MolMVC: Enhancing molecular representations for drug-related tasks through multi-view contrastive learning.

MOTIVATION: Effective molecular representation is critical in drug development. The complex nature of molecules demands comprehensive multi-view representations, considering 1D, 2D, and 3D aspects, to capture diverse perspectives. Obtaining representations that encompass these varied structures is crucial for a holistic understanding of molecules in drug-related contexts. RESULTS: In this study, we introduce an innovative multi-view contrastive learning framework for molecular representation, denoted as MolMVC. Initially, we use a Transformer encoder to capture 1D sequence information and a Graph Transformer to encode the intricate 2D and 3D structural details of molecules. Our approach incorporates a novel attention-guided augmentation scheme, leveraging prior knowledge to create positive samples tailored to different molecular data views. To align multi-view molecular positive samples effectively in latent space, we introduce an adaptive multi-view contrastive loss (AMCLoss). In particular, we calculate AMCLoss at various levels within the model to effectively capture the hierarchical nature of the molecular information. Eventually, we pre-train the encoders via minimizing AMCLoss to obtain the molecular representation, which can be used for various down-stream tasks. In our experiments, we evaluate the performance of our MolMVC on multiple tasks, including molecular property prediction (MPP), drug-target binding affinity (DTA) prediction and cancer drug response (CDR) prediction. The results demonstrate that the molecular representation learned by our MolMVC can enhance the predictive accuracy on these tasks and also reduce the computational costs. Furthermore, we showcase MolMVC's efficacy in drug repositioning across a spectrum of drug-related applications. AVAILABILITY AND IMPLEMENTATION: The code and pre-trained model are publicly available at https://github.com/Hhhzj-7/MolMVC.

Mental health literacy and help-seeking intention among Chinese elite athletes: the mediating roles of stigma and social support.

Objectives: Considering the importance of mental health help-seeking, researchers have closely examined the relationship between mental health literacy (MHL) and help-seeking intention (HSI). Furthermore, the high impact of stigma and the potential value of social support on HSI have been recognised. However, the relationship between these variables has not been fully tested within the context of Chinese elite athletes. This study addressed this gap by examining the relationship between MHL and HSI. Furthermore, it explored the mediating effects of public stigma, self-stigma, and social support on the relationship between MHL and HSI among Chinese elite athletes. Methods: 450 Chinese elite athletes (M age = 18.12, SD = 3.20, 46.2% female) self-reported their MHL, public stigma, self-stigma, social support, and HSI. Mediation analysis was conducted using the bootstrap approach of the PROCESS macro version 3.3 of SPSS 25. Results: The results showed a significant positive correlation between MHL and HSI (r = 0.348). The results also demonstrated that MHL was a predictor of HSI (ß = 0.337, 95%CI [0.249, 0.425], p < 0.001). Furthermore, 1) the indirect effect of MHL → public stigma→HSI was 0.024 and a 95%CI [0.003, 0.053]. Specifically, MHL predicted public stigma (Estimate = -0.151, 95%CI [-0.187, -0.045], p < 0.001), and public stigma predicted HSI (Estimate = -0.161, 95%CI [- 0.549, -0.164], p < 0.001); 2) the indirect effect of MHL → self-stigma→ HSI was 0.016 and 95%CI [0.002, 0.038]. Specifically, MHL predicted self-stigma (Estimate = -0.137, 95%CI [-0.069, -0.013], p < 0.01), and self-stigma predicted HSI (Estimate = -0.120, 95%CI [-1.181, -0.186], p < 0.01); as well as 3) the indirect effect of MHL → social support→HSI was 0.029 and a 95%CI [0.009, 0.055]. Specifically, MHL predicted social support (Estimate = 0.208, 95%CI [0.018, 0.047], p < 0.001), and social support predicted HSI (Estimate = 0.141, 95%CI [0.578, 2.442], p < 0.01). Additionally, the direct effects from MHL to HSI is (ß = 0.452, 95%CI [0.304, 0.600], p < 0.001). Conclusion: Our findings provide empirical support for the roles of public stigma, self-stigma, and social support as mechanisms of behavioural change in MHL interventions. These factors increase HSI among elite athletes. Future studies should further test these mediating effects using experimental designs.

Dendrobium nobile-derived polysaccharides stimulate the glycolytic pathway by activating SIRT2 to regulate insulin resistance in polycystic ovary syndrome granulosa cells.

