Pre-Operative Immunonutrition Enhances Postoperative Outcomes and Elevates Tumor-Infiltrating Lymphocyte Counts in Colorectal Cancer Patients: A Meta-Analysis of Randomized Controlled Trials.

OBJECTIVE: This study (CRD42023464989) aimed to explore the effects of pre-operation immunonutrition on safety and immune related factors in colorectal cancer patients undergoing surgery. METHODS: We systematically searched PubMed, Embase, and Wanfang databases to collect all clinical randomized controlled trials of the application of pre-operation immunonutrition for patients with colorectal cancer, published until July 2023. The primary outcomes were safety and immune related factors. RESULTS: A total of 16 studies were finally included. Preoperative immunonutrition could reduce the postoperative infection rate (risk ratio (RR) = 0.56, 95% confidence interval (CI): 0.36, 0.88; p = .01), and wound infection rate (RR = 0.44, 95% CI: 0.27, 0.70; p < .001) in patients with colorectal cancer. For length of stay (mean difference (MD) = -1.10, 95% CI: -2.70, 0.49; p = .17), it was similar between groups. Meanwhile, patients in the pre-operation immune nutrition group also had significantly increased infiltrative lymphocytes CD16+ (MD = 0.04, 95% CI: 0.02, 0.06; p < .001), and CD56+ (MD = 0.05, 95% CI: 0.03, 0.06; p < .001) cells in the tumor tissues, compared to the control group. CONCLUSION: Immunonutrition intervention has the potential to reduce postoperative infectious complications and improve tumor infiltrative lymphocytes in patients with colorectal cancer undergoing surgery.

Prophylactic hyperthermic intraperitoneal chemotherapy in T4 colorectal cancer: Can it improve the oncologic prognosis? - A propensity score matching study.

BACKGROUND: Some studies show that cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (HIPEC) may improve overall survival and is a possible curative treatment for selected colorectal cancer (CRC) patients with restricted peritoneal metastasis (PM). The value of HIPEC in preventing PM of CRC is still controversial. MATERIALS AND METHODS: In this retrospective propensity score matching (PSM) cohort study, all patients with cT4N0-2M0 undergoing treatment at a single institution in China (2014-2018) were reviewed. The 3-year disease-free survival (DFS) was set as the primary outcome, and the 3-year PM rate was also analyzed. RESULTS: 220 patients were included in this study for analysis. After 1:3 PSM: HIPEC (n = 45) and No HIPEC (n = 135). Through analysis, it was found that prophylactic HIPEC correlated to better DFS [hazard ratio (HR) 0.43, 95 % confidence interval (CI) 0.19-0.95; p = 0.037], and N2 stage correlated to worse DFS [HR 1.97, 95 % CI 1.09-3.56; p = 0.025]. For laparoscopic surgery subgroup analyses, 3-year PM rate of patients with laparoscopic surgery was 13.8 % in No HIPEC group, and 2.6 % in HIPEC group (p = 0.070). Besides, no post-operative death occurred, the anastomotic leakage rate was 2.2 % in HIPEC group and 0.7 % in the control group (p = 0.439). CONCLUSIONS: Prophylactic HIPEC may improve the prognosis in patients with cT4N0-1M0 CRC, but not in cT4N2M0 CRC, and it does not significantly increase surgery-related complications. Laparoscopic surgery followed by HIPEC for T4 stage CRC may not increase risk of PM.

KIF15 knockdown inhibits colorectal cancer proliferation and migration through affecting the ubiquitination modification of NRAS.

As one of the most common malignancies, colorectal cancer (CRC) requires a thorough understanding of the mechanisms that promote its development and the discovery of new therapeutic targets. In this study, immunohistochemical staining confirmed significantly higher expression levels of KIF15 in CRC. qPCR and western blot results demonstrated the effective suppression of KIF15 mRNA and protein expression by shKIF15. Downregulation of KIF15 inhibited the proliferation and migration of CRC cells while promoting apoptosis. In addition, evidence from the xenograft experiments in nude mice demonstrated that KIF15 knockdown also suppressed tumor growth. Through bioinformatics analysis, the downstream molecular NRAS and Rac signaling pathway associated with KIF15 were identified. KIF15 knockdown was found to inhibit NRAS expression and disrupt Rac signaling pathway. Moreover, WB and Co-IP assays revealed that KIF15 reduced the ubiquitination modification of NRAS protein by interacting with the E3 ligase MDM2, thereby enhancing NRAS protein stability. Functionally, NRAS knockdown was shown to inhibit cell proliferation and migration. In conclusion, KIF15 promoted CRC progression by regulating NRAS expression and Rac signaling pathway.

