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Colorectal cancer (CRC) remains a challenging and deadly disease with high tumor microenvironment (TME) heterogeneity. Using an integrative multi-omics analysis and artificial intelligence-enabled spatial analysis of whole-slide images, we performed a comprehensive characterization of TME in colorectal cancer (CCCRC). CRC samples were classified into four CCCRC subtypes with distinct TME features, namely, C1 as the proliferative subtype with low immunogenicity; C2 as the immunosuppressed subtype with the terminally exhausted immune characteristics; C3 as the immune-excluded subtype with the distinct upregulation of stromal components and a lack of T cell infiltration in the tumor core; and C4 as the immunomodulatory subtype with the remarkable upregulation of anti-tumor immune components. The four CCCRC subtypes had distinct histopathologic and molecular characteristics, therapeutic efficacy, and prognosis. We found that the C1 subtype may be suitable for chemotherapy and cetuximab, the C2 subtype may benefit from a combination of chemotherapy and bevacizumab, the C3 subtype has increased sensitivity to the WNT pathway inhibitor WIKI4, and the C4 subtype is a potential candidate for immune checkpoint blockade treatment. Importantly, we established a simple gene classifier for accurate identification of each CCCRC subtype. Collectively our integrative analysis ultimately established a holistic framework to thoroughly dissect the TME of CRC, and the CCCRC classification system with high biological interpretability may contribute to biomarker discovery and future clinical trial design.

Background Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by dysregulated inflammatory response lacking reliable diagnosis biomarkers and therapy targets. Extracellular vesicles (EVs)-derived cargo as biomarkers and mediators of SLE have garnered significant attention, however, quantitative inflammatory protein profile of SLE EVs remain uncovered. Objective Current study focuses on exploring the inflammatory protein landscape of SLE serum EVs via quantitative proximity extension assay (PEA) and evaluates their diagnostic utility for SLE and lupus nephritis (LN). Methods In this cross-sectional study, we first utilized PEA to profile inflammatory proteins derived from serum EVs in 101 individuals, including 70 SLE patients and 33 healthy controls (HCs). Subsequently, candidate EV proteins identified from this analysis were subsequently validated via ELISA in an independent cohort comprising 54 SLE patients and 58 HCs. Furthermore, machine-learning classification was utilized to generate prediction models for SLE diagnosis and LN discrimination. Finally, correlation analysis was applied to evaluate the association between EV-derived inflammatory proteins and clinical parameters. Results In the sEV PEA discovery cohort, a total of 49 significantly dysregulated inflammatory proteins with 43 elevated proteins were identified in serum EVs from SLE patients. Two precision prediction models were generated using the random Forest algorithm (RF) for SLE identification and LN discrimination, achieving AUCs of 0.999 and 0.793, respectively. Multiple EV proteins such as CCL23, IL-18R1, SCF and CSF-1 showed a significant correlation with SLE severity parameters including SLEDAI, eGFR and UACR. Furthermore, representative EV proteins including IL-18R1, CCL23 and IFN-γ were further tested in the sEV ELISA validation cohort including 54 SLE patients and 58 HCs. Conclusions The present study identified a unique pattern EV-derived inflammatory proteins in patients with SLE, which could serve as novel biomarkers for SLE diagnosis and disease monitoring.

Immune checkpoint inhibitor (ICI) resistance in hepatocellular carcinoma (HCC) poses a major therapeutic challenge. Here we present a Phase 2 trial evaluating stereotactic body radiotherapy (SBRT) combined with sintilimab and bevacizumab biosimilar (PD-1/VEGF blockade) to overcome resistance in ICI-refractory HCC. Twenty-one patients with progressive HCC after ICI therapy receive SBRT followed by sintilimab 200 mg and bevacizumab biosimilar 15 mg/kg every 3 weeks. The primary outcome, objective response rate in non-irradiated lesions is 33.3%, with a disease control rate of 66.7%. Median progression-free survival is 6.2 months, and estimated median overall survival is 24.4 months. SBRT achieves 100% local control, with 33.3% experiencing grade 3 or higher adverse events. Proteomic profiling reveals that responders exhibit lower baseline IFN-γ and elevated IL-6, while post-SBRT increases in IFN-γ, IL-2, and IL-6 correlate with improved outcomes. These results indicate that combination of SBRT in ICI-refractory HCC is effective, well-tolerated, and may be guided by cytokine assessment. Immune checkpoint inhibitor resistance limits treatment options in advanced hepatocellular carcinoma. Here, the authors report a Phase 2 trial of stereotactic body radiotherapy combined with PD-1/VEGF blockade in patients with refractory hepatocellular carcinoma.

