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Venous thromboembolism is a significant source of morbidity and mortality worldwide. Catheter-directed thrombolytics is the primary treatment used to relieve critical obstructions, though its efficacy varies based on the thrombus composition. Non-responsive portions of the specimen often remain in situ, which prohibits mechanistic investigation of lytic resistance or the development of diagnostic indicators for treatment outcomes. In this study, thrombus samples extracted from venous thromboembolism patients were analyzed ex vivo to determine their histological properties, susceptibility to lytic therapy, and imaging characteristics. A wide range of thrombus morphologies were observed, with a dependence on age and etymology of the specimen. Fibrinolytic inhibitors including PAI-1, alpha 2-antiplasmin, and TAFI were present in samples, which may contribute to the response venous thrombi to catheter-directed thrombolytics. Finally, a weak but significant correlation was observed between the response of the sample to lytic drug and its magnetic microstructure assessed with a quantitative MRI sequence. These findings highlight the myriad of changes in venous thrombi that may promote lytic resistance, and imaging metrics that correlate with treatment outcomes.

This study proposes the comprehensive index of biomarker (CIB), based on the consistency of a biomarker in case control (Youden index, J) and cohort studies (Crc), to evaluate biomarker efficacy. CIB was calculated as the mean of J and Crc. Analysis of the effect of sensitivity and specificity on CIB and ROC analysis of CIB were performed in simulated and actual datasets. J and CIB had similar values for high-probability events (say probability was 0.50), but there was a significant difference between J and CIB for low-probability events (say probability was 0.05). Therefore, as the subjects considered for diagnosis are usually symptomatic, the occurrence of a disease can be assumed to be a high-probability event. In contrast, as the subjects considered in screening for a disease are usually healthy and asymptomatic, the occurrence of a disease is assumed to be a low-probability event. Although J is the common index used to evaluate the diagnostic effectiveness, unfortunately, the J value is significantly larger than CIB value in a low-probability event, showing overestimation for screening purpose. CIB could have more potential than J for determining the screening efficacy of a biomarker. The efficacy of a biomarker could differ for diagnostic, screening, predictive, and prognostic purposes, and it would be better to evaluate the efficacy of biomarkers for specific systems or contexts.

Breast cancer; Predictive markers; Translational research Cáncer de mama; Maradores predictivos; Investigación traslacional Càncer de mama; Marcadors predictius; Recerca translacional Eribulin prolongs overall survival in patients with pre-treated advanced breast cancer. However, no biomarker exists to prospectively select patients who will benefit the most from this drug. SOLTI-1007-NeoEribulin is a phase II, open-label, two-cohort, exploratory pharmacogenomic study in patients with clinical stage I–II HER2-negative breast cancer receiving neoadjuvant eribulin monotherapy treatment. Primary objective was to explore the association of baseline tumor gene expression with pathological complete response in the breast (pCRB) at surgery. Key secondary objectives were pCRB rates in all patients and according to HR status, gene expression changes during treatment and safety. One-hundred one hormonal receptor-positive (HR + ) and seventy-three triple-negative breast cancer (TNBC) patients were recruited. The pCRB rates were 6.4% in all patients, 4.9% in HR + disease and 8.2% in TNBC. The TNBC cohort was interrupted due to a progression disease rate of 30.1%. The pCRB rates differed according to intrinsic subtypes: 28.6% in HER2-enriched, 11.1% in Normal-like, 7.9% in Luminal B, 5.9% in Basal-like and 0% in Luminal A (HER2-enriched vs. others odds ratio = 7.05, 95% CI 1.80–42.14; p-value = 0.032). Intrinsic subtype changes at surgery occurred in 33.3% of cases, mostly (49.0%) Luminal B converting to Luminal A or Basal-like converting to Normal-like. Baseline tumor-infiltrating lymphocytes (TILs) were significantly associated with pCR. Eribulin showed a good safety profile with a low response and pCRB rates. Patients with HER2-negative disease with a HER2-enriched profile may benefit the most from eribulin. In addition, significant biological activity of eribulin is observed in Luminal B and Basal-like subtypes.

HER2 is a predictive biomarker for HER2-targeted therapeutics. For antibody–drug conjugates (ADCs; e.g., trastuzumab emtansine (T-DM1)), HER2 is utilized as a transport gate for cytotoxic agents into the cell. ADC biomarkers may therefore be more complex, also reflecting the intracellular drug transport. Here we report on a positive correlation between the early endosome marker RAB5A and T-DM1 sensitivity in five HER2-positive cell lines. Correlation between RAB5A expression and T-DM1 sensitivity is confirmed in breast cancer patients treated with trastuzumab emtansine/pertuzumab in the I-SPY2 trial (NCT01042379), but not in the trastuzumab/paclitaxel control arm. The clinical correlation is further verified in patients from the KAMILLA trial (NCT01702571). In conclusion, our results suggest RAB5A as a predictive biomarker for T-DM1 response and outline proteins involved in endocytic trafficking as predictive biomarkers for ADCs., Antibody Drug Conjugates (ADCs) are emerging in the field of precision cancer medicine. Here, the authors suggest using endocytosis as a predictive biomarker for response

Early detection of infectious diseases is crucial for reducing transmission and facilitating early intervention. In this study, we built a real-time smartwatch-based alerting system that detects aberrant physiological and activity signals (heart rates and steps) associated with the onset of early infection and implemented this system in a prospective study. In a cohort of 3,318 participants, of whom 84 were infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), this system generated alerts for pre-symptomatic and asymptomatic SARS-CoV-2 infection in 67 (80%) of the infected individuals. Pre-symptomatic signals were observed at a median of 3 days before symptom onset. Examination of detailed survey responses provided by the participants revealed that other respiratory infections as well as events not associated with infection, such as stress, alcohol consumption and travel, could also trigger alerts, albeit at a much lower mean frequency (1.15 alert days per person compared to 3.42 alert days per person for coronavirus disease 2019 cases). Thus, analysis of smartwatch signals by an online detection algorithm provides advance warning of SARS-CoV-2 infection in a high percentage of cases. This study shows that a real-time alerting system can be used for early detection of infection and other stressors and employed on an open-source platform that is scalable to millions of users., In a prospective study, a smartwatch-based alerting system was able to detect pre-symptomatic and asymptomatic SARS-CoV-2 infection in a high percentage of cases.

Immune checkpoint inhibitors (ICIs) alone or in combination with chemotherapy have become one of the key approaches in the treatment of patients with advanced non-small cell lung cancer (NSCLC). Evaluation of level of PD-L1 (ligand of the programmed cell death receptor 1) expression on tumor cells using immunohistochemistry is the only approved option for determining the indications of ICIs in this group of patients. However, despite high level of PD-L1 expression, up to 80 % of patients do not respond to therapy due to the presence of primary or acquired resistance, which determines the limited effectiveness of ICI. In addition, 8–17 % of PD-L1-negative patients with NSCLC are also able to respond to ICIs. The limitation of this marker is that it does not allow assessing both intratumoral and systemic immune status. It is necessary to search for additional predictive markers to improve the accuracy of the selection of candidates for immunotherapy, which will avoid costs, wasted time, and a high risk of immune-related adverse events in potentially unresponsive patients. The attention of researchers is devoted to circulating markers in peripheral blood, as a non-invasive alternative to biopsy for predicting and monitoring the response. This review focuses on the most promising immunological markers in peripheral blood as potential predictors of response to ICIs in patients with advanced NSCLC.

Accurately evaluating minimal residual disease (MRD) could facilitate early intervention and personalized adjuvant therapies. Here, using ultradeep targeted next-generation sequencing (NGS), we evaluate the clinical utility of circulating tumor DNA (ctDNA) for dynamic recurrence risk and adjuvant chemotherapy (ACT) benefit prediction in resected non-small cell lung cancer (NSCLC). Both postsurgical and post-ACT ctDNA positivity are significantly associated with worse recurrence-free survival. In stage II-III patients, the postsurgical ctDNA positive group benefit from ACT, while ctDNA negative patients have a low risk of relapse regardless of whether or not ACT is administered. During disease surveillance, ctDNA positivity precedes radiological recurrence by a median of 88 days. Using joint modeling of longitudinal ctDNA analysis and time-to-recurrence, we accurately predict patients’ postsurgical 12-month and 15-month recurrence status. Our findings reveal longitudinal ctDNA analysis as a promising tool to detect MRD in NSCLC, and we show pioneering work of using postsurgical ctDNA status to guide ACT and applying joint modeling to dynamically predict recurrence risk, although the results need to be further confirmed in future studies., ctDNA has been shown to identify minimal residual disease (MRD) and is thus dynamically monitored in different types of tumours. Here, the authors show that serial longitudinal ctDNA analysis can be used as a tool to detect MRD, inform the use of adjuvant therapy, and predict recurrence risk in lung cancer.

