669 malignant, 804 control) from institutions throughout Taiwan, the DL tool distinguished between CT malignant and control studies with 89.7% (600 of 669; 95% CI: 87.1, 91.9) sensitivity and 92.8% specificity (746 of 804; 95% CI: 90.8, 94.5) (AUC, 0.95; 95% CI: 0.94, 0.96), with 74.7% (68 of 91; 95% CI: 64.5, 83.3) sensitivity for malignancies smaller than 2 cm. Conclusion The deep learning-based tool enabled accurate detection of pancreatic cancer on CT scans, with reasonable sensitivity for tumors smaller than 2 cm. © RSNA, 2022 See also the editorial by Aisen and Rodrigues in this issue. <<<

The effects of potentially important processing conditions at each step of differential precipitation on the yield and purity of κ-casein fractionated from caprine micellar casein concentrate (MCC) were investigated. The optimal conditions were: rehydrating (3% casein) MCC using homogenisation followed by dissociating micelles at pH 11.0; complexing caseins using 45 mm added Ca at 25 °C for 60 min, followed by precipitating β-/αS-caseins using 2 m acetic acid at pH 7.0 again at 25 °C for 60 min. Two fractionation cycles were used with 50 mm added Ca for the second cycle, followed by precipitating κ-casein at pH 3.8 and 50 °C. To increase processing capacity for scale-up, increased casein concentrations of 4–7% along with 60 mm added Ca resulted in comparable yields and purity of the κ-casein. Maximum yield and purity of 84.6% and 84.4%, respectively, were achieved for κ-casein from the MCC dispersions at 4% casein. <<<

This survey provides an overview of higher-order tensor decompositions, their applications, and available software. A tensor is a multidimensional or N-way array. Decompositions of higher-order tensors (i.e., N-way arrays with N≥3) have applications in psycho-metrics, chemometrics, signal processing, numerical linear algebra, computer vision, numerical analysis, data mining, neuroscience, graph analysis, and elsewhere. Two particular tensor decompositions can be considered to be higher-order extensions of the matrix singular value decomposition: CANDECOMP/PARAFAC (CP) decomposes a tensor as a sum of rank-one tensors, and the Tucker decomposition is a higher-order form of principal component analysis. There are many other tensor decompositions, including INDSCAL, PARAFAC2, CANDELINC, DEDICOM, and PARATUCK2 as well as nonnegative variants of all of the above. The N-way Toolbox, Tensor Toolbox, and Multilinear Engine are examples of software packages for working with tensors. <<<

Federico Comitani, Joshua O Nash, Sarah Cohen-Gogo, Astra I Chang, Timmy T Wen, Anant Maheshwari, Bipasha Goyal, Earvin S Tio, Kevin Tabatabaei, Chelsea Mayoh, Regis Zhao, Ben Ho, Ledia Brunga, John E G Lawrence, Petra Balogh, Adrienne M Flanagan, Sarah Teichmann, Annie Huang, Vijay Ramaswamy, Johann Hitzler, Jonathan D Wasserman, Rebecca A Gladdy, Brendan C Dickson, Uri Tabori, Mark J Cowley, Sam Behjati, David Malkin, Anita Villani, Meredith S Irwin, Adam Shlien <<<

The causes of pediatric cancers' distinctiveness compared to adult-onset tumors of the same type are not completely clear and not fully explained by their genomes. In this study, we used an optimized multilevel RNA clustering approach to derive molecular definitions for most childhood cancers. Applying this method to 13,313 transcriptomes, we constructed a pediatric cancer atlas to explore age-associated changes. Tumor entities were sometimes unexpectedly grouped due to common lineages, drivers or stemness profiles. Some established entities were divided into subgroups that predicted outcome better than current diagnostic approaches. These definitions account for inter-tumoral and intra-tumoral heterogeneity and have the potential of enabling reproducible, quantifiable diagnostics. As a whole, childhood tumors had more transcriptional diversity than adult tumors, maintaining greater expression flexibility. To apply these insights, we designed an ensemble convolutional neural network classifier. We show that this tool was able to match or clarify the diagnosis for 85% of childhood tumors in a prospective cohort. If further validated, this framework could be extended to derive molecular definitions for all cancer types. <<<

Ignaty Leshchiner, Edmund A Mroz, Justin Cha, Daniel Rosebrock, Oliver Spiro, Juliana Bonilla-Velez, William C Faquin, Armida Lefranc-Torres, Derrick T Lin, William A Michaud, Gad Getz, James W Rocco <<<