Insulin resistance (IR) is one of the major complications of polycystic ovary syndrome (PCOS). This study aimed to investigate the effects and the molecular regulatory mechanism by which Dendrobium nobile-derived polysaccharides (DNP) improve IR in rats with letrozole and high-fat-diet induced PCOS. In vivo, DNP (200 mg/kg/d) administration not only reduced body weight, blood glucose, and insulin levels in PCOS rats, but also improve the disrupted estrous cycle. In addition, DNP treatment reduced atretic and cystic follicles and enhanced granulosa cell layer thickness, thereby restoring follicle development. In vitro, DNP treatment (100 µM) increased lactate levels and decreased pyruvate levels in insulin-treated (8 µg/mL) KGN cells. Additionally, DNP also decreased the expression of IGF1 and increased that of IGF1R, SIRT2, LDHA, PKM2 and HK2 both in vivo and in vitro. Also, SIRT2 expression was specifically inhibited by AGK2, while DNP significantly improved IR and glycolysis by reversing the effect of AGK2 treatment on lactate and pyruvate production, upregulating the expression levels of IGF1R, LDHA, HK2, and PKM2 and downregulating the expression level of IGF1. The results indicate that DNP can effectively improve IR and restore glycolytic pathway by activating SIRT2, which may provide a potential therapeutic approach for PCOS patients.

Machine learning-based analysis identifies and validates serum exosomal proteomic signatures for the diagnosis of colorectal cancer.

The potential of serum extracellular vesicles (EVs) as non-invasive biomarkers for diagnosing colorectal cancer (CRC) remains elusive. We employed an in-depth 4D-DIA proteomics and machine learning (ML) pipeline to identify key proteins, PF4 and AACT, for CRC diagnosis in serum EV samples from a discovery cohort of 37 cases. PF4 and AACT outperform traditional biomarkers, CEA and CA19-9, detected by ELISA in 912 individuals. Furthermore, we developed an EV-related random forest (RF) model with the highest diagnostic efficiency, achieving AUC values of 0.960 and 0.963 in the train and test sets, respectively. Notably, this model demonstrated reliable diagnostic performance for early-stage CRC and distinguishing CRC from benign colorectal diseases. Additionally, multi-omics approaches were employed to predict the functions and potential sources of serum EV-derived proteins. Collectively, our study identified the crucial proteomic signatures in serum EVs and established a promising EV-related RF model for CRC diagnosis in the clinic.

A nomogram predicting distant metastasis risk for gastric cancer patients with preoperative anemia: a multicenter retrospective study.

BACKGROUND: Anemia represents a well-established risk factor for patients diagnosed with gastric cancer, and is often associated with an unfavorable prognosis. In this context, the timely prediction of distant metastasis risk in patients with anemic gastric cancer assumes paramount importance. METHODS: Information of gastric cancer patients complicated with preoperative anemia in the First Affiliated Hospital of Sun Yat-sen University was collected. The cohort from the First Affiliated Hospital of Guangxi Medical University was used as an external validation set. A Nomogram was established based on the risk factors screened by univariate and multivariate logistic regression analyses. RESULTS: A total of 848 gastric cancer patients with preoperative anemia were enrolled. Pyloric obstruction, carcinoma antigen 125, T stage, N stage, tumor size, and preoperative weight loss were independent predictors of distant metastasis in gastric cancer patients with anemia (p < 0.05), based on which a nomogram was constructed. The accuracy, reliability and clinical value of the nomogram were evaluated by concordance index, receiver operating characteristic curve, decision curve analysis, calibration curve and showed good stability and clinical predictive value. CONCLUSIONS: Preoperative anemic gastric cancer patients, complicated with pyloric obstruction, elevated CA125, advanced T and N stage, larger tumor size, and preoperative weight loss, should be paid more attention to distant metastasis.

Prevotella copri transplantation promotes neurorehabilitation in a mouse model of traumatic brain injury.