We assessed the diagnostic accuracy of the age-adjusted quick Sequential Organ Failure Assessment score (qSOFA) for predicting mortality and disease severity in pediatric patients with suspected or confirmed infection. We conducted a systematic search of PubMed, EMBASE, the Cochrane Library, and Web of Science. Eleven studies with a total of 172,569 patients were included in the meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio of the age-adjusted qSOFA for predicting mortality and disease severity were 0.69 (95% confidence interval [CI] 0.53–0.81), 0.71 (95% CI 0.36–0.91), and 6.57 (95% CI 4.46–9.67), respectively. The area under the summary receiver-operating characteristic curve was 0.733. The pooled sensitivity and specificity for predicting mortality were 0.73 (95% CI 0.66–0.79) and 0.63 (95% CI 0.21–0.92), respectively. The pooled sensitivity and specificity for predicting disease severity were 0.73 (95% CI 0.21–0.97) and 0.72 (95% CI 0.11–0.98), respectively. The performance of the age-adjusted qSOFA for predicting mortality and disease severity was better in emergency department patients than in intensive care unit patients. The age-adjusted qSOFA has moderate predictive power and can help in rapidly identifying at-risk children, but its utility may be limited by its insufficient sensitivity.

It has been extensively debated whether selective serotonin reuptake inhibitors (SSRIs) are more efficacious than placebo in affective disorders, and it is not fully understood how SSRIs exert their beneficial effects. Along with serotonin transporter blockade, altered dopamine signaling and psychological factors may contribute. In this randomized clinical trial of participants with social anxiety disorder (SAD) we investigated how manipulation of verbally-induced expectancies, vital for placebo response, affect brain monoamine transporters and symptom improvement during SSRI treatment. Twenty-seven participants with SAD (17 men, 10 women), were randomized, to 9 weeks of overt or covert treatment with escitalopram 20 mg. The overt group received correct treatment information whereas the covert group was treated deceptively with escitalopram, described as an active placebo in a cover story. Before and after treatment, patients underwent positron emission tomography (PET) assessments with the [C-11]DASB and [C-11]PE2I radiotracers, probing brain serotonin (SERT) and dopamine (DAT) transporters. SAD symptoms were measured by the Liebowitz Social Anxiety Scale. Overt was superior to covert SSRI treatment, resulting in almost a fourfold higher rate of responders. PET results showed that SERT occupancy after treatment was unrelated to anxiety reduction and equally high in both groups. In contrast, DAT binding decreased in the right putamen, pallidum, and the left thalamus with overt SSRI treatment, and increased with covert treatment, resulting in significant group differences. DAT binding potential changes in these regions correlated negatively with symptom improvement. Findings support that the anxiolytic effects of SSRIs involve psychological factors contingent on dopaminergic neurotransmission while serotonin transporter blockade alone is insufficient for clinical response. Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission; Riksbankens Jubileumsfond-the Swedish Foundation for Humanities and Social Sciences; Kjell and Marta Beijer Foundation

To evaluate whether mammographic texture features were associated with second primary contralateral breast cancer (CBC) risk, we created a “texture risk score” using pre-treatment mammograms in a case–control study of 212 women with CBC and 223 controls with unilateral breast cancer. The texture risk score was associated with CBC (odds per adjusted standard deviation = 1.25, 95% CI 1.01–1.56) after adjustment for mammographic percent density and confounders. These results support the potential of texture features for CBC risk assessment of breast cancer survivors.

Increasing evidences supported that subjective cognitive decline (SCD) might be a potential first symptomatic manifestation of Alzheimer’s disease (AD). The rapidly growing number of SCD individuals who seek medical help and advice also makes it urgent to develop more precise strategy for SCD. Therefore, this study aimed to explore the risk factors for SCD. Logistics and linear regression models were performed to investigate 41 factors for SCD in 1165 participants without objective cognitive impairment. Cochran-Armitage trend test was used to confirm the constant trend toward higher prevalence of SCD with an increasing number of risk factors. A high overall prevalence of SCD was found in total participants (42%). Eight factors were eventually identified as risk factors for SCD, including four stable factors associated with both SCD statues and severity (older age, thyroid diseases, minimal anxiety symptoms, and day time dysfunction; odds ratio (OR) ranging from 1.74 to 2.29) as well as four suggestive factors associated with either SCD statues or severity (female sex, anemia, lack of physical exercises, and living alone; OR ranging from 1.30 to 2.29). The prevalence of SCD gradually increased with the number of risk factors clustering increased in individuals (p for trend

Background The incidence of hand foot and mouth disease (HFMD) has increased in recent years, making it a very common childhood illness worldwide. The relationship between different enterovirus genotypes and disease severity is not clearly understood. Given that enteroviruses are transmitted through the gastrointestinal tract, we hypothesized that variation in intestinal microorganisms of the host might play a role in the prognosis of HFMD. Methods We carried out a meta-transcriptomic-wide association study of fecal samples obtained from a cohort of children (254 patients, 227 tested positive for enterovirus, including 16 patients co-infectied with 2 kinds of enterovirus) with mild and severe HFMD and healthy controls. Results We found there was no significant difference in the amount of each virus type between the mild and severe cases. Genes of enterovirus 71 (EV71) and coxsackievirus A (CV-A) from the severe and mild cases did not show significant clustering. Clostridium sp. L2-50 and Bacteroides stercoris ATCC 43183 were enriched in the guts of children with severe HFMD and KEGG enrichment was found between mild and severe cases. Conclusions Intestinal microorganisms appear to interact with enterovirus to determine the progression of HFMD. Genes of Bacteroides and Clostridium may be used as predictive markers for a more efficient prognosis and intervention. The enrichment of intestinal bacteria genes with functions may facilitate the development of severe symptoms for HFMD patients.

Traditional clinical approaches diagnose disorders of the nervous system using standardized observational criteria. Although aiming for homogeneity of symptoms, this method often results in highly heterogeneous disorders. A standing question thus is how to automatically stratify a given random cohort of the population, such that treatment can be better tailored to each cluster9s symptoms, and severity of any given group forecasted to provide neuroprotective therapies. In this work we introduce new methods to automatically stratify a random cohort of the population composed of healthy controls of different ages and patients with different disorders of the nervous systems. Using a simple walking task and measuring micro-fluctuations in their biorhythmic motions, we show that gait is compromised in healthy aging and that in young FMR1 premutation carriers, gait forecasts, even by 15 years ahead, symptoms resembling those of elderly with Parkinson9s disease. Our methods combine non-linear causal network connectivity analyses in the temporal and frequency domains with stochastic mapping, defining a new type of internal motor timings amenable to create personalized clinical interventions. We frame our results using the principle of reafference and operationalize them using causal prediction, thus renovating the theory of internal models for the study of neuromotor control.

Peripheral blood mononuclear cells (PBMC) are widely used as a biomarker source in nutrition/obesity studies because they reflect gene expression profiles of internal tissues. In this pilot proof-of-concept study we analysed in humans if, as we previously suggested in rodents, PBMC could be a surrogate tissue to study overweight/obesity impact on lipid metabolism. Pre-selected key lipid metabolism genes based in our previous preclinical studies were analysed in PBMC of normoglycemic normal-weight (NW), and overweight-obese (OW-OB) subjects before and after a 6-month weight-loss plan. PBMC mRNA levels of CPT1A, FASN and SREBP-1c increased in the OW-OB group, according with what described in liver and adipose tissue of humans with obesity. This altered expression pattern was related to increased adiposity and early signs of metabolic impairment. Greater weight loss and/or metabolic improvement as result of the intervention was related to lower CPT1A, FASN and SREBP-1c gene expression in an adjusted linear mixed-effects regression analysis, although no gene expression recovery was observed when considering mean comparisons. Thus, human PBMC reflect lipid metabolism expression profile of energy homeostatic tissues, and early obesity-related alterations in metabolic at-risk subjects. Further studies are needed to understand PBMC usefulness for analysis of metabolic recovery in weigh management programs.