De novo and acquired resistance are major impediments to the efficacy of conventional and targeted cancer therapy. In unselected gastric cancer (GC) patients with advanced disease, trials combining chemotherapy and an anti-EGFR monoclonal antibody have been largely unsuccessful. In an effort to identify biomarkers of resistance so as to better select patients for such trials, we screened the secretome of chemotherapy-treated human GC cell lines. We found that levels of CGA, the α-subunit of glycoprotein hormones, were markedly increased in the conditioned media of chemoresistant GC cells, and CGA immunoreactivity was enhanced in GC tissues that progressed on chemotherapy. CGA levels in plasma increased in GC patients who received chemotherapy, and this increase was correlated with reduced responsiveness to chemotherapy and poor survival. Mechanistically, secreted CGA was found to bind to EGFR and activate EGFR signaling, thereby conferring a survival advantage to GC cells. N-glycosylation of CGA at Asn52 and Asn78 is required for its stability, secretion, and interaction with EGFR. GATA2 was found to activate CGA transcription, whose increase, in turn, induced the expression and phosphorylation of GATA2 in an EGFR-dependent manner, forming a positive feedback circuit that was initiated by GATA2 autoregulation upon sublethal exposure to chemotherapy. Based on this circuit, combination strategies involving anti-EGFR therapies or targeting CGA with microRNAs (miR-708-3p and miR-761) restored chemotherapy sensitivity. These findings identify a clinically actionable CGA/EGFR/GATA2 circuit and highlight CGA as a predictive biomarker and therapeutic target in chemoresistant GC.

Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and widely adopted for various tumor types. Nevertheless, tumor immunotherapy has a few drawbacks, including significant uncertainty of outcome, the possibility of severe immune-related adverse events for patients receiving such treatments, and the lack of effective biomarkers to determine the ICI treatments’ responsiveness. DNA methylation profiles were recently identified as an indicator of the tumor immune microenvironment. They serve as a potential hot spot for predicting responses to ICI treatment for their stability and convenience of measurement by liquid biopsy. We demonstrated the possibility of DNA methylation profiles as a predictor for responses to the ICI treatments at the pan-cancer level by analyzing DNA methylation profiles considered responsive and non-responsive to the treatments. An SVM model was built based on this differential analysis in the pan-cancer levels. The performance of the model was then assessed both at the pan-cancer level and in specific tumor types. It was also compared to the existing gene expression profile-based method. DNA methylation profiles were shown to be predictable for the responses to the ICI treatments in the TCGA cases in pan-cancer levels. The proposed SVM model was shown to have high performance in pan-cancer and specific cancer types. This performance was comparable to that of gene expression profile-based one. The combination of the two models had even higher performance, indicating the potential complementarity of the DNA methylation and gene expression profiles in the prediction of ICI treatment responses.

Parkinson’s disease is a relatively common neurodegenerative disorder in clinical practice, and its prevalence is increasing worldwide. It not only causes patients to have movement disorders such as tremors and delayed initiation but also makes them suffer from olfactory disorders, gastrointestinal disorders, insomnia and other symptoms, which imposes a heavy burden on both patients and their families. In recent years, some scholars believe that the gut-brain axis may be the key to revealing the pathogenesis of Parkinson’s disease. The changes in intestinal flora, or bacterial infections and oxidative stress, lead to abnormal aggregation of alpha-synuclein and formation of neurotoxic Lewy bodies, which are transmitted to the central nervous system via the vagus nerve, thus causing Parkinson’s disease. A large number of evidence-based studies have shown that acupuncture is effective in treating motor disorders and non-motor symptoms such as constipation, neuropsychiatric symptoms, and dysphagia symptoms in Parkinson’s disease, also this treatment is safe. However, its mechanism remains unclear. Acupuncture may affect the gut-brain axis and treat PD by improving intestinal flora imbalance, interfering with the expression of alpha-synuclein protecting neurological function, reducing imflammation, and influencing glial cells, etc. Therefore, the aim of this review is to elucidate the pathogenesis of PD from the perspective of neural, immune, and metabolic signaling pathways of the microbiota-gut-brain axis. In addition, this paper integrates the mechanism of acupuncture treatment with the pathogenesis of PD for the first time and to provide potential new strategies for its treatment.

