Communications medicine最新文献

Background: This study aimed to evaluate the distinct prognostic value of [¹⁸F]FDG and [⁶⁸Ga]Ga-PSMA-11 PET imaging in advanced hormone-sensitive prostate cancer, highlighting their complementary roles at both patient and lesion levels.

Methods: This study retrospectively included 298 patients with newly diagnosed prostate cancer who underwent baseline dual-tracer PET imaging. Quantitative PET parameters for both [¹⁸F]FDG and [⁶⁸Ga]Ga-PSMA-11 were extracted. Clinical outcomes, including progression-free survival, biochemical response, and radiographic response, were collected during follow-up. Lesion-based analysis was performed in 267 measurable lesions to evaluate the association between tracer uptake and local radiographic response, as determined by changes in lesion diameter following systemic therapy.

Results: Here we show that higher whole-body [¹⁸F]FDG uptake, including total lesion glycolysis (HR = 3.525, p < 0.001) and metabolic tumor volume (HR = 2.757, p < 0.001), is significantly associated with shorter progression-free survival. In contrast, only PSMA-derived tumor volume (HR = 2.019, p = 0.018), but not total lesion PSMA uptake (HR = 1.438, p = 0.221), demonstrates prognostic value. Moreover, patients with higher whole-body [¹⁸F]FDG burden receive greater benefit from chemotherapy (HR = 2.936, p = 0.004). At the lesion level, higher [⁶⁸Ga]Ga-PSMA-11 uptake is significantly correlated with more favorable radiographic response (p < 0.001), while lesion-level [¹⁸F]FDG uptake does not demonstrate predictive value.

Conclusions: [¹⁸F]FDG PET and [⁶⁸Ga]Ga-PSMA-11 PET provide distinct but complementary prognostic value in advanced hormone-sensitive prostate cancer. Dual-tracer PET imaging enhances prognostic accuracy and provides comprehensive guidance for individualized treatment strategies.

Background: Cardiorenal-protective sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) lack selection guidance. We aimed to build a SGLT-2i/GLP-1RA Decision Score (TiP DecScore) to tailor selection between them.

Methods: We developed the TiP DecScore in type 2 diabetes (T2D) patients receiving either therapy from the China Metabolic Analytics Project (derivation dataset: n = 24,322; validation dataset: n = 1,459), using gradient boosting decision tree and 15 features. The primary outcomes were glycated haemoglobin (HbA_1c) control (<7%) and HbA_1c levels at 6 and 12 months. The model's clinical effectiveness was evaluated by comparing HbA_1c control between concordant (receiving the predicted optimal therapy) and discordant groups (receiving the predicted non-optimal therapy).

Results: Here we show the derivation cohort has mean (SD) age 53.7 (11.5) years, 63.0% males. Model validation shows good predictive performance (the receiver operating characteristic curve 0.71-0.78). GLP-1RA is favored over SGLT-2i (57.6% vs. 24.2% at 6 months; 57.9% vs. 28.6% at 12 months). At 6 months, compared with SGLT-2i, GLP-1RA is prioritized for patients with a shorter diabetes duration and higher fasting C-peptide, alanine aminotransferase, body mass index (BMI), and low-density lipoprotein cholesterol levels. At 12 months, patients with higher baseline HbA_1c and BMI levels are more likely to be recommended GLP-1RA than SGLT-2i. Higher rates of HbA_1c control are observed in concordant versus discordant groups, especially in younger patients (<55 years; 64.1% vs. 46.2%, P = 0.001) and males (58.6% vs. 45.6%, P = 0.018) at 12 months.

Conclusions: The TiP DecScore effectively guides personalized selection between SGLT-2i and GLP-1RA therapies for T2D patients.

Background: Early detection of hepatocellular carcinoma (HCC) remains a significant clinical challenge due to the limited sensitivity of current surveillance tools, alpha-fetoprotein (AFP) and ultrasound. Recently, cell-free DNA (cfDNA) fragmentation analysis has shown promise in cancer detection; however, current sequencing-based approaches remain costly and unsuitable for large-scale screening.