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, This work was supported by the Medical Research Council (G0901310) and the Wellcome Trust (grants 085475/B/08/Z, 085475/Z/08/Z). This study was supported by the NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust and University College London and by the NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust at King’s College London. Further support to EB: Mental Health Research UK’s John Grace QC award, BMA Margaret Temple grants 2016 and 2006, MRC—Korean Health Industry Development Institute Partnering Award (MC_PC_16014), MRC New Investigator Award and a MRC Centenary Award (G0901310), National Institute of Health Research UK post-doctoral fellowship, the Psychiatry Research Trust, the Schizophrenia Research Fund, the Brain and Behaviour Research foundation’s NARSAD Young Investigator Awards 2005, 2008, Wellcome Trust Research Training Fellowship, the NIHR Biomedical Research Centre at UCLH, and the NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust and Institute of Psychiatry King’s College London. Further support to co-authors: The Brain and Behaviour Research foundation’s (NARSAD’s) Young Investigator Award (Grant 22604, awarded to CI). The BMA Margaret Temple grant 2016 to JT. A 2014 European Research Council Marie Curie award to A Díez-Revuelta. HI has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 747429. A Medical Research Council doctoral studentship to JH-S, IA-Z and AB. A Mental Health Research UK studentship to RM. VB is supported by a Wellcome Trust Seed Award in Science (200589/Z/16/Z). FWO Senior Clinical Fellowship to RvW. The infrastructure for the GROUP consortium is funded through the Geestkracht programme of the Dutch Health Research Council (ZON-MW, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly, Janssen Cilag) and universities and mental health care organisations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Centre and the mental health institutions: GGZ Ingeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord Holland Noord. Groningen: University Medical Centre Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia psycho-medical centre The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGZ Eindhoven en De Kempen, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh voor Geestelijke Gezondheid, Mondriaan, Virenze riagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-Jozef Kortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Centre Utrecht and the mental health institutions Altrecht, GGZ Centraal and Delta). The Santander cohort was supported by Instituto de Salud Carlos III (PI020499, PI050427, PI060507), SENY Fundació (CI 2005-0308007), Fundacion Ramón Areces and Fundacion Marqués de Valdecilla (API07/011, API10/13). We thank Valdecilla Biobank for providing the biological PAFIP samples and associated data included in this study and for its help in the technical execution of this work; we also thank IDIVAL Neuroimaging Unit for its help in the acquisition and processing of imaging PAFIP data.

Ketamine has been demonstrated to be a rapid-onset and long-lasting antidepressant, but its underlying molecular mechanisms remain unclear. Recent studies have emerged microRNAs as important modulators for depression treatment. In this study, we report that miR-98-5p is downregulated in the prefrontal cortex and hippocampus of mice subjected to chronic social stress, while overexpressing it by its agonist alleviates depression-like behaviors. More importantly, we demonstrate that miR-98-5p is upregulated by ketamine administration, while inhibition of it by its antagonist blocks the antidepressant effect of ketamine. Our data implicate a novel molecular mechanism underlying the antidepressant effect of ketamine, and that therapeutic strategies targeting miR-98-5p could exert beneficial effects for depression treatment.

Despite increasing knowledge on microRNAs, their role in the pathogenesis of neonatal encephalopathy remains to be elucidated. Herein, we identify let-7b-5p as a significant microRNA in neonates with moderate to severe encephalopathy from dried blood spots using next generation sequencing. Validation studies using Reverse Transcription and quantitative Polymerase Chain Reaction on 45 neonates showed that let-7b-5p expression was increased on day 1 in neonates with moderate to severe encephalopathy with unfavourable outcome when compared to those with mild encephalopathy. Mechanistic studies performed on glucose deprived cell cultures and the cerebral cortex of two animal models of perinatal brain injury, namely hypoxic-ischaemic and intrauterine inflammation models confirm that let-7b-5p is associated with the apoptotic Hippo pathway. Significant reduction in neuronal let-7b-5p expression corresponded with activated Hippo pathway, with increased neuronal/nuclear ratio of Yes Associated Protein (YAP) and increased neuronal cleaved caspase-3 expression in both animal models. Similar results were noted for let-7b-5p and YAP expression in glucose-deprived cell cultures. Reduced nuclear YAP with decreased intracellular let-7b-5p correlated with neuronal apoptosis in conditions of metabolic stress. This finding of the Hippo-YAP association with let-7b needs validation in larger cohorts to further our knowledge on let-7b-5p as a biomarker for neonatal encephalopathy., Using next generation sequencing of dried blood spots and subsequent validation, Ponnusamy et al identify let-7b-5p as an elevated microRNA in neonates with moderate to severe encephalopathy. Using cell culture and murine models of perinatal brain injury they demonstrate that the effects of let-7b-5p are elicited via the Hippo-YAP pathway, which should be validated in large neonate cohorts to expand our understanding of let-7b-5p as a biomarker for neonatal encephalopathy.

Tinnitus, the phantom perception of noise originating from the inner ear, has been reported by 15% of the world’s population, with many patients reporting major deficits to cognition and mood. However, both objective diagnostic tools and targeted therapeutic strategies have yet to be established. To better understand the underlying genes that may preclude tinnitus, we performed a genome-wide association study of the UK Biobank’s 49,960 whole exome sequencing participants to identify any loci strongly associated with tinnitus. We identified 17 suggestive single nucleotide polymorphisms (p WDPCP (p = 3.959e−10) in the female cohort, a mutation which has been previously implicated in typical neuronal functioning through axonal migration and structural reinforcement, as well as in Bardet-Biedl syndrome-15, a ciliopathy. Additionally, in situ hybridization in the embryonic and P56 mouse brain demonstrated that the majority of these genes are expressed within the dorsal cochlear nucleus, the region of the brain theorized to initially induce tinnitus. Further RT-qPCR and RNAScope data also reveals this expression pattern. The results of this study indicate that predisposition to tinnitus may span across multiple genomic loci and be established by weakened neuronal circuitry and maladaptive cytoskeletal modifications within the dorsal cochlear nucleus.

CDK4/6 inhibitors combined with endocrine therapy have demonstrated higher antitumor activity than endocrine therapy alone for the treatment of advanced estrogen receptor-positive breast cancer. Some of these tumors are de novo resistant to CDK4/6 inhibitors and others develop acquired resistance. Here, we show that p16 overexpression is associated with reduced antitumor activity of CDK4/6 inhibitors in patient-derived xenografts (n = 37) and estrogen receptor-positive breast cancer cell lines, as well as reduced response of early and advanced breast cancer patients to CDK4/6 inhibitors (n = 89). We also identified heterozygous RB1 loss as biomarker of acquired resistance and poor clinical outcome. Combination of the CDK4/6 inhibitor ribociclib with the PI3K inhibitor alpelisib showed antitumor activity in estrogen receptor-positive non-basal-like breast cancer patient-derived xenografts, independently of PIK3CA, ESR1 or RB1 mutation, also in drug de-escalation experiments or omitting endocrine therapy. Our results offer insights into predicting primary/acquired resistance to CDK4/6 inhibitors and post-progression therapeutic strategies. This study has been supported by the Susan G. Komen Foundation (CCR15330331) and by the Catalan Agency AGAUR (2017 SGR 540) [to V.S.]. V.S. received funds from the Instituto de Salud Carlos III: grants PI13/01714, CP14/00228, MV15/00041, CPII19/00033 and PI20/00892. M.P. received a Juan de la Cierva Grant from the Ministerio de Economía y Competitividad (FJCI-2015-25412), L.Mo. a grant from FI-AGAUR (2019 FI_B 01199), F.B-M. a grant from the Fundación Científica Asociación Española Contra el Cáncer (AECC_Postdoctoral17-1062) and M.S-G, a Marie Slodowska-Curie Innovative Training Networks PhD fellowship (H2020-MSCA-ITN-2015_675392). This work was supported by Breast Cancer Research Foundation (BCRF-19-08), Instituto de Salud Carlos III Project Reference number AC15/00062 and the EC under the framework of the ERA-NET TRANSCAN-2 initiative co-financed by FEDER, Instituto de Salud Carlos III (CB16/12/00449 and PI19/01181) and Asociación Española Contra el Cáncer (to J.A.). R.B.C. laboratory is supported by Breast Cancer Now (grant numbers: MAN-Q1 and MAN-Q2), NIHR Manchester Biomedical Research Centre (IS-BRC-1215-20007) and EdiREX Horizon 2020 grant No.731105. The xenograft program in the C.C. laboratory is supported by Cancer Research UK and also received funding from an EU H2020 Network of Excellence (EuroCAN). This work has been supported by NIH grants P30 CA008748 and RO1CA190642-01, the CDMRP grant BC171535P1, and the Breast Cancer Research Foundation [to M.S.]. A.P. received funds from Instituto de Salud Carlos III—PI16/00904 and PI19/01846, Breast Cancer Now—2018NOVPCC1294, Breast Cancer Research Foundation-AACR Career Development Awards for Translational Breast Cancer Research 19-20-26-PRAT, Fundació La Marató TV3 201935-30, the European Union’s Horizon 2020 research and innovation program H2020-SC1-BHC-2018-2020. IRB Barcelona is a recipient of a Severo Ochoa Centre of Excellence Award from the Spanish Ministry of Economy and Competitiveness (MINECO; Government of Spain) and is supported by CERCA (Generalitat de Catalunya). C. S. Verma reports grants from MSD International and grants from Ipsen outside the submitted work.

