Integrative Proteomic Characterization of Human Lung Adenocarcinoma.

Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90ß as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.

Direct Hydrogen Production Promoted by Laser-Induced Water Plasma.

Hydrogen, as a clean energy carrier, plays an important role in addressing the current energy and environmental crisis. However, conventional hydrogen production technologies require extreme reaction conditions, such as high temperature, high pressure, and catalysts. Herein, we study the microscopic mechanism of laser-induced water plasma and subsequent H2 production with real-time time-dependent density functional theory simulations and ab initio molecular dynamics simulations. The results demonstrate that intense laser excites liquid water to generate nonequilibrium plasma in a warm-dense state, which constitutes a superior reaction environment. Subsequent annealing leads to the recombination of energetic reactive particles to generate H2, O2, and H2O2 molecules. Annealing rate and laser wavelength are shown to modulate the product ratio, and the energy conversion efficiency can reach ∼9.2% with an annealing rate of 1.0 K/fs. This work reveals the nonequilibrium atomistic mechanisms of hydrogen production from laser-induced water plasma and shows far-reaching implications for the design of optically controllable hydrogen technology.

Proteome and Metabolome Profiling of Anticoagulant Disorders Induced by Familial Protein S Deficiency.

Protein S deficiency (PSD) is an autosomal dominant disorder characterized by congenital thrombophilia. Studies on PSD are limited yet, resulting in a lack of clarity about molecular changes during abnormal coagulation. Proteomics and metabolomics analyses were conducted on the plasma of PSD patients based on liquid and gas chromatography-mass spectrometry (LC- and GC-MS). Differential proteins and metabolites of PSD were then filtered by univariate statistical analysis and subjected to network analysis using the ingenuity pathway analysis (IPA) platform. The proteome and metabolome of PSD were obviously disturbed, and the biological pathway of coagulation and complement cascades was the most affected. During PSD, overall levels of anticoagulant protein decreased and negative regulation of thrombin production was reduced, causing the formation of fibrin clots and platelet aggregation. Furthermore, 9 differential proteins correlated significantly with protein S, comprising A2M, AGT, APOE, FGG, GPLD1, IGHV1-69, CFHR5, CPN2, and CA1. The biological networks suggested that the pathways of acute phase response, FXR/RXR activation, serotonin receptor signaling, and p70S6K signaling were associated with PSD, indicating an interaction disorder of inflammatory immune and lipid metabolism. The findings may contribute to knowledge of available functional molecules and biological pathways of familial PSD and help with treatment improvement. Data are available via ProteomeXchange with identifier PXD055111 and MetaboLights with reference number MTBLS2653.

Early Diagnostic Markers for Esophageal Squamous Cell Carcinoma: Copy Number Alteration Gene Identification and cfDNA Detection.

The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis revealed widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer data sets. Subsequent validation of 5 candidate markers via ddPCR underscored the efficacy of combined predictive models encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1 in early ESCC screening, as evidenced by the area-under-the-curve values exceeding 0.92 (P < .0001) across various detection contexts. The findings highlighted the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.

A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial.

BACKGROUND: This study aims to develop a stacking model for accurately predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) using longitudinal MRI in breast cancer. METHODS: We included patients with node-positive breast cancer who received NAC following surgery from January 2012 to June 2022. We collected MRIs before and after NAC, and extracted radiomics features from the tumour, peritumour, and ALN regions. The Mann-Whitney U test, least absolute shrinkage and selection operator, and Boruta algorithm were used to select features. We utilised machine learning techniques to develop three single-modality models and a stacking model for predicting ALN response to NAC. RESULTS: This study consisted of a training cohort (n = 277), three external validation cohorts (n = 313, 164, and 318), and a prospective cohort (n = 81). Among the 1153 patients, 60.62% achieved ypN0. The stacking model achieved excellent AUCs of 0.926, 0.874, and 0.862 in the training, external validation, and prospective cohort, respectively. It also showed lower false-negative rates (FNRs) compared to radiologists, with rates of 14.40%, 20.85%, and 18.18% (radiologists: 40.80%, 50.49%, and 63.64%) in three cohorts. Additionally, there was a significant difference in disease-free survival between high-risk and low-risk groups (p < 0.05). CONCLUSIONS: The stacking model can accurately predict ALN status after NAC in breast cancer, showing a lower false-negative rate than radiologists. TRIAL REGISTRATION NUMBER: The clinical trial numbers were NCT03154749 and NCT04858529.