Methods: Here, we introduce a predictive model for early HCC detection called "CEliver" (CfDNA-based automated capillary Electrophoresis method for Liver cancer screening), a model leveraging high-dimensional fragmentation profiling from the intensity distribution of cfDNA fragment lengths using automated capillary electrophoresis. We developed CF-2D features, a computational framework that extracts over 300 quantitative features from electropherogram data, including cfDNA concentration, dominant fragment sizes, two-dimensional shape descriptors, and short-to-long fragment ratios. We integrated these features with AFP levels to build the CEliver model, developed in 111 individuals and validated in an independent cohort of 69 subjects.

Results: Here we show the CF-2D profiles differ significantly between HCC patients and high-risk individuals. The CEliver model achieves 98% sensitivity across all HCC cases, and 96% sensitivity with 99% specificity for early-stage HCC (stage 0/A), substantially outperforming AFP (60% overall sensitivity, 35% for early-stage). In external validation, CEliver shows 88% sensitivity and 100% specificity.

Conclusions: CEliver provides a practical and accurate strategy for early HCC detection. By enabling high-dimensional cfDNA fragmentomics analysis on a widely accessible electrophoresis platform, it bridges the gap between research-grade cfDNA technologies and real-world clinical implementation. This method represents a simple and scalable approach that could potentially be applied in HCC surveillance.

Background: Homologous recombination deficiency (HRD) originating from inactivation of genes like BRCA1/BRCA2 is a targetable abnormality common in triple-negative breast cancer (TNBC). In estrogen-receptor (ER)-positive HER2-negative (ERpHER2n) breast cancer (BC), HRD prevalence and clinical impact are unclear.

Methods: We analyzed 502 ERpHER2n tumors from patients recruited via the population-representative Swedish SCAN-B study by whole genome sequencing (WGS), defining mutational signatures-based HRD, as well as matched transcriptional, DNA methylation, clinicopathological, adjuvant treatment, and outcome data.

Results: We show that HRD is much less frequent in ERpHER2n BC (8.4%) compared to TNBC, though induced by similar genetic/epigenetic mechanisms acting on mainly BRCA1/BRCA2/RAD51C/PALB2 together, providing a plausible HR-inactivation mechanism for 71.4% of HRD tumors. Our modelled estimate of HRD in Western European/Nordic BC is ~10-13%. HRD tumors were observed across all PAM50 gene expression subtypes with the exception of Luminal A tumors ( < 1%) and did not exhibit a unique, defining transcriptional or DNA methylation profile. While HRD status was not statistically associated with differences in patient outcome for patients treated with combined chemotherapy and endocrine therapy, a nonsignificant trend of poorer outcome for patients with HRD tumors was observed for patients treated with adjuvant endocrine therapy only.

Conclusions: ERpHER2n HRD tumors show features of aggressive disease, but do not display a distinct transcriptional or DNA methylation profile that clearly differentiates them from HR-proficient tumors. Though numbers are limited, we present early evidence that HRD stratification by WGS could impact therapeutic strategies, as HRD BCs trended to poorer outcomes when not treated with chemotherapy.

Background: Spinal Muscular Atrophy (SMA) is a genetic disorder resulting from deficiency of the survival motor neuron (SMN) protein. Emerging evidence indicates that SMA is associated with disruptions in neuroactive amino acid metabolism, contributing to altered neurotransmission. Taurine, the predominant inhibitory neuromodulator in the developing central nervous system (CNS), is critical for synaptic function, osmoregulation, and neuroprotection. Despite its physiological significance, the effects of SMN deficiency on taurine homeostasis and its potential role in SMA pathophysiology remain unexplored.

Methods: We used high-performance liquid chromatography (HPLC) to quantify taurine in the spinal cord, brainstem, cortex, and cerebellum in SMN∆7 mice, during postnatal development. We then translate our observation into the clinic by measuring taurine concentrations in the cerebrospinal fluid (CSF) from control individuals (n = 7) and SMA patients of varying disease severity (n = 37) before and after therapy with the SMN-inducing drug Nusinersen.

Results: Our data show a downregulation of taurine levels in the brainstem of SMN∆7 mice at late symptomatic stage relative to control littermates. Furthermore, we highlight a taurine reduction in the CSF of naïve SMA1 patients compared to controls. Importantly, Nusinersen treatment restored the taurine deficit in these SMA patients.