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) have revolutionized bladder cancer management. However, stratification of patients that would benefit most from these modalities remains a major clinical challenge. Here, we combine single nuclei RNA sequencing with spatial transcriptomics and single-cell resolution spatial proteomic analysis of human bladder cancer to identify an epithelial subpopulation with therapeutic response prediction ability. These cells express Cadherin 12 (CDH12, N-Cadherin 2), catenins, and other epithelial markers. CDH12-enriched tumors define patients with poor outcome following surgery with or without NAC. In contrast, CDH12-enriched tumors exhibit superior response to ICT. In all settings, patient stratification by tumor CDH12 enrichment offers better prediction of outcome than currently established bladder cancer subtypes. Molecularly, the CDH12 population resembles an undifferentiated state with inherently aggressive biology including chemoresistance, likely mediated through progenitor-like gene expression and fibroblast activation. CDH12-enriched cells express PD-L1 and PD-L2 and co-localize with exhausted T-cells, possibly mediated through CD49a (ITGA1), providing one explanation for ICT efficacy in these tumors. Altogether, this study describes a cancer cell population with an intriguing diametric response to major bladder cancer therapeutics. Importantly, it also provides a compelling framework for designing biomarker-guided clinical trials., The identification of response biomarkers for surgery, chemotherapy and immune checkpoint therapy in bladder cancer is crucial. Here, single nuclei RNA sequencing and spatial profiling identify a cancer cell population expressing Neural Type Cadherin 2 that associates with distinct treatment outcomes.

Inflammation plays a crucial role in stroke pathogenesis. Thus, it is not surprising that cytokines, chemokines, and growth factors have been advocated in stroke diagnostics. Our study is the first to evaluate the salivary cytokine profile in patients with ischemic stroke. Twenty-five patients with subacute ischemic stroke and an age-, sex-, and oral hygiene status-matched control group were enrolled in the study. The number of patients was set a priori based on our previous experiment (α = 0.05, test power = 0.9). Salivary concentrations of tumor necrosis factor α (TNF-α), interleukin 6 (IL-6), and interleukin 10 (IL-10) were assessed using an ELISA method. We showed that salivary TNF-α and IL-6 were significantly higher, whereas IL-10 content was statistically lower in both non-stimulated (NWS) and stimulated (SWS) whole saliva of ischemic stroke patients. However, evaluation of cytokines in NWS rather than in SWS may be of greater diagnostic value. Of particular note is salivary TNF-α, which may indicate cognitive/physical impairment in post-stroke individuals. This parameter distinguishes stroke patients from healthy controls and correlates with cognitive decline and severity of functional impairment. It also differentiates (with high sensitivity and specificity) stroke patients with normal cognition from mild to moderate cognitive impairment. Saliva may be an alternative to blood for assessing cytokines in stroke patients, although further studies on a larger patient population are needed.

Funder: Department of Health, Biologic therapies have transformed the management of psoriasis, but clinical outcome is variable leaving an unmet clinical need for predictive biomarkers of response. Here we perform in-depth immunomonitoring of blood immune cells of 67 patients with psoriasis, before and during therapy with the anti-TNF drug adalimumab, to identify immune mediators of clinical response and evaluate their predictive value. Enhanced NF-κBp65 phosphorylation, induced by TNF and LPS in type-2 dendritic cells (DC) before therapy, significantly correlates with lack of clinical response after 12 weeks of treatment. The heightened NF-κB activation is linked to increased DC maturation in vitro and frequency of IL-17+ T cells in the blood of non-responders before therapy. Moreover, lesional skin of non-responders contains higher numbers of dermal DC expressing the maturation marker CD83 and producing IL-23, and increased numbers of IL-17+ T cells. Finally, we identify and clinically validate LPS-induced NF-κBp65 phosphorylation before therapy as a predictive biomarker of non-response to adalimumab, with 100% sensitivity and 90.1% specificity in an independent cohort. Our study uncovers important molecular and cellular mediators underpinning adalimumab mechanisms of action in psoriasis and we propose a blood biomarker for predicting clinical outcome.

Plasma neurofilament light (NfL) is a marker for neurodegenerative diseases. Few studies have examined the association of NfL with middle-aged changes in cognitive performance, and no studies have examined differential NfL effects by race. Using data from the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study (n = 625, Agev1: 30–66 y, 41.6% male, 56.3% African American, 27.8% below poverty), we investigated the associations of initial NfL levels and annualized change with cognitive performance over time in global mental status, verbal and visual memory, fluency, attention, and executive function. We used ordinary least squares and mixed-effects regressions stratified by race, while exploring differential associations by age group, sex, and poverty status. Over a mean follow-up of 4.3 years, we found initial NfL level was associated with a faster decline on normalized mental status scores in Whites only and in those >50 years old. Annualized increase in NfL was associated with a greater decline in verbal fluency in men. In other exploratory analyses, annualized increase in NfL was associated with a slower decline in verbal memory among individuals living above poverty; in the older group (>50 years), first-visit NfL was linked with better performance at baseline in global mental status and verbal memory. In summary, first-visit NfL was primarily associated with the global mental status decline among Whites, while exhibiting inconsistent relationships in some exploratory analyses. Plasma NfL levels can be detected and quantified in non-demented middle-aged adults and changes can be analyzed over time. More longitudinal studies are needed to address the clinical utility of this biomarker for early cognitive defects.

Epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma are a frequent class of driver mutations. Single EGFR tyrosine kinase inhibitor (TKI) provides substantial clinical benefit, but almost nil radiographic complete responses. Patients invariably progress, although survival can reach several years with post-treatment therapies, including EGFR TKIs, chemotherapy or other procedures. Endeavours have been clinically oriented to manage the acquisition of EGFR TKI-resistant mutations; however, basic principles on cancer evolution have not been considered in clinical trials. For years, evidence has displayed rapidly adaptive mechanisms of resistance to selective monotherapy, posing several dilemmas for the practitioner. Strict adherence to non-small cell lung cancer (NSCLC) guidelines is not always practical for addressing the clinical progression that EGFR-mutant lung adenocarcinoma patients suffer. The purpose of this review is to highlight regulatory mechanisms and signalling pathways that cause therapy-induced resistance to EGFR TKIs. It suggests combinatorial therapies that target EGFR, as well as potential mechanisms underlying EGFR-mutant NSCLC, alerting the reader to clinical opportunities that may lead to a deeper and more durable response. Molecular reprogramming contributes to EGFR TKI resistance, and the compiled information is relevant in understanding the development of new combined targeted strategies in EGFR-mutant NSCLC.

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.