Analysis of premalignant tissue has identified the typical order of somatic events leading to invasive tumors in several cancer types. For other cancers, premalignant tissue is unobtainable, leaving genetic progression unknown. Here, we demonstrate how to infer progression from exome sequencing of primary tumors. Our computational method, PhylogicNDT, recapitulated the previous experimentally determined genetic progression of human papillomavirus-negative (HPV) head and neck squamous cell carcinoma (HNSCC). We then evaluated HPV HNSCC, which lacks premalignant tissue, and uncovered its previously unknown progression, identifying early drivers. We converted relative timing estimates of driver mutations and HPV integration to years before diagnosis based on a clock-like mutational signature. We associated the timing of transitions to aneuploidy with increased intratumor genetic heterogeneity and shorter overall survival. Our approach can establish previously unknown early genetic progression of cancers with unobtainable premalignant tissue, supporting development of experimental models and methods for early detection, interception and prognostication. <<<

The amygdala is assumed to contribute to a bottom-up attentional bias during visual processing of emotional faces. Still, how its response to emotion interacts with top-down attention is not fully understood. It is also unclear if amygdala activity and scalp EEG respond to emotion and attention in a similar way. Therefore, we studied the interaction of emotion and attention during face processing in oscillatory gamma-band activity (GBA) in the amygdala and on the scalp. Amygdala signals were recorded via intracranial EEG (iEEG) in 9 patients with epilepsy. Scalp recordings were collected from 19 healthy participants. Three randomized blocks of angry, neutral, and happy faces were presented, and either negative, neutral, or positive expressions were denoted as targets. Both groups detected happy faces fastest and most accurately. In the amygdala, the earliest effect was observed around 170 ms in high GBA (105-117.5 Hz) when neutral faces served as targets. Here, GBA was higher for emotional than neutral faces. During attention to negative faces, low GBA (< 90 Hz) increased specifically for angry faces both in the amygdala and over posterior scalp regions, albeit earlier on the scalp (60 ms) than in the amygdala (210 ms). From 570 ms, amygdala high GBA (117.5-145 Hz) was also increased for both angry and neutral, compared to happy, faces. When positive faces were the targets, GBA did not differentiate between expressions. The present data reveal that attention-independent emotion detection in amygdala high GBA may only occur during a neutral focus of attention. Top-down threat vigilance coordinates widespread low GBA, biasing stimulus processing in favor of negative faces. These results are in line with a multi-pathway model of emotion processing and help specify the role of GBA in this process by revealing how attentional focus can tune timing and amplitude of emotional GBA responses. <<<

Zheng Sun, Shi Huang, Meng Zhang, Qiyun Zhu, Niina Haiminen, Anna Paola Carrieri, Yoshiki Vázquez-Baeza, Laxmi Parida, Ho-Cheol Kim, Rob Knight, Yang-Yu Liu <<<

Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling. <<<

Deformable image registration is one of the fundamental tasks in medical imaging. Classical registration algorithms usually require a high computational cost for iterative optimizations. Although deep-learning-based methods have been developed for fast image registration, it is still challenging to obtain realistic continuous deformations from a moving image to a fixed image with less topological folding problem. To address this, here we present a novel diffusion-model-based image registration method, called DiffuseMorph. DiffuseMorph not only generates synthetic deformed images through reverse diffusion but also allows image registration by deformation fields. Specifically, the deformation fields are generated by the conditional score function of the deformation between the moving and fixed images, so that the registration can be performed from continuous deformation by simply scaling the latent feature of the score. Experimental results on 2D facial and 3D medical image registration tasks demonstrate that our method provides flexible deformations with topology preservation capability. <<<

Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data. <<<

Alexandra Mousset, Enora Lecorgne, Isabelle Bourget, Pascal Lopez, Kitti Jenovai, Julien Cherfils-Vicini, Chloé Dominici, Géraldine Rios, Cédric Girard-Riboulleau, Bodu Liu, David L Spector, Sidse Ehmsen, Shufang Renault, Caroline Hego, Fatima Mechta-Grigoriou, François-Clément Bidard, Mikkel Green Terp, Mikala Egeblad, Cédric Gaggioli, Jean Albrengues <<<

Metastasis is the major cause of cancer death, and the development of therapy resistance is common. The tumor microenvironment can confer chemotherapy resistance (chemoresistance), but little is known about how specific host cells influence therapy outcome. We show that chemotherapy induces neutrophil recruitment and neutrophil extracellular trap (NET) formation, which reduces therapy response in mouse models of breast cancer lung metastasis. We reveal that chemotherapy-treated cancer cells secrete IL-1β, which in turn triggers NET formation. Two NET-associated proteins are required to induce chemoresistance: integrin-αvβ1, which traps latent TGF-β, and matrix metalloproteinase 9, which cleaves and activates the trapped latent TGF-β. TGF-β activation causes cancer cells to undergo epithelial-to-mesenchymal transition and correlates with chemoresistance. Our work demonstrates that NETs regulate the activities of neighboring cells by trapping and activating cytokines and suggests that chemoresistance in the metastatic setting can be reduced or prevented by targeting the IL-1β-NET-TGF-β axis. <<<