BACKGROUND: The gut microbiota plays a critical role in regulating brain function through the microbiome-gut-brain axis (MGBA). Dysbiosis of the gut microbiota is associated with neurological impairment in Traumatic brain injury (TBI) patients. Our previous study found that TBI results in a decrease in the abundance of Prevotella copri (P. copri). P. copri has been shown to have antioxidant effects in various diseases. Meanwhile, guanosine (GUO) is a metabolite of intestinal microbiota that can alleviate oxidative stress after TBI by activating the PI3K/Akt pathway. In this study, we investigated the effect of P. copri transplantation on TBI and its relationship with GUO-PI3K/Akt pathway. METHODS: In this study, a controlled cortical impact (CCI) model was used to induce TBI in adult male C57BL/6J mice. Subsequently, P. copri was transplanted by intragastric gavage for 7 consecutive days. To investigate the effect of the GUO-PI3K/Akt pathway in P. copri transplantation therapy, guanosine (GUO) was administered 2 h after TBI for 7 consecutive days, and PI3K inhibitor (LY294002) was administered 30 min before TBI. Various techniques were used to assess the effects of these interventions, including quantitative PCR, neurological behavior tests, metabolite analysis, ELISA, Western blot analysis, immunofluorescence, Evans blue assays, transmission electron microscopy, FITC-dextran permeability assay, gastrointestinal transit assessment, and 16 S rDNA sequencing. RESULTS: P. copri abundance was significantly reduced after TBI. P. copri transplantation alleviated motor and cognitive deficits tested by the NSS, Morris's water maze and open field test. P. copri transplantation attenuated oxidative stress and blood-brain barrier damage and reduced neuronal apoptosis after TBI. In addition, P. copri transplantation resulted in the reshaping of the intestinal flora, improved gastrointestinal motility and intestinal permeability. Metabolomics and ELISA analysis revealed a significant increase in GUO levels in feces, serum and injured brain after P. copri transplantation. Furthermore, the expression of p-PI3K and p-Akt was found to be increased after P. copri transplantation and GUO treatment. Notably, PI3K inhibitor LY294002 treatment attenuated the observed improvements. CONCLUSIONS: We demonstrate for the first time that P. copri transplantation can improve GI functions and alter gut microbiota dysbiosis after TBI. Additionally, P. copri transplantation can ameliorate neurological deficits, possibly via the GUO-PI3K/Akt signaling pathway after TBI.

The intestine microbiota of shrimp and its impact on cultivation.

Intestinal microbiome contains several times of functional genes compared to the host and mediates the generation of multiple metabolic products, and therefore it is called "second genome" for host. Crustaceans rank second among the largest subphylum of aquaculture animals that are considered potentially satisfy global substantial food and nutrition security, among which the Pacific white shrimp (Litopenaeus vannamei) ranks the first in the production. Currently, increasing evidences show that outbreaks of some most devastating diseases in shrimp, including white feces syndrome (WFS) and acute hepatopancreatic necrosis disease (AHPND), are related to intestinal microbiota dysbiosis. Importantly, the intestine microbial composition can be altered by environmental stress, diet, and age. In this review, we overview the progress of intestinal microbiota dysbiosis and WFS or ANPHD in shrimp, and how the microbial composition is altered by external factors. Hence, developing suitable microbial micro-ecological prevention and control strategy to maintain intestinal balance may be a feasible solution to reduce the risk of disease outbreaks. Moreover, we highlight that defining the "healthy intestine microbiota" and evaluating the causality of intestinal microbiota dysbiosis and diseases following the logic of "Microecological Koch's postulates" should be the key goal in future shrimp intestinal field, which help to guide disease diagnosis and prevent disease outbreaks in shrimp farming. KEY POINTS: • Intestinal microbiota dysbiosis is relevant to multiple shrimp diseases. • Microecological Koch's postulates help to evaluate the causality of shrimp diseases.

Enhancing Predictions of Drug Solubility through Multidimensional Structural Characterization Exploitation.

Solubility is not only a significant physical property of molecules but also a vital factor in smallmolecule drug development. Determining drug solubility demands stringent equipment, controlled environments, and substantial human and material resources. The accurate prediction of drug solubility using computational methods has long been a goal for researchers. In this study, we introduce MSCSol, a solubility prediction model that integrates multidimensional molecular structure information. We incorporate a graph neural network with geometric vector perceptrons (GVP-GNN) to encode 3D molecular structures, representing spatial arrangement and orientation of atoms, as well as atomic sequences and interactions. We also employ Selective Kernel Convolution combined with Global and Local attention mechanisms to capture molecular features context at different scales. Additionally, various descriptors are calculated to enrich the molecular representation. For the 2D and 3D structural data of molecules, we design different data augmentation strategies to enhance generalization ability and prevent the model from learning irrelevant information. Extensive experiments on benchmark and independent datasets demonstrate MSCSol's superior performance. Ablation studies further confirm the effectiveness of different modules. Interpretability analysis highlights the importance of various atomic groups and substructures for solubility and verifies that our model effectively captures functional molecular structures and higher-order knowledge. The source code and datasets are freely available at https://github.com/ZiyuFanCSU/MSCSol.