We aimed to identify serum metabolites related to abnormal glucose metabolism (AGM) among women with gestational diabetes mellitus (GDM). The study recruited 50 women diagnosed with GDM during mid-late pregnancy and 50 non-GDM matchees in a Singapore birth cohort. At the 5-year post-partum follow-up, we applied an untargeted approach to investigate the profiles of serum metabolites among all participants. We first employed OPLS-DA and logistic regression to discriminate women with and without follow-up AGM, and then applied area under the curve (AUC) to assess the incremental indicative value of metabolic signatures on AGM. We identified 23 candidate metabolites that were associated with postpartum AGM among all participants. We then narrowed down to five metabolites [p-cresol sulfate, linoleic acid, glycocholic acid, lysoPC(16:1) and lysoPC(20:3)] specifically associating with both GDM and postpartum AGM. The combined metabolites in addition to traditional risks showed a higher indicative value in AUC (0.92–0.94 vs. 0.74 of traditional risks and 0.77 of baseline diagnostic biomarkers) and R2 (0.67–0.70 vs. 0.25 of traditional risks and 0.32 of baseline diagnostic biomarkers) in terms of AGM indication, compared with the traditional risks model and traditional risks and diagnostic biomarkers combined model. These metabolic signatures significantly increased the AUC value of AGM indication in addition to traditional risks, and might shed light on the pathophysiology underlying the transition from GDM to AGM.

Crises such as the COVID-19 pandemic are known to exacerbate depression and anxiety, though their temporal trajectories remain under-investigated. The present study aims to investigate fluctuations in depression and anxiety using the COVID-19 pandemic as a model crisis. A total of 1512 adults living in the United States enrolled in this online study beginning April 2, 2020 and were assessed weekly for 10 weeks (until June 4, 2020). We measured depression and anxiety using the Zung Self-Rating Depression scale and State-Trait Anxiety Inventory (state subscale), respectively, along with demographic and COVID-related surveys. Linear mixed-effects models were used to examine factors contributing to longitudinal changes in depression and anxiety. We found that depression and anxiety levels were high in early April, but declined over time. Being female, younger age, lower-income, and previous psychiatric diagnosis correlated with higher overall levels of anxiety and depression; being married additionally correlated with lower overall levels of depression, but not anxiety. Importantly, worsening of COVID-related economic impact and increase in projected pandemic duration exacerbated both depression and anxiety over time. Finally, increasing levels of informedness correlated with decreasing levels of depression, while increased COVID-19 severity (i.e., 7-day change in cases) and social media use were positively associated with anxiety over time. These findings not only provide evidence for overall emotional adaptation during the initial weeks of the pandemic, but also provide insight into overlapping, yet distinct, factors contributing to depression and anxiety throughout the first wave of the pandemic.

Naltrexone can aid in reducing alcohol consumption, while acamprosate supports abstinence; however, not all patients with alcohol use disorder (AUD) benefit from these treatments. Here we present the first genome-wide association study of AUD treatment outcomes based on data from the COMBINE and PREDICT studies of acamprosate and naltrexone, and the Mayo Clinic CITA study of acamprosate. Primary analyses focused on treatment outcomes regardless of pharmacological intervention and were followed by drug-stratified analyses to identify treatment-specific pharmacogenomic predictors of acamprosate and naltrexone response. Treatment outcomes were defined as: (1) time until relapse to any drinking (TR) and (2) time until relapse to heavy drinking (THR; ≥ 5 drinks for men, ≥4 drinks for women in a day), during the first 3 months of treatment. Analyses were performed within each dataset, followed by meta-analysis across the studies (N = 1083 European ancestry participants). Single nucleotide polymorphisms (SNPs) in the BRE gene were associated with THR (min p = 1.6E−8) in the entire sample, while two intergenic SNPs were associated with medication-specific outcomes (naltrexone THR: rs12749274, p = 3.9E−8; acamprosate TR: rs77583603, p = 3.1E−9). The top association signal for TR (p = 7.7E−8) and second strongest signal in the THR (p = 6.1E−8) analysis of naltrexone-treated patients maps to PTPRD, a gene previously implicated in addiction phenotypes in human and animal studies. Leave-one-out polygenic risk score analyses showed significant associations with TR (p = 3.7E−4) and THR (p = 2.6E−4). This study provides the first evidence of a polygenic effect on AUD treatment response, and identifies genetic variants associated with potentially medication-specific effects on AUD treatment response.

Conventional chemotherapy is still of great utility in oncology and rationally constructing combinations with it remains a top priority. Drug-induced mitochondrial apoptotic priming, measured by dynamic BH3 profiling (DBP), has been shown in multiple cancers to identify drugs that promote apoptosis in vivo. We therefore hypothesized that we could use DBP to identify drugs that would render cancers more sensitive to conventional chemotherapy. We found that targeted agents that increased priming of non-small cell lung cancer (NSCLC) tumor cells resulted in increased sensitivity to chemotherapy in vitro. To assess whether targeted agents that increase priming might enhance the efficacy of cytotoxic agents in vivo as well, we carried out an efficacy study in a PC9 xenograft mouse model. The BH3 mimetic navitoclax, which antagonizes BCL-xL, BCL-w, and BCL-2, consistently primed NSCLC tumors in vitro and in vivo. The BH3 mimetic venetoclax, which electively antagonizes BCL-2, did not. Combining navitoclax with etoposide significantly reduced tumor burden compared to either single agent, while adding venetoclax to etoposide had no effect on tumor burden. Next, we assessed priming of primary patient NSCLC tumor cells on drugs from a clinically relevant oncology combination screen (CROCS). Results confirmed for the first time the utility of BCL-xL inhibition by navitoclax in priming primary NSCLC tumor cells and identified combinations that primed further. This is a demonstration of the principle that DBP can be used as a functional precision medicine tool to rationally construct combination drug regimens that include BH3 mimetics in solid tumors like NSCLC.

Slowed processing speed is considered a hallmark feature of cognitive decline in cerebral small vessel disease (SVD); however, it is unclear whether SVD’s association with slowed processing might be due to its association with overall declining general cognitive ability. We quantified the total MRI-visible SVD burden of 540 members of the Lothian Birth Cohort 1936 (age: 72.6 ± 0.7 years; 47% female). Using latent growth curve modelling, we tested associations between total SVD burden at mean age 73 and changes in general cognitive ability, processing speed, verbal memory and visuospatial ability, measured at age 73, 76, 79 and 82. Covariates included age, sex, vascular risk and childhood cognitive ability. In the fully adjusted models, greater SVD burden was associated with greater declines in general cognitive ability (standardised β: −0.201; 95% CI: [−0.36, −0.04]; pFDR = 0.022) and processing speed (−0.222; [−0.40, −0.04]; pFDR = 0.022). SVD burden accounted for between 4 and 5% of variance in declines of general cognitive ability and processing speed. After accounting for the covariance between tests of processing speed and general cognitive ability, only SVD’s association with greater decline in general cognitive ability remained significant, prior to FDR correction (−0.222; [−0.39, −0.06]; p = 0.008; pFDR = 0.085). Our findings do not support the notion that SVD has a specific association with declining processing speed, independent of decline in general cognitive ability (which captures the variance shared across domains of cognitive ability). The association between SVD burden and declining general cognitive ability supports the notion of SVD as a diffuse, whole-brain disease and suggests that trials monitoring SVD-related cognitive changes should consider domain-specific changes in the context of overall, general cognitive decline.

The efficacy of quantitative ultrasound (QUS) multi-parametric imaging in conjunction with unsupervised classification algorithms was investigated for the first time in characterizing intra-tumor regions to predict breast tumor response to chemotherapy before the start of treatment. QUS multi-parametric images of breast tumors were generated using the ultrasound radiofrequency data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for neo-adjuvant chemotherapy followed by surgery. A hidden Markov random field (HMRF) expectation maximization (EM) algorithm was applied to identify distinct intra-tumor regions on QUS multi-parametric images. Several features were extracted from the segmented intra-tumor regions and tumor margin on different parametric images. A multi-step feature selection procedure was applied to construct a QUS biomarker consisting of four features for response prediction. Evaluation results on an independent test set indicated that the developed biomarker coupled with a decision tree model with adaptive boosting (AdaBoost) as the classifier could predict the treatment response of patient at pre-treatment with an accuracy of 85.4% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.89. In comparison, the biomarkers consisted of the features derived from the entire tumor core (without consideration of the intra-tumor regions), and the entire tumor core and the tumor margin could predict the treatment response of patients with an accuracy of 74.5% and 76.4%, and an AUC of 0.79 and 0.76, respectively. Standard clinical features could predict the therapy response with an accuracy of 69.1% and an AUC of 0.6. Long-term survival analyses indicated that the patients predicted by the developed model as responders had a significantly better survival compared to the non-responders. Similar findings were observed for the two response cohorts identified at post-treatment based on standard clinical and pathological criteria. The results obtained in this study demonstrated the potential of QUS multi-parametric imaging integrated with unsupervised learning methods in identifying distinct intra-tumor regions in breast cancer to characterize its responsiveness to chemotherapy prior to the start of treatment.