Conclusions: These findings demonstrate that SMN deficiency dysregulates taurine homeostasis in the CNS of overt symptomatic mouse models and SMA1 patients. They also reveal the therapeutic efficacy of Nusinersen treatment in correcting this amino acid deficit. However, further research is needed to determine the mechanisms by which SMN deficiency causes taurine dysregulation and its potential contribution to SMA pathology.

Background: Accurate detection of tuberculosis (TB) treatment failure and recurrence can improve disease control, but current sputum-based monitoring tools pose significant limitations. This study aimed to identify sputum-independent biomarkers for detecting and predicting TB treatment failure and recurrence.

Methods: Within the Pan-African TB Sequel study, we conducted a matched case-control study with 40 participants who had recurrent TB or treatment failure and 37 successfully treated controls matched by sex, age, and HIV status. Cases were classified as (a) non-converters with persistently positive sputum Mycobacterium tuberculosis (MTB) results during treatment, (b) reverters at the end of treatment (EOT), or (c) recurrence after EOT. Peripheral blood was collected at baseline, months 2, 4, 6, 9, and 12, and at suspected recurrence. MTB-specific T-cell activation markers (CD38, CD27, HLA-DR, Ki67) and transcriptomic signatures (Sweeney3, Risk6, MAMS6) were assessed and compared to the reference standard MTB culture and smear results.

Results: Here, we show that both MTB-specific T-cell activation and transcriptomic signatures detected non-conversion and TB recurrence at month 9 or 12 after treatment initiation. CD38 expression demonstrates 100% sensitive (95% CI: 56.6-100%) and 78% specific (95% CI: 56.5-99.4%) for detecting TB recurrence, with an AUC of 0.98 (95% CI: 91-100%). Among transcriptomic signatures, MAMS6, RISK6, and Sweeney3 achieve 75% sensitivity (95% CI: 50-100%) and 87-93% specificity (95% CI: MAMS6 0-100%, RISK6 0-93%, Sweeney3 0-100%), with comparable AUCs (0.78-0.83). Neither marker detected TB reversion at EOT.

Conclusion: These sputum-independent biomarkers effectively identify TB disease, non-conversion and recurrence TB after EOT, whereas their utility in detecting TB reversion during treatment remains limited.

Background: Severe Covid-19 leads to higher neutralizing antibody levels, a key correlate of protection. However, the host proteins associated with this response have not been fully characterized. We asked which proteins in the blood plasma associate with neutralization, anti-spike antibody levels, and disease severity in a South African cohort upon first SARS-CoV-2 exposure.

Methods: We used a longitudinal observational cohort design to collect blood at 6 days (acute infection) and 32 days (convalescence) post-diagnosis. We performed SomaScan proteomics on acute blood plasma and measured SARS-CoV-2 plasma neutralization capacity and anti-spike antibody levels in convalescent plasma. Disease severity was scored based on requirement for supplemental oxygen and was mild to moderate (no critically ill participants).

Results: We find differentially expressed proteins associating with neutralization, anti-spike antibody levels, and disease severity, with strong overlap between proteins associated with neutralization and spike binding, and moderate overlap between neutralization and disease severity. High neutralizers, regardless of requirement for supplemental oxygen, are found to have risk factors and markers for being more ill compared to low neutralizers. We can reasonably predict who becomes a high neutralizer based on individual proteins. The best predictor for neutralization is HSPA8, known to bind viral proteins and cross-present extracellular antigens. The strongest associated pathway is fatty acid metabolism, whose inhibition results in suppression of viral replication.

Conclusions: These results show that host proteins and pathways involved early in SARS-CoV-2 infection associate with neutralizing antibody levels elicited by the infection at convalescence.

Background: Post-stroke hemiplegia of the upper extremities continues to pose a significant therapeutic hurdle. Contralesional uncrossed corticospinal pathways (CST) are involved in the recovery processes.