Objectives MET aberrations are capable of triggering oncogenesis through multiple clinical significance genomic alterations. In non‐small cell lung cancer, MET exon 14 skipping and MET amplification confer sensitivity to MET tyrosine kinase inhibitors. The MET gene is also one of the druggable genes in high‐grade gliomas. However, a systematic comparison of MET variations between lung cancer and brain tumors is lacking. Methods We analyzed a large Chinese cohort of 30,355 lung cancer and 6004 brain tumor patients. Different MET mutation types were characterized, and somatic genomic mutational characteristics were examined across various MET mutation subgroups in both lung cancer and brain tumor cohorts. The impact of MET mutations on prognosis in these two cohorts was also assessed. The study cohort underwent comprehensive genomic profiling using targeted next‐generation sequencing (NGS) panels. Results We found that clinically significant MET mutations exist in both lung and brain tumor cohorts, with the lung cancer group having a higher overall frequency (p < 0.001), but the frequency of different MET mutation types, mutation characteristics, tumor mutation burden, and co‐mutated genes with high frequency all differ. MET alterations were significantly enriched in post‐treatment brain tumors (8.5% vs. 4.8% in treatment‐naïve, p < 0.001). MET mutations also have different prognostic effects in the two cancer types. MET alterations were not prognostic in lung cancer but were associated with significantly poorer survival in brain tumors (median OS: 19.9 vs. 62.9 months, p < 0.001), a finding that held in multivariate analysis. Conclusions Our study demonstrated that the biological and clinical significance of MET alterations is highly context dependent. In lung cancer, MET serves primarily as a predictive biomarker for targeted therapy, whereas in brain tumors, it functions as a prognostic marker of genomic instability and aggressive disease. These findings advocate for context‐specific clinical management strategies.

[...]there is an urgent need for research on the whole genomic landscape of ISMCs using WES. Pathway analysis showed the mutations enriched in the Wnt (4/68), Notch (4/71), receptor-tyrosine kinase (RTK)-Ras (4/85), MYC (2/13), PI3K (2/29), and Hippo (1/38) signaling pathways in ISMCs (Fig. 1E). [...]we also explored potential drug targets based on somatic mutational genes in DGLDB database, such as FLT1, CENPF, DMD, and ADAMTS17, etc. Epithelial–mesenchymal transition (EMT)-related, Wnt and Notch signaling pathways were altered with a high number of genes in our research, which was consistent with EMT-prone characteristics in ISMCs reported by a previous study [4].

Modern electronic systems usually use third‐party IP cores to build basic blocks. However, there may be Hardware Trojans (HTs) in IP cores, which will cause critical security problem. There are already many HT detection methods which claim to detect all publicly available HT benchmarks. But these methods can still be defeated by designing novel HTs. In this article, a method called Blinding HT is proposed, which camouflages itself as a normal circuit and is difficult to be triggered. The Blinding HT hides input signals of HT modules by tracing across multiple sequential levels. This method increases the influence of HT trigger inputs on output signals, so that trigger inputs are not be identified as redundant inputs. In this way, this approach can defeat the detection methods which identify weakly affecting trigger inputs and redundant trigger inputs across multiple sequential levels. As shown in the experimental results, the proposed HTs are hardly detected even by the novel HT detection approach based on machine learning algorithm. These HTs have small footprints on the design in terms of area and power to resist the side‐channel effect analysis. The proposed HT has stealthiness, general applicability and imperceptibility.

Metastasis contributes to the poor prognosis of colorectal cancer, the causative factor of which is not fully understood. Previously, we found that miR-125b (Accession number: MIMAT0000423) contributed to cetuximab resistance in colorectal cancer (CRC). In this study, we identified a novel mechanism by which miR-125b enhances metastasis by targeting cystic fibrosis transmembrane conductance regulator (CFTR) and the tight junction-associated adaptor cingulin (CGN) in CRC. We found that miR-125b expression was upregulated in primary CRC tumors and metastatic sites compared with adjacent normal tissues. Overexpression of miR-125b in CRC cells enhanced migration capacity, while knockdown of miR-125b decreased migration and invasion. RNA-sequencing (RNA-seq) and dual-luciferase reporter assays identified CFTR and CGN as the target genes of miR-125b, and the inhibitory impact of CFTR and CGN on metastasis was further verified both in vitro and in vivo. Moreover, we found that miR-125b facilitated the epithelial-mesenchymal transition (EMT) process and the expression and secretion of urokinase plasminogen activator (uPA) by targeting CFTR and enhanced the Ras Homolog Family Member A (RhoA)/Rho Kinase (ROCK) pathway activity by targeting CGN. Together, these findings suggest miR-125b as a key functional molecule in CRC and a promising biomarker for the diagnosis and treatment of CRC.