Function and mechanism of MCM8 in the development and progression of colorectal cancer.

Colorectal cancer (CRC) has become a global health problem which has almost highest morbidity and mortality in all types of cancers. This study aimed to uncover the biological functions and underlying mechanism of MCM8 in the development and progression of CRC. The expression level of MCM8 was found to be upregulated in CRC tissues and significantly associated with tumor grade and patients' survival. Knocking down MCM8 expression in CRC cells could restrain cell growth and cell motility while promoting cell apoptosis in vitro, as well as inhibit tumor growth in xenograft mice model. Based on the RNA screening performing on CRC cells with or without MCM8 knockdown and the following IPA analysis, CHSY1 was identified as a potential target of MCM8 in CRC, whose expression was also found to be higher in tumor tissues than in normal tissues. Moreover, it was demonstrated that MCM8 may regulate the expression of CHSY1 through affecting its NEDD4-mediated ubiquitination, both of which synergistically execute tumor promotion effects on CRC. In conclusion, the outcomes of our study showed the first evidence that MCM8 act as a tumor promotor in CRC, and may be a promising therapeutic target of CRC treatment.

R-Mixup: Riemannian Mixup for Biological Networks.

Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological entities. However, due to their characteristics of high dimensionality and low sample size, directly applying deep learning models on biological networks usually faces severe overfitting. In this work, we propose R-MIXUP, a Mixup-based data augmentation technique that suits the symmetric positive definite (SPD) property of adjacency matrices from biological networks with optimized training efficiency. The interpolation process in R-MIXUP leverages the log-Euclidean distance metrics from the Riemannian manifold, effectively addressing the swelling effect and arbitrarily incorrect label issues of vanilla Mixup. We demonstrate the effectiveness of R-MIXUP with five real-world biological network datasets on both regression and classification tasks. Besides, we derive a commonly ignored necessary condition for identifying the SPD matrices of biological networks and empirically study its influence on the model performance. The code implementation can be found in Appendix E.

Comparison of short-term surgical outcomes and long-term survival between emergency and elective surgery for colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: The objective of this study was to summarize relevant data from previous reports and perform a meta-analysis to compare short-term surgical outcomes and long-term oncological outcomes between emergency and elective surgery for colorectal cancer (CRC). METHODS: A systematic literature search was performed using PubMed and Embase databases, and relevant data were extracted. Postoperative morbidity, hospital mortality within 30 days, postoperative recovery, overall survival (OS), and relapse-free survival (RFS) were compared using a fixed or random-effect model. RESULTS: A total of 28 studies involving 353,686 participants were enrolled for this systematic review and meta-analysis, and 23.5% (83,054/353,686) of CRC patients underwent emergency surgery. The incidence of emergency presentations in CRC patients ranged from 2.7 to 38.8%. The lymph node yield of emergency surgery was comparable to that of elective surgery (WMD:0.70, 95%CI: - 0.74,2.14, P = 0.340; I2 = 80.6%). Emergency surgery had a higher risk of postoperative complications (OR:1.83, 95%CI:1.62-2.07, P < 0.001; I2 = 10.6%) and hospital mortality within 30 days (OR:4.62, 95%CI:4.18-5.10, P < 0.001; I2 = 42.9%) than elective surgery for CRC. In terms of long-term oncological outcomes, emergency surgery was significantly associated with poorer RFS (HR: 1.51, 95%CI:1.24-1.83, P < 0.001; I2 = 58.9%) and OS(HR:1.60, 95%CI: 1.47-1.73, P < 0.001; I2 = 63.4%) of CRC patients. In addition, the subgroup analysis for colon cancer patients revealed a pooled HR of 1.73 for OS (95%CI:1.52-1.96, P < 0.001), without the evidence of significant heterogeneity (I2 = 21.2%). CONCLUSION: Emergency surgery for CRC had an adverse impact on short-term surgical outcomes and long-term survival. A focus on early screening programs and health education was warranted to reduce emergency presentations of CRC patients.

R-Mixup: Riemannian Mixup for Biological Networks.

Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological entities. However, due to their characteristics of high dimensionality and low sample size, directly applying deep learning models on biological networks usually faces severe overfitting. In this work, we propose R-Mixup, a Mixup-based data augmentation technique that suits the symmetric positive definite (SPD) property of adjacency matrices from biological networks with optimized training efficiency. The interpolation process in R-Mixup leverages the log-Euclidean distance metrics from the Riemannian manifold, effectively addressing the swelling effect and arbitrarily incorrect label issues of vanilla Mixup. We demonstrate the effectiveness of R-Mixup with five real-world biological network datasets on both regression and classification tasks. Besides, we derive a commonly ignored necessary condition for identifying the SPD matrices of biological networks and empirically study its influence on the model performance. The code implementation can be found in Appendix E.

Analysis of antibiotic resistance genes reveals their important roles in influencing the community structure of ocean microbiome.

Antibiotic resistance gene (ARG) content is a well-established driver of microbial abundance and diversity in an environment. By reanalyzing 132 metagenomic datasets from the Tara Oceans project, we aim to unveil the associations between environmental factors, the ocean microbial community structure and ARG contents. We first investigated the structural patterns of microbial communities including both prokaryotes such as bacteria and eukaryotes such as protists. Additionally, several ARG-dominant horizontal gene transfer events between Protist and Prokaryote have been identified, indicating the potential roles of ARG in shaping the ocean microbial communities. For a deeper insight into the role of ARGs in ocean microbial communities on a global scale, we identified 1926 unique types of ARGs and discovered that the ARGs are more abundant and diverse in the mesopelagic zone than other water layers, potentially caused by limited resources. Finally, we found that ARG-enriched genera were often more abundant compared to their ARG-less neighbors in the same environment (e.g. coastal oceans). A deeper understanding of the ARG-microbiome relationships could help in the conservation of the oceanic ecosystem.

A novel immune-related lncRNA pair signature for prognostic prediction and immune response evaluation in gastric cancer: a bioinformatics and biological validation study.

BACKGROUND: Gastric cancer (GC), the most commonly diagnosed cancer worldwide with poor 5-year survival rate in advanced stages. Although immune-related and survival-related biomarkers, which typically comprise aberrantly expressed long non-coding RNAs (lncRNAs) and genes, have been identified, there are no reports of immune-related lncRNA pair (IRLP) signatures for GC. METHODS: In this study, we acquired lncRNA expression profiles from The Cancer Genome Atlas (TCGA) and used the least absolute shrinkage and selection operator (LASSO) Cox proportional hazards model (iteration = 1000) to develop a IRLP prognostic signature. The area under curve (AUC) was used to assess the prognosis predictive power. The multivariate Cox regression analysis was performed to identify whether this signature was an independent prognostic factor. The immune cell infiltration analysis was performed between the two risk groups. Last, molecular experiments were performed to explore LINC01082 is involved in the development of GC. RESULTS: We acquired lncRNA expression profiles and used the LASSO Cox model to develop an 18-IRLP signature with a strong prognostic predictive power. The 5-year AUC values of the training, validation, and overall TCGA datasets were 0.77, 0.86, and 0.80, respectively. The different prognostic outcomes between the high- and low-risk groups were determined using our 18-IRLP signature. Moreover, our 18-IRLP signature was an independent prognostic factor as per the multivariate Cox regression analysis, and showed better prognostic evaluation than the traditional TNM staging system as well as other clinical features. We also found differences in cancer-associated fibroblast and macrophage M2 infiltration and the expression of PD-L1, CTLA4, LAG3, and HLA were also observed between the two risk groups (P < 0.05). Analysis of biological functions revealed that target genes of the lncRNAs in the IRLP signature were enriched in focal adhesion and regulation of actin cytoskeleton. Finally, as one of significant candidates of IRLP signature, overexpression of LINC01082 suppressed the invasion ability of GC cells as well as PD-L1 expression profiles. CONCLUSIONS: Our novel 18-IRLP signature provides new insights regarding immunological biomarkers, imparts a better understanding of the tumor immune microenvironment, and can be used for predicting prognosis and evaluating immune response in GC.

Neoantigen vaccine and neoantigen-specific cell adoptive transfer therapy in solid tumors: Challenges and future directions.

The phenomenon of tumor hierarchy and genetic instability can be explained by the "two-hits theory" and results in the occurrence of many somatic mutations. The expression of nonsynonymous mutations results in the production of mutant proteins from tumor cells, namely tumor-specific antigens called neoantigens. Because neoantigens do not exist in healthy cells, they have the potential to stimulate antitumor immune responses by CD4+ and CD8+ T-cell activation without jeopardizing normal tissues. Immunotherapy has reshaped the cancer treatment paradigm in recent decades with the introduction of immune-checkpoint blockade therapy and transgenic T-cell receptor/chimeric antigen receptor T cells. However, these strategies performed poorly in solid tumors because of the obstacles of the immunosuppressive microenvironment caused by regulatory T cells and other suppressor cells. Therefore, other immunotherapeutic strategies are under development, such as personalized vaccines, to trigger de novo T-cell responses against neoantigens and lead to the amplification of tumor-specific T-cell subclones. Neoantigen epitope prediction algorithms have enabled the detection of neoantigens and the creation of tailored neoantigen vaccines as a result of the fast development of next-generation sequencing and cancer bioinformatics. Here we provide an overview of the current neoantigen cancer vaccines and adoptive T-cell transfer therapy with neoantigen-specific lymphocytes. We also discuss the challenges in developing neoantigen-targeted immunotherapeutic strategies for cancer.

Factors Prognostic for Brain Metastases from Colorectal Cancer: A Single-Center Experience in China.

PURPOSE: This study aimed to analyze clinicopathological, survival, prognostic factors, as well as the timing of brain metastases (BM) in colorectal cancer (CRC) using data from a Chinese center. PATIENTS AND METHODS: Data of 65 consecutive CRC patients with BM were collected from a single institution in China. The time from primary tumor surgery to the occurrence of BM was calculated. Kaplan-Meier analysis was used to evaluate cumulative survival of patients. Factors associated with prognosis of overall survival (OS) were explored using Cox's proportional hazard regression models. RESULTS: The median time interval from CRC surgery to the diagnosis of BM was 24 months. After diagnosis of BM, median OS values for patients were 11 months. Extracranial metastases occurred in 45 cases (69.2%) when BM was diagnosed, and 58.5% of these patients with lung metastases Time of BMs (P=0.018), presence of extracranial metastases (P=0.033), treatment (P=0.003), CA199 (P=0.034), CA125 (P<0.001), CA242 (P=0.018), and CA211 (P=0.012) were associated with OS of patients through univariate analysis. Multivariate analysis using a Cox regression model showed that only treatment was an independent predictor for OS (conservative treatment; HR=1.861, 95% CI=1.077-3.441; P=0.048). CONCLUSION: Surgical treatment of metastatic lesions may be an alternative choice for CRC patients with BM. Identifying the timing of brain metastases can help to detect this disease early, leading to a better survival outcome.

A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer's disease.

Alzheimer's disease (AD) is influenced by both genetic and environmental factors; thus, brain epigenomic alterations may provide insights into AD pathogenesis. Multiple array-based Epigenome-Wide Association Studies (EWASs) have identified robust brain methylation changes in AD; however, array-based assays only test about 2% of all CpG sites in the genome. Here, we develop EWASplus, a computational method that uses a supervised machine learning strategy to extend EWAS coverage to the entire genome. Application to six AD-related traits predicts hundreds of new significant brain CpGs associated with AD, some of which are further validated experimentally. EWASplus also performs well on data collected from independent cohorts and different brain regions. Genes found near top EWASplus loci are enriched for kinases and for genes with evidence for physical interactions with known AD genes. In this work, we show that EWASplus implicates additional epigenetic loci for AD that are not found using array-based AD EWASs.

Accuracy and Feasibility of Ultrasound-Guided Intra-articular Injection of the Rat Hip Joint.

Intra-articular injection is frequently used as an effective diagnostic and treatment tool for hip joint diseases. However, the underlying treatment mechanism remains unclear because of a lack of experimental animal models. A challenge facing researchers is how to accurately and consistently perform injections involving animal hip joints. The purpose of this study, then, was to establish an ultrasound (US)-guided intra-articular (IA) injection technique using rat hip joints and to evaluate its accuracy and feasibility versus a fluoroscopy (FL)-guided technique. For this study, 20 US-guided and 20 FL-guided IA injections were administered to separate groups of Sprague-Dawley rats. For each procedure, 50 µL of iohexol was injected into the hip joint using a 25G needle. The US-guided injections were performed using a linear probe, and the FL-guided IA injections were performed using C-arm X-ray fluoroscopy. All injections were verified by computed tomography imaging. The number of successful injections and needle repositions per injection, as well as operating times, were recorded, and the rats were observed for complications for 10 d after the injections. Statistical analysis was used to compare US-guided and FL-guided techniques with significance set at p < 0.05. The success rate was markedly higher for the US-guided interventions (90%) than for the FL-guided interventions (75%) (p<0.05). The intervention time was shorter in the US-guided group (95.95 ± 8.376 s) than in the FL-guided group (110.70 ± 20.236 s) (p < 0.05), and the median number of needles repositioned per injection in the US-guided group (1.20 ± 0.41) was notably less than that in the FL-guided group (1.60 ± 0.68) (p < 0.05). A puncture site hematoma was noted in two rat hips (10%) the day after injection in the FL-guided group. Overall, the study indicated that ultrasound-guided intra-articular injection of the hip is a feasible, accurate and safe method for use in rats. This makes it a promising tool for diagnosing coxofemoral pain, producing hip osteoarthritis animal models and administering intra-articular medication.

Factors Prognostic for Peritoneal Metastases from Colorectal Cancer Treated with Surgery.

PURPOSE: To analysis factors prognostic for peritoneal metastases (PM) from colorectal cancer (CRC) treated with surgery using data from two sources and investigate the origin and effective treatment of ovarian metastases (OM). PATIENTS AND METHODS: Data from CRC patients with PM who had undergone surgery were collected from the Surveillance, Epidemiology, and End Results (SEER) database (n = 639) and a single Chinese institution (n = 60). Cumulative survival was evaluated by Kaplan-Meier analysis. Factors associated with overall survival (OS) and progression-free survival (PFS) prognosis were assessed using Cox's proportional hazard regression models. RESULTS: Median OS values for patients who underwent surgery were 19 and 32 months in the SEER database and Chinese center, respectively. Age was an independent predictor of OS in both datasets. Signet-ring cell cancer and perineural invasion were independent predictors of inferior OS only in the SEER dataset, while completeness of cytoreduction (CC) and peritoneal carcinomatosis index were independent predictors for OS and PFS only in the Chinese center. Median OS was 24 months in CRC patients with PM alone and 36 months in those with both PM and OM (p = 0.181). Further, median PSF in patients with PM alone was 10 months, while that in individuals with both PM and OM was 20 months (p = 0.181). CONCLUSION: Surgical treatment of the primary and metastatic sites is effective and safe for CRC patients with PM. CC-0 is recommended for improved prognosis. Moreover, OM should be recognized as a feature of PM, and cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy is beneficial for CRC patients with OM.

A novel prognostic signature of immune-related genes for patients with colorectal cancer.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers with an estimated 1.8 million new cases worldwide and associated with high mortality rates of 881 000 CRC-related deaths in 2018. Screening programs and new therapies have only marginally improved the survival of CRC patients. Immune-related genes (IRGs) have attracted attention in recent years as therapeutic targets. The aim of this study was to identify an immune-related prognostic signature for CRC. To this end, we combined gene expression and clinical data from the CRC data sets of The Cancer Genome Atlas (TCGA) into an integrated immune landscape profile. We identified a total of 476 IRGs that were differentially expressed in CRC vs normal tissues, of which 18 were survival related according to univariate Cox analysis. Stepwise multivariate Cox proportional hazards analysis established an immune-related prognostic signature consisting of SLC10A2, FGF2, CCL28, NDRG1, ESM1, UCN, UTS2 and TRDC. The predictive ability of this signature for 3- and 5-year overall survival was determined using receiver operating characteristics (ROC), and the respective areas under the curve (AUC) were 79.2% and 76.6%. The signature showed moderate predictive accuracy in the validation and GSE38832 data sets as well. Furthermore, the 8-IRG signature correlated significantly with tumour stage, invasion, lymph node metastasis and distant metastasis by univariate Cox analysis, and was established an independent prognostic factor by multivariate Cox regression analysis for CRC. Gene set enrichment analysis (GSEA) revealed a relationship between the IRG prognostic signature and various biological pathways. Focal adhesions and ECM-receptor interactions were positively correlated with the risk scores, while cytosolic DNA sensing and metabolism-related pathways were negatively correlated. Finally, the bioinformatics results were validated by real-time RT-qPCR. In conclusion, we identified and validated a novel, immune-related prognostic signature for patients with CRC, and this signature reflects the dysregulated tumour immune microenvironment and has a potential for better CRC patient management.

A circulating extracellular vesicles-based novel screening tool for colorectal cancer revealed by shotgun and data-independent acquisition mass spectrometry.

Background: Early screening for colorectal cancer (CRC) is essential to improve its prognosis. Liquid biopsies are increasingly being considered for diagnosing cancer due to low invasiveness and high reproducibility. In addition, circulating extracellular vesicles (crEVs, extracellular vesicles isolated from plasma) expressing tumour-specific proteins are potential biomarkers for various cancers. Here, we present a data-independent acquisition (DIA)-mass spectrometry (MS)-based diagnostic method for liquid biopsies. Methods: Extracellular vesicles (EVs) were isolated from culture supernatants of human CRC cell lines, and plasma of patients with CRC at different tumour stages, by overnight ultracentrifugation coupled with sucrose density gradient centrifugation. Tumour-specific EV proteins were prioritized using Tandem Mass Tag (TMT)-based shotgun proteomics and phosphoproteomics. The results were verified in a second independent cohort and a mouse tumour-bearing model using Western blotting (WB). The candidate biomarkers were further validated in a third cohort by DIA-MS. Finally, the DIA-MS methodology was accelerated to permit high-throughput detection of EV biomarkers in another independent cohort of patients with CRC and healthy controls. Results: High levels of total and phosphorylated fibronectin 1 (FN1) in crEVs, haptoglobin (HP), S100A9 and fibrinogen α chain (FGA) were significantly associated with cancer progression. FGA was the most dominant biomarker candidate. Analysis of the human CRC cell lines and the mouse model indicated that FGA+ crEVs were likely released by CRC cells. Furthermore, fast DIA-MS and parallel reaction monitoring (PRM)-MS both confirmed that FGA+ crEVs could distinguish colon adenoma with an area of curve (AUC) in the receiver operating characteristic (ROC) curve of 0.949 and patients with CRC (AUC of ROC is 1.000) from healthy individuals. The performance outperformed conventional tumour biomarkers. The DIA-MS quantification of FGA+ crEVs among three groups agreed with that from PRM-MS. Conclusion: DIA-MS detection of FGA+ crEVs is a potential rapid and non-invasive screening tool to identify early stage CRC. Abbreviations: FGA: fibrinogen α chain; CRC: colorectal cancer; crEVs: circulating extracellular vesicles; EV: extracellular vesicles;MS: mass spectrometry; WB: Western blotting; ROC: receiver operating characteristic; PRM: Parallel Reaction Monitoring; GPC1: Glypican-1; GO: Gene ontology; TEM: transmission electron microscopy; FN1: Fibronectin 1; HP: haptoglobin; TMT: Tandem Mass Tag; LC-MS/MS: liquid chromatography coupled to tandem mass spectrometry; DIA: data-independent acquisition; DDA: data-dependent acquisition; CiRT: Common internal Retention Time standards;AGC: Automatic gain control; AUC: area under curve.

MicroRNA-30a targets BECLIN-1 to inactivate autophagy and sensitizes gastrointestinal stromal tumor cells to imatinib.

Gastrointestinal stromal tumors (GISTs), the most widespread type of sarcoma, contain driver gene mutations predominantly of receptor tyrosine kinase and platelet-derived growth factor receptor alpha. However, the inevitable development of resistance to imatinib (IM) cannot be fully attributed to secondary driver gene mutations. In this study, we investigated the role of microRNA-30a in sensitization of GIST cells to IM in vivo and in vitro. Higher levels of miR-30a were detected in GIST-T1 cells, which were more sensitive to IM than GIST-882 cells. IM treatment also reduced miR-30a levels, indicating the possible role of miR-30a in GIST IM resistance. Subsequently, miR-30a was confirmed to be an IM sensitizer via a mechanism that was attributed to its involvement in the regulation of cell autophagy. The interaction of miR-30a and autophagy in IM treated GIST cells was found to be linked by beclin-1. Beclin-1 knockdown increased IM sensitivity in GIST cell lines. Finally, miR-30a was confirmed to enhance IM sensitivity of GIST cells in mouse tumor models. Our study provides evidence for the possible role of miR-30a in the emergence of secondary IM resistance in GIST patients, indicating a promising target for overcoming this chemoresistance.

Understanding mixed environmental exposures using metabolomics via a hierarchical community network model in a cohort of California women in 1960's.

Even though the majority of population studies in environmental health focus on a single factor, environmental exposure in the real world is a mixture of many chemicals. The concept of "exposome" leads to an intellectual framework of measuring many exposures in humans, and the emerging metabolomics technology offers a means to read out both the biological activity and environmental impact in the same dataset. How to integrate exposome and metabolome in data analysis is still challenging. Here, we employ a hierarchical community network to investigate the global associations between the metabolome and mixed exposures including DDTs, PFASs and PCBs, in a women cohort with sera collected in California in the 1960s. Strikingly, this analysis revealed that the metabolite communities associated with the exposures were non-specific and shared among exposures. This suggests that a small number of metabolic phenotypes may account for the response to a large class of environmental chemicals.