Noninvasive Artificial Intelligence System for Early Predicting Residual Cancer Burden during Neoadjuvant Chemotherapy in Breast Cancer.

OBJECTIVE: To develop an artificial intelligence (AI) system for the early prediction of residual cancer burden (RCB) scores during neoadjuvant chemotherapy (NAC) in breast cancer. SUMMARY BACKGROUND DATA: RCB III indicates drug resistance in breast cancer, and early detection methods are lacking. METHODS: This study enrolled 1048 patients with breast cancer from four institutions, who were all receiving NAC. Magnetic resonance images were collected at the pre- and mid-NAC stages, and radiomics and deep learning features were extracted. A multitask AI system was developed to classify patients into three groups (RCB 0-I, II, and III ) in the primary cohort (PC, n=335). Feature selection was conducted using the Mann-Whitney U- test, Spearman analysis, least absolute shrinkage and selection operator regression, and the Boruta algorithm. Single-modality models were developed followed by model integration. The AI system was validated in three external validation cohorts. (EVCs, n=713). RESULTS: Among the patients, 442 (42.18%) were RCB 0-I, 462 (44.08%) were RCB II and 144 (13.74%) were RCB III. Model-I achieved an area under the curve (AUC) of 0.975 in the PC and 0.923 in the EVCs for differentiating RCB III from RCB 0-II. Model-II distinguished RCB 0-I from RCB II-III, with an AUC of 0.976 in the PC and 0.910 in the EVCs. Subgroup analysis confirmed that the AI system was consistent across different clinical T stages and molecular subtypes. CONCLUSIONS: The multitask AI system offers a noninvasive tool for the early prediction of RCB scores in breast cancer, supporting clinical decision-making during NAC.

Ultrasensitive Detection of Cancer Biomarkers Using Photonic-Crystal-Enhanced Single-Molecule Imaging.

The rapid and sensitive quantification of low-abundance protein markers holds immense significance in early disease diagnosis and treatment. Single-molecule fluorescence imaging exhibits very high detection sensitivity and thus has great application potential in this area. The single-molecule signal, however, is often susceptible to interference from background noise due to its inherently weak intensity. A variety of signal amplification techniques based on cascading reactions have been developed to improve the signal-to-noise ratio of single-molecule imaging. Nevertheless, the operation of these methods is typically complicated and time-consuming, which limits the clinical application. Herein, we introduce an enzyme-free, photonic-crystal-based single-molecule (PC-SM) biochip for cost-effective, time-efficient, and ultrasensitive detection of disease markers. The PC-SM biochip can enhance the signal-to-noise ratio of single molecules by nearly 3-fold compared with unamplified samples, through coupling of the single-molecule photon energy with the optical band gap of the photonic crystal. We used the PC-SM biochip to detect the low-abundance leukemia inhibitory factor in the blood of pancreatic cancer patients and healthy people and achieved a detection limit of 2.0 pg/L and an AUC of 0.9067. The method exhibits exceptional sensitivity and specificity, showing great application potential in various clinical settings.

Megakaryocytic IGF1 coordinates activation and ferroptosis to safeguard hematopoietic stem cell regeneration after radiation injury.

BACKGROUND: Hematopoietic stem cell (HSC) regeneration underlies hematopoietic recovery from myelosuppression, which is a life-threatening side effect of cytotoxicity. HSC niche is profoundly disrupted after myelosuppressive injury, while if and how the niche is reshaped and regulates HSC regeneration are poorly understood. METHODS: A mouse model of radiation injury-induced myelosuppression was built by exposing mice to a sublethal dose of ionizing radiation. The dynamic changes in the number, distribution and functionality of HSCs and megakaryocytes were determined by flow cytometry, immunofluorescence, colony assay and bone marrow transplantation, in combination with transcriptomic analysis. The communication between HSCs and megakaryocytes was determined using a coculture system and adoptive transfer. The signaling mechanism was investigated both in vivo and in vitro, and was consolidated using megakaryocyte-specific knockout mice and transgenic mice. RESULTS: Megakaryocytes become a predominant component of HSC niche and localize closer to HSCs after radiation injury. Meanwhile, transient insulin-like growth factor 1 (IGF1) hypersecretion is predominantly provoked in megakaryocytes after radiation injury, whereas HSCs regenerate paralleling megakaryocytic IGF1 hypersecretion. Mechanistically, HSCs are particularly susceptible to megakaryocytic IGF1 hypersecretion, and mTOR downstream of IGF1 signaling not only promotes activation including proliferation and mitochondrial oxidative metabolism of HSCs, but also inhibits ferritinophagy to restrict HSC ferroptosis. Consequently, the delicate coordination between proliferation, mitochondrial oxidative metabolism and ferroptosis ensures functional HSC expansion after radiation injury. Importantly, punctual IGF1 administration simultaneously promotes HSC regeneration and hematopoietic recovery after radiation injury, representing a superior therapeutic approach for myelosuppression. CONCLUSIONS: Our study identifies megakaryocytes as a last line of defense against myelosuppressive injury and megakaryocytic IGF1 as a novel niche signal safeguarding HSC regeneration.