Pharmacogenetics/pharmacogenomics have enabled the detection of risk of human leukocyte antigen (HLA) variants for clozapine-induced agranulocytosis/granulocytopenia (CIAG). To apply this evidence to the clinical setting, we compared the cost-effectiveness of the proposed “HLA-guided treatment schedule” and the “current schedule” being used in Japan and the United Kingdom (UK) (absolute neutrophil count (ANC) cutoff at 1500/mm3); in the “HLA-guided treatment schedules,” we considered a situation wherein the HLA test performed before clozapine initiation could provide “a priori information” by detecting patients harboring risk of HLA variants (HLA-B*59:01 and “HLA-B 158T/HLA-DQB1 126Q” for Japanese and Caucasian populations, respectively), a part of whom can then avoid CIAG onset (assumed 30% “prevention rate”). For the primary analysis, we estimated the incremental cost-effectiveness ratio (ICER) of “HLA-guided treatment schedule” and “current schedule” used in Japan and the UK, using a Markov model to calculate the cost and quality-adjusted life years (QALYs) over a 10-year time period. Furthermore, as an explorative analysis, we simulated several situations with various ANC cutoffs (1000/mm3 and 500/mm3) and plotted the cost/QALYs for each option to identify the best, or estimate the next best candidate option applicable in actual clinical settings. The primary probabilistic analysis showed that the “HLA-guided treatment schedule” was more cost effective than the “current schedule”; the ICER was £20,995 and £21,373 for the Japanese and the UK populations, respectively. Additional simulation revealed that the treatment option of ANC cutoff at 500/mm3 without HLA screening was the most cost-effective option; however, several options may be candidates to break away from the “current schedule” of ANC cutoff at 1500/mm3. Owing to its cost-effectiveness, we propose such pharmacogenetic-guided/pharmacogenomic-guided clozapine treatment for use in the real-world setting, which provides key information for optimization of clinical guidelines for high-risk patients for gradual change of clozapine treatment schedule under the safety consideration.

Posttraumatic stress (PTS), depressive symptoms (DS), and musculoskeletal pain (MSP) are common sequelae of trauma exposure. Although these adverse posttraumatic neuropsychiatric sequelae (APNS) are often studied separately, clinical comorbidity is high. In a cohort of European American motor vehicle collision (MVC) trauma survivors (n = 781), substantial PTS (≥33, IES-R), DS (≥26, CES-D), and MSP (≥4, 0–10 NRS) were identified via a 6-month survey. Genetic risk was estimated using polygenic risk scores (PRSs) calculated from the largest available GWAS datasets of PTSD, MDD, and back pain. We then assessed comorbidity and genetic risk influence for developing chronic PTS, DS, and MSP after MVC. Secondary analyses explored whether common social determinants of health ameliorate genetic vulnerability. We found that 6 months after MVC, nearly half 357/781 (46%) of the participants had substantial PTS, DS, and/or MSP, and overlap was common (PTS + MSP (23%), DS + MSP (18%), PTS + DS (12%)). Genetic risk predicted post-MVC outcomes. PTSD-PRSs predicted PTS and DS (R2 = 2.21% and 2.77%, padj R2 = 1.89%, padj padj R2 = 1.49%, padj p = 0.048) and 52% (p = 0.04) less risk of developing PTS, and those with high social support had 60% (p = 0.008) less risk of developing DS. Overall, genetic factors influence the risk of APNS after MVC, genetic risk of distinct APNS are overlapping, and specific social determinants greatly augment genetic risk of APNS development after MVC.

Purpose. - To define the factors which may be related to brain metastasis (BM) in patients with locally advanced non-small cell lung cancer (LA-NSCLC) who developed brain metastases after definitive treatment. Patients and methods. - A total of 208 patients with LA-NSCLC, without BM who received definitive radiotherapy (RT) or RT + chemotherapy (CT) between January 2005 and January 2016 were evaluated retrospectively. Platelet, neutrophil, lymphocyte counts, LDH, CRP, Hb levels, neutrophil-to-lymphocyte radio (NLR), platelet-to-lymphocyte radio (PLR), advanced lung cancer inflammation index (ALI) and FDG-PET/CT parameters (SUVmax of the primary tumor and mediastinal lymph nodes), and patient characteristics were evaluated for brain metastasis free survival (BMFS). Results. - Median follow-up duration was 25 months (range: 3-130 months). Cut-off values for platelet, NLR, PLR, LDH, CRP, and Hb were 290 x 103/mu L, 2.6, 198, 468 IU/L, 2.5 mg/dL, and 11.5 g/d1. We defined each parameter as low or high according to the cut-off values. 56 patients (26.9%) developed brain metastases during follow-up. In univariate analysis, high NLR (P=0.001), PLR (P=0.037), LDH (P = 0.028), CRP (P = 0.002) values, value >= 7.5 for lymph nodes (P = 0.005) and low ALI value (P = 0.002) were poor prognostic factors for BMFS. In multivariate analysis, high NLR (P= 0.022), PLR (P= 0.017), CRP (P= 0.006), stage >= IIIB disease (P< 0.001), multi-stational N2 disease (P= 0.036), adenocarcinoma histology (P< 0.001) and SUVmax value >= 7.5 (P = 0.035) were poor prognostic factors for BMFS. Conclusions. - High NLR, PLR, LDH, CRP values, SUVmax values for lymph nodes, and low ALI which indicates high tumor burden were additional prognostic factors besides stage, histology, and lymph node status. (C) 2020 Societe francaise de radiotherapie oncologique (SFRO). Published by Elsevier Masson SAS. All rights reserved.

While several resources exist that interpret therapeutic significance of genomic alterations in cancer, many regional real-world issues limit access to drugs. There is a need for a pragmatic, evidence-based, context-adapted tool to guide clinical management based on molecular biomarkers. To this end, we have structured a compendium of approved and experimental therapies with associated biomarkers following a survey of drug regulatory databases, existing knowledge bases, and published literature. Each biomarker-disease-therapy triplet was categorised using a tiering system reflective of key therapeutic considerations: approved and reimbursed therapies with respect to a jurisdiction (Tier 1), evidence of efficacy or approval in another jurisdiction (Tier 2), evidence of antitumour activity (Tier 3), and plausible biological rationale (Tier 4). Two resistance categories were defined: lack of efficacy (Tier R1) or antitumor activity (Tier R2). Based on this framework, we curated a digital resource focused on drugs relevant in the Australian healthcare system (TOPOGRAPH: Therapy Oriented Precision Oncology Guidelines for Recommending Anticancer Pharmaceuticals). As of November 2020, TOPOGRAPH comprised 2810 biomarker-disease-therapy triplets in 989 expert-appraised entries, including 373 therapies, 199 biomarkers, and 106 cancer types. In the 345 therapies catalogued, 84 (24%) and 65 (19%) were designated Tiers 1 and 2, respectively, while 271 (79%) therapies were supported by preclinical studies, early clinical trials, retrospective studies, or case series (Tiers 3 and 4). A companion algorithm was also developed to support rational, context-appropriate treatment selection informed by molecular biomarkers. This framework can be readily adapted to build similar resources in other jurisdictions to support therapeutic decision-making.

Predicting all-cause mortality risk is challenging and requires extensive medical data. Recently, large-scale proteomics datasets have proven useful for predicting health-related outcomes. Here, we use measurements of levels of 4,684 plasma proteins in 22,913 Icelanders to develop all-cause mortality predictors both for short- and long-term risk. The participants were 18-101 years old with a mean follow up of 13.7 (sd. 4.7) years. During the study period, 7,061 participants died. Our proposed predictor outperformed, in survival prediction, a predictor based on conventional mortality risk factors. We could identify the 5% at highest risk in a group of 60-80 years old, where 88% died within ten years and 5% at the lowest risk where only 1% died. Furthermore, the predicted risk of death correlates with measures of frailty in an independent dataset. Our results show that the plasma proteome can be used to assess general health and estimate the risk of death., Eiriksdottir et al. use a temporal proteomic dataset from over 22,000 Icelandic individuals to identify predictors and predict all-cause mortality. Their findings suggest that the plasma proteome may be of value in general health screening for risk of death.