Long Song, Jie Liu, Beilu Cao, Bin Liu, Xiaoping Zhang, Zhaoyan Chen, Chaoqun Dong, Xiangqing Liu, Zhaoheng Zhang, Wenxi Wang, Lingling Chai, Jing Liu, Jun Zhu, Shubin Cui, Fei He, Huiru Peng, Zhaorong Hu, Zhenqi Su, Weilong Guo, Mingming Xin, Yingyin Yao, Yong Yan, Yinming Song, Guihua Bai, Qixin Sun, Zhongfu Ni <<<

Modern green revolution varieties of wheat (Triticum aestivum L.) confer semi-dwarf and lodging-resistant plant architecture owing to the Reduced height-B1b (Rht-B1b) and Rht-D1b alleles. However, both Rht-B1b and Rht-D1b are gain-of-function mutant alleles encoding gibberellin signalling repressors that stably repress plant growth and negatively affect nitrogen-use efficiency and grain filling. Therefore, the green revolution varieties of wheat harbouring Rht-B1b or Rht-D1b usually produce smaller grain and require higher nitrogen fertilizer inputs to maintain their grain yields. Here we describe a strategy to design semi-dwarf wheat varieties without the need for Rht-B1b or Rht-D1b alleles. We discovered that absence of Rht-B1 and ZnF-B (encoding a RING-type E3 ligase) through a natural deletion of a haploblock of about 500 kilobases shaped semi-dwarf plants with more compact plant architecture and substantially improved grain yield (up to 15.2%) in field trials. Further genetic analysis confirmed that the deletion of ZnF-B induced the semi-dwarf trait in the absence of the Rht-B1b and Rht-D1b alleles through attenuating brassinosteroid (BR) perception. ZnF acts as a BR signalling activator to facilitate proteasomal destruction of the BR signalling repressor BRI1 kinase inhibitor 1 (TaBKI1), and loss of ZnF stabilizes TaBKI1 to block BR signalling transduction. Our findings not only identified a pivotal BR signalling modulator but also provided a creative strategy to design high-yield semi-dwarf wheat varieties by manipulating the BR signal pathway to sustain wheat production. <<<

Zachariah H. Foda , Akshaya V. Annapragada , Kavya Boyapati , Daniel C. Bruhm , Nicholas A. Vulpescu , Jamie E. Medina , Dimitrios Mathios , Stephen Cristiano , Noushin Niknafs , Harry T. Luu , Michael G. Goggins , Robert A. Anders , Jing Sun , Shruti H. Mehta , David L. Thomas , Gregory D. Kirk , Vilmos Adleff , Jillian Phallen , Robert B. Scharpf , Amy K. Kim , Victor E. Velculescu <<<

Abstract Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high-risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA fragmentome analyses to evaluate 724 individuals from the US, EU, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multi-feature fragmentome data, the sensitivity for detecting cancer was 88% in an average risk population at 98% specificity, and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for non-invasive cancer detection. <<<

Andrew Chow, Sara Schad, Michael D Green, Matthew D Hellmann, Viola Allaj, Nicholas Ceglia, Giulia Zago, Nisargbhai S Shah, Sai Kiran Sharma, Marissa Mattar, Joseph Chan, Hira Rizvi, Hong Zhong, Cailian Liu, Yonina Bykov, Dmitriy Zamarin, Hongyu Shi, Sadna Budhu, Corrin Wohlhieter, Fathema Uddin, Aditi Gupta, Inna Khodos, Jessica J Waninger, Angel Qin, Geoffrey J Markowitz, Vivek Mittal, Vinod Balachandran, Jennifer N Durham, Dung T Le, Weiping Zou, Sohrab P Shah, Andrew McPherson, Katherine Panageas, Jason S Lewis, Justin S A Perry, Elisa de Stanchina, Triparna Sen, John T Poirier, Jedd D Wolchok, Charles M Rudin, Taha Merghoub <<<

Immune checkpoint blockade (ICB) has been a remarkable clinical advance for cancer; however, the majority of patients do not respond to ICB therapy. We show that metastatic disease in the pleural and peritoneal cavities is associated with poor clinical outcomes after ICB therapy. Cavity-resident macrophages express high levels of Tim-4, a receptor for phosphatidylserine (PS), and this is associated with reduced numbers of CD8 T cells with tumor-reactive features in pleural effusions and peritoneal ascites from patients with cancer. We mechanistically demonstrate that viable and cytotoxic anti-tumor CD8 T cells upregulate PS and this renders them susceptible to sequestration away from tumor targets and proliferation suppression by Tim-4 macrophages. Tim-4 blockade abrogates this sequestration and proliferation suppression and enhances anti-tumor efficacy in models of anti-PD-1 therapy and adoptive T cell therapy in mice. Thus, Tim-4 cavity-resident macrophages limit the efficacy of immunotherapies in these microenvironments. <<<