Hepatic arterial infusion therapy for advanced hepatocellular carcinoma after systemic treatment failure: Multicenter, real-world study.

AIM: The study was conducted to evaluate the feasibility and safety profile of hepatic arterial infusion chemotherapy with oxaliplatin, 5-fluorouracil, and leucovorin (HAIC-FOLFOX) as an alternative therapeutic choice for patients with advanced hepatocellular carcinoma (HCC) that is refractory to systemic treatment including immune checkpoint blockades or molecular targeting agents. METHODS: Two hundred and forty five consecutive patients with advanced HCC who received HAIC-FOLFOX treatment after systemic treatment failure were retrospectively reviewed in six institutions and their survival, tumor response, and tolerance were assessed. RESULTS: The median overall survival (OS) and progression-free survival of the 209 included participants were 10.5 months (95% confidence interval [CI], 8.1-12.9) and 6.0 months (95% CI, 5.1-6.9), respectively. According to Response Evaluation Criteria in Solid Tumors 1.1 criteria, the objective response rate was 21.1%, and the disease control rate was 64.6%. Multivariate analysis of risk factors of OS were albumin-bilirubin grade (2 and 3 vs. 1, hazard ratio [HR] 1.57; 95% CI, 1.05-2.34; p = 0.028), tumor number (>3 vs. 1-3, HR 2.18; 95% CI, 1.10-4.34; p = 0.026), extrahepatic spread (present vs. absent, HR 1.61, 95% CI, 1.06-2.45; p = 0.027), synchronous systemic treatment (present vs. absent, HR 0.55, 95% CI, 0.37-0.83; p = 0.004) and treatment response (responder vs. nonresponder, HR 0.30, 95% CI, 0.17-0.53; p < 0.001). Grade 3-4 adverse events (AEs) occurred in 59 (28.2%) HCC patients. All AEs were manageable, and deaths related to hepatic artery infusion chemotherapy treatment were not observed. CONCLUSIONS: Our findings support the effectiveness and safety of HAIC-FOLFOX treatment for patients with advanced HCC who have failed systemic treatment.

The role of ferroptosis in DM-induced liver injury.

The liver damage caused by Diabetes Mellitus (DM) has attracted increasing attention in recent years. Liver injury in DM can be caused by ferroptosis, a form of cell death caused by iron overload. However, the role of iron transporters in this context is still not clear. Herein, we attempted to shed light on the pathophysiological mechanism of ferroptosis. DM was induced in 8-week-old male rats by streptozotocin (STZ) before assessment of the degree of liver injury. Together with histopathological changes, variations in glutathione peroxidase 4 (GPX4), glutathione (GSH), superoxide dismutase (SOD), transferrin receptor 1 (TFR1), ferritin heavy chain (FTH), ferritin light chain (FTL), ferroportin and Prussian blue staining, were monitored in rat livers before and after treatment with Fer-1. In the liver of STZ-treated rats, GSH and SOD levels decreased, whereas those of malondialdehyde (MDA) increased. Expression of TFR1, FTH and FTL increased whereas that of glutathione peroxidase 4 (GPX4) and ferroportin did not change significantly. Prussian blue staining showed that iron levels increased. Histopathology showed liver fibrosis and decreased glycogen content. Fer-1 treatment reduced iron and MDA levels but GSH and SOD levels were unchanged. Expression of FTH and FTL was reduced whereas that of ferroportin showed a mild decrease. Fer-1 treatment alleviated liver fibrosis, increased glycogen content and mildly improved liver function. Our study demonstrates that ferroptosis is involved in DM-induced liver injury. Regulating the levels of iron transporters may become a new therapeutic strategy in ferroptosis-induced liver injury.