The amniotic fluid (AF) cell-free RNA was shown to reflect physiological and pathological processes in pregnancy, but its value in the prediction of spontaneous preterm delivery is unknown. Herein we profiled cell-free RNA in AF samples collected from women who underwent transabdominal amniocentesis after an episode of spontaneous preterm labor and subsequently delivered within 24 h (n = 10) or later (n = 28) in gestation. Expression of known placental single-cell RNA-Seq signatures was quantified in AF cell-free RNA and compared between the groups. Random forest models were applied to predict time-to-delivery after amniocentesis. There were 2385 genes differentially expressed in AF samples of women who delivered within 24 h of amniocentesis compared to gestational age-matched samples from women who delivered after 24 h of amniocentesis. Genes with cell-free RNA changes were associated with immune and inflammatory processes related to the onset of labor, and the expression of placental single-cell RNA-Seq signatures of immune cells was increased with imminent delivery. AF transcriptomic prediction models captured these effects and predicted delivery within 24 h of amniocentesis (AUROC = 0.81). These results may inform the development of biomarkers for spontaneous preterm birth.

Background Prognostic stratification of breast cancers remains a challenge to improve clinical decision making. We employ machine learning on breast cancer transcriptomics from multiple studies to link the expression of specific genes to histological grade and classify tumours into a more or less aggressive prognostic type. Materials and methods Microarray data of 5031 untreated breast tumours spanning 33 published datasets and corresponding clinical data were integrated. A machine learning model based on gradient boosted trees was trained on histological grade-1 and grade-3 samples. The resulting predictive model (Cancer Grade Model, CGM) was applied on samples of grade-2 and unknown-grade (3029) for prognostic risk classification. Results A 70-gene signature for assessing clinical risk was identified and was shown to be 90% accurate when tested on known histological-grade samples. The predictive framework was validated through survival analysis and showed robust prognostic performance. CGM was cross-referenced with existing genomic tests and demonstrated the competitive predictive power of tumour risk. Conclusions CGM is able to classify tumours into better-defined prognostic categories without employing information on tumour size, stage, or subgroups. The model offers means to improve prognosis and support the clinical decision and precision treatments, thereby potentially contributing to preventing underdiagnosis of high-risk tumours and minimising over-treatment of low-risk disease.

Depression is a multifaceted illness with large interindividual variability in clinical response to treatment. In the era of digital medicine and precision therapeutics, new personalized treatment approaches are warranted for depression. Here, we use a combination of longitudinal ecological momentary assessments of depression, neurocognitive sampling synchronized with electroencephalography, and lifestyle data from wearables to generate individualized predictions of depressed mood over a 1-month time period. This study, thus, develops a systematic pipeline for N-of-1 personalized modeling of depression using multiple modalities of data. In the models, we integrate seven types of supervised machine learning (ML) approaches for each individual, including ensemble learning and regression-based methods. All models were verified using fourfold nested cross-validation. The best-fit as benchmarked by the lowest mean absolute percentage error, was obtained by a different type of ML model for each individual, demonstrating that there is no one-size-fits-all strategy. The voting regressor, which is a composite strategy across ML models, was best performing on-average across subjects. However, the individually selected best-fit models still showed significantly less error than the voting regressor performance across subjects. For each individual’s best-fit personalized model, we further extracted top-feature predictors using Shapley statistics. Shapley values revealed distinct feature determinants of depression over time for each person ranging from co-morbid anxiety, to physical exercise, diet, momentary stress and breathing performance, sleep times, and neurocognition. In future, these personalized features can serve as targets for a personalized ML-guided, multimodal treatment strategy for depression.

Here, we present a next-generation sequencing (NGS) methylation-based blood test called methylation DETEction of Circulating Tumour DNA (mDETECT) designed for the optimal detection and monitoring of metastatic triple-negative breast cancer (TNBC). Based on a highly multiplexed targeted sequencing approach, this assay incorporates features that offer superior performance and included 53 amplicons from 47 regions. Analysis of a previously characterised cohort of women with metastatic TNBC with limited quantities of plasma (TNBC was quantitative and showed superior performance to an NGS TP53 mutation-based test carried out on the same patients and to the conventional CA15-3 biomarker. mDETECT also functioned well in serum samples from metastatic TNBC patients where it produced an AUC of 0.97 for detection of a tumour with a sensitivity of 93% for a specificity of 100%. An assay for BRCA1 promoter methylation was also incorporated into the mDETECT assay and functioned well but its clinical significance is currently unclear. Clonal Hematopoiesis of Indeterminate Potential was investigated as a source of background in control subjects but was not seen to be significant, though a link to adiposity may be relevant. The mDETECTTNBC assay is a liquid biopsy able to quantitatively detect all TNBC cancers and has the potential to improve the management of patients with this disease.

Alzheimer’s disease (AD) is the leading cause of dementia, and many studies have focused on finding effective blood biomarkers for the accurate diagnosis of this disease. Predicting cerebral amyloid deposition is considered the key for AD diagnosis because a cerebral amyloid deposition is the hallmark of AD pathogenesis. Previously, blood biomarkers were discovered to predict cerebral amyloid deposition, and further efforts have been made to increase their sensitivity and specificity. In this study, we analyzed blood-test factors (BTFs) that can be commonly measured in medical health check-ups from 149 participants with cognitively normal, 87 patients with mild cognitive impairment, and 64 patients with clinically diagnosed AD dementia with brain amyloid imaging data available. We demonstrated that four factors among regular health check-up blood tests, cortisol, triglyceride/high-density lipoprotein cholesterol ratio, alanine aminotransferase, and free triiodothyronine, showed either a significant difference by or correlation with cerebral amyloid deposition. Furthermore, we made a prediction model for Pittsburgh compound B-positron emission tomography positivity, using BTFs and the previously discovered blood biomarkers, the QPLEXTM Alz plus assay kit biomarker panel, and the area under the curve was significantly increased up to 0.845% with 69.4% sensitivity and 90.6% specificity. These results show that BTFs could be used as co-biomarkers and that a highly advanced prediction model for amyloid plaque deposition could be achieved by the combinational use of diverse biomarkers., Alzheimer’s disease: routine blood-test results could assist early diagnosis Four blood components measured in routine tests may highlight the cerebral protein build-up indicative of Alzheimer’s disease and could improve diagnosis. Amyloid protein plaque accumulation in the brain is a hallmark of Alzheimer’s, and early detection prior to symptoms appearing is invaluable. PET imaging is currently used for detecting plaque deposition, but scientists are developing simpler detection methods using blood biomarkers such as amyloid peptide levels. Haeng Jun Kim at Seoul National University, South Korea, and co-workers demonstrated that biomarker test accuracy could be boosted by including routine blood-test data. They correlated PET imaging data with blood results from patients with mild cognitive impairment, Alzheimer’s, and healthy controls. They identified components whose levels are associated with amyloid deposition, including a liver enzyme and the hormone cortisol, and developed a proof-of-concept plaque prediction model.

Preclinical models propose that increased hippocampal activity drives subcortical dopaminergic dysfunction and leads to psychosis-like symptoms and behaviors. Here, we used multimodal neuroimaging to examine the relationship between hippocampal regional cerebral blood flow (rCBF) and striatal dopamine synthesis capacity in people at clinical high risk (CHR) for psychosis and investigated its association with subsequent clinical and functional outcomes. Ninety-five participants (67 CHR and 28 healthy controls) underwent arterial spin labeling MRI and 18F-DOPA PET imaging at baseline. CHR participants were followed up for a median of 15 months to determine functional outcomes with the global assessment of function (GAF) scale and clinical outcomes using the comprehensive assessment of at-risk mental states (CAARMS). CHR participants with poor functional outcomes (follow-up GAF n = 25) showed higher rCBF in the right hippocampus compared to CHRs with good functional outcomes (GAF ≥ 65, n = 25) (pfwe = 0.026). The relationship between rCBF in this right hippocampal region and striatal dopamine synthesis capacity was also significantly different between groups (pfwe = 0.035); the association was negative in CHR with poor outcomes (pfwe = 0.012), but non-significant in CHR with good outcomes. Furthermore, the correlation between right hippocampal rCBF and striatal dopamine function predicted a longitudinal increase in the severity of positive psychotic symptoms within the total CHR group (p = 0.041). There were no differences in rCBF, dopamine, or their associations in the total CHR group relative to controls. These findings indicate that altered interactions between the hippocampus and the subcortical dopamine system are implicated in the pathophysiology of adverse outcomes in the CHR state.