Methods: We test the safety, and preliminary efficacy of targeted upregulation of uncrossed CST excitability through self-modulation of cortical activities via noninvasive brain-machine interaction training (Registered with the University Hospital Medical Information Network: UMIN000017525). In this single-arm prospective trial, eight individuals with persistent severe post-stroke motor disability voluntarily actuated their affected shoulder using a brain-computer interface (BCI) bridging the contralesional motor cortex (M1) and an exoskeleton robot. While patients attempted to elevate the affected arm, scalp electroencephalogram (EEG) signals over the contralesional M1 were processed online to provide them with feedback on M1 excitability.

Results: Here we show that the BCI reconstructs neural pathways, allowing arm elevation without any adverse effects. As evidenced by an increase in primary outcome measure (Fugl- Meyer Assessment, p < 0.05, d = 1.24), seven days of consecutive system use results in rapid, sustained, and clinically significant improvement in motor function when removed from the system and promotes contralesional M1 functional remodeling.

Conclusions: This closed-loop system is safe, feasible, and a promising intervention that recruits intact neural resources to allow patients to recover upper-extremity motor abilities.

Background: Preterm birth remains a leading cause of neonatal morbidity and mortality. It is classified as spontaneous, characterized by the unexpected onset of labor, or medically indicated, resulting from obstetric intervention due to pregnancy complications. The mechanisms underlying each subtype are incompletely understood, and obesity further modulates preterm birth risk through unclear biological pathways. This study aims to identify second trimester maternal plasma proteomic signatures distinguishing spontaneous and medically-indicated preterm birth and to determine how body mass index modifies these profiles.

Methods: In 100 pregnant individuals (30 spontaneous preterm birth, 30 medically-indicated preterm birth, 40 uncomplicated term deliveries), second trimester plasma was profiled using 7 K SomaScan v4.1 aptamer-based proteomic assay. Multivariate modeling and pathway analyses identified protein signatures distinguishing preterm birth subtypes, and computational network modeling with in silico perturbation analysis defined protein intermediates linking body mass index and preterm birth subtypes.

Results: Here we show distinct proteomic signatures among spontaneous preterm birth, medically-indicated preterm birth, and term deliveries. Supervised modeling achieves clear separation and identifies key discriminatory proteins including SIGLEC6, DHFR, UBASH3A, and PHB2. Early pregnancy body mass index substantially contributes to proteomic variance and modifies preterm birth associated expression of inflammatory (PROK2, IL36A), vascular (F11R) and oxidative stress (GLX1) proteins. Network perturbation identifies FABP4, CRP, UBE2G2, and LRP8 as critical intermediates linking body mass index and preterm birth.

Conclusions: Distinct proteomic profiles characterize spontaneous and medically-indicated preterm birth. Body mass index emerges as a key modifier of these molecular signatures, offering insight into the obesity-associated pathways underlying preterm birth.

Background: Postoperative pancreatic fistula (POPF) is the major driver of postoperative morbidity after pancreatoduodenectomy (PD) and a healthcare issue. In patients with pancreatic tumors the occurrence of POPF could lead to a complete failure of the oncologic strategy by delaying or annihilating the delivery of the indicated adjuvant chemotherapy. However, current preoperative prediction models lack precision. This study aimed to determine the ability of a high dimensional analysis of the patient's peripheral immune system before PD to predict POPF.

Methods: Twenty-two patients in the prospective IMMUNOPANC trial (NCT03978702) underwent PD. Blood samples collected preoperatively were analyzed by combining single-cell mass cytometry and a sparse machine-learning pipeline, Stabl, to identify the most relevant POPF-predictive features. The logistic regression model output was evaluated using a five-fold cross-validation procedure.

Results: Eight (36%) patients experience POPF (grade B, n = 7; grade C, n = 1). The multivariable predictive model includes 11 features-six natural killer, three CD8⁺ T, and two CD4⁺ T lymphocyte cell clusters-revealing a preoperative POPF lymphocyte signature (Pancreatic Fistula Lymphocyte Signature, PFLS). The Stabl algorithm identifies a predictive model classifying POPF patients with high performance (area under the receiver operating characteristic curve=0.81, P = 2.04e-02).

Conclusions: In summary, preoperative circulating immune-cell composition can predict POPF in patients undergoing PD. The clinical application of the PFLS may enable the early identification of patients at high risk before pancreatic surgery, giving clinicians the opportunity to anticipate and mitigate POPF risk through tailored strategies in pre-, intra-, and post-operative settings.