Identification and validation of the surface proteins FIBG, PDGF-ß, and TGF-ß on serum extracellular vesicles for non-invasive detection of colorectal cancer: experimental study.

OBJECTIVES: The absence of non-invasive biomarkers for the early diagnosis of colorectal cancer (CRC) has contributed to poor prognosis. Extracellular vesicles (EVs) have emerged as promising candidates for cancer monitoring using liquid biopsy. However, the complexity of EVs isolation procedures and the absence of clear targets for detecting serum-derived EVs have hindered the clinical application of EVs in early CRC diagnosis. METHODS: In the discovery phase, we conducted a comprehensive 4D-DIA proteomic analysis of serum-derived EVs samples from 37 individuals, performing an initial screening of EVs surface proteins. In the technical validation phase, we developed an extraction-free CRC-EVArray microarray to assess the expression of these potential EVs surface proteins in a multi-centre study comprising 404 individuals. In the application phase, the authors evaluated the diagnostic efficacy of the CRC-EVArray model based on machine-learning algorithms. RESULTS: Through 4D-DIA proteomic analysis, the authors identified seven potential EVs surface proteins showing significantly differential expression in CRC patients compared to healthy controls. Utilizing our developed high-throughput CRC-EVArray microarray, we further confirmed the differential expression of three EVs surface proteins, FIBG, PDGF-ß and TGF-ß, in a large sample population. Moreover, we established an optimal CRC-EVArray model using the NNET algorithm, demonstrating superior diagnostic efficacy with an area under the curve (AUC) of 0.882 in the train set and 0.937 in the test set. Additionally, we predicted the functions and potential origins of these EVs-derived proteins through a series of multi-omics approaches. CONCLUSIONS: Our systematic exploration of surface protein expression profiles on serum-derived EVs has identified FIBG, PDGF-ß, and TGF-ß as novel diagnostic biomarkers for CRC. The development of CRC-EVArray diagnostic model based on these findings provided an effective tool for the large-scale CRC screening, thus facilitating its translation into clinical practice.

Mental health literacy, mental health experiences and help-seeking behaviours of Chinese elite athletes: a qualitative study.

Introduction: Elite athletes' help-seeking on mental health might be influenced by their mental health literacy (MHL) and mental health experiences. The current study aimed to explore the MHL, experiences and help-seeking behaviours among elite athletes using a qualitative approach. Methods: Face-to-face semi-structured interviews were conducted among 20 Chinese elite athletes, 12 coaches, and 5 team officials. Interview data was analyzed using content analysis. Results: Seven main themes emerged from the analysis. The current study revealed that Chinese elite athletes suffered from various mental health issues and athletes' MHL levels, help-seeking attitudes and intentions, Chinese sports environments, and Chinese cultural background could impact their help-seeking behaviours. Conclusion: Support for Chinese elite athletes' mental health and help-seeking requires improvement.

Changes of bacterial communities and bile acid metabolism reveal the potential "intestine-hepatopancreas axis" in shrimp.

The interaction between the gut and the liver plays a significant role in individual health and diseases. Mounting evidence supports that bile acids are important metabolites in the bidirectional communication between the gut and the liver. Most of the current studies on the "gut-liver axis" have focused on higher vertebrates, however, few was reported on lower invertebrates such as shrimp with an open circulatory system. Here, microbiomic and metabolomic analyses were conducted to investigate the bacterial composition and bile acid metabolism in intestine, hemolymph and hepatopancreas of Penaeus vannamei fed diets supplemented with octanoic acid and oleic acid. After six days of feeding, the bacterial composition in intestine, hemolymph and hepatopancreas changed at different stages, with significant increases in the relative abundance of several genera such as Pseudomonas and Rheinheimera in intestine and hepatopancreas. Notably, there was a more similar bacterial composition in intestine and hepatopancreas at the genus level, which indicated the close communication between shrimp intestine and hepatopancreas. Meanwhile, higher content of some bile acids such as lithocholic acid (LCA) and α-muricholic acid (α-MCA) in intestine and lower content of some bile acids such as taurohyocholic acids (THCA) and isolithocholic acid (IsoLCA) in hepatopancreas were detected. Furthermore, Spearman correlation analysis revealed a significant correlation between bacterial composition and bile acid metabolism in intestine and hepatopancreas. The microbial source tracking analysis showed that there was a high proportion of intestine and hepatopancreas bacterial community as the source of each other. Collectively, these results showed a strong crosstalk between shrimp intestine and hepatopancreas, which suggests a unique potential "intestine-hepatopancreas axis" in lower invertebrate shrimp with an open circulatory system. Our finding contributed to the understanding of the interplay between shrimp intestine and hepatopancreas in the view of microecology and provided new ideas for shrimp farming and disease control.

SGCLDGA: unveiling drug-gene associations through simple graph contrastive learning.

Drug repurposing offers a viable strategy for discovering new drugs and therapeutic targets through the analysis of drug-gene interactions. However, traditional experimental methods are plagued by their costliness and inefficiency. Despite graph convolutional network (GCN)-based models' state-of-the-art performance in prediction, their reliance on supervised learning makes them vulnerable to data sparsity, a common challenge in drug discovery, further complicating model development. In this study, we propose SGCLDGA, a novel computational model leveraging graph neural networks and contrastive learning to predict unknown drug-gene associations. SGCLDGA employs GCNs to extract vector representations of drugs and genes from the original bipartite graph. Subsequently, singular value decomposition (SVD) is employed to enhance the graph and generate multiple views. The model performs contrastive learning across these views, optimizing vector representations through a contrastive loss function to better distinguish positive and negative samples. The final step involves utilizing inner product calculations to determine association scores between drugs and genes. Experimental results on the DGIdb4.0 dataset demonstrate SGCLDGA's superior performance compared with six state-of-the-art methods. Ablation studies and case analyses validate the significance of contrastive learning and SVD, highlighting SGCLDGA's potential in discovering new drug-gene associations. The code and dataset for SGCLDGA are freely available at https://github.com/one-melon/SGCLDGA.

TREM2 alleviates white matter injury after traumatic brain injury in mice might be mediated by regulation of DHCR24/LXR pathway in microglia.

BACKGROUND: White matter injury (WMI) is an important pathological process after traumatic brain injury (TBI). The correlation between white matter functions and the myeloid cells expressing triggering receptor-2 (TREM2) has been convincingly demonstrated. Moreover, a recent study revealed that microglial sterol metabolism is crucial for early remyelination after demyelinating diseases. However, the potential roles of TREM2 expression and microglial sterol metabolism in WMI after TBI have not yet been explored. METHODS: Controlled cortical injury was induced in both wild-type (WT) and TREM2 depletion (TREM2 KO) mice to simulate clinical TBI. COG1410 was used to upregulate TREM2, while PLX5622 and GSK2033 were used to deplete microglia and inhibit the liver X receptor (LXR), respectively. Immunofluorescence, Luxol fast blue staining, magnetic resonance imaging, transmission electron microscopy, and oil red O staining were employed to assess WMI after TBI. Neurological behaviour tests and electrophysiological recordings were utilized to evaluate cognitive functions following TBI. Microglial cell sorting and transcriptomic sequencing were utilized to identify alterations in microglial sterol metabolism-related genes, while western blot was conducted to validate the findings. RESULTS: TREM2 expressed highest at 3 days post-TBI and was predominantly localized to microglial cells within the white matter. Depletion of TREM2 worsened aberrant neurological behaviours, and this phenomenon was mediated by the exacerbation of WMI, reduced renewal of oligodendrocytes, and impaired phagocytosis ability of microglia after TBI. Subsequently, the upregulation of TREM2 alleviated WMI, promoted oligodendrocyte regeneration, and ultimately facilitated the recovery of neurological behaviours after TBI. Finally, the expression of DHCR24 increased in TREM2 KO mice after TBI. Interestingly, TREM2 inhibited DHCR24 and upregulated members of the LXR pathway. Moreover, LXR inhibition could partially reverse the effects of TREM2 upregulation on electrophysiological activities. CONCLUSIONS: We demonstrate that TREM2 has the potential to alleviate WMI following TBI, possibly through the DHCR24/LXR pathway in microglia.

Extracellular vesicles-derived CXCL4 is a candidate serum tumor biomarker for colorectal cancer.

Extracellular vesicles (EVs) were promising circulating biomarkers for multiple diseases, but whether serum EVs-derived proteins could be used as a reliable tumor biomarker for colorectal cancer (CRC) remained inconclusive. In this study, we identified CXCL4 by a 4D data-independent acquisition-based quantitative proteomics assay of serum EVs-derived proteins in 40 individuals and subsequently analyzed serum EVs-derived CXCL4 levels by ELISA in 2 cohorts of 749 individuals. The results revealed that EVs-derived CXCL4 levels were dramatically elevated in CRC patients than in benign colorectal polyp patients or healthy controls (HC). Furthermore, receiver operating characteristic curves revealed that EVs-derived CXCL4 exhibited superior diagnostic performance with area under the curve of 0.948 in the training cohort. Additionally, CXCL4 could effectively distinguish CRC in stage I/II from HC. Notably, CRC patients with high levels of EVs-derived CXCL4 have shorter 2-year progression-free survival than those with low levels. Overall, our findings demonstrated that serum EVs-derived CXCL4 was a candidate diagnostic and prognostic biomarker for CRC.

Transcriptional dynamics and regulatory function of milRNAs in Ascosphaera apis invading Apis mellifera larvae.

In the present study, small RNA (sRNA) data from Ascosphaera apis were filtered from sRNA-seq datasets from the gut tissues of A. apis-infected Apis mellifera ligustica worker larvae, which were combined with the previously gained sRNA-seq data from A. apis spores to screen differentially expressed milRNAs (DEmilRNAs), followed by trend analysis and investigation of the DEmilRNAs in relation to significant trends. Additionally, the interactions between the DEmilRNAs and their target mRNAs were verified using a dual-luciferase reporter assay. In total, 974 A. apis milRNAs were identified. The first base of these milRNAs was biased toward U. The expression of six milRNAs was confirmed by stem-loop RT-PCR, and the sequences of milR-3245-y and milR-10285-y were validated using Sanger sequencing. These miRNAs grouped into four significant trends, with the target mRNAs of DEmilRNAs involving 42 GO terms and 120 KEGG pathways, such as the fungal-type cell wall and biosynthesis of secondary metabolites. Further investigation demonstrated that 299 DEmilRNAs (novel-m0011-3p, milR-10048-y, bantam-y, etc.) potentially targeted nine genes encoding secondary metabolite-associated enzymes, while 258 (milR-25-y, milR-14-y, milR-932-x, etc.) and 419 (milR-4561-y, milR-10125-y, let-7-x, etc.) DEmilRNAs putatively targeted virulence factor-encoded genes and nine genes involved in the MAPK signaling pathway, respectively. Additionally, the interaction between ADM-B and milR-6882-x, as well as between PKIA and milR-7009-x were verified. Together, these results not only offer a basis for clarifying the mechanisms underlying DEmilRNA-regulated pathogenesis of A. apis and a novel insight into the interaction between A. apis and honey bee larvae, but also provide candidate DEmilRNA-gene axis for further investigation.

Feasibility and tolerability of eribulin-based chemotherapy versus other chemotherapy regimens for patients with metastatic triple-negative breast cancer: a single-centre retrospective study.

Background: Patients with Triple-negative breast cancer (TNBC) face a poor prognosis and limited therapeutic options. Current data on eribulin usage to treat TNBC is scarce. Therefore, we sought to compare the feasibility and tolerability of eribulin-based regimens with other chemotherapy regimens in patients with TNBC. Method: This retrospective study was conducted at Fujian Medical University Cancer Hospital and included 159 patients with TNBC enrolled between October 2011 and January 2023. Patients underwent treatment with eribulin-based and other chemotherapy regimens. The study's primary endpoints were progression-free survival (PFS) and overall survival (OS), while its secondary endpoint was objective response rate (ORR), disease control rate (DCR), and safety. Tumour response was assessed using RECIST V.1.1 criteria. Results: Of the 159 participants in the study, 42 individuals (26.4%) received treatment with eribulin, whereas 117 participants (73.6%) were administered alternative chemotherapy regimens, which included nab-paclitaxel-based therapy (n = 45) and platinum-based therapy (n = 51). The follow-up period for all patients ended on 31 December 2022, and the median follow-up time was 18.3 months (range:0.7-27.5). Following propensity score matching (PSM), eribulin-based treatment resulted in longer median progression-free survival compared to platinum-based (hazard ratio (HR) = 0.41, p = 0.006), nab-paclitaxel-based (hazard ratio = 0.36, p = 0.001) and other chemotherapy (HR = 0.39, p < 0.001). Also, eribulin induced a remarkable prolongation of the median overall survival duration in all three comparative groups. The group receiving eribulin treatment showed significantly reduced incidences of any grade of anaemia, peripheral neuropathy, nausea and vomiting, and hair loss compared to other chemotherapy groups. Conclusion: For the salvage treatment of advanced TNBC, treatment with eribulin produced longer median PFS and OS than other chemotherapy regimens, with a well-tolerated safety profile. Therefore, further investigation of eribulin-based treatment in larger randomized trials for patients with advanced TNBC is warranted.

RNA methylation-related genes INHBB and SOWAHA are associated with MSI status in colorectal cancer patients and may serve as prognostic markers for predicting immunotherapy efficacy.

The role of RNA methylation is vital in the advancement and spread of tumors. However, its exact role in microsatellite instability in colorectal cancer (CRC) is still not fully understood. To address this gap in knowledge, this study investigated the impact of genes associated with RNA methylation on the prognosis and response to immunotherapy in individuals diagnosed with low microsatellite instability (MSI-L) or microsatellite stable (MSS) CRC. The differentially expressed genes (DEGs) in two groups of patients: those with high microsatellite instability (MSI-H) and those with MSI-L/MSS was thoroughly investigated and compared with aims of exploring the association between them and the 60 RNA methylation regulators. We employed these genes and developed an MSI-RMscore to establish a risk signature capable of forecasting patient outcomes. Furthermore, an investigation of the immunophenotypic traits was conducted encompassing patients categorized as high-risk and low-risk. By combining the MSI-RMscore and clinicopathological features, a predictive nomogram was developed, which was subsequently validated using the GEO database. Furthermore, immunohistochemistry was employed to establish the correlation between INHBB and SOWAHA and the MSI status, as well as patient prognosis. Our findings indicated that the high-risk subgroup exhibited unfavorable overall survival rates, reduced responsiveness to immune checkpoint blockers, elevated estimate scores, and increased infiltration of macrophages and fibroblasts. We also confirmed that INHBB and SOWAHA were associated with CRC patient prognosis and MSI status, as well as immunotherapy response. These findings suggest that targeting INHBB and SOWAHA could be a promising strategy to enhance patient responsiveness to immunotherapy.

Macrophages Promote Subtype Conversion and Endocrine Resistance in Breast Cancer.

BACKGROUND: The progression of tumors from less aggressive subtypes to more aggressive states during metastasis poses challenges for treatment strategies. Previous studies have revealed the molecular subtype conversion between primary and metastatic tumors in breast cancer (BC). However, the subtype conversion during lymph node metastasis (LNM) and the underlying mechanism remains unclear. METHODS: We compared clinical subtypes in paired primary tumors and positive lymph nodes (PLNs) in BC patients and further validated them in the mouse model. Bioinformatics analysis and macrophage-conditioned medium treatment were performed to investigate the role of macrophages in subtype conversion. RESULTS: During LNM, hormone receptors (HRs) were down-regulated, while HER2 was up-regulated, leading to the transformation of luminal A tumors towards luminal B tumors and from luminal B subtype towards HER2-enriched (HER2-E) subtype. The mouse model demonstrated the elevated levels of HER2 in PLN while retaining luminal characteristics. Among the various cells in the tumor microenvironment (TME), macrophages were the most clinically relevant in terms of prognosis. The treatment of a macrophage-conditioned medium further confirmed the downregulation of HR expression and upregulation of HER2 expression, inducing tamoxifen resistance. Through bioinformatics analysis, MNX1 was identified as a potential transcription factor governing the expression of HR and HER2. CONCLUSION: Our study revealed the HER2-E subtype conversion during LNM in BC. Macrophages were the crucial cell type in TME, inducing the downregulation of HR and upregulation of HER2, probably via MNX1. Targeting macrophages or MNX1 may provide new avenues for endocrine therapy and targeted treatment of BC patients with LNM.