Post-traumatic stress disorder (PTSD) is characterized by complex, heterogeneous symptomology, thus detection outside traditional clinical contexts is difficult. Fortunately, advances in mobile technology, passive sensing, and analytics offer promising avenues for research and development. The present study examined the ability to utilize Global Positioning System (GPS) data, derived passively from a smartphone across seven days, to detect PTSD diagnostic status among a cohort (N = 185) of high-risk, previously traumatized women. Using daily time spent away and maximum distance traveled from home as a basis for model feature engineering, the results suggested that diagnostic group status can be predicted out-of-fold with high performance (AUC = 0.816, balanced sensitivity = 0.743, balanced specificity = 0.8, balanced accuracy = 0.771). Results further implicate the potential utility of GPS information as a digital biomarker of the PTSD behavioral repertoire. Future PTSD research will benefit from application of GPS data within larger, more diverse populations.

Various biomarkers have been proposed for sepsis; however, only a few become the standard. We previously reported that plasma histidine-rich glycoprotein (HRG) levels decreased in septic mice, and supplemental infusion of HRG improved survival in mice model of sepsis. Moreover, our previous clinical study demonstrated that HRG levels in septic patients were lower than those in noninfective systemic inflammatory response syndrome patients, and it could be a biomarker for sepsis. In this study, we focused on septic patients and assessed the differences in HRG levels between the non-survivors and survivors. We studied ICU patients newly diagnosed with sepsis. Blood samples were collected within 24 h of ICU admission, and HRG levels were determined using an enzyme-linked immunosorbent assay. Ninety-nine septic patients from 11 institutes in Japan were included. HRG levels were significantly lower in non-survivors (n = 16) than in survivors (n = 83) (median, 15.1 [interquartile ranges, 12.7–16.6] vs. 30.6 [22.1–39.6] µg/ml; p

Gliosis is implicated in the pathophysiology of many neuropsychiatric diseases, including treatment-resistant major depressive disorder (TRD). Translocator protein total distribution volume (TSPO VT), a brain marker mainly reflective of gliosis in disease, can be measured using positron emission tomography (PET). Minocycline reduces gliosis and translocator protein binding in rodents, but this is not established in humans. Here, the ability of oral minocycline to reduce TSPO VT was assessed in TRD. To determine whether oral minocycline, as compared to placebo, can reduce prefrontal cortex (PFC), anterior cingulate cortex (ACC), and insula TSPO VT in TRD, twenty-one TRD participants underwent two [18F]FEPPA PET scans to measure TSPO VT. These were completed before and after either oral minocycline 100 mg bid or placebo which was administered in a randomized double-blinded fashion for 8 weeks. There was no significant difference between the minocycline and placebo groups on change in TSPO VT within the PFC, ACC, and insula (repeated measures ANOVA, effect of group interaction, PFC: F1,19 = 0.28, P = 0.60; ACC: F1,19 = 0.54, P = 0.47; insula F1,19 = 1.6, P = 0.22). Oral minocycline had no significant effect on TSPO VT which suggests that this dosage is insufficient to reduce gliosis in TRD. To target gliosis in TRD either alternative therapeutics or intravenous formulations of minocycline should be investigated. These results also suggest that across neuropsychiatric diseases in humans, it should be assumed that oral minocycline will not reduce TSPO VT or gliosis unless empirically demonstrated.

The role of high-mobility group box-1 (HMGB1) in outcome prediction in sepsis is controversial. Furthermore, its association with necroptosis, a programmed cell necrosis mechanism, is still unclear. The purpose of this study is to identify the association between the plasma levels of HMGB1 and the severity and clinical outcomes of sepsis, and to examine the correlation between HMGB1 and key executors of necroptosis including receptor-interacting kinase 3 (RIPK3) and mixed lineage kinase domain-like- (MLKL) proteins. Plasma HMGB1, RIPK3, and MLKL levels were measured with the enzyme-linked immunosorbent assay from the derivation cohort of 188 prospectively enrolled, critically-ill patients between April 2014 and December 2016, and from the validation cohort of 77 patients with sepsis between January 2017 and January 2019. In the derivation cohort, the plasma HMGB1 levels of the control (n = 46, 24.5%), sepsis (n = 58, 30.9%), and septic shock (n = 84, 44.7%) groups were significantly increased (P P = 0.009). There were positive linear correlations of plasma HMGB1 with RIPK3 (R2 = 0.61, P 2 = 0.7890, P

Deeply involved with dyslipidemia, cardiovascular disease has becoming the leading cause of mortality since the early twentieth century in the modern world. Whose correlation with metabolic syndrome (MetS), hypertension and type 2 diabetes mellitus (T2DM) has been well established. We conducted a 9-year longitudinal study to identify the association between easily measured lipid parameters, future MetS, hypertension and T2DM by gender and age distribution. Divided into three groups by age (young age

The G84E germline mutation of HOXB13 predisposes to prostate cancer and is clinically tested for familial cancer care. We investigated the HOXB locus to define a potentially broader contribution to prostate cancer heritability. We sought HOXB locus germline variants altering prostate cancer risk in three European-ancestry case–control study populations (combined 7812 cases and 5047 controls): the International Consortium for Prostate Cancer Genetics Study; the Nashville Familial Prostate Cancer Study; and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Multiple rare genetic variants had concordant and strong risk effects in these study populations and exceeded genome-wide significance. Independent risk signals were best detected by sentinel variants rs559612720 within SKAP1 (OR = 8.1, P = 2E−9) and rs138213197 (G84E) within HOXB13 (OR = 5.6, P = 2E−11), separated by 567 kb. Half of carriers inherited both risk alleles, while others inherited either alone. Under mutual adjustment, the variants separately carried 3.6- and 3.1-fold risk, respectively, while joint inheritance carried 11.3-fold risk. These risks were further accentuated among men meeting criteria for hereditary prostate cancer, and further still for those with early-onset or aggressive disease. Among hereditary prostate cancer cases diagnosed under age 60 and with aggressive disease, joint inheritance carried a risk of OR = 27.7 relative to controls, P = 2E−8. The HOXB sentinel variant pair more fully captured genetic risk for prostate cancer within the study populations than either variant alone.

Immunotherapy has reshaped the field of cancer therapeutics but the population that benefits are small in many tumor types, warranting a companion diagnostic test. While immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) or mismatch repair (MMR) and polymerase chain reaction (PCR) for microsatellite instability (MSI) are the only approved companion diagnostics others are under consideration. An optimal companion diagnostic test might combine the spatial information of IHC with the quantitative information from RNA expression profiling. Here, we show proof of concept for combination of spatially resolved protein information acquired by the NanoString GeoMx® Digital Spatial Profiler (DSP) with transcriptomic information from bulk mRNA gene expression acquired using NanoString nCounter® PanCancer IO 360™ panel on the same cohort of immunotherapy treated melanoma patients to create predictive models associated with clinical outcomes. We show that the combination of mRNA and spatially defined protein information can predict clinical outcomes more accurately (AUC 0.97) than either of these factors alone.

Sarcomas harboring EWSR1-NFATc2 fusions have historically been categorized and treated as Ewing sarcoma. Emerging evidence suggests unique molecular characteristics and chemotherapy sensitivities in EWSR1-NFATc2 fusion positive sarcomas. Comprehensive genomic profiles of 1024 EWSR1 fusion positive sarcomas, including 14 EWSR1-NFATc2 fusions, were identified in the FoundationCore® database. Additional data from the Gene Expression Omnibus, the Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas datasets were included for analysis. EWSR1-NFATc2 fusion positive sarcomas were genomically distinct from traditional Ewing sarcoma and demonstrated upregulation of the mTOR pathway. We also present a case of a 58-year-old male patient with metastatic EWSR1-NFATc2 fusion positive sarcoma who achieved 47 months of disease stabilization when treated with combination mTOR and VEGF inhibition. EWSR1-NFATc2 fusion positive sarcomas are molecularly distinct entities with overactive mTOR signaling; which may be therapeutically targetable. These findings support the use of precision medicine in the Ewing